An integrated computational-experimental approach reveals Yersinia pestis genes essential across a narrow or a broad range of environmental conditions

Model-driven insights into the effects of temperature on metabolism

Temperature affects cellular processes at different spatiotemporal scales, and identifying the genetic and molecular mechanisms underlying temperature responses paves the way to develop approaches for mitigating the effects of future climate scenarios. A systems view of the effects of temperature on cellular physiology can be obtained by focusing on metabolism since: (i) its functions depend on transcription and translation and (ii) its outcomes support organisms' development, growth, and reproduction. Here we provide a systematic review of modelling efforts directed at investigating temperature effects on properties of single biochemical reactions, system-level traits, metabolic subsystems, and whole-cell metabolism across different prokaryotes and eukaryotes. We compare and contrast computational approaches and theories that facilitate modelling of temperature effects on key properties of enzymes and their consideration in constraint-based as well as kinetic models of metabolism. In addition, we provide a summary of insights from computational approaches, facilitating integration of omics data from temperature-modulated experiments with models of metabolic networks, and review the resulting biotechnological applications. Lastly, we provide a perspective on how different types of metabolic modelling can profit from developments in machine learning and models of different cellular layers to improve model-driven insights into the effects of temperature relevant for biotechnological applications.

Yersiniomics, a Multi-Omics Interactive Database for Yersinia Species

The genus Yersinia includes a large variety of nonpathogenic and life-threatening pathogenic bacteria, which cause a broad spectrum of diseases in humans and animals, such as plague, enteritis, Far East scarlet-like fever (FESLF), and enteric redmouth disease. Like most clinically relevant microorganisms, Yersinia spp. are currently subjected to intense multi-omics investigations whose numbers have increased extensively in recent years, generating massive amounts of data useful for diagnostic and therapeutic developments. The lack of a simple and centralized way to exploit these data led us to design Yersiniomics, a web-based platform allowing straightforward analysis of Yersinia omics data. Yersiniomics contains a curated multi-omics database at its core, gathering 200 genomic, 317 transcriptomic, and 62 proteomic data sets for Yersinia species. It integrates genomic, transcriptomic, and proteomic browsers, a genome viewer, and a heatmap viewer to navigate within genomes and experimental conditions. For streamlined access to structural and functional properties, it directly links each gene to GenBank, the Kyoto Encyclopedia of Genes and Genomes (KEGG), UniProt, InterPro, IntAct, and the Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) and each experiment to Gene Expression Omnibus (GEO), the European Nucleotide Archive (ENA), or the Proteomics Identifications Database (PRIDE). Yersiniomics provides a powerful tool for microbiologists to assist with investigations ranging from specific gene studies to systems biology studies. IMPORTANCE The expanding genus Yersinia is composed of multiple nonpathogenic species and a few pathogenic species, including the deadly etiologic agent of plague, Yersinia pestis. In 2 decades, the number of genomic, transcriptomic, and proteomic studies on Yersinia grew massively, delivering a wealth of data. We developed Yersiniomics, an interactive web-based platform, to centralize and analyze omics data sets on Yersinia species. The platform allows user-friendly navigation between genomic data, expression data, and experimental conditions. Yersiniomics will be a valuable tool to microbiologists.

An inducible transposon mutagenesis approach for the intracellular human pathogen Chlamydia trachomatis

