RMH

Compartmentation of proteins into biomolecular condensates or membraneless organelles formed by phase separation is an emerging principle for the regulation of cellular processes. Creating synthetic condensates that accommodate specific intracellular proteins on demand would have various applications in chemical biology, cell engineering, and synthetic biology. Here, we report the construction of synthetic protein condensates capable of recruiting and/or releasing proteins of interest in living mammalian cells in response to a small molecule or light. By a modular combination of a tandem fusion of two oligomeric proteins, which forms phase-separated synthetic protein condensates in cells, with a chemically induced dimerization tool, we first created a chemogenetic protein condensate system that can rapidly recruit target proteins from the cytoplasm to the condensates by addition of a small-molecule dimerizer. We next coupled the protein-recruiting condensate system with an engineered proximity-dependent protease, which gave a second protein condensate system wherein target proteins previously expressed inside the condensates are released into the cytoplasm by small-molecule-triggered protease recruitment. Furthermore, an optogenetic condensate system that allows reversible release and sequestration of protein activity in a repeatable manner using light was constructed successfully. These condensate systems were applicable to control protein activity and cellular processes such as membrane ruffling and ERK signaling in a time scale of minutes. This proof-of-principle work provides a new platform for chemogenetic and optogenetic control of protein activity in mammalian cells and represents a step toward tailor-made engineering of synthetic protein condensate-based soft materials with various functionalities for biological and biomedical applications.

We previously developed REXER (Replicon EXcision Enhanced Recombination); this method enables the replacement of >100 kb of the Escherichia coli genome with synthetic DNA in a single step and allows the rapid identification of non-viable or otherwise problematic sequences with nucleotide resolution. Iterative repetition of REXER (GENESIS, GENomE Stepwise Interchange Synthesis) enables stepwise replacement of longer contiguous sections of genomic DNA with synthetic DNA, and even the replacement of the entire E. coli genome with synthetic DNA. Here we detail protocols for REXER and GENESIS. A standard REXER protocol typically takes 7–10 days to complete. Our description encompasses (i) synthetic DNA design, (ii) assembly of synthetic DNA constructs, (iii) utilization of CRISPR–Cas9 coupled to lambda-red recombination and positive/negative selection to enable the high-fidelity replacement of genomic DNA with synthetic DNA (or insertion of synthetic DNA), (iv) evaluation of the success of the integration and replacement and (v) identification of non-tolerated synthetic DNA sequences with nucleotide resolution. This protocol provides a set of precise genome engineering methods to create custom synthetic E. coli genomes. 

The l-arabinose-responsive AraC and its cognate PBAD promoter underlie one of the most often used chemically inducible prokaryotic gene expression systems in microbiology and synthetic biology. Here, we change the sensing capability of AraC from l-arabinose to blue light, making its dimerization and the resulting PBAD activation light-inducible. We engineer an entire family of blue light-inducible AraC dimers in Escherichia coli (BLADE) to control gene expression in space and time. We show that BLADE can be used with pre-existing l-arabinose-responsive plasmids and strains, enabling optogenetic experiments without the need to clone. Furthermore, we apply BLADE to control, with light, the catabolism of l-arabinose, thus externally steering bacterial growth with a simple transformation step. Our work establishes BLADE as a highly practical and effective optogenetic tool with plug-and-play functionality—features that we hope will accelerate the broader adoption of optogenetics and the realization of its vast potential in microbiology, synthetic biology and biotechnology.

Antibiotic resistance spreads among bacteria through horizontal transfer of antibiotic resistance genes (ARGs). Here, we set out to determine predictive features of ARG transfer among bacterial clades. We use a statistical framework to identify putative horizontally transferred ARGs and the groups of bacteria that disseminate them. We identify 152 gene exchange networks containing 22,963 bacterial genomes. Analysis of ARG-surrounding sequences identify genes encoding putative mobilization elements such as transposases and integrases that may be involved in gene transfer between genomes. Certain ARGs appear to be frequently mobilised by different mobile genetic elements. We characterise the phylogenetic reach of these mobilisation elements to predict the potential future dissemination of known ARGs. Using a separate database with 472,798 genomes from Streptococcaceae, Staphylococcaceae and Enterobacteriaceae, we confirm 34 of 94 predicted mobilisations. We explore transfer barriers beyond mobilisation and show experimentally that physiological constraints of the host can explain why specific genes are largely confined to Gram-negative bacteria although their mobile elements support dissemination to Gram-positive bacteria. Our approach may potentially enable better risk assessment of future resistance gene dissemination.

