From next-generation sequencing to systematic modeling of the gut microbiome

Using short-read 16S rRNA sequencing of multiple variable regions to generate high-quality results to a species level

Introduction

Short-read amplicon sequencing studies have typically focused on 1-2 variable regions of the 16S rRNA gene. Species-level resolution is limited in these studies, as each variable region enables the characterisation of a different subsection of the microbiome. Although long-read sequencing techniques take advantage of all 9 variable regions by sequencing the entire 16S rRNA gene, they are substantially more expensive. This work assessed the feasibility of accurate species-level resolution and reproducibility using a relatively new sequencing kit and bioinformatics pipeline developed for short-read sequencing of multiple variable regions of the 16S rRNA gene. In addition, we evaluated the potential impact of different sample collection methods on our outcomes.

Methods

Using xGen™ 16S Amplicon Panel v2 kits, sequencing of all 9 variable regions of the 16S rRNA gene was carried out on an Illumina MiSeq platform. Mock cells and mock DNA for 8 bacterial species were included as extraction and sequencing controls respectively. Within-run and between-run replicate samples, and pairs of stool and rectal swabs collected at 0-5 weeks from the same participants, were incorporated. Observed relative abundances of each species were compared to theoretical abundances provided by ZymoBIOMICS. Paired Wilcoxon rank sum tests and distance-based intraclass correlation coefficients were used to statistically compare alpha and beta diversity measures, respectively, for pairs of replicates and stool/rectal swab sample pairs.

Results

Using multiple variable regions of the 16S ribosomal Ribonucleic Acid (rRNA) gene, we found that we could accurately identify taxa to a species level and obtain highly reproducible results at a species level. Yet, the microbial profiles of stool and rectal swab sample pairs differed substantially despite being collected concurrently from the same infants.

Conclusion

This protocol provides an effective means for studying infant gut microbial samples at a species level. However, sample collection approaches need to be accounted for in any downstream analysis.

From the Gut to the Brain: Is Microbiota a New Paradigm in Parkinson's Disease Treatment?

Parkinson's disease (PD) is recognized as the second most prevalent primary chronic neurodegenerative disorder of the central nervous system. Clinically, PD is characterized as a movement disorder, exhibiting an incidence and mortality rate that is increasing faster than any other neurological condition. In recent years, there has been a growing interest concerning the role of the gut microbiota in the etiology and pathophysiology of PD. The establishment of a brain-gut microbiota axis is now real, with evidence denoting a bidirectional communication between the brain and the gut microbiota through metabolic, immune, neuronal, and endocrine mechanisms and pathways. Among these, the vagus nerve represents the most direct form of communication between the brain and the gut. Given the potential interactions between bacteria and drugs, it has been observed that the therapies for PD can have an impact on the composition of the microbiota. Therefore, in the scope of the present review, we will discuss the current understanding of gut microbiota on PD and whether this may be a new paradigm for treating this devastating disease.

The Evolving Microbiome of Dental Caries

Dental caries is a significant oral and public health problem worldwide, especially in low-income populations. The risk of dental caries increases with frequent intake of dietary carbohydrates, including sugars, leading to increased acidity and disruption of the symbiotic diverse and complex microbial community of health. Excess acid production leads to a dysbiotic shift in the bacterial biofilm composition, demineralization of tooth structure, and cavities. Highly acidic and acid-tolerant species associated with caries include Streptococcus mutans, Lactobacillus, Actinomyces, Bifidobacterium, and Scardovia species. The differences in microbiotas depend on tooth site, extent of carious lesions, and rate of disease progression. Metagenomics and metatranscriptomics not only reveal the structure and genetic potential of the caries-associated microbiome, but, more importantly, capture the genetic makeup of the metabolically active microbiome in lesion sites. Due to its multifactorial nature, caries has been difficult to prevent. The use of topical fluoride has had a significant impact on reducing caries in clinical settings, but the approach is costly; the results are less sustainable for high-caries-risk individuals, especially children. Developing treatment regimens that specifically target S. mutans and other acidogenic bacteria, such as using nanoparticles, show promise in altering the cariogenic microbiome, thereby combatting the disease.

A mathematical model of Bacteroides thetaiotaomicron, Methanobrevibacter smithii, and Eubacterium rectale interactions in the human gut

The human gut microbiota is a complex ecosystem that affects a range of human physiology. In order to explore the dynamics of the human gut microbiota, we used a system of ordinary differential equations to model mathematically the biomass of three microorganism populations: Bacteroides thetaiotaomicron, Eubacterium rectale, and Methanobrevibacter smithii. Additionally, we modeled the concentrations of relevant nutrients necessary to sustain these populations over time. Our model highlights the interactions and the competition among these three species. These three microorganisms were specifically chosen due to the system's end product, butyrate, which is a short chain fatty acid that aids in developing and maintaining the intestinal barrier in the human gut. The basis of our mathematical model assumes the gut is structured such that bacteria and nutrients exit the gut at a rate proportional to its volume, the rate of volumetric flow, and the biomass or concentration of the particular population or nutrient. We performed global sensitivity analyses using Sobol' sensitivities to estimate the relative importance of model parameters on simulation results.

Microbiome modulation in inflammatory diseases: Progress to microbiome genetic engineering

Recent developments in sequencing technology and analytical approaches have allowed researchers to show that the healthy gut microbiome is very varied and capable of performing a wide range of tasks. The importance of gut microbiota in controlling immunological, neurological, and endocrine function is becoming well-recognized. Thereby, numerous inflammatory diseases, including those that impact the gastrointestinal system, as well as less obvious ones, including Rheumatoid arthritis (RA), cancer, gestational diabetes (GD), type 1 diabetes (T1D), and type 2 diabetes (T2D), have been linked to dysbiotic gut microbiota. Microbiome engineering is a rapidly evolving frontier for solutions to improve human health. Microbiome engineering seeks to improve the function of an ecosystem by manipulating the composition of microbes. Thereby, generating potential therapies against metabolic, inflammatory, and immunological diseases will be possible through microbiome engineering. This essay first provides an overview of the traditional technological instruments that might be used for microbiome engineering, such as Fecal Microbiota Transplantation (FMT), prebiotics, and probiotics. Moreover, we will also discuss experimental genetic methods such as Metagenomic Alteration of Gut microbiome by In situ Conjugation (MAGIC), Bacteriophage, and Conjugative plasmids in manipulating intestinal microbiota.

Portal Vein Thrombosis in Patients with Liver Cirrhosis: What Went Wrong?

Purpose

This study aimed to explore inflammatory biomarkers, stool's functional bacterial groups and their possible link to portal vein thrombosis (PVT) in patients with liver cirrhosis (LC).

Materials and Methods

An observational study of 300 participants: 200 inhospital cirrhotic patients, who met inclusion criteria, equally assigned into two groups, based on the presence or absence of PVT and 100 healthy controls was carried out.

Results

The PVT group displayed significant differences related to older age, cigarettes smoking history, emergency admission, higher Child-Pugh score, metabolic related disorders and nonalcoholic fatty liver disease, as well as non-obstructive aspects, with chronic thrombi. The PVT group exhibited significant differences related to biomarkers such as tumor necrosis factor (TNF)-alpha, C-reactive protein (CRP), D-dimers (D-D), as well as gut overall dysbiosis (DB) and alteration of different functional bacterial groups of the gut microbiota. Strong positive correlations were observed between PVT severity, and TNF-alpha, CRP, D-D as well as lipopolysaccharide (LPS) positive bacteria. Esophageal varices, age and abdominal pain were independent predictors for PVT severity as well as CRP, TNF-alpha and D-D.

