Microbial abundance, activity and population genomic profiling with mOTUs2

Aminolipids in bacterial membranes and the natural environment

Our comprehension of membrane function has predominantly advanced through research on glycerophospholipids, also known as phosphoglycerides, which are glycerol phosphate-based lipids found across all three domains of life. However, in bacteria, a perplexing group of lipids distinct from glycerol phosphate-based ones also exists. These are amino acid-containing lipids that form an amide bond between an amino acid and a fatty acid. Subsequently, a second fatty acid becomes linked, often via the 3-hydroxy group on the first fatty acid. These amide-linked aminolipids have, as of now, been exclusively identified in bacteria. Several hydrophilic head groups have been discovered in these aminolipids including ornithine, glutamine, glycine, lysine, and more recently, a sulfur-containing non-proteinogenic amino acid cysteinolic acid. Here, we aim to review current advances in the genetics, biochemistry and function of these aminolipids as well as giving an ecological perspective. We provide evidence for their potential significance in the ecophysiology of all major microbiomes, i.e. gut, soil, and aquatic as well as highlighting their important roles in influencing biological interactions.

Segmental patterning of microbiota and immune cells in the murine intestinal tract

The intestine exhibits distinct characteristics along its length, with a substantial immune cell reservoir and diverse microbiota crucial for maintaining health. This study investigates how anatomical location and regional microbiota influence intestinal immune cell abundance. Using conventionally colonized and germ-free mice, segment-specific immune cell composition and microbial communities were assessed. Metagenomic sequencing analyzed microbiome variations, while flow cytometry and immunofluorescence examined immune cell composition. Microbiome composition varied significantly along the intestine, with diversity and abundance increasing from upper to lower segments. Immune cells showed distinct segment-specific patterning influenced by microbial colonization and localization. T cell subsets displayed varied dependence on microbiome presence and anatomical location. This study highlights locoregional differences in intestinal immune cell and microbiome composition, identifying immune subsets susceptible to microbiota presence. The findings provide context for understanding immune cell alterations in disease models.

A metatranscriptomics strategy for efficient characterization of the microbiome in human tissues with low microbial biomass

The high background of host RNA poses a major challenge to metatranscriptome analysis of human samples. Hence, metatranscriptomics has been mainly applied to microbe-rich samples, while its application in human tissues with low ratio of microbial to host cells has yet to be explored. Since there is no computational workflow specifically designed for the taxonomic and functional analysis of this type of samples, we propose an effective metatranscriptomics strategy to accurately characterize the microbiome in human tissues with a low ratio of microbial to host content. We experimentally generated synthetic samples with well-characterized bacterial and host cell compositions, and mimicking human samples with high and low microbial loads. These synthetic samples were used for optimizing and establishing the workflow in a controlled setting. Our results show that the integration of the taxonomic analysis of optimized Kraken 2/Bracken with the functional analysis of HUMAnN 3 in samples with low microbial content, enables the accurate identification of a large number of microbial species with a low false-positive rate, while improving the detection of microbial functions. The effectiveness of our metatranscriptomics workflow was demonstrated in synthetic samples, simulated datasets, and most importantly, human gastric tissue specimens, thus providing a proof of concept for its applicability on mucosal tissues of the gastrointestinal tract. The use of an accurate and reliable metatranscriptomics approach for human tissues with low microbial content will expand our understanding of the functional activity of the mucosal microbiome, uncovering critical interactions between the microbiome and the host in health and disease.

Shotgun metagenomics and systemic targeted metabolomics highlight indole-3-propionic acid as a protective gut microbial metabolite against influenza infection

