Multiple levels of the unknown in microbiome research

Gut Microbiome Signature in Predisease Phase of Inflammatory Bowel Disease: Prediction to Pathogenesis to Prevention

Advances in understanding the pathogenesis of inflammatory bowel disease (IBD) point toward a key role of the gut microbiome. We review the data describing the changes in the gut microbiome from IBD case-control studies and compare these findings with emerging data from studies of the preclinical phase of IBD. What is apparent is that assessing changes in the composition and function of the gut microbiome during the preclinical phase helps address confounding factors, such as disease activity and drug therapy, which can directly influence the gut microbiome. Understanding these changes in the predisease phase provides a means of predicting IBD in high-risk populations and offers insights into possible mechanisms involved in disease pathogenesis. Finally, we discuss strategies to use this information to design interventions aimed at modulating the microbiome as a means of preventing or delaying the onset of IBD.

Enabling next-generation anaerobic cultivation through biotechnology to advance functional microbiome research

Microbiomes are complex communities of microorganisms that are essential for biochemical processes on Earth and for the health of humans, animals and plants. Many environmental and host-associated microbiomes are dominated by anaerobic microbes, some of which cannot tolerate oxygen. Anaerobic microbial communities have been extensively studied over the last 20 years using molecular techniques, especially next-generation sequencing. However, there is a renewed interest in microbial cultivation because isolates provide the basis for understanding the taxonomic and functional units of biodiversity, elucidating novel biochemical pathways and the mechanisms underlying microbe-microbe and microbe-host interactions and opening new avenues for biotechnological and clinical applications. In this Perspective, we present areas of research and applications that will benefit from advancement in anaerobic microbial cultivation. We highlight key technical and infrastructural hurdles associated with the development and deployment of sophisticated cultivation workflows. Improving the performance of cultivation techniques will set new trends in functional microbiome research in the coming years.

Coupling culturomics and metagenomics sequencing to characterize the gut microbiome of patients with cancer treated with immune checkpoint inhibitors

BACKGROUND

The gut microbiome represents a novel biomarker for melanoma and non-small cell lung cancer (NSCLC) patients treated with immune checkpoint inhibitors (ICI). Gut microbiome metagenomics profiling studies of patients treated with immunotherapy identified bacteria associated with ICI efficacy, while others have been linked to resistance. However, limitations of metagenomics sequencing, such as complex bioinformatic processing requirements, necessity of a threshold for positive detection, and the inability to detect live organisms, have hindered our ability to fully characterize the gut microbiome. Therefore, combining metagenomics with high-throughput culture-based techniques (culturomics) represents an ideal strategy to fully characterize microbiome composition to more robustly position the microbiome as a biomarker of response to ICI.

METHODS

We performed culturomics using fecal samples from 22 patients from two academic centres in Canada and the United Kingdom with NSCLC and cutaneous melanoma treated with ICI (cancer group), comparing their microbiome composition to that of 7 healthy volunteers (HV), along with matching shotgun metagenomics sequencing.

RESULTS

For culturomics results, 221 distinct species were isolated. Among these 221 distinct species, 182 were identified in the cancer group and 110 in the HV group. In the HV group, the mean species richness was higher compared to the cancer group (34 vs. 18, respectively, p = 0.002). Beta diversity revealed separate clusters between groups (p = 0.004). Bifidobacterium spp. and Bacteroides spp. were enriched in HV, while cancer patients showed an overrepresentation of Enterocloster species, as well as Veillonella parvula. Next, comparing cancer patients' clinical outcomes to ICI, we observed that among the 20 most abundant bacteria present in non-responder patients, 2 belonged to the genus Enterocloster, along with an enrichment of Hungatella hathewayi and Cutibacterium acnes. In contrast, responders to ICI exhibited a predominance of Bacteroides spp. In NSCLC patients, metagenomics analysis revealed that of the 154 bacteria species isolated through culturomics, 61/154 (39%) were also identified by metagenomics sequencing. Importantly, 94 individual species were uniquely detected by culturomics.

CONCLUSION

These findings highlight that culturomics and metagenomics can serve as complementary tools to characterize the microbiome in patients with cancer. This integrated approach uncovers specific microbiome signatures that differentiate HV from cancer patients, and identifies specific species associated with therapy response and resistance.

Lineage-specific microbial protein prediction enables large-scale exploration of protein ecology within the human gut

Microbes use a range of genetic codes and gene structures, yet these are often ignored during metagenomic analysis. This causes spurious protein predictions, preventing functional assignment which limits our understanding of ecosystems. To resolve this, we developed a lineage-specific gene prediction approach that uses the correct genetic code based on the taxonomic assignment of genetic fragments, removes incomplete protein predictions, and optimises prediction of small proteins. Applied to 9634 metagenomes and 3594 genomes from the human gut, this approach increased the landscape of captured expressed microbial proteins by 78.9%, including previously hidden functional groups. Optimised small protein prediction captured 3,772,658 small protein clusters, which form an improved microbial protein catalogue of the human gut (MiProGut). To enable the ecological study of a protein's prevalence and association with host parameters, we developed InvestiGUT, a tool which integrates both the protein sequences and sample metadata. Accurate prediction of proteins is critical to providing a functional understanding of microbiomes, enhancing our ability to study interactions between microbes and hosts.

Cultivation of anaerobic bacteria: Foundations and principles

A brief history of techniques in anaerobic microbiology are presented leading up to the incorporation of several improvements we have used over the years to improve our culture of anaerobic microorganisms of environmental, industrial and clinical importance. Two overriding aspects from our combined 90 years of experience here are: the better one's control of anaerobic conditions and gas phases, the better results are obtained; techniques can and should be targeted for individual microorganisms and accompanying experiments. Continued improvements in anaerobic microbiology are expected and encouraged for the future.

Integration of 168,000 samples reveals global patterns of the human gut microbiome

The factors shaping human microbiome variation are a major focus of biomedical research. While other fields have used large sequencing compendia to extract insights requiring otherwise impractical sample sizes, the microbiome field has lacked a comparably sized resource for the 16S rRNA gene amplicon sequencing commonly used to quantify microbiome composition. To address this gap, we processed 168,464 publicly available human gut microbiome samples with a uniform pipeline. We use this compendium to evaluate geographic and technical effects on microbiome variation. We find that regions such as Central and Southern Asia differ significantly from the more thoroughly characterized microbiomes of Europe and Northern America and that composition alone can be used to predict a sample's region of origin. We also find strong associations between microbiome variation and technical factors such as primers and DNA extraction. We anticipate this growing work, the Human Microbiome Compendium, will enable advanced applied and methodological research.

Newly identified species from the dog dental plaque microbiome highlight little overlap with humans

Understudied pet-associated microbiomes represent a rich source for the discovery of microbial taxa important for pet and human health. From a cohort of 23 dogs, we sampled and metagenomically sequenced 64 dental plaque microbiomes, generating 1945 metagenome-assembled genomes spanning 347 microbial species, including 277 undercharacterized species without cultivated representatives. Integration with human microbiome data revealed the dog plaque microbiome is more diverse than - and shows little overlap (5.9% species in common) with - the human plaque microbiome, even though some shared periodontal pathobionts arise as a potential concern.