Conclusion

Patients with LC and PVT displayed elevation of TNF-alpha, CRP, D-D alterations of the functional gut microbiota, as well as several morphological and clinical particularities. Although the LPS positive gut microbiota was linked to inflammatory biomarkers and PVT severity, it was not proven to be an independent predictor of the PVT severity like CRP, TNF-alpha and D-D.

Effects of isolation and confinement on gastrointestinal microbiota-a systematic review

Purpose

The gastrointestinal (GI) microbiota is a complex and dynamic ecosystem whose composition and function are influenced by many internal and external factors. Overall, the individual GI microbiota composition appears to be rather stable but can be influenced by extreme shifts in environmental exposures. To date, there is no systematic literature review that examines the effects of extreme environmental conditions, such as strict isolation and confinement, on the GI microbiota.

Methods

We conducted a systematic review to examine the effects of isolated and confined environments on the human GI microbiota. The literature search was conducted according to PRISMA criteria using PubMed, Web of Science and Cochrane Library. Relevant studies were identified based on exposure to isolated and confined environments, generally being also antigen-limited, for a minimum of 28 days and classified according to the microbiota analysis method (cultivation- or molecular based approaches) and the isolation habitat (space, space- or microgravity simulation such as MARS-500 or natural isolation such as Antarctica). Microbial shifts in abundance, alpha diversity and community structure in response to isolation were assessed.

Results

Regardless of the study habitat, inconsistent shifts in abundance of 40 different genera, mainly in the phylum Bacillota (formerly Firmicutes) were reported. Overall, the heterogeneity of studies was high. Reducing heterogeneity was neither possible by differentiating the microbiota analysis methods nor by subgrouping according to the isolation habitat. Alpha diversity evolved non-specifically, whereas the microbial community structure remained dissimilar despite partial convergence. The GI ecosystem returned to baseline levels following exposure, showing resilience irrespective of the experiment length.

Conclusion

An isolated and confined environment has a considerable impact on the GI microbiota composition in terms of diversity and relative abundances of dominant taxa. However, due to a limited number of studies with rather small sample sizes, it is important to approach an in-depth conclusion with caution, and results should be considered as a preliminary trend. The risk of dysbiosis and associated diseases should be considered when planning future projects in extreme environments.

Systematic review registration

https://www.crd.york.ac.uk/prospero/, identifier CRD42022357589.

A cloud-based pipeline for analysis of FHIR and long-read data

Motivation

As genome sequencing becomes cheaper and more accurate, it is becoming increasingly viable to merge this data with electronic health information to inform clinical decisions.

Results

In this work, we demonstrate a full pipeline for working with both PacBio sequencing data and clinical FHIR^® data, from initial data to tertiary analysis. The electronic health records are stored in FHIR^® (Fast Healthcare Interoperability Resource) format, the current leading standard for healthcare data exchange. For the genomic data, we perform variant calling on long-read PacBio HiFi data using Cromwell on Azure. Both data formats are parsed, processed and merged in a single scalable pipeline which securely performs tertiary analyses using cloud-based Jupyter notebooks. We include three example applications: exporting patient information to a database, clustering patients and performing a simple pharmacogenomic study.

Availability and implementation

https://github.com/microsoft/genomicsnotebook/tree/main/fhirgenomics.

Supplementary information

Supplementary data are available at Bioinformatics Advances online.

Human Gut Microbiota Plasticity throughout the Life Course

The role of the gut microbiota in human health and disease has garnered heightened attention over the past decade. A thorough understanding of microbial variation over the life course and possible ways to influence and optimize the microbial pattern is essential to capitalize on the microbiota's potential to influence human health. Here, we review our current understanding of the concept of plasticity of the human gut microbiota throughout the life course. Characterization of the plasticity of the microbiota has emerged through recent research and suggests that the plasticity in the microbiota signature is largest at birth when the microbial colonization of the gut is initiated and mode of birth imprints its mark, then decreases postnatally continuously and becomes less malleable and largely stabilized with advancing age. This continuing loss of plasticity has important implication for the impact of the exposome on the microbiota and health throughout the life course and the identification of susceptible 'windows of opportunity' and methods for interventions.

Microbiome systems biology advancements for natural well-being

Throughout the years all data from epidemiological, physiological and omics have suggested that the microbial communities play a considerable role in modulating human health. The population of microorganisms residing in the human intestine collectively known as microbiota presents a genetic repertoire that is higher in magnitude than the human genome. They play an essential role in host immunity and neuronal signaling. Rapid enhancement of sequence based screening and development of humanized gnotobiotic model has sparked a great deal of interest among scientists to probe the dynamic interactions of the commensal bacteria. This review focuses on systemic analysis of the gut microbiome to decipher the complexity of the host-microbe intercommunication and gives a special emphasis on the evolution of targeted precision medicine through microbiome engineering. In addition, we have also provided a comprehensive description of how interconnection between metabolism and biochemical reactions in a specific organism can be obtained from a metabolic network or a flux balance analysis and combining multiple datasets helps in the identification of a particular metabolite. The review highlights how genetic modification of the critical components and programming the resident microflora can be employed for targeted precision medicine. Inspite of the ongoing debate on the utility of gut microbiome we have explored on the probable new therapeutic avenues like FMT (Fecal microbiota transplant) can be utilized. This review also recapitulates integrating human-relevant 3D cellular models coupled with computational models and the metadata obtained from interventional and epidemiological studies may decipher the complex interactome of diet-microbiota-disease pathophysiology. In addition, it will also open new avenues for the development of therapeutics derived from microbiome or implementation of personalized nutrition. In addition, the identification of biomarkers can also help towards the development of new diagnostic tools and eventually will lead to strategic management of the disease. Inspite of the ongoing debate on the utility of the gut microbiome we have explored how probable new therapeutic avenues like FMT (Fecal microbiota transplant) can be utilized. This review also summarises integrating human-relevant 3D cellular models coupled with computational models and the metadata obtained from interventional and epidemiological studies may decipher the complex interactome of diet- microbiota-disease pathophysiology. In addition, it will also open new avenues for the development of therapeutics derived from the microbiome or implementation of personalized nutrition. In addition, the identification of biomarkers can also help towards the development of new diagnostic tools and eventually will lead to strategic management of disease.

The human "contaminome": bacterial, viral, and computational contamination in whole genome sequences from 1000 families

The unmapped readspace of whole genome sequencing data tends to be large but is often ignored. We posit that it contains valuable signals of both human infection and contamination. Using unmapped and poorly aligned reads from whole genome sequences (WGS) of over 1000 families and nearly 5000 individuals, we present insights into common viral, bacterial, and computational contamination that plague whole genome sequencing studies. We present several notable results: (1) In addition to known contaminants such as Epstein-Barr virus and phiX, sequences from whole blood and lymphocyte cell lines contain many other contaminants, likely originating from storage, prep, and sequencing pipelines. (2) Sequencing plate and biological sample source of a sample strongly influence contamination profile. And, (3) Y-chromosome fragments not on the human reference genome commonly mismap to bacterial reference genomes. Both experiment-derived and computational contamination is prominent in next-generation sequencing data. Such contamination can compromise results from WGS as well as metagenomics studies, and standard protocols for identifying and removing contamination should be developed to ensure the fidelity of sequencing-based studies.

Gallstone Disease and Bacterial Metabolic Performance of Gut Microbiota in Middle-Aged and Older Patients

Background

Gallstone disease (GSD) is more commonly presented in aged people.

Purpose

The purpose of the study was to explore the insights of metabolic performance of bacterial species from gut microbiota as well as the clinical background in middle-aged and elderly patients with GSD.

