Metagenomics-Based, Strain-Level Analysis of Escherichia coli From a Time-Series of Microbiome Samples From a Crohn's Disease Patient

The global stress response regulator oxyS in an adherent-invasive Escherichia coli strain attenuates experimental colitis

Crohn's disease and ulcerative colitis in humans and experimental immune-mediated colitis in mice are likely due in part to overactive immune responses to resident intestinal bacteria, including certain strains of adherent-invasive Escherichia coli (E. coli) such as E. coli NC101. We have previously shown that specific E. coli NC101 stress responses are upregulated during experimental colitis and attenuate inflammation. However, the roles of broader stress response pathways in E. coli NC101 during experimental colitis are unknown. We hypothesize that the global stress response regulator in E. coli, oxyS, also reduces experimental colitis. We show that intestinal E. coli NC101 upregulate oxyS expression during colitis in monocolonized interleukin-10 deficient mice. Furthermore, we demonstrate that oxyS-sufficient E. coli NC101 have decreased motility and biofilm formation in vitro and attenuated intestinal translocation and colitogenic potential in vivo compared with oxyS-deficient E. coli. These data suggest that activation of a generalized E. coli stress response, oxyS, reduces experimental colitis and may be a potential therapeutic target.

Scaling metabolic model reconstruction up to the pan-genome level: A systematic review and prospective applications to photosynthetic organisms

Advances in genomics technologies have generated large data sets that provide tremendous insights into the genetic diversity of taxonomic groups. However, it remains challenging to pinpoint the effect of genetic diversity on different traits without performing resource-intensive phenotyping experiments. Pan-genome-scale metabolic models (panGEMs) extend traditional genome-scale metabolic models by considering the entire reaction repertoire that enables the prediction and comparison of metabolic capabilities within a taxonomic group. Here, we systematically review the state-of-the-art methodologies for constructing panGEMs, focusing on used tools, databases, experimental datasets, and orthology relationships. We highlight the unique advantages of panGEMs compared to single-species GEMs in predicting metabolic phenotypes and in guiding the experimental validation of genome annotations. In addition, we emphasize the disparity between the available (pan-)genomic data on photosynthetic organisms and their under-representation in current (pan)GEMs. Finally, we propose a perspective for tackling the reconstruction of panGEMs for photosynthetic eukaryotes that can help advance our understanding of the metabolic diversity in this taxonomic group.

Systematic review of bidirectional interaction between gut microbiome, miRNAs, and human pathologies

MicroRNAs (miRNAs) and the gut microbiome are key regulators of human health, with emerging evidence highlighting their complex, bidirectional interactions in chronic diseases. miRNAs, influence gene expression and can modulate the composition and function of the gut microbiome, impacting metabolic and immune processes. Conversely, the microbiome can affect host miRNA expression, influencing inflammatory pathways and disease susceptibility. This systematic review examines recent studies (2020-2024) focusing exclusively on human subjects, selected through rigorous inclusion and exclusion criteria. Studies were included if they investigated the interaction between miRNAs and the gut microbiome in the context of gastrointestinal diseases, obesity, autoimmune diseases, cognitive and neurodegenerative disorders, and autism. In vitro, in vivo and in silico analyses were excluded to ensure a strong translational focus on human pathophysiology. Notably, miRNAs, stable and abundant in patients, are emerging as promising biomarkers of microbiome-driven inflammation. This systematic review provides an overview of miRNAs, their regulatory effects on bacterial strains, and their associations with specific diseases. It also explores therapeutic advances and the potential of miRNA-based therapies to restore microbial balance and reduce inflammation.

Applications of genome-scale metabolic models to the study of human diseases: A systematic review

BACKGROUND AND OBJECTIVES

Genome-scale metabolic networks (GEMs) represent a valuable modeling and computational tool in the broad field of systems biology. Their ability to integrate constraints and high-throughput biological data enables the study of intricate metabolic aspects and processes of different cell types and conditions. The past decade has witnessed an increasing number and variety of applications of GEMs for the study of human diseases, along with a huge effort aimed at the reconstruction, integration and analysis of a high number of organisms. This paper presents a systematic review of the scientific literature, to pursue several important questions about the application of constraint-based modeling in the investigation of human diseases. Hopefully, this paper will provide a useful reference for researchers interested in the application of modeling and computational tools for the investigation of metabolic-related human diseases.

METHODS

This systematic review was conducted according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Elsevier Scopus®, National Library of Medicine PubMed® and Clarivate Web of Science™ databases were enquired, resulting in 566 scientific articles. After applying exclusion and eligibility criteria, a total of 169 papers were selected and individually examined.

RESULTS

The reviewed papers offer a thorough and up-to-date picture of the latest modeling and computational approaches, based on genome-scale metabolic models, that can be leveraged for the investigation of a large variety of human diseases. The numerous studies have been categorized according to the clinical research area involved in the examined disease. Furthermore, the paper discusses the most typical approaches employed to derive clinically-relevant information using the computational models.

