Mucosal Immunity

This study included biospecimens from 100 children: 19 children were clinically diagnosed with MIS-C as defined by CDC criteria (Supplemental Table 1; supplemental material available online with this article; https://doi.org/10.1172/JCI149633DS1); 26 children had COVID-19 confirmed by RT-PCR; and 55 children served as non–COVID-19 controls (32 pre-pandemic). The average age of the children with MIS-C (8 years old) was younger than that of the children who presented with COVID-19 (14 years old), which is consistent with the national averages (2, 15). The patients with MIS-C presented with a median of 3 days of acute symptoms associated with MIS-C (range, 1–28 days), after a previous COVID-19 exposure or SARS-CoV-2 infection 26 days prior to the presentation with MIS-C (range, 13–62 days). Notably, GI symptoms were predominant in the MIS-C cohort, affecting 89% of these patients, compared with 27% of children with acute COVID-19 (Fisher’s exact test, P < 0.0001; Table 1). Figure 1 outlines the specimens collected for the analysis and the timing of specimen collection from the children with MIS-C or acute COVID-19. Figure 1Study overview. Timing of sample collection and sample analysis for children with MIS-C or acute COVID-19. Table 1Age and sex for all pediatric patients and controls, and clinical features of illness for the children with acute COVID-19 or MIS-C SARS-CoV-2 in the GI tract of children with MIS-C coincides with a loss of intestinal epithelial barrier function. MIS-C develops several weeks after a SARS-CoV-2 infection or exposure (Table 1), and the viral load in respiratory secretions is known to decrease over the course of 7–10 days after infection (11, 16, 17). As most children with MIS-C have negative nasopharyngeal viral swabs (11), MIS-C is unlikely to be related to this initial infection of the respiratory tract. To assess the presence of SARS-CoV-2 in the GI tract, we measured SARS-CoV-2 RNA from MIS-C stool samples collected several weeks after the initial SARS-CoV-2 infection or exposure. Indeed, a majority of the patients showed detectable viral loads in the stool ranging from 1.5 × 102 to 2.5 × 107 RNA copies/mL, suggesting an ongoing nidus of infection in MIS-C (Supplemental Table 1). An intact, functional intestinal mucosal barrier should prevent the passage of large antigens from the gut lumen into the bloodstream, including viral antigens derived from SARS-CoV-2 present in the GI tract (12). Zonulin belongs to a family of structurally and functionally related proteins that reversibly regulate intestinal permeability by modulating intercellular tight junctions (18–20). Increased circulating zonulin levels resulting in increased intestinal permeability have been reported in several diseases (21) including autoimmune and hyperinflammatory diseases such as celiac disease (22), inflammatory bowel disease (23), and Kawasaki disease (24). Zonulin release from epithelial cells can result in permissibility of paracellular trafficking of large inflammatory antigens from the gut lumen into the bloodstream. In this study, mass spectrometry showed that, compared with controls, children with MIS-C had significantly increased release of zonulin into the circulation (P = 0.003; Figure 2A), which can result in a breakdown of mucosal barrier function. Correspondingly, children with MIS-C also had increased LPS-binding protein (LBP) levels compared with controls (P = 0.007; Figure 2B), signaling increased microbial translocation. Levels of soluble CD14, another marker of microbial translocation, were also increased in children with MIS-C (P = 0.1; Figure 2C), indicating a loss of GI mucosal barrier integrity. None of these markers of GI barrier integrity — zonulin, LBP, or CD14 — was significantly increased in the children with acute COVID-19 infection. Identification of SARS-CoV-2 within the stool, coupled with the loss of competency of tight junctions seen in MIS-C, but not acute COVID-19, suggests that GI sources of SARS-CoV-2 viral components could breach the mucosal barrier and enter the circulation. Figure 2Plasma (A) zonulin, (B) LPS-binding protein, and (C) soluble CD14 levels were quantified by multiplexed MS–based proteomics (54, 55) for children with MIS-C (n = 13) or COVID-19 (n = 21) and for non–COVID-19 control participants (n = 23). Results were compared by ANOVA. (D) SARS-CoV-2 spike, (E) S1, and (F) nucleocapsid protein levels were quantified in plasma from children with MIS-C (n = 16), children with acute COVID-19 (n = 22), and pre-pandemic healthy controls (n = 32). Results were compared by 1-way ANOVA with multiple comparisons. * P < 0.05, **P < 0.01, ***P < 0.001, and ****P < 0.0001. Median values and 95% CI are presented. Children with MIS-C have SARS-CoV-2 antigenemia. Although viremia and antigenemia have been shown to correlate with severe acute COVID-19 in adults (17, 25), viremia has not been detected in MIS-C (11), and antigenemia has not previously been assessed in children. Using single-molecule array (Simoa) assays (25), we detected SARS-CoV-2 spike, S1, and nucleocapsid antigens in the plasma of children with MIS-C despite being weeks past their initial SARS-CoV-2 infection or exposure. The SARS-CoV-2 spike protein was significantly elevated in patients with MIS-C compared with healthy controls (P < 0.0001) and compared with children with acute COVID-19 (P < 0.001; Figure 2D). We also detected the SARS-CoV-2 S1 protein at significantly elevated levels in patients with MIS-C compared with healthy controls (P = 0.004) and with children with acute COVID-19 (P = 0.02; Figure 2E). SARS-CoV-2 nucleocapsid protein levels were increased in patients with MIS-C, although these levels did not reach significance (Figure 2F). We detected no significant increase in SARS-CoV-2 antigenemia in children with acute COVID-19 as compared with healthy controls. SARS-CoV-2 antigens showed no correlation with age (Supplemental Figure 1). Circulating SARS-CoV-2 antigen indicates that viral components have leaked from infected tissues. We attribute circulating antigen in patients with MIS-C to leakage from the GI system, as corroborated by the increased zonulin levels and microbial translocation markers we detected in the patients with MIS-C. The SARS-CoV-2 spike protein, specifically the S1 component (9, 10), has been hypothesized to have superantigen-like properties that are similar to those seen in the bacterial superantigen–mediated toxic shock syndrome. Superantigens bind to specific β-chains of T cell receptors (TCRs) at the variable domain in a complementary-determining region 3–independent (CDR3-independent) manner (26), thereby bypassing TCR specificity and resulting in skewing and overrepresentation of specific TCRs. Recent reports have identified TCR β variable (TRBV) gene skewing in MIS-C, with a profound expansion of TRBV11-2 (10, 27). Our data reveal a strong correlation between S1 antigenemia and the previously reported expression of TRBV11-2 in MIS-C (ref. 10; Pearson’s correlation, r = 0.89, P = 0.0005; Supplemental Figure 2). We found no correlation between the spike or nucleocapsid antigens and TRBV11-2 expression (Supplemental Figure 2). Consistent with hyperinflammatory responses, children with MIS-C experienced a cytokine storm with significantly elevated levels of IL-1β, IL-6, IL-10, and TNF-α (Supplemental Figure 3, A–D). Notably, the antiviral cytokine IFN-γ was also significantly increased in patients with MIS-C compared with both healthy controls and children with acute COVID-19 (Supplemental Figure 3E). This increase in IFN-γ is typical of a viral exposure, however, it can be paradoxically suppressed in adults with severe acute COVID-19 (28). We also assessed IL-12p70, IL-8, IL-5, and IL-22 levels but found that they were not altered in the children with MIS-C or acute COVID-19 (Supplemental Figure 3, F–I). MIS-C immunoprofiles reflect ongoing mucosal exposure to SARS-CoV-2. The immunoglobulin IgM, IgG, and IgA subsets targeting SARS-CoV-2 antigens in patients with MIS-C were most highly elevated against spike and S1 proteins (Figure 3, A–C, and Supplemental Figure 4), corresponding to the antigens most highly detected in the bloodstream of these children. As expected, anti–spike IgM was highest in children with acute COVID-19, reflecting early adaptive immune responses (Figure 3A). However, anti–spike IgM levels remained higher than would be expected, given that MIS-C presents weeks after the original infection with or exposure to SARS-CoV-2, but was on a downward trend over time (Figure 3D). As expected, anti–spike IgG, anti–S1 IgG, and anti–RBD IgG were highest in the children with delayed-onset MIS-C (Figure 3B and Supplemental Figure 4) and remained plateaued over time (Figure 3E). IgA is the immunoglobulin most reflective of mucosal immunity and typically wanes following viral clearance (29). Here, the levels of anti–spike IgA, anti–S1 IgA, and anti–RBD IgA were all significantly increased in the patients with MIS-C (Figure 3C and Supplemental Figure 4), and anti–spike IgA remained unexpectedly elevated for months after the initial SARS-CoV-2 infection (Figure 3F). The persistence of elevated anti–SARS-CoV-2 IgA and IgM in patients with MIS-C supports the hypothesis of ongoing viral antigenic exposure and inflammation in the GI mucosal surfaces of children with MIS-C. Figure 3Peak values of (A) anti–spike IgM, (B) anti–spike IgG, and (C) anti–spike IgA were quantified in plasma from children with MIS-C (n = 16), children with acute COVID-19 (n = 22), and pre-pandemic healthy controls (n = 32). Results were compared by 1-way ANOVA with multiple comparisons. Time course of (D) anti–spike IgM, (E) anti–spike IgG, and (F) anti–spike IgA were plotted over time following symptom onset for MIS-C. (G) The IC50 for antibody neutralization for children with MIS-C and children with acute COVID-19 were compared by Mann-Whitney t test. Mean values and the SD are presented. *P < 0.05, **P < 0.01, and ****P < 0.0001. We compared the capacity of plasma neutralization against SARS-CoV-2 between children with MIS-C and those with acute COVID-19. Interestingly, although the children with MIS-C had significantly elevated IgG antibody titers against SARS-CoV-2 relative to those with acute COVID-19, the neutralization titers were comparable between the children from both groups (Figure 3G). This suggests that in children with MIS-C, increasing quantities of IgG antibodies against the SARS-CoV-2 spike protein did not result in a gain in neutralizing capacity over time. Ineffective neutralization and poor antigen clearance, combined with ongoing viral antigen leakage from GI sources, could partially explain the high levels of antigen detected in the children with MIS-C. Temporal kinetics reveal that SARS-CoV-2 antigenemia is inadequately contained by humoral responses in MIS-C. Both SARS-CoV-2 antigen and immunoglobulins were detectable in patients with MIS-C at levels significantly higher than those detected in healthy controls. Antigenemia in adults occurs early in the COVID-19 disease course and is associated with pulmonary symptoms (25), whereas in MIS-C, antigenemia is found in the setting of prominent GI symptoms weeks to months after resolution of a SARS-CoV-2 upper respiratory tract infection or asymptomatic infection. To understand the relationship between viral antigenemia and the humoral response, we studied longitudinal samples from patients with MIS-C. First, we assessed antigens over time following MIS-C symptom onset. Previous reports show that in adults with acute COVID-19, SARS-CoV-2 antigens are rapidly cleared as the patient reaches seroconversion (25, 30). In contrast, our studies showed that spike antigens rose over the first few days of MIS-C symptoms and persisted for more than 10 days, occasionally through 6 months (Supplemental Figure 5), despite seroconversion to anti–spike IgG and anti–spike IgA antibodies. The elevated presence of spike protein in seroconverted patients was not observed in any adult COVID-19 cases (25). We also found that SARS-CoV-2 antigen levels did not significantly decrease in our cohort following the initiation of steroid and/or intravenous immunoglobulin (IVIG) replacement therapy (Figure 4A), which are the only currently recommended treatments for MIS-C (31). This suggests that current therapies are targeted toward the downstream consequences of MIS-C, namely the inflammatory responses, but fail to address the ongoing antigenemia instigating ongoing inflammation. Figure 4B provides a detailed overview of spike antigenemia and the humoral inflammatory responses in a representative hospitalized child with MIS-C, relative to SARS-CoV-2 exposure, symptom onset, and treatment course. Figure 4(A) SARS-CoV-2 spike, S1, and nucleocapsid levels in plasma from children with MIS-C were quantified before treatment with steroids and/or immunoglobulin replacement therapy, through 14 days following treatment (n = 11). Shaded regions signify the limit of detection for each specific antigen test. (B) Spike and anti–spike IgM, anti–spike IgG, and anti–spike IgA levels were measured over the course of illness of a child with MIS-C. Of note, the spike protein remained above the limit of detection for the spike antigen test at the 213-day follow-up point. Zonulin antagonism reduces spike antigenemia and cytokine storm, with subsequent improvement in clinical outcomes in MIS-C. Although steroids and IVIG do not block leakage of SARS-CoV-2 antigen across the mucosal barrier, therapies targeting GI mucosal permeability could potentially reduce or prevent antigenemia. Larazotide, a zonulin antagonist, is an investigational therapy that has been well characterized in preclinical trials (32, 33), with an excellent safety profile (34), and is currently in phase III trials for the treatment of refractory celiac disease (35). Given this theoretical benefit, we obtained US FDA approval for compassionate use of larazotide, 10 μg/kg every 6 hours, to treat a critically ill 17-month-old boy with MIS-C after he failed to improve with antiinflammatory therapies. The toddler, who had a complex past medical history including partial duplication of chromosome 14, biliary atresia status post Kasai procedure, and gastrotomy tube placement, with frequent episodes of ascending cholangitis, required hospitalization for severe COVID-19, complicated by respiratory failure and cardiac resuscitation. One month after he was diagnosed with COVID-19, he developed abdominal compartment syndrome with a C-reactive protein (CRP) level of 286 mg/L, a ferritin level of 51,223 μg/L, and a N-terminal pro-b–type natriuretic peptide (NT-proBNP) level of 16,462 pg/mL without evidence of cardiac injury on echocardiogram. He was treated with IVIG, steroids, and anakinra with transient improvement of inflammatory markers but rapid recrudescence of symptoms. We detected 1020 copies of SARS-CoV-2 RNA in the patient’s stool, as quantified by RT-PCR, and a plasma spike antigen level of 566 pg/mL more than 2 weeks after initiation of IVIG and steroid treatment for MIS-C. After the initiation of larazotide, his CRP level, which had quickly rebounded to 173 mg/L following withdrawal of anakinra, dropped by 85% from peak values, and spike antigen levels dropped by 90% to 59 pg/mL (Figure 5A). The SARS-CoV-2 nucleocapsid protein levels also dropped by 98% from 77 pg/mL to 1.45 pg/mL (limit of detection). His fever curve, which also rebounded after discontinuation of anakinra, improved, as did his ferritin and D-dimer levels (Figure 5A). The patient also experienced an improvement in cytokine and inflammatory mediator levels, including IL-1β, IFN-γ, IL-2R, and IL-17, representing an improvement in inflammasome activation, virus-induced IFN release, and immune cell activation (Figure 5B). These cytokines and inflammatory mediators initially spiked during the development of MIS-C, then improved following IVIG but plateaued or rebounded despite steroid treatment. We observed an improvement in these inflammatory mediators following the precipitous drop in SARS-CoV-2 antigens, which occurred as a result of or coincident with the initiation of larazotide therapy. Importantly, the patient achieved his longest stretches without fever since his hospital admission, his GI symptoms improved and he was able to resume full feedings, and his ventilatory status improved. Figure 5Timeline for the child treated with larazotide. The hospital course is delineated by hospitalization for acute COVID-19 (day 0) followed by development of MIS-C (day 39), with the treatment courses identified along the time course. (A) CRP and SARS-CoV-2 spike antigen levels, the median daily temperature (temp) curve, and D-dimer and ferritin levels throughout the hospital course are shown. Light blue shading represents a normal body temperature. The light gray shading highlights the days of larazotide treatment. (B) Inflammatory cytokine IL-17F, IL-2R, IFN-γ, and IL-1β levels following the development of MIS-C, in relation to the treatment courses.

Innate lymphoid cells (ILCs) and in particular ILC3s have been described to be vital for mucosal barrier functions and homeostasis within the gastrointestinal (GI) tract.Importantly, IL-22-secreting ILC3 have been implicated in the control of inflammatory bowel disease (IBD) and were shown to reduc...