Patients and Methods

This is an observational study concerning 120 research participants. Of those, 90 patients with symptomatic GSD addressed for cholecystectomy, average age 59.83 ± 15.32 years: 45 with cholesterol rich gallstones (CGSs), 45 with pigment gallstones (PGSs) and 30 healthy controls joined this observational study. Clinical examination, lab work-ups, upper and lower digestive video-endoscopies, abdominal ultrasound/CT and gallbladder motility assessment by Dodd’s method were performed. Overall stool dysbiosis (DB) was assessed as 1 = minor, 2 = mild, 3 = severe, species being identified by matrix-assisted laser desorption ionization method. Stool samples from dysbiotic patients were analyzed by a next generation sequencing method with operational taxonomic unit identification.

Results

Patients with GSD presented with a significant high range of overall gut DB (p < 0.0001) when compared with controls. Those with CGSs compared with those having PGSs displayed significant clinical differences related to elderly age, lifestyle and diet particularities, obesity, dyslipidemia, nonalcoholic fatty liver disease, hypertension, type 2 diabetes mellitus or impaired glucose tolerance, as well as motility disturbances of gallbladder with a decrease of the ejection fraction. Significant increase of overall DB range and alterations of several functional bacterial species with a decrease of butyrate, lactate, acetate/propionate and methane producers, mucin degrading bacteria, biodiversity index of microbiota, as well as an increase of lipopolysaccharide positive bacteria were significantly present in patients with CGSs.

Conclusion

Middle-aged and elderly patients with GSD and a clinical background characterized by particular lifestyle, metabolic and gallbladder motility issues displayed significant modifications of biodiversity, overall gut DB and alterations of several functional bacterial species, with a decrease of their metabolic performance.

Untargeted Metabolomics Sensitively Differentiates Gut Bacterial Species in Single Culture and Co-Culture Systems

Gut microbiome plays a vital role in human health, and its characteristic has been widely identified through next-generation sequencing techniques. Although with great genomic insights into gut microbiome, its functional information is not clearly elaborated through metagenomic techniques. On the other hand, it is suggested that fecal metabolome can be used as a functional readout of the microbiome composition; therefore, we designed a proof-of-concept study to first characterize the metabolome of different gut microbes and then investigate the relationship between bacterial metabolomes and their compositions in co-culture systems. We selected eight representative bacteria species from Bifidobacterium (2), Bacteroides (1), Lactobacillus (4), and Akkermansia (1) genera as our model microbes. Liquid chromatography coupled mass spectrometry-based untargeted metabolomics was utilized to explore the microbial metabolome of bacteria single cultures and co-culture systems. Through spectral comparisons, our results showed that untargeted metabolomics could capture the similarity and differences in metabolic profiles from eight representative gut bacteria. Also, untargeted metabolomics could sensitively differentiate gut bacterial species based on our statistical analyses. For example, citrulline and histamine levels were significantly different among four Lactobacillus species. In addition, in the co-culture systems with different bacteria population ratios, gut bacterial metabolomes can be used to quantitatively reflect bacterial population in a mixed culture. For instance, the relative abundance of 2-hydroxybutyric acid changed proportionately with the changed population ratio of Lactobacillus reuteri in the co-culture system. In summary, we proposed a workflow that could demonstrate the capability of untargeted metabolomics in differentiating gut bacterial species and detecting their characteristic metabolites proportionally to the microbial population in co-culture systems.

Metagenomics analysis of the fecal microbiota in Ring-necked pheasants (Phasianus colchicus) and Green pheasants (Phasianus versicolor) using next generation sequencing

Pheasant reintroduction and conservation efforts have been in place in Pakistan since the 1980 s, yet there is still a scarcity of data on pheasant microbiome and zoonosis. Instead of growing vast numbers of bacteria in the laboratory, to investigate the fecal microbiome, pheasants (green and ring neck pheasant) were analyzed using 16S rRNA metagenomics and using IonS5TMXL sequencing from two flocks more than 10 birds. Operational taxonomic unit (OTU) cluster analysis and phylogenetic tree analysis was performed using Mothur software against the SSUrRNA database of SILVA and the MUSCLE (Version 3.8.31) software. Results of the analysis showed that firmicutes were the most abundant phylum among the top ten phyla, in both pheasant species, followed by other phyla such as actinobacteria and proteobacteria in ring necked pheasant and bacteroidetes in green necked pheasant. Bacillus was the most relatively abundant genus in both pheasants followed by Oceanobacillus and Teribacillus for ring necked pheasant and Lactobacillus for green necked pheasant. Because of their well-known beneficial characteristics, these genus warrants special attention. Bird droppings comprise germs from the urinary system, gut, and reproductive sites, making it difficult to research each anatomical site at the same time. We conclude that metagenomic analysis and classification provides baseline information of the pheasant fecal microbiome that plays a role in disease and health.

Dyspepsia and Gut Microbiota in Female Patients with Postcholecystectomy Syndrome

BACKGROUND

Gallstone disease (GSD) represents one of the most frequent digestive disorders, highly reported in female gender. The purpose of the study was to explore the clinical and gut microbiota particularities of female patients with postcholecystectomy syndrome (PCS) and the possible relationship between gut dysbiosis (DB) and abdominal complaints.

PATIENTS AND METHODS

In total, 129 female participants: 104 outpatients divided into two equal groups, 52 PCS (+), 52 PCS (-) and 25 healthy controls were consecutively enrolled in this observational study. Patients underwent clinical examination with assessment of pain, bloating, transit disturbances, abdominal ultrasound/computer tomography/magnetic resonance imaging/endoscopic retrograde cholangiopancreatography, upper and lower digestive endoscopies. Laboratory work-ups and stool microbiology assessments were performed for all study participants (patients and controls). Stool microorganisms were identified by matrix-assisted laser desorption ionization - time-of-flight- mass spectrometry and in patients with DB also by next-generation sequencing.

RESULTS

Older age, complicated gallstones disease, associated conditions like diabetes mellitus/impaired glucose tolerance and irritable bowel syndrome were significantly present in PCS (+) group, as well as sedentary lifestyle and diets characterized by a low fiber intake (p<0.0001). PCS (+) patients displayed significant differences related to the incidence and severity of overall gut microbiota DB, decreased H index of biodiversity and the unbalanced Firmicutes/Bacteroidetes (F/B) ratios by comparison to the PCS (-) group (p<0.0001). Strong positive correlations of the severity of overall DB with bloating and the intestinal habit disorders, as well as of F/B ratios to all abdominal symptoms were noted.

CONCLUSION

PCS in female patients was associated with older age, sedentary lifestyle, specific dietary habits, history of complicated gallstone disease, diabetes mellitus/impaired glucose tolerance and irritable bowel syndrome, as well as gut microbiota particularities. Overall DB and unbalanced F/B ratios were strongly correlated to abdominal complaints.

Re-examining chemically defined liquid diets through the lens of the microbiome

Trends in nutritional science are rapidly shifting as information regarding the value of eating unprocessed foods and its salutary effect on the human microbiome emerge. Unravelling the evolution and ecology by which humans have harboured a microbiome that participates in every facet of health and disease is daunting. Most strikingly, the host habitat has sought out naturally occurring foodstuff that can fulfil its own metabolic needs and also the needs of its microbiota, each of which remain inexorably connected to one another. With the introduction of modern medicine and complexities of critical care, came the assumption that the best way to feed a critically ill patient is by delivering fibre-free chemically defined sterile liquid foods (that is, total enteral nutrition). In this Perspective, we uncover the potential flaws in this assumption and discuss how emerging technology in microbiome sciences might inform the best method of feeding malnourished and critically ill patients.