CONCLUSIONS

The number of scientific papers, utilizing GEM-based approaches for the investigation of human diseases, suggests an increasing interest in these types of approaches; hopefully, the present review will represent a useful reference for scientists interested in applying computational modeling approaches to investigate the aetiopathology of human diseases; we also hope that this work will foster the development of novel applications and methods for the discovery of clinically-relevant insights on metabolic-related diseases.

A single rare σ70 variant establishes a unique gene expression pattern in the E. coli pathobiont LF82

LF82, an adherent-invasive Escherichia coli (AIEC) pathobiont, is associated with Crohn's disease, an inflammatory bowel disease of unknown etiology. Although AIEC phenotypes differ from those of 'commensal' or pathogenic E. coli, work has failed to identify genetic features accounting for these differences. We have investigated a natural, but rare, single nucleotide polymorphism (SNP) in LF82 present within the highly conserved rpoD gene, encoding σ70 [primary sigma factor, RNA polymerase (RNAP)]. We demonstrate that σ70 D445V results in transcriptomic and phenotypic changes consistent with LF82 phenotypes, including increased antibiotic resistance and biofilm formation and increased capacity for methionine biosynthesis. RNA-seq analyses comparing σ70 V445 versus σ70 D445 identified 24 genes upregulated by σ70 V445 in both LF82 and the laboratory E. coli K-12 strain MG1655. Using in vitro transcription, we demonstrate that σ70 D445V directly increases transcription from promoters for several of the up-regulated genes and that the presence of a 16 bp spacer and -14 G:C is associated with this increase. The position of D445V within RNAP suggests that it could affect RNAP/spacer interaction. Our work represents the first identification of a distinguishing SNP for this pathobiont and suggests an underrecognized mechanism by which pathobionts and strain variants can emerge.

Characterizing the Pathogenic Potential of Crohn's Disease-Associated Adherent-Invasive Escherichia coli

The microbiome of Crohn's disease (CD) patients is composed of a microbial community that is considered dysbiotic and proinflammatory in nature. The overrepresentation of Enterobacteriaceae species is a common feature of the CD microbiome, and much attention has been given to understanding the pathogenic role this feature plays in disease activity. Over 2 decades ago, a new Escherichia coli subtype called adherent-invasive E. coli (AIEC) was isolated and linked to ileal Crohn's disease. Since the isolation of the first AIEC strain, additional AIEC strains have been isolated from both inflammatory bowel disease (IBD) patients and non-IBD individuals using the original in vitro phenotypic characterization methods. Identification of a definitive molecular marker of the AIEC pathotype has been elusive; however, significant advancements have been made in understanding the genetic, metabolic, and virulence determinants of AIEC infection biology. Here, we review the current knowledge of AIEC pathogenesis to provide additional, objective measures that could be considered in defining AIEC and their pathogenic potential.

VAX014, an Oncolytic Therapy, Reduces Adenomas and Modifies Colon Microenvironment in Mouse Model of CRC

Colorectal cancer (CRC) remains the third most common form of cancer and, despite its reduced mortality, results in over 50,000 deaths annually, highlighting the need for novel therapeutic approaches. VAX014 is a novel clinical-stage, oncolytic bacterial minicell-based therapy shown to elicit protective antitumor immune responses in cancer, but it has not been fully evaluated in CRC. Here, VAX014 was demonstrated to induce oncolysis in CRC cell lines in vitro and was evaluated in vivo, both as a prophylactic (before spontaneous development of adenomatous polyps) and as a neoadjuvant treatment using the Fabp-CreXApc^fl468 preclinical animal model of colon cancer. As a prophylactic, VAX014 significantly reduced the size and number of adenomas without inducing long term changes in the gene expression of inflammatory, T helper 1 antitumor, and immunosuppression markers. In the presence of adenomas, a neoadjuvant VAX014 treatment reduced the number of tumors, induced the gene expression of antitumor T_H1 immune markers in adenomas, and promoted the expansion of the probiotic bacterium Akkermansia muciniphila. The neoadjuvant VAX014 treatment was associated with decreased Ki67 proliferation in vivo, suggesting that VAX014 inhibits adenoma development through both oncolytic and immunotherapeutic effects. Combined, these data support the potential of VAX014 treatment in CRC and "at risk" polyp-bearing or early adenocarcinoma populations.

Dietary (poly)phenols mitigate inflammatory bowel disease: Therapeutic targets, mechanisms of action, and clinical observations

Inflammatory bowel diseases (IBD), which include Crohn's disease and ulcerative colitis, are a rapidly growing public health concern worldwide. These diseases are heterogeneous at the clinical, immunological, molecular, genetic, and microbial level, but characteristically involve a disrupted immune-microbiome axis. Shortcomings in conventional treatment options warrant the need for novel therapeutic strategies to mitigate these life-long and relapsing disorders of the gastrointestinal tract. Polyphenols, a diverse group of phytochemicals, have gained attention as candidate treatments due to their array of biological effects. Polyphenols exert broad anti-inflammatory and antioxidant effects through the modulation of cellular signaling pathways and transcription factors important in IBD progression. Polyphenols also bidirectionally modulate the gut microbiome, supporting commensals and inhibiting pathogens. One of the primary means by which gut microbiota interface with the host is through the production of metabolites, which are small molecules produced as intermediate or end products of metabolism. There is growing evidence to support that modulation of the gut microbiome by polyphenols restores microbially derived metabolites critical to the maintenance of intestinal homeostasis that are adversely disrupted in IBD. This review aims to define the therapeutic targets of polyphenols that may be important for mitigation of IBD symptoms, as well as to collate evidence for their clinical use from randomized clinical trials.