Evaluating metagenomic analyses for undercharacterized environments: what's needed to light up the microbial dark matter?

Non-human-associated microbial communities play important biological roles, but they remain less understood than human-associated communities. Here, we assess the impact of key environmental sample properties on a variety of state-of-the-art metagenomic analysis methods. In simulated datasets, all methods performed similarly at high taxonomic ranks, but newer marker-based methods incorporating metagenomic assembled genomes outperformed others at lower taxonomic levels. In real environmental data, taxonomic profiles assigned to the same sample by different methods showed little agreement at lower taxonomic levels, but the methods agreed better on community diversity estimates and estimates of the relationships between environmental parameters and microbial profiles.

Bat Ecology and Microbiome of the Gut: A Narrative Review of Associated Potentials in Emerging and Zoonotic Diseases

In this review, we tentatively tried to connect the most recent findings on the bat microbiome and to investigate on their microbial communities, that may vary even in conspecific hosts and are influenced by host physiology, feeding behavior and diet, social interactions, but also by habitat diversity and climate change. From a conservation perspective, understanding the potentially negative and indirect effects of habitat destruction on animal microbiota can also play a crucial role in the conservation and management of the host itself. According to the One Health concept, which recognizes an interdependence between humans, animals, and the environment, bat microbiota represents an indicator of host and environmental health, besides allowing for evaluation of the risk of emerging infectious diseases. We noticed that a growing number of studies suggest that animal microbiota may respond in various ways to changes in land use, particularly when such changes lead to altered or deficient food resources. We have highlighted that the current literature is strongly focused on the initial phase of investigating the microbial communities found in Chiroptera from various habitats. However, there are gaps in effectively assessing the impacts of pathogens and microbial communities in general in animal conservation, veterinary, and public health. A deeper understanding of bat microbiomes is paramount to the implementation of correct habitat and host management and to the development of effective surveillance protocols worldwide.

MBCN: A novel reference database for Effcient Metagenomic analysis of human gut microbiome

Metagenomic shotgun sequencing data can identify microbes and their proportions. But metagenomic shotgun data profiling results obtained from multiple projects using different reference databases are difficult to compare and apply meta-analysis. Our work aims to create a novel collection of human gut prokaryotic genomes, named Microbiome Collection Navigator (MBCN). 2379 human gut metagenomic samples are screened, and 16,785 metagenome-assembled genomes (MAGs) are assembled using a standardized pipeline. In addition, MAGs are combined with the representative genomes from public prokaryotic genomes collections to cluster, and pan-genomes for each cluster's genomes are constructed to build Kraken2 and Bracken databases. The databases built by MBCN are more comprehensive and accurate for profiling metagenomic reads comparing with other collections on simulated reads and virtual bio-projects. We profile 1082 human gut metagenomic samples with MBCN database and organize profiles and metadata on the web program. Meanwhile, using MBCN as a reference database, we also develop a unified, standardized, and systematic metagenomic analysis pipeline and platform, named MicrobiotaCN (http://www.microbiota.cn) and common statistical and visualization tools for microbiome research are integrated into the web program. Taken together, MBCN and MicrobiotaCN can be a valuable resource and a powerful tool that allows researchers to perform metagenomic analysis by a unified pipeline efficiently.

Boreal moss-microbe interactions are revealed through metagenome assembly of novel bacterial species

Moss-microbe interactions contribute to ecosystem processes in boreal forests. Yet, how host-specific characteristics and the environment drive the composition and metabolic potential of moss microbiomes is still poorly understood. In this study, we use shotgun metagenomics to identify the taxonomy and metabolic potential of the bacteria of four moss species of the boreal forests of Northern Québec, Canada. To characterize moss bacterial community composition and diversity, we assembled the genomes of 110 potentially novel bacterial species. Our results highlight that moss genus, species, gametophyte section, and to a lesser extent soil pH and soil temperature, drive moss-associated bacterial community composition and diversity. In the brown gametophyte section, two Stigonema spp. showed partial pathway completeness for photosynthesis and nitrogen fixation, while all brown-associated Hyphomicrobiales had complete assimilatory nitrate reduction pathways and many nearly complete carbon fixation pathways. Several brown-associated species showed partial to complete pathways for coenzyme M and F420 biosynthesis, important for methane metabolism. In addition, green-associated Hyphomicrobiales (Methylobacteria spp.) displayed potential for the anoxygenic photosystem II pathway. Overall, our findings demonstrate how host-specific characteristics and environmental factors shape the composition and metabolic potential of moss bacteria, highlighting their roles in carbon fixation, nitrogen cycling, and methane metabolism in boreal forests.

Enhancing antimicrobial resistance detection with MetaGeneMiner: Targeted gene extraction from metagenomes

BACKGROUND

Accurately and efficiently extracting microbial genomic sequences from complex metagenomic data is crucial for advancing our understanding in fields such as clinical diagnostics, environmental microbiology, and biodiversity. As sequencing technologies evolve, this task becomes increasingly challenging due to the intricate nature of microbial communities and the vast amount of data generated. Especially in intensive care units (ICUs), infections caused by antibiotic-resistant bacteria are increasingly prevalent among critically ill patients, significantly impacting the effectiveness of treatments and patient prognoses. Therefore, obtaining timely and accurate information about infectious pathogens is of paramount importance for the treatment of patients with severe infections, which enables precisely targeted anti-infection therapies, and a tool that can extract microbial genomic sequences from metagenomic dataset would be of help.

METHODS

We developed MetaGeneMiner to help with retrieving specific microbial genomic sequences from metagenomes using a k-mer-based approach. It facilitates the rapid and accurate identification and analysis of pathogens. The tool is designed to be user-friendly and efficient on standard personal computers, allowing its use across a wide variety of settings. We validated MetaGeneMiner using eight metagenomic samples from ICU patients, which demonstrated its efficiency and accuracy.

RESULTS

The software extensively retrieved coding sequences of pathogens Acinetobacter baumannii and herpes simplex virus type 1 and detected a variety of resistance genes. All documentation and source codes for MetaGeneMiner are freely available at https://gitee.com/sculab/MetaGeneMiner .

CONCLUSIONS

It is foreseeable that MetaGeneMiner possesses the potential for applications across multiple domains, including clinical diagnostics, environmental microbiology, gut microbiome research, as well as biodiversity and conservation biology. Particularly in ICU settings, MetaGeneMiner introduces a novel, rapid, and precise method for diagnosing and treating infections in critically ill patients. This tool is capable of efficiently identifying infectious pathogens, guiding personalized and precise treatment strategies, and monitoring the development of antibiotic resistance, significantly impacting the diagnosis and treatment of severe infections.

