Boolean analysis reveals systematic interactions among low-abundance species in the human gut microbiome

The analysis of microbiome compositions in the human gut has gained increasing interest due to the broader availability of data and functional databases and substantial progress in data analysis methods, but also due to the high relevance of the microbiome in human health and disease. While most analyses infer interactions among highly abundant species, the large number of low-abundance species has received less attention. Here we present a novel analysis method based on Boolean operations applied to microbial co-occurrence patterns. We calibrate our approach with simulated data based on a dynamical Boolean network model from which we interpret the statistics of attractor states as a theoretical proxy for microbiome composition. We show that for given fractions of synergistic and competitive interactions in the model our Boolean abundance analysis can reliably detect these interactions. Analyzing a novel data set of 822 microbiome compositions of the human gut, we find a large number of highly significant synergistic interactions among these low-abundance species, forming a connected network, and a few isolated competitive interactions

High throughput genome scale modeling predicts microbial vitamin requirements contribute to gut microbiome community structure

Data availability statement: All data generated or analyzed during this study are included in this published article and its supplementary information files.Copyright © 2022 The Author(s). Human gut microbiome structure and emergent metabolic outputs impact health outcomes. However, what drives such community characteristics remains underexplored. Here, we rely on high throughput genomic reconstruction modeling, to infer the metabolic attributes and nutritional requirements of 816 gut strains, via a framework termed GEMNAST. This has been performed in terms of a group of human vitamins to examine the role vitamin exchanges have at different levels of community organization. We find that only 91 strains can satisfy their vitamin requirements (prototrophs) while the rest show various degrees of auxotrophy/specialization, highlighting their dependence on external sources, such as other members of the microbial community. Further, 79% of the strains in our sample were mapped to 11 distinct vitamin requirement profiles with low phylogenetic consistency. Yet, we find that human gut microbial community enterotype indicators display marked metabolic differences. Prevotella strains display a metabolic profile that can be complemented by strains from other genera often associated with the Prevotella enterotype and agrarian diets, while Bacteroides strains occupy a prototrophic profile. Finally, we identify pre-defined interaction modules (IMs) of gut species from human and mice predicted to be driven by, or highly independent of vitamin exchanges. Our analysis provides mechanistic grounding to gut microbiome stability and to co-abundance-based observations, a fundamental step toward understanding emergent processes that influence health outcomes. Further, our work opens a path to future explorations in the field through applications of GEMNAST to additional nutritional dimensions.University of Sydney (PhD scholarship and à Beckett Cancer Research Trust Fellowship)

Research gaps in diet and nutrition in inflammatory bowel disease. A topical review by D-ECCO Working Group (Dietitians of ECCO)

Although the current doctrine of IBD pathogenesis proposes an interaction between environmental factors with gut microbiota in genetically-susceptible individuals, dietary exposures have attracted recent interest and are, at least in part, likely to explain the rapid rise in disease incidence and prevalence. The D-ECCO working group along with other ECCO experts with expertise in nutrition, microbiology, physiology and medicine reviewed the evidence investigating the role of diet and nutritional therapy in the onset, perpetuation and management of IBD. A narrative topical review is presented where evidence pertinent to the topic is summarized collectively under three main thematic domains: i) the role of diet as an environmental factor in IBD aetiology; ii) the role of diet as induction and maintenance therapy in IBD; and iii) assessment of nutritional status and supportive nutritional therapy in IBD. A summary of research gaps for each of these thematic domains is proposed which is anticipated to be agenda setting for future research in the area of diet and nutrition in IBD