Intestinal Microbiota and miRNA in IBD: A Narrative Review about Discoveries and Perspectives for the Future

Inflammatory bowel disease (IBD) includes Crohn's disease (CD) and ulcerative colitis (UC) and comprises a chronic gastrointestinal tract disorder characterized by hyperactive and dysregulated immune responses to environmental factors, including gut microbiota and dietary components. An imbalance of the intestinal microbiota may contribute to the development and/or worsening of the inflammatory process. MicroRNAs (miRNAs) have been associated with various physiological processes, such as cell development and proliferation, apoptosis, and cancer. In addition, they play an important role in inflammatory processes, acting in the regulation of pro- and anti-inflammatory pathways. Differences in the profiles of miRNAs may represent a useful tool in the diagnosis of UC and CD and as a prognostic marker in both diseases. The relationship between miRNAs and the intestinal microbiota is not completely elucidated, but recently this topic has gained prominence and has become the target of several studies that demonstrate the role of miRNAs in the modulation of the intestinal microbiota and induction of dysbiosis; the microbiota, in turn, can regulate the expression of miRNAs and, consequently, alter the intestinal homeostasis. Therefore, this review aims to describe the interaction between the intestinal microbiota and miRNAs in IBD, recent discoveries, and perspectives for the future.

Strong pathogen competition in neonatal gut colonisation

Opportunistic bacterial pathogen species and their strains that colonise the human gut are generally understood to compete against both each other and the commensal species colonising this ecosystem. Currently we are lacking a population-wide quantification of strain-level colonisation dynamics and the relationship of colonisation potential to prevalence in disease, and how ecological factors might be modulating these. Here, using a combination of latest high-resolution metagenomics and strain-level genomic epidemiology methods we performed a characterisation of the competition and colonisation dynamics for a longitudinal cohort of neonatal gut microbiomes. We found strong inter- and intra-species competition dynamics in the gut colonisation process, but also a number of synergistic relationships among several species belonging to genus Klebsiella, which includes the prominent human pathogen Klebsiella pneumoniae. No evidence of preferential colonisation by hospital-adapted pathogen lineages in either vaginal or caesarean section birth groups was detected. Our analysis further enabled unbiased assessment of strain-level colonisation potential of extra-intestinal pathogenic Escherichia coli (ExPEC) in comparison with their propensity to cause bloodstream infections. Our study highlights the importance of systematic surveillance of bacterial gut pathogens, not only from disease but also from carriage state, to better inform therapies and preventive medicine in the future.

Role of adherent invasive Escherichia coli in pathogenesis of inflammatory bowel disease

Gut microbiota imbalances play an important role in inflammatory bowel disease (IBD), but no single pathogenic microorganism critical to IBD that is specific to the IBD terminal ileum mucosa or can invade intestinal epithelial cells has been found. Invasive Escherichia coli (E. coli) adhesion to macrophages is considered to be closely related to the pathogenesis of inflammatory bowel disease. Further study of the specific biological characteristics of adherent invasive E. coli (AIEC) may contribute to a further understanding of IBD pathogenesis. This review explores the relationship between AIEC and the intestinal immune system, discusses the prevalence and relevance of AIEC in Crohn's disease and ulcerative colitis patients, and describes the relationship between AIEC and the disease site, activity, and postoperative recurrence. Finally, we highlight potential therapeutic strategies to attenuate AIEC colonization in the intestinal mucosa, including the use of phage therapy, antibiotics, and anti-adhesion molecules. These strategies may open up new avenues for the prevention and treatment of IBD in the future.

Novel technologies to characterize and engineer the microbiome in inflammatory bowel disease

We present an overview of recent experimental and computational advances in technology used to characterize the microbiome, with a focus on how these developments improve our understanding of inflammatory bowel disease (IBD). Specifically, we present studies that make use of flow cytometry and metabolomics assays to provide a functional characterization of microbial communities. We also describe computational methods for strain-level resolution, temporal series, mycobiome and virome data, co-occurrence networks, and compositional data analysis. In addition, we review novel techniques to therapeutically manipulate the microbiome in IBD. We discuss the benefits and drawbacks of these technologies to increase awareness of specific biases, and to facilitate a more rigorous interpretation of results and their potential clinical application. Finally, we present future lines of research to better characterize the relation between microbial communities and IBD pathogenesis and progression.