Nutr Clin Pract. Author manuscript; available in PMC 2016 Dec 1. Published in final edited form as: Published online 2015 Oct 8. doi: 10.1177/0884533615609899 PMCID: PMC4838018 NIHMSID: NIHMS777222 PMID: 26449893 The Gut Microbiome: What we do and don’t know Gail A. Cresci, PhD, RD, LD, CNSC, Associate Staff and Emmy Bawden, RD The publisher's final edited version of this article is available at Nutr Clin Pract See other articles in PMC that cite the published article. Introduction Interest in and knowledge of the gut microbiome has increased exponentially in the past decade. An internet search using key words such as “gut microbiome” or “gut microbiota” generates between 1 and 2.2 million results. Once overlooked, this component of the gastrointestinal (GI) tract is now gaining appreciation for its importance in optimal health. The food industry has taken this to full heights and a plethora of food and supplement products touting “probiotic” or “fermented foods” populate store shelves; and advertisements for them can be found in magazines, the internet and television commercials. Never before has the discussion of one’s bowel habits and GI symptoms been more mainstream. Interestingly, this rapid growth has left both consumers and many clinicians confused as the data, while growing, still leave many unanswered questions. Dating back to the early 1900’s Eli Metchnikoff, a Russian scientist of the Pasteur Institute in Paris, associated longevity of rural Bulgarians to their consumption of fermented milk products. He postulated that the lactic acid bacteria in the fermented milk products ingested by these peasants living in harsh climate and poverty provided an anti-aging effect which contributed to their greatly outliving wealthier Europeans. He named the organism “Lactobacillus bulgaricus.” As Metchnikoff researched, he hypothesized that seeding the gut with healthy bacteria by drinking fermented milk products could fight off harmful bacteria and prolong life. He was the first scientist to suggest that it was possible to modify the gut microbiome by replacing bad bacteria with good bacteria, and he earned a Nobel Prize in 1908 for his work in immunity. The discovery of penicillin in 1928 by Sir Alexander Fleming, a Scottish biologist, turned the attention of researchers away from using bacteria to assist with healing to that of using soil fungi derivatives to kill bacteria. During the golden age of antibiotic discovery from 1940–1960, most antibiotics were originally isolated by screening soil-derived actinomycetes (1). However as returns diminished on this discovery platform, new discoveries were based upon synthetic compounds. However this target-focused screening process of large libraries also failed, partly due to the inability of these synthetic compounds to penetrate the bacterial envelope (1). Unfortunately the deceleration of antibiotic discovery is accompanied with the spread of resistant bacteria, and a major public health threat of untreatable infections. With advances in micro- and molecular biology techniques, the culture is poised to revisit past successes with bacterial therapy for gut health and immunity in order to develop future treatments. One of several international efforts, the Human Microbiome Project (HMP) utilizes high through multi ‘omics analyses to identify and study the microbiome in human health (2,3). Funded by the NIH common fund in 2008, the HMP has resulted in the isolation and sequencing of over 1,300 reference strains thus far from the human body (2,3). The HMP Consortium has reported the structure and function of the human microbiome in 300 healthy adults (18–40 yrs) at 18 body sites from a single time point. This has led to an unprecedented amount of data about the complexity of the human microbiome allowing for a baseline for further research into the impacts of the microbiome on health and disease. As a precursor to the Human Microbiome Project, the Human Gut Microbiome Project has widened our appreciation for the bacterial ecosystem that resides within the human intestinal tract. This system is comprised of microorganisms such as bacteria, archaea, fungus and viruses that are distributed throughout the entire gastrointestinal tract (4). Ongoing investigations are revealing the importance of the gut microorganisms in exerting beneficial effects on human health. The typical healthy person is inhabited with trillions of microbes (Figure 1). But to confuse matters, two healthy people may have very different microbiomes. Analysis of HMP samples with lifestyle and history questionnaires has revealed associations between life-history characteristics and microbiome composition (5). Ding and Schloss analyzed a 16S rRNA gene sequence data set from the HMP Consortium. As a significant difficulty in analyzing microbiome data has been the considerable intra- and interpersonal variation in the composition of the human microbiome, this study took the approach of clustering samples into bins based on their taxonomic similarity. Using bacterial community structures collected from18 body sites and up to three time points, they applied community typing analysis to better understand the factors that affect the structure of the microbiome and contribute to human health. Using Dirichlet multinomial mixture models to partition the data into community types for each body site, their analysis of simulated data and the HMP data suggest that the community types represent clusters of relative abundance profiles. Three important observations were made with this approach. Firstly, there were strong associations between whether someone was breastfed, their gender and education level with their community types at several body sites. Secondly, the community types of the oral cavity and gut microbiome were predictive of each other even though the specific taxonomic compositions were different. Lastly, stability of community types was least stable in the oral cavity and most stable in the vagina and gut communities over the course of the sampling period. Therefore the authors concluded that despite substantial intra- and interpersonal variation in the human microbiome, by partitioning this variation intocommunity types, the types became predictive of each other and are likely the result of life-history characteristics (5). The gut microbiome is influenced by multiple factors including mode of infant delivery and feeding, aging process, diet composition, geography, medications, and stress (Figure 2). The following sections provide a brief overview of current knowledge regarding variances in the gut microbiota related to these factors. Our first colonization In utero It was previously believed that the GI tract was sterile in utero, and that during the birthing process was when first colonization and initiation of the gut microbiome occurred (6). However, recent studies have challenged this belief by demonstrating the presence of microorganisms in the placenta, amniotic fluid and umbilical cord (7–9). This work is still preliminary but deserves further study as it highlights the importance of maternal gut microbiota health. It is hypothesized that by swallowing amniotic fluid and its bacteria in utero, the fetus begins to colonize the developing GI tract (10). The meconium, the first infant stool sample, has also been shown to contain microorganisms (11). Notably, the meconium from preterm infants shows a different microbiota composition from that seen in a sample acquired after the first week of life, demonstrating how normal gut colonization takes place throughout the course of fetal development (10). Absence of this progressive colonization could place preterm infants at risk for various gastrointestinal infections, including necrotizing enterocolitis (NEC) (10). As a means to mimic the natural inoculation of the gut, multiple studies have evaluated probiotic supplementation as a means to influence the incidence and severity of NEC. A recent Cochrane review, which included 24 randomized controlled trials (n=5529), assessed the role of probiotic supplementation in preterm neonates. The review confirmed previous findings that probiotic supplementation significantly reduces the risk of stage II or greater necrotizing enterocolitis and all cause mortality in this patient population (12). As probiotics are known to have potentially beneficial effects on gut function and maturity, Athalye-Jape et al conducted a meta-analysis that included 25 randomized controlled trials (n=5895) to determine if probiotic supplementation influenced the time to establish first full enteral feeds in preterm neonates (13). Overall, the subjects supplemented with probiotics took less time to achieve full feeds (mean difference: −1.54 d; 95% CI: −2.75, −0.32d; p=0.01; I2 = 93%). The type and/or number of probiotic strains (e.g., Bifidobacterium or non-Bifidobacterium) did not influence this improvement. Additionally, probiotic supplementation reduced hospital length of stay, feeding intolerance, and duration of indirect hyperbilirubinemia as well as increased weight gain and growth velocity. None of the trials reported adverse effects of probiotics on outcomes. Delivery Mode The birthing process exposes newborns to a wide range of microorganisms that also contribute to the colonization of the gut microbiome. The mode of delivery affects the composition of the infant’s gut microbiota, and interestingly, the gut microbiota of the newborn will closely resemble the microbiota with which they encountered during birth. During a vaginal birth, the infant is inoculated with vaginal microbiota, which differs from skin microbiota encountered during a caesarian section (14). At the phylum level, studies have shown that infants delivered vaginally have a larger population of Bacteroidetes than Firmicutes when compared to infants delivered via cesarean section (15). Despite exposure in utero, the majority of microbes that will colonize the infant gut are acquired postpartum. The initial colonization pattern is thought to be chaotic, and increasing evidence suggests that environmental exposures early in life, including diet, are responsible for these variations (16). Gut colonization in an infant occurs in a succession of stages. Early on, the gut becomes colonized by primarily aerobic organisms, such as enterobacteria, staphylococci, and streptococci, many of which have the potential to be pathogenic. These early colonizers begin to change the gut environment, paving the way for colonization by an increasingly anaerobic community of microbes (17). The structure of the gut community continues to change over the first year of life and thereafter in response to external factors such as diet and antibiotic use (18, 19). Weaning, breastfeeding status, and the successive introduction of different types of food all correspondingly affect the infant gut microbiome and immune system (20). Infant Feeding Method Breast milk is the optimal food for infants as it meets all their nutritional and physiologic requirements. Human milk contains protein, fat and carbohydrate, as well as immunoglobulins and endocannabinoids (21). Breast milk is not sterile as it contains as many as 600 different species of bacteria including beneficial Bifidobacterium breve, B. adolescentis, B. longum, B. bifidum, and B. dentium (22). In addition to lactose, the carbohydrate component of human milk also contains oligosaccharides which comprise the third largest solid component (23). Human milk oligosaccharides are indigestible polymers formed by a small number of different monosacchrides that serve as prebiotics by selectively stimulating growth of members of the genus Bifidobacterium(23). Some of the beneficial effects of breast feeding over formula feeding are attributed to the effects of oligosaccharides on the beneficial bacteria as an increased proportion of Bifidobacteria is noted in breast-fed infants compared to those fed formula (24). Bifidobacteria have been linked with strengthening gut mucosal protection through activities against pathogens (25). Bifidobacteria have been shown to increase the production of immunoglobulin A which is correlated with modulation of the intestinal immune system (26). Schwartz et al studied breast-fed and formula-fed infants and their mothers. Stool samples from each infant were collected, and microbial DNA was extracted and sequenced; and mRNA was isolated from stool containing host gut exfoliated epithelial cells and processed for microarray analysis (20). They found that the microbiome of breast-fed infants to be significantly enriched in genes associated with virulence functionality, and demonstrated a multivariate correlation between the gut flora genes associated with bacterial pathogenicity and the expression of host genes associated with immune and defense mechanisms. Interestingly, the operational taxonomic unit (OTU) composition and genetic potential of the microbiota differed between breast-fed and formula-fed infants. The researchers suggested their findings indicate human milk promotes the mutualistic crosstalk between the mucosal immune system and the microbiome in the maintenance of intestinal homeostasis. More research is needed to better determine the mechanisms by which Bifidobacteria produce these effects. Aerotolerance of the intestinal microbiota also seems to differ between breast-fed and formula-fed infants. Aerobic organisms are more common in the feces of breast-fed infants, whereas anaerobic and facultatively anaerobic organisms, which preferentially use anaerobic glycolysis, are more frequently identified in feces of formula-fed infants (27). Bacteroides and Clostridia colonization differs between the two types of feeding, with breast-fed infants characterized with lower concentrations of both (28–30). With a better understanding of the composition of human breast milk, developments of complex infant formulas have attempted to mimic its nutritional value making them an acceptable alternative for mothers unable to breast-feed. Infant formulas are not a perfect substitute for human milk since bioactive compounds contained in breast milk known to affect nutrient absorption and digestion, immune protection, and defense against potentially pathogenic microbes are lacking (21). Unfortunately it is difficult to mimic the actions of these bioactive compounds. While infants fed a formula enriched with oligosaccharides have been shown to harbor more Bididobacteria in the feces, more evidence is needed for affirmation that infant formulas designed to mimic breast milk are beneficial (31). Changes in the Gut Microbiome with Age Revealed by metagenomic analysis, gut microbiota composition transforms throughout early stages of human development and is influenced by the diet (32). As an infant’s diet comprises breast milk and formula, this is reflective in that the microbiome has minimal diversity and is enriched in genes to facilitate lactate utilization (33). A shift in the functional capacity to preferentially utilize plant-derived glycans occurs prior to the introduction of solid foods. Around 3-years of age, the bacterial composition resembles that of an adult and remains stable until old age when variability in community composition increases (34). In terms of ecological succession, the Bifidobacterium-dominated microbiota of the infant changes over time into the Bacteroidetes- and Firmicutes-dominated microbiota of the adult (35). This distribution remains fairly stable throughout adulthood in the absence of perturbations, such as long-term dietary changes or repeated antibiotic usage. Declines in dentition, salivary function, digestion and intestinal transit time may affect the gut microbiota upon ageing (36). There are notable differences in the microbiota in elderly people compared to young adults, with relative proportions of Bacteroidetes predominating in the elderly compared to higher proportions of Firmicutes in young adults (37). The elderly are also noted to have significant decreases in Bifidobacteria, Bacteriodes, and Clostridium cluster IV (38). Variability varies greatly among individuals ranging from 3 to 92% for Bacteroidetes and 7 to 94% for Firmicutes (34). However the microbiota are less variable within individual subjects (34). Alterations in gut microbiome are associated with health concerns pertaining to the elderly, such as frailty. A significant reduction in microbial diversity with reduced composition of lactobacilli, Bacteroides/Prevotella and Faecalibacterium prausnitzii, and increased proportions of Ruminococcus, Atopobium and Enterobacteriaceae was observed in people with high frailty scores (39). Claesson et al investigated the links between diet, environment, health and microbiota in 178 older people (>65 years) subjects and found an association between gut microbiome diversity and functional independence (39). Decreased microbial diversity was noted in individuals living in short- or long-term residential care compared to those living in the community, and this difference was associated with increased frailty, decreased diet diversity and health parameters as well as increased inflammatory markers (serum TNF-α, IL-6, IL-8 and C-reactive protein) (38). Dietary patterns in residential location correlated with separations based on microbiota composition with the most discriminating food types being vegetables, fruit and meats. Complete linkage clusterings revealed four dietary groupings: low fat/high fiber and moderate fat/high fiber included 98% of the community and day hospital subjects; and moderate fat/low fiber and high fat/low fiber included 83% of long-stay subjects (39).Significant associations between several health/frailty measurements were found with minimum variability amongst community dwellers, but within the long-stay subjects the most significant associations were related to functional independence, Barthel index (functional assessment) and nutrition, followed by blood pressure and calf circumference. The authors speculated that the later may be attributable to the influence of diet and/or the microbiota on muscle mass and sarcopenia and hence frailty. Influences on the Gut Microbiome Geography Geographical location and ethnicity have been shown to be determinants of the diversity and overall composition of microbiota. A 2013 study performed by Prideaux (40) et al looked at Caucasian and Chinese subjects in the United States and Hong Kong and found that microbial composition differed between countries and between ethnicities within the same country. In an elegant study, Yatsunenko et al characterized bacterial species in fecal samples from 531 individuals comprised of healthy children and adults from the Amazonas of Venezuela, rural Malawi and US metropolitan areas and included mono- and dizygotic twins (41). All populations studied showed shared features of gut microbiome development during the first three years of life including age-associated changes in the genes involved in vitamin biosynthesis and metabolism. Phylogenetic composition of fecal microbiota was significantly altered between individuals living in the different countries, with pronounced separation occurring between the US and the Malawian and Amerindian gut communities; this was true for individuals aged 0–3 years, 3–17 years, and for adults. However there was also separation between the non-US populations. Bacterial diversity increased with age in all three populations with the microbiome of the US population having the least diversity. Microbiome datasets from breastfed children (n=110: (24 babies (0.6–5 months old), 60 children and adolescents (6 months to 17 years old) and 26 adults) were analyzed to determine which bacterial taxa changed monotonically with increasing age within and between the three sampled populations. In all babies 16S rRNA sequences mapped to members of the Bifidobacterium genus, and while Bifidobacteria dominated fecal communities during the first year of life, they proportionally declined during this period. Also noted were age and population-related changes in metabolism. A total of 476 enzymes were identified as being significantly different in US versus Malawian and Amerindian breastfed babies (p<.0.001). The most prominent differences involved pathways related to vitamin biosynthesis and carbohydrate metabolism. Malawian and Amerindian babies, but not adults, had higher representation of enzymes that were components of the vitamin B2 (riboflavin) biosynthetic pathway. Compared with adults, baby microbiomes were enriched in enzymes involved in the scavenging of glycans represented in breastmilk and the intestinal mucosa (mannans, sialylated glycans, galactose and fucosyloligosaccharides), with several of these genes significantly overrepresented in Amerindian and Malawian baby microbiomes compared with US. Interestingly, urease gene representation was significantly higher but decreased with age in Malawian and Amerindian baby microbiomes, as opposed to the United States, where it was low from infancy to adulthood. Urea, which comprises up to 15% of the nitrogen present in human breast milk, is broken down by urease to ammonia which can then be used for microbial biosynthesis of essential and nonessential amino acids. Urease also has a crucial role in nitrogen recycling, particularly when diets are deficient in protein making urease potentially advantageous to both the microbiome and host when dietary nitrogen supply is suboptimal (42). A typical US diet is rich in protein, whereas diets in Malawian and Amerindian populations are dominated by corn and cassava. The differences between US and Malawian/Amerindian microbiomes can be related to these differences in diet. The enzymes that were the most significantly enriched in US fecal microbiomes parallel differences observed in carnivorous versus herbivorous mammals (43). Interestingly, several enzymes involved in the degradation of amino acids were overrepresented in adult US fecal microbiomes including aspartate, proline, ornithine and lysine as were enzymes involved in the catabolism of simple sugars (glucose-6-phosphate dehydrogenase and 6-phosphofructokinase), sugar substitutes (L-iditol 2-dehydrogenase, which degrades sorbitol), and host glycans (α-mannosidase, β-mannosidase and α-fucosidase). By contrast Malawian and Amerindian microbiomes had an over-representation of α-amylase which participates in the degradation of starch reflecting their corn-rich diet. Perhaps reflecting a fat-rich diet, the US microbiomes had an over-representation of enzymes involved with vitamin biosynthesis (cobalamin, biotin and lipoic acid), in the