Gut microbiota functions: metabolism of nutrients and other food components

The diverse microbial community that inhabits the human gut has an extensive metabolic repertoire that is distinct from, but complements the activity of mammalian enzymes in the liver and gut mucosa and includes functions essential for host digestion. As such, the gut microbiota is a key factor in shaping the biochemical profile of the diet and, therefore, its impact on host health and disease. The important role that the gut microbiota appears to play in human metabolism and health has stimulated research into the identification of specific microorganisms involved in different processes, and the elucidation of metabolic pathways, particularly those associated with metabolism of dietary components and some host-generated substances. In the first part of the review, we discuss the main gut microorganisms, particularly bacteria, and microbial pathways associated with the metabolism of dietary carbohydrates (to short chain fatty acids and gases), proteins, plant polyphenols, bile acids, and vitamins. The second part of the review focuses on the methodologies, existing and novel, that can be employed to explore gut microbial pathways of metabolism. These include mathematical models, omics techniques, isolated microbes, and enzyme assays

Strain-resolved analysis of the human intestinal microbiota

The gut microbiota is ascribed a crucial role in human health, particularly in regulating immune and inflammatory responses, which is why it is being associated with a wide range of diseases, including obesity, diabetes, and cancer. Nonetheless, fundamental ecological questions of microbiome establishment, stability and resilience, as well as its transmission across hosts and generations remain incompletely understood, partly due to the lack of methods for high-resolution microbiome profiling. New insights in this field can therefore directly contribute to the development of bacterial and microbiota-based therapies. This work introduces SameStr, a novel bioinformatic program for strain-resolved metagenomics that allows for the specific tracking of microbes across samples, enabling the detection and quantification of microbial transmission and persistence, as well as the observation of direct strain competition. Deployed across cohorts to process over 4200 metagenomes, SameStr enabled analysis of the microbiome with unprecedented phylogenetic resolution. The data included both publicly available metagenomes and sequence data generated in collaboration with our research partners, and was examined using multivariate statistics and machine learning frameworks. First, the establishment and development of the neonatal microbiota was studied, revealing a birth mode-dependent vertical transmission of the maternal microbiota. The microbiota of neonates born by cesarean section was characterized by increased relative abundance of oxygen-tolerant and atypical organisms and showed signs of a delayed establishment of a strictly anaerobic gut environment in these children. Such birth mode-dependent differences diminished over time, yet were measurable within the first two years of life. Furthermore, strain analysis verified the transmission and colonization of parental microbes, which indicated a possible lifelong colonization by microbes from selected species. The temporal persistence of microbes was also characterized in healthy adults, revealing similar taxonomy-dependent patterns of stability. For some species, persistence has been demonstrated both in children and in adults over a period of at least two years. These species are known for their capability to metabolize host-derived glycans found both in breastmilk and intestinal mucus, pointing to a potential strategy for effective cross-generational microbiota transmission, and warranting additional research to assess the implications of their disturbed transfer for long-term health. Since their specificity allows assignment to individual hosts, fingerprints of individual microbial strains offer the potential to be used in forensics and data quality control applications. Finally, to gain new insights into the microbiota dynamics during Fecal Microbiota Transplantation (FMT), microbial strain transmission was analyzed in the context of a diverse set of patient, microbiome, and clinical conditions. In the analyzed studies, FMT was used for the experimental treatment of a variety of diseases, including colonization with drug-resistant and pathogenic microbes, metabolic and inflammatory bowel diseases, and as an adjunct to the immunotherapeutic treatment of cancer. Analyses uncovered what appear to be the universal drivers of post-FMT microbiota assembly, including clinical and ecological factors that are important for successful transplantation of donor strains. In particular, the relevance of the microbiota dysbiosis of the recipient was emphasized, which was inducible by pre-treating the patient with antibiotics or laxatives. Presumably, this can open up ecological niches in the patients intestines, which favors colonization with donor strains. Colonization rates did not play a role for the treatment success of recurrent C. difficile infections and inflammatory bowel disease, but indicated a trend associated with an improved immune response in cancer patients. Concerningly, the transfer of an atypical and potentially pro-inflammatory microbial community from one donor was also observed, calling for further investigations into the immediate and long-term clinical consequences of FMT. These analyses demonstrate the advantages of a strain-based microbiome analysis. Due to the achieved methodological accuracy, strain-resolved microbial dynamics could be precisely disentangled when comparing longitudinal samples from healthy