The genus Pseudomonas can enhance plant resistance to a range of pathogens and herbivores. However, resistance to these different classes of plant antagonists is mediated by different molecular mechanisms, and the extent to which induced systemic resistance by Pseudomonas can simultaneously protect plants against both pathogens and herbivores remains unclear. We screened 12 root-colonizing Pseudomonas strains to assess their ability to induce resistance in Arabidopsis thaliana against a foliar pathogen (Pseudomonas syringae DC3000) and a chewing herbivore (Spodoptera littoralis). None of our 12 strains increased plant resistance against herbivory; however, four strains enhanced pathogen resistance, and one of these (Pseudomonas strain P97-38) also made plants more susceptible to herbivory. Phytohormone analyses revealed stronger SA induction in plants colonized by P97-38 (vs controls) following subsequent pathogen infection but weaker induction of JA-mediated defenses following herbivory. We found no effects of P97-38 inoculation on herbivore-relevant nutrients such as sugars and protein, suggesting that the observed enhancement of susceptibility to S. littoralis is due to effects on plant defense chemistry rather than nutrition. These findings suggest that Pseudomonas strains that enhance plant resistance to pathogens may have neutral or negative effects on resistance to herbivores and provide insight into potential mechanisms associated with effects on different classes of plant antagonists. Improved understanding of these effects has potentially important implications for the use of rhizobacteria inoculation in agriculture.

The current perspective presents an outlook on developing gut-like bioreactors with immobilized probiotic bacteria using cellulose hydrogels. The innovative concept of using hydrogels to simulate the human gut environment by generating and maintaining pH and oxygen gradients in the gut-like bioreactors is discussed. Fundamentally, this approach presents novel methods of production as well as delivery of multiple strains of probiotics using bioreactors. The relevant existing synthesis methods of cellulose hydrogels are discussed for producing porous hydrogels. Harvesting methods of multiple strains are discussed in the context of encapsulation of probiotic bacteria immobilized on cellulose hydrogels. Furthermore, we also discuss recent advances in using cellulose hydrogels for encapsulation of probiotic bacteria. This perspective also highlights the mechanism of probiotic protection by cellulose hydrogels. Such novel gut-like hydrogel bioreactors will have the potential to simulate the human gut ecosystem in the laboratory and stimulate new research on gut microbiota.

• Cable bacteria are sulfide‐oxidizing, filamentous bacteria which reduce toxic sulfide levels, suppress methane emissions, and drive nutrient and carbon cycling in sediments. Recently, cable bacteria have been found associated with roots of aquatic plants and rice (Oryza sativa). However, the extent to which cable bacteria are associated with aquatic plants in nature remains unexplored.
• Using newly generated and public 16S rRNA gene sequence datasets combined with fluorescence in situ hybridization, we investigated the distribution of cable bacteria around the roots of aquatic plants, encompassing seagrass (including seagrass seedlings), rice, freshwater and saltmarsh plants.
• Diverse cable bacteria were found associated with roots of 16 out of 28 plant species and at 36 out of 55 investigated sites, across four continents. Plant associated cable bacteria were confirmed across a variety of ecosystems, including marine coastal environments, estuaries, freshwater streams, isolated pristine lakes and intensive agricultural systems. This pattern indicates that this plant‐microbe relationship is globally widespread and neither obligate nor species‐specific.
• The occurrence of cable bacteria in plant rhizospheres may be of general importance to vegetation vitality, primary productivity, coastal restoration practices and greenhouse gas balance of rice fields and wetlands.