metabolism of xenobiotics (phenylacetate CoA ligase), which participates in the metabolism of aromatic compounds, and mercury reductase, and in bile salt metabolism (choloylglycine hydrolase). To obtain insights into commonalities and differences between gut microbiomes across different populations, Arumugam et al sequenced 22 European metagenomes from Danish, French, Italian and Spanish individuals that were selected for diversity and combined them with previous sequencing results from Japanese and Americans to total 39 individuals (44). They found that despite the vast number of species residing in the gut and their inter-individual variability, the microbiota composition can be classified into at least 3 distinct groups, or enterotypes. The enterotypes contain functional markers that correlate with individual features such as age and body mass index (BMI). For example, starch degradation enzymes such as glycosidases and glucan phosphorylases increase with age, which could be a reaction to decreased efficiency of host breakdown of dietary carbohydrates with age (45). Three marker modules, two of which were ATPase complexes, correlated strongly with the hosts’ BMI supporting the link found between the gut microbiota’s capacity for energy harvest and obesity in the host (46). The authors concluded that these functional markers might be utilizable for diagnostic and perhaps even prognostic tools for numerous human disorders, for instance colorectal cancer and obesity-linked co-morbidities such as metabolic syndrome, diabetes and cardiovascular pathologies. Food Supply Diet has emerged as one of the most relevant factors in influencing the gut microbiome. Significant and meaningful changes in the gut microbiota have been associated with dietary alterations, primarily consumption of dietary fiber from fruits, vegetables and other plants. A diet that is varied and complex is associated with a more diversified microbiome. Globally the microbiome composition is noted to be different amongst different populations and cultures. De Filippo et al compared the gut microbiota of children aged 1–6 years living in a village of rural Africa in an environment that still resembles that of Neolithic subsistence farmers with the gut microbiota of western European children (Florence, Italy) of the same age, with dietary habits and living conditions typical of the developed world (47). Traditionally the African children are breast-fed until the age of 2 after which their diet is predominantly vegetarian; low in fat and animal protein and rich in starch, plant polysaccharides and fiber. All food resources are completely produced locally, cultivated and harvested nearby the village. The dietary content of carbohydrate, fiber and non-animal protein is very high. Animal protein intake is low and consists of mainly chicken and termites during the rainy season. The European children were breast-fed for up to 1 y of age after which they ate a typical Western diet high in animal protein, sugar, starch, and fat and low in fiber. Average caloric intake differed between the two populations (African children: 1–2 y old, 672 kcal/d; 2–6 y old, 996 kcal/d; European children: 1–2 y old, 1,068 kcal/d; 2–6 y old, 1,512 kcal/d). Multiplex pyrosequencing of the 16S rRNA gene revealed that 94.2% of the sequences in all of the African and European samples were found to belong to the four most populated bacterial phyla, namely Actinobacteria, Bacteroidetes, Firmicutes,and Proteobacteria, in agreement with previous studies describing such phyla as those contributing to the majority of human gut microbiota (48). Relevant differences were found in the proportions of four phyla: Actinobacteria and Bacteroidetes were more represented in African than in European children’s microbiota (10.1% versus 6.7% and 57.7% versus 22.4%, respectively), whereas Firmicutes and Proteobacteria were more abundant in European than in African children (63.7% versus 27.3% and 6.7% versus 0.8%, respectively). Firmicutes were twice as abundant in the European children as evidenced by the different ratio between Firmicutes and Bacteroidetes (F/B ratio ± SD, 2.8 ± 0.06 in European and 0.47 ± 0.05 in African). While short-chain fatty acid (SCFA)-producing bacteria were found in both populations, bacteria (Xylanibacter, Prevotella, Butyrivibrio, and Treponema) which use xylane, xylose, and carboxymethylcellulose to produce high levels of SCFAs and have a protective role against gut inflammation (49) were found exclusively in the African children. Notably, the African children had higher levels of total SCFA than the European children, with 4 times higher levels of butyrate and propionate. The authors concluded a correlation exists between polysaccharide-degrading microbiota and the calories that the host can extract from his/her diet, potentially influencing the survival and fitness of the host, suggesting that the microbiome of the African children co-evolved with their diet to assist with energy harvest by producing high levels of SCFA. Microbial enrichment has been associated with diets high in fruits, vegetables and fiber compared to a Western diet rich in fat, sugars and animal protein and depleted of fiber. Zimmer et al analyzed the fecal flora of a large group of healthy volunteers on a strict vegetarian or vegan diet with classical microbiological culture and compared them with age and gender matched subjects consuming an omnivorous diet (50). The faecal microbiota of vegetarian and vegan subjects showed significantly lower microbial counts of Bifidobacterium, Bacteroides, E. coli and Enterobacteriaceae species and lower stool pH compared with omnivores. Compared to an omnivore diet, a vegetarian/vegan diet is associated with a higher carbohydrate and fiber content in which the undigestible polysaccharides can be fermented into SCFA by the gut microbiota. Production of SCFA is associated with decreasing luminal pH. The fact that E. coli and Enterobacteriacea do not thrive in lower pH ranges (5.5–6.5) and that they prefer proteins as their energy source, may explain the lower counts in the subjects consuming a vegan/vegetarian diet. Depleted microbial biodiversity of the gut microbiota in people consuming a Western diet is associated with increasing incidence of obesity, coronary vascular disease, metabolic syndrome and certain malignancies. Detailed discussion of each of these associations is beyond the scope of this paper. At a minimum, the diversity of the gut microbiome may be a future biomarker of long-term consumption of a “healthy” versus “unhealthy” diet which may be linked to potential for disease development. Stress Stress is defined as an organism’s total response to environmental demands or pressures. There are several different types of stressors, such as acute or chronic, acute on chronic, or repetitive acute. Stress can be predictable and controllable as well as unpredictable and uncontrollable, mild or severe, and occur in or out of context (51). Both the perception of stress and the persistence of its consequences vary between people. Stress contributes to susceptibility to disease and disabilities, therefore represents a severe economic burden. Psychological and physical stressors activate the hypothalamic-pituitary-adrenal (HPA) axis. This results in a series or hormonal responses including release of corticotrophin-releasing hormone which induces the release of adrenocorticotrophic hormone systemically with then stimulates glucocorticoid synthesis (cortisol) in the adrenal cortex (52). Additionally, catecholamines (noradrenaline and adrenaline) are also released following psychological and physical stressors. The GI tract, and more recently known, the gut microbiota, is sensitive to stress and stress mediators. Enteric bacteria respond to the release of stress-related neurochemical mediators by the host which can influence the response to a bacterial infection (53). Recent theory suggests that bacteria act as delivery vehicles for neuroactive compounds, and therefore can affect host physiology by providing neurochemicals (54). Physiological Stress-Exercise High intensity exercise is a physiological stressor that can lead to gastrointestinal distress. There are some reports that between 30–90% of distance runners have experienced intestinal problems related to exercise (55). The degree of intestinal distress can range from mild to severe, and symptoms include nausea, vomiting, abdominal angina, and bloody diarrhea. High intensity training has been associated with reduced GI blood flow, tissue hyperthermia and hypoxia leading to possible alterations of microbiota and gut barrier. Athletes often have different dietary pattern from non-athletes depending upon the type of activity they in which they participate. In a study of professional rugby players during a regulated environment of preseason training, Clarke et al demonstrated the impact of exercise and associated dietary changes on the gut microbiota (56). Enhanced gut microbial diversity was significantly higher and positively correlated with increased exercise and dietary protein intake in athletes as compared with size matched (high Body Mass Index – BMI ~30 kg/m2) and age/gender matched (lower BMI <25) non-athletic control groups, with fewer differences seen between the two control groups. Interestingly, when compared to controls, the athletes also exhibited lower inflammatory markers and improved metabolic markers. Athletes consumed more calories, with a higher percentage of protein, and grazed eating throughout the day compared to non-athletes. Microbiota diversity measures were positively correlated with protein intake and plasma creatine kinase levels, a marker of extreme exercise, suggesting that both diet and exercise were influencing changes in microbial diversity. The athlete’s increased microbial diversity was reflected by the presence of representatives of 22 phyla of bacteria in contrast to 11 and 9 phyla in the low and high BMI controls, respectively. There are several potential mechanisms by which physical activity and fitness might modify the microbiota. Abrupt exercise produces multiple metabolites and inflammatory mediators whereas habitual exercise and fitness leads to suppression of basal inflammatory cytokines suggesting a regulatory loop between exercise biology and host immunity (57). Regular exercise has an anti-inflammatory effect which improves the immunological profile in type 2 diabetes mellitus, coronary artery disease, peripheral arterial disease and obesity (58–61). In animal models, repeated exercise results in reduced pro-inflammatory cytokine expression and increased anti-inflammatory IL-10 expression (62, 63). Regular exercise also decreases colonic oxidative insult in a rat model of colitis (64). Contrary to the benefits of regular exercise, prolonged excessive exercise can negatively affect intestinal function. As high-intensity exercise can lead to prolonged intestinal hypo-perfusion, intestinal ischemia may result. Increased intestinal permeability can result making the gut susceptible to endotoxin translocation (65–67). Probiotic supplements, in conjunction with other dietary strategies, have been studied in athletes as a means to improve gut health, as characterized by decreased symptoms of nausea, cramping, bloating and diarrhea,as well as improved immunity. Primarily supplements containing Lactobacillus and/or Bifidobacterium species have been utilized. Products have been provided from 1 to 6 months, before and/or after exercise or a competition, and at varying doses (109–1012 CFU/day). Some studies report clinical outcomes of improved upper respiratory tract illness (64–69), gastrointestinal illness (70–72)), as well as immunological measures and outcomes (67, 68, 73–76)). Physiological Stress-Critical Illness As seen in high intensity exercise, intestinal hypoperfusion resulting from redistribution of splanchnic circulation severe enough to cause gut ischemia and mucosal injury, often occurs in the critically ill. In the critically ill, the gut has an important role in promoting infectious complications and multiple organ dysfunction syndrome (MODS). This is due to deteriorated intestinal epithelium, altered gut immune system, and dysfunctional metabolic activities of commensal bacteria (77). Shimizu et al, evaluated the gut microbiota and gut environment (fecal pH and presence of organic acids) in patients with systemic inflammatory response syndrome (SIRS) (78). In comparison to healthy controls, patients with severe SIRS had significantly lower total anaerobic bacterial counts (especially 2–4 log fewer commensal Bifidobacterium and Lactobacillus) and 2 log higher potentially pathogenic Staphylococcus and Pseudomonas group counts. Concentrations of total organic acids, in particular the short-chain fatty acids (SCFA) acetate, propionate and butyrate, were significantly decreased in the patients, whereas pH was markedly increased. This group of researchers further investigated the impact of fecal pH in critical illness in 138 trauma patients (79). Patients with acidic or alkaline feces were noted to have decreased Bacteroide and Bifidobacterium species. The incidence of bacteremia in patients with an acidic or alkaline fecal pH was significantly higher than those with a fecal pH in the normal range (P < 0.05 versus normal range). The incidence of both bacteremia and mortality were associated with an increased pH of 6.6. When the pH level was increased or decreased by one, the incidence of bacteremia more than tripled and mortality more than doubled. Total SCFA (propionate, butyrate) concentrations decreased with pH >6.6; lactic, succinic, and formic acids were increased in acidic feces which is notable as these are produced by Enterobacteriaceae (80). Whether these changes are a cause or consequence of SIRS is yet to be determined. While this study lends potential that fecal pH could be a risk factor marker, it does have limitations because these data were made with the use of culture-based interrogation of the microbiota and because the pH was not specified by gastrointestinal region. Alterations in the gut microbiome have been shown to occur within 6 hours of a metabolic insult and the microbiome fails to return to microbial patterns seen in healthy controls (81). Numerous studies attempting to modify the gut microbiome and improve clinical outcomes in the critically ill by providing probiotics, prebiotics or synbiotics have been performed (82–89). Details of these studies are beyond the scope of this review. Methods of dosing, supplement duration and supplements utilized vary amongst studies making general recommendations difficult. Several meta-analyses and systematic reviews have been performed evaluating probiotics in the critically ill (89–91)). The choice of the studies included in the analysis will determine the overall outcome of the study. Generally, it seems probiotic supplementation in the critically ill favorably improves outcomes. However, the issue of heterogeneity and lack of good quality studies is a highlight of systematic reviews of probiotic use in critically ill patients. Knowing that unrecoverable gut dysbiosis occurs early after metabolic insult and knowing the potential mechanisms of action of certain probiotic strains, further rigorous study on probiotic provision in the critically ill deserves attention. Future studies should focus on 1) clarification of viable probiotic strain(s) provided, and their dosage, route and timing of delivery; 2) clear definitions for the outcomes attempting to modify (ventilator associated pneumonia, diarrhea); and 3) focus effect of probiotic supplementation on meaningful clinical endpoints (mortality, duration of mechanical ventilation, other infections, length of stay). Psychological Stress The discovery of hormonal regulation of digestion initiated the concept of the gut-brain axis (92). The interaction of psychological factors and altered gut physiology via the gut-brain axis, where brain and gut symptoms are reciprocally influencing each other’s expression, is a conceptual framework of functional GI disorders (irritable bowel syndrome, functional dyspepsia). Early life stressors (e.g., psychological, sexual and/or physical abuse) have been suggested as important contributors to the pathogenesis of functional GI disorders (93–96)). This is a crucial developmental period when the gut microbiota are diversifying, thus making it particularly vulnerable to these stressors. Animal models of maternal separation, a model commonly used for early life stress, induces prolonged HPA-axis hyperactivity (97–103), anxiety-like behavior (100,,104–106), visceral hypersensitivity (107, 108–110), and altered cholinergic activity in the gut (111, 112), along with increased intestinal permeability (107, 113–116). This model results in a dysfunctional gut-brain axis and produces phenotypes found in irritable bowel syndrome patients (106, 116– 118). This animal model also yields gut dysbiosis in addition to other physiological and behavioral features of irritable bowel syndrome (118–120)). Various means to restore gut dysbiosis with probiotics have been investigated and appear to improve the negative stress-induced effects (107, 111, 120– 122).). Morphologic changes also result from maternal separation with increased goblet cells in the crypts of proximal colon with a subsequent increase in mucus secretion and a thinner mucosal layer (112). Thus changes in the gut microbiota in maternally separated animals could be resultant from changes to gut physiology (111– 114)) and morphology (112). Although the exact mechanisms are unknown, data thus suggest that stress, whether acute or chronic, creates a dysbiotic gut microbiome which then may induce anxiety and depression (52). It seems that metabolites produced by the gut microbiota might modulate brain biochemistry and behavior (54, 123–125). Through regulation of the vagus nerve, behavior can be altered by the gut microbiota which then affects neurotransmitter metabolism (126, 127)) or other undefined pathways (128)). Thus futuristic therapy for patients with irritable bowel syndrome with co-morbid depression or anxiety may be targeted probiotic and/or synbiotic either alone or as an adjuvant to traditional therapy. Pharmaceuticals There is substantial variation in the pharmacokinetics of most commonly used drugs, and large differences in the responses of ill persons to therapeutics. The gut microbiota assists in the conversion of inactive therapeutics (e.g., prodrugs) and dietary bioactives into their active forms (129–131). For example, a medication prescribed for ulcerative colitis, sulfasalazine remains inactive until it reaches the distal gut. This prodrug consists of an ant-iinflammatory 5-aminosalicylic acid (5-ASA) molecule connected to a sulfapyridine molecule through an N-N double bond. Gut microbiota encoded azoreductases cleave the N-N double bond to release active 5-ASA (131). Likewise, foods such as fruits, vegetables, cereals and coffee contain conjugated hydroxycinnamates, antioxidant and anti-inflammatory compounds which are activated following microbial biotransformation (132). Therefore, a question arises whether variation in medication response amongst people is due to alterations in their gut microbiome? The host possesses many protective mechanisms to protect against ingested pathogens including an acidic gastric environment, optimal bile flow, peristalsis and the gut microbiota. Current data suggest that the gut microbiota protects the host from pathogens by competing for binding sites, competing for requirements, and by direct inhibition through release of inhibitory molecules (133). When these protective mechanisms are disrupted, an imbalance in the gut microbiota can occur. Gastric Acid Suppression Several conditions such as intestinal dysmotility, altered GI anatomy, immune deficiencies, and hypochlorhydria (134) are predisposing factors for the development of small intestinal bacterial overgrowth (SIBO). While hypochlorhydria can be a result of Helicobacter pylori colonization and aging, many people also take medications to reduce their gastric acidity for stress ulcer prophylaxis or gastric esophageal reflux disease. The pH of gastric acid in the stomach lumen is normally 1.5–3.5; maintaining intragastric pH above 3.5–5.0 prevents gastric mucosal injury and may be facilitated with histamine 2 receptor antagonists (H2RAs), sucralfate, and proton pump inhibitors (PPIs) (135). Previous studies show that PPIs are known to alter the GI bacterial population in 50% of patients on long-term treatment with any type of effective antisecretory drug (135, 136). Lombardo et al, conducted a study in 200 patients with gastroesophageal reflux disease (GERD) receiving PPI treatment, 200 patients with irritable bowel syndrome (IBS) not receiving PPI treatment, and 50 healthy control subjects not receiving PPI treatment greater than 10 years and showed that SIBO occurs more frequently in long-term PPI users than patients with IBS or control subjects (137). They found the incidence of SIBO was significantly different (P< .001) in patients using PPIs (50%) as compared to patients with IBS not using PPIs (24.5%), and healthy control subjects (6%). According to a multivariate analysis including 5,387 elderly subjects, the presence of diarrhea was significantly associated with use of PPIs (odds ratio [OR] 2.97, 95% confidence interval [CI] 2.03–4.35) and antibiotics (OR 4.58, 95% CI 1.95–10.73) (138). Theisen et al, found that the suppression of gastric acid with omeprazole led to a high prevalence of SIBO, leading to a markedly increased concentration of unconjugated bile acids (139). Conversely a retrospective chart review completed in 1,191 patients with glucose hydrogen breath testing (GHBT) evaluated whether this value positively correlated with patients on PPI therapy (134). Interestingly, GHBT was positively associated with older age and antidiarrheal use, but not with PPI use. Therefore, the authors concluded that PPI use was not associated with the presence of SIBO as measured by GHBT. However, Lombardo (140) challenged these results making a point that PPI use has become very common, both prescription and over-the-counter, and many patients may not consider non-prescription use as a medication and not disclose it to their physician. The authors were unable to confirm actual use of PPI due to the nature of a retrospective chart review. Additionally, as PPI duration is related to incidence of SIBO, the lack of knowledge regarding the duration the patients were taking a