adults as well as parent-child and patient-donor pairs. This revealed taxonomic, clinical, and ecological factors that are critical to microbiome assembly, including microbial transmission, persistence, and competition. Together, these findings lay the groundwork for future developments of precision personalized microbiota modulation therapies.Der Darmmikrobiota wird eine entscheidende Rolle für die menschliche Gesundheit zugeschrieben, was insbesondere die Regulation von Immun- und Entzündungsreaktionen betrifft, weshalb sie mit einer Vielzahl von Krankheiten wie etwa Fettleibigkeit, Diabetes oder Krebs in Verbindung gebracht wird. Nichtsdestotrotz sind grundlegende ökologische Fragen der Etablierung, Stabilität und Resilienz von Mikrobiomen sowie ihrer Übertragung über Wirte und Generationen hinweg noch immer unvollständig untersucht, was teilweise auf das Fehlen von Methoden zur hochauflösenden Mikrobiom-Profilierung zurückzuführen ist. Neue Erkenntnisse auf diesem Gebiet können daher unmittelbar zur Entwicklung von Bakterien- und Mikrobiota-basierten Therapien beitragen. Diese Arbeit stellt SameStr vor, ein neues bioinformatisches Programm für stammaufgelöste Metagenomik, das die spezifische probenübergreifende Untersuchung von Mikroorganismen ermöglicht. Hiermit können der Nachweis und die Quantifizierung der Übertragung und Persistenz, sowie die Beobachtung der direkten Konkurrenz mikrobieller Stämme erfolgen. SameStr wurde kohortenübergreifend für die Analyse von über 4200 Metagenomen eingesetzt und ermöglichte die Profilierung des Mikrobioms mit einer beispiellosen phylogenetischen Auflösung. Die Metagenome, welche sowohl öffentlich verfügbare als auch in Zusammenarbeit mit unseren Forschungspartnern generierte Daten beinhalteten, konnten mittels multivariater Statistik und maschinellen Lernens beleuchtet werden. Zunächst wurde die Etablierung und Entwicklung der neonatalen Mikrobiota analysiert, was eine vom Geburtsmodus abhängige vertikale Übertragung der mütterlichen Mikrobiota aufzeigte. Die Mikrobiota von Neugeborenen die durch einen Kaiserschnitt zur Welt gekommen waren, war vermehrt von Sauerstoff-toleranten und Darm-untypischen Organismen besiedelt und deutete darauf hin, dass sich ein strikt anaerobes Darmmilieu bei diesen Kindern mit einer gewissen Verzögerung einstellte. Derartige geburtsabhängige Veränderungen schwächten sich mit der Zeit ab, waren jedoch bis zum zweiten Lebensjahr messbar. Weiterhin konnte die Übertragung und Kolonisierung elterlicher Organismen mittels Stamm-Analyse nachgewiesen werden, was außerdem auf eine mögliche lebenslange Besiedlung durch Mikroben ausgewählter Spezies hindeutete. Die zeitliche Persistenz von Mikroorganismen wurde darüber hinaus auch bei gesunden Erwachsenen charakterisiert, was ebenfalls Taxonomie-abhängige Stabilitätsmuster zum Vorschein brachte. Bei einigen Spezies, die bekannt dafür sind vom menschlichen Wirt stammende Glykane zu metabolisieren, wurde die Persistenz sowohl bei Kindern als auch bei Erwachsenen über einen Zeitraum von mindestens zwei Jahren nachgewiesen. Diese Glykane kommen sowohl in der Muttermilch als auch im Darmschleim vor, was auf eine potenzielle Strategie für eine effektive generationsübergreifende Übertragung der Mikrobiota hinweist. Um die langfristigen Auswirkungen einer gestörten Mikrobiota-Übertragung auf die Gesundheit bewerten zu können, wird jedoch weitere Forschung benötigt. Da ihre Spezifität die Zuordnung zu individuellen Wirten ermöglicht, bieten mikrobielle Stämme zudem das Potenzial in der Forensik und bei Datenqualitätstests Anwendung zu finden. Um schließlich neue Erkenntnisse zur Mikrobiota-Dynamik während der fäkalen Mikrobiota-Transplantation (FMT) zu gewinnen, wurde die Stammübertragung im Kontext einer Vielzahl von Patienten-, Mikrobiom- und klinischen Parametern analysiert. FMT wurde in den vorliegenden Studien zur experimentellen Behandlung verschiedenster Erkrankungen eingesetzt, darunter Kolonisierung mit resistenten und pathogenen Keimen, metabolische Erkrankungen, entzündliche Erkrankungen des Darms, sowie begleitend zur immuntherapeutischen Behandlung von Krebs. Die Analysen zeigten scheinbar universelle klinische und ökologische Faktoren auf, welche für eine erfolgreiche Integration von Spenderstämmen von Bedeutung sind. Insbesondere wurde die Relevanz der Mikrobiota-Dysbiose des Empfängers hervorgehoben, welche zudem durch Vorbehandlung der Patienten mittels Gabe von Antibiotika oder Laxativa induziert werden kann. Vermutlich können hierdurch ökologische Nischen im Darm der Patienten eröffnet werden, was eine Kolonisierung mit Spenderstämmen begünstigt. Kolonisierungsraten spielten für den Behandlungserfolg wiederkehrender Clostridien-Infektionen und entzündlicher Darmerkrankungen keine Rolle, deuteten jedoch auf einen Trend hin, der mit einer verbesserten Immunantwort bei Krebspatienten einhergeht. Beunruhigenderweise wurde auch die Übertragung einer atypischen und potenziell entzündungsfördernden Mikrobiota eines Donoren beobachtet, was weitere Untersuchungen zu unmittelbaren und langfristigen klinischen Folgen der FMT erforderlich macht. Die Ergebnisse dieser Arbeit zeigen die Vorteile einer Stamm-basierten Mikrobiom-Analyse auf. Durch die erreichte methodische Genauigkeit konnten bei Vergleichen von Zeitverlaufsproben gesunder Erwachsener sowie Eltern-Kind- und Patienten-Spender-Paaren, die Dynamiken mikrobieller Stämme präzise entschlüsselt werden. Dabei kamen taxonomische, klinische und ökologische Faktoren zum Vorschein, welche für die Zusammensetzung der Mikrobiota, einschließlich der mikrobiellen Übertragung, Persistenz und Kompetition, maßgebend sind. Diese neuen Erkenntnisse bilden die Grundlage für künftige Entwicklungen von Therapien zur präzisen, personalisierten Modulation der Mikrobiota