Lung microbiome of stable and exacerbated COPD patients in Tshwane, South Africa

Chronic obstructive pulmonary disease (COPD) is characterised by the occurrence of exacerbations triggered by infections. The aim of this study was to determine the composition of the lung microbiome and lung virome in patients with COPD in an African setting and to compare their composition between the stable and exacerbated states. Twenty-four adult COPD patients were recruited from three hospitals. Sputum was collected and bacterial DNA was extracted. Targeted metagenomics was performed to determine the microbiome composition. Viral DNA and RNA were extracted from selected samples followed by cDNA conversion. Shotgun metagenomics sequencing was performed on pooled DNA and RNA. The most abundant phyla across all samples were Firmicutes and Proteobacteria. The following genera were most prevalent: Haemophilus and Streptococcus. There were no considerable differences for alpha and beta diversity measures between the disease states. However, a difference in the abundances between disease states was observed for: (i) Serratia (3% lower abundance in exacerbated state), (ii) Granulicatella (2.2% higher abundance in exacerbated state), (iii) Haemophilus (5.7% higher abundance in exacerbated state) and (iv) Veillonella (2.5% higher abundance in exacerbated state). Virome analysis showed a high abundance of the BeAn 58058 virus, a member of the Poxviridae family, in all six samples (90% to 94%). This study is among the first to report lung microbiome composition in COPD patients from Africa. In this small sample set, no differences in alpha or beta diversity between stable and exacerbated disease state was observed, but an unexpectedly high frequency of BeAn 58058 virus was observed. These observations highlight the need for further research of the lung microbiome of COPD patients in African settings.

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.

Comparative Analysis of 16S rRNA Gene and Metagenome Sequencing in Pediatric Gut Microbiomes

The colonization of the human gut microbiome begins at birth, and over time, these microbial communities become increasingly complex. Most of what we currently know about the human microbiome, especially in early stages of development, was described using culture-independent sequencing methods that allow us to identify the taxonomic composition of microbial communities using genomic techniques, such as amplicon or shotgun metagenomic sequencing. Each method has distinct tradeoffs, but there has not been a direct comparison of the utility of these methods in stool samples from very young children, which have different features than those of adults. We compared the effects of profiling the human infant gut microbiome with 16S rRNA amplicon vs. shotgun metagenomic sequencing techniques in 338 fecal samples; younger than 15, 15-30, and older than 30 months of age. We demonstrate that observed changes in alpha-diversity and beta-diversity with age occur to similar extents using both profiling methods. We also show that 16S rRNA profiling identified a larger number of genera and we find several genera that are missed or underrepresented by each profiling method. We present the link between alpha diversity and shotgun metagenomic sequencing depth for children of different ages. These findings provide a guide for selecting an appropriate method and sequencing depth for the three studied age groups.

The Role of Gut Microbiota in Modulating Tumor Growth and Anticancer Agent Efficacy

An increasing number of studies have revealed an interaction between gut microbiota and tumors. The enrichment of specific bacteria strains in the intestines has been found to modulate tumor growth and influence the mechanisms of tumor treatment. Various bacteria are involved in modulating the effects of chemotherapeutic drugs currently used to treat patients with cancer, and they affect not only gastrointestinal tract tumors but also distant organ tumors. In addition, changes in the gut microbiota are known to be involved in the antitumor immune response as well as the modulation of the intestinal immune system. As a result, the gut microbiota plays an important role in modulating the efficacy of immune checkpoint inhibitors. Therefore, gut microbiota could be considered as an adjuvant treatment option with other cancer treatment or as another marker for predicting treatment response. In this review, we examine how gut microbiota affects cancer treatments.

Effects of Dietary Maltol on Innate Immunity, Gut Health, and Growth Performance of Broiler Chickens Challenged With Eimeria maxima

Two studies were conducted to evaluate the effects of maltol as a postbiotic on innate immunity, gut health, and enteric infection. In the first study, an in vitro culture system was used to evaluate the effects of maltol on the innate immune response of chicken macrophage cells (CMC), gut integrity of chicken intestinal epithelial cells (IEC), anti-parasitic activity against Eimeria maxima, and differentiation of quail muscle cells (QMC) and primary chicken embryonic muscle cells (PMC). All cells seeded in the 24-well plates were treated with maltol at concentrations of 0.1, 1.0, and 10.0 μg. CMC and IEC were stimulated by lipopolysaccharide to induce an innate immune response, and QMC and PMC were treated with 0.5 and 2% fetal bovine serum, respectively. After 18 h of incubation, pro-inflammatory cytokines, tight junction proteins (TJPs), and muscle cell growth markers were measured. In the second study, the dietary effect of maltol was evaluated on disease parameters in broiler chickens infected with E. maxima. Eighty male 1-day-old broiler chickens were allocated into the following four treatment groups: (1) Control group without infection, (2) Basal diet with E. maxima, (3) High maltol (HI; 10.0 mg /kg feed) with E. maxima, and (4) Low maltol (LO; 1.0 mg/kg feed) with E. maxima. Body weights (BW) were measured on days 0, 7, 14, 20, and 22. All chickens except the CON group were orally infected with 10⁴E. maxima per chicken on day 14. Jejunum samples were collected for gut lesion scoring, and the gene expression of cytokines and TJPs. Data was analyzed using PROC MIXED in SAS. In vitro, maltol not only increased TJPs in IEC and cytokines in the LPS-stimulated CMC but also showed direct cytotoxicity against sporozoites of E. maxima. In vivo, the HI group improved the BW, reduced the gut lesion scores and fecal oocyst shedding, and decreased jejunal TNFSF15 and IL-1β expression in E. maxima-infected chickens. In conclusion, these results demonstrate the beneficial effects of dietary maltol in the enhancement of growth performance, gut health, and coccidiosis resistance and the applicability of maltol as a postbiotic for the replacement of antibiotic growth promoters in commercial poultry production.

Spare and repair the gut microbiota from antibiotic-induced dysbiosis: state-of-the-art

Homeostasis of the intestinal microbiota is currently recognized as a major contributor to human health. Furthermore, intestinal dysbiosis is associated with a multitude of consequences, including intestinal colonization by antibiotic-resistant or pathogenic bacteria, such as Clostridioides difficile, and reduced efficacy of promising anticancer immunotherapies. By far, the most immediate and drastic exposure leading to dysbiosis is antibiotic treatment. Many attempts have been made to prevent or repair antibiotic-associated dysbiosis. Here, we review these innovations and the difficulties associated with their development.

Metabolic Modeling to Interrogate Microbial Disease: A Tale for Experimentalists

The explosion of microbiome analyses has helped identify individual microorganisms and microbial communities driving human health and disease, but how these communities function is still an open question. For example, the role for the incredibly complex metabolic interactions among microbial species cannot easily be resolved by current experimental approaches such as 16S rRNA gene sequencing, metagenomics and/or metabolomics. Resolving such metabolic interactions is particularly challenging in the context of polymicrobial communities where metabolite exchange has been reported to impact key bacterial traits such as virulence and antibiotic treatment efficacy. As novel approaches are needed to pinpoint microbial determinants responsible for impacting community function in the context of human health and to facilitate the development of novel anti-infective and antimicrobial drugs, here we review, from the viewpoint of experimentalists, the latest advances in metabolic modeling, a computational method capable of predicting metabolic capabilities and interactions from individual microorganisms to complex ecological systems. We use selected examples from the literature to illustrate how metabolic modeling has been utilized, in combination with experiments, to better understand microbial community function. Finally, we propose how such combined, cross-disciplinary efforts can be utilized to drive laboratory work and drug discovery moving forward.