The gut-to-lung axis is critical during respiratory infections, including influenza A virus (IAV) infection. In the present study, we used high-resolution shotgun metagenomics and targeted metabolomic analysis to characterize influenza-associated changes in the composition and metabolism of the mouse gut microbiota. We observed several taxonomic-level changes on day (D)7 post-infection, including a marked reduction in the abundance of members of the Lactobacillaceae and Bifidobacteriaceae families, and an increase in the abundance of Akkermansia muciniphila. On D14, perturbation persisted in some species. Functional scale analysis of metagenomic data revealed transient changes in several metabolic pathways, particularly those leading to the production of short-chain fatty acids (SCFAs), polyamines, and tryptophan metabolites. Quantitative targeted metabolomics analysis of the serum revealed changes in specific classes of gut microbiota metabolites, including SCFAs, trimethylamine, polyamines, and indole-containing tryptophan metabolites. A marked decrease in indole-3-propionic acid (IPA) blood level was observed on D7. Changes in microbiota-associated metabolites correlated with changes in taxon abundance and disease marker levels. In particular, IPA was positively correlated with some Lactobacillaceae and Bifidobacteriaceae species (Limosilactobacillus reuteri, Lactobacillus animalis) and negatively correlated with Bacteroidales bacterium M7, viral load, and inflammation markers. IPA supplementation in diseased animals reduced viral load and lowered local (lung) and systemic inflammation. Treatment of mice with antibiotics targeting IPA-producing bacteria before infection enhanced viral load and lung inflammation, an effect inhibited by IPA supplementation. The results of this integrated metagenomic-metabolomic analysis highlighted IPA as an important contributor to influenza outcomes and a potential biomarker of disease severity.

Growth rates of marine prokaryotes are extremely diverse, even among closely related taxa

Marine prokaryotes play crucial roles in ocean biogeochemical cycles, being their contribution strongly influenced by their growth rates. Hence, elucidating the variability and phylogenetic imprint of marine prokaryotes' growth rates are crucial for better determining the role of individual taxa in biogeochemical cycles. Here, we estimated prokaryotic growth rates at high phylogenetic resolution in manipulation experiments using water from the northwestern Mediterranean Sea. Experiments were run in the four seasons with different treatments that reduced growth limiting factors: predators, nutrient availability, viruses, and light. Single-amplicon sequence variants (ASVs)-based growth rates were calculated from changes in estimated absolute abundances using total prokaryotic abundance and the proportion of each individual ASV. The trends obtained for growth rates in the different experiments were consistent with other estimates based on total cell-counts, catalyzed reporter deposition fluorescence in situ hybridization subcommunity cell-counts or metagenomic-operational taxonomic units (OTUs). Our calculations unveil a broad range of growth rates (0.3-10 d-1) with significant variability even within closely related ASVs. Likewise, the impact of growth limiting factors changed over the year for individual ASVs. High numbers of responsive ASVs were shared between winter and spring seasons, as well as throughout the year in the treatments with reduced nutrient limitation and viral pressure. The most responsive ASVs were rare in the in situ communities, comprising a large pool of taxa with the potential to rapidly respond to environmental changes. Essentially, our results highlight the lack of phylogenetic coherence in the range of growth rates observed, and differential responses to the various limiting factors, even for closely related taxa.

Turnover of strain-level diversity modulates functional traits in the honeybee gut microbiome between nurses and foragers

BACKGROUND

Strain-level diversity is widespread among bacterial species and can expand the functional potential of natural microbial communities. However, to what extent communities undergo consistent shifts in strain composition in response to environmental/host changes is less well understood.

RESULTS

Here, we used shotgun metagenomics to compare the gut microbiota of two behavioral states of the Western honeybee (Apis mellifera), namely nurse and forager bees. While their gut microbiota is composed of the same bacterial species, we detect consistent changes in strain-level composition between nurses and foragers. Single nucleotide variant profiles of predominant bacterial species cluster by behavioral state. Moreover, we identify strain-specific gene content related to nutrient utilization, vitamin biosynthesis, and cell-cell interactions specifically associated with the two behavioral states.

CONCLUSIONS

Our findings show that strain-level diversity in host-associated communities can undergo consistent changes in response to host behavioral changes modulating the functional potential of the community.

GDmicro: classifying host disease status with GCN and deep adaptation network based on the human gut microbiome data

MOTIVATION

With advances in metagenomic sequencing technologies, there are accumulating studies revealing the associations between the human gut microbiome and some human diseases. These associations shed light on using gut microbiome data to distinguish case and control samples of a specific disease, which is also called host disease status classification. Importantly, using learning-based models to distinguish the disease and control samples is expected to identify important biomarkers more accurately than abundance-based statistical analysis. However, available tools have not fully addressed two challenges associated with this task: limited labeled microbiome data and decreased accuracy in cross-studies. The confounding factors, such as the diet, technical biases in sample collection/sequencing across different studies/cohorts often jeopardize the generalization of the learning model.