Evaluation of the oesophagogastric cancer associated microbiome: a systematic review and quality assessment

Objective. Oesophagogastric cancer is the fifth most common cancer worldwide, with poor survival outcomes. The role of bacteria in the pathogenesis of oesophagogastric cancer remains poorly understood. Design. A systematic search identified studies assessing the oesophagogastric cancer microbiome. The primary outcome was to identify bacterial enrichment specific to oesophagogastric cancer. Secondary outcomes included appraisal of the methodology, diagnostic performance of cancer bacteria and the relationship between oral and tissue microbiome. Results. A total of 9295 articles were identified, and 87 studies were selected for analysis. Five genera were enriched in gastric cancer: Lactobacillus, Streptococcus, Prevotella, Fusobacterium and Veillonella. No clear trends were observed in oesophageal adenocarcinoma. Streptococcus, Prevotella and Fusobacterium were abundant in oesophageal squamous cell carcinoma. Functional analysis supports the role of immune cells, localised inflammation and cancer-specific pathways mediating carcinogenesis. STORMS reporting assessment identified experimental deficiencies, considering batch effects and sources of contamination prevalent in low-biomass samples. Conclusions. Functional analysis of cancer pathways can infer tumorigenesis within the cancer–microbe–immune axis. There is evidence that study design, experimental protocols and analytical techniques could be improved to achieve more accurate and representative results. Whole-genome sequencing is recommended to identify key metabolic and functional capabilities of candidate bacteria biomarkers