Intercontinental Gut Microbiome Variances in IBD

The development of biomarkers for inflammatory bowel disease (IBD) diagnosis would be relevant in a generalized context. However, intercontinental investigation on these microbial biomarkers remains scarce. We examined taxonomic microbiome variations in IBD using published DNA shotgun metagenomic data. For this purpose, we used sequenced data from our previous Spanish Crohn’s disease (CD) and ulcerative colitis (UC) cohort, downloaded sequence data from a Chinese CD cohort, and downloaded taxonomic and functional profiling tables from a USA CD and UC cohort. At the global level, geographical location and disease phenotype were the main explanatory covariates of microbiome variations. In healthy controls (HC) and UC, geography turned out to be the most important factor, while disease intestinal location was the most important one in CD. Disease severity correlated with lower alpha-diversity in UC but not in CD. Across geography, alpha-diversity was significantly different independently of health status, except for CD. Despite recruitment from different countries and with different disease severity scores, CD patients may harbor a very similar microbial taxonomic profile. Our study pointed out that geographic location, disease activity status, and other environmental factors are important contributing factors in microbiota changes in IBD. We therefore strongly recommend taking these factors into consideration for future IBD studies to obtain globally valid and reproducible biomarkers.

Microbiome risk profiles as biomarkers for inflammatory and metabolic disorders

The intestine harbours a complex array of microorganisms collectively known as the gut microbiota. The past two decades have witnessed increasing interest in studying the gut microbiota in health and disease, largely driven by rapid innovation in high-throughput multi-omics technologies. As a result, microbial dysbiosis has been linked to many human pathologies, including type 2 diabetes mellitus and inflammatory bowel disease. Integrated analyses of multi-omics data, including metagenomics and metabolomics along with measurements of host response and cataloguing of bacterial isolates, have identified many bacteria and bacterial products that are correlated with disease. Nevertheless, insight into the mechanisms through which microbes affect intestinal health requires going beyond correlation to causation. Current understanding of the contribution of the gut microbiota to disease causality remains limited, largely owing to the heterogeneity of microbial community structures, interindividual differences in disease evolution and incomplete understanding of the mechanisms that integrate microbiota-derived signals into host signalling pathways. In this Review, we provide a broad insight into the microbiome signatures linked to inflammatory and metabolic disorders, discuss outstanding challenges in this field and propose applications of multi-omics technologies that could lead to an improved mechanistic understanding of microorganism-host interactions.

StrainGE: a toolkit to track and characterize low-abundance strains in complex microbial communities

Human-associated microbial communities comprise not only complex mixtures of bacterial species, but also mixtures of conspecific strains, the implications of which are mostly unknown since strain level dynamics are underexplored due to the difficulties of studying them. We introduce the Strain Genome Explorer (StrainGE) toolkit, which deconvolves strain mixtures and characterizes component strains at the nucleotide level from short-read metagenomic sequencing with higher sensitivity and resolution than other tools. StrainGE is able to identify strains at 0.1x coverage and detect variants for multiple conspecific strains within a sample from coverages as low as 0.5x.

When to suspect contamination rather than colonization - lessons from a putative fetal sheep microbiome

There is an ongoing controversy around the existence of a prenatal, fetal microbiome in humans, livestock, and other animals. The 'in utero microbial colonization' hypothesis challenges the clinical paradigm of the 'sterile womb' but has been criticized for its reliance on DNA-based evidence to detect microbiomes and the failure to conciliate the routine experimental derivation of germ-free animals from surgically resected embryos with a thriving fetal microbiome. In order to avoid the propagation of misinformation in the scientific literature, a critical assessment and careful review of newly published studies, particularly those that challenge the convincing current clinical dogma of the sterile womb, is of critical importance.We read with interest a recent publication that postulated the presence of a fetal microbiome in sheep, but questioned the plausibility of the reported findings and their meaningfulness to prove "microbial colonisation of the fetal gut […] in utero". We reanalyzed the published metagenomic and metatranscriptomic sequence data from the original publication and identified evidence for different types of contamination that affected all samples alike and could explain the reported findings without requiring the existence of a fetal microbiome.Our reanalysis challenges the reported findings as supportive of a prenatal fetal lamb microbiome. The shortcomings of the original analysis and data interpretation highlight common problems of low-biomass microbiome projects. We propose genomic independence of separate biological samples, i.e. distinctive profiles at the microbial strain level, as a potential new microbiome marker to increase confidence in metagenomics analyses of controversial low-biomass microbiomes.

Single-gene long-read sequencing illuminates Escherichia coli strain dynamics in the human intestinal microbiome

Gut microbiome is of major interest due to its close relationship to health and disease. Bacteria usually vary in gene content, leading to functional variations within species, so resolution higher than species-level methods is needed for ecological and clinical relevance. We design a protocol to identify strains in selected species with high discrimination and in high numbers by amplicon sequencing of the flagellin gene. We apply the protocol to fecal samples from a human diet trial, targeting Escherichia coli. Across the 119 samples from 16 individuals, there are 1,532 amplicon sequence variants (ASVs), but only 32 ASVs are dominant in one or more fecal samples, despite frequent dominant strain turnover. Major strains in an intestine are found to be commonly accompanied by a large number of satellite cells, and many are identified as potential extraintestinal pathogens. The protocol could be used to track epidemics or investigate the intra- or inter-host diversity of pathogens.