PPI leads one to speculate that if they only took it for a short time would it have an influence in GHBT results? Knowing the protective role gastric acidity has in regards to protecting the host against ingested pathogens, it is plausible that prolonged use of gastric acid suppressants contributes to the incidence of SIBO and that clinicians should be judicious in recommending their use. Antibiotics Antibiotic therapies not only target pathogenic microorganisms, but also the host-associated microbial communities in the gut. Most antibiotics have broad-spectrum activity so they can be used to treat many diseases. Thus, although antibiotics are designed to target pathogenic organisms, related members of the microbiota are also affected, leaving a lasting negative effect on the gut microbial community long after the antibiotics have ceased (141). Antibiotics can also promote the expansion of antibiotic-resistant strains which can act as a reservoir for resistance genes in the gut microenvironment (142). Decreased diversity in the microbiome typically follows antibiotic treatment, and even though most of the microbiota return to pretreatment levels, some members are lost from the community indefinitely (142). As microorganisms can be dependent upon other colonizers for the provision of nutrition, secondary metabolites or removal of toxic waste products, alterations in microbial co-dependence can leave detrimental effects (143). The antibiotic spectrum of activity will influence the shift in gut microbiota composition. Additionally, the administration dose of the antibiotic is also important in determining the ecological impact it will have on the microbiota. While the sub-therapeutic antibiotic dosing often used by the agriculture industry prophylactically and to promote animal growth does not reduce the total bacterial mass, this use is criticized as it shifts the composition of the microbiota and promotes dangerous levels of antibiotic resistance (144). Similarly in humans, antibiotic therapeutic doses are designed to minimize these effects, but despite these efforts, subsets of the microbiota can shift to that of increased colonization by opportunistic pathogens such as Clostridium difficile and Candida albicans. Noteworthy is that these effects of antibiotic delivery are not limited to oral delivery. Intravenously delivered antibiotics can have an effect on the gut microbiota as they become incorporated into bile and secreted into the intestine via the biliary system (144). Gut microbial community alterations can result in dysregulation of host immune homeostasis and an increased susceptibility to disease. Host-microbial interactions are very specific and antibiotic therapy causes alterations or loss of highly co-evolved processes (145, 146). Antibiotic-induced changes that are important to microbial regulation of host immunity include loss of bacterial ligands that are recognized by the host, loss of specific bacterial signals, and alterations in the metabolites produced by the microbiota such as short-chain fatty acids (147). Short-chain fatty acids (SCFA) are beneficial for gut health as they serve as a primary fuel source for the colonocyte, are involved with water and electrolyte absorption, help to maintain the intestinal barrier, and modulate cell proliferation, differentiation, growth and apoptosis (147). Provision of butyrate during broad-spectrum antibiotic therapy mitigated the negative effects of antibiotics on gut health, notably the mRNA and protein expression for several anion exchangers, butyrate receptor and transports as well as protein expression of intestinal tight junction proteins (148). Changes in gut immunity increase host susceptibility to infection by pathogens. For instance, treatment with metronidazole, an antibiotic that targets anaerobic bacteria, reduces the integrity of the mucus layer and accelerates mucosal attachment of C. rodentium (149). Changes in gut microbiota structure and function after antibiotic treatment create a metabolic environment that favors C. difficile germination and colonization and associated infectious diarrhea (150). While antibiotic therapy is the major risk factor for C. difficile colonization, the accepted treatment for C. difficile infection is further antibiotic therapy, initially with metronidazole and then vancomycin, if C. difficile persists (151). Repeated antibiotic use is often necessary in the treatment of recurrent Clostridium difficile infections which unfortunately causes further disruption of an imbalanced microbiota (152). Chang et al, identified that patients with recurrent C. difficile infection possessed a microbiota characterized by markedly reduced overall diversity compared to controls and to patients with an initial episode of the infection (152). C. difficile infection is debilitating to patients and extremely costly, with symptoms ranging from diarrhea to fulminant colitis, toxic megacolon and death (153). Fecal Microbiota Transplantation (FMT) is the process by which a homogenized stool sample from a healthy donor is administered into the GI tract of an individual. This therapy is now becoming a sought-out treatment to eradicate C. difficile colonization and correct gut dysbiosis. FMT has been shown to be a successful treatment option to eliminate recurrent and refractory C. difficile infection and to re-establish a healthy colony in certain patients (154). With its 91% primary and 98% secondary cure rates, FMT is gaining increased interest among researchers as a treatment option for other gastrointestinal disorders (154). Perspective and future directions With technological advances, knowledge regarding the gut microbiome has expanded from earlier beliefs (155, 156). The topics covered in this review are examples of what is currently understood regarding how the human gut microbiome is first established and how certain life encounters alter the composition, but they are by no means inclusive. The influence of the gut microbiome on health and disease is currently one of the most exciting areas of science. Learning more about how breaches upon the gut microbiome early in life coupled with further insults throughout life influences health may provide new insights for treatments of many challenging syndromes and diseases (e.g., fibromyalgia, irritable bowel disease, IBD, autism). We are just beginning to uncover the impact of how things we ingest can influence pathology. Future research should direct its focus to the gut microbiome as a biomarker for dietary intake and disease development, the effect of probiotic supplementation on clinical endpoints, and bacterial therapy for gut health, immunity and therapeutic treatments. New available and developing technologies to uncover the metabolon opens the path of exploration to this exciting frontier. The horizons are broad with exciting developments sure to come. Supplementary Material Copyright Click here to view.(14K, docx) Contributor Information Gail A. 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Chronic rhinosinusitis (CRS) is defined as inflammation of the mucosal lining of the nasal cavity and paranasal sinuses that has been present for more than 3 months, causing characteristic symptoms such as nasal blockage, discharge, reduction or loss of smell sensation and facial pressure. It is a broad clinical description that encompasses several phenotypes, most often divided into CRS with polyps and CRS without polyps. CRS may be the endpoint of several different inflammatory pathways and may be secondary to specific conditions such as cystic fibrosis or fungal aetiology, but most often cannot be attributed to a single pathophysiological trigger. CRS places an enormous burden on both physicians and its sufferers. It is common among the general population, affecting approximately 11% of UK adults,1 and causes greater detriment to quality of life (QoL) than angina or chronic lower respiratory tract disease.2 Not only is it a QoL issue, patients with CRS frequently have comorbid asthma, and poorly controlled CRS is associated with more frequent asthma exacerbations and a need for hospitalisation. The socio-economic cost of CRS is significant with 57% of patients reporting absenteeism and 28% experiencing associated anxiety and depression.3 4 One per cent of all UK adults will visit their general practitioner (GP) with CRS symptoms each year and require an average of four appointments each year; despite this, one in three patients in primary care has poorly controlled symptoms.5 CRS that cannot be adequately managed in primary care may require referral to secondary care, and data from Hospital Episode Statistics show that in a single year there were approximately 120 000 outpatient consultations for CRS and 40 000 sinus operations performed in England and Wales.6 However, there remains considerable debate regarding optimum management strategies leading to wide variation in practice.7 Treatment evidence and guidelines The touchstone for treatment of CRS is The European Position Paper on Rhinosinusitis and Nasal Polyps published in 2012 (EPOS 2012).8 EPOS 2012 syntheses the best available evidence and expert opinion into easy to follow treatment flowcharts for both primary care physicians and ear, nose and throat specialists, but acknowledges the large gaps in high-quality trial data on which to base their guidance. In the intervening 7 years since EPOS was published, the International Consensus Statement on Allergy and Rhinology (ICAR)9 was agreed by a multinational working group who undertook a comprehensive overview of the literature. The working group graded the available evidence and used it as the basis for recommendations; where no evidence was available, no recommendation was made. ICAR is therefore an exhaustive insight into the current state of the science in CRS and an invaluable tool for the otolaryngology community; for primary care, however, the EPOS 2012 remains perhaps the more accessible guide. In addition, there have also been several Cochrane reviews10–16 of treatments available for CRS, and these reviews along with the international consensus guidelines have been used to synthesise a National Institute for Health and Care Excellence (NICE) clinical knowledge summary, most recently updated in 2018.17 Intranasal treatment The foundation of CRS treatment is regular use of intranasal saline irrigation and corticosteroids and this strategy finds unanimous favour among the guidelines mentioned above. The evidence is weak but consistent: a Cochrane systematic review studied the effects of saline irrigation in people with chronic sinusitis.12 This identified only two studies that could robustly be included—one which compared the effect of high volume hypertonic saline irrigation to placebo in patients with CRS both with and without polyps, and another which studied only patients with polyps and compared the use of nasal saline irrigation. This Cochrane review concluded that there was weak evidence from these trials to support the use of nasal saline irrigation. In addition, it is a low-cost treatment which with low risk of adverse events. For this reason, it is recommended for virtually all patients with CRS although in practice is usually used in combination with other therapies. Intranasal corticosteroids are similarly favoured by all expert guidelines. There is a greater number of trials on which to base this opinion. A Cochrane systematic review11 identified (search date August 2015) 18 randomised controlled trials which studied the use of intranasal steroids versus placebo in CRS. The majority of these studies included patients with nasal polyps. Regular intranasal corticosteroid use was reported to be superior to placebo in all reported symptoms, although there was no evidence to support an overall improvement in QoL. A further Cochrane review of the different formulations of intranasal corticosteroids and methods of delivery13 did not identify any single agent with convincing evidence of superiority; however, there is an advantage offered by the second-generation agents (eg, mometasone furoate, fluticasone propionate, fluticasone furoate) which have favourable pharmacokinetic characteristics that minimise systemic bioavailability (<1%) compared with older intranasal corticosteroids (eg, beclomethasone diproprionate, betamethasone). Oral corticosteroids Oral corticosteroids are commonly prescribed in the treatment of CRS although there is a distinct lack of evidence for their efficacy. The NICE Clinical Knowledge Summary (CKS) makes no reference to their use. A Cochrane review in 201616 identified no studies of their use in CRS without polyps, a fact which is also reflected in the ICAR guideline.9 Their use in patients with polyps is better established, with several studies demonstrating short-term efficacy of oral corticosteroids in improving CRS-related QoL scores. Treatment courses are short—a typical regime might be 30 mg per day of prednisolone for 2–3 weeks—and thus the risk of side effects such as adrenal suppression and loss of bone mass is minimal. However, there is a risk of side effects such as gastrointestinal disturbance and insomnia even with these short courses. Patients should also be warned of the risk of osteonecrosis—a risk which may occur at doses of steroid previously thought to be safe (lowest reported associated total dose 105 mg, median associated dose 981 mg).18 The benefit of oral corticosteroids typically last 3–6 months, and so are a reasonable choice for patients who have not improved on the first line of saline irrigation and topical corticosteroids. However, an evidence‐based risk analysis of oral corticosteroid use in CRS with polyps performed by Leung et al 19 demonstrated that risk exceeded benefit if used more frequently than once every 2 years. Oral corticosteroid use is therefore restricted to short, infrequent courses, and with full disclosure of the potential serious associated side effects for patients. Antibiotics Where there is consensus recommending the use of nasal douches and corticosteroids, there is controversy regarding the use of antibiotics. Antibiotics are one of the most commonly prescribed medicines for CRS: of the 1% of UK adults with CRS who visit their GP each year, 91% of them will receive an antibiotic prescription.20 They will often receive not just one but repeated courses of antibiotics.21 There is pressure on GPs to use antibiotics as a first-line treatment, as recently some Clinical Commissioning Groups have insisted on a 3-month trial of macrolide antibiotics prior to secondary care referral.22 With the exception of acute infective exacerbations, routine use of antibiotics is controversial for three main reasons: first; the lack of high-quality evidence to support their efficacy; second, the emerging threat of antibiotic resistance and third, the side effects which may accompany some of the most commonly used agents. In 2016, the ICAR guideline noted a paucity of evidence for antibiotic use9; however, on balance it recommended that patients with polyps should not be prescribed short courses of non-macrolide antibiotics, unless in the particular circumstances of suffering an acute exacerbation. No conclusions could be drawn on longer courses, or for patients without polyps. This echoes the findings of a Cochrane review of the use of antibiotics in CRS, which found very little evidence that non-macrolide antibiotics are effective in patients with CRS although only two studies were fit for inclusion in analysis.15 These recommendations guided the NICE CKS17 to make the recommendation to seek specialist advice before initiating long-term antibiotics in primary care. It is, however, recognised that there does remain a role for appropriate use of macrolide antibiotics in specific circumstances. In particular, there is growing interest in immune-modulating and anti-inflammatory effects of macrolides in chronic airway inflammatory disease, with low-dose long-term macrolides being prescribed for its effects on the immune response and not primarily as an anti-bacterial agent.23 The Cochrane review of 2016 noted that there was a moderate quality of evidence of a modest improvement in disease‐specific QoL in patients with CRS without nasal polyps receiving 3 months of a macrolide.15 However, this improvement was short-lived, as 3 months following the cessation of the antibiotics there was no measurable effect of treatment. Resistance Antibiotic resistance is considered one of the most significant threats to patients’ safety in Europe.24 Evaluating effectiveness of antibiotics and promoting appropriate usage is integral to the UK 5-year antimicrobial resistance strategy.25 Given the high prevalence of CRS and the variability in prescribing, overuse of inappropriate antibiotics may represent a public health danger through selective pressure on bacteria and resistance. In particular, macrolide resistance has been noted to have implications in infections secondary to Streptococcus pneumoniae (upper and lower respiratory tract infections) and Mycoplasma genitalium (sexually transmitted infections), leading to longer duration of illness and requirement for multiple antibiotic courses.26 Side effects Antibiotics are commonly associate with wide range of side effects ranging from the mild (rash, nausea, diarrhoea) to the life threatening (anaphylaxis). Specific to the use of macrolides are concerns about potential cardiovascular side effects.27 There have been a number of publications raising concerns about cardiac toxicity with erythromycin in patients with a prolonged QT interval.28 29 A 2016 study which looked at adverse outcomes associated with clarithromycin use found a significant association was found between clarithromycin use and cardiovascular mortality, where longer durations of clarithromycin use were associated with more cardiovascular events.29 By contrast, this association was not found with use of β-lactam antibiotics leading the authors to hypothesise that it was an effect specific to clarithromycin. This hypothesis was unintentionally tested by the lead investigators of the CLARICOR trial (Effect of Clarithromycin on Mortality and Morbidity in Patients With Ischemic Heart Disease) who had planned to measure the efficacy of a 2-week course of 500 mg clarithromycin two times per day to improve the clinical manifestations of stable coronary heart disease.30 The study was halted prematurely due to the finding of excess deaths in the intervention group: all-cause mortality was significantly higher in the group had taken clarithromycin, an effect which persisted for 10 years post-intervention. The use of clarithromycin in patients with known cardiovascular disease is therefore only undertaken with a significant degree of caution. Surgery Patients who are referred to secondary care who are considered to have tried and failed appropriate medical therapy – which is to say, a sufficient trial of nasal douching and topical steroids—are considered candidates for endoscopic sinus surgery (ESS).31 32 ESS is a loosely defined procedure and can range from very simple balloon expansion of the sinus openings, to extensive procedures that open every bony partition within the sinuses. The risks of surgery include epistaxis, breach of the skull base with resultant CSF leak or meningitis and injury to the intraorbital structures which may result in impaired vision. Insufficient evidence to define the role and extent of surgery contributes to a fivefold variation in UK intervention rates,33 with wide variation in surgical practice and very high rates of revision surgery.34 35 Such uncertainty resulted in inclusion of ESS in the NICE Database of Treatment Uncertainties.36 However, there can be no doubt that in appropriately selected patients, surgery offers significant and durable relief from symptoms. The largest UK study of CRS and its outcomes demonstrated that not only was there a significant improvement in patient-reported symptoms following ESS, but that patients who had surgery earlier in their disease course had a greater degree of improvement that lasted longer versus those who underwent delayed surgery.37 In addition to improving nasal symptoms, a systematic review demonstrated that ESS is associated with improved asthma control with significantly fewer attacks, hospitalisations, and a reduced requirement for medication use following sinus surgery in patients with comorbid CRS and asthma.38 Each of the international consensus guidelines referenced above recommends that patients who have tried a course of appropriate medical therapy but do not have control of their symptoms should be considered as a candidate for surgery.8 9 The path forwards In the last two decades, the majority of new treatments that have become available for CRS have in the main been refinements rather than revolutions—for example, new formulations of intranasal steroids or third-generation antihistamines. However, there are some genuinely new and exciting innovations which are on the cusp of integration to clinical practice. Monoclonal antibodies that bind to targets such as IgE, interleukin-4 (IL-4) and IL-5 were developed primarily as treatments for asthma, but clinical trials have demonstrated that several of these agents may also be effective in CRS with polyps.39 At present, they remain expensive and are limited to subsets of patients with difficult to treat asthma, but as prices fall in future and evidence for their efficacy accumulates then in future they may become available for the treatment of CRS. There have also been several promising avenues of research that may unlock further therapeutic targets, such as the role of the microbiome in sinus disease. However, as alluded to in the many international guidelines, there is a paucity of evidence for many of the treatments that are currently used in CRS before even considering new innovations. This has led to a redoubling of efforts in CRS research to produce high-quality evidence for commonly available treatments. Key to these efforts is the need to accurately define the endotypes of disease which will be studied in trials, as broad clinical phenotypes such as ‘polyps’ may encompass a wide range of underlying pathophysiology. Tightly defining the endotypes of disease for trial inclusion will permit robust examination of the response to treatment in each subgroup. Meta-analyses of CRS outcomes have been hampered by the broad clinical phenotypes, and using precise endotypes will enhance our ability to pool data from multiple trials; this will also be enabled by international consensus statements that define key criteria such appropriateness for ESS40 and standardised sets of outcome measures;41 and funding has been secured for one of the largest ever trials of interventions in CRS which will specifically examine the question of the efficacy of both macrolides and ESS (the MACRO trial42) in subgroups of patients defined by precise clinical and pathological parameters. At present, treatment of CRS exists in a time of genuine clinical equipoise where treatment is empirical and even international guidelines depend more heavily on expert opinion than robust scientific statements. Ongoing research endeavours aim to transform the treatment of CRS and usher in the era of precise, personalised medicine for these patients. Main messages Chronic rhinosinusitis (CRS) is a common disease in UK adults and causes significant detriment to life. The best evidence for effective treatment is for topical intranasal corticosteroids and saline irrigation. For patients who do not respond to this first-line treatment, there are many potential avenues for further treatment but there is controversy about which strategy is the most effective Current research questions Is it possible to identify specific endotypes of CRS to replace the broad clinical phenotypes that we currently base our treatment plans on? Are macrolide antibiotics an effective treatment in CRS? Is best medical treatment superior to surgery in the treatment of CRS? Key references Fokkens WJ, et al, European Position Paper on Rhinosinusitis and Nasal Polyps 2012. Rhinolgy 2012 3 p preceding table of contents, 1–298. Orlandi RR, et al, International Consensus Statement on Allergy and Rhinology: Rhinosinusitis. Int Forum Allergy Rhinol 2016. 