Using metabolic networks to resolve ecological properties of microbiomes

The systematic collection, integration and modelling of high-throughput molecular data (multi-omics) allows the detailed characterisation of microbiomes in situ. Through metabolic trait inference, metabolic network reconstruction and modelling, we are now able to define ecological interactions based on metabolic exchanges, identify keystone genes, functions and species, and resolve ecological niches of constituent microbial populations. The resulting knowledge provides detailed information on ecosystem functioning. However, as microbial communities are dynamic in nature the field needs to move towards the integration of time- and space-resolved multi-omic data along with detailed environmental information to fully harness the power of community- and population-level metabolic network modelling. Such approaches will be fundamental for future targeted management strategies with wide-ranging applications in biotechnology and biomedicine

Exploring gut microbiome – host interactions in the extremes of health and disease

Introduction: Multi ‘omics analyses, including metabonomic and metagenomic profiling techniques, have enabled new insights into systems biology over the past decade. Using two extremes of a continuum between health and disease – elite athletes and obese patients undergoing bariatric surgery – the work in this thesis aims to apply metabolic phenotyping to further understand the impact of exercise, diet and obesity on human metabolism. Furthermore, through combinatorial analysis of metabonomic and gut microbiome data sets, host – gut microbiome co-metabolism and its influence on health is explored in these two extreme populations. Methods: Biofluids were collected from three cohorts: i) elite athletes and age and sex matched controls, ii) healthy individuals before and after a high protein diet, exercise regime or both, and iii) obese subjects pre and post bariatric surgery. Multiple analytical platforms were utilised for metabolic profiling including 1H-NMR spectroscopy, UPLC-MS and GC-MS. Gut microbiome analysis was performed using next generation metagenomic sequencing. After pre-processing the metabonomic and metagenomic data; univariate, unsupervised and supervised multivariate analyses were performed as well as gut microbiome-metabolite association studies. Results: Distinct metabolic and microbial phenotypes existed between both athletes and controls and between obese patients before and after bariatric surgery. Discriminatory metabolites higher in athletes include metabolites associated with muscle turnover, vitamins and recovery supplements, a high protein diet and those derived from gut microbes. Interestingly, increased bacterial diversity seen in athletes correlated with a specific subset of metabolites. Similarly, bariatric surgery resulted in large changes to circulating metabolites. A number of these metabolites were linked to changes in the gut microbiome, including bile acids, short-chain fatty acids and amino acids. Conclusion: This thesis extends existing knowledge of the gut microbiome’s influence on human health through small molecule signalling. Mechanistic studies are now needed to establish causal links between gut microbes, changes to circulating metabolites and disease status.Open Acces

Observational causality from -omics

Some human traits like disease are heritable, which means that they run in families. This indicates that there must be something on the DNA that affects an individual’s susceptibility to developing a trait. In the last 15 years, scientists from around the world have been very successful in mapping the locations on the DNA that are associated to traits like disease, finding thousands of loci, and hundreds of DNA locations per trait, making them truly complex traits. So, we have a very good understanding about which locations on the DNA are important for developing complex traits like disease. Unfortunately, it’s still unclear how these locations on the DNA affect an individual’s trait. In this thesis I investigate how we can best understand the DNA locations that affect trait susceptibility and in doing so, identify the causes for human traits like disease. One important technique that we have used to test for finding these causal relationships is called Mendelian randomization. Mendelian randomization identifies naturally occurring experiments that have happened in observational data. In principle, Mendelian randomization can conclude the same things from observational data as from an experimental study. So called `observational causality` has many benefits as it’s cheaper than an experiment, and is less burdensome on the subjects, as they are not subjected to any intervention. The causes that I’m interested in are so called `-omics` traits. -omics traits are molecular measurements that are usually strongly regulated by the DNA. This strong DNA regulation makes -omics traits interesting candidates to understand the mechanism behind the genetic loci of other traits. In this thesis we have investigated gene expression, protein levels and microbiome measurements as our -omics traits of interest for a wide variety of traits including celiac disease and LDL-cholesterol levels