Psychological stress impairs IL22-driven protective gut mucosal immunity against colonising pathobionts

Crohn's disease is an inflammatory disease of the gastrointestinal tract characterized by an aberrant response to microbial and environmental triggers. This includes an altered microbiome dominated by Enterobacteriaceae and in particular adherent-invasive E. coli (AIEC). Clinical evidence implicates periods of psychological stress in Crohn's disease exacerbation, and disturbances in the gut microbiome might contribute to the pathogenic mechanism. Here we show that stress-exposed mice develop ileal dysbiosis, dominated by the expansion of Enterobacteriaceae. In an AIEC colonisation model, stress-induced glucocorticoids promote apoptosis of CD45+CD90+ cells that normally produce IL-22, a cytokine that is essential for the maintenance of ileal mucosal barrier integrity. Blockade of glucocorticoid signaling or administration of recombinant IL-22 restores mucosal immunity, prevents ileal dysbiosis, and blocks AIEC expansion. We conclude that psychological stress impairs IL-22-driven protective immunity in the gut, which creates a favorable niche for the expansion of pathobionts that have been implicated in Crohn's disease. Importantly, this work also shows that immunomodulation can counteract the negative effects of psychological stress on gut immunity and hence disease-associated dysbiosis.

Synergies of Systems Biology and Synthetic Biology in Human Microbiome Studies

A number of studies have shown that the microbial communities of the human body are integral for the maintenance of human health. Advances in next-generation sequencing have enabled rapid and large-scale quantification of the composition of microbial communities in health and disease. Microorganisms mediate diverse host responses including metabolic pathways and immune responses. Using a system biology approach to further understand the underlying alterations of the microbiota in physiological and pathological states can help reveal potential novel therapeutic and diagnostic interventions within the field of synthetic biology. Tools such as biosensors, memory arrays, and engineered bacteria can rewire the microbiome environment. In this article, we review the computational tools used to study microbiome communities and the current limitations of these methods. We evaluate how genome-scale metabolic models (GEMs) can advance our understanding of the microbe-microbe and microbe-host interactions. Moreover, we present how synergies between these system biology approaches and synthetic biology can be harnessed in human microbiome studies to improve future therapeutics and diagnostics and highlight important knowledge gaps for future research in these rapidly evolving fields.

Genome-Scale Metabolic Modeling of the Human Microbiome in the Era of Personalized Medicine

The human microbiome plays an important role in human health and disease. Meta-omics analyses provide indispensable data for linking changes in microbiome composition and function to disease etiology. Yet, the lack of a mechanistic understanding of, e.g., microbiome-metabolome links hampers the translation of these findings into effective, novel therapeutics. Here, we propose metabolic modeling of microbial communities through constraint-based reconstruction and analysis (COBRA) as a complementary approach to meta-omics analyses. First, we highlight the importance of microbial metabolism in cardiometabolic diseases, inflammatory bowel disease, colorectal cancer, Alzheimer disease, and Parkinson disease. Next, we demonstrate that microbial community modeling can stratify patients and controls, mechanistically link microbes with fecal metabolites altered in disease, and identify host pathways affected by the microbiome. Finally, we outline our vision for COBRA modeling combined with meta-omics analyses and multivariate statistical analyses to inform and guide clinical trials, yield testable hypotheses, and ultimately propose novel dietary and therapeutic interventions. Expected final online publication date for the Annual Review of Microbiology, Volume 75 is October 2021. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

Gastrointestinal Surgery for Inflammatory Bowel Disease Persistently Lowers Microbiome and Metabolome Diversity

BACKGROUND

Many studies have investigated the role of the microbiome in inflammatory bowel disease (IBD), but few have focused on surgery specifically or its consequences on the metabolome that may differ by surgery type and require longitudinal sampling. Our objective was to characterize and contrast microbiome and metabolome changes after different surgeries for IBD, including ileocolonic resection and colectomy.

METHODS

The UC San Diego IBD Biobank was used to prospectively collect 332 stool samples from 129 subjects (50 ulcerative colitis; 79 Crohn's disease). Of these, 21 with Crohn's disease had ileocolonic resections, and 17 had colectomies. We used shotgun metagenomics and untargeted liquid chromatography followed by tandem mass spectrometry metabolomics to characterize the microbiomes and metabolomes of these patients up to 24 months after the initial sampling.

RESULTS

The species diversity and metabolite diversity both differed significantly among groups (species diversity: Mann-Whitney U test P value = 7.8e-17; metabolomics, P-value = 0.0043). Escherichia coli in particular expanded dramatically in relative abundance in subjects undergoing surgery. The species profile was better able to classify subjects according to surgery status than the metabolite profile (average precision 0.80 vs 0.68).