6 Suppl 1: p. S22-209. NICE. Sinusitis. 2018; Available from: https://cks.nice.org.uk/sinusitis%23!scenario:1 Head K, et al, Systemic and topical antibiotics for chronic rhinosinusitis. Cochrane Database Syst Rev 2016. 4: p. CD011994 Hopkins C, et al, Long-term outcomes from the English national comparative audit of surgery for nasal polyposis and chronic rhinosinusitis. Laryngoscope 2009. 119 : p. 2459–65. Self-assessment questions Which of the following are typical symptoms of chronic rhinosinusitis? (a) Bleeding and crusting (b) Unilateral blood tinged discharge (c) Blockage, discharge, loss of sense of smell, facial pressure (d) Visual disturbance The first-line treatment for chronic rhinosinusitis (CRS) is oral steroids and antibiotics. True or false? A prolonged course of antibiotics (eg, up to 3 months) may occasionally be used in specific circumstances. What group of antibiotics has the best evidence to support their use for prolonged courses in CRS? (a) Penicillins (b) Macrolides (c) Aminoglycosides (d) Fluoroquinolones And what adverse effects should the patient be advised of with these long-term antibiotics? (a) Cardiac comorbidity (b) Osteonecrosis of the femoral head (c) Epistaxis (d) Infertility There is good evidence to support the superiority of surgical treatment of CRS compared with medical treatment. True or false? Answers Answer: (c) These are typical CRS symptoms. Bleeding and crusting should raise the possibility of vasculitis, septal perforations, or recreational cocaine use. Unilateral blood tinged discharge is a red flag sign that should prompt concerns of malignancy. Visual disturbance may be caused by rare complications of CRS, but is not at all typical. Answer: False. The first-line treatment for CRS should be topical steroids and saline irrigation. Answer: Macrolides. Answer: Cardiac comorbidity, particularly in patients with known heart disease. Osteonecrosis of the femoral head is a complication of oral steroids while topical steroids may cause epistaxis. Macrolides are not recognised to cause infertility but their use should be restricted during pregnancy. The Food and Drug Administration of USA recommend that if a macrolide must be used in pregnancy then azithromycin is category B (ie, safe in animal studies) while clarithromycin is category C (ie, shown to cause harm in animal studies). Answer: False. There are very few high-quality trials that compare medical treatment to surgery, and meta-analysis is made difficult by wide variability in study protocols. References ↵ Hastan D , Fokkens WJ , Bachert C , et al . Chronic rhinosinusitis in Europe--an underestimated disease. A GA²LEN study. Allergy 2011;66:1216–23.doi:10.1111/j.1398-9995.2011.02646.x ↵ Gliklich RE , Metson R . The health impact of chronic sinusitis in patients seeking otolaryngologic care. Otolaryngol Head Neck Surg 1995;113:104–9.doi:10.1016/S0194-5998(95)70152-4 ↵ Sahlstrand-Johnson P , Ohlsson B , Von Buchwald C , et al . A multi-centre study on quality of life and absenteeism in patients with CRS referred for endoscopic surgery. Rhinology 2011;49:420–8.doi:10.4193/Rhino11.101 OpenUrlPubMed ↵ Erskine SE , Hopkins C , Clark A , et al . Chronic rhinosinusitis and mood disturbance. Rhin 2017;55:113–9.doi:10.4193/Rhin16.111 OpenUrl ↵ Lange B , Holst R , Thilsing T , et al . Quality of life and associated factors in persons with chronic rhinosinusitis in the general population: a prospective questionnaire and clinical cross-sectional study. Clin Otolaryngol 2013;38:474–80.doi:10.1111/coa.12189 OpenUrlCrossRefPubMed ↵Hospital Episode Statistics Department of Health; 2013. ↵ Vennik J , Eyles C , Thomas M , et al . Management strategies for chronic rhinosinusitis: a qualitative study of GP and ENT specialist views of current practice in the UK. BMJ Open 2018;8:e022643.doi:10.1136/bmjopen-2018-022643 ↵ Fokkens WJ , Lund VJ , Mullol J , et al . EPOS 2012: European position paper on rhinosinusitis and nasal polyps 2012. A summary for otorhinolaryngologists. Rhinology 2012;50:1–12.doi:10.4193/Rhino50E2 OpenUrlCrossRefPubMed ↵ Orlandi RR , Kingdom TT , Hwang PH , et al . International Consensus Statement on Allergy and Rhinology: Rhinosinusitis. Int Forum Allergy Rhinol 2016;6 Suppl 1:S22–S209.doi:10.1002/alr.21695 OpenUrl ↵ Head K , Sharp S , Chong L-Y , et al . Topical and systemic antifungal therapy for chronic rhinosinusitis. Cochrane Database Syst Rev 2018;16.doi:10.1002/14651858.CD012453.pub2 ↵ Chong LY , Head K , Hopkins C , et al . Intranasal steroids versus placebo or no intervention for chronic rhinosinusitis. Cochrane Database Syst Rev 2016;115.doi:10.1002/14651858.CD011996.pub2 ↵ Chong LY , Head K , Hopkins C , et al . Saline irrigation for chronic rhinosinusitis. Cochrane Database Syst Rev 2016;67.doi:10.1002/14651858.CD011995.pub2 ↵ Chong LY , Head K , Hopkins C , et al . Different types of intranasal steroids for chronic rhinosinusitis. Cochrane Database Syst Rev 2016;25(Suppl 2).doi:10.1002/14651858.CD011993.pub2 ↵ Head K , Chong LY , Hopkins C , et al . Short-course oral steroids as an adjunct therapy for chronic rhinosinusitis. Cochrane Database Syst Rev 2016;27.doi:10.1002/14651858.CD011992.pub2 ↵ Head K , Chong LY , Piromchai P , et al . Systemic and topical antibiotics for chronic rhinosinusitis. Cochrane Database Syst Rev 2016;19.doi:10.1002/14651858.CD011994.pub2 ↵ Head K , Chong LY , Hopkins C , et al . Short-course oral steroids alone for chronic rhinosinusitis. Cochrane Database Syst Rev 2016;2.doi:10.1002/14651858.CD011991.pub2 ↵NICE. Sinusitis, 2018. Available: https://cks.nice.org.uk/sinusitis#!scenario:1 ↵ Kennedy P , Bassiouni A , Psaltis A , et al . Avascular necrosis after oral corticosteroids in otolaryngology: Case report and review of the literature. Allergy Rhinol 2016;7:50–4.doi:10.2500/ar.2016.7.0142 OpenUrl ↵ Leung RM , Dinnie K , Smith TL . When do the risks of repeated courses of corticosteroids exceed the risks of surgery? Int Forum Allergy Rhinol 2014;4:871–6.doi:10.1002/alr.21377 OpenUrl ↵ Gulliford MC , Dregan A , Moore MV , et al . Continued high rates of antibiotic prescribing to adults with respiratory tract infection: survey of 568 UK general practices. BMJ Open 2014;4:e006245.doi:10.1136/bmjopen-2014-006245 ↵ Akkerman AE , Kuyvenhoven MM , van der Wouden JC , et al . Prescribing antibiotics for respiratory tract infections by GPs: management and prescriber characteristics. Br J Gen Pract 2005;55:114–8. ↵ Soni-Jaiswal A , Philpott C , Hopkins C . The impact of commissioning for rhinosinusitis in England. Clin Otolaryngol 2015;40:639–45.doi:10.1111/coa.12430 OpenUrl ↵ Cervin A , Wallwork B . Macrolide therapy of chronic rhinosinusitis. Rhinology 2007;45:259–67. ↵ Lodato EM , Kaplan W . Priority Medicines for Europe and the World "A Public Health Approach to Innovation": Background Paper 6.1 Antimicrobial resistance World Health Organisation; 2013. ↵ Davies SC , Gibbens N . UK Five Year Antimicrobial Resistance Strategy 2013 to 2018 Department of Health and Department for Environment, Food & Rural Affairs; 2013. ↵ Gaynor M , Mankin AS . Macrolide antibiotics: binding site, mechanism of action, resistance. Curr Top Med Chem 2003;3:949–60.doi:10.2174/1568026033452159 ↵ Gibbins NE , Theokli C , Hopkins C . Time to reconsider guidelines on clarithromycin in chronic rhinosinusitis? BMJ 2013;346:f2678.doi:10.1136/bmj.f2678 ↵ Wong AYS , Chan EW , Anand S , et al . Managing Cardiovascular Risk of Macrolides: Systematic Review and Meta-Analysis. Drug Saf 2017;40:663–77.doi:10.1007/s40264-017-0533-2 OpenUrlCrossRef ↵ Cheng Y-J , Nie X-Y , Chen X-M , et al . The Role of Macrolide Antibiotics in Increasing Cardiovascular Risk. J Am Coll Cardiol 2015;66:2173–84.doi:10.1016/j.jacc.2015.09.029 OpenUrlFREE Full Text ↵ Winkel P , Hilden J , Hansen JF , et al . Clarithromycin for stable coronary heart disease increases all-cause and cardiovascular mortality and cerebrovascular morbidity over 10years in the CLARICOR randomised, blinded clinical trial. Int J Cardiol 2015;182:459–65.doi:10.1016/j.ijcard.2015.01.020 OpenUrl ↵ Baguley C , Brownlow A , Yeung K , et al . The fate of chronic rhinosinusitis sufferers after maximal medical therapy. Int Forum Allergy Rhinol 2014;4:525–32.doi:10.1002/alr.21315 OpenUrl ↵ Young LC , Stow NW , Zhou L , et al . Efficacy of medical therapy in treatment of chronic rhinosinusitis. Allergy Rhinol 2012;3:8–12.doi:10.2500/ar.2012.3.0027 OpenUrl ↵ Hopkins C . Commissioing Guide: Chronic Rhinosinusitis. Royal College of Surgeons of England London; 2016. ↵ Philpott C , Hopkins C , Erskine S , et al . The burden of revision sinonasal surgery in the UK-data from the Chronic Rhinosinusitis Epidemiology Study (CRES): a cross-sectional study. BMJ Open 2015;5:e006680.doi:10.1136/bmjopen-2014-006680 ↵ Hopkins C , Slack R , Lund V , et al . Long-term outcomes from the English national comparative audit of surgery for nasal polyposis and chronic rhinosinusitis. Laryngoscope 2009;119:2459–65.doi:10.1002/lary.20653 ↵NICE. Database of Uncertainties of Treatments. ↵ Hopkins C , Rimmer J , Lund VJ . Does time to endoscopic sinus surgery impact outcomes in Chronic Rhinosinusitis? Prospective findings from the National Comparative Audit of Surgery for Nasal Polyposis and Chronic Rhinosinusitis. Rhinology 2015;53:10–17.doi:10.4193/Rhin13.217 OpenUrl ↵ Vashishta R , Soler ZM , Nguyen SA , et al . A systematic review and meta-analysis of asthma outcomes following endoscopic sinus surgery for chronic rhinosinusitis. Int Forum Allergy Rhinol 2013;3:788–94.doi:10.1002/alr.21182 OpenUrlCrossRefPubMed ↵ Pauwels B , Jonstam K , Bachert C . Emerging biologics for the treatment of chronic rhinosinusitis. Expert Rev Clin Immunol 2015;11:349–61.doi:10.1586/1744666X.2015.1010517 OpenUrlCrossRefPubMed ↵ Rudmik L , Soler ZM , Hopkins C , et al . Defining appropriateness criteria for endoscopic sinus surgery during management of uncomplicated adult chronic rhinosinusitis: a RAND/UCLA appropriateness study. Int Forum Allergy Rhinol 2016;6:557–67.doi:10.1002/alr.21769 OpenUrl ↵ Hopkins C , Hettige R , Soni-Jaiswal A , et al . CHronic Rhinosinusitis Outcome MEasures (CHROME), developing a core outcome set for trials of interventions in chronic rhinosinusitis. Rhinology 2018;56:22–32.doi:10.4193/Rhin17.247 OpenUrl ↵ Philpott C , le Conte S , Beard D , et al . 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KEY POINTS Pre-existing BCG immunity influences T cell responses of subunit booster vaccines. M. tuberculosis–specific subunit vaccines bypass this mechanism and improve protection. Abstract Despite the fact that the majority of people in tuberculosis (TB)–endemic areas are vaccinated with the Bacillus Calmette–Guérin (BCG) vaccine, TB remains the leading infectious cause of death. Data from both animal models and humans show that BCG and subunit vaccines induce T cells of different phenotypes, and little is known about how BCG priming influences subsequent booster vaccines. To test this, we designed a novel Mycobacterium tuberculosis–specific (or “non-BCG”) subunit vaccine with protective efficacy in both mice and guinea pigs and compared it to a known BCG boosting vaccine. In naive mice, this M. tuberculosis–specific vaccine induced similar protection compared with the BCG boosting vaccine. However, in BCG-primed animals, only the M. tuberculosis–specific vaccine added significantly to the BCG-induced protection. This correlated with the priming of T cells with a lower degree of differentiation and improved lung-homing capacity. These results have implications for TB vaccine design. This article is featured in Top Reads, p.1979 Introduction Mycobacterium tuberculosis infection is the leading cause of death because of a single infectious agent and has been in the top 10 causes of death worldwide for years (1).The only vaccine currently available against tuberculosis (TB) is M. bovis Bacillus Calmette–Guérin (BCG). When administered in early life, BCG efficiently prevents severe forms of childhood TB, but the efficacy against pulmonary disease in adulthood, the most common form of TB disease, is variable (2, 3). Thus, a new vaccine that prevents active pulmonary TB is needed to reduce M. tuberculosis transmission and TB-related mortality. CD4 T cells have been shown to be critical for host resistance to M. tuberculosis infections and are therefore the most common cell type targeted in preclinical and clinical TB vaccine development (4, 5). During M. tuberculosis infection, Ag expression and presentation have a major effect on differentiation and function of CD4 T cells. Recent mouse studies have shown that TB infection drives the differentiation of M. tuberculosis–specific CD4 T cells away from central memory T cells (e.g., secreting IL-2) toward effector/effector memory T cells that predominantly secrete IFN-γ (6). This results in a loss of self-renewing T cell subsets because of an impairment in the IL-2–producing capacity and a reduced capacity to traffic into the infected lung parenchyma (7, 8). Circulating T cells’ ability to populate the lung parenchyma has been established as a necessity for T cell–mediated protection in the lung (7, 9), possibly because a direct recognition of infected cells by CD4 T cells via the TCR is required (10). Thus, the ability to resist functional differentiation and home into inflamed lung tissues are key features for long-term protective CD4 T cells (7, 9). Similar to M. tuberculosis infection, the live mycobacterial BCG vaccine has been shown to promote differentiation and functional exhaustion of CD4 T cells in parenteral BCG-vaccinated mice, resulting in a failure to efficiently maintain long-term protection against M. tuberculosis (11–13). A recent study comparing different TB vaccines in clinical testing suggests that BCG may also induce more differentiated T cells than subunit vaccines in people (14). In line with this, we have recently shown that vaccination with an adjuvanted protein subunit vaccine (H56/CAF01) elicits less differentiated CD4 T cells with the capacity to localize to the infected parenchyma (15). In naive animals, such T cells are readily induced, but it has proven difficult to substantially reprogram the immune response after M. tuberculosis exposure by subunit vaccination (16–20). Given the similarities between the immune response arising from BCG vaccination and M. tuberculosis infection, we hypothesize that pre-existing “BCG-imprinted” T cells dictate the phenotype of the immune response induced by subsequent subunit booster vaccines. To investigate this, we designed two novel vaccines, H64 and H74, that selectively incorporated M. tuberculosis–specific (or “non-BCG”) Ags and compared the protective efficacy and T cell phenotype to a known booster vaccine sharing all of its Ags with BCG (H65) (21). Thus, H65 was tested as a classical BCG booster vaccine, whereas the H64 and H74 subunit vaccines supplement BCG’s Ag repertoire with M. tuberculosis–specific Ags. For comparability, the three vaccines consisted of six Ags that were either secreted by or associated with the type VII secretion system (also called the ESX secretion systems). H64 and H74 consisted of ESX-1–associated Ags (M. tuberculosis specific), whereas H65 consisted of Ags associated to ESX-2, 3, and 5 (also present in BCG). We first confirmed that the ESX-1 Ags were protective in mice and guinea pigs and that the level of protection was similar to the BCG boosting vaccine H65. We then moved on to show that in BCG-primed mice, the CD4 T cells induced by the H65 booster vaccine were more differentiated than the CD4 T cells induced by the ESX-1–based vaccine. Importantly, the T cells specific for the ESX-1 vaccine maintained their polyfunctionality and low differentiation status during chronic M. tuberculosis infection and were superior in entering the M. tuberculosis–infected lung parenchyma. As a result, the lung bacterial burden was significantly decreased in the BCG plus ESX-1 vaccination group compared with the groups with either BCG alone or BCG boosted with the H65 vaccine. These data add to the body of evidence supporting the use of ESX-1–associated (or other M. tuberculosis–specific/non-BCG) Ags in future TB vaccines (16, 22–25) and address the potential influence of BCG priming on subsequent booster vaccines. Materials and Methods Animals Six- to ten-week-old female mice or 400–500 g outbred female Hartley guinea pigs (Charles River Laboratories) were rested for 1 wk prior to initiation of any experimental procedures. Except for the M. tuberculosis Beijing HN878 challenge study, all mouse experiments were performed with female CB6F1 mice (Envigo) at Statens Serum Institut according to the Danish Ministry of Justice and Animal Protection Committees under permit 2014-15-2934-01065 and in compliance with European Union Directive 2010/63/EU. Mice were provided with radiation-sterilized food (Harlan Scandinavia) and water ad libitum and handled in accordance with the Danish Ministry of Justice and Animal Protection Committee regulations by authorized personnel. Infected mice were housed in a biosafety level 3 facility in cages contained within laminar flow safety enclosures (Scantainer, Scanbur). In the challenge study with the hypervirulent M. tuberculosis Beijing HN878, female C57BL/6 mice were purchased from SLC (Shizuoka, Japan). All animal experiments were performed according to the Korean Food and Drug Administration regulations and guidelines. The experimental protocols were reviewed and approved by the Ethics Committee and Institutional Animal Care and Use Committee (Permit Number: 2017-0264). All in vivo experiments were carried out under barrier conditions in an animal biological safety level 3 facility at the Avison Biomedical Research Center at Yonsei College of Medicine. Guinea pigs were maintained under animal biosafety level 3 barrier conditions in isolator cages (Thoren Caging Systems, Hazleton, PA) at Colorado State University. All experimental procedures were conducted in accordance with the Public Health Service Policy on the Humane Care and Use of Laboratory Animals and approved by the Colorado State University Institutional Animal Care and Use Committee (approval no. 13-4565A). Recombinant proteins All DNA constructs used in this study were made by chemical synthesis and codon optimized for expression in Escherichia coli before insertion into the pJ 411 expression vector (ATUM, Menlo Park, CA). Hybrid H64 and H74 were protein fusions without linkers between the six open reading frames. To minimize protein aggregation, all codons encoding cysteine were replaced with serine codons, five in H74 and three in H64. In both fusions, we added a His tag at the N-terminal end (MHHHHHH-). After transformation into E. coli BL21 (DE3) (Agilent Technologies), protein expression was induced with 1 mM isopropyl β-d-1-thiogalactopyranoside in 3-l cultures, and the proteins were purified from inclusion bodies by a three-step process as previously described (26). Hybrid H56 and H65 were designed as earlier described (21, 27) and expressed and purified in the same way as H74 and H64. The products were pure full-length products (>99% purity) with a protein concentration between 0.3 and 0.7 mg/ml and a total yield between 4 and 15 mg for the protein batches produced for this work. The identity of all purified protein batches was confirmed by mass spectrometry analysis (matrix-assisted laser desorption/ionization–time-of-flight). Immunizations and infections Mice were immunized s.c. three times at 2-wk intervals at the base of the tail with the fusion protein formulated in a cationic liposome adjuvant. Cationic liposomes (CAF01, 250 μg dimethyldioctadecyl-ammonium/50 μg trehalose 6,6-dibehenate) were emulsified with 1–10 μg fusion protein in 10 mM sterile Tris buffer (pH 7.4) to a final volume of 200 μl for each injection. Negative control mice received three equivalent doses of saline, and positive control mice received a single dose of 1 × 105 CFU M. bovis BCG Danish 1331 (Statens Serum Institut, Copenhagen, Denmark) given s.c. in the first round of immunization. In M. bovis BCG boost experiments, mice received one s.c. injection of 1 × 105 CFU M. bovis BCG Danish 1331 and were rested 8–26 wk, depending on the experiment, before vaccination three times with fusion protein as described above. Six weeks after the third immunization, mice were challenged with 50–100 M. tuberculosis strain Erdman (American Type Culture Collection), H37Rv (American Type Culture Collection 27294), Kazakhstan (mycobacterial interspersed repetitive units [MIRU] 1270-52), Vietnam (MIRU 1393-252), Beijing (MIRU 94-32), or Beijing HN878 suspended in PBS Tween 20 (0.05%). For M. tuberculosis strain Erdman, H37Rv, Beijing, Vietnam, and Kazakhstan, performed at Statens Serum Institut, we used a Biaera exposure system controlled by the AeroMP aerosol management, and for the hypervirulent M. tuberculosis strain Beijing