The gut microbiome as a target for adjuvant therapy in obstructive sleep apnea

Introduction: Gut dysbiosis is assumed to play a role in obstructive sleep apnea (OSA)-associated morbidities. Pre- and probiotics, short chain fatty acids (SCFA) and fecal matter transplantation (FMT) may offer potential as novel therapeutic strategies that target this gut dysbiosis. As more mechanisms of OSA-induced dysbiosis are being elucidated, these novel approaches are being tested in preclinical and clinical development. Areas covered: We examined the evidence linking OSA to gut dysbiosis and discuss the effects of pre- and probiotics on associated cardiometabolic, neurobehavioral and gastrointestinal disorders. The therapeutic potential of SCFA and FMT are also discussed. We reviewed the National Center for Biotechnology Information database, including PubMed and PubMed Central between 2000 - 2020. Expert opinion: To date, there are no clinical trials and only limited evidence from animal studies describing the beneficial effects of pre- and probiotic supplementation on OSA-mediated dysbiosis. Thus, more work is necessary to assess whether prebiotics, probiotics and SCFA are promising future novel strategies for targeting OSA-mediated dysbiosis.

Metagenome analysis from the sediment of river Ganga and Yamuna: In search of beneficial microbiome

Beneficial microbes are all around us and it remains to be seen, whether all diseases and disorders can be prevented or treated with beneficial microbes. In this study, the presence of various beneficial bacteria were identified from the sediments of Indian major Rivers Ganga and Yamuna from nine different sites using a metagenomic approach. The metagenome sequence analysis using the Kaiju Web server revealed the presence of 69 beneficial bacteria. Phylogenetic analysis among these bacterial species revealed that they were highly diverse. Relative abundance analysis of these bacterial species is highly correlated with different pollution levels among the sampling sites. The PCA analysis revealed that Lactobacillus spp. group of beneficial bacteria are more associated with sediment sampling sites, KAN-2 and ND-3; whereas Bacillus spp. are more associated with sites, FAR-2 and ND-2. This is the first report revealing the richness of beneficial bacteria in the Indian rivers, Ganga and Yamuna. The study might be useful in isolating different important beneficial microorganisms from these river sediments, for possible industrial applications.

Systematic review of an intervention: the use of probiotics to improve health and productivity of calves

The aims of this study were to undertake a systematic review and meta-analysis of the types of probiotic formulations that are commercially available and to critically appraise the available evidence for the effectiveness of probiotics in improving the health and productivity of calves. Relevant papers were identified to answer the question: 'In calves aged between birth to one year, is the use of probiotics associated with changes in haematological or biochemical parameters, faecal bacteria counts, average daily live weight gain, dry matter intake, or feed conversion ratio?' The search of the literature yielded 67 studies that fit the primary screening criteria. Included studies were assessed for bias and confounding using a predefined risk assessment tool adapted from the Cochrane Collaboration's tool for assessing risk of bias in randomised trials and GRADE guidelines. Meta-analysis was performed using Review Manager and R. Random sequence generation was low in more than 59 % of studies. Risk of allocation concealment and performance bias were largely unclear in over 68 % of studies. Calves fed probiotics had increased average daily live weight gains (ADG) from birth to weaning (mean difference [MD] = 83.14 g/d 95 % CI = 58.36-107.91, P < 0.001) compared with calves on a control diet. Calf age reduced the level of heterogeneity of the effect of probiotics on ADG for calves between one to three weeks of age (τ² = 73.15; I² = 4%; P = 0.40) but not for calves older than three weeks of age (τ² = 2892.91; I² = 73 %; P < 0.001). Feed conversion ratio (FCR) was lower for calves on probiotics (MD = -0.13 kg of dry matter intake (DMI) to kg of live weight (LW) gain, 95 % CI = -0.17 to -0.09, P < 0.001), and the heterogeneity of effect was large in younger aged calves (τ² = 0.05; I² = 78 %; P = 0.03). The risk of bias regarding the methodology in the included studies was high. The quality of evidence for each outcome was categorised as moderate. There is sufficient data to support the effectiveness of probiotic use in some applications such as for the improvement of performance and productivity parameters of calves. However, the evidence is weak for other potential probiotic uses in calves such as improved health and reduced risk of disease. Therefore, the existing data are inconclusive and do not support the use of probiotics as an alternative to antimicrobials to improve calf health and productivity.

Systems Biology Approaches to Understand the Host-Microbiome Interactions in Neurodegenerative Diseases

Neurodegenerative diseases (NDDs) comprise a broad range of progressive neurological disorders with multifactorial etiology contributing to disease pathophysiology. Evidence of the microbiome involvement in the gut-brain axis urges the interest in understanding metabolic interactions between the microbiota and host physiology in NDDs. Systems Biology offers a holistic integrative approach to study the interplay between the different biologic systems as part of a whole, and may elucidate the host–microbiome interactions in NDDs. We reviewed direct and indirect pathways through which the microbiota can modulate the bidirectional communication of the gut-brain axis, and explored the evidence of microbial dysbiosis in Alzheimer’s and Parkinson’s diseases. As the gut microbiota being strongly affected by diet, the potential approaches to targeting the human microbiota through diet for the stimulation of neuroprotective microbial-metabolites secretion were described. We explored the potential of Genome-scale metabolic models (GEMs) to infer microbe-microbe and host-microbe interactions and to identify the microbiome contribution to disease development or prevention. Finally, a systemic approach based on GEMs and ‘omics integration, that would allow the design of sustainable personalized anti-inflammatory diets in NDDs prevention, through the modulation of gut microbiota was described.

Carbohydrate active enzymes are affected by diet transition from milk to solid food in infant gut microbiota

Infants experience a dramatic change in their food in the first year after birth when they shift from breast milk to solid food. This results in a large change in presence of indigestible polysaccharides, a primary energy resource of gut microbes. How the gut microbiota adapts to this dietary shift has not been well examined. Here, by using metagenomics data, we studied carbohydrate-active enzymes (CAZymes) of gut microbiota, which are essential enzymes catalyzing the breakdown of polysaccharides, during this dietary shift. We developed a new approach to categorize CAZyme families by food intake and found CAZyme families associated with milk or solid food. We also found CAZymes with most abundance in 12 months infants that are not associated with solid food or milk but may be related to modulating carbohydrates in the mucus. Additionally, the abundance of gut CAZymes were found to be affected by many other factors, including delivery modes and life style in adults. Taken together, our findings provide novel insights into the dynamic change of gut CAZymes in early human life and provide potential markers for food interference or gut microbiota restoration.

The interaction between microbiome and host central nervous system: the gut-brain axis as a potential new therapeutic target in the treatment of obesity and cardiometabolic disease

INTRODUCTION

The role of the intestinal microbiota in host cardiometabolic health and disease has gained significant attention over recent decades. Previous studies have shown effects on metabolic health through gut microbiota modulation; this suggests diverse interaction pathways that constitute the communication between gut microbiota and host central nervous system, the so-called gut-brain axis.

AREAS COVERED

This article provides an overview of the various mechanisms that may mediate the gut-brain axis. It places an emphasis on cardiometabolic health, including effects of short-chain fatty acids (SCFA), alterations in neurotransmitters and gut peptides and microbial effects on chronic inflammation and immune function. Moreover, this paper sheds light on whether these mechanisms afford therapeutic targets to promote metabolic health. To this end, a PubMed search with the terms 'gut microbiota,' 'obesity' and 'insulin sensitivity' was performed.

EXPERT OPINION

Many properties of the human gut microbiome are associated with the central regulation of appetite and metabolic status. Some of these relationships are causal and there are positive effects from certain intervention methods. Microbial manipulation may offer a means to prevent or treat obesity and associated co-morbidities. However, to establish direct causal relations between altered gut microbiota and metabolic disease, clinical intervention studies are necessary.