RESULTS

To address these challenges, we develop a new tool GDmicro, which combines semi-supervised learning and domain adaptation to achieve a more generalized model using limited labeled samples. We evaluated GDmicro on human gut microbiome data from 11 cohorts covering 5 different diseases. The results show that GDmicro has better performance and robustness than state-of-the-art tools. In particular, it improves the AUC from 0.783 to 0.949 in identifying inflammatory bowel disease. Furthermore, GDmicro can identify potential biomarkers with greater accuracy than abundance-based statistical analysis methods. It also reveals the contribution of these biomarkers to the host's disease status.

AVAILABILITY AND IMPLEMENTATION

https://github.com/liaoherui/GDmicro.

Gut microbiomes of agropastoral children from the Adadle region of Ethiopia reflect their unique dietary habits

The composition and function of the intestinal microbiota are major determinants of human health and are strongly influenced by diet, antibiotic treatment, lifestyle and geography. Nevertheless, we currently have only little data on microbiomes of non-westernized communities. We assess the stool microbiota composition in 59 children aged 2-5 years from the Adadle district of Ethiopia, Somali Regional State. Here, milk and starch-rich food are predominant components of the local diet, where the inhabitants live a remote, traditional agropastoral lifestyle. Microbiota composition, function and the resistome were characterized by both 16S rRNA gene amplicon and shotgun metagenomic sequencing and compared to 1471 publicly available datasets from children living in traditional, transitional, and industrial communities with different subsistence strategies. Samples from the Adadle district are low in Bacteroidaceae, and Prevotellaceae, the main bacterial representatives in the feces of children living in industrialized and non-industrialized communities, respectively. In contrast, they had a higher relative abundance in Streptococcaceae, Bifidobacteriaceae and Erysipelatoclostridiaceae. Further, genes involved in degradation pathways of lactose, D-galactose and simple carbohydrates were enriched. Overall, our study revealed a unique composition of the fecal microbiota of these agropastoral children, highlighting the need to further characterize the fecal bacterial composition of human populations living different lifestyles.

Metagenome-assembled genomes reveal greatly expanded taxonomic and functional diversification of the abundant marine Roseobacter RCA cluster

BACKGROUND

The RCA (Roseobacter clade affiliated) cluster belongs to the family Roseobacteracea and represents a major Roseobacter lineage in temperate to polar oceans. Despite its prevalence and abundance, only a few genomes and one described species, Planktomarina temperata, exist. To gain more insights into our limited understanding of this cluster and its taxonomic and functional diversity and biogeography, we screened metagenomic datasets from the global oceans and reconstructed metagenome-assembled genomes (MAG) affiliated to this cluster.

RESULTS

The total of 82 MAGs, plus five genomes of isolates, reveal an unexpected diversity and novel insights into the genomic features, the functional diversity, and greatly refined biogeographic patterns of the RCA cluster. This cluster is subdivided into three genera: Planktomarina, Pseudoplanktomarina, and the most deeply branching Candidatus Paraplanktomarina. Six of the eight Planktomarina species have larger genome sizes (2.44-3.12 Mbp) and higher G + C contents (46.36-53.70%) than the four Pseudoplanktomarina species (2.26-2.72 Mbp, 42.22-43.72 G + C%). Cand. Paraplanktomarina is represented only by one species with a genome size of 2.40 Mbp and a G + C content of 45.85%. Three novel species of the genera Planktomarina and Pseudoplanktomarina are validly described according to the SeqCode nomenclature for prokaryotic genomes. Aerobic anoxygenic photosynthesis (AAP) is encoded in three Planktomarina species. Unexpectedly, proteorhodopsin (PR) is encoded in the other Planktomarina and all Pseudoplanktomarina species, suggesting that this light-driven proton pump is the most important mode of acquiring complementary energy of the RCA cluster. The Pseudoplanktomarina species exhibit differences in functional traits compared to Planktomarina species and adaptations to more resource-limited conditions. An assessment of the global biogeography of the different species greatly expands the range of occurrence and shows that the different species exhibit distinct biogeographic patterns. They partially reflect the genomic features of the species.

CONCLUSIONS

Our detailed MAG-based analyses shed new light on the diversification, environmental adaptation, and global biogeography of a major lineage of pelagic bacteria. The taxonomic delineation and validation by the SeqCode nomenclature of prominent genera and species of the RCA cluster may be a promising way for a refined taxonomic identification of major prokaryotic lineages and sublineages in marine and other prokaryotic communities assessed by metagenomics approaches. Video Abstract.