Assembling bacterial puzzles: piecing together functions into microbial pathways

Functional metagenomics enables the study of unexplored bacterial diversity, gene families, and pathways essential to microbial communities. However, discovering biological insights with these data is impeded by the scarcity of quality annotations. Here, we use a co-occurrence-based analysis of predicted microbial protein functions to uncover pathways in genomic and metagenomic biological systems. Our approach, based on phylogenetic profiles, improves the identification of functional relationships, or participation in the same biochemical pathway, between enzymes over a comparable homology-based approach. We optimized the design of our profiles to identify potential pathways using minimal data, clustered functionally related enzyme pairs into multi-enzymatic pathways, and evaluated our predictions against reference pathways in the KEGG database. We then demonstrated a novel extension of this approach to predict inter-bacterial protein interactions amongst members of a marine microbiome. Most significantly, we show our method predicts emergent biochemical pathways between known and unknown functions. Thus, our work establishes a basis for identifying the potential functional capacities of the entire metagenome, capturing previously unknown and abstract functions into discrete putative pathways.

The Role of Fecal Microbiota Transplantation in IBD

Gut microbiota dysbiosis has a critical role in the pathogenesis of inflammatory bowel diseases, prompting the exploration of novel therapeutic approaches like fecal microbiota transplantation, which involves the transfer of fecal microbiota from a healthy donor to a recipient with the aim of restoring a balanced microbial community and attenuating inflammation. Fecal microbiota transplantation may exert beneficial effects in inflammatory bowel disease through modulation of immune responses, restoration of mucosal barrier integrity, and alteration of microbial metabolites. It could alter disease course and prevent flares, although long-term durability and safety data are lacking. This review provides a summary of current evidence on fecal microbiota transplantation in inflammatory bowel disease management, focusing on its challenges, such as variability in donor selection criteria, standardization of transplant protocols, and long-term outcomes post-transplantation.

Bacterial community of ticks (Acari: Ixodidae) and mammals from Arauca, Colombian Orinoquia

Ticks are obligate hematophagous ectoparasites of vertebrates and are relevant worldwide due to the number of bacterial and other pathogens they can transmit. To date, the knowledge about the microorganisms that ticks harbor and transmit to their hosts is incipient. In this study, 24 samples of mammals belonging to four taxonomic orders and ticks of the genera Amblyomma and Rhipicephalus from the Orinoco region of Colombia were analyzed to described and compare the bacterial microbiome. Genetic extraction was performed, and the V3-V4 region of the 16S rRNA gene was amplified by PCR. Libraries were created, and those samples with adequate quality indices were sequenced using Illumina MiSeq technology. Bacterial taxonomic assignment analyses were conducted through Amplicon Sequence Variants (ASVs) and Operational Taxonomic Units (OTUs). The results correspond to 16 samples that passed the quality filters, with 3218 OTUs (415 families). Although a considerable number of unknown bacteria was found, Enterobacteriaceae, Beijerinckiaceae, Moraxellaceae, and Burkholderiaceae are the most prevalent families, and the presence of the genera Coxiella, Escherichia-Shigella, Enterobacter, which can harbor pathogenic species was confirmed. In individuals of Amblyomma mixtum found actively feeding on Hydrochoerus hydrochaeris, bacteria of the genera Escherichia-Shigella and Enterobacter were documented. Similarly, Rhipicephalus microplus found actively feeding on Odocoileus virginianus cariacou shared Escherichia-Shigella. Ralstonia was shared among the blood samples of H. hydrochaeris, while Anaplasma and Eubacterium were shared in blood and liver samples of O. v. cariacou. Shared bacteria between A. mixtum and R. microplus included Bacillus, Coxiella, and Escherichia-Shigella. The results highlight the need of additional studies in other natural regions of Colombia and other American countries where tick-borne diseases have been detected. Likewise, the recorded data are the first at the level of bacterial communities in ticks of the family Ixodidae and provide valuable knowledge for the understanding host-tick and pathogen interactions.

The impact of the human gut microbiome on the treatment of autoimmune disease

Autoimmune (or rheumatic) diseases are increasing in prevalence but selecting the best therapy for each patient proceeds in trial-and-error fashion. This strategy can lead to ineffective therapy resulting in irreversible damage and suffering; thus, there is a need to bring the promise of precision medicine to patients with autoimmune disease. While host factors partially determine the therapeutic response to immunosuppressive drugs, these are not routinely used to tailor therapy. Thus, non-host factors likely contribute. Here, we consider the impact of the human gut microbiome in the treatment of autoimmunity. We propose that the gut microbiome can be manipulated to improve therapy and to derive greater benefit from existing therapies. We focus on the mechanisms by which the human gut microbiome impacts treatment response, provide a framework to interrogate these mechanisms, review a case study of a widely-used anti-rheumatic drug, and discuss challenges with studying multiple complex systems: the microbiome, the human immune system, and autoimmune disease. We consider open questions that remain in the field and speculate on the future of drug-microbiome-autoimmune disease interactions. Finally, we present a blue-sky vision for how the microbiome can be used to bring the promise of precision medicine to patients with rheumatic disease.

Draft genome sequences of multiple bacterial strains isolated from human feces

Bacterial isolation is necessary for functional and mechanistic analyses, and the increased human microbiome diversity revealed by metagenomic sequencing is expanding the relevant cultivation targets. Here, we report 46 draft genome sequences of bacterial isolates obtained from fecal samples of healthy adults in Trento and Milan (Italy), including strains from seven taxonomically uncharacterized species.

Emerging tools and best practices for studying gut microbial community metabolism

The human gut microbiome vastly extends the set of metabolic reactions catalysed by our own cells, with far-reaching consequences for host health and disease. However, our knowledge of gut microbial metabolism relies on a handful of model organisms, limiting our ability to interpret and predict the metabolism of complex microbial communities. In this Perspective, we discuss emerging tools for analysing and modelling the metabolism of gut microorganisms and for linking microorganisms, pathways and metabolites at the ecosystem level, highlighting promising best practices for researchers. Continued progress in this area will also require infrastructure development to facilitate cross-disciplinary synthesis of scientific findings. Collectively, these efforts can enable a broader and deeper understanding of the workings of the gut ecosystem and open new possibilities for microbiome manipulation and therapy.

Exploring the Complexity of the Human Respiratory Virome through an In Silico Analysis of Shotgun Metagenomic Data Retrieved from Public Repositories

BACKGROUND

Respiratory viruses significantly impact global morbidity and mortality, causing more disease in humans than any other infectious agent. Beyond pathogens, various viruses and bacteria colonize the respiratory tract without causing disease, potentially influencing respiratory diseases' pathogenesis. Nevertheless, our understanding of respiratory microbiota is limited by technical constraints, predominantly focusing on bacteria and neglecting crucial populations like viruses. Despite recent efforts to improve our understanding of viral diversity in the human body, our knowledge of viral diversity associated with the human respiratory tract remains limited.

METHODS

Following a comprehensive search in bibliographic and sequencing data repositories using keyword terms, we retrieved shotgun metagenomic data from public repositories (n = 85). After manual curation, sequencing data files from 43 studies were analyzed using EVEREST (pipEline for Viral assEmbly and chaRactEriSaTion). Complete and high-quality contigs were further assessed for genomic and taxonomic characterization.