Applying Differential Neural Networks to Characterize Microbial Interactions in an Ex Vivo Gastrointestinal Gut Simulator

The structure of mixed microbial cultures—such as the human gut microbiota—is influenced by a complex interplay of interactions among its community members. The objective of this study was to propose a strategy to characterize microbial interactions between particular members of the community occurring in a simulator of the human gastrointestinal tract used as the experimental system. Four runs were carried out separately in the simulator: two of them were fed with a normal diet (control system), and two more had the same diet supplemented with agave fructans (fructan-supplemented system). The growth kinetics of Lactobacillus spp., Bifidobacterium spp., Salmonella spp., and Clostridium spp. were assessed in the different colon sections of the simulator for a nine-day period. The time series of microbial concentrations were used to estimate specific growth rates and pair-wise interaction coefficients as considered by the generalized Lotka-Volterra (gLV) model. A differential neural network (DNN) composed of a time-adaptive set of differential equations was applied for the nonparametric identification of the mixed microbial culture, and an optimization technique was used to determine the interaction parameters, considering the DNN identification results and the structure of the gLV model. The assessment of the fructan-supplemented system showed that microbial interactions changed significantly after prebiotics administration, demonstrating their modulating effect on microbial interactions. The strategy proposed here was applied satisfactorily to gain quantitative and qualitative knowledge of a broad spectrum of microbial interactions in the gut community, as described by the gLV model. In the future, it may be utilized to study microbial interactions within mixed cultures using other experimental approaches and other mathematical models (e.g., metabolic models), which will yield crucial information for optimizing mixed microbial cultures to perform certain processes—such as environmental bioremediation or modulation of gut microbiota—and to predict their dynamics.

Towards Predicting Gut Microbial Metabolism: Integration of Flux Balance Analysis and Untargeted Metabolomics

Genomics-based metabolic models of microorganisms currently have no easy way of corroborating predicted biomass with the actual metabolites being produced. This study uses untargeted mass spectrometry-based metabolomics data to generate a list of accurate metabolite masses produced from the human commensal bacteria Citrobacter sedlakii grown in the presence of a simple glucose carbon source. A genomics-based flux balance metabolic model of this bacterium was previously generated using the bioinformatics tool PyFBA and phenotypic growth curve data. The high-resolution mass spectrometry data obtained through timed metabolic extractions were integrated with the predicted metabolic model through a program called MS_FBA. This program correlated untargeted metabolomics features from C. sedlakii with 218 of the 699 metabolites in the model using an exact mass match, with 51 metabolites further confirmed using predicted isotope ratios. Over 1400 metabolites were matched with additional metabolites in the ModelSEED database, indicating the need to incorporate more specific gene annotations into the predictive model through metabolomics-guided gap filling.

Resources and tools for the high-throughput, multi-omic study of intestinal microbiota

The human gut microbiome impacts several aspects of human health and disease, including digestion, drug metabolism and the propensity to develop various inflammatory, autoimmune and metabolic diseases. Many of the molecular processes that play a role in the activity and dynamics of the microbiota go beyond species and genic composition and thus, their understanding requires advanced bioinformatics support. This article aims to provide an up-to-date view of the resources and software tools that are being developed and used in human gut microbiome research, in particular data integration and systems-level analysis efforts. These efforts demonstrate the power of standardized and reproducible computational workflows for integrating and analysing varied omics data and gaining deeper insights into microbe community structure and function as well as host-microbe interactions.

Microbial composition of enigmatic bird parasites: Wolbachia and Spiroplasma are the most important bacterial associates of quill mites (Acariformes: Syringophilidae)

Background

The microbiome is an integral component of many animal species, potentially affecting behavior, physiology, and other biological properties. Despite this importance, bacterial communities remain vastly understudied in many groups of invertebrates, including mites. Quill mites (Acariformes: Syringophilidae) are a poorly known group of permanent bird ectoparasites that occupy quills of feathers and feed on bird subcutaneous tissue and fluids. Most of the known species have strongly female‐biased sex ratio, and it was hypothesized that this is caused by endosymbiotic bacteria. Previously, Anaplasma phagocytophilum (Foggie) and a high diversity of Wolbachia strains were detected in quill mites via targeted PCR screens. Here, we use an unbiased 16S rRNA gene amplicon sequencing approach to determine other bacteria that potentially impact quill mite biology.

Results

We performed 16S rRNA gene amplicon sequencing of 126 quill mite individuals from eleven species parasitizing twelve species (four families) of passeriform birds. In addition to Wolbachia, we found Spiroplasma as potential symbiont of quill mites. Consistently, high Spiroplasma titers were only found in individuals of two mite species associated with finches of the genus Carduelis, suggesting a history of horizontal transfers of Spiroplasma via the bird host. Furthermore, there was evidence for Spiroplasma negatively affecting Wolbachia titers. We found no evidence for the previously reported Anaplasma in quill mites, but detected sequences of high similarity to the potential pathogens Brucella and Bartonella at low abundances. Other amplicon sequence variants (ASVs) could be assigned to a diverse number of bacterial taxa, including several that were previously isolated from bird skin. Further, many frequently found ASVs were assigned to taxa that show a very broad distribution with no strong prior evidence for symbiotic association with animals. We interpret these findings as evidence for a scarcity of resident microbial associates (other than inherited symbionts) in quill mites.

Contents, Construction Methods, Data Resources, and Functions Comparative Analysis of Bacteria Databases

Many bacterial-related databases are developed to meet the researchers' needs of analysis and search for a number of bacterial information. However, these databases have different data resources, construction methods, data formats, and analysis tools. It's difficult for researchers to select appropriate databases and analysis tools to promote their researches. In the paper, we compared the contents, construction methods, data sources, update frequency, scope and scale of data, analysis tools, and features of nine famous bacterial databases: CARD, EffectiveDB, MBGD, MPD, PATRCI, PHI-base, VFDB, gcMeta and SILVA, and help researchers to better make better use of these databases. In addition, we also hope this review can help researchers develop a more comprehensive database and better tools to meet the needs of researchers.

Computational Modeling of the Human Microbiome

The impact of microorganisms on human health has long been acknowledged and studied, but recent advances in research methodologies have enabled a new systems-level perspective on the collections of microorganisms associated with humans, the human microbiome. Large-scale collaborative efforts such as the NIH Human Microbiome Project have sought to kick-start research on the human microbiome by providing foundational information on microbial composition based upon specific sites across the human body. Here, we focus on the four main anatomical sites of the human microbiome: gut, oral, skin, and vaginal, and provide information on site-specific background, experimental data, and computational modeling. Each of the site-specific microbiomes has unique organisms and phenomena associated with them; there are also high-level commonalities. By providing an overview of different human microbiome sites, we hope to provide a perspective where detailed, site-specific research is needed to understand causal phenomena that impact human health, but there is equally a need for more generalized methodology improvements that would benefit all human microbiome research.

Signature of Gut Microbiome by Conventional and Advanced Analysis Techniques: Advantages and Disadvantages

Gut microbiota is considered as a human organ with its own specific functions and complexity. Development of novel techniques such as shut gun sequencing, metagenomics, and next-generation sequencing (NGS) has enabled bypassing the traditional culturedependent bias and has significantly expanded our understanding of the composition, diversity, and roles of the gut microbiota in human health and diseases. Although amplicon sequencing characterizes the taxonomic composition of the gut microbiome, it is impossible to cover the direct evidence of the microbial biological functions related to the gut microbial community. Hence, the critical next step for gut microbiome studies is shifting from gene/ genome-centric analysis to mechanism-centric techniques by integrating omics data with experimental results. Realizing gut microbial diversity and their bioactive metabolites function will provide insight into the clinical application of gut microbiota in diagnoses and treatments of several diseases. In this review, we focused on explaining the conventional and advanced microbiome analysis techniques regarding gut microbiota investigation with considering the advantages and disadvantages of the platforms.