HN878 experiment, performed at Yonsei College of Medicine, mice were infected with 60–70 virulent mycobacteria per mouse via the respiratory route using the inhalation chamber (Glas-Col, Terre Haute, IN). Guinea pigs (10/group), housed at Colorado State University, were immunized via the i.m. route and rested for 10 wk. A saline-treated and an intradermal M. bovis BCG–vaccinated group (inoculated with 103 CFU via the intradermal route) were included as a negative and positive control, respectively. Ten weeks postvaccination, guinea pigs were infected with a low-dose aerosol delivering ∼10 viable mycobacteria of virulent M. tuberculosis strain H37Rv into the lung of each animal. The animals were euthanized when they reached the set criteria established by the Institutional Animal Care and Use Committee, such as being moribund or exceeding acceptable weight loss and/or being affected in their respiratory rate (labored/heavy breathing). The body temperature was measured to track the clinical progression of the disease. For this, guinea pigs received a s.c. microchip implant (IPT-300 Bio Medic Data Systems, Seaford, DE) that allowed for the measurement of temperature and also carried information about experiment number and animal number. The body temperatures of individual guinea pigs were assessed each day at approximately the same time in the afternoon using a DAS-6006/7 scanner transponder (Bio Medic Data Systems). Isolation of cells and CFU measurements Spleen and lymph nodes from individual animals were kept at 4°C until processed through 70-μm nylon cell strainers (BD Pharmingen) followed by two washes and resuspension of the mononuclear cells in RPMI 1640 containing 5% FBS. Isolated lungs were transferred into Miltenyi C tubes containing HEPES/RPMI 1640 supplemented with collagenase (Roche/Sigma). The lungs were subsequently homogenized and digested for 30–45 min at 37°C and passed through cell strainers (BD Biosciences). After washing, the cells were resuspended in RPMI 1640 containing 5% FBS and stored at 4°C until use. For CFU measurements, lung homogenates were prepared in PBS Tween 80 (0.05%) from individual mice and plated at 3-fold serial dilutions on Middlebrook 7H11 Bacto Agar. After 3 wk of incubation at 37°C, the CFU were enumerated. Flow cytometry Single-cell suspensions of splenocytes or lung mononuclear cells (2 × 106 cells/well) were stimulated in vitro in V-bottom 96-well plates at 37°C in 200 μl complete media containing anti-CD49d (1 μg/ml) and anti-CD28 (1 μg/ml) Abs in the presence of rAg (2 μg/ml) for 1 h. Subsequently, 10 μg/ml brefeldin A (Sigma-Aldrich) was added, and the incubation continued for another 5–6 h. Following overnight storage at 4°C, cells were washed in FACS buffer (PBS containing 0.1% sodium azide and 1% FBS) and stained 30 min at 4°C for surface markers with mAbs as indicated. We used 1:400 dilutions of anti-CD4–Brilliant Violet 510 (clone RM 4.5; BioLegend), anti-CD4–Brilliant Violet 786 (clone GK1.5; BioLegend), 1:100 dilutions of anti-CD4–PerCP (clone GK1.5; BioLegend), or 1:200 dilutions of anti-CD4–FITC (clone RM4.4; BD Biosciences) and 1:600 dilutions of anti-CD44–FITC (clone IM7; eBioscience) and anti-CD8–PerCP-Cy5.5 (clone 53-6.7; eBioscience). Cells were then washed in FACS buffer, permeabilized using the Cytofix/Cytoperm kit (BD Biosciences) according to the manufacturer’s instructions, and stained intracellularly for 30 min at 4°C in dilutions of 1:200 using anti–IFN-γ–PE-Cy7 or anti–IFN-γ–PerCP-Cy5.5 (clone XMG1.2; eBioscience), anti–TNF-α–PE or anti–TNF-α–PeCy7 (clone MP6-XT22; eBioscience), anti–IL-17–allophycocyanin (clone eBio17B7; eBioscience), or dilutions of 1:100 using anti–IL-2–allophycocyanin-Cy7 (clone JES6-5H4; BD Biosciences) mAbs. Cells were subsequently washed with BD Perm/Wash Buffer (BD Biosciences) and resuspended in FACS buffer. Data were collected by running the stained cells on a FACSCanto, FACSCalibur, or FACSFortesa flow cytometer (BD Biosciences) and analyzed using FlowJo software v.10.0.7. In vivo intravascular labeling of T cells At the day of the experiment, mice were injected i.v. with 2 μg of FITC-labeled Abs against CD45.2 in a total volume of 200 μl (clone 102; BioLegend, San Diego, CA). Three minutes after Ab injection, mice were euthanized, and single-cell suspensions were prepared as described above. Adoptive transfer and lung homing For coadoptive transfer studies, donor CD4 T cells from subunit-vaccinated and M. bovis BCG plus subunit–vaccinated animals were isolated by negative selection 3 wk after the last immunization. In brief, cells were isolated from spleen, medial iliac, inguinal, and axillary lymph nodes from eight individual vaccinated donor animals, pooled within the groups and enumerated. Untouched CD4 T cell enrichment was performed from 5 × 108 cells per group using the EasySep Mouse CD4 T cell Enrichment Kit following the manufacturer’s instructions (STEMCELL Technologies). After enrichment, cells were counted, and the density was adjusted to 2.5 × 107 cells per ml for each group (93–95% purity). For tracking, the purified cells were differentially stained for 10 min with 10 μM Cell Proliferation Dye eFluor 450 or 5 μM Cell Proliferation Dye eFluor 670 (Thermo Fisher Scientific). The proliferation dyes were quenched with PBS containing 20% FBS followed by washing and resuspension in PBS. Stained cells were mixed in a ∼1:1 ratio and coadoptively transferred into recipient mice that were infected with M. tuberculosis strain Erdman 3 wk prior. Two hundred microliters (5 × 106 CD4 T cells) was injected into the lateral tail vein of individual recipient mice (the equivalent of one donor mouse per recipient mouse). Eighteen hours after transfer, recipient mice were injected with FITC-labeled anti-CD45.2 Abs for intravascular labeling (clone 102; BD Biosciences) and single-cell suspensions from the lung prepared as described above. Statistical analysis Prism 7 software (GraphPad Prism ver. 8.2.1, San Diego, CA) was used for all statistical analyses. Mean and SEM are indicated for log-transformed CFU counts. Mean and SD are indicated for immune responses. One-way ANOVA combined with Tukey multiple comparison test was used for comparing multiple groups. Statistical significant differences are indicated by asterisks in the figures: *p < 0.05, **p < 0.01, ***p < 0.001, and ****p < 0.0001. In the guinea pig experiment, the nonparametric log-rank test was used to compare the survival distributions of two samples comparing the survival curves for the vaccinated groups against the saline group. Results ESX-1–associated Ags (M. tuberculosis–specific) provide protection in mice and guinea pigs To investigate the influence of BCG priming on subsequent subunit vaccination, we first designed protective subunit vaccines that selectively incorporated M. tuberculosis–specific Ags, which are not shared with BCG. The M. tuberculosis genome encodes ∼4000 proteins, of which many are potential vaccine targets. However, ∼3900 of these have highly similar orthologs in the BCG genome, which significantly limits the number of potential Ags for this type of vaccine (28, 29). In our selection, we exploited that all BCG substrains lack the genomic locus “region of difference 1” (23), which includes the core genes for the ESX-1 secretion system. In virulent M. tuberculosis strains, ESX-1–secreted proteins are among the most immunogenic Ags and are frequently recognized in TB patients and latently infected individuals (30, 31). However, in BCG, the region of difference 1 deletion is expected to prevent priming of T cells against ESX-1–associated Ags, and we therefore selected among this group of proteins for the first subunit vaccine, referred to as H64. We selected six ESX-1–associated Ags for which proteome studies had identified the proteins in M. tuberculosis culture filtrate or membrane fractions (Table I) and constructed the H64 subunit vaccine as a recombinant fusion protein (Fig. 1A). In H64-vaccinated CB6F1 mice, the CD4 T cells recognized the EsxA, EspD, and EspR Ags (Fig. 1B), and we found that the subunit vaccine induced protection with protein doses ranging from 0.01 to 25 μg per vaccination peaking in the range of 1–5 μg (Fig. 1C). Based on this, an intermediate dose of 2 μg was selected for future mouse studies. Because disease progression and granuloma formation in M. tuberculosis–infected guinea pigs better mimic features of human TB pathology, we also tested the H64 vaccine in Hartley guinea pigs in a long-term infection model. Guinea pigs were challenged with a low dose of virulent M. tuberculosis H37Rv after vaccination with different doses of H64. Animals that reached predefined human end points (weight loss or impact on respiratory rate) were euthanized. Twenty-two weeks after being infected, all animals in the saline control group had been euthanized with a mean survival time of 16.2 wk (SD = ±1.8) (Supplemental Fig. 1A). In comparison, the mean survival time of the M. bovis BCG-vaccinated guinea pigs was 65.1 wk (±8.9). In the four H64-vaccinated groups, the mean survival time ranged from 22.4 wk (±2.3) to 41.6 wk (±9.0) (Fig. 1C). Statistical comparison confirmed that all vaccination groups were better protected than saline-vaccinated animals (p < 0.02, log-rank test). After having confirmed that the ESX-1–associated Ag combination was protective in both mice and guinea pigs, we continued our study of the H64 vaccine by testing its protective efficacy against different challenge strains. Because M. tuberculosis strains harbor genetic diversity that translates into significant differences in Ag diversity, immunogenicity, and virulence, we selected four clinically relevant M. tuberculosis strains belonging to different lineages (2–4) to ensure that the protective signal of H64 was robust and broadly relevant (Fig. 1D, Supplemental Fig. 1B) (32). Similarly to the results with M. tuberculosis Erdman in Fig. 1C, H64 vaccination induced significant protection against all four strains (p < 0.05 or lower) and was equal to or better than the protection obtained with the H56 subunit vaccine that was included to benchmark the new vaccine. In the experiment with H37Rv, H64 was more protective than BCG, but with the other clinical strains, BCG induced similar or better protection than H64 (Fig. 1D). To test how the vaccine performed against a more “aggressive” strain, we challenged mice with M. tuberculosis HN878, which is regarded as hypervirulent because of its rapid growth and induction of severe lung inflammation in mice (33). In this model, both BCG and H64 protected efficiently at week 4 of the infection (p < 0.001), but by week 12, BCG had lost most of its protection, whereas bacterial numbers in H64-vaccinated animals remained significantly lower than BCG as well as the saline control (Fig. 1E, p < 0.005 and p < 0.0001, respectively). View inlineView popup Table I. M. tuberculosis Ags in the H64 fusion protein FIGURE 1. H64 (ESX-1–associated Ags) provide protection against M. tuberculosis in mice and guinea pigs. (A) Illustration of the subunit vaccine H64. The fusion protein is based on ESX-1–associated Ags and does not share Ags with M. bovis BCG. The figure is not drawn to scale. The m.w. of the individual Ags is given in Table I. (B) Ag recognition of splenocytes after immunizing CB6F1 mice with H64 (n = 3). Single-cell cytokine expression was measured by flow cytometry. Any CD4 cell that produced either IFN-γ, TNF-α, and/or IL-2 in response to Ag stimulation was taken as Ag specific. The spleen cells were stimulated with single Ags from H64. EsxH stimulation was included as a negative control (“Control”). Bars and lines illustrate the mean and SD for each Ag. (C) Black curve: protective efficacy studies in CB6F1 mice. Animals were immunized with different doses of H64 in CAF01 adjuvant. The bacterial load was measured in lungs from individual mice 6 wk after M. tuberculosis Erdman challenge (n = 8). The number of bacteria was logarithmic transformed and subtracted from the bacteria numbers in a nonvaccinated control group. Blue curve: protective efficacy studies in guinea pigs (performed at Colorado State University). Guinea pigs were immunized with different doses of H64 in CAF01 and euthanized when predefined humane end points were met after M. tuberculosis infection. Kaplan–Meier survival curves (Supplemental Fig. 1A) were used to estimate the mean survival time for guinea pigs in each of the vaccination groups (n = 10). SDs are shown for each data point. (D) CB6F1 mice immunized with H64, H56, or M. bovis BCG or injected with saline were infected for 6 wk with one of four clinical isolates of M. tuberculosis: H37Rv, Vietnam, Nepal, and Kazakhstan (n = 6–8 per group). MIRU typing in Supplemental Fig. 1B. CFU Log10/lung ± SEM. One-way ANOVA was used for statistical comparison with the saline group for each strain; degree of freedom = 24. (E) H64 or M. bovis BCG immunized or saline-injected C57BL/6 mice were infected 6 wk after immunization with the hypervirulent M. tuberculosis strain Beijing HN878 (performed at Yonsei College of Medicine). After 4- and 12-wk infection, the bacterial burden was measured in the lung (n = 5–8). Mean values and SEMs are illustrated. One-way ANOVA was used for statistical comparison between groups for each time point; degree of freedom = 18. *p < 0.05, **p < 0.01, ***p < 0.001, ****p < 0.0001. In parallel to working with H64, we designed an additional ESX-1 fusion protein in which EspF and PE35 (not immunogenic in H64) were replaced with the Ags EspB and EspA to potentially optimize immunogenicity and/or efficacy (Fig. 2A, Table II). In H74-vaccinated animals, there was a dominant CD4 T cell response to EspB and an increased recognition of EsxA and EspD (Fig. 2B). Similar to H64, H74 induced protective efficacy over a broad range of vaccination doses peaking between 1 and 5 μg (Supplemental Fig. 1C). Because both vaccines were designed to be used in BCG-primed animals, we did a direct head-to-head comparison in this setting. After challenge with M. tuberculosis Erdman, both vaccines induced robust protection on top of BCG at all the measured time points (Fig. 2C). However, at the late time point (20 wk postinfection), lung bacterial numbers were reduced by 1.7 log10 in the BCG control group (p < 0.0001), 1.88 log10 in the BCG-H64–vaccinated group, and 2.22 log10 in the BCG-H74–vaccinated group compared with the saline group. The bacterial burden was thus significantly lower in the H74-vaccinated animals (p < 0.01), and H74 was selected as the ESX-1 vaccine for further studies. FIGURE 2. Improved Ag recognition and protection of H74 compared with H64. (A) Illustration of the subunit vaccine H74. The fusion protein is based on ESX-1–associated Ags. Ags shared with H64 are in light green. The length in amino acids of the individual Ags is given in Table I. (B) Ag recognition of splenocytes isolated from H74-immunized CB6F1 mice (n = 4). The cells were stimulated with single Ags from H74, and EsxH stimulation was included as negative control (Control). CD4 T cells producing either IFN-γ, TNF-α, and/or IL-2 in response to Ag stimulation were taken as Ag specific. Means and SDs are shown for each Ag. (C) Six months after being M. bovis BCG–vaccinated, CB6F1 mice were divided into three groups and vaccinated with either H64 or H74 or saline injected. An age-matched control group was included that did not receive any of the vaccines. All animals were aerosol infected with M. tuberculosis Erdman, and the number of mycobacteria was measured in individual lungs from immunized and nonimmunized mice 6, 12, and 20 wk postinfection (n = 8 per time point). Vertical lines illustrate SEMs. One-way ANOVA was used for statistical comparison between groups at the late time point; degree of freedom = 28. **p < 0.01, ****p < 0.0001. View inlineView popup Table II. M. tuberculosis Ags in the H74 fusion protein In summary, we designed two novel vaccines based exclusively on ESX-1–associated Ags H64 and H74 which demonstrated robust protection in both mice and guinea pigs. H74 was selected for further studies in BCG-primed animals. In BCG-vaccinated mice, ESX-1–associated Ags induce less differentiated CD4 T cells and improve protection compared with BCG boosting It has been demonstrated that BCG vaccination induces highly differentiated T cells (34), but it has not been systematically investigated how this influences T cell quality and protection of subsequent subunit vaccine boosters. We approached this issue by first comparing the protective efficacy of the ESX-1–based H74 vaccine and a BCG booster vaccine (H65), described in a previous study (21). H65 consists of six EsxA family proteins related to ESX-2, -3, or -5 that are all present in BCG (Fig. 3A). Naive mice were immunized with either H65 or H74 as standalone vaccines. Six weeks after M. tuberculosis aerosol challenge, both vaccines reduced the bacterial load by more than 1.0 log10 relative to nonvaccinated animals (p < 0.0001) with no statistical difference between them (Fig. 3B). Having confirmed that the two vaccines induced similar levels of protection in naive mice, we continued by comparing their efficacy in mice that were BCG primed 6 mo prior to subunit vaccination. Twelve weeks after M. tuberculosis Erdman challenge, BCG vaccination reduced the lung bacterial number by 0.85 log10 (p < 0.05). In two separate experiments, H65 boosting did not add significantly to this protection (Fig. 3C, top, Supplemental Fig. 2A), whereas vaccination with the H74 vaccine enhanced the BCG-induced protection (p < 0.05), resulting in a 1.78 log10 reduction of the number of bacteria relative to the nonvaccinated group (p < 0.0001). This observation was robust as similar results were found in a second study with the clinical strain M. tuberculosis Kazakhstan (Fig. 3C, bottom), showing consistently that although the protection was equal in naive mice, the ESX-1 vaccine (M. tuberculosis–specific) induced better protection than the BCG boosting vaccine in BCG-primed animals. FIGURE 3. H74 vaccination (ESX-1–associated Ags) improve protection in BCG-primed animals and induce less differentiated CD4 T cells compared with BCG boosting (H65). (A) Illustration of the BCG booster vaccine H65. All six Ags are shared with M. bovis BCG (21). (B) Groups of naive CB6F1 mice were vaccinated with H74 or H65, and control groups received either a BCG vaccination or saline injections (n = 8). The bacterial numbers were enumerated in lungs 6 wk after an aerosol M. tuberculosis Erdman infection. Means and SEMs are shown by bars and lines. One-way ANOVA was used for statistical analysis; degree of freedom = 27. (C) CB6F1 mice were BCG vaccinated followed by a resting period of 6 mo before being vaccinated with either H74 or H65 (n = 7–8). The bacterial numbers were measured in individual animals 12 wk after they were infected with M. tuberculosis strain Erdman (top) or 25 wk after M. tuberculosis Kazakhstan infection (bottom). One-way ANOVA was used for statistical analysis; degree of freedom = 25 and 26. (D) Timeline for measuring T cell responses in vaccinated CB6F1 mice pre– and post–M. tuberculosis Erdman challenge in the BCG prime–boost model. (E) Splenocytes isolated from CB6F1 mice vaccinated with BCG alone or boosted with H65 were stimulated with the H65 fusion protein. In parallel, splenocytes from BCG-vaccinated animals complemented with H74 were stimulated with the H74 fusion protein. Single-cell expression of cytokine IFN-γ, TNF-α, and IL-2 was measured by flow cytometry, and the frequencies of activated (CD44high) CD4 T cells expressing any of the possible combinations of cytokines are shown in a bar plot for each vaccination group with mean and SD indicated (n = 3). Means (gray bars) and SDs (vertical lines) are shown. The pies are a simplified view of the data illustrating cytokine coexpression patterns of the specific CD4 T cells. The five identified subgroups of cytokine-producing CD4 T cells were as follows: light blue, TNF-α+; dark blue, TNF-α+ and IL-2+; green, TNF-α+, IL-2+, and IFN-γ+; orange, IFN-γ+ and TNF-α+; and red, IFN-γ+. The dotted arches illustrate the fraction of specific CD4 T cells that produced IFN-γ (red) or did not produce cytokine IFN-γ (blue) in response to ex vivo Ag stimulation. The FDS was calculated as the ratio of IFN-γ producers/IFN-γ nonproducers as previously described (6). (F) Cytokine expression profiles were measured in spleens before and in lungs after M. tuberculosis Erdman infection, and the associated FDS score was calculated for each time point and vaccination group (n = 3–4 per time point). Filled circles and vertical bars represents means and SDs. **p < 0.01, ***p < 0.001, ****p < 0.0001. Next, we compared the phenotype of the subunit-specific CD4 T cell response among the vaccinated groups before and after M. tuberculosis challenge (Fig. 3D). We used the individual CD4 T cell cytokine expression profile as a specific and sensitive measure to assess the degree of differentiation (35). For each group, we calculated a simple functional differentiation score (FDS) based on the ratio of IFN-γ producers and nonproducers as has previously been suggested (6). In BCG-vaccinated animals, we found the highest degree of T cell differentiation (FDS = 4.0) with the majority of responding CD4 T cells expressing IFN-γ either alone or in combination with TNF-α and/or IL-2 (Fig. 3E, top). In the H65-boosted group, there was almost a 3-fold increase in the percentage of H65-specific CD4 T cells compared with BCG alone, but H65 boosting induced only minor changes in the cytokine expression profile of the CD4 T cells (FDS = 2.8, Fig. 3E, middle). In contrast, H74 vaccination induced CD4 T cells with a lower degree of differentiation with almost half of the responding T cells expressing TNF-α alone or TNF-α and IL-2 in combination (FDS = 1.0, Fig. 3E, bottom). After M. tuberculosis Erdman infection, the CD4 T cells recruited to the lung maintained an FDS score of ∼ 4.0 in BCG-vaccinated mice during the initial phase of the infection. However, this increased to 10.7 after 6 wk and to 26.1 after 12 wk of infection, clearly showing a further differentiation of the T cell pool during TB infection (Fig. 3F, top). In the H65-boosted group, there was a delay in the differentiation of the CD4 T cells, but at the late time point, the FDS score had increased to 12.8 (Fig. 3F, middle). In contrast, the FDS score for the vaccine-specific CD4 T cells remained around ∼1.0 for all time points in the H74-vaccinated group (Fig. 3F, bottom). Thus, the pool of H74-specific CD4 