CONCLUSIONS

Intestinal surgeries seem to reduce the diversity of the gut microbiome and metabolome in IBD patients, and these changes may persist. Surgery also further destabilizes the microbiome (but not the metabolome) over time, even relative to the previously established instability in the microbiome of IBD patients. These long-term effects and their consequences for health outcomes need to be studied in prospective longitudinal trials linked to microbiome-involved phenotypes.

High-throughput fitness screening and transcriptomics identify a role for a type IV secretion system in the pathogenesis of Crohn's disease-associated Escherichia coli

Adherent-invasive Escherichia coli (AIEC) are pathogenic bacteria frequently isolated from patients who have Crohn's disease (CD). Despite the phenotypic differences between AIEC and commensal E. coli, comparative genomic approaches have been unable to differentiate these two groups, making the identification of key virulence factors a challenge. Here, we conduct a high-resolution, in vivo genetic screen to map AIEC genes required for intestinal colonization of mice. In addition, we use in vivo RNA-sequencing to define the host-associated AIEC transcriptome. We identify diverse metabolic pathways required for efficient gut colonization by AIEC and show that a type IV secretion system (T4SS) is required to form biofilms on the surface of epithelial cells, thereby promoting AIEC persistence in the gut. E. coli isolated from CD patients are enriched for a T4SS, suggesting a possible connection to disease activity. Our findings establish the T4SS as a principal AIEC colonization factor and highlight the use of genome-wide screens in decoding the infection biology of CD-associated bacteria that otherwise lack a defined genetic signature.

The role of the intestinal microbiota in allogeneic HCT: clinical associations and preclinical mechanisms

Allogeneic hematopoietic cell transplantation (allo-HCT) is a curative-intent therapy for patients with hematological malignancies, but despite advances in the field in recent years, there is still a significant risk of post-transplant mortality. In addition to relapse of the underlying malignancy, the key contributors to this high mortality are graft-versus-host disease (GVHD) and infection. The intestinal microbiota is the collective term describing the community of bacteria, fungi, viruses and protozoa that resides in the human gastrointestinal tract. Bacterial communities have been studied most comprehensively, and disruption of these communities has been associated with the development of a variety of medical conditions in large clinical associative studies. Preclinical studies suggest a mechanistic role for the intestinal microbiota in the instruction and maintenance of both intestinal and systemic immune cell function. This review outlines our current understanding of the relationship between gut bacteria and allo-HCT outcomes, including infection, immune reconstitution, GVHD and relapse, drawing on evidence from both clinical associative studies and preclinical mechanistic studies.

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.

In search for interplay between stool microRNAs, microbiota and short chain fatty acids in Crohn's disease - a preliminary study

Background

Inflammatory bowel diseases are classic polygenic disorders, with genetic loads that reflect immunopathological processes in response to the intestinal microbiota. Herein we performed the multiomics analysis by combining the large scale surveys of gut bacterial community, stool microRNA (miRNA) and short chain fatty acid (SCFA) signatures to correlate their association with the activity of Crohn’s disease (CD).

Methods

DNA, miRNA, and metabolites were extracted from stool samples of 15 CD patients, eight with active disease and seven in remission, and nine healthy individuals. Microbial, miRNA and SCFA profiles were assessed using datasets from 16S rRNA sequencing, Nanostring miRNA and GC-MS targeted analysis, respectively.

Results

Pairwise comparisons showed that 9 and 23 taxa differed between controls and CD patients with active and inactive disease, respectively. Six taxa were common to both comparisons, whereas four taxa differed in CD patients. α-Diversity was lower in both CD groups than in controls. The levels of 13 miRNAs differed (p-value < 0.05; FC > 1.5) in CD patients and controls before FDR correction and 4 after. Of six SCFAs, the levels of two differed significantly (p-value < 0.05, FC > 1.5) in CD patients and controls, and the levels of four differed in patients with active and inactive CD. PLS-DA revealed models with smallest error rate for controls in bacterial component and inactive disease in metabolites.

Conclusion

A complex interrelationship may exist between gut dysbiosis, miRNA profiling and SCFA level in response to intestinal inflammation.

Computational Methods for Strain-Level Microbial Detection in Colony and Metagenome Sequencing Data

Metagenomic sequencing is a powerful tool for examining the diversity and complexity of microbial communities. Most widely used tools for taxonomic profiling of metagenomic sequence data allow for a species-level overview of the composition. However, individual strains within a species can differ greatly in key genotypic and phenotypic characteristics, such as drug resistance, virulence and growth rate. Therefore, the ability to resolve microbial communities down to the level of individual strains within a species is critical to interpreting metagenomic data for clinical and environmental applications, where identifying a particular strain, or tracking a particular strain across a set of samples, can help aid in clinical diagnosis and treatment, or in characterizing yet unstudied strains across novel environmental locations. Recently published approaches have begun to tackle the problem of resolving strains within a particular species in metagenomic samples. In this review, we present an overview of these new algorithms and their uses, including methods based on assembly reconstruction and methods operating with or without a reference database. While existing metagenomic analysis methods show reasonable performance at the species and higher taxonomic levels, identifying closely related strains within a species presents a bigger challenge, due to the diversity of databases, genetic relatedness, and goals when conducting these analyses. Selection of which metagenomic tool to employ for a specific application should be performed on a case-by case basis as these tools have strengths and weaknesses that affect their performance on specific tasks. A comprehensive benchmark across different use case scenarios is vital to validate performance of these tools on microbial samples. Because strain-level metagenomic analysis is still in its infancy, development of more fine-grained, high-resolution algorithms will continue to be in demand for the future.