RESULTS

Viral contigs were obtained from 194 out of the 868 FASTQ files processed through EVEREST. Of the 1842 contigs that were quality assessed, 8% (n = 146) were classified as complete/high-quality genomes. Most of the identified viral contigs were taxonomically classified as bacteriophages, with taxonomic resolution ranging from the superkingdom level down to the species level. Captured contigs were spread across 25 putative families and varied between RNA and DNA viruses, including previously uncharacterized viral genomes. Of note, airway samples also contained virus(es) characteristic of the human gastrointestinal tract, which have not been previously described as part of the lung virome. Additionally, by performing a meta-analysis of the integrated datasets, ecological trends within viral populations linked to human disease states and their biogeographical distribution along the respiratory tract were observed.

CONCLUSION

By leveraging publicly available repositories of shotgun metagenomic data, the present study provides new insights into viral genomes associated with specimens from the human respiratory tract across different disease spectra. Further studies are required to validate our findings and evaluate the potential impact of these viral communities on respiratory tract physiology.

Occurrence of Free-Living Amoebae in Non-Human Primate Gut

The gut microbiome reflects health and predicts possible disease in hosts. A holistic view of this community is needed, focusing on identifying species and dissecting how species interact with their host and each other, regardless of whether their presence is beneficial, inconsequential, or detrimental. The distribution of gut-associated eukaryotes within and across non-human primates is likely driven by host behavior and ecology. To ascertain the existence of free-living amoebae (FLA) in the gut of wild and captive non-human primates, 101 stool samples were collected and submitted to culture-dependent microscopy examination and DNA sequencing. Free-living amoebae were detected in 45.4% (46/101) of fecal samples analyzed, and their morphological characteristics matched those of Acanthamoeba spp., Vermamoeba spp., heterolobosean amoeboflagellates and fan-shaped amoebae of the family Vannellidae. Sequence analysis of the PCR products revealed that the suspected amoebae are highly homologous (99% identity and 100% query coverage) with Acanthamoeba T4 genotype and Vermamoeba vermiformis amoebae. The results showed a great diversity of amoebae in the non-human primate's microbiome, which may pose a potential risk to the health of NHPs. To our knowledge, this is the first report of free-living amoebae in non-human primates that are naturally infected. However, it is unknown whether gut-borne amoebae exploit a viable ecological niche or are simply transient residents in the gut.

Meta-analysis of the Microbial Diversity Cultured in Bioreactors Simulating the Gut Microbiome

Understanding the intricate ecological interactions within the gut microbiome and unravelling its impact on human health is a challenging task. Bioreactors are valuable tools that have contributed to our understanding of gut microbial ecology. However, there is a lack of studies describing and comparing the microbial diversity cultivated in these models. This knowledge is crucial for refining current models to reflect the gastrointestinal microbiome accurately. In this study, we analysed the microbial diversity of 1512 samples from 18 studies available in public repositories that employed cultures performed in batches and various bioreactor models to cultivate faecal microbiota. Community structure comparison between samples using t-distributed stochastic neighbour embedding and the Hellinger distance revealed a high variation between projects. The main driver of these differences was the inter-individual variation between the donor faecal inocula. Moreover, there was no overlap in the structure of the microbial communities between studies using the same bioreactor platform. In addition, α-diversity analysis using Hill numbers showed that highly complex bioreactors did not exhibit higher diversities than simpler designs. However, analyses of five projects in which the samples from the faecal inoculum were also provided revealed an amplicon sequence variants enrichment in bioreactors compared to the inoculum. Finally, a comparative analysis of the taxonomy of the families detected in the projects and the GMRepo database revealed bacterial families exclusively found in the bioreactor models. These findings highlight the potential of bioreactors to enrich low-abundance microorganisms from faecal samples, contributing to uncovering the gut microbial "dark matter".

Update on microbiota-derived therapies for recurrent Clostridioides difficile infections

BACKGROUND

Faecal microbiota transplantation (FMT) is the standard treatment for patients with multiple recurrent Clostridioides difficile infection (rCDI). Recently, new commercially developed human microbiota-derived medicinal products have been evaluated and Food and Drug Administration-approved with considerable differences in terms of composition, administration, and targeted populations.

OBJECTIVES

To review available data on the different microbiota-derived treatments at the stage of advanced clinical evaluation and research in rCDI in comparison with FMT.

SOURCES

Phase II or III trials evaluating a microbiota-derived medicinal product to prevent rCDI.

CONTENT

Two commercial microbiota-derived medicinal products are approved by the Food and Drug Administration: Rebyota (RBX2660 Ferring Pharmaceuticals, marketed in the United States) and VOWST (SER-109 -Seres Therapeutics, marketed in the United States), whereas VE303 (Vedanta Biosciences Inc) will be studied in phase III trial. RBX2660 and SER-109 are based on the processing of stools from healthy donors, whereas VE303 consists of a defined bacterial consortium originating from human stools and produced from clonal cell banks. All have proven efficacy to prevent rCDI compared with placebo in patients considered at high risk of recurrence. However, the heterogeneity of the inclusion criteria, and the time between each episode and CDI diagnostics makes direct comparison between trials difficult. The differences regarding the risk of recurrence between the treatment and placebo arms were lower than previously described for FMT (FMT: Δ = 50.5%; RBX2660-phase III: Δ = 13.1%; SER-109-phase III: Δ = 28%; high-dose VE303-phase-II: Δ = 31.7%). All treatments presented a good overall safety profile with mainly mild gastrointestinal symptoms.

IMPLICATIONS

Stool-derived products and bacterial consortia need to be clearly distinguished in terms of product characterization and their associated risks with specific long-term post-marketing evaluation similar to registries used for FMT. Their place in the therapeutic strategy for patients with rCDI requires further studies to determine the most appropriate patient population and administration route to prevent rCDI.

Comprehensive profile of the companion animal gut microbiome integrating reference-based and reference-free methods

The gut microbiome of companion animals is relatively underexplored, despite its relevance to animal health, pet owner health, and basic microbial community biology. Here, we provide the most comprehensive analysis of the canine and feline gut microbiomes to date, incorporating 2639 stool shotgun metagenomes (2272 dog and 367 cat) spanning 14 publicly available datasets (n = 730) and 8 new study populations (n = 1909). These are compared with 238 and 112 baseline human gut metagenomes from the Human Microbiome Project 1-II and a traditionally living Malagasy cohort, respectively, processed in a manner identical to the animal metagenomes. All microbiomes were characterized using reference-based taxonomic and functional profiling, as well as de novo assembly yielding metagenomic assembled genomes clustered into species-level genome bins. Companion animals shared 184 species-level genome bins not found in humans, whereas 198 were found in all three hosts. We applied novel methodology to distinguish strains of these shared organisms either transferred or unique to host species, with phylogenetic patterns suggesting host-specific adaptation of microbial lineages. This corresponded with functional divergence of these lineages by host (e.g. differences in metabolic and antibiotic resistance genes) likely important to companion animal health. This study provides the largest resource to date of companion animal gut metagenomes and greatly contributes to our understanding of the "One Health" concept of a shared microbial environment among humans and companion animals, affecting infectious diseases, immune response, and specific genetic elements.

Relevance of gut microbiome research in food safety assessment

The gut microbiome is indispensable for the host physiological functioning. Yet, the impact of non-nutritious dietary compounds on the human gut microbiota and the role of the gut microbes in their metabolism and potential adverse biological effects have been overlooked. Identifying potential hazards and benefits would contribute to protecting and harnessing the gut microbiome's role in supporting human health. We discuss the evidence on the potential detrimental impact of certain food additives and microplastics on the gut microbiome and human health, with a focus on underlying mechanisms and causality. We provide recommendations for the incorporation of gut microbiome science in food risk assessment and identify the knowledge and tools needed to fill these gaps. The incorporation of gut microbiome endpoints to safety assessments, together with well-established toxicity and mutagenicity studies, might better inform the risk assessment of certain contaminants in food, and/or food additives.

Extending and improving metagenomic taxonomic profiling with uncharacterized species using MetaPhlAn 4

Metagenomic assembly enables new organism discovery from microbial communities, but it can only capture few abundant organisms from most metagenomes. Here we present MetaPhlAn 4, which integrates information from metagenome assemblies and microbial isolate genomes for more comprehensive metagenomic taxonomic profiling. From a curated collection of 1.01 M prokaryotic reference and metagenome-assembled genomes, we define unique marker genes for 26,970 species-level genome bins, 4,992 of them taxonomically unidentified at the species level. MetaPhlAn 4 explains ~20% more reads in most international human gut microbiomes and >40% in less-characterized environments such as the rumen microbiome and proves more accurate than available alternatives on synthetic evaluations while also reliably quantifying organisms with no cultured isolates. Application of the method to >24,500 metagenomes highlights previously undetected species to be strong biomarkers for host conditions and lifestyles in human and mouse microbiomes and shows that even previously uncharacterized species can be genetically profiled at the resolution of single microbial strains.

Integration of 168,000 samples reveals global patterns of the human gut microbiome

Understanding the factors that shape variation in the human microbiome is a major goal of research in biology. While other genomics fields have used large, pre-compiled compendia to extract systematic insights requiring otherwise impractical sample sizes, there has been no comparable resource for the 16S rRNA sequencing data commonly used to quantify microbiome composition. To help close this gap, we have assembled a set of 168,484 publicly available human gut microbiome samples, processed with a single pipeline and combined into the largest unified microbiome dataset to date. We use this resource, which is freely available at microbiomap.org, to shed light on global variation in the human gut microbiome. We find that Firmicutes, particularly Bacilli and Clostridia, are almost universally present in the human gut. At the same time, the relative abundance of the 65 most common microbial genera differ between at least two world regions. We also show that gut microbiomes in undersampled world regions, such as Central and Southern Asia, differ significantly from the more thoroughly characterized microbiomes of Europe and Northern America. Moreover, humans in these overlooked regions likely harbor hundreds of taxa that have not yet been discovered due to this undersampling, highlighting the need for diversity in microbiome studies. We anticipate that this new compendium can serve the community and enable advanced applied and methodological research.

Fecal Microbial Composition and Predicted Functional Profile in Irritable Bowel Syndrome Differ between Subtypes and Geographical Locations

Increasing evidence suggests a microbial pathogenesis in irritable bowel syndrome (IBS) but the relationship remains elusive. Fecal DNA samples from 120 patients with IBS, 82 Mexican (IBS-C: n = 33, IBS-D: n = 24, IBS-M: n = 25) and 38 British (IBS-C: n = 6, IBS-D: n = 27, IBS-M: n = 5), were available for analysis using 16S rRNA gene sequencing. Firmicutes (mean: 82.1%), Actinobacteria (10.2%), and Bacteroidetes (4.4%) were the most abundant taxa. The analysis of all samples (n = 120), and females (n = 94) only, showed no significant differences in bacterial microbiota, but the analysis of Mexican patients (n = 82) showed several differences in key taxa (e.g., Faecalibacterium) among the different IBS subtypes. In IBS-D there were significantly higher Bacteroidetes in British patients (n = 27) than in Mexican patients (n = 24), suggesting unique fecal microbiota signatures within the same IBS subtype. These differences in IBS-D were also observed at lower phylogenetic levels (e.g., higher Enterobacteriaceae and Streptococcus in Mexican patients) and were accompanied by differences in several alpha diversity metrics. Beta diversity was not different among IBS subtypes when using all samples, but the analysis of IBS-D patients revealed consistent differences between Mexican and British patients. This study suggests that fecal microbiota is different between IBS subtypes and also within each subtype depending on geographical location.

Gut OncoMicrobiome Signatures (GOMS) as next-generation biomarkers for cancer immunotherapy

Oncogenesis is associated with intestinal dysbiosis, and stool shotgun metagenomic sequencing in individuals with this condition might constitute a non-invasive approach for the early diagnosis of several cancer types. The prognostic relevance of antibiotic intake and gut microbiota composition urged investigators to develop tools for the detection of intestinal dysbiosis to enable patient stratification and microbiota-centred clinical interventions. Moreover, since the advent of immune-checkpoint inhibitors (ICIs) in oncology, the identification of biomarkers for predicting their efficacy before starting treatment has been an unmet medical need. Many previous studies addressing this question, including a meta-analysis described herein, have led to the description of Gut OncoMicrobiome Signatures (GOMS). In this Review, we discuss how patients with cancer across various subtypes share several GOMS with individuals with seemingly unrelated chronic inflammatory disorders who, in turn, tend to have GOMS different from those of healthy individuals. We discuss findings from the aforementioned meta-analysis of GOMS patterns associated with clinical benefit from or resistance to ICIs across different cancer types (in 808 patients), with a focus on metabolic and immunological surrogate markers of intestinal dysbiosis, and propose practical guidelines to incorporate GOMS in decision-making for prospective clinical trials in immuno-oncology.

Gene-based microbiome representation enhances host phenotype classification

With the concomitant advances in both the microbiome and machine learning fields, the gut microbiome has become of great interest for the potential discovery of biomarkers to be used in the classification of the host health status. Shotgun metagenomics data derived from the human microbiome is composed of a high-dimensional set of microbial features. The use of such complex data for the modeling of host-microbiome interactions remains a challenge as retaining de novo content yields a highly granular set of microbial features. In this study, we compared the prediction performances of machine learning approaches according to different types of data representations derived from shotgun metagenomics. These representations include commonly used taxonomic and functional profiles and the more granular gene cluster approach. For the five case-control datasets used in this study (Type 2 diabetes, obesity, liver cirrhosis, colorectal cancer, and inflammatory bowel disease), gene-based approaches, whether used alone or in combination with reference-based data types, allowed improved or similar classification performances as the taxonomic and functional profiles. In addition, we show that using subsets of gene families from specific functional categories of genes highlight the importance of these functions on the host phenotype. This study demonstrates that both reference-free microbiome representations and curated metagenomic annotations can provide relevant representations for machine learning based on metagenomic data. IMPORTANCE Data representation is an essential part of machine learning performance when using metagenomic data. In this work, we show that different microbiome representations provide varied host phenotype classification performance depending on the dataset. In classification tasks, untargeted microbiome gene content can provide similar or improved classification compared to taxonomical profiling. Feature selection based on biological function also improves classification performance for some pathologies. Function-based feature selection combined with interpretable machine learning algorithms can generate new hypotheses that can potentially be assayed mechanistically. This work thus proposes new approaches to represent microbiome data for machine learning that can potentiate the findings associated with metagenomic data.

Amplicon-Based Microbiome Profiling: From Second- to Third-Generation Sequencing for Higher Taxonomic Resolution

The 16S rRNA amplicon-based sequencing approach represents the most common and cost-effective strategy with great potential for microbiome profiling. The use of second-generation sequencing (NGS) technologies has led to protocols based on the amplification of one or a few hypervariable regions, impacting the outcome of the analysis. Nowadays, comparative studies are necessary to assess different amplicon-based approaches, including the full-locus sequencing currently feasible thanks to third-generation sequencing (TGS) technologies. This study compared three different methods to achieve the deepest microbiome taxonomic characterization: (a) the single-region approach, (b) the multiplex approach, covering several regions of the target gene/region, both based on NGS short reads, and (c) the full-length approach, which analyzes the whole length of the target gene thanks to TGS long reads. Analyses carried out on benchmark microbiome samples, with a known taxonomic composition, highlighted a different classification performance, strongly associated with the type of hypervariable regions and the coverage of the target gene. Indeed, the full-length approach showed the greatest discriminating power, up to species level, also on complex real samples. This study supports the transition from NGS to TGS for the study of the microbiome, even if experimental and bioinformatic improvements are still necessary.

Comparison of k-mer-based de novo comparative metagenomic tools and approaches

Aim: Comparative metagenomic analysis requires measuring a pairwise similarity between metagenomes in the dataset. Reference-based methods that compute a beta-diversity distance between two metagenomes are highly dependent on the quality and completeness of the reference database, and their application on less studied microbiota can be challenging. On the other hand, de-novo comparative metagenomic methods only rely on the sequence composition of metagenomes to compare datasets. While each one of these approaches has its strengths and limitations, their comparison is currently limited. Methods: We developed sets of simulated short-reads metagenomes to (1) compare k-mer-based and taxonomy-based distances and evaluate the impact of technical and biological variables on these metrics and (2) evaluate the effect of k-mer sketching and filtering. We used a real-world metagenomic dataset to provide an overview of the currently available tools for de novo metagenomic comparative analysis. Results: Using simulated metagenomes of known composition and controlled error rate, we showed that k-mer-based distance metrics were well correlated to the taxonomic distance metric for quantitative Beta-diversity metrics, but the correlation was low for presence/absence distances. The community complexity in terms of taxa richness and the sequencing depth significantly affected the quality of the k-mer-based distances, while the impact of low amounts of sequence contamination and sequencing error was limited. Finally, we benchmarked currently available de-novo comparative metagenomic tools and compared their output on two datasets of fecal metagenomes and showed that most k-mer-based tools were able to recapitulate the data structure observed using taxonomic approaches. Conclusion: This study expands our understanding of the strength and limitations of k-mer-based de novo comparative metagenomic approaches and aims to provide concrete guidelines for researchers interested in applying these approaches to their metagenomic datasets.

Key determinants of success in fecal microbiota transplantation: From microbiome to clinic

Fecal microbiota transplantation (FMT) has achieved satisfactory results in preventing the recurrence of Clostridioides difficile infection, but these positive outcomes have only been partially replicated in other diseases. Several factors influence FMT success, including those related to donors and recipients (including diversity and specific composition of the gut microbiome, immune system, and host genetics) as well as to working protocols (fecal amount and number of infusions, route of delivery, and adjuvant treatments). Moreover, initial evidence suggests that the clinical success of FMT may be related to the degree of donor microbial engraftment. The application of cutting-edge technologies for microbiome assessment, along with changes in the current vision of fecal transplants, are expected to improve FMT protocols and outcomes. Here, we review the key determinants of FMT success and insights and strategies that will enable a close integration of lab-based and clinical approaches for increasing FMT success.

Gut-liver axis: barriers and functional circuits

The gut and the liver are characterized by mutual interactions between both organs, the microbiome, diet and other environmental factors. The sum of these interactions is conceptualized as the gut-liver axis. In this Review we discuss the gut-liver axis, concentrating on the barriers formed by the enterohepatic tissues to restrict gut-derived microorganisms, microbial stimuli and dietary constituents. In addition, we discuss the establishment of barriers in the gut and liver during development and their cooperative function in the adult host. We detail the interplay between microbial and dietary metabolites, the intestinal epithelium, vascular endothelium, the immune system and the various host soluble factors, and how this interplay establishes a homeostatic balance in the healthy gut and liver. Finally, we highlight how this balance is disrupted in diseases of the gut and liver, outline the existing therapeutics and describe the cutting-edge discoveries that could lead to the development of novel treatment approaches.

Targeting the human gut microbiome with small-molecule inhibitors

The human gut microbiome is a complex microbial community that is strongly linked to both host health and disease. However, the detailed molecular mechanisms underlying the effects of these microorganisms on host biology remain largely uncharacterized. The development of non-lethal, small-molecule inhibitors that target specific gut microbial activities enables a powerful but underutilized approach to studying the gut microbiome and a promising therapeutic strategy. In this Review, we will discuss the challenges of studying this microbial community, the historic use of small-molecule inhibitors in microbial ecology, and recent applications of this strategy. We also discuss the evidence suggesting that host-targeted drugs can affect the growth and metabolism of gut microbes. Finally, we address the issues of developing and implementing microbiome-targeted small-molecule inhibitors and define important future directions for this research.

Targeting the gut microbiota in inflammatory bowel diseases: where are we?

The gut microbiota is now recognized to be a key driver of mucosal inflammation in inflammatory bowel disease (IBD). Robust functional and compositional alterations of the gut microbiota have been described in IBD with a reduction in bacterial diversity, a reduction in some anti-inflammatory anaerobic bacteria, and an increase in bacteria with pro-inflammatory potential. However, despite 15 years of active research, therapeutical applications are still lacking. Recent studies have shed new light on how targeting the gut microbiota can be beneficial in IBD with fecal microbiota transplantation, next-generation probiotics, and phage therapy. Given the similarities in dysfunction and structure of the gut microbiota between IBD and other chronic conditions associated with intestinal inflammation, such as celiac disease, Familial Mediterranean Fever, or common variable immunodeficiency, common therapeutic strategies targeting the host-microbiota symbiosis may be applied in these different conditions.

Intestinal Barrier Dysfunction and Microbiota-Gut-Brain Axis: Possible Implications in the Pathogenesis and Treatment of Autism Spectrum Disorder

Autism spectrum disorder (ASD) is a complex neurodevelopmental disorder with multifactorial etiology, characterized by impairment in two main functional areas: (1) communication and social interactions, and (2) skills, interests and activities. ASD patients often suffer from gastrointestinal symptoms associated with dysbiotic states and a "leaky gut." A key role in the pathogenesis of ASD has been attributed to the gut microbiota, as it influences central nervous system development and neuropsychological and gastrointestinal homeostasis through the microbiota-gut-brain axis. A state of dysbiosis with a reduction in the Bacteroidetes/Firmicutes ratio and Bacteroidetes level and other imbalances is common in ASD. In recent decades, many authors have tried to study and identify the microbial signature of ASD through in vivo and ex vivo studies. In this regard, the advent of metabolomics has also been of great help. Based on these data, several therapeutic strategies, primarily the use of probiotics, are investigated to improve the symptoms of ASD through the modulation of the microbiota. However, although the results are promising, the heterogeneity of the studies precludes concrete evidence. The aim of this review is to explore the role of intestinal barrier dysfunction, the gut-brain axis and microbiota alterations in ASD and the possible role of probiotic supplementation in these patients.

Metagenomic Analysis of the Abundance and Composition of Antibiotic Resistance Genes in Hospital Wastewater in Benin, Burkina Faso, and Finland

Antibiotic resistance is a global threat to human health, with the most severe effect in low- and middle-income countries. We explored the presence of antibiotic resistance genes (ARGs) in the hospital wastewater (HWW) of nine hospitals in Benin and Burkina Faso, two low-income countries in West Africa, with shotgun metagenomic sequencing. For comparison, we also studied six hospitals in Finland. The highest sum of the relative abundance of ARGs in the 68 HWW samples was detected in Benin and the lowest in Finland. HWW resistomes and mobilomes in Benin and Burkina Faso resembled each other more than those in Finland. Many carbapenemase genes were detected at various abundances, especially in HWW from Burkina Faso and Finland. The bla_GES genes, the most widespread carbapenemase gene in the Beninese HWW, were also found in water intended for hand washing and in a puddle at a hospital yard in Benin. mcr genes were detected in the HWW of all three countries, with mcr-5 being the most common mcr gene. These and other mcr genes were observed in very high relative abundances, even in treated wastewater in Burkina Faso and a street gutter in Benin. The results highlight the importance of wastewater treatment, with particular attention to HWW. IMPORTANCE The global emergence and increased spread of antibiotic resistance threaten the effectiveness of antibiotics and, thus, the health of the entire population. Therefore, understanding the resistomes in different geographical locations is crucial in the global fight against the antibiotic resistance crisis. However, this information is scarce in many low- and middle-income countries (LMICs), such as those in West Africa. In this study, we describe the resistomes of hospital wastewater in Benin and Burkina Faso and, as a comparison, Finland. Our results help to understand the hitherto unrevealed resistance in Beninese and Burkinabe hospitals. Furthermore, the results emphasize the importance of wastewater management infrastructure design to minimize exposure events between humans, HWW, and the environment, preventing the circulation of resistant bacteria and ARGs between humans (hospitals and community) and the environment.

LDMD: A database of microbes in human lung disease

Background

Lungs were initially thought to be sterile. However, with the development of sequencing technologies, various commensal microorganisms, especially bacteria, have been observed in the lungs of healthy humans. Several studies have also linked lung microbes to infectious lung diseases. However, few databases have focused on the metagenomics of lungs to provide microbial compositions and corresponding metadata information. Such a database would be handy for researching and treating lung diseases.

Methods

To provide researchers with a preliminary understanding of lung microbes and their research methods, the LDMD collated nearly 10,000 studies in the literature covering over 30 diseases, gathered basic information such as the sources of lung microbe samples, sequencing methods, and processing software, as well as analyzed the metagenomic sequencing characteristics of lung microbes. Besides, the LDMD also contained data collected in our laboratory.

Results

In this study, we established the Lung Disease Microorganisms Database (LDMD), a comprehensive database of microbes involved in lung disease. The LDMD offered sequence analysis capabilities, allowing users to upload their sequencing results, align them with the data collated in the database, and visually analyze the results.

Conclusion

In conclusion, the LDMD possesses various functionalities that provide a convenient and comprehensive resource to study the lung metagenome and treat lung diseases.

Expanding the genomic encyclopedia of Actinobacteria with 824 isolate reference genomes

The phylum Actinobacteria includes important human pathogens like Mycobacterium tuberculosis and Corynebacterium diphtheriae and renowned producers of secondary metabolites of commercial interest, yet only a small part of its diversity is represented by sequenced genomes. Here, we present 824 actinobacterial isolate genomes in the context of a phylum-wide analysis of 6,700 genomes including public isolates and metagenome-assembled genomes (MAGs). We estimate that only 30%-50% of projected actinobacterial phylogenetic diversity possesses genomic representation via isolates and MAGs. A comparison of gene functions reveals novel determinants of host-microbe interaction as well as environment-specific adaptations such as potential antimicrobial peptides. We identify plasmids and prophages across isolates and uncover extensive prophage diversity structured mainly by host taxonomy. Analysis of >80,000 biosynthetic gene clusters reveals that horizontal gene transfer and gene loss shape secondary metabolite repertoire across taxa. Our observations illustrate the essential role of and need for high-quality isolate genome sequences.

Seasonal microbial dynamics in the ocean inferred from assembled and unassembled data: a view on the unknown biosphere

In environmental metagenomic experiments, a very high proportion of the microbial sequencing data (> 70%) remains largely unexploited because rare and closely related genomes are missed in short-read assemblies. The identity and the potential metabolisms of a large fraction of natural microbial communities thus remain inaccessible to researchers. The purpose of this study was to explore the genomic content of unassembled metagenomic data and test their level of novelty. We used data from a three-year microbial metagenomic time series of the NW Mediterranean Sea, and conducted reference-free and database-guided analysis. The results revealed a significant genomic difference between the assembled and unassembled reads. The unassembled reads had a lower mean identity against public databases, and fewer metabolic pathways could be reconstructed. In addition, the unassembled fraction presented a clear temporal pattern, unlike the assembled ones, and a specific community composition that was similar to the rare communities defined by metabarcoding using the 16S rRNA gene. The rare gene pool was characterised by keystone bacterial taxa, and the presence of viruses, suggesting that viral lysis could maintain some taxa in a state of rarity. Our study demonstrates that unassembled metagenomic data can provide important information on the structure and functioning of microbial communities.

Meta-Analysis and Validation of a Colorectal Cancer Risk Prediction Model Using Deep Sequenced Fecal Metagenomes

The gut microbiome is a potential modifiable risk factor for colorectal cancer (CRC). We re-analyzed all eight previously published stool sequencing data and conducted an MWAS meta-analysis. We used cross-validated LASSO predictive models to identify a microbiome signature for predicting the risk of CRC and precancerous lesions. These models were validated in a new study, Colorectal Cancer Screening (COLSCREEN), including 156 participants that were recruited in a CRC screening context. The MWAS meta-analysis identified 95 bacterial species that were statistically significantly associated with CRC (FDR < 0.05). The LASSO CRC predictive model obtained an area under the receiver operating characteristic curve (aROC) of 0.81 (95%CI: 0.78−0.83) and the validation in the COLSCREEN dataset was 0.75 (95%CI: 0.66−0.84). This model selected a total of 32 species. The aROC of this CRC-trained model to predict precancerous lesions was 0.52 (95%CI: 0.41−0.63). We have identified a signature of 32 bacterial species that have a good predictive accuracy to identify CRC but not precancerous lesions, suggesting that the identified microbes that were enriched or depleted in CRC are merely a consequence of the tumor. Further studies should focus on CRC as well as precancerous lesions with the intent to implement a microbiome signature in CRC screening programs.

The systemic anti-microbiota IgG repertoire can identify gut bacteria that translocate across gut barrier surfaces

Unique gut microbiota compositions have been associated with inflammatory diseases, but identifying gut bacterial functions linked to immune activation in humans remains challenging. Translocation of pathogens from mucosal surfaces into peripheral tissues can elicit immune activation, although whether and which gut commensal bacteria translocate in inflammatory diseases is difficult to assess. We report that a subset of commensal gut microbiota constituents that translocate across the gut barrier in mice and humans are associated with heightened systemic immunoglobulin G (IgG) responses. We present a modified high-throughput, culture-independent approach to quantify systemic IgG against gut commensal bacteria in human serum samples without the need for paired stool samples. Using this approach, we highlight several commensal bacterial species that elicit elevated IgG responses in patients with inflammatory bowel disease (IBD) including taxa within the clades Collinsella, Bifidobacterium, Lachnospiraceae, and Ruminococcaceae. These and other taxa identified as translocating bacteria or targets of systemic immunity in IBD concomitantly exhibited heightened transcriptional activity and growth rates in IBD patient gut microbiomes. Our approach represents a complementary tool to illuminate interactions between the host and its gut microbiota and may provide an additional method to identify microbes linked to inflammatory disease.

Microbiome Research as an Effective Driver of Success Stories in Agrifood Systems – A Selection of Case Studies

Increasing knowledge of the microbiome has led to significant advancements in the agrifood system. Case studies based on microbiome applications have been reported worldwide and, in this review, we have selected 14 success stories that showcase the importance of microbiome research in advancing the agrifood system. The selected case studies describe products, methodologies, applications, tools, and processes that created an economic and societal impact. Additionally, they cover a broad range of fields within the agrifood chain: the management of diseases and putative pathogens; the use of microorganism as soil fertilizers and plant strengtheners; the investigation of the microbial dynamics occurring during food fermentation; the presence of microorganisms and/or genes associated with hazards for animal and human health (e.g., mycotoxins, spoilage agents, or pathogens) in feeds, foods, and their processing environments; applications to improve HACCP systems; and the identification of novel probiotics and prebiotics to improve the animal gut microbiome or to prevent chronic non-communicable diseases in humans (e.g., obesity complications). The microbiomes of soil, plants, and animals are pivotal for ensuring human and environmental health and this review highlights the impact that microbiome applications have with this regard.

Mutualistic interplay between bacteriophages and bacteria in the human gut

Bacteriophages (phages) are often described as obligate predators of their bacterial hosts, and phage predation is one of the leading forces controlling the density and distribution of bacterial populations. Every 48 h half of all bacteria on Earth are killed by phages. Efficient killing also forms the basis of phage therapy in humans and animals and the use of phages as food preservatives. In turn, bacteria have a plethora of resistance systems against phage attack, but very few bacterial species, if any, have entirely escaped phage predation. However, in complex communities and environments such as the human gut, this antagonistic model of attack and counter-defence does not fully describe the scope of phage-bacterium interactions. In this Review, we explore some of the more mutualistic aspects of phage-bacterium interactions in the human gut, and we suggest that the relationship between phages and their bacterial hosts in the gut is best characterized not as a fight to the death between enemies but rather as a mutualistic relationship between partners.

Introducing untargeted data-independent acquisition for metaproteomics of complex microbial samples

Mass spectrometry-based metaproteomics is a relatively new field of research that enables the characterization of the functionality of microbiota. Recently, we demonstrated the applicability of data-independent acquisition (DIA) mass spectrometry to the analysis of complex metaproteomic samples. This allowed us to circumvent many of the drawbacks of the previously used data-dependent acquisition (DDA) mass spectrometry, mainly the limited reproducibility when analyzing samples with complex microbial composition. However, the DDA-assisted DIA approach still required additional DDA data on the samples to assist the analysis. Here, we introduce, for the first time, an untargeted DIA metaproteomics tool that does not require any DDA data, but instead generates a pseudospectral library directly from the DIA data. This reduces the amount of required mass spectrometry data to a single DIA run per sample. The new DIA-only metaproteomics approach is implemented as a new open-source software package named glaDIAtor, including a modern web-based graphical user interface to facilitate wide use of the tool by the community.

The relationship between land cover and microbial community composition in European lakes

Microbes are essential for element cycling and ecosystem functioning. However, many questions central to understanding the role of microbes in ecology are still open. Here, we analyze the relationship between lake microbiomes and the lakes' land cover. By applying machine learning methods, we quantify the covariance between land cover categories and the microbial community composition recorded in the largest amplicon sequencing dataset of European lakes available to date. Our results show that the aggregation of environmental features or microbial taxa before analysis can obscure ecologically relevant patterns. We observe a comparatively high covariation of the lakes' microbial community with herbaceous and open spaces surrounding the lake; nevertheless, the microbial covariation with land cover categories is generally lower than the covariation with physico-chemical parameters. Combining land cover and physico-chemical bioindicators identified from the same amplicon sequencing dataset, we develop analytical data structures that facilitate insights into the ecology of the lake microbiome. Among these, a list of the environmental parameters sorted by the number of microbial bioindicators we have identified for them points towards apparent environmental drivers of the lake microbial community composition, such as the altitude, conductivity, and area covered herbaceous vegetation surrounding the lake. Furthermore, the response map, a similarity matrix calculated from the Jaccard similarity of the environmental parameters' lists of bioindicators, allows us to study the ecosystem's structure from the standpoint of the microbiome. More specifically, we identify multiple clusters of highly similar and possibly functionally linked ecological parameters, including one that highlights the importance of the calcium-bicarbonate equilibrium for lake ecology. Taken together, we demonstrate the use of machine learning approaches in studying the interplay between microbial diversity and environmental factors and introduce novel approaches to integrate environmental molecular diversity into monitoring and water quality assessments.

Enterococci-Involvement in Pathogenesis and Therapeutic Potential in Cancer Treatment: A Mini-Review

Enterococcus spp. are Gram-positive, heterogeneous lactic acid bacteria inhabiting various environments. Several species of Enterococci are considered to be able to stimulate the immune system and play an important role in intestinal homeostasis. Some Enterococci can be used as probiotics. Some strains of E. faecium are components of pharmaceutical products used to treat diarrhea, antibiotic-associated diarrhea, or irritable bowel syndrome (IBS). However, it has been proved that they are responsible for food contamination, and are sometimes undesirable from the point of view of food technology. Additionally, the virulence and multi-drug resistance of Enterococci potentially pose a risk of an epidemic, especially in hospital environments. Moreover, there are indications of their negative role in colon tumorigenesis; however, some nterococci are proved to support immunotherapy in cancer treatment. In general, it can be concluded that this group of microorganisms, despite its nature, has properties that can be used to support cancer treatment—both aggressive chemotherapy and cutting-edge therapy targeting immune checkpoints (IC).