T cells effectively resisted infection-driven differentiation throughout a 12-wk infection period. We further investigated this in a follow-up study, in which BCG-primed animals were immunized simultaneously with H74 and H65 so that each animal served as its own internal control. In these animals, the H65-specific CD4 T cells had a mean FDS of 3.0 compared with 0.84 for the H74-specific CD4 T cells, confirming that BCG boosting leads to higher T cell differentiation than vaccination with M. tuberculosis–specific Ags (Supplemental Fig. 2B). Finally, ESAT-6 has been shown to be essential for postexposure protection (16), and of relevance to the vaccination of M. tuberculosis–exposed individuals, H74 vaccination induced less differentiated T cells and lower bacterial burdens in the modified Cornell model of latent TB infection, supporting ESX-1–based vaccines for this application (27, 36) (Supplemental Fig. 2C). In summary, in BCG-primed mice, H65 vaccination did neither lead to substantial improvements in T cell differentiation nor did it add significantly to the protection induced by BCG. Conversely, vaccination with ESX-1–associated Ags (H74) induced CD4 T cells with a low differentiation score, which remained low during M. tuberculosis infection. This correlated with a significantly increased protective efficacy. In BCG-vaccinated mice, ESX-1–associated Ags induce CD4 T cells with superior lung-homing capacity Recent studies directly link T cell differentiation status to the ability to enter the infected lung parenchyma and restrict mycobacterial growth (7, 9, 15, 37). In H56/CAF01-vaccinated mice, we have previously shown that lung parenchymal CD4 T cells (protected from anti-CD45 i.v. stain) are less differentiated and express increased levels of the parenchymal homing marker, CXCR3 (15). For this study, to directly link FDS with lung parenchymal trafficking, we first confirmed that there was a strong correlation between FDS and i.v. CD45 labeling in vaccinated animals (Supplemental Fig. 3). Because our data this far showed that pre-existing BCG immunity had a major influence on the differentiation status of subunit-specific CD4 T cells, we next investigated the impact of BCG boosting on lung-homing capacity. For this, we performed an adoptive transfer experiment using donor cells from H74- and H65-vaccinated mice with or without BCG priming. Before cell transfer, we confirmed that all four groups had a solid vaccine-specific CD4 T cell response and used the cytokine expression profiles to determine the degree of CD4 T cell differentiation (Fig. 4A, 4B). Importantly, the T cell differentiation was similar after H74 and H65 vaccination when administered as standalone vaccines, confirming there was no inherent difference in the priming capability of these vaccines. However, in BCG-primed mice, H65 boosting led to a higher T cell differentiation than H74 vaccination, as previously observed (Fig. 4B). FIGURE 4. H74 (ESX-1–associated Ags) induces CD4 T cells with superior lung-homing capacity in BCG-vaccinated mice. (A) Eight weeks after being BCG vaccinated, CB6F1 mice were vaccinated with H65 or H74. Three weeks later, splenocytes were stimulated with H65 or H74 fusion protein, and the expression of cytokines IFN-γ, IL-2, and TNF-α was measured by flow cytometry. CD4 T cells that produced at least one of the cytokines in response to Ag stimulation was regarded as “Ag specific” (n = 4 per group). The mean (gray bar) and SD is shown for each group. (B) The FDS score was calculated as the ratio of IFN-γ+/IFN-γ− cells based on the cytokine expression profile for the individual animal and plotted for each of the four vaccination groups. Horizontal lines represent means, vertical lines, and SDs. One-way ANOVA was used for statistical comparison; degree of freedom = 12. (C) The influence of BCG priming on the lung-homing capacity of H65- and H74-induced CD4 T cells. CD4 T cells were purified from spleens and lymph nodes and pooled within the vaccination groups before labeling with tracker dyes to distinguish cells from donor animals with and without BCG priming. After labeling, cells were mixed 1:1 (e.g., naive plus H65:BCG plus H65) and adoptively transferred to M. tuberculosis Erdman–infected mice. The next day, intravascular localized cells in the recipient mice were labeled using FITC CD45.2, and purified lung cells were stimulated with fusion proteins to identify cytokine expressing (“Ag-specific”) CD4 T cells. For the entire gating strategy, see Supplemental Fig. 4. (D) For each of the four vaccination groups, the percentage of vaccine-specific donor cells entering into the lung parenchyma was calculated, and the influence of BCG priming on vaccine-specific homing was compared for the two subunit vaccines. The lines connect measurements from the same recipient mouse (n = 4). The statistical comparison was done by two-tailed t tests. *p < 0.05. To compare the ability of the vaccine-specific CD4 T cells to enter infected lung parenchyma, we transferred mixed populations of CD4 T cells into M. tuberculosis–infected recipients. Donor CD4 T cells from the four vaccination groups were isolated by negative selection from spleens and inguinal lymph nodes and stained either with Cell Proliferation Dye eFluor 450 or Cell Proliferation Dye eFluor 670 to distinguish cells from BCG-primed animals and cells from animals receiving the subunit vaccine as a standalone. Stained cells were mixed in a ∼1:1 ratio (subunit:BCG prime plus subunit) and cotransferred into M. tuberculosis Erdman–infected recipients in a total 5 × 106 donor CD4 T cells per recipient. Eighteen hours after transfer, recipient mice were injected with FITC-labeled anti-CD45.2 for intravascular labeling, and lung cells were harvested for flow cytometric analysis based on CDP450/670 as well as cytokine staining following H65/H74 stimulation (Fig. 4C, Supplemental Fig. 4). In mice receiving H65-specific cells, only 39.6–72.0% (mean 64%) of the cells from the BCG-H65–boosted donor mice were located in the lung parenchyma, whereas the range was 79.3–99.4% (mean 90%) for donor cells from H65-only vaccinated mice (Fig. 4D). In contrast, we found no significant differences in the percentage of H74-specific CD4 T cells in the parenchyma regardless of whether the cells came from H74 only or BCG-H74–vaccinated animals (range 78.0–99.4 and 72.0–99.4%, respectively, with means of 85.0 and 84.2%). These results clearly demonstrate that pre-existing BCG immunity significantly impacts the functionality of the T cells induced by subunit booster vaccines and that this mechanism can be efficiently bypassed by designing vaccines that selectively incorporate BCG-complementing TB Ags. Discussion The capacity of CD4 T cells to protect against M. tuberculosis is governed by their differentiation state and ability to localize to the site of infection (37). M. bovis BCG vaccination primes a polyfunctional CD4 T cell response that differentiates over time and gradually loses the ability to produce IL-2, proliferate, and to localize to the site of infection, which results in a loss of long-term protective efficacy (11–13). Heterologous prime–boost strategies, in which BCG vaccination is followed by a subunit vaccine boost, are aiming at improving the BCG-induced adaptive immunity in terms of magnitude, durability, and quality of the CD4 T cell response (38). In this study, we tested whether pre-existing BCG immunity impacts the vaccine response of either a “traditional” BCG booster vaccine (H65) or a complementary vaccine based on ESX-1–associated Ags that are specific for M. tuberculosis (H74 and H64, referred to collectively as “ESX-1 vaccines”). In the initial characterization of the ESX-1 vaccines, we demonstrated significant long-term protection in M. tuberculosis H37Rv–challenged guinea pigs as well as M. tuberculosis Erdman–challenged mice. To extend the study beyond the conventional laboratory M. tuberculosis strains, we challenged vaccinated mice with four different strains of M. tuberculosis belonging to three phylogenetically different lineages. The ESX-1 vaccine induced significant protection against all four strains, suggesting that the vaccine will be effective against a broad range of clinical isolates. Two of the selected isolates were part of the W-Beijing family of M. tuberculosis strains, one of them being the hypervirulent M. tuberculosis Beijing HN878. The Beijing strains are particularly relevant to include in this screening as they are highly prevalent, overrepresented among drug-resistant isolates (39), and significantly associated with HIV coinfection in human cases of TB meningitis (40). In a conventional protection readout at 4 wk postinfection, both the ESX-1 vaccine and BCG were highly protective against M. tuberculosis Beijing HN878. This was also true at the later time point for the ESX-1 vaccine, but in line with earlier studies (27, 41), BCG’s protective efficacy waned at the later stage of infection. In the prime–boost model, our data indicates that BCG vaccination has a major influence on the immune responses induced by subsequent subunit vaccines, depending on whether the Ags are shared with BCG or not. Specifically, we observed that boosting BCG with H65 only marginally changed the specific CD4 T cell differentiation status with little or no improvement of the protection. In contrast, BCG priming had minimal influence on the differentiation and functionality of CD4 T cells induced by the ESX-1 vaccine (not sharing Ags with BCG). The ESX-1 vaccine–specific T cells retained their differentiation status after M. tuberculosis infection, and their ability to enter the infected lung parenchyma was increased compared with the T cells in the H65-boosted group. As a result, the ESX-1 vaccine significantly augmented an already strong BCG-induced protection, and we obtained 1.8–2.9 log10 reduction in the lung bacterial load. Importantly, the BCG-priming vaccine was administered more than 6 mo prior to subunit vaccination, suggesting that it was the BCG “T cell imprint,” rather than ongoing bacterial multiplication, that influenced the response of the subunit booster vaccine. In other words, the BCG-specific CD4 T cells appeared to be “locked” with minimal capacity for reprograming into potentially more favorable phenotypes 6 mo later. This is likely because highly differentiated Th1 cells exhibit limited functional plasticity (42, 43) and that subunit boosting merely expands the existing pool (or a subset) of BCG-imprinted CD4 T cells. In addition, BCG may also induce a specific regulatory T cell response that could influence booster vaccines, although this was not investigated in this study (44, 45). Regardless, de novo priming of CD4 T cells using ESX-1–associated (or other M. tuberculosis–specific) Ags bypass this issue, which could be a useful strategy to increase durable protection in BCG-vaccinated populations. A limitation of this study was a lack of specific homing-related makers in the analysis, and in future studies, it will be important to establish whether vaccine-induced reduction of T cell differentiation leads to increased expression of such markers and/or increased contact between Ag-specific CD4 T cells and M. tuberculosis–infected macrophages in the lung. The mouse model has been extensively used to evaluate new prime–boost strategies using M. bovis BCG and subunit vaccines. The results have varied from no additional protection to almost 2 log10 protection compared with the BCG control group (46–48). It is difficult to do a comparative evaluation of these results as the studies differ with regard to vaccine design, mouse strain, M. tuberculosis challenge strain, BCG strain, and dose as well as the interval between prime–boost, boost–challenge, and challenge–sacrifice. However, by evaluating eight different available studies with BCG booster vaccines, we observed that the added protection of BCG boosting only was significant when the BCG-induced protection in itself was low (<0.5 log10) (47, 49–55). In light of our results, one explanation for this could be that a poor BCG vaccine take (or a waning response) will open up for better priming of less differentiated T cell response by the subunit vaccine. In humans, BCG will in most cases be administered to infants, and future booster vaccines are intended to be administered 10–15 y later and preferably before the protective efficacy of BCG wanes. It is not clear how pre-existing BCG immunity will influence subunit vaccination in this setting, and exposure to M. tuberculosis is also likely to play a dominant role in high-endemic areas. In this regard, results demonstrating that subunit vaccines can build on pre-existing M. tuberculosis immunity have been obtained in the recent phase IIb trial, in which M72/AS01e induced 49.7% vaccine efficacy against pulmonary disease in quantiferon positive individuals after 3 y of follow-up (56). Encouragingly, in this study, we also demonstrate that H74 vaccination significantly reduced bacterial burden in the modified Cornell model of postexposure vaccination. Similarly, regarding BCG-vaccinated quantiferon negative individuals, a recent study showed that it is possible to boost BCG protection with a subunit vaccine in adolescents and adults to some extent (57). In this study, H4:IC31 boosting led to 30.1% vaccine efficacy against sustained quantiferon conversion, and based on our data, we speculate that subunit vaccines with ESX-1–associated Ags have the potential to further improve on this result. Additionally, in the study by Nemes et al., BCG revaccination showed a vaccine efficacy of 40.5%, which has sparked renewed interest in using BCG revaccination as a readily applicable intervention (58). In such settings, the influence of recent “BCG imprinting” is likely to be significantly higher if BCG revaccination is to be combined with future subunit vaccines. In conclusion, mycobacterial priming by BCG vaccination induces highly differentiated CD4 T cells that, for at least 6 mo in the mouse model, restrict subsequent booster vaccines in priming additional protective T cells with sufficient memory and lung-homing potential. This phenomenon can efficiently be bypassed by designing vaccines with M. tuberculosis–specific Ags, like the ESX-1–associated Ags studied in this report. We suggest that future studies explore these findings in the human setting, in which it could also be investigated whether exposure to non-tuberculousis mycobacteria play a role in maintaining BCG immunity/T cell “imprint.” Disclosures C.A., N.P.H.K., I.S., E.H.K., T.L., E.M.A., M.R., I.R., P.A., and R.M. are employed by Statens Serum Institut, a nonprofit government research facility of which H56, H64, and H74 and the CAF01 adjuvant are proprietary products. C.A., P.A., and R.M. are coinventors of patents covering ESX-1–based vaccines. Acknowledgments We thank Joshua Woodworth for input on data interpretation and gratefully acknowledge Vivi Andersen and Camilla Rasmussen at Statens Serum Institut for excellent technical assistance. Footnotes This work was supported by The Danish Research Council (DFF - 7016-00310), the National Institutes of Health/National Institute of Allergy and Infectious Diseases (Grant 1R01AI135721-01), the European Union’s Horizon 2020 Framework Programme for Research and Innovation under Grant Agreement 643381 as part of the TBVAC2020 Consortium, and the National Institutes of Health/National Institute of Allergy and Infectious Diseases program Advanced Small Animal Models for the Testing of Candidate Therapeutic and Preventative Interventions against Mycobacteria (HHSN272201000009I-003, Task Order 12) at Colorado State University. The online version of this article contains supplemental material. 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Fungi cover epithelial surfaces of the human body, engaging in many mutualistic interactions with the host and other microbiota such as the more prevalent bacteria. These interactions are shaped by multiple factors, including host physiology and immunity, as well as nutrient competition. The beneficial effects of fungal colonization for hosts include resistance to pathogens and tuning of the immune system. Although health benefits continue to be explored, recent studies have revealed expanded roles of fungi in human disease, including inflammatory disorders and specific cancers. The global burden of fungal infections is also expanding, with increased numbers of at-risk patients and increased resistance to limited antifungal drugs. More fungal research is needed to overcome these unmet needs. Fungi exist as single-celled yeast, multicellular molds, or dimorphic species occurring as both yeast and filamentous cells. Saccharomyces cerevisiae, Cryptococcus neoformans, and Candida and Malassezia spp. are frequently studied yeast, whereas Penicillium, Mucor, and Aspergillus are well-known molds. As with many microbiota, fungi are classically recognized for their roles as human-associated pathogens. Candidal bloodstream infections are the most common form of fungal invasive disease, affecting about 1 in 10,000 people in the United States. Globally, cryptococcal meningitis contributes to a substantial burden of disease, particularly in HIV-positive individuals. The paucity of available antifungal treatments contributes to the morbidity and mortality of fungal infections. Classes of antifungals include azoles (e.g., fluconazole), echinocandins, and amphotericin B. However, fluconazole is the only antifungal drug available in many parts of the world. Additionally, some fungal diseases can be difficult to diagnose because of nonspecific patient symptoms, invasive tissue sampling, specific culture conditions, and identification requiring sophisticated techniques. Recent studies have begun to explore how fungi are multifaceted in their potential to lead to beneficial as well as pathogenic outcomes for the host. Commensalism in the context of human fungi is exemplified by colonization resistance against pathogens. An example of a beneficial effect is the dominant human skin–associated Malassezia, which have adapted to their niche by making use of skin lipids as a nutrient, and then secreting antimicrobial products that deter bacterial pathogens (1). Another example of the importance of colonization resistance is Candida albicans commensalism in the gastrointestinal tract. In an evolutionary experiment, C. albicans strains acquired genetic mutations that enabled them to more stably colonize the mouse gastrointestinal tract. These evolved C. albicans strains provided protection against subsequent experimental challenges with different virulent fungi (C. albicans, Aspergillus fumigatus) and bacteria (Staphylococcus aureus, Pseudomonas aeruginosa) (2). However, these C. albicans strains evolved only in antibiotic-treated mice and were unable to stably colonize mice with endogenous gut bacteria, highlighting the genetic trade-offs of adaptation to the host and competition within mixed microbial communities. Complementary studies demonstrated that mutations in transcription factors that regulate morphology are key determinants of the gut commensal fitness of C. albicans (3). In addition to these direct host-microbial interactions, mouse gut colonization with C. albicans tuned host immunity, resulting in a systemic increase in fungal-specific T helper 17 (TH17) CD4+ T cells and interleukin-17 (IL-17)–responsive circulating neutrophils, which protected against more invasive bacterial and fungal, but not viral, infections (4). Ex vivo experiments showed that C. albicans elicited robust IL-17A and IL-22 responses from peripheral C. albicans– and A. fumigatus–specific TH17 CD4+ T cells from healthy human donors, demonstrating that C. albicans can modulate human immunity as well (5). Given the complexity of host-microbial interactions, any alteration in the host or microbiota can result in infections, ranging from chronic chromoblastomycosis of the skin, dermatophyte nail infections, and acute vaginal yeast infections to potentially fatal mucormycosis in diabetics, candidal sepsis, and disseminated aspergillosis. Deficiencies in human immunity provide insight into the host-microbiota interplay. For example, patients with advanced HIV infections suffer from specific opportunistic fungal infections such as cryptococcal meningitis, mucosal candidiasis, and Pneumocystis jirovecii pneumonia. In patients receiving a hematopoietic stem cell transplant, candidal bloodstream infections were preceded by blooms of intestinal Candida spp. with altered bacterial communities, which could be used as biomarkers to identify and alter medical management (6). Additionally, the specificity of host-fungal immune interactions is reflected in patients with genetically defined primary immunodeficiency syndromes such as chronic granulomatous disease, autoimmune polyendocrinopathy–candidiasis–ectodermal dystrophy (APECED), or caspase recruitment domain–containing protein 9 (CARD9) deficiency, each of which renders patients susceptible to a specific fungal infection. Other examples of host-specific fungal susceptibilities include mice deficient in the chemokine (C-X-C motif ) receptor 1 (Cxcr1) gene, which have defective neutrophil killing of Candida, decreased survival, and higher fungal burden. This phenotype is similar to that of disseminated candidiasis patients and healthy donors with the CXCR1-T276 allele who also demonstrate impaired neutrophil killing of Candida (7). Recurrent vulvovaginal candidiasis, a localized fungal infection, is estimated to affect more than 100 million women worldwide annually and has been linked with a functional variant in the SIGLEC15 (sialic acid–binding immunoglobulin-like lectin 15) gene (8). Expressed on immune cells, SIGLEC15 can bind C. albicans and induces IL-17A and interferon-γ (IFN-γ) production, suggesting a role in anti–C. albicans immune responses. Host susceptibility contributes to the development of more persistent or severe fungal infections—for example, from dermatophytes or penetrating wounds. Studies of other single-nucleotide polymorphism (SNP) variants in immune-related genes that correlate with increased susceptibility to mucosal or life-threatening fungal infections hold promise for the future development of precision medicine approaches for risk stratification and preventive treatment of patients at the highest risk for fungal disease. Inflammatory and autoimmune diseases are increasingly linked to alterations in fungal communities, particularly in genetically defined hosts. SNPs in CARD9 and CLEC7A (C-type lectin