Microbial communities, complex ecological networks crucial for human and planetary health, remain poorly understood in terms of the quantitative principles governing their composition, assembly, and function. Dynamic modeling using ordinary differential equations (ODEs) is a powerful framework for understanding and predicting microbiome behaviors. However, developing reliable ODE models is severely hampered by their nonlinear nature and the presence of significant challenges, particularly critical issues related to identifiability. Here, we address the identification problem in dynamic microbial community models by proposing an integrated methodology to tackle key challenges. Focusing on nonlinear ODE-based models, we examine four critical pitfalls: identifiability issues (structural and practical), unstable dynamics (potentially leading to numerical blow-up), underfitting (convergence to suboptimal solutions), and overfitting (fitting noise rather than signal). These pitfalls yield unreliable parameter estimates, unrealistic model behavior, and poor generalization. Our study presents a comprehensive workflow incorporating structural and practical identifiability analysis, robust global optimization for calibration, stability checks, and rigorous predictive power assessment. The methodology’s effectiveness and versatility in mitigating these pitfalls are demonstrated through case studies of increasing complexity, paving the way for more reliable and mechanistically insightful models of microbial communities. https://doi.org/10.5281/zenodo.15309438 

The impact of anaerobic oxidation of methane (AOM) coupled with denitrification on the emission of the denitrification intermediate N2O remains poorly understood. Here, we investigated the influence of AOM coupled with nitrate and nitrite reduction on soil N2O emissions and the associated microbial interactions. We show that AOM coupled with denitrification markedly reduces soil N2O emissions, with the type I methanotroph Methylobacter species collaborating with the Methylophilaceae and Gemmatimonadaceae families to perform key roles. The suppression of N2O emissions by AOM primarily stems from its role in supplying electrons and carbon sources, fueling complete denitrification by associated bacteria. In addition, we uncovered distinct microbial interaction strategies for AOM-coupled nitrate and nitrite reduction. While nitrite reduction necessitates both bacterial cooperation and extracellular electron transfer during its initial stages, nitrate reduction predominantly depends on methanotrophic bacteria alone at the outset. These findings advance our understanding of carbon-nitrogen cycle coupling and underscore AOM’s potential to simultaneously mitigate both CH4 and N2O emissions.

T cells targeting epitopes in infectious diseases or cancer play a central role in spontaneous and therapy-induced immune responses. Epitope recognition is mediated by the binding of the T cell receptor (TCR), and TCRs recognizing clinically relevant epitopes are promising for T cell–based therapies. Starting from a TCR targeting the cancer-testis antigen NY-ESO-1157–165 epitope, we built large phage display libraries of TCRs with randomized complementary determining region 3 of the β chain. The TCR libraries were panned against NY-ESO-1, which enabled us to collect thousands of epitope-specific TCR sequences. Leveraging these data, we trained a machine learning TCR-epitope interaction predictor and identified several epitope-specific TCRs from TCR repertoires. Cellular assays revealed that the predicted TCRs displayed activity toward NY-ESO-1 and no detectable cross-reactivity. Our work demonstrates how display technologies combined with TCR-epitope interaction predictors can effectively leverage large TCR repertoires for TCR discovery.

Microplastics and nanoplastics pollution (MNPP) is a major environmental issue due to its small size, long-lasting nature, and potentially harmful impacts on ecosystems and human health. Plastics can be degraded in nature by physical, chemical, and biological processes. Plastic biodegradation is a potential sustainable solution to MNPP, but understanding the fitness of potential plastic-degrading proteins (PPDPs) across environments requires comparative resources. Here, we introduce the Plastic-Degrading Clusters of Orthologous Groups (PDCOGs) database, available at https://phylobone.com/microworld/PDCOG  The resource includes 625,616 PPDPs from free-living prokaryotes classified in 51 PDCOGs. The PDCOG database is a robust resource that improves understanding of plastic biodegradation and supports research on global MNPP challenges. Overall, PDPPs represent 3.5% of proteins in prokaryotes and are widely distributed across the Earth, spanning across most prokaryotic species and environments. Nearly all prokaryotic species (>95%) have the potential to biodegrade at least one polymer type.

