Genetic and Microbial Analysis of Invasiveness for Escherichia coli Strains Associated With Inflammatory Bowel Disease

BACKGROUND & AIMS

The adherent-invasive Escherichia coli (AIEC) pathotype is implicated in inflammatory bowel disease (IBD) pathogenesis. AIEC strains are currently defined by phenotypic measurement of their pathogenicity, including invasion of epithelial cells. This broad definition, combined with the genetic diversity of AIEC across patients with IBD, has complicated the identification of virulence determinants. We sought to quantify the invasion phenotype of clinical isolates from patients with IBD and identify the genetic basis for their invasion into epithelial cells.

METHODS

A pangenome with core and accessory genes (genotype) was assembled using whole genome sequencing of 168 E coli samples isolated from 13 patients with IBD. A modified assay for invasion of epithelial cells (phenotype) was established with consideration of antibiotic resistance phenotypes. Isolate genotype was correlated to invasiveness phenotype to identify genetic factors that cosegregate with invasion.

RESULTS

Pangenome-wide comparisons of E coli clinical isolates identified accessory genes that can cosegregate with invasion phenotype. These correlations found the acquisition of antibiotic resistance genes in clinical isolates compromised the traditional gentamicin protection assays used to quantify invasion. Therefore, an alternate assay, based on amikacin resistance, identified genes cosegregating with invasion. These genes encode an arylsulfatase, a glycoside hydrolase, and genetic islands carrying propanediol utilization and sulfoquinovose metabolism pathways.

CONCLUSIONS

This study highlights the importance of incorporating antibiotic resistance screening for invasion assays used in AIEC identification. Accurately screened invasion phenotypes identified accessory genome elements among E coli IBD isolates that correlate with their ability to invade epithelial cells. These results help explain why single genetic markers for the AIEC phylotype are challenging to identify.

Diagnosis and mitigation of the systemic impact of genome reduction in Escherichia coli DGF-298

Microorganisms with simplified genomes represent interesting cell chassis for systems and synthetic biology. However, genome reduction can lead to undesired traits, such as decreased growth rate and metabolic imbalances. To investigate the impact of genome reduction on Escherichia coli strain DGF-298, a strain in which ~ 36% of the genome has been removed, we reconstructed a strain-specific metabolic model (iAC1061), investigated the regulation of gene expression using iModulon-based transcriptome analysis, and performed adaptive laboratory evolution to let the strain correct potential imbalances that arose during its simplification. The model notably predicted that the removal of all three key pathways for glycolaldehyde disposal in this microorganism would lead to a metabolic bottleneck through folate starvation. Glycolaldehyde is also known to cause self-generation of reactive oxygen species, as evidenced by the increased expression of oxidative stress resistance genes in the SoxS iModulon. The reintroduction of the aldA gene, responsible for one native glycolaldehyde disposal route, alleviated the constitutive oxidative stress response. Our results suggest that systems-level approaches and adaptive laboratory evolution have additive benefits when trying to repair and optimize genome-engineered strains.

IMPORTANCE

Genomic streamlining can be employed in model organisms to reduce complexity and enhance strain predictability. One of the most striking examples is the bacterial strain Escherichia coli DGF-298, notable for having over one-third of its genome deleted. However, such extensive genome modifications raise the question of how similar this simplified cell remains when compared with its parent, and what are the possible unintended consequences of this simplification. In this study, we used metabolic modeling along with iModulon-based transcriptomic analysis in different growth conditions to assess the impact of genome reduction on metabolism and gene regulation. We observed little impact of genomic reduction on the regulatory network of E. coli DGF-298 and identified a potential metabolic bottleneck leading to the constitutive activity of the SoxS iModulon. We then leveraged the model's predictions to successfully restore SoxS activity to the basal level.

Unveiling a Comprehensive Multi-epitope Subunit Vaccine Strategy Against Salmonella subsp. enterica: Bridging Core, Subtractive Proteomics, and Immunoinformatics

Salmonella subsp. enterica (SE) presents a significant global health challenge in both developed and developing countries. Current SE vaccines have limitations, targeting specific strains and demonstrating moderate efficacy in adults, while also being unsuitable for young children and often unaffordable in regions with lower income levels where the disease is prevalent. To address these challenges, this study employed a computational approach integrating core proteomics, subtractive proteomics, and immunoinformatics to develop a universal SE vaccine and identify potential drug targets. Analysis of the core proteome of 185 SE strains revealed 1964 conserved proteins. Subtractive proteomics identified 9 proteins as potential vaccine candidates and 41 as novel drug targets. Using reverse vaccinology-based immunoinformatics, four multi-epitope-based subunit vaccine constructs (MESVCs) were designed, aiming to stimulate cytotoxic T lymphocyte, helper T lymphocyte, and linear B lymphocyte responses. These constructs underwent comprehensive evaluations for antigenicity, immunogenicity, toxicity, hydropathicity, and physicochemical properties. Predictive modeling, refinement, and validation were conducted to determine the secondary and tertiary structures of the SE-MESVCs, followed by docking studies with MHC-I, MHC-II, and TLR4 receptors. Molecular docking assessments showed favorable binding with all three receptors, with SE-MESVC-4 exhibiting the most promising binding energy. Molecular dynamics simulations confirmed the binding affinity and stability of SE-MESVC-4 with the TLR4/MD2 complex. Additionally, codon optimization and in silico cloning verified the efficient translation and successful expression of SE-MESVC-4 in Escherichia coli (E. coli) str. K12. Subsequent in silico immune simulation evaluated the efficacy of SE-MESVC-4 in triggering an effective immune response. These results suggest that SE-MESVC-4 may induce both humoral and cellular immune responses, making it a potential candidate for an effective SE vaccine. However, further experimental investigations are necessary to validate the immunogenicity and efficacy of SE-MESVC-4, bringing us closer to effectively combating SE infections.

Comparative genomics reveals insights into the potential of Lysinibacillus irui as a plant growth promoter

Members of the genus Lysinibacillus attract attention for their mosquitocidal, bioremediation, and plant growth-promoting abilities. Despite this interest, comprehensive studies focusing on genomic traits governing plant growth and stress resilience in this genus using whole-genome sequencing are still scarce. Therefore, we sequenced and compared the genomes of three endophytic Lysinibacillus irui strains isolated from Canary Island date palms with the ex-type strain IRB4-01. Overall, the genomes of these strains consist of a circular chromosome with an average size of 4.6 Mb and a GC content of 37.2%. Comparative analysis identified conserved gene clusters within the core genome involved in iron acquisition, phosphate solubilization, indole-3-acetic acid biosynthesis, and volatile compounds. In addition, genome analysis revealed the presence of genes encoding carbohydrate-active enzymes, and proteins that confer resistance to oxidative, osmotic, and salinity stresses. Furthermore, pathways of putative novel bacteriocins were identified in all genomes. This illustrates possible common plant growth-promoting traits shared among all strains of L. irui. Our findings highlight a rich repertoire of genes associated with plant lifestyles, suggesting significant potential for developing inoculants to enhance plant growth and resilience. This study is the first to provide insights into the overall genomic signatures and mechanisms of plant growth promotion and biocontrol in the genus Lysinibacillus. KEY POINTS: • Pioneer study in elucidating plant growth promoting in L. irui through comparative genomics. • Genome mining identified biosynthetic pathways of putative novel bacteriocins. • Future research directions to develop L. irui-based biofertilizers for sustainable agriculture.

Advancements in synthetic biology-based bacterial cancer therapy: A modular design approach

Synthetic biology aims to program living bacteria cells with artificial genetic circuits for user-defined functions, transforming them into powerful tools with numerous applications in various fields, including oncology. Cancer treatments have serious side effects on patients due to the systemic action of the drugs involved. To address this, new systems that provide localized antitumoral action while minimizing damage to healthy tissues are required. Bacteria, often considered pathogenic agents, have been used as cancer treatments since the early 20th century. Advances in genetic engineering, synthetic biology, microbiology, and oncology have improved bacterial therapies, making them safer and more effective. Here we propose six modules for a successful synthetic biology-based bacterial cancer therapy, the modules include Payload, Release, Tumor-targeting, Biocontainment, Memory, and Genetic Circuit Stability Module. These will ensure antitumor activity, safety for the environment and patient, prevent bacterial colonization, maintain cell stability, and prevent loss or defunctionalization of the genetic circuit.

Comparative genomics reveals the acquisition of mobile genetic elements by the plant growth-promoting Pantoea eucrina OB49 in polluted environments

Heavy metal-tolerant plant growth-promoting bacteria (PGPB) have gained popularity in bioremediation in recent years. A genome-assisted study of a heavy metal-tolerant PGPB Pantoea eucrina OB49 isolated from the rhizosphere of wheat grown on a heavy metal-contaminated site is presented. Comparative pan-genome analysis indicated that OB49 acquired heavy metal resistance genes through horizontal gene transfer. On contigs S10 and S12, OB49 has two arsRBCH operons that give arsenic resistance. On the S12 contig, an arsRBCH operon was discovered in conjunction with the merRTPCADE operon, which provides mercury resistance. P. eucrina OB49 may be involved in an ecological alternative for heavy metal remediation and growth promotion of wheat grown in metal-polluted soils. Our results suggested the detection of mobile genetic elements that harbour the ars operon and the fluoride resistance genes adjacent to the mer operon.

Avian strains of emerging pathogen Escherichia fergusonii are phylogenetically diverse and harbor the greatest AMR dissemination potential among different sources: Comparative genomic evidence

Introduction

Escherichia fergusonii is regarded as an emerging pathogen with zoonotic potential. In the current study, we undertook source-wise comparative genomic analyses (resistome, virulome, mobilome and pangenome) to understand the antimicrobial resistance, virulence, mobile genetic elements and phylogenetic diversity of E. fergusonii.

Methods

Six E. fergusonii strains (5 multidrug resistant strains and 1 biofilm former) were isolated from poultry (duck faeces and retail chicken samples). Following confirmation by phenotypic and molecular methods, the isolates were further characterized and their genomes were sequenced. Comparative resisto-virulo-mobilome analyses and pangenomics were performed for E. fergusonii genomes, while including 125 other E. fergusonii genomes available from NCBI database.

Results and discussion

Avian and porcine strains of E. fergusonii were found to carry significantly higher number of antimicrobial resistance genes (p < 0.05) and mobile genetic elements (plasmids, transposons and integrons) (p < 0.05), while the pathogenic potential of bovine strains was significantly higher compared to other strains (p < 0.05). Pan-genome development trends indicated open pan-genome for all strains (0 < γ < 1). Genomic diversity of avian strains was found to be greater than that from other sources. Phylogenetic analysis revealed close clustering among isolates of similar isolation source and geographical location. Indian isolates of E. fergusonii clustered closely with those from Chinese and a singleton Australian isolate. Overall, being the first pangenomic study on E. fergusonii, our analysis provided important cues on genomic features of the emerging pathogen E. fergusonii while highlighting the potential role of avian strains in dissemination of AMR.

IPGA: A handy integrated prokaryotes genome and pan-genome analysis web service

Pan-genomics is one of the most powerful means to study genomic variation and obtain a sketch of genes within a defined clade of species. Though there are a lot of computational tools to achieve this, an integrated framework to evaluate their performance and offer the best choice to users has never been achieved. To ease the process of large-scale prokaryotic genome analysis, we introduce Integrated Prokaryotes Genome and pan-genome Analysis (IPGA), a one-stop web service to analyze, compare, and visualize pan-genome as well as individual genomes, that rids users of installing any specific tools. IPGA features a scoring system that helps users to evaluate the reliability of pan-genome profiles generated by different packages. Thus, IPGA can help users ascertain the profiling method that is most suitable for their data set for the following analysis. In addition, IPGA integrates several downstream comparative analysis and genome analysis modules to make users achieve diverse targets.

High-quality pan-genome of Escherichia coli generated by excluding confounding and highly similar strains reveals an association between unique gene clusters and genomic islands

The pan-genome analysis of bacteria provides detailed insight into the diversity and evolution of a bacterial population. However, the genomes involved in the pan-genome analysis should be checked carefully, as the inclusion of confounding strains would have unfavorable effects on the identification of core genes, and the highly similar strains could bias the results of the pan-genome state (open versus closed). In this study, we found that the inclusion of highly similar strains also affects the results of unique genes in pan-genome analysis, which leads to a significant underestimation of the number of unique genes in the pan-genome. Therefore, these strains should be excluded from pan-genome analysis at the early stage of data processing. Currently, tens of thousands of genomes have been sequenced for Escherichia coli, which provides an unprecedented opportunity as well as a challenge for pan-genome analysis of this classical model organism. Using the proposed strategies, a high-quality E. coli pan-genome was obtained, and the unique genes was extracted and analyzed, revealing an association between the unique gene clusters and genomic islands from a pan-genome perspective, which may facilitate the identification of genomic islands.

To kill or to be killed: pangenome analysis of Escherichia coli strains reveals a tailocin specific for pandemic ST131

BACKGROUND

Escherichia coli (E. coli) has been one of the most studied model organisms in the history of life sciences. Initially thought just to be commensal bacteria, E. coli has shown wide phenotypic diversity including pathogenic isolates with great relevance to public health. Though pangenome analysis has been attempted several times, there is no systematic functional characterization of the E. coli subgroups according to the gene profile.

RESULTS

Systematically scanning for optimal parametrization, we have built the E. coli pangenome from 1324 complete genomes. The pangenome size is estimated to be ~25,000 gene families (GFs). Whereas the core genome diminishes as more genomes are added, the softcore genome (≥95% of strains) is stable with ~3000 GFs regardless of the total number of genomes. Apparently, the softcore genome (with a 92% or 95% generation threshold) can define the genome of a bacterial species listing the critically relevant, evolutionarily most conserved or important classes of GFs. Unsupervised clustering of common E. coli sequence types using the presence/absence GF matrix reveals distinct characteristics of E. coli phylogroups B1, B2, and E. We highlight the bi-lineage nature of B1, the variation of the secretion and of the iron acquisition systems in ST11 (E), and the incorporation of a highly conserved prophage into the genome of ST131 (B2). The tail structure of the prophage is evolutionarily related to R2-pyocin (a tailocin) from Pseudomonas aeruginosa PAO1. We hypothesize that this molecular machinery is highly likely to play an important role in protecting its own colonies; thus, contributing towards the rapid rise of pandemic E. coli ST131.

CONCLUSIONS

This study has explored the optimized pangenome development in E. coli. We provide complete GF lists and the pangenome matrix as supplementary data for further studies. We identified biological characteristics of different E. coli subtypes, specifically for phylogroups B1, B2, and E. We found an operon-like genome region coding for a tailocin specific for ST131 strains. The latter is a potential killer weapon providing pandemic E. coli ST131 with an advantage in inter-bacterial competition and, suggestively, explains their dominance as human pathogen among E. coli strains.

Genome-Scale Metabolic Modeling Enables In-Depth Understanding of Big Data

Genome-scale metabolic models (GEMs) enable the mathematical simulation of the metabolism of archaea, bacteria, and eukaryotic organisms. GEMs quantitatively define a relationship between genotype and phenotype by contextualizing different types of Big Data (e.g., genomics, metabolomics, and transcriptomics). In this review, we analyze the available Big Data useful for metabolic modeling and compile the available GEM reconstruction tools that integrate Big Data. We also discuss recent applications in industry and research that include predicting phenotypes, elucidating metabolic pathways, producing industry-relevant chemicals, identifying drug targets, and generating knowledge to better understand host-associated diseases. In addition to the up-to-date review of GEMs currently available, we assessed a plethora of tools for developing new GEMs that include macromolecular expression and dynamic resolution. Finally, we provide a perspective in emerging areas, such as annotation, data managing, and machine learning, in which GEMs will play a key role in the further utilization of Big Data.

Natural Bred ε2-Phages Have an Improved Host Range and Virulence against Uropathogenic Escherichia coli over Their Ancestor Phages

Alternative treatments for Escherichia coli infections are urgently needed, and phage therapy is a promising option where antibiotics fail, especially for urinary tract infections (UTI). We used wastewater-isolated phages to test their lytic activity against a panel of 47 E. coli strains reflecting the diversity of strains found in UTI, including sequence type 131, 73 and 69. The plaquing host range (PHR) was between 13 and 63%. In contrast, the kinetic host range (KHR), describing the percentage of strains for which growth in suspension was suppressed for 24 h, was between 0% and 19%, substantially lower than the PHR. To improve the phage host range and their efficacy, we bred the phages by mixing and propagating cocktails on a subset of E. coli strains. The bred phages, which we termed evolution-squared ε2-phages, of a mixture of Myoviridae have KHRs up to 23% broader compared to their ancestors. Furthermore, using constant phage concentrations, Myoviridae ε2-phages suppressed the growth of higher bacterial inocula than their ancestors did. Thus, the ε2-phages were more virulent compared to their ancestors. Analysis of the genetic sequences of the ε2-phages with the broadest host range reveals that they are mosaic intercrossings of 2-3 ancestor phages. The recombination sites are distributed over the whole length of the genome. All ε2-phages are devoid of genes conferring lysogeny, antibiotic resistance, or virulence. Overall, this study shows that ε2-phages are remarkably more suitable than the wild-type phages for phage therapy.

Investigation of the Genes Involved in the Outbreaks of Escherichia coli and Salmonella spp. in the United States

Salmonella spp. and Escherichiacoli (E. coli) are two of the deadliest foodborne pathogens in the US. Genes involved in antimicrobial resistance, virulence, and stress response, enable these pathogens to increase their pathogenicity. This study aims to examine the genes detected in both outbreak and non-outbreak Salmonella spp. and E. coli by analyzing the data from the National Centre for Biotechnology Information (NCBI) Pathogen Detection Isolates Browser database. A multivariate statistical analysis was conducted on the genes detected in isolates of outbreak Salmonella spp., non-outbreak Salmonella spp., outbreak E. coli, and non-outbreak E. coli. The genes from the data were projected onto a two-dimensional space through principal component analysis. Hierarchical clustering was then used to quantify the relationship between the genes in the dataset. Most of the outlier genes identified in E. coli isolates are virulence genes, while outlier genes identified in Salmonella spp. are mainly involved in stress response. Gene epeA, which encodes a high-molecular-weight serine protease autotransporter of Enterobacteriaceae (SPATE) protein, along with subA and subB that encode cytotoxic activity, may contribute to the pathogenesis of outbreak E. coli. The iro operon and ars operon may play a role in the ecological success of the epidemic clones of Salmonella spp. Concurrent relationships between esp and ter operons in E. coli and pco and sil operons in Salmonella spp. are found. Stress-response genes (asr, golT, golS), virulence gene (sinH), and antimicrobial resistance genes (mdsA and mdsB) in Salmonella spp. also show a concurrent relationship. All these findings provide helpful information for experiment design to combat outbreaks of E. coli and Salmonella spp.

Complete Genome Sequence of Weissella confusa LM1 and Comparative Genomic Analysis

The genus Weissella is attracting an increasing amount of attention because of its multiple functions and probiotic potential. In particular, the species Weissella confusa is known to have great potential in industrial applications and exhibits numerous biological functions. However, the knowledge on this bacterium in insects is not investigated. Here, we isolated and identified W. confusa as the dominant lactic acid bacteria in the gut of the migratory locust. We named this strain W. confusa LM1, which is the first genome of an insect-derived W. confusa strain with one complete chromosome and one complete plasmid. Among all W. confusa strains, W. confusa LM1 had the largest genome. Its genome was the closest to that of W. confusa 1001271B_151109_G12, a strain from human feces. Our results provided accurate evolutionary relationships of known Weissella species and W. confusa strains. Based on genomic analysis, the pan-genome of W. confusa is in an open state. Most strains of W. confusa had the unique genes, indicating that these strains can adapt to different ecological niches and organisms. However, the variation of strain-specific genes did represent significant correlations with their hosts and ecological niches. These strains were predicted to have low potential to produce secondary metabolites. Furthermore, no antibiotic resistance genes were identified. At the same time, virulence factors associated with toxin production and secretion system were not found, indicating that W. confusa strains were not sufficient to perform virulence. Our study facilitated the discovery of the functions of W. confusa LM1 in locust biology and their potential application to locust management.

A pan-genome method to determine core regions of the Bacillus subtilis and Escherichia coli genomes

Background: Synthetic engineering of bacteria to produce industrial products is a burgeoning field of research and application. In order to optimize genome design, designers need to understand which genes are essential, which are optimal for growth, and locations in the genome that will be tolerated by the organism when inserting engineered cassettes.

Methods: We present a pan-genome based method for the identification of core regions in a genome that are strongly conserved at the species level.

Results: We show that the core regions determined by our method contain all or almost all essential genes. This demonstrates the accuracy of our method as essential genes should be core genes. We show that we outperform previous methods by this measure. We also explain why there are exceptions to this rule for our method.

Conclusions: We assert that synthetic engineers should avoid deleting or inserting into these core regions unless they understand and are manipulating the function of the genes in that region. Similarly, if the designer wishes to streamline the genome, non-core regions and in particular low penetrance genes would be good targets for deletion. Care should be taken to remove entire cassettes with similar penetrance of the genes within cassettes as they may harbor toxin/antitoxin genes which need to be removed in tandem. The bioinformatic approach introduced here saves considerable time and effort relative to knockout studies on single isolates of a given species and captures a broad understanding of the conservation of genes that are core to a species.

A pan-genome method to determine core regions of the Bacillus subtilis and Escherichia coli genomes

Background: Synthetic engineering of bacteria to produce industrial products is a burgeoning field of research and application. In order to optimize genome design, designers need to understand which genes are essential, which are optimal for growth, and locations in the genome that will be tolerated by the organism when inserting engineered cassettes. Methods: We present a pan-genome based method for the identification of core regions in a genome that are strongly conserved at the species level. Results: We show that the core regions determined by our method contain all or almost all essential genes. This demonstrates the accuracy of our method as essential genes should be core genes. We show that we outperform previous methods by this measure. We also explain why there are exceptions to this rule for our method. Conclusions: We assert that synthetic engineers should avoid deleting or inserting into these core regions unless they understand and are manipulating the function of the genes in that region. Similarly, if the designer wishes to streamline the genome, non-core regions and in particular low penetrance genes would be good targets for deletion. Care should be taken to remove entire cassettes with similar penetrance of the genes within cassettes as they may harbor toxin/antitoxin genes which need to be removed in tandem. The bioinformatic approach introduced here saves considerable time and effort relative to knockout studies on single isolates of a given species and captures a broad understanding of the conservation of genes that are core to a species.

Genomic Characterization Provides an Insight into the Pathogenicity of the Poplar Canker Bacterium Lonsdalea populi

An emerging poplar canker caused by the gram-negative bacterium, Lonsdalea populi, has led to high mortality of hybrid poplars Populus × euramericana in China and Europe. The molecular bases of pathogenicity and bark adaptation of L. populi have become a focus of recent research. This study revealed the whole genome sequence and identified putative virulence factors of L. populi. A high-quality L. populi genome sequence was assembled de novo, with a genome size of 3,859,707 bp, containing approximately 3434 genes and 107 RNAs (75 tRNA, 22 rRNA, and 10 ncRNA). The L. populi genome contained 380 virulence-associated genes, mainly encoding for adhesion, extracellular enzymes, secretory systems, and two-component transduction systems. The genome had 110 carbohydrate-active enzyme (CAZy)-coding genes and putative secreted proteins. The antibiotic-resistance database annotation listed that L. populi was resistant to penicillin, fluoroquinolone, and kasugamycin. Analysis of comparative genomics found that L. populi exhibited the highest homology with the L. britannica genome and L. populi encompassed 1905 specific genes, 1769 dispensable genes, and 1381 conserved genes, suggesting high evolutionary diversity and genomic plasticity. Moreover, the pan genome analysis revealed that the N-5-1 genome is an open genome. These findings provide important resources for understanding the molecular basis of the pathogenicity and biology of L. populi and the poplar-bacterium interaction.

Distinguishing Pathovars from Nonpathovars: Escherichia coli

Escherichia coli is one of the most well-adapted and pathogenically versatile bacterial organisms. It causes a variety of human infections, including gastrointestinal illnesses and extraintestinal infections. It is also part of the intestinal commensal flora of humans and other mammals. Groups of E. coli that cause diarrhea are often described as intestinal pathogenic E. coli (IPEC), while those that cause infections outside of the gut are called extraintestinal pathogenic E. coli (ExPEC). IPEC can cause a variety of diarrheal illnesses as well as extraintestinal syndromes such as hemolytic-uremic syndrome. ExPEC cause urinary tract infections, bloodstream infection, sepsis, and neonatal meningitis. IPEC and ExPEC have thus come to be referred to as pathogenic variants of E. coli or pathovars. While IPEC can be distinguished from commensal E. coli based on their characteristic virulence factors responsible for their associated clinical manifestations, ExPEC cannot be so easily distinguished. IPEC most likely have reservoirs outside of the human intestine but it is unclear if ExPEC represent nothing more than commensal E. coli that breach a sterile barrier to cause extraintestinal infections. This question has become more complicated by the advent of whole genome sequencing (WGS) that has raised a new question about the taxonomic characterization of E. coli based on traditional clinical microbiologic and phylogenetic methods. This review discusses how molecular epidemiologic approaches have been used to address these questions, and how answers to these questions may contribute to our better understanding of the epidemiology of infections caused by E. coli. *This article is part of a curated collection.

Reconstructing organisms in silico: genome-scale models and their emerging applications

Escherichia coli is considered to be the best-known microorganism given the large number of published studies detailing its genes, its genome and the biochemical functions of its molecular components. This vast literature has been systematically assembled into a reconstruction of the biochemical reaction networks that underlie E. coli's functions, a process which is now being applied to an increasing number of microorganisms. Genome-scale reconstructed networks are organized and systematized knowledge bases that have multiple uses, including conversion into computational models that interpret and predict phenotypic states and the consequences of environmental and genetic perturbations. These genome-scale models (GEMs) now enable us to develop pan-genome analyses that provide mechanistic insights, detail the selection pressures on proteome allocation and address stress phenotypes. In this Review, we first discuss the overall development of GEMs and their applications. Next, we review the evolution of the most complete GEM that has been developed to date: the E. coli GEM. Finally, we explore three emerging areas in genome-scale modelling of microbial phenotypes: collections of strain-specific models, metabolic and macromolecular expression models, and simulation of stress responses.

A systematic strategy for the investigation of vaccines and drugs targeting bacteria

Infectious and epidemic diseases induced by bacteria have historically caused great distress to people, and have even resulted in a large number of deaths worldwide. At present, many researchers are working on the discovery of viable drug and vaccine targets for bacteria through multiple methods, including the analyses of comparative subtractive genome, core genome, replication-related proteins, transcriptomics and riboswitches, which plays a significant part in the treatment of infectious and pandemic diseases. The 3D structures of the desired target proteins, drugs and epitopes can be predicted and modeled through target analysis. Meanwhile, molecular dynamics (MD) analysis of the constructed drug/epitope-protein complexes is an important standard for testing the suitability of these screened drugs and vaccines. Currently, target discovery, target analysis and MD analysis are integrated into a systematic set of drug and vaccine analysis strategy for bacteria. We hope that this comprehensive strategy will help in the design of high-performance vaccines and drugs.

Comprehensive Genome Analysis on the Novel Species Sphingomonas panacis DCY99T Reveals Insights into Iron Tolerance of Ginseng

Plant growth-promoting rhizobacteria play vital roles not only in plant growth, but also in reducing biotic/abiotic stress. Sphingomonas panacis DCY99T is isolated from soil and root of Panax ginseng with rusty root disease, characterized by raised reddish-brown root and this is seriously affects ginseng cultivation. To investigate the relationship between 159 sequenced Sphingomonas strains, pan-genome analysis was carried out, which suggested genomic diversity of the Sphingomonas genus. Comparative analysis of S. panacis DCY99T with Sphingomonas sp. LK11 revealed plant growth-promoting potential of S. panacis DCY99T through indole acetic acid production, phosphate solubilizing, and antifungal abilities. Detailed genomic analysis has shown that S. panacis DCY99T contain various heavy metals resistance genes in its genome and the plasmid. Functional analysis with Sphingomonas paucimobilis EPA505 predicted that S. panacis DCY99T possess genes for degradation of polyaromatic hydrocarbon and phenolic compounds in rusty-ginseng root. Interestingly, when primed ginseng with S. panacis DCY99T during high concentration of iron exposure, iron stress of ginseng was suppressed. In order to detect S. panacis DCY99T in soil, biomarker was designed using spt gene. This study brings new insights into the role of S. panacis DCY99T as a microbial inoculant to protect ginseng plants against rusty root disease.

Toward a high-quality pan-genome landscape of Bacillus subtilis by removal of confounding strains

Pan-genome analysis is widely used to study the evolution and genetic diversity of species, particularly in bacteria. However, the impact of strain selection on the outcome of pan-genome analysis is poorly understood. Furthermore, a standard protocol to ensure high-quality pan-genome results is lacking. In this study, we carried out a series of pan-genome analyses of different strain sets of Bacillus subtilis to understand the impact of various strains on the performance and output quality of pan-genome analyses. Consequently, we found that the results obtained by pan-genome analyses of B. subtilis can be influenced by the inclusion of incorrectly classified Bacillus subspecies strains, phylogenetically distinct strains, engineered genome-reduced strains, chimeric strains, strains with a large number of unique genes or a large proportion of pseudogenes, and multiple clonal strains. Since the presence of these confounding strains can seriously affect the quality and true landscape of the pan-genome, we should remove these deviations in the process of pan-genome analyses. Our study provides new insights into the removal of biases from confounding strains in pan-genome analyses at the beginning of data processing, which enables the achievement of a closer representation of a high-quality pan-genome landscape of B. subtilis that better reflects the performance and credibility of the B. subtilis pan-genome. This procedure could be added as an important quality control step in pan-genome analyses for improving the efficiency of analyses, and ultimately contributing to a better understanding of genome function, evolution and genome-reduction strategies for B. subtilis in the future.

High Genomic Diversity and Heterogenous Origins of Pathogenic and Antibiotic-Resistant Escherichia coli in Household Settings Represent a Challenge to Reducing Transmission in Low-Income Settings

Escherichia coli is present in multiple hosts and environmental compartments as a normal inhabitant, temporary or persistent colonizer, and as a pathogen. Transmission of E. coli between hosts and with the environment is considered to occur more often in areas with poor sanitation. We performed whole-genome comparative analyses on 60 E. coli isolates from soils and fecal sources (cattle, chickens, and humans) in households in rural Bangladesh. Isolates from household soils were in multiple branches of the reconstructed phylogeny, intermixed with isolates from fecal sources. Pairwise differences between all strain pairs were large (minimum, 189 single nucleotide polymorphisms [SNPs]), suggesting high diversity and heterogeneous origins of the isolates. The presence of multiple virulence and antibiotic resistance genes is indicative of the risk that E. coli from soil and feces represent for the transmission of variants that pose potential harm to people. Analysis of the accessory genomes of the Bangladeshi E. coli relative to E. coli genomes available in NCBI identified a common pool of accessory genes shared among E. coli isolates in this geographic area. Together, these findings indicate that in rural Bangladesh, a high level of E. coli in soil is likely driven by contributions from multiple and diverse E. coli sources (human and animal) that share an accessory gene pool relatively unique to previously published E. coli genomes. Thus, interventions to reduce environmental pathogen or antimicrobial resistance transmission should adopt integrated One Health approaches that consider heterogeneous origins and high diversity to improve effectiveness and reduce prevalence and transmission.IMPORTANCEEscherichia coli is reported in high levels in household soil in low-income settings. When E. coli reaches a soil environment, different mechanisms, including survival, clonal expansion, and genetic exchange, have the potential to either maintain or generate E. coli variants with capabilities of causing harm to people. In this study, we used whole-genome sequencing to identify that E. coli isolates collected from rural Bangladeshi household soils, including pathogenic and antibiotic-resistant variants, are diverse and likely originated from multiple diverse sources. In addition, we observed specialization of the accessory genome of this Bangladeshi E. coli compared to E. coli genomes available in current sequence databases. Thus, to address the high level of pathogenic and antibiotic-resistant E. coli transmission in low-income settings, interventions should focus on addressing the heterogeneous origins and high diversity.