domain–containing 7A), which encodes Dectin-1, have been associated with inflammatory bowel diseases in humans. Dectin-1 is a C-type lectin receptor (CLR) that recognizes β-glucan in fungal cell walls and, through CARD9, signals to induce inflammatory mediators and TH1 and TH17 cell differentiation. Mice deficient in Dectin-1 had more severe experimentally induced colitis with increased C. tropicalis burden, and a SNP in human CLEC7A is associated with more severe ulcerative colitis (9). Similarly, Crohn's disease patients have higher relative abundances of intestinal Malassezia compared with healthy controls, and oral gavage of Malassezia demonstrated worsening of experimental colitis in mice, again through activation of CARD9 signaling and downstream TH1 and TH17 cell polarization (10). Genetic ablation of CX3CR1+ mononuclear phagocytes, which express antifungal CLRs, also exacerbated experimental colitis in mice. Furthermore, a missense mutation in CX3CR1 in Crohn's disease patients has been associated with reduced immunoglobulin G (IgG) responses to fungi (11). These and other studies suggest that inflammatory diseases may result from host-fungal imbalances. Although bacteria and viruses have been implicated in cancer, fungi typically have not been. Histologic observations revealed higher amounts of intratumoral fungi, particularly of Malassezia, infiltrating human pancreatic ductal adenocarcinomas (PDAs). Further investigation of mouse models of PDA demonstrated fungal translocation from the intestinal tract into the pancreas, increased burden of Malassezia accelerated PDA progression, and antifungal treatment slowed pancreatic cancer growth (12). The complement cascade integrates immune recognition and fungal killing with tumor development by stimulating proinflammatory pathways. Human tissue expression of mannose-binding lectin (MBL), which activates the complement cascade, was associated with worse survival in PDA patients. Similarly, PDA progression in mice depended on Malassezia stimulation of MBL, linking fungi, inflammation, and tumorigenesis. This study has prompted researchers to reconsider the potential relationships between fungi and broader human diseases. Candida auris epitomizes the gravest concerns about an emerging fungal pathogen because it has evolved resistance to all classes of antifungal drugs, particularly azoles. Numerous countries have reported active outbreaks, with increasing cases of C. auris bloodstream infections. The high prevalence of resistance renders these infections difficult to treat, with resultant high mortality. Over the past decade, four distinct strains of C. auris have emerged independently on different continents. The origin of C. auris as a human pathogen has remained a mystery since it was first identified in 2009. The propensity of C. auris to colonize human skin for a long time, which is an atypical feature for non-auris Candida species, is of substantial concern because shedding from patients into the environment facilitates transmissions within health care facilities (13). The emergence of a new human fungal pathogen points to urgent unmet medical needs for new antifungal drugs and environmental disinfectants, genomic datasets that include fungal sequences to map global fungal diversity, and a coordinated global health response. Aspergillus spores are frequently inhaled into lungs but cause disease only in some people. PHOTO: THE NATURAL HISTORY MUSEUM, LONDON/SCIENCE SOURCE Investigations into the role of fungi in human health and disease are challenging. Despite a myriad of bacteria, fungi, and viruses existing together in and on humans, researchers tend to focus on a few microbial species because they are more tractable to study. Diverse culture conditions or inclusion of metabolically distinct forms of dimorphic fungi (3) may reveal different functions and interactions. In vivo systems also have limitations. For example, conventional laboratory mice have a lower fungal burden and different immune profiles than those of wild-type mice (14). Additionally, adaptation to stress—induced by, for example, culture conditions, passaging through mammalian hosts, antifungal pressures, high temperatures, or acidic pH—can lead to alterations in morphology, fungal capsule, and cell wall components. This can result in evasion or triggering of host immunity and radically altered genomes in fungal cells. Genomic plasticity in fungi, including loss of heterozygosity, copy number variation, and aneuploidy, underscores the importance of incorporating metagenomic analyses into studies of fungal community adaptation to different niches (15). Fungal research is an area of considerable potential. This includes understanding how fungi are beneficial to human health and mining the multiple compounds produced by fungi that may benefit clinical medicine (for example, penicillin is derived from the fungal species Penicillium spp.). The emergence of multidrug-resistant C. auris has been postulated to be due in part to rising temperatures and to the widespread use of azoles in agriculture and in the clinic. Because these pressures on host-microbial homeostasis are likely to persist and evolve, the development of new antifungal drugs is critical to counteract outbreaks from existing and future pathogens. Advances in technology, such as targeted CRISPR-Cas9–mediated gene deletion for fungal mutagenesis, can provide precise tools for testing genetic hypotheses and elucidating fungal pathophysiology. Further advances will continue to improve our understanding of how fungi affect human health and disease. http://www.sciencemag.org/about/science-licenses-journal-article-reuse This is an article distributed under the terms of the Science Journals Default License. References and Notes ↵ G. Wu et al., PLOS Genet. 11, e1005614 (2015).OpenUrlCrossRefPubMed ↵ G. H. W. Tso et al., Science 362, 589 (2018). ↵ J. N. 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Significance Functional loss of gut barrier integrity with subsequent increased antigen trafficking and occurrence of low-grade intestinal inflammation precede the onset of type 1 diabetes (T1D) in patients and preclinical models, thus suggesting that these events are mechanistically linked to the autoimmune pathogenesis of the disease. However, a causal relationship between increased intestinal permeability and autoimmune diabetes was never demonstrated. Our data show that breakage of gut barrier continuity leads to activation of islet-reactive T cells in the intestine, thus triggering autoimmune diabetes. An important implication of our findings is that restoration of a healthy gut barrier through microbiota and diet modulation in diabetes-prone individuals could reduce intestinal activation of islet-reactive T cells and prevent T1D occurrence. Abstract Low-grade intestinal inflammation and alterations of gut barrier integrity are found in patients affected by extraintestinal autoimmune diseases such as type 1 diabetes (T1D), but a direct causal link between enteropathy and triggering of autoimmunity is yet to be established. Here, we found that onset of autoimmunity in preclinical models of T1D is associated with alterations of the mucus layer structure and loss of gut barrier integrity. Importantly, we showed that breakage of the gut barrier integrity in BDC2.5XNOD mice carrying a transgenic T cell receptor (TCR) specific for a beta cell autoantigen leads to activation of islet-reactive T cells within the gut mucosa and onset of T1D. The intestinal activation of islet-reactive T cells requires the presence of gut microbiota and is abolished when mice are depleted of endogenous commensal microbiota by antibiotic treatment. Our results indicate that loss of gut barrier continuity can lead to activation of islet-specific T cells within the intestinal mucosa and to autoimmune diabetes and provide a strong rationale to design innovative therapeutic interventions in “at-risk” individuals aimed at restoring gut barrier integrity to prevent T1D occurrence. Footnotes ↵1To whom correspondence may be addressed. Email: falcone.marika{at}hsr.it. Author contributions: M.F. designed research; C.S., I.C., M.L.C., L.D.G., F.F., R.L., M.R., and R.F. performed research; C.S., R.F., F.S., F.C., and M.F. analyzed data; and C.S. and M.F. wrote the paper. The authors declare no conflict of interest. This article is a PNAS Direct Submission. This article contains supporting information online at www.pnas.org/lookup/suppl/doi:10.1073/pnas.1814558116/-/DCSupplemental. Copyright © 2019 the Author(s). Published by PNAS. 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PubMed ID: 29716793 Allaire JM, Crowley SM, Law HT, Chang SY, Ko HJ, Vallance BA Trends Immunol. Sep 2018 COMMENT:  The intestinal mucosa, a single layer of cells, interacts with and, at the same time, is a barrier to luminal microbiota. The communication between microbes and intestinal epithelial cells (IECs) and how these cells interacts with the immune system is a crucial matter and the main topic of this review. This review illustrates the cellular and functional complexity of the intestinal mucosa: Various differentiated cell types are found within the gut epithelium, and each carries out unique and specialized functions. The distribution of these cell types is also different between the small and large bowel These cell types include: enterocytes, the most prominent cell type of the intestinal epithelium that is responsible for nutrient and water absorption, various secretory cells such as goblet cells that secrete mucins, enteroendocrine cells that secrete hormones, and Paneth cells that release antimicrobial factors to protect nearby stem cells at the base of small intestinal crypts. Finally, there are the chemosensory tuft cells which play a key role in defense against helminths, and M cells that are integral to the uptake and eventual presentation of luminal antigens to the immune system Regarding the well known and close relationship between microbiome and Intestinal mucosa, the authors indicate: The intestinal mucosa of germ- free mice is very thin, displaying reduced IEC proliferation as well as impaired production of mucins and other IEC-derived mediators. This thinning of the protective mucin layer makes germ-free mice highly susceptible to the direct toxic effects of the colitogenic agent dextran sodium sulfate (DSS), reinforcing the importance of gut microbes in promoting intestinal tissue protection and repair It seems that the presence of continous antigenic stimulus at the mucosa is an important factor to maintain a normal mucosa and that this depends on an intact innate MyD88 signalling pathway. Another important factor is the metabolic products of microbiota: Obligate anaerobes such as Clostridium clusters IV and IXa, Faecalibacterium prausnitzii, and Bacteroides thetaiotaomicron produce the majority of butyrate, a short-chain fatty acid (SCFA) that is found in the lumen of the colon and is mostly converted through fermentation of dietary fiber Luminal butyrate is largely consumed by differentiated colonocytes residing at the top of the crypts. The architecture of the intestinal crypt shields the stem cells located at the crypt base from this metabolite. Disruption/damage of the crypt architecture (as occurs in DSS colitis) exposes stem cells to higher butyrate levels, which in turn suppresses their proliferative capacity by inhibiting histone deacetylase (HDAC) enzymes and inducing transcription factor Forkhead box O3 (FoxO3) Other microbial metabolites have been found to modulate IEC function.  Lactate is an important energy source for small intestinal stem cells to sustain their proliferation and differentiation capacity. Acetate, an SCFA produced by Bifidobacterium, has also been shown to influence goblet cell differentiation. The presence of acetate-producing microbes as well as acetate itself increased goblet cell secretion of mucin, and also promoted the terminal decoration of mucin glycans with sialic acid, whereas the presence of an acetate-consumer (Fecalibacterium) reduced these effects. Germ-free mice, which lack these bacterial metabolites, displayed shorter Muc2 O-glycans, and this correlated with a decrease in the expression of their respective glycosyltransferase enzymes by IECs In summary: Bacterial metabolites within the intestinal environment are important in maintaining normal IEC physiology in the small intestine as well as in the colon. Crosstalk between the microbiota and IECs developed as a means to prevent IEC dysfunction, and recent studies have shown that disruption of this crosstalk can also lead to aberrant changes in the resident microbial populations, termed ‘dysbiosis’. There is substantial evidence that the resident intestinal microbiota works in concert with colonocytes to prevent enteric microbial dysbiosis such as that observed in IBD patients Butyrate is an important metabolic factor modulating intestinal immune cells functions: Butyrate can also epigenetically regulate gene expression through the inhibition of histone deacetylases. This appears to be the mode of action for the modulating influence of commensal microbiota on peripheral regulatory T cell (Treg) differentiation. In butyrate-treated naïve CD4+ T cells has been reported an increased histone H3 acetylation of Foxp3 at its promoter region and at the intronic enhancer ‘intragenic enhancer elements conserved noncoding DNA sequence 1’ (CNS1) and CNS3 . This increased acetylation of Foxp3 resulted in increased gene expression. CNS1-deficient mice were unresponsive to the pres- ence of butyrate and did not induce FOXP3 expression in naïve CD4+ T cells Overall, butyrate influences the balance between intestinal pro- and anti-inflammatory mechanisms Colonization resistance is an important feature of a healthy microbiome: Invading microbes must compete for limited space and nutrients against entrenched microbiota–host symbiotic relationships as well as resist against potent antimicrobial molecules produced by some resident gut microbes. For example, Bacteroides thuringiensis, a bacterium found in human feces, produces a narrow-spectrum bacteriocin that is highly potent against the nosocomial pathogen Clostridium difficile. This bacteriocin, named thucin CD, is a two-component antimicrobial that acts synergistically to disrupt the cell membrane of its target Innate Immune System molecules and IECs: Situated at the interface between the luminal microbiota and the underlying immune system, the intestinal epithelium plays a crucial role in the detection of microbes under homeostatic as well as pathologic conditions. IECs express a variety of innate receptors that detect microbes and endogenous danger signals, including the TLRs Enterocytes are known to express TLR2, TLR3, TLR4, TLR5, and TLR9 The polarized nature of IECs facilitates the anatomical distribution of TLRs, segregating the majority to the basolateral membrane, while TLR2 and TLR9 are also expressed at the apical surface Once activated at the basolateral membrane, TLR signaling initiates a signaling cascade cumulating in the nuclear translocation of NF-kB. This leads to the expression and secretion of various cytokines and chemokines, including TNF-a, IL-6, IL-8, IL-18, and CCL20, which signal and prime underlying immune cells By contrast, apical stimulation of TLR9 results in a net immune inhibitory effect through the stabilization of IkB, demonstrating the unique ability of IECs to differentially respond to microbial signals using the same receptors but at varying spatiotemporal positions TLRs expressed by IECs play a key role in recognizing nearby microbes and their products, the responses they elicit are primarily aimed at keeping microbes at a distance (mucin secretion and antimicrobial production) or recruiting immune cells (via chemokines) to the site of infection. Upon direct invasion of IECs by intracellular pathogens, a more vigorous means of host defense is triggered, by which enterocytes can physically expel themselves from the intestinal epithelial lining while still maintaining mucosal barrier function. This process prevents intracellular pathogens from breaching the epithelial barrier, and instead they are extruded into the fecal stream, along with the sloughed enterocyte. This expulsion is independent from the homeostatic process of continuous enterocyte renewal. and instead involves activation of the inflammatory caspases (caspase-1, -4, and -11) as well as caspase-8 Not only enterocytes and colonocytes but also enterochromaffin cells make a crosstalk with microbiota: Some members of the intestinal microbiota, particularly spore-forming Clostridia spp., can stimulate colonic entero- chromaffin cells to upregulate their production of the neurotransmitter 5-HT In the context of an enteric infection, a limited number of studies suggest that production of 5-HT can aid in preventing incursion by microbial (S. Typhimurium) and helminthic (Trichuris muris) pathogens, possibly through the modulation of enterocyte function (such as antimicrobial peptide secretion and IL-13 receptor a1 signaling). Recent findings revealed that L cells, another type of enteroendocrine cell, can secrete glucagon-like peptide (GLP) 1 in a TLR4-dependent manner upon exposure to bacteria-derived LPS during gut injury or chemical-induced colitis in mice And also Paneth cells with a potential very interesting relationship with Crohn’s disease: Paneth cells, found specifically in the small intestine, have received the most attention based on their specialized role in secreting large granules filled with antimicrobial peptides and enzymes such as a-defensins, RegIIIg, sPLA2, and lysozyme. The baseline release of these antimicrobials is thought to promote normal microbial composition within the intestinal lumen.  This theory is based on recent studies linking the presence of structurally and functionally abnormal Paneth cells in Crohn’s disease (CD) patients to the development of microbial dysbiosis within the ileum. Significant reductions in barrier promoting microbes such as Faecalibacterium prausnitzii were also observed, emphasizing the crucial role played by Paneth cells in regulating intestinal microbial homeostasis. In this regard, single-nucleotide polymorphisms (SNPs) in several IBD-associated genes such as NOD2, XBP1, ATG16L1, and IRGM have been linked to Paneth cell dysfunction in IBD patients. These Paneth cell abnormalities include structurally irregular granules as well as impaired autophagic secretory pathways and failure in autophagy-based removal of damaged organelles. Two different hypomorphic Atg16l mouse models suggest that ATG16L1 controls the shape and distribution of Paneth cell granules as well as their production of lysozyme. Interestingly, biopsies of CD patients possessing the relevant ATG16L1 polymorphisms, but with quiescent disease, show an increased incidence of intestinal colonization by the microbial pathobiont adherent-invasive Escherichia coli (AIEC). This suggests that defects in autophagy, presumably within Paneth cells, may increase the susceptibility of CD patients to colonization or infection by specific microbes such as AIEC, and potentially predispose the patients to disease progression that requires intestinal surgery Although innate signaling plays an important role in the function of Paneth cells, presumably there are other pathways involved in controlling their ability to release their secretory granules, such as would occur in response to an infection of the small intestine. Interestingly, both in vivo and in vitro studies have demonstrated that exposure to IFN-g causes rapid and complete degranulation of Paneth cells, accompanied by their luminal extrusion and apoptosis And Globet cells: Intestinal goblet cells are best known for their production and secretion of the glycosylated mucin protein Muc2 which forms the protective mucus barrier atop the intestinal epithelium.  In its absence, Muc2
-/-
mice suffer exaggerated bacterial contact with their colonic epithelium, provoking inflammatory responses that eventually develop into spontaneous colitis. While Muc2 is normally released at a baseline level, in response to noxious luminal stimuli goblet cells undergo compound exocytosis, thereby releasing all of their mucin granules and other contents into the lumen to protect the epithelial barrier from direct contact with these threats. Intestinal goblet cells exposed to bacterial products or cytokines such IL-22 and IFN-g undergo this compound exocytosis IECs communicate with the Immune System: Early in the 1990s enterocytes were found to secrete an array of chemokines and cytokines, particularly in response to direct contact with bacteria or their products. Many of these secreted molecules are known to recruit and/or activate neutrophils, macrophages, dendritic cells, and T cells. The ability of enterocytes, and presumably other IEC types, to direct these cells and the local immune response is thought to be key to the resolution of infections that have crossed the gut barriers, as well as to the promotion mucosal repair following intestinal damage. Tuft cells: Renewed interest in tuft cells has been prompted recently owing to their newly discovered roles in detecting helminth parasites and as drivers of ILC2 expansion. Luminal helminths such as T. muris can be sensed by tuft cells through their GTP-binding protein a-gustducin that activates the non-selective cation channel transient receptor potential melastatin-like subtype 5 channel (Trpm5). Interestingly, in the oral cavity Trpm5 is responsible for the transduction of bitter, sweet, and umami tastes, and when colonic tuft cells are subjected to the bitter substrate denatonium this correlated with a sharp increase in intracellular calcium. This may denote chemosensors as a new class of pathogen recognition receptors if tuft cells are truly responding to chemicals secreted by invading parasites. Tuft cells constitutively secrete IL-25 to maintain ILC2 homeostasis, but upon recognizing helminths they increased their secretion of IL-25, which directly acts on ILC2 cells to release IL-13 This in turns feeds forward, with IL- 13 acting on epithelial progenitors in an IL-13Ra1/IL-4aR-dependent manner to promote tuft cell and goblet cell hyperplasia, cumulating in a dramatic increase in bulk mucin release that drives the expulsion of the parasite from the intestinal tract In summary, this review highlights the importance and complexity of IECs for the microbiome, defense against pathogens and local modulation of the Immune System  Contributor Eduardo Pareja