Multi-kingdom gut microbiota analyses define bacterial-fungal interplay and microbial markers of pan-cancer immunotherapy across cohorts

The effect of gut bacteria on the response to immune checkpoint inhibitors (ICIs) has been studied, but the relationship between fungi and ICI responses is not fully understood. Herein, 862 fecal metagenomes from 9 different cohorts were integrated for the identification of differentially abundant fungi and subsequent construction of random forest (RF) models to predict ICI responses. Fungal markers demonstrate excellent performance, with an average area under the curve (AUC) of 0.87. Their performance improves even further, reaching an average AUC of 0.89 when combined with bacterial markers. Higher enrichment of exhausted T cells is detected in responders, as predicted by fungal markers. Multi-kingdom network and functional analysis reveal that the fungus Schizosaccharomyces octosporus may ferment starch into short-chain fatty acids in responders. This study provides a fungal profile of the ICI response and the identification of multi-kingdom microbial markers with good performance that may improve the overall applicability of ICI therapy.

Dispersal, habitat filtering, and eco-evolutionary dynamics as drivers of local and global wetland viral biogeography

Wetlands store 20-30% of the world's soil carbon, and identifying the microbial controls on these carbon reserves is essential to predicting feedbacks to climate change. Although viral infections likely play important roles in wetland ecosystem dynamics, we lack a basic understanding of wetland viral ecology. Here 63 viral size-fraction metagenomes (viromes) and paired total metagenomes were generated from three time points in 2021 at seven fresh- and saltwater wetlands in the California Bodega Marine Reserve. We recovered 12,826 viral population genomic sequences (vOTUs), only 4.4% of which were detected at the same field site two years prior, indicating a small degree of population stability or recurrence. Viral communities differed most significantly among the seven wetland sites and were also structured by habitat (plant community composition and salinity). Read mapping to a new version of our reference database, PIGEONv2.0 (515,763 vOTUs), revealed 196 vOTUs present over large geographic distances, often reflecting shared habitat characteristics. Wetland vOTU microdiversity was significantly lower locally than globally and lower within than between time points, indicating greater divergence with increasing spatiotemporal distance. Viruses tended to have broad predicted host ranges via CRISPR spacer linkages to metagenome-assembled genomes, and increased SNP frequencies in CRISPR-targeted major tail protein genes suggest potential viral eco-evolutionary dynamics in response to both immune targeting and changes in host cell receptors involved in viral attachment. Together, these results highlight the importance of dispersal, environmental selection, and eco-evolutionary dynamics as drivers of local and global wetland viral biogeography.

Systematic analysis of drug combinations against Gram-positive bacteria

Drug combinations can expand options for antibacterial therapies but have not been systematically tested in Gram-positive species. We profiled ~8,000 combinations of 65 antibacterial drugs against the model species Bacillus subtilis and two prominent pathogens, Staphylococcus aureus and Streptococcus pneumoniae. Thereby, we recapitulated previously known drug interactions, but also identified ten times more novel interactions in the pathogen S. aureus, including 150 synergies. We showed that two synergies were equally effective against multidrug-resistant S. aureus clinical isolates in vitro and in vivo. Interactions were largely species-specific and synergies were distinct from those of Gram-negative species, owing to cell surface and drug uptake differences. We also tested 2,728 combinations of 44 commonly prescribed non-antibiotic drugs with 62 drugs with antibacterial activity against S. aureus and identified numerous antagonisms that might compromise the efficacy of antimicrobial therapies. We identified even more synergies and showed that the anti-aggregant ticagrelor synergized with cationic antibiotics by modifying the surface charge of S. aureus. All data can be browsed in an interactive interface ( https://apps.embl.de/combact/ ).

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.

Exercise and microbiome: From big data to therapy

Exercise is a vital component in maintaining optimal health and serves as a prospective therapeutic intervention for various diseases. The human microbiome, comprised of trillions of microorganisms, plays a crucial role in overall health. Given the advancements in microbiome research, substantial databases have been created to decipher the functionality and mechanisms of the microbiome in health and disease contexts. This review presents an initial overview of microbiomics development and related databases, followed by an in-depth description of the multi-omics technologies for microbiome. It subsequently synthesizes the research pertaining to exercise-induced modifications of the microbiome and diseases that impact the microbiome. Finally, it highlights the potential therapeutic implications of an exercise-modulated microbiome in intestinal disease, obesity and diabetes, cardiovascular disease, and immune/inflammation-related diseases.