Strain-level epidemiology of microbial communities and the human microbiome

The biological importance and varied metabolic capabilities of specific microbial strains have long been established in the scientific community. Strains have, in the past, been largely defined and characterized based on microbial isolates. However, the emergence of new technologies and techniques has enabled assessments of their ecology and phenotypes within microbial communities and the human microbiome. While it is now more obvious how pathogenic strain variants are detrimental to human health, the consequences of subtle genetic variation in the microbiome have only recently been exposed. Here, we review the operational definitions of strains (e.g., genetic and structural variants) as they can now be identified from microbial communities using different high-throughput, often culture-independent techniques. We summarize the distribution and diversity of strains across the human body and their emerging links to health maintenance, disease risk and progression, and biochemical responses to perturbations, such as diet or drugs. We list methods for identifying, quantifying, and tracking strains, utilizing high-throughput sequencing along with other molecular and “culturomics” technologies. Finally, we discuss implications of population studies in bridging experimental gaps and leading to a better understanding of the health effects of strains in the human microbiome.

Metagenomic approaches in microbial ecology: an update on whole-genome and marker gene sequencing analyses

Metagenomics and marker gene approaches, coupled with high-throughput sequencing technologies, have revolutionized the field of microbial ecology. Metagenomics is a culture-independent method that allows the identification and characterization of organisms from all kinds of samples. Whole-genome shotgun sequencing analyses the total DNA of a chosen sample to determine the presence of micro-organisms from all domains of life and their genomic content. Importantly, the whole-genome shotgun sequencing approach reveals the genomic diversity present, but can also give insights into the functional potential of the micro-organisms identified. The marker gene approach is based on the sequencing of a specific gene region. It allows one to describe the microbial composition based on the taxonomic groups present in the sample. It is frequently used to analyse the biodiversity of microbial ecosystems. Despite its importance, the analysis of metagenomic sequencing and marker gene data is quite a challenge. Here we review the primary workflows and software used for both approaches and discuss the current challenges in the field.

Why the discovery of adherent-invasive Escherichia coli molecular markers is so challenging?

Adherent-invasive Escherichia coli (AIEC) strains have been extensively related to Crohn’s disease (CD) etiopathogenesis. Higher AIEC prevalence in CD patients versus controls has been reported, and its mechanisms of pathogenicity have been linked to CD physiopathology. In CD, the therapeutic armamentarium remains limited and non-curative; hence, the necessity to better understand AIEC as a putative instigator or propagator of the disease is certain. Nonetheless, AIEC identification is currently challenging because it relies on phenotypic assays based on infected cell cultures which are highly time-consuming, laborious and non-standardizable. To address this issue, AIEC molecular mechanisms and virulence genes have been studied; however, a specific and widely distributed genetic AIEC marker is still missing. The finding of molecular tools to easily identify AIEC could be useful in the identification of AIEC carriers who could profit from personalized treatment. Also, it would significantly promote AIEC epidemiological studies. Here, we reviewed the existing data regarding AIEC genetics and presented those molecular markers that could assist with AIEC identification. Finally, we highlighted the problems behind the discovery of exclusive AIEC biomarkers and proposed strategies to facilitate the search of AIEC signature sequences.

Enhanced E. coli LF82 Translocation through the Follicle-associated Epithelium in Crohn's Disease is Dependent on Long Polar Fimbriae and CEACAM6 expression, and Increases Paracellular Permeability

BACKGROUND AND AIMS

Patients with Crohn's disease [CD] harbour an increased number of adherent-invasive E. coli [AIEC]. The strain LF82, identified in the ileal mucosa of CD patients, has been extensively studied for pathogenic mechanisms. However, understanding of the interaction of LF82 with the intestinal mucosa of CD patients is lacking.

METHODS

Here, we investigated the importance of long polar fimbriae [LPF] type 1 pili and the carcinoembryonic antigen-related cell-adhesion molecule 6 [CEACAM6] for translocation of LF82 in an in vitro model of follicle-associated epithelium [FAE], and in the FAE and villus epithelium [VE] of patients with CD and controls, using Ussing chambers.

RESULTS

Significantly greater LF82 passage occurred in the FAE model compared with in the VE Caco-2cl1 mono-culture. Moreover, bacterial translocation was inhibited by either LPF disruption or pre-incubation with anti-CEACAM6 antibody. Tissue mounted in Ussing chambers showed significantly higher LF82 passage in FAE from patients with CD compared with control FAE, that was diminished in LF82 lacking LPF and by blocking host CEACAM6. Interestingly, addition of LF82 to the CD FAE tissues significantly increased paracellular permeability [of 51Chromium-EDTA] compared with baseline, and the increase was inhibited by anti-CEACAM6. Immunofluorescence and immunoblots showed higher expression of CEACAM6 in FAE of patients with CD compared with in FAE from controls.

CONCLUSIONS

These data suggest that the FAE of CD patients is a site of vulnerability for invasion by LF82 via a mechanism that requires both bacterial LPF and host CEACAM6. Further, LF82 has the ability to increase paracellular passage through the FAE of patients with CD. These data can help define novel therapeutic targets in CD for the prevention of clinical recurrence.

Cultivated Escherichia coli diversity in intestinal microbiota of Crohn's disease patients and healthy individuals: Whole genome data

Dysbiosis of the gut microbiota in inflammatory bowel disease (IBD) patients is of great interest. It has been reported that Crohn's disease (CD) is associated with a general decrease in microbial diversity [1]. Altered microbial composition and function in CD results in imbalance in host-bacteria interaction and increased immune stimulation [2]. It is shown that microbiota in CD is characterized by increased proportion of E. coli in human gut in contrast to healthy individuals [3]. However, the overall qualitative and quantitative diversity of E. coli strains in CD is not fully understood. Here, we present a dataset of whole-genome sequences of E. coli's.

A workflow for generating multi-strain genome-scale metabolic models of prokaryotes

Genome-scale models (GEMs) of bacterial strains' metabolism have been formulated and used over the past 20 years. Recently, with the number of genome sequences exponentially increasing, multi-strain GEMs have proved valuable to define the properties of a species. Here, through four major stages, we extend the original Protocol used to generate a GEM for a single strain to enable multi-strain GEMs: (i) obtain or generate a high-quality model of a reference strain; (ii) compare the genome sequence between a reference strain and target strains to generate a homology matrix; (iii) generate draft strain-specific models from the homology matrix; and (iv) manually curate draft models. These multi-strain GEMs can be used to study pan-metabolic capabilities and strain-specific differences across a species, thus providing insights into its range of lifestyles. Unlike the original Protocol, this procedure is scalable and can be partly automated with the Supplementary Jupyter notebook Tutorial. This Protocol Extension joins the ranks of other comparable methods for generating models such as CarveMe and KBase. This extension of the original Protocol takes on the order of weeks to multiple months to complete depending on the availability of a suitable reference model.

Species abundance information improves sequence taxonomy classification accuracy

Popular naive Bayes taxonomic classifiers for amplicon sequences assume that all species in the reference database are equally likely to be observed. We demonstrate that classification accuracy degrades linearly with the degree to which that assumption is violated, and in practice it is always violated. By incorporating environment-specific taxonomic abundance information, we demonstrate a significant increase in the species-level classification accuracy across common sample types. At the species level, overall average error rates decline from 25% to 14%, which is favourably comparable to the error rates that existing classifiers achieve at the genus level (16%). Our findings indicate that for most practical purposes, the assumption that reference species are equally likely to be observed is untenable. q2-clawback provides a straightforward alternative for samples from common environments.

Taxonomy classification of amplicon sequences is an important step in investigating microbial communities in microbiome analysis. Here, the authors show incorporating environment-specific taxonomic abundance information can lead to improved species-level classification accuracy across common sample types.

Species abundance information improves sequence taxonomy classification accuracy

Popular naive Bayes taxonomic classifiers for amplicon sequences assume that all species in the reference database are equally likely to be observed. We demonstrate that classification accuracy degrades linearly with the degree to which that assumption is violated, and in practice it is always violated. By incorporating environment-specific taxonomic abundance information, we demonstrate a significant increase in the species-level classification accuracy across common sample types. At the species level, overall average error rates decline from 25% to 14%, which is favourably comparable to the error rates that existing classifiers achieve at the genus level (16%). Our findings indicate that for most practical purposes, the assumption that reference species are equally likely to be observed is untenable. q2-clawback provides a straightforward alternative for samples from common environments.

The Unique Lifestyle of Crohn's Disease-Associated Adherent-Invasive Escherichia coli

Escherichia coli is one of the most genetically and phenotypically diverse species of bacteria. This remarkable diversity produces a plethora of clinical outcomes following infection and has informed much of what we currently know about host-pathogen interactions for a wide range of bacteria-host relationships. In studying the role of microbes in disease, adherent-invasive E. coli (AIEC) has emerged as having a strong association with Crohn's disease (CD). Thus, there has been an equally strong effort to uncover the root origins of AIEC, to appreciate how AIEC differs from other well-known pathogenic E. coli variants, and to understand its connection to disease. Emerging from a growing body of research on AIEC is the understanding that AIEC itself is remarkably diverse, both in phylogenetic origins, genetic makeup, and behavior in the host setting. Here, we describe the unique lifestyle of CD-associated AIEC and review recent research that is uncovering the inextricable link between AIEC and its host in the context of CD.