Genetic variations in transcriptional regulators (TRs) of metabolic loci can influence host-bacterial interactions by affecting carbon utilization. Although the metabolism of sugar acids, including D-galactonate, is extensively implicated in the colonization and virulence of enteric bacteria, there has been no investigation on the extent of variations in their pathway-specific TRs. DgoR, the TF of D-galactonate metabolism, is the best-characterized GntR/FadR family sugar acid TFs in enteric bacteria, recognized by the presence of an N-terminal winged helix-turn-helix DNA-binding domain and a C-terminal effector-binding and oligomerization (E-O) domain connected by a linker. Here, we examined 340 Escherichia coli isolates for variations in dgoR and studied their effect on repressor function. Genetic and biochemical studies identified variants with a partial loss of DNA-binding ability (P24L and A152E) and a decreased response to D-galactonate (R71C and P92L). Because the linker residue R71C resulted in a reduced response to D-galactonate and the E-O domain residue A152E led to a DNA binding defect, we performed simulations to probe their altered allosteric behavior. We observed that the correlation patterns, dynamics, and networks of the variants are indeed distinct from the wild type. Importantly, corroborating their repressor function, R71C and A152E variations impacted the growth of natural isolates in D-galactonate. Alignment-based variation detection across all E. coli and Enterobacterales identical protein group data sets revealed less prevalence of these four variations. Collectively, the present study highlights the need for a thorough analysis of the effect of variations in sugar acid TRs on repressor function and their effect on host-bacterial interactions.

During pathogen attack, plants recruit beneficial microbes in a cry for help to mitigate disease development. Simultaneously, pathogens secrete effectors to promote host colonization through various mechanisms, including targeted host microbiota manipulation. Here, we characterize the Av2 effector of the vascular wilt fungus Verticillium dahliae as a suppressor of the cry for help. Inspired by in silico antimicrobial activity prediction, we investigated the antimicrobial activity of Av2 in vitro. Furthermore, its role in V. dahliae virulence was assessed through microbiota sequencing of inoculated plants, microbial co-cultivation assays, and inoculations in a gnotobiotic plant cultivation system. We show that Av2 inhibits bacterial growth, and acts as a virulence factor during host colonization. Microbiota sequencing revealed involvement of Av2 in suppression of Pseudomonas spp. recruitment upon plant inoculation with V. dahliae, suggesting that Av2 suppresses the cry for help. We show that several Pseudomonas spp. are antagonistic to V. dahliae and sensitive to Av2 treatment. We conclude that V. dahliae secretes Av2 to suppress the cry for help by inhibiting the recruitment of antagonistic Pseudomonas spp. to pave the way for successful plant invasion.

Steel corrosion is an extensive problem worldwide, substantially impacting marine infrastructures. In this study, the influence of steel on bacterial succession and corrosion was investigated by culturing marine water samples with and without steel coupons for 14 days. Compared to abiotic controls, oxygen levels were rapidly depleted in biotic cultures. Fe levels increased in controls compared to biotic cultures, potentially due to anoxic conditions and the incorporation of Fe in the biofilm. Proteobacteria dominated the initial cultures, but over 14 days the number of phylogenetic groups decreased overall in abundance. Taxons that increased in abundance included Clostridiaceae, Fusobacteriaceae, Flavobacteriaceae and Prolixibacteraceae, some members of which can utilize Fe. While initially in low abundance, Arcobacteraceae, Pseudoalteromonadaceae, Rhodobacteraceae and Rhizobiaceae numbers increased over time. Sites 1 and 2 cultures displayed localised deep pitting corrosion on coupon surfaces, consistent with microbial action, with an increase in Bacteroidetes, suggesting this phylum facilitates corrosion. In contrast, Site 3 cultures displayed uniform, superficial corrosion, with Clostridiaceae being the dominating family by Day 14, suggesting corrosion inhibition through biofilm formation. By identifying bacteria associated with corrosion, targeted approaches to corrosion reduction may be developed through identifying significant metabolic pathways by transcriptomics and the application of metabolic inhibitors.

Bacterial transcription initiation is a tightly regulated process that canonically relies on sequence-specific promoter recognition by dedicated sigma (σ) factors, leading to functional DNA engagement by RNA polymerase (RNAP). Although the seven σ factors in E. coli have been extensively characterized, Bacteroidetes species encode dozens of specialized, extracytoplasmic function σ factors (σE) whose precise roles are unknown, pointing to additional layers of regulatory potential. Here we uncover an unprecedented mechanism of RNA-guided gene activation involving the coordinated action of σE factor in complex with nuclease-dead Cas12f (dCas12f). We screened a large set of genetically-linked dCas12f and σE homologs in E. coli using RIP-seq and ChIP-seq experiments, revealing systems that exhibited robust guide RNA enrichment and DNA target binding with a minimal 5ʹ-G target-adjacent motif (TAM). Recruitment of σE was dependent on dCas12f and guide RNA (gRNA), suggesting direct protein-protein interactions, and co-expression experiments demonstrated that the dCas12f-gRNA-σE ternary complex was competent for programmable recruitment of the RNAP holoenzyme. Remarkably, dCas12f-RNA-σE complexes drove potent gene expression in the absence of any requisite promoter motifs, with de novo transcription start sites defined exclusively by the relative distance from the dCas12f-mediated R-loop. Our findings highlight a new paradigm of RNA-guided transcription (RGT) that embodies natural features reminiscent of CRISPRa technology developed by humans.