Recent trends in molecular diagnostics of yeast infections: from PCR to NGS

The incidence of opportunistic yeast infections in humans has been increasing over recent years. These infections are difficult to treat and diagnose, in part due to the large number and broad diversity of species that can underlie the infection. In addition, resistance to one or several antifungal drugs in infecting strains is increasingly being reported, severely limiting therapeutic options and showcasing the need for rapid detection of the infecting agent and its drug susceptibility profile. Current methods for species and resistance identification lack satisfactory sensitivity and specificity, and often require prior culturing of the infecting agent, which delays diagnosis. Recently developed high-throughput technologies such as next generation sequencing or proteomics are opening completely new avenues for more sensitive, accurate and fast diagnosis of yeast pathogens. These approaches are the focus of intensive research, but translation into the clinics requires overcoming important challenges. In this review, we provide an overview of existing and recently emerged approaches that can be used in the identification of yeast pathogens and their drug resistance profiles. Throughout the text we highlight the advantages and disadvantages of each methodology and discuss the most promising developments in their path from bench to bedside.

The Role of Adipose Tissue in the Pathogenesis and Therapeutic Outcomes of Inflammatory Bowel Disease

Though historically regarded as an inert energy store, adipose tissue is a complex endocrine organ, which is increasingly implicated in the pathogenesis of inflammatory bowel disease (IBD). Accumulating evidence points to visceral adipose tissue and specifically to its mesenteric component, or “creeping fat” as impacting on the disease course through its immunomodulatory properties. On the one hand, mesenteric fat acts as a physical barrier to inflammation and is involved in controlling host immune response to translocation of gut bacteria. On the other hand, however, there exists a strong link between visceral fat and complicated course of the disease with unfavorable therapeutic outcomes. Furthermore, “creeping fat” appears to play different roles in different IBD phenotypes, with the greatest pathogenetic contribution probably to an ileal form of Crohn’s disease. In this review, we summarize and discuss the existing literature on the subject and identify high-priority areas for future research. It may be that a better understanding of the role of mesenteric fat in IBD will determine new therapeutic targets and translate into improved clinical outcomes.

Sphingosine-1-phosphate signaling and the gut-liver axis in liver diseases

The liver is the central organ involved in lipid metabolism and the gastrointestinal (GI) tract is responsible for nutrient absorption and partitioning. Obesity, dyslipidemia and metabolic disorders are of increasing public health concern worldwide, and novel therapeutics that target both the liver and the GI tract (gut-liver axis) are much needed. In addition to aiding fat digestion, bile acids act as important signaling molecules that regulate lipid, glucose and energy metabolism via activating nuclear receptor, G protein-coupled receptors (GPCRs), Takeda G protein receptor 5 (TGR5) and sphingosine-1-phosphate receptor 2 (S1PR2). Sphingosine-1-phosphate (S1P) is synthesized by two sphingosine kinase isoforms and is a potent signaling molecule that plays a critical role in various diseases such as fatty liver, inflammatory bowel disease (IBD) and colorectal cancer. In this review, we will focus on recent findings related to the role of S1P-mediated signaling pathways in the gut-liver axis.

Analyzing the Secretome of Gut Microbiota as the Next Strategy For Early Detection of Colorectal Cancer

Dysbiosis of gut microbiome can contribute to inflammation, and subsequently initiation and progression of colorectal cancer (CRC). Throughout these stages, various proteins and metabolites are secreted to the external environment by microorganisms or the hosts themselves. Studying these proteins may help enhance our understanding of the host-microorganism relationship or they may even serve as useful biomarkers for CRC. However, secretomic studies of gut microbiome of CRC patients, until now, are scarcely performed. In this review article, the focus is on the roles of gut microbiome in CRC, the current findings on CRC secretome are highlighted, and the emerging challenges and strategies to drive forward this area of research are addressed.

The Human Mesenteric Lymph Node Microbiome Differentiates Between Crohn's Disease and Ulcerative Colitis

BACKGROUND AND AIMS

Mesenteric lymph nodes are sites in which translocated bacteria incite and progress immunological responses. For this reason, understanding the microbiome of mesenteric lymph nodes in inflammatory bowel disease is important. The bacterial profile of Crohn's disease mesenteric lymph nodes has been analysed using culture-independent methods in only one previous study. This study aimed to investigate the mesenteric lymph node microbiota from both Crohn's disease and ulcerative colitis patients.

METHODS

Mesenteric lymph nodes were collected from Crohn's disease and ulcerative colitis patients undergoing resection. Total DNA was extracted from mesenteric lymph nodes and assessed for the presence of bacterial DNA [16S]. All work was completed in a sterile environment using aseptic techniques. Samples positive for 16S DNA underwent next-generation sequencing, and the identity of bacterial phyla and species were determined.

RESULTS

Crohn's disease mesenteric lymph nodes had a distinctly different microbial profile to that observed in ulcerative colitis. The relative abundance of Firmicutes was greater in nodes from ulcerative colitis patients, whereas Proteobacteria were more abundant in Crohn's disease. Although species diversity was reduced in the mesenteric lymph nodes of patients with Crohn's disease, these lymph nodes contained greater numbers of less dominant phyla, mainly Fusobacteria.

CONCLUSION

This study confirms that there are distinct differences between the Crohn's disease and ulcerative colitis mesenteric lymph node microbiomes. Such microbial differences could aid in the diagnosis of Crohn's disease or ulcerative colitis, particularly in cases of indeterminate colitis at time of resection, or help explain their mechanisms of development and progression.

A Diverse Range of Human Gut Bacteria Have the Potential To Metabolize the Dietary Component Gallic Acid

The human gut microbiota contains a broad variety of bacteria that possess functional genes, with resultant metabolites that affect human physiology and therefore health. Dietary gallates are phenolic components that are present in many foods and beverages and are regarded as having health-promoting attributes. However, the potential for metabolism of these phenolic compounds by the human microbiota remains largely unknown. The emergence of high-throughput sequencing (HTS) technologies allows this issue to be addressed. In this study, HTS was used to assess the incidence of gallate-decarboxylating bacteria within the gut microbiota of healthy individuals for whom bacterial diversity was previously determined to be high. This process was facilitated by the design and application of degenerate PCR primers to amplify a region encoding the catalytic C subunit of gallate decarboxylase (LpdC) from total metagenomic DNA extracted from human fecal samples. HTS resulted in the generation of a total of 3,261,967 sequence reads and revealed that the primary gallate-decarboxylating microbial phyla in the intestinal microbiota were Firmicutes (74.6%), Proteobacteria (17.6%), and Actinobacteria (7.8%). These reads corresponded to 53 genera, i.e., 47% of the bacterial genera detected previously in these samples. Among these genera, Anaerostipes and Klebsiella accounted for the majority of reads (40%). The usefulness of the HTS-lpdC method was demonstrated by the production of pyrogallol from gallic acid, as expected for functional gallate decarboxylases, among representative strains belonging to species identified in the human gut microbiota by this method.IMPORTANCE Despite the increasing wealth of sequencing data, the health contributions of many bacteria found in the human gut microbiota have yet to be elucidated. This study applies a novel experimental approach to predict the ability of gut microbes to carry out a specific metabolic activity, i.e., gallate metabolism. The study showed that, while gallate-decarboxylating bacteria represented 47% of the bacterial genera detected previously in the same human fecal samples, no gallate decarboxylase homologs were identified from representatives of Bacteroidetes The presence of functional gallate decarboxylases was demonstrated in representative Proteobacteria and Firmicutes strains from the human microbiota, an observation that could be of considerable relevance to the in vivo production of pyrogallol, a physiologically important bioactive compound.