The isoelectric point is the pH at which a particular molecule is electrically neutral due to the equilibrium of positive and negative charges. In proteins and peptides, this depends on the dissociation constant (pKa) of charged groups of seven amino acids and NH+ and COO− groups at polypeptide termini. Information regarding isoelectric point and pKa is extensively used in two-dimensional gel electrophoresis (2D-PAGE), capillary isoelectric focusing (cIEF), crystallisation, and mass spectrometry. Therefore, there is a strong need for the in silico prediction of isoelectric point and pKa values. In this paper, I present Isoelectric Point Calculator 2.0 (IPC 2.0), a web server for the prediction of isoelectric points and pKa values using a mixture of deep learning and support vector regression models. The prediction accuracy (RMSD) of IPC 2.0 for proteins and peptides outperforms previous algorithms: 0.848 versus 0.868 and 0.222 versus 0.405, respectively. Moreover, the IPC 2.0 prediction of pKa using sequence information alone was better than the prediction from structure-based methods (0.576 versus 0.826) and a few folds faster. The IPC 2.0 webserver is freely available at www.ipc2-isoelectric-point.org

A diverse community of microorganisms inhabits various parts of a plant. Recent findings indicate that perturbations to the normal microbiota can be associated with positive and negative effects on plant health. In this review, we discuss these findings in the context of understanding how microbiota homeostasis is regulated in plants for promoting health and/or for preventing dysbiosis.

Efforts to use RNA-cleaving DNA enzymes (DNAzymes) as gene-silencing agents in therapeutic applications have stalled due to their low efficacy in clinical trials. Here we report a xeno-nucleic-acid-modified version of the classic DNAzyme 10–23 that achieves multiple-turnover activity under cellular conditions and resists nuclease digestion. The new reagent, X10–23, overcomes the problem of product inhibition, which limited previous 10–23 designs, using molecular chemotypes with DNA, 2′-fluoroarabino nucleic acid and α-l-threofuranosyl nucleic acid backbone architectures that balance the effects of enhanced biological stability with RNA hybridization and divalent metal ion coordination. In cultured mammalian cells, X10–23 facilitates persistent gene silencing by efficiently degrading exogenous and endogenous messenger RNA transcripts. Together, these results demonstrate that new molecular chemotypes can improve the activity and stability of DNAzymes, and may provide a new route for nucleic acid enzymes to reach the clinic.

Biofilm formation is often attributed to post-harvest bacteria persistence on fresh produce and food handling surfaces. In this study, a predicted glycosyl hydrolase enzyme was expressed, purified and validated for removal of microbial biofilms from biotic and abiotic surfaces under conditions used for chemical cleaning agents. Crystal violet biofilm staining assays revealed that 0.1 mg/mL of enzyme inhibited up to 41% of biofilm formation by E. coli O157:H7, E. coli 25922, Salmonella Typhimurium, and Listeria monocytogenes. Further, the enzyme was effective at removing mature biofilms, providing a 35% improvement over rinsing with a saline solution alone. Additionally, a parallel-plate flow cell was used to directly observe and quantify the impact of enzyme rinses on E. coli O157:H7 cells adhered to spinach leaf surfaces. The presence of 1 mg/L enzyme resulted in nearly 6 times greater detachment rate coefficients than a DI water rinse, while the total cells removed from the surface increased from 10% to 25% over the 30 minute rinse time, reversing the initial phases of biofilm formation. Enzyme treatment of all 4 cell types resulted in significantly reduced cell surface hydrophobicity, and collapse of negatively stained E. coli 25922 cells imaged by electron microscopy, suggesting potential polysaccharide surface modification of enzyme-treated bacteria. Collectively, these results point to the broad substrate specificity and robustness of the enzyme to different types of biofilm stages, solution conditions and pathogen biofilm types, and may be useful as a method for removal or inhibition of bacterial biofilm formation.

Transcription-factor-based biosensors (TFBs) are often used for metabolite detection, adaptive evolution, and metabolic flux control. However, designing TFBs with superior performance for applications in synthetic biology remains challenging. Specifically, natural TFBs often do not meet real-time detection requirements owing to their slow response times and inappropriate dynamic ranges, detection ranges, sensitivity, and selectivity. Furthermore, designing and optimizing complex dynamic regulation networks is time-consuming and labor-intensive. This Review highlights TFB-based applications and recent engineering strategies ranging from traditional trial-and-error approaches to novel computer-model-based rational design approaches. The limitations of the applications and these engineering strategies are additionally reviewed.