Background: Chlamydia trachomatis is a prolific human pathogen that can cause serious long-term conditions if left untreated. Recent developments in Chlamydia genetics have opened the door to conducting targeted and random mutagenesis experiments to identify gene function. In the present study, an inducible transposon mutagenesis approach was developed for C. trachomatis using a self-replicating vector to deliver the transposon-transposase cassette - a significant step towards our ultimate aim of achieving saturation mutagenesis of the Chlamydia genome. Methods: The low transformation efficiency of C. trachomatis necessitated the design of a self-replicating vector carrying the transposon mutagenesis cassette (i.e. the Himar-1 transposon containing the beta lactamase gene as well as a hyperactive transposase gene under inducible control of the tet promoter system with the addition of a riboswitch). Chlamydia transformed with this vector (pSW2-RiboA-C9Q) were induced at 24 hours post-infection. Through dual control of transcription and translation, basal expression of transposase was tightly regulated to stabilise the plasmid prior to transposition. Results: Here we present the preliminary sequencing results of transposon mutant pools of both C. trachomatis biovars, using two plasmid-free representatives: urogenital strain   C. trachomatis SWFP- and the lymphogranuloma venereum isolate L2(25667R). DNA sequencing libraries were generated and analysed using Oxford Nanopore Technologies' MinION technology. This enabled 'proof of concept' for the methods as an initial low-throughput screen of mutant libraries; the next step is to employ high throughput sequencing to assess saturation mutagenesis. Conclusions: This significant advance provides an efficient method for assaying C. trachomatis gene function and will enable the identification of the essential gene set of C. trachomatis. In the long-term, the methods described herein will add to the growing knowledge of chlamydial infection biology leading to the discovery of novel drug or vaccine targets.

PsaF Is a Membrane-Localized pH Sensor That Regulates psaA Expression in Yersinia pestis

The Yersinia pestis pH 6 antigen (PsaA) forms fimbria-like structures and is required for full virulence during bubonic plague. High temperature and low pH regulate PsaA production, and while recent work has uncovered the molecular aspects of temperature control, the mechanisms underlying this unusual regulation by pH are poorly understood. Using defined growth conditions, we recently showed that high levels of PsaE and PsaF (two regulatory proteins required for expression of psaA) are present at mildly acidic pH, but these levels are greatly reduced at neutral pH, resulting in low psaA expression. In prior work, the use of translational reporters suggested that pH had no impact on translation of psaE and psaF, but rather affected protein stability of PsaE and/or PsaF. Here, we investigated the pH-dependent posttranslational mechanisms predicted to regulate PsaE and PsaF stability. Using antibodies that recognize the endogenous proteins, we showed that the amount of PsaE and PsaF is defined by a distinct pH threshold. Analysis of histidine residues in the periplasmic domain of PsaF suggested that it functions as a pH sensor and indicated that the presence of PsaF is important for PsaE stability. At neutral pH, when PsaF is absent, PsaE appears to be targeted for proteolytic degradation by regulated intramembrane proteolysis. Together, our work shows that Y. pestis utilizes PsaF as a pH sensor to control psaA expression by enhancing the stability of PsaE, an essential psaA regulatory protein. IMPORTANCE Yersinia pestis is a bacterial pathogen that causes bubonic plague in humans. As Y. pestis cycles between fleas and mammals, it senses the environment within each host to appropriately control gene expression. PsaA is a protein that forms fimbria-like structures and is required for virulence. High temperature and low pH together stimulate psaA transcription by increasing the levels of two essential integral membrane regulators, PsaE and PsaF. Histidine residues in the PsaF periplasmic domain enable it to function as a pH sensor. In the absence of PsaF, PsaE (a DNA-binding protein) appears to be targeted for proteolytic degradation, thus preventing expression of psaA. This work offers insight into the mechanisms that bacteria use to sense pH and control virulence gene expression.

Exploring the druggable proteome of Candida species through comprehensive computational analysis

Candida albicans and non-albicans Candida spp. are major cause of systemic mycoses. Antifungal drugs such as azoles and polyenes are not efficient to successfully eradicate Candida infection owing to their fungistatic nature or low bioavailability. Here, we have adopted a comprehensive computational workflow for identification, prioritization and validation of targets from proteomes of Candida albicans and Candida tropicalis. The protocol involves identification of essential drug-target candidates using subtractive genomics, protein-protein interaction network properties and systems biology based methods. The essentiality of the novel metabolic and non-metabolic targets was established by performing in silico gene knockouts, under aerobic as well as anaerobic conditions, and in vitro drug inhibition assays respectively. Deletion of twelve genes that are involved in amino acid, secondary metabolite, and carbon metabolism showed zero growth in metabolic model under simulated conditions. The algorithm, used in this study, can be downloaded from http://pbit.bicnirrh.res.in/offline.php and executed locally.

Inhibiting the reproduction of SARS-CoV-2 through perturbations in human lung cell metabolic network

Viruses rely on their host for reproduction. Here, we made use of genomic and structural information to create a biomass function capturing the amino and nucleic acid requirements of SARS-CoV-2. Incorporating this biomass function into a stoichiometric metabolic model of the human lung cell and applying metabolic flux balance analysis, we identified host-based metabolic perturbations inhibiting SARS-CoV-2 reproduction. Our results highlight reactions in the central metabolism, as well as amino acid and nucleotide biosynthesis pathways. By incorporating host cellular maintenance into the model based on available protein expression data from human lung cells, we find that only few of these metabolic perturbations are able to selectively inhibit virus reproduction. Some of the catalysing enzymes of such reactions have demonstrated interactions with existing drugs, which can be used for experimental testing of the presented predictions using gene knockouts and RNA interference techniques. In summary, the developed computational approach offers a platform for rapid, experimentally testable generation of drug predictions against existing and emerging viruses based on their biomass requirements.

A Trimeric Autotransporter Enhances Biofilm Cohesiveness in Yersinia pseudotuberculosis but Not in Yersinia pestis

Cohesion of biofilms made by Yersinia pestis and Yersinia pseudotuberculosis has been attributed solely to an extracellular polysaccharide matrix encoded by the hms genes (Hms-dependent extracellular matrix [Hms-ECM]). However, mutations in the Y. pseudotuberculosis BarA/UvrY/CsrB regulatory cascade enhance biofilm stability without dramatically increasing Hms-ECM production. We found that treatment with proteinase K enzyme effectively destabilized Y. pseudotuberculosis csrB mutant biofilms, suggesting that cell-cell interactions might be mediated by protein adhesins or extracellular matrix proteins. We identified an uncharacterized trimeric autotransporter lipoprotein (YPTB2394), repressed by csrB, which has been referred to as YadE. Biofilms made by a ΔyadE mutant strain were extremely sensitive to mechanical disruption. Overexpression of yadE in wild-type Y. pseudotuberculosis increased biofilm cohesion, similar to biofilms made by csrB or uvrY mutants. We found that the Rcs signaling cascade, which represses Hms-ECM production, activated expression of yadE The yadE gene appears to be functional in Y. pseudotuberculosis but is a pseudogene in modern Y. pestis strains. Expression of functional yadE in Y. pestis KIM6+ weakened biofilms made by these bacteria. This suggests that although the YadE autotransporter protein increases Y. pseudotuberculosis biofilm stability, it may be incompatible with the Hms-ECM production that is essential for Y. pestis biofilm production in fleas. Inactivation of yadE in Y. pestis may be another instance of selective gene loss in the evolution of flea-borne transmission by this species.IMPORTANCE The evolution of Yersinia pestis from its Y. pseudotuberculosis ancestor involved gene acquisition and gene losses, leading to differences in biofilm production. Characterizing the unique biofilm features of both species may provide better understanding of how each adapts to its specific niches. This study identifies a trimeric autotransporter, YadE, that promotes biofilm stability of Y. pseudotuberculosis but which has been inactivated in Y. pestis, perhaps because it is not compatible with the Hms polysaccharide that is crucial for biofilms inside fleas. We also reveal that the Rcs signaling cascade, which represses Hms expression, activates YadE in Y. pseudotuberculosis The ability of Y. pseudotuberculosis to use polysaccharide or YadE protein for cell-cell adhesion may help it produce biofilms in different environments.

Fragment-based target screening as an empirical approach to prioritising targets: a case study on antibacterials

Here, we describe a novel workflow combining informatic and experimental approaches to enable evidence-based prioritising of targets from large sets in parallel. High-throughput protein production and biophysical fragment screening is used to identify those targets that are tractable and ligandable. As proof of concept we have applied this to a set of antibacterial targets comprising 146 essential genes. Of these targets, 51 were selected and 38 delivered results that allowed us to rank them by ligandability. The data obtained against these derisked targets have enabled rapid progression into structurally enabled drug discovery projects, demonstrating the practical value of the fragment-based target screening workflow.

Tn-Core: A Toolbox for Integrating Tn-seq Gene Essentiality Data and Constraint-Based Metabolic Modeling

The design of synthetic cells requires a detailed understanding of the relevance of genes and gene networks underlying complex cellular phenotypes. Transposon-sequencing (Tn-seq) and constraint-based metabolic modeling can be used to probe the core genetic and metabolic networks underlying a biological process. Integrating these highly complementary experimental and in silico approaches has the potential to yield a highly comprehensive understanding of the core networks of a cell. Specifically, it can facilitate the interpretation of Tn-seq data sets and identify gaps in the data that could hinder the engineering of the cellular system, while also providing refined models for the accurate predictions of cellular metabolism. Here, we present Tn-Core, the first easy-to-use computational pipeline specifically designed for integrating Tn-seq data with metabolic modeling, prepared for use by both experimental and computational biologists. Tn-Core is a MATLAB toolbox that contains several custom functions, and it is built upon existing functions within the COBRA Toolbox and the TIGER Toolbox. Tn-Core takes as input a genome-scale metabolic model, Tn-seq data, and optionally RNA-seq data, and returns: (i) a context-specific core metabolic model; (ii) an evaluation of redundancies within core metabolic pathways, and optionally (iii) a refined genome-scale metabolic model. A simple, user-friendly workflow, requiring limited knowledge of metabolic modeling, is provided that allows users to run the analyses and export the data as easy-to-explore files of value to both experimental and computational biologists. We demonstrate the utility of Tn-Core using Sinorhizobium meliloti, Pseudomonas aeruginosa, and Rhodobacter sphaeroides genome-scale metabolic reconstructions as case studies.

The Complex Rcs Regulatory Cascade

RcsB, a response regulator of the FixJ/NarL family, is at the center of a complex network of regulatory inputs and outputs. Cell surface stress is sensed by an outer membrane lipoprotein, RcsF, which regulates interactions of the inner membrane protein IgaA, lifting negative regulation of a phosphorelay. In vivo evidence supports a pathway in which histidine kinase RcsC transfers phosphate to phosphotransfer protein RcsD, resulting in phosphorylation of RcsB. RcsB acts either alone or in combination with RcsA to positively regulate capsule synthesis and synthesis of small RNA (sRNA) RprA as well as other genes, and to negatively regulate motility. RcsB in combination with other FixJ/NarL auxiliary proteins regulates yet other functions, independent of RcsB phosphorylation. Proper expression of Rcs and its targets is critical for success of Escherichia coli commensal strains, for proper development of biofilm, and for virulence in some pathogens. New understanding of how the Rcs phosphorelay works provides insight into the flexibility of the two-component system paradigm.

Robustness encoded across essential and accessory replicons of the ecologically versatile bacterium Sinorhizobium meliloti

Bacterial genome evolution is characterized by gains, losses, and rearrangements of functional genetic segments. The extent to which large-scale genomic alterations influence genotype-phenotype relationships has not been investigated in a high-throughput manner. In the symbiotic soil bacterium Sinorhizobium meliloti, the genome is composed of a chromosome and two large extrachromosomal replicons (pSymA and pSymB, which together constitute 45% of the genome). Massively parallel transposon insertion sequencing (Tn-seq) was employed to evaluate the contributions of chromosomal genes to growth fitness in both the presence and absence of these extrachromosomal replicons. Ten percent of chromosomal genes from diverse functional categories are shown to genetically interact with pSymA and pSymB. These results demonstrate the pervasive robustness provided by the extrachromosomal replicons, which is further supported by constraint-based metabolic modeling. A comprehensive picture of core S. meliloti metabolism was generated through a Tn-seq-guided in silico metabolic network reconstruction, producing a core network encompassing 726 genes. This integrated approach facilitated functional assignments for previously uncharacterized genes, while also revealing that Tn-seq alone missed over a quarter of wild-type metabolism. This work highlights the many functional dependencies and epistatic relationships that may arise between bacterial replicons and across a genome, while also demonstrating how Tn-seq and metabolic modeling can be used together to yield insights not obtainable by either method alone.

S. meliloti, which has traditionally facilitated ground-breaking insights into symbiotic communication, is also emerging as an excellent model for studying the evolution of functional relationships between bacterial chromosomes and anciently acquired accessory replicons. Multi-replicon genome architecture is present in ~ 10% of presently sequenced bacterial genomes. The S. meliloti genome is composed of three circular replicons, two of which are dispensable even though they encompass nearly half of the protein-coding genes in this organism. The construction of strains lacking these replicons has enabled a straightforward, genome-wide analysis of interactions between the chromosome and the non-essential replicons, revealing extensive functional cooperation between these genomic components. This analysis enabled a substantial refinement of a metabolic network model for S. meliloti. The integration of massively parallel genotype-phenotype screening with in silico metabolic reconstruction has enhanced our understanding of metabolic network structure as it relates to genome evolution in S. meliloti, and exemplifies an approach that may be productively applied to other taxa. The combined experimental and computational approach employed here further provides unique insights into the pervasive genetic interactions that may exist within large bacterial genomes.

Novel Genes Required for the Fitness of Streptococcus pyogenes in Human Saliva

Streptococcus pyogenes (group A streptococcus [GAS]) causes 600 million cases of pharyngitis each year. Despite this considerable disease burden, the molecular mechanisms used by GAS to infect, cause clinical pharyngitis, and persist in the human oropharynx are poorly understood. Saliva is ubiquitous in the human oropharynx and is the first material GAS encounters in the upper respiratory tract. Thus, a fuller understanding of how GAS survives and proliferates in saliva may provide valuable insights into the molecular mechanisms at work in the human oropharynx. We generated a highly saturated transposon insertion mutant library in serotype M1 strain MGAS2221, a strain genetically representative of a pandemic clone that arose in the 1980s and spread globally. The transposon mutant library was exposed to human saliva to screen for GAS genes required for wild-type fitness in this clinically relevant fluid. Using transposon-directed insertion site sequencing (TraDIS), we identified 92 genes required for GAS fitness in saliva. The more prevalent categories represented were genes involved in carbohydrate transport/metabolism, amino acid transport/metabolism, and inorganic ion transport/metabolism. Using six isogenic mutant strains, we confirmed that each of the mutants was significantly impaired for growth or persistence in human saliva ex vivo. Mutants with an inactivated Spy0644 (sptA) or Spy0646 (sptC) gene had especially severe persistence defects. This study is the first to use of TraDIS to study bacterial fitness in human saliva. The new information we obtained will be valuable for future translational maneuvers designed to prevent or treat human GAS infections. IMPORTANCE The human bacterial pathogen Streptococcus pyogenes (group A streptococcus [GAS]) causes more than 600 million cases of pharyngitis annually worldwide, 15 million of which occur in the United States. The human oropharynx is the primary anatomic site for GAS colonization and infection, and saliva is the first material encountered. Using a genome-wide transposon mutant screen, we identified 92 GAS genes required for wild-type fitness in human saliva. Many of the identified genes are involved in carbohydrate transport/metabolism, amino acid transport/metabolism, and inorganic ion transport/metabolism. The new information is potentially valuable for developing novel GAS therapeutics and vaccine research.