Methanobacterium formicicum as a target rumen methanogen for the development of new methane mitigation interventions: A review

Methanobacterium formicicum (Methanobacteriaceae family) is an endosymbiotic methanogenic Archaean found in the digestive tracts of ruminants and elsewhere. It has been significantly implicated in global CH₄ emission during enteric fermentation processes. In this review, we discuss current genomic and metabolic aspects of this microorganism for the purpose of the discovery of novel veterinary therapeutics. This microorganism encompasses a typical H₂ scavenging system, which facilitates a metabolic symbiosis across the H₂ producing cellulolytic bacteria and fumarate reducing bacteria. To date, five genome-scale metabolic models (iAF692, iMG746, iMB745, iVS941 and iMM518) have been developed. These metabolic reconstructions revealed the cellular and metabolic behaviors of methanogenic archaea. The characteristics of its symbiotic behavior and metabolic crosstalk with competitive rumen anaerobes support understanding of the physiological function and metabolic fate of shared metabolites in the rumen ecosystem. Thus, systems biological characterization of this microorganism may provide a new insight to realize its metabolic significance for the development of a healthy microbiota in ruminants. An in-depth knowledge of this microorganism may allow us to ensure a long term sustainability of ruminant-based agriculture.

From metagenomic data to personalized in silico microbiotas: predicting dietary supplements for Crohn's disease

Crohn's disease (CD) is associated with an ecological imbalance of the intestinal microbiota, consisting of hundreds of species. The underlying complexity as well as individual differences between patients contributes to the difficulty to define a standardized treatment. Computational modeling can systematically investigate metabolic interactions between gut microbes to unravel mechanistic insights. In this study, we integrated metagenomic data of CD patients and healthy controls with genome-scale metabolic models into personalized in silico microbiotas. We predicted short chain fatty acid (SFCA) levels for patients and controls, which were overall congruent with experimental findings. As an emergent property, low concentrations of SCFA were predicted for CD patients and the SCFA signatures were unique to each patient. Consequently, we suggest personalized dietary treatments that could improve each patient's SCFA levels. The underlying modeling approach could aid clinical practice to find dietary treatment and guide recovery by rationally proposing food aliments.

Understanding the Representative Gut Microbiota Dysbiosis in Metformin-Treated Type 2 Diabetes Patients Using Genome-Scale Metabolic Modeling

Dysbiosis in the gut microbiome composition may be promoted by therapeutic drugs such as metformin, the world’s most prescribed antidiabetic drug. Under metformin treatment, disturbances of the intestinal microbes lead to increased abundance of Escherichia spp., Akkermansia muciniphila, Subdoligranulum variabile and decreased abundance of Intestinibacter bartlettii. This alteration may potentially lead to adverse effects on the host metabolism, with the depletion of butyrate producer genus. However, an increased production of butyrate and propionate was verified in metformin-treated Type 2 diabetes (T2D) patients. The mechanisms underlying these nutritional alterations and their relation with gut microbiota dysbiosis remain unclear. Here, we used Genome-scale Metabolic Models of the representative gut bacteria Escherichia spp., I. bartlettii, A. muciniphila, and S. variabile to elucidate their bacterial metabolism and its effect on intestinal nutrient pool, including macronutrients (e.g., amino acids and short chain fatty acids), minerals and chemical elements (e.g., iron and oxygen). We applied flux balance analysis (FBA) coupled with synthetic lethality analysis interactions to identify combinations of reactions and extracellular nutrients whose absence prevents growth. Our analyses suggest that Escherichia sp. is the bacteria least vulnerable to nutrient availability. We have also examined bacterial contribution to extracellular nutrients including short chain fatty acids, amino acids, and gasses. For instance, Escherichia sp. and S. variabile may contribute to the production of important short chain fatty acids (e.g., acetate and butyrate, respectively) involved in the host physiology under aerobic and anaerobic conditions. We have also identified pathway susceptibility to nutrient availability and reaction changes among the four bacteria using both FBA and flux variability analysis. For instance, lipopolysaccharide synthesis, nucleotide sugar metabolism, and amino acid metabolism are pathways susceptible to changes in Escherichia sp. and A. muciniphila. Our observations highlight important commensal and competing behavior, and their association with cellular metabolism for prevalent gut microbes. The results of our analysis have potential important implications for development of new therapeutic approaches in T2D patients through the development of prebiotics, probiotics, or postbiotics.

Gut metabolome meets microbiome: A methodological perspective to understand the relationship between host and microbe

It is well established that gut microbes and their metabolic products regulate host metabolism. The interactions between the host and its gut microbiota are highly dynamic and complex. In this review we present and discuss the metabolomic strategies to study the gut microbial ecosystem. We highlight the metabolic profiling approaches to study faecal samples aimed at deciphering the metabolic product derived from gut microbiota. We also discuss how metabolomics data can be integrated with metagenomics data derived from gut microbiota and how such approaches may lead to better understanding of the microbial functions. Finally, the emerging approaches of genome-scale metabolic modelling to study microbial co-metabolism and host-microbe interactions are highlighted.

Microbiota dysbiosis in inflammatory bowel diseases: in silico investigation of the oxygen hypothesis

BACKGROUND

Inflammatory bowel diseases (IBD), which include ulcerative colitis and Crohn's disease, cause chronic inflammation of the digestive tract in approximately 1.6 million Americans. A signature of IBD is dysbiosis of the gut microbiota marked by a significant reduction of obligate anaerobes and a sharp increase in facultative anaerobes. Numerous experimental studies have shown that IBD is strongly correlated with a decrease of Faecalibacterium prausnitzii and an increase of Escherichia coli. One hypothesis is that chronic inflammation induces increased oxygen levels in the gut, which in turn causes an imbalance between obligate and facultative anaerobes.

RESULTS

To computationally investigate the oxygen hypothesis, we developed a multispecies biofilm model based on genome-scale metabolic reconstructions of F. prausnitzii, E. coli and the common gut anaerobe Bacteroides thetaiotaomicron. Application of low bulk oxygen concentrations at the biofilm boundary reproduced experimentally observed behavior characterized by a sharp decrease of F. prausnitzii and a large increase of E. coli, demonstrating that dysbiosis consistent with IBD disease progression could be qualitatively predicted solely based on metabolic differences between the species. A diet with balanced carbohydrate and protein content was predicted to represent a metabolic "sweet spot" that increased the oxygen range over which F. prausnitzii could remain competitive and IBD could be sublimated. Host-microbiota feedback incorporated via a simple linear feedback between the average F. prausnitzii concentration and the bulk oxygen concentration did not substantially change the range of oxygen concentrations where dysbiosis was predicted, but the transition from normal species abundances to severe dysbiosis was much more dramatic and occurred over a much longer timescale. Similar predictions were obtained with sustained antibiotic treatment replacing a sustained oxygen perturbation, demonstrating how IBD might progress over several years with few noticeable effects and then suddenly produce severe disease symptoms.

CONCLUSIONS

The multispecies biofilm metabolic model predicted that oxygen concentrations of ∼1 micromolar within the gut could cause microbiota dysbiosis consistent with those observed experimentally for inflammatory bowel diseases. Our model predictions could be tested directly through the development of an appropriate in vitro system of the three species community and testing of microbiota-host interactions in gnotobiotic mice.