Distinctive features of the oropharyngeal microbiome in Inuit of Nunavik and correlations of mild to moderate bronchial obstruction with dysbiosis

Inuit of Nunavik are coping with living conditions that can influence respiratory health. Our objective was to investigate associations between respiratory health in Inuit communities and their airway microbiome. Oropharyngeal samples were collected during the Qanuilirpitaa? 2017 Inuit Health Survey and subjected to metagenomic analyses. Participants were assigned to a bronchial obstruction group or a control group based on their clinical history and their pulmonary function, as monitored by spirometry. The Inuit microbiota composition was found to be distinct from other studied populations. Within the Inuit microbiota, differences in diversity measures tend to distinguish the two groups. Bacterial taxa found to be more abundant in the control group included candidate probiotic strains, while those enriched in the bronchial obstruction group included opportunistic pathogens. Crossing taxa affiliation method and machine learning consolidated our finding of distinct core microbiomes between the two groups. More microbial metabolic pathways were enriched in the control participants and these were often involved in vitamin and anti-inflammatory metabolism, while a link could be established between the enriched pathways in the disease group and inflammation. Overall, our results suggest a link between microbial abundance, interactions and metabolic activities and respiratory health in the Inuit population.

Benchmarking Metagenomic Classifiers on Simulated Ancient and Modern Metagenomic Data

Taxonomic profiling of ancient metagenomic samples is challenging due to the accumulation of specific damage patterns on DNA over time. Although a number of methods for metagenome profiling have been developed, most of them have been assessed on modern metagenomes or simulated metagenomes mimicking modern metagenomes. Further, a comparative assessment of metagenome profilers on simulated metagenomes representing a spectrum of degradation depth, from the extremity of ancient (most degraded) to current or modern (not degraded) metagenomes, has not yet been performed. To understand the strengths and weaknesses of different metagenome profilers, we performed their comprehensive evaluation on simulated metagenomes representing human dental calculus microbiome, with the level of DNA damage successively raised to mimic modern to ancient metagenomes. All classes of profilers, namely, DNA-to-DNA, DNA-to-protein, and DNA-to-marker comparison-based profilers were evaluated on metagenomes with varying levels of damage simulating deamination, fragmentation, and contamination. Our results revealed that, compared to deamination and fragmentation, human and environmental contamination of ancient DNA (with modern DNA) has the most pronounced effect on the performance of each profiler. Further, the DNA-to-DNA (e.g., Kraken2, Bracken) and DNA-to-marker (e.g., MetaPhlAn4) based profiling approaches showed complementary strengths, which can be leveraged to elevate the state-of-the-art of ancient metagenome profiling.

Clostridium scindens secretome suppresses virulence gene expression of Clostridioides difficile in a bile acid-independent manner

Clostridioides difficile infection (CDI) is a major health concern and one of the leading causes of hospital-acquired diarrhea in many countries. C. difficile infection is challenging to treat as C. difficile is resistant to multiple antibiotics. Alternative solutions are needed as conventional treatment with broad-spectrum antibiotics often leads to recurrent CDI. Recent studies have shown that specific microbiota-based therapeutics such as bile acids (BAs) are promising approaches to treat CDI. Clostridium scindens encodes the bile acid-induced (bai) operon that carries out 7-alpha-dehydroxylation of liver-derived primary BAs to secondary BAs. This biotransformation is thought to increase the antibacterial effects of BAs on C. difficile. Here, we used an automated multistage fermentor to study the antibacterial actions of C. scindens and BAs on C. difficile in the presence/absence of a gut microbial community derived from healthy human donor fecal microbiota. We observed that C. scindens inhibited C. difficile growth when the medium was supplemented with primary BAs. Transcriptomic analysis indicated upregulation of C. scindens bai operon and suppressed expression of C. difficile exotoxins that mediate CDI. We also observed BA-independent antibacterial activity of the secretome from C. scindens cultured overnight in a medium without supplementary primary BAs, which suppressed growth and exotoxin expression in C. difficile mono-culture. Further investigation of the molecular basis of our observation could lead to a more specific treatment for CDI than current approaches. IMPORTANCE There is an urgent need for new approaches to replace the available treatment options against Clostridioides difficile infection (CDI). Our novel work reports a bile acid-independent reduction of C. difficile growth and virulence gene expression by the secretome of Clostridium scindens. This potential treatment combined with other antimicrobial strategies could facilitate the development of alternative therapies in anticipation of CDI and in turn reduce the risk of antimicrobial resistance.

Ecogenomics and cultivation reveal distinctive viral-bacterial communities in the surface microlayer of a Baltic Sea slick

Visible surface films, termed slicks, can extensively cover freshwater and marine ecosystems, with coastal regions being particularly susceptible to their presence. The sea-surface microlayer (SML), the upper 1-mm at the air-water interface in slicks (herein slick SML) harbors a distinctive bacterial community, but generally little is known about SML viruses. Using flow cytometry, metagenomics, and cultivation, we characterized viruses and bacteria in a brackish slick SML in comparison to non-slick SML as well as seawater below slick and non-slick areas (subsurface water = SSW). Size-fractionated filtration of all samples distinguished viral attachment to hosts and particles. The slick SML contained higher abundances of virus-like particles, prokaryotic cells, and dissolved organic carbon compared to non-slick SML and SSW. The community of 428 viral operational taxonomic units (vOTUs), 426 predicted as lytic, distinctly differed across all size fractions in the slick SML compared to non-slick SML and SSW. Specific metabolic profiles of bacterial metagenome-assembled genomes and isolates in the slick SML included a prevalence of genes encoding motility and carbohydrate-active enzymes (CAZymes). Several vOTUs were enriched in slick SML, and many virus variants were associated with particles. Nine vOTUs were only found in slick SML, six of them being targeted by slick SML-specific clustered-regularly interspaced short palindromic repeats (CRISPR) spacers likely originating from Gammaproteobacteria. Moreover, isolation of three previously unknown lytic phages for Alishewanella sp. and Pseudoalteromonas tunicata, abundant and actively replicating slick SML bacteria, suggests that viral activity in slicks contributes to biogeochemical cycling in coastal ecosystems.

Plastics shape the black soldier fly larvae gut microbiome and select for biodegrading functions

BACKGROUND

In the last few years, considerable attention has been focused on the plastic-degrading capability of insects and their gut microbiota in order to develop novel, effective, and green strategies for plastic waste management. Although many analyses based on 16S rRNA gene sequencing are available, an in-depth analysis of the insect gut microbiome to identify genes with plastic-degrading potential is still lacking.

RESULTS

In the present work, we aim to fill this gap using Black Soldier Fly (BSF) as insect model. BSF larvae have proven capability to efficiently bioconvert a wide variety of organic wastes but, surprisingly, have never been considered for plastic degradation. BSF larvae were reared on two widely used plastic polymers and shotgun metagenomics was exploited to evaluate if and how plastic-containing diets affect composition and functions of the gut microbial community. The high-definition picture of the BSF gut microbiome gave access for the first time to the genomes of culturable and unculturable microorganisms in the gut of insects reared on plastics and revealed that (i) plastics significantly shaped bacterial composition at species and strain level, and (ii) functions that trigger the degradation of the polymer chains, i.e., DyP-type peroxidases, multicopper oxidases, and alkane monooxygenases, were highly enriched in the metagenomes upon exposure to plastics, consistently with the evidences obtained by scanning electron microscopy and 1H nuclear magnetic resonance analyses on plastics.

CONCLUSIONS

In addition to highlighting that the astonishing plasticity of the microbiota composition of BSF larvae is associated with functional shifts in the insect microbiome, the present work sets the stage for exploiting BSF larvae as "bioincubators" to isolate microbial strains and enzymes for the development of innovative plastic biodegradation strategies. However, most importantly, the larvae constitute a source of enzymes to be evolved and valorized by pioneering synthetic biology approaches. Video Abstract.

Consistency across multi-omics layers in a drug-perturbed gut microbial community

Multi-omics analyses are used in microbiome studies to understand molecular changes in microbial communities exposed to different conditions. However, it is not always clear how much each omics data type contributes to our understanding and whether they are concordant with each other. Here, we map the molecular response of a synthetic community of 32 human gut bacteria to three non-antibiotic drugs by using five omics layers (16S rRNA gene profiling, metagenomics, metatranscriptomics, metaproteomics and metabolomics). We find that all the omics methods with species resolution are highly consistent in estimating relative species abundances. Furthermore, different omics methods complement each other for capturing functional changes. For example, while nearly all the omics data types captured that the antipsychotic drug chlorpromazine selectively inhibits Bacteroidota representatives in the community, the metatranscriptome and metaproteome suggested that the drug induces stress responses related to protein quality control. Metabolomics revealed a decrease in oligosaccharide uptake, likely caused by Bacteroidota depletion. Our study highlights how multi-omics datasets can be utilized to reveal complex molecular responses to external perturbations in microbial communities.

Phage-microbe dynamics after sterile faecal filtrate transplantation in individuals with metabolic syndrome: a double-blind, randomised, placebo-controlled clinical trial assessing efficacy and safety

Bacteriophages (phages) are bacterial viruses that have been shown to shape microbial communities. Previous studies have shown that faecal virome transplantation can decrease weight gain and normalize blood glucose tolerance in diet-induced obese mice. Therefore, we performed a double-blind, randomised, placebo-controlled pilot study in which 24 individuals with metabolic syndrome were randomised to a faecal filtrate transplantation (FFT) from a lean healthy donor (n = 12) or placebo (n = 12). The primary outcome, change in glucose metabolism, and secondary outcomes, safety and longitudinal changes within the intestinal bacteriome and phageome, were assessed from baseline up to 28 days. All 24 included subjects completed the study and are included in the analyses. While the overall changes in glucose metabolism are not significantly different between both groups, the FFT is well-tolerated and without any serious adverse events. The phage virion composition is significantly altered two days after FFT as compared to placebo, which coincides with more virulent phage-microbe interactions. In conclusion, we provide evidence that gut phages can be safely administered to transiently alter the gut microbiota of recipients.

Computational exploration of the global microbiome for antibiotic discovery

Novel antibiotics are urgently needed to combat the antibiotic-resistance crisis. We present a machine learning-based approach to predict prokaryotic antimicrobial peptides (AMPs) by leveraging a vast dataset of 63,410 metagenomes and 87,920 microbial genomes. This led to the creation of AMPSphere, a comprehensive catalog comprising 863,498 non-redundant peptides, the majority of which were previously unknown. We observed that AMP production varies by habitat, with animal-associated samples displaying the highest proportion of AMPs compared to other habitats. Furthermore, within different human-associated microbiota, strain-level differences were evident. To validate our predictions, we synthesized and experimentally tested 50 AMPs, demonstrating their efficacy against clinically relevant drug-resistant pathogens both in vitro and in vivo. These AMPs exhibited antibacterial activity by targeting the bacterial membrane. Additionally, AMPSphere provides valuable insights into the evolutionary origins of peptides. In conclusion, our approach identified AMP sequences within prokaryotic microbiomes, opening up new avenues for the discovery of antibiotics.

Metabolic engineering of human gut microbiome: Recent developments and future perspectives

Many studies have demonstrated that the gut microbiota is associated with human health and disease. Manipulation of the gut microbiota, e.g. supplementation of probiotics, has been suggested to be feasible, but subject to limited therapeutic efficacy. To develop efficient microbiota-targeted diagnostic and therapeutic strategies, metabolic engineering has been applied to construct genetically modified probiotics and synthetic microbial consortia. This review mainly discusses commonly adopted strategies for metabolic engineering in the human gut microbiome, including the use of in silico, in vitro, or in vivo approaches for iterative design and construction of engineered probiotics or microbial consortia. Especially, we highlight how genome-scale metabolic models can be applied to advance our understanding of the gut microbiota. Also, we review the recent applications of metabolic engineering in gut microbiome studies as well as discuss important challenges and opportunities.

Gut microbial carbohydrate metabolism contributes to insulin resistance

Insulin resistance is the primary pathophysiology underlying metabolic syndrome and type 2 diabetes1,2. Previous metagenomic studies have described the characteristics of gut microbiota and their roles in metabolizing major nutrients in insulin resistance3-9. In particular, carbohydrate metabolism of commensals has been proposed to contribute up to 10% of the host's overall energy extraction10, thereby playing a role in the pathogenesis of obesity and prediabetes3,4,6. Nevertheless, the underlying mechanism remains unclear. Here we investigate this relationship using a comprehensive multi-omics strategy in humans. We combine unbiased faecal metabolomics with metagenomics, host metabolomics and transcriptomics data to profile the involvement of the microbiome in insulin resistance. These data reveal that faecal carbohydrates, particularly host-accessible monosaccharides, are increased in individuals with insulin resistance and are associated with microbial carbohydrate metabolisms and host inflammatory cytokines. We identify gut bacteria associated with insulin resistance and insulin sensitivity that show a distinct pattern of carbohydrate metabolism, and demonstrate that insulin-sensitivity-associated bacteria ameliorate host phenotypes of insulin resistance in a mouse model. Our study, which provides a comprehensive view of the host-microorganism relationships in insulin resistance, reveals the impact of carbohydrate metabolism by microbiota, suggesting a potential therapeutic target for ameliorating insulin resistance.

Current concepts, advances, and challenges in deciphering the human microbiota with metatranscriptomics

Metatranscriptomics refers to the analysis of the collective microbial transcriptome of a sample. Its increased utilization for the characterization of human-associated microbial communities has enabled the discovery of many disease-state related microbial activities. Here, we review the principles of metatranscriptomics-based analysis of human-associated microbial samples. We describe strengths and weaknesses of popular sample preparation, sequencing, and bioinformatics approaches and summarize strategies for their use. We then discuss how human-associated microbial communities have recently been examined and how their characterization may change. We conclude that metatranscriptomics insights into human microbiotas under health and disease have not only expanded our knowledge on human health, but also opened avenues for rational antimicrobial drug use and disease management.

Removal of false positives in metagenomics-based taxonomy profiling via targeting Type IIB restriction sites

Accurate species identification and abundance estimation are critical for the interpretation of whole metagenome sequencing (WMS) data. Yet, existing metagenomic profilers suffer from false-positive identifications, which can account for more than 90% of total identified species. Here, by leveraging species-specific Type IIB restriction endonuclease digestion sites as reference instead of universal markers or whole microbial genomes, we present a metagenomic profiler, MAP2B (MetAgenomic Profiler based on type IIB restriction sites), to resolve those issues. We first illustrate the pitfalls of using relative abundance as the only feature in determining false positives. We then propose a feature set to distinguish false positives from true positives, and using simulated metagenomes from CAMI2, we establish a false-positive recognition model. By benchmarking the performance in metagenomic profiling using a simulation dataset with varying sequencing depth and species richness, we illustrate the superior performance of MAP2B over existing metagenomic profilers in species identification. We further test the performance of MAP2B using real WMS data from an ATCC mock community, confirming its superior precision against sequencing depth. Finally, by leveraging WMS data from an IBD cohort, we demonstrate the taxonomic features generated by MAP2B can better discriminate IBD and predict metabolomic profiles.

Inter-comparison of marine microbiome sampling protocols

Research on marine microbial communities is growing, but studies are hard to compare because of variation in seawater sampling protocols. To help researchers in the inter-comparison of studies that use different seawater sampling methodologies, as well as to help them design future sampling campaigns, we developed the EuroMarine Open Science Exploration initiative (EMOSE). Within the EMOSE framework, we sampled thousands of liters of seawater from a single station in the NW Mediterranean Sea (Service d'Observation du Laboratoire Arago [SOLA], Banyuls-sur-Mer), during one single day. The resulting dataset includes multiple seawater processing approaches, encompassing different material-type kinds of filters (cartridge membrane and flat membrane), three different size fractionations (>0.22 µm, 0.22-3 µm, 3-20 µm and >20 µm), and a number of different seawater volumes ranging from 1 L up to 1000 L. We show that the volume of seawater that is filtered does not have a significant effect on prokaryotic and protist diversity, independently of the sequencing strategy. However, there was a clear difference in alpha and beta diversity between size fractions and between these and "whole water" (with no pre-fractionation). Overall, we recommend care when merging data from datasets that use filters of different pore size, but we consider that the type of filter and volume should not act as confounding variables for the tested sequencing strategies. To the best of our knowledge, this is the first time a publicly available dataset effectