Biology subjects

Jana, B.

Publications and source records attributed to Jana, B..

At least 19 recordsLinked to original sources

bioRxiv2026

An Expanded Lpt Pathway Couples Surface Lipoprotein Export to Outer Membrane Vesicle Biogenesis in Bacteroides

The ecological dominance of Bacteroidota in the human gut microbiota derives from their exceptional capacity to metabolize diverse dietary and host-derived glycans. This ability relies on surface-exposed lipoproteins (SLPs), which are displayed on the bacterial surface and selectively packaged into outer membrane vesicles (OMVs). Although SLP export and OMV biogenesis are tightly coupled, the mechanism linking these processes has remained unknown. Here, we identify LptZ, a previously uncharacterized protein, as a critical link between SLP surface translocation and OMV biogenesis. Cryo-electron tomography of the lptZ mutant revealed chains of vesicles tethered to the outer membrane, offering a rare glimpse into an arrested stage of OMV formation in which vesicle fission is impaired. Proteomic analysis further showed that, in the absence of LptZ, a subset of SLPs fails to reach the cell surface and instead accumulates at the inner membrane. Unexpectedly, LptZ associates with the lipopolysaccharide transport (Lpt) machinery and repurposes it for SLP translocation. Crosslinking experiments revealed selective associations between multiple SLPs and Lpt proteins, providing mechanistic evidence for the direct involvement of the Lpt machinery in SLP trafficking. We further show that the Bacteroides Lpt machinery contains previously unrecognized components, revealing an unanticipated level of specialization relative to canonical Lpt systems. Together, our findings uncover a previously unknown protein export pathway, expand the functional role of the Lpt machinery, and establish a direct mechanistic link between SLP translocation and OMV biogenesis in Bacteroidota.

microbiology↗

bioRxiv2026

Conformational Barrier-Driven Flux Redistribution across Competing Catalytic Pathways Unifies Diverse Enzyme Kinetic Regimes

Enzymes are central to biological function, catalyzing the chemical transformations that sustain metabolism, signalling, molecular transport, and cellular regulation. Understanding their catalytic activity requires connecting molecular structure and conformational dynamics to measurable reaction kinetics. Classical Michaelis--Menten kinetics describes turnover through a dominant catalytic pathway approaching a single saturation limit, whereas conformational-selection, induced-fit, allosteric, and dynamic-disorder models account for additional complexity arising from conformational exchange and heterogeneous catalytic states. Experimental studies further reveal concentration-dependent changes in pathway usage, cooperative or sigmoidal responses, transitions between distinct turnover regimes, and intermittent single-molecule activity. These behaviours are typically treated within separate kinetic descriptions, leaving their mechanistic relationship within a common physical picture incompletely resolved. Here, we formulate a minimal conformational free-energy landscape with interconverting enzyme states and competing catalytic routes to examine whether these apparently distinct kinetic signatures can arise from a shared physical mechanism. In this framework, substrate availability and conformational barriers redistribute catalytic flux between slower and faster pathways, thereby altering both pathway occupancy and turnover times. Stochastic Gillespie simulations together with deterministic mean-first-passage-time analysis show that different parameter regimes generate low- and high-turnover states, concentration-dependent kinetic crossovers, burst--halt intermittency consistent with single-molecule observations, and effectively Michaelis--Menten-like or sigmoidal allosteric-like responses. The same underlying landscape can therefore produce qualitatively different kinetic behaviours depending on how conformational exchange and substrate capture partition catalytic flux. It also explains how finite substrate windows can mask underlying bimodal behaviour. These results provide a physically interpretable framework linking conformational dynamics, pathway selection, and experimentally observed enzyme kinetics.

biophysics↗

bioRxiv2026

Transferable Collective Variable to accelerate Protein-Ligand (Un)Binding Transitions via Explainable Machine Learning and Intriguing Role of Ligand Solvation

The process of drug unbinding is of immense importance in the field of biophysics and therapeutics. The behavior of these systems is greatly influenced by their thermodynamic and kinetic properties. Therefore, it is crucial to accurately estimate the ligand binding free energies and rate of ligand dissociation, yet these processes are often governed by rare event transitions that lie beyond the reach of standard brute-force molecular dynamics simulations. While enhanced sampling simulations offer a solution, their efficacy is strictly contingent upon the selection of appropriate collective variables (CVs) which is non-trivial for complex systems like protein-ligand complexes. In this study, we present a method to derive optimized CV from transition state region (TS) via an interpretable machine learning (ML) model, Elastic Net. By employing some physically intuitive order parameters, the derived optimized CV from the TS-region greatly accelerate ligand binding-unbinding transitions and achieves rapid free energy surface (FES) convergence across diverse systems including buried and solvent exposed active sites such as Trpsin-benzamidine complex, host-guest systems and sodium epoxidase etc. Intriguingly significant contribution of the ligand hydration is found in the optimized CV which depicts crucial role of solvent in driving ligand binding-unbinding transitions. The estimated binding free energies for different protein-ligand complexes match quite well with experiments, while maintaining a low computational cost. The derived optimized CV is also used to calculate the ligand residence times across different systems and calculated residence times are within the experimental range for all systems, again with very little computational costs. Moreover, we show that the optimized CV constructed from TS region via an interpretable ML model is transferable across diverse systems, offering a robust and scalable framework for drug discovery and investigation of complex biomolecular recognition.

biophysics↗

bioRxiv2026

Local cooperative interactions reshape the folding transition in a one-dimensional spin-glass model

Protein folding is the process by which a polypeptide chain organizes into its three-dimensional structure through a balance of stabilizing and destabilizing interactions encoded by the sequence. A central question in protein biophysics is how thermodynamic factors guide a polypeptide toward its native folded state despite the rugged energy landscape and the competing influence of nonnative interactions. In many biomolecular processes, cooperativity provides a mechanism by which multiple weak interactions act collectively to generate a robust response. In the context of protein folding, such cooperative effects may arise when the formation of one native contact enhances the stability or likelihood of nearby native contacts, thereby promoting collective organization toward the folded state. At the same time, folding is opposed by the much larger number of non-native interactions, whose heterogeneity can introduce frustration and destabilize folding even when the average native bias favors the folded phase. The interplay of these competing effects in determining foldability remains unclear in statistical-mechanical models. Here, we address this problem using a one-dimensional spin-glass model of protein folding with explicit shared-residue cooperative interactions encoded through wedge-based motifs. We show that modest cooperative bias can stabilize folding even where the noncooperative system remains unfolded, whereas non-native energetic fluctuation suppresses folding and shifts the transition to higher cooperative strengths. We further find that partial cooperative coverage is sufficient to lower the folding threshold. Therefore, the model provides a mean-field framework for incorporating cooperative interaction strength into the native one-dimensional model of protein folding and for describing how local cooperativity reshapes the folding transition.

biophysics↗

bioRxiv2025

Dual Membrane-spanning Anti-Sigma 2 Controls OMV biogenesis and Colonization Fitness in Bacteroides thetaiotaomicron

Bacteroides spp. are Gram-negative, gut commensals that shape the enteric landscape by producing outer membrane vesicles (OMVs) that degrade dietary fibers and traffic immunomodulatory biomolecules. Understanding the mechanism behind OMV biogenesis in Bacteroides spp. is necessary to determine their role in the gut. Recent studies showed that mutation of Dual Membrane-spanning Anti-sigma factor 1 increased OMV production in Bacteroides thetaiotaomicron (Bt) by regulating members of its downstream regulon. Additional members of the Dma family have been identified, but very little is known regarding their roles in Bt. Here, we investigate the role of Dual Membrane-spanning Anti-sigma factor 2 (Dma2) in controlling OMV biogenesis in Bt. We employ biochemical and proteomic analyses to show that mutation of dma2 increases OMV production in a manner that is dependent on the expression of its cognate sigma factor, das2. The precise mechanism by which dma2 increases OMV biogenesis remains elusive. However, transcriptome analyses revealed that{Delta} dma2 has decreased expression of select polysaccharide utilization loci (PULs) that primarily target host-associated glycans. Follow-up comparative proteomics showed that the PUL repertoire was most impacted in the OMV fraction. In vitro growth assessments showed that{Delta} dma2 exhibits delayed growth in the presence of select host-associated glycans. Colonization studies in mice revealed that{Delta} dma2 is outcompeted by the wild-type in the gut, which indicates that dma2 is a key determinant of colonization fitness in Bt. Altogether, these findings expand our knowledge of the Dma familys role in OMV biogenesis and demonstrates their importance in Bacteroides physiology. ImportanceDual membrane-spanning anti-sigma factors (Dma) are a novel class of regulatory system found solely amongst Bacteroidota. Previous studies have demonstrated the role of Dma1 in vesiculation, but the overall role of the Dma family in Bacteroides physiology remains poorly understood. Here, we demonstrate that Dma2 modulates vesiculation and regulates the expression of select polysaccharide utilization loci (PULs) that target host-associated glycans. In vivo studies revealed that Dma2 is an important fitness determinant when competing against kin bacteria. This work begins characterizing the multifaceted involvement of Dma2 in OMV biogenesis, PUL regulation, and colonization fitness.

microbiology↗

bioRxiv2025

Correlations among hydrogen bond fluctuations in the apo state are enough to reveal allosteric networks in proteins

Allostery is essential for regulating biochemical pathways, where ligand binding at one site influences enzymatic activity at a distant functional site. Identifying allosteric sites and mapping signal transduction pathways in biomolecules remain a significant challenge. Existing experimental or computational methods, in general, can identify a subset of total allosteric network. Here, we consider that in addition to providing structural stability and flexibility of proteins, hydrogen bonds inside the protein may act as conduits for long-range communication. To this end, we develop a computational framework that predicts allosteric sites and total allosteric network by analyzing correlations among hydrogen bond fluctuation from equilibrium molecular dynamics trajectory of apo state of proteins. We demonstrated that this method can accurately captures experimentally verified allosteric sites and suggest allosteric signal transduction pathways across three different proteins. Furthermore, since our predictions are derived solely from the simulation trajectory of the apo state, these findings reinforce the idea that the signature of allostery is inherently encoded in the apo state of the protein. This approach offers a useful strategy to decode allosteric network and pockets, with broad implications for drug discovery and the targeted modulation of allostery in proteins. SignificanceAllostery, distal ligand-induced functional modulation of biomolecules, is central to biological regulation, yet its intricate mechanisms remain elusive. Precise identification of allosteric sites and pathways is essential for targeted drug development, minimizing off-target effect. Here, we introduce a novel computational approach, Hydrogen Bond Allosteric Map (HBAlloMap), which leverages the dynamic fluctuations of hydrogen bond networks derived from microsecond molecular dynamics simulations to comprehensively map allosteric modules within proteins. By analyzing the fluctuation of correlated hydrogen bonds, our method effectively reveals key allosteric hotspots and signal transduction pathways in PDZ3, PDZ2, and Pin1. By providing a robust and efficient tool for deciphering allosteric mechanisms, this method has the potential to accelerate drug discovery and deepen our understanding of allostery.

biophysics↗

bioRxiv2025

A model of protein folding with multiple native states:Metamorphicity, Intrinsic disorderness and folding uponbinding of proteins

The sequence-structure-function paradigm in biology states that proteins amino acid sequence determines its unique folded state structure which in turn dictates its unique biological function. This classic concept has been severely challenged by the discovery of metamorphic and intrinsically disorder proteins (IDPs). Metamorphic proteins can fold into multiple native structures and perform multiple functions. IDPs, on the contrary, remain unstructured at physiological conditions, but can fold to unique structure upon binding to a target protein and show functionality. Here, we present a statistical mechanics model of protein folding with multiple native states and analyze their folding phase diagrams. While recovering classic sequence-structure-function paradigm for single native state, our model shows metamorphicity at lower number of native states. An expansion of unfolded region in the phase diagram at higher number of native states, making unfolded state as the stable state at physiological conditions, indicates the emergence of IDP-like scenario. Folding upon binding scenario of IDPs has also been demonstrated when an energetic bias is introduced for a specific native state. A regaining of folded region upon biasing, increasing the folding propensity of the system, with folding towards a specific native state is shown. Therefore, our model is general enough to reproduce the classic sequence-structure-function, metamorphicity, intrinsic disorderness and folding upon binding scenarios of proteins. Significance StatementProteins exhibit remarkable structural diversity, from having unique single native structure to having no particular structure but an inherently disordered ensemble that usually attains a single structure upon binding to another target. Here, we present a general statistical mechanics model of protein folding that reproduces single native state folding, metamorphicity, intrinsic disorder, and bindinginduced folding by incorporating multiple native states. A notable increase in propensity of being in unfolded state, resembling intrinsic disorder at physiological conditions, for system with larger number of native state was shown. Introduction of a bias was shown to increase the folding propensity of such proteins directed toward a specific native state. The models ability to capture a wide range of structural diversity in proteins makes it highly versatile.

biophysics↗

bioRxiv2025

Prediction of Enzyme function using interpretable optimized Ensemble learning framework

Accurate prediction of enzyme function, particularly for newly discovered uncharacterized sequences, is immensely important for modern biology research. Recently machine learning (ML) based methods have shown promises. However, such tools often suffer from complexity in feature extraction, interpretability, and generalization ability. Here we present an interpretable ML method, SOLVE that addresses these issues by using only combination of tokenized subsequences from the proteins primary sequence for classification. Its optimized ensemble learning framework improves prediction accuracy, distinguishes enzymes from non-enzymes, and predicts enzyme commission (EC) numbers for mono- and multi-functional enzymes. Additionally, SOLVE provides interpretability through Shapley analyses, identifying functional motifs at catalytic and allosteric sites of enzymes. By focusing only on primary sequence data, SOLVE simplifies high-throughput enzyme function prediction for functionally uncharacterized sequences and outperforms existing tools. With high prediction accuracy and its identification ability of functional regions, SOLVE can become a promising tool in different fields of biology and therapeutic drug design.

biophysics↗

bioRxiv2025

Wearable Photonic Device for Multiple Biomarker Sampling and Detection Without Blood Draws

Blood draws or phlebotomy using needles have been practiced in clinics for several centuries and it often causes pain, discomfort, and inconvenience. Herein, we create a wearable photonic device by integrating a microlens array (MLA) and an optic microneedle array (OMNA) functionalized with immunobinding capacity for safe and needle-free biomarker sampling and detection. The MLA-integrated OMNA amplified and transmitted LED light at 595 nm into the skin through the OMNA, bypassing the light-absorbing melanin in the epidermal layer, and evenly distributing it in the capillary-enriched dermis. The 595 nm light was preferably absorbed by hemoglobin (Hb) and oxygen-Hb within the capillaries, triggering thermal dilation of capillaries without damaging them or causing petechiae. The light illumination resulted in remarkable increases in the concentrations of various blood biomarkers in the skin owing to capillary dilation and biomarker extravasation. These extravasated biomarkers bound specifically to the OMNA, which was covalently decorated with capture antibodies, each microneedle immobilized with one specific antibody. The multi-functional OMNA was extensively modified to amplify the immunobinding signals and achieve sensitivity superior to that of enzyme-linked immunosorbent assay (ELISA) kits. As a proof of concept, we validated the functionality of the prototype for minimally invasive sampling and precise multiplexed blood biomarker detection in two mouse models to quantify acute inflammation and specific antibody production. This cost-efficient device provides a promising platform for blood-free, multiplexed detection of blood biomarkers.

bioengineering↗

bioRxiv2024

Dual CRISPRi-Seq for genome-wide genetic interaction studies identifies key genes involved in the pneumococcal cell cycle

A major goal in biology is to uncover the relationship between genotype and phenotype. However, identifying gene function is often hampered by genetic redundancy. For example, under standard laboratory conditions, three-quarters of the genes in the human pathogen Streptococcus pneumoniae are non-essential. A powerful approach to unravel genetic redundancy is by identifying gene-gene interactions. To uncover genetic interactions (GIs) in S. pneumoniae on a genome-wide scale, a generally applicable dual CRISPRi-Seq method and associated analysis pipeline was developed. Specifically, we created a library of 869 dual sgRNAs targeting high-confidence operons that encode essential and non-essential genes, covering over 70% of the genetic elements in the pneumococcal genome. Testing these 378,015 unique combinations, 4,026 significant GIs were identified, including 1,935 negative and 2,091 positive interactions. Besides known GIs, we found and confirmed previously unknown interactions involving genes responsible for fundamental cellular processes such as cell division, cell shape maintenance, and chromosome segregation. The presented methods and bioinformatic approaches can serve as a roadmap for genome-wide gene interaction studies in other organisms. Lastly, all interactions are available for exploration via the Pneumococcal Genetic Interaction Network (PneumoGIN) at https://veeninglab.shinyapps.io/PneumoGIN, which can serve as a starting point for new biological discoveries and translational research.

microbiology↗

bioRxiv2024

In vivo tests of the E. coli TonB system working model:interaction of ExbB with unknown proteins, identification of TonB-ExbD transmembrane heterodimers and PMF-dependent ExbD structures.

The TonB system of Escherichia coli resolves the dilemma posed by its outer membrane that protects it from a variety of external threats, but also constitutes a diffusion barrier to nutrient uptake. Our working model involves interactions among a set of cytoplasmic membrane-bound proteins: tetrameric ExbB that serves as a scaffold for a dimeric TonB complex (ExbB4-TonB2), and also engages dimeric ExbD (ExbB4-ExbD2). Through a set of synchronized conformational changes and movements these complexes are proposed to cyclically transduce cytoplasmic membrane protonmotive force to energize active transport of nutrients through TonB-dependent transporters in the outer membrane (described in Gresock et al., J. Bacteriol. 197:3433). In this work, we provide experimental validation of three important aspects of the model. The majority of ExbB is exposed to the cytoplasm, with an [~]90-residue cytoplasmic loop and an [~]50 residue carboxy terminal tail. Here we found for the first time, that the cytoplasmic regions of ExbB served as in vivo contacts for three heretofore undiscovered proteins, candidates to move ExbB complexes within the membrane. Support for the model also came from visualization of in vivo PMF-dependent conformational transitions in ExbD. Finally, we also show that TonB forms homodimers and heterodimers with ExbD through its transmembrane domain in vivo. This trio of in vivo observations suggest how and why solved in vitro structures of ExbB and ExbD differ significantly from the in vivo results and submit that future inclusion of the unknown ExbB-binding proteins may bring solved structures into congruence with proposed in vivo energy transduction cycle intermediates.

molecular biology↗

bioRxiv2023

Dual Membrane-Sspanning Anti-Sigma Factors Regulate Vesiculation in Gut Bacteroidota

Bacteroidota are abundant members of the human gut microbiota that shape the enteric landscape by modulating host immunity and degrading dietary- and host-derived glycans. These processes are at least partially mediated by Outer Membrane Vesicles (OMVs). In this work, we developed a high-throughput screen to identify genes required for OMV biogenesis and its regulation in Bacteroides thetaiotaomicron (Bt). Our screening led us to the identification of a novel family of Dual Membrane-spanning Anti-sigma factors (Dma), which regulate OMV biogenesis in Bt. We employed molecular and multiomic analyses to demonstrate that deletion of Dma1, the founding member of the Dma family, results in hypervesiculation by modulating the expression of NigD1, which belongs to a family of uncharacterized proteins found throughout Bacteroidota. Dma1 has an unprecedented domain organization: it contains a C-terminal {beta}-barrel embedded in the OM; its N-terminal domain interacts with its cognate sigma factor in the cytoplasm, and both domains are tethered via an intrinsically disordered region that traverses the periplasm. Phylogenetic analyses reveal that the Dma family is a unique feature of Bacteroidota. This study provides the first mechanistic insights into the regulation of OMV biogenesis in human gut bacteria.

microbiology↗

bioRxiv2023

CRISPRi-TnSeq: A genome-wide high-throughput tool for bacterial essential-nonessential genetic interaction mapping

Genetic interaction networks can help identify functional connections between genes and pathways, which can be leveraged to establish (new) gene function, drug targets, and fill pathway gaps. Since there is no optimal tool that can map genetic interactions across many different bacterial strains and species, we develop CRISPRi-TnSeq, a genome-wide tool that maps genetic interactions between essential genes and nonessential genes through the knockdown of a targeted essential gene (CRISPRi) and the simultaneous knockout of individual nonessential genes (Tn-Seq). CRISPRi-TnSeq thereby identifies, on a genome-wide scale, synthetic and suppressor-type relationships between essential and nonessential genes, enabling the construction of essential-nonessential genetic interaction networks. To develop and optimize CRISPRi-TnSeq, CRISPRi strains were obtained for 13 essential genes in Streptococcus pneumoniae, involved in different biological processes including metabolism, DNA replication, transcription, cell division and cell envelope synthesis. Transposon-mutant libraries were constructed in each strain enabling screening of [~]24,000 gene-gene pairs, which led to the identification of 1,334 genetic interactions, including 754 negative and 580 positive genetic interactions. Through extensive network analyses and validation experiments we identify a set of 17 pleiotropic genes, of which a subset tentatively functions as genetic capacitors, dampening phenotypic outcomes and protecting against perturbations. Furthermore, we focus on the relationships between cell wall synthesis, integrity and cell division and highlight: 1) how essential gene knockdown can be compensated by rerouting flux through nonessential genes in a pathway; 2) the existence of a delicate balance between Z-ring formation and localization, and septal and peripheral peptidoglycan (PG) synthesis to successfully accomplish cell division; 3) the control of c-di-AMP over intracellular K+ and turgor, and thereby modulation of the cell wall synthesis machinery; 4) the dynamic nature of cell wall protein CozEb and its effect on PG synthesis, cell shape morphology and envelope integrity; 5) functional dependency between chromosome decatenation and segregation, and the critical link with cell division, and cell wall synthesis. Overall, we show that CRISPRi-TnSeq uncovers genetic interactions between closely functionally linked genes and pathways, as well as disparate genes and pathways, highlighting pathway dependencies and valuable leads for gene function. Importantly, since both CRISPRi and Tn-Seq are widely used tools, CRISPRi-TnSeq should be relatively easy to implement to construct genetic interaction networks across many different microbial strains and species.

genetics↗

bioRxiv2022

Studies on the Escherichia coli ExbD Transmembrane Domain, Residue L132, and an Inhibitory Cyclic Peptide.

The TonB system of Escherichia coli uses the cytoplasmic membrane protonmotive force (PMF) to energize active transport of nutrients across the otherwise unenergized outer membrane. Because it overcomes limitations for nutrient diffusion through outer membrane size-limiting porins, it provides a growth advantage and is widespread among Gram-negative bacteria. It consists of three known cytoplasmic membrane proteins, TonB, ExbB and ExbD that energize a variety of customized TonB-dependent transporters in the outer membrane. The sole ExbD transmembrane domain is proposed to consist of residues 23-43 (Kampfenkel and Braun, 1992, J. Bacteriol. 174:5485-7). Here we showed that the charge and location of residue Asp25 were essential for activity of the TonB system, thus identifying it as the only PMF-responsive element in the TonB system. The proposed boundaries of the transmembrane domain -helix were revised to consist of residues 23-39, with residues 40-43 initiating the subsequent disordered region required for signal transduction (Kopp and Postle, 2020, J. Bacteriol. 202, e00687-19). Trapping of disulfide-linked ExbD homodimers through T42C or V43C prevented TonB system activity that was restored by addition of the reducing agent dithiothreitol, indicating a requirement for motion. In vivo photo-cross-linking experiments suggested that motion was rotation of ExbD transmembrane domains. Inactivity of ExbD L132Q, the first ExbD mutant identified, was likely due to steric hindrance. A conserved and defined site of in vivo ExbD interaction with TonB was identified. Exogenous addition of a cyclic peptide based on that site inhibited ExbD-TonB interaction while concomitantly decreasing iron transport efficiency. This suggested that a novel antimicrobial strategy against ESKAPE and other Gram-negative pathogens could be developed by targeting ExbD protein-protein interactions.

molecular biology↗

bioRxiv2022

Multiple T6SSs, mobile auxiliary modules, and effectors revealed in a systematic analysis of the Vibrio parahaemolyticus pan-genome

Type VI secretion systems (T6SSs) play a major role in interbacterial competition and in bacterial interactions with eukaryotic cells. The distribution of T6SSs and the effectors they secrete vary between strains of the same bacterial species. Therefore, a pan-genome investigation is required to better understand the T6SS potential of a bacterial species of interest. Here, we performed a comprehensive, systematic analysis of T6SS gene clusters and auxiliary modules found in the pan-genome of Vibrio parahaemolyticus, an emerging pathogen widespread in marine environments. We identified four different T6SS gene clusters within genomes of this species; two systems appear to be ancient and widespread, whereas the other two systems are rare and appear to have been more recently acquired via horizontal gene transfer. In addition, we identified diverse T6SS auxiliary modules containing putative effectors with either known or predicted toxin domains. Many auxiliary modules are possibly horizontally shared between V. parahaemolyticus genomes, since they are flanked by DNA mobility genes. We further investigated a DUF4225-containing protein encoded on an Hcp auxiliary module, and we showed that it is an antibacterial T6SS effector that exerts its toxicity in the bacterial periplasm, leading to cell lysis. Computational analyses of DUF4225 revealed a widespread toxin domain associated with various toxin delivery systems. Taken together, our findings reveal a diverse repertoire of T6SSs and auxiliary modules in the V. parahaemolyticus pan-genome, as well as novel T6SS effectors and toxin domains that can play a major role in the interactions of this species with other cells. ImportanceGram-negative bacteria employ toxin delivery systems to mediate their interactions with neighboring cells. Vibrio parahaemolyticus, an emerging pathogen of humans and marine animals, was shown to deploy antibacterial toxins into competing bacteria via the type VI secretion system (T6SS). Here, we analyzed 1,727 V. parahaemolyticus genomes and revealed the pan-genome T6SS repertoire of this species, including the T6SS gene clusters, horizontally shared auxiliary modules, and toxins. We also identified a role for a previously uncharacterized domain, DUF4225, as a widespread antibacterial toxin associated with diverse toxin delivery systems.

microbiology↗

bioRxiv2022

The MIX domain is required for T6SS-mediated effector secretion

ABTRACTGram-negative bacteria often employ the type VI secretion system (T6SS) to deliver diverse cocktails of antibacterial effectors into rival bacteria. In many cases, even when the identity of the delivered effectors is known, their toxic activity and mechanism of secretion are not. Here, we investigate VPA1263, a Vibrio parahaemolyticus T6SS effector that belongs to a widespread class of polymorphic effectors containing a MIX domain. We reveal a C-terminal DNase toxin domain belonging to the HNH nuclease superfamily, and we show that it mediates the antibacterial toxicity of this effector during bacterial competition. Furthermore, we demonstrate that the VPA1263 MIX domain is necessary for T6SS-mediated secretion and intoxication of recipient bacteria. These results are the first indication of a functional role for MIX domains in T6SS secretion. IMPORTANCESpecialized protein delivery systems are used during bacterial competition to deploy cocktails of toxins that target conserved cellular components. Although numerous toxins have been revealed, the activity of many remains unknown. In this study, we investigated such a toxin from the pathogen Vibrio parahaemolyticus. Our findings indicated that the toxin employs a DNase domain to intoxicate competitors. We also showed that a domain used as a marker for secreted toxins is required for secretion of the toxin via a type VI secretion system.

microbiology↗

bioRxiv2022

A genome-wide atlas of antibiotic susceptibility targets and pathways to tolerance.

Detailed knowledge on how bacteria evade antibiotics and eventually develop resistance could open avenues for novel therapeutics and diagnostics. It is thereby key to develop a comprehensive genome-wide understanding of how bacteria process antibiotic stress, and how modulation of the involved processes affects their ability to overcome said stress. Here we undertake a comprehensive genetic analysis of how the major human pathogen Streptococcus pneumoniae responds to 20 antibiotics. We built a genome-wide atlas of drug susceptibility determinants and generate a genetic interaction network that connects cellular processes and genes of unknown function, which we show can be used as therapeutic targets. Pathway analysis reveals a genome-wide "tolerome", defined by cellular processes that can make a bacterium less susceptible, and often tolerant, in an antibiotic specific manner. Importantly, modulation of these processes confers fitness benefits during active infections under antibiotic selection. Moreover, screening of sequenced clinical isolates demonstrates that mutations in tolerome genes readily evolve and are frequently associated with resistant strains, indicating such mutations may be an important harbinger for the emergence of antibiotic resistance.

microbiology↗

bioRxiv2021

A binary effector module secreted by a type VI secretion system

Gram-negative bacteria use type VI secretion systems (T6SSs) to deliver toxic effector proteins into neighboring cells. Cargo effectors are secreted by binding non-covalently to the T6SS apparatus. Occasionally, effector secretion is assisted by an adaptor protein, although the adaptor itself is not secreted. Here, we report a new T6SS secretion mechanism, in which an effector and a co-effector are secreted together. Specifically, we identified a novel periplasm-targeting effector that is secreted together with its co-effector, which contains a MIX (marker for type sIX effector) domain previously reported only in polymorphic toxins. The effector and co-effector directly interact, and they are dependent on each other for secretion. We termed this new secretion mechanism "a binary effector module", and we show that it is widely distributed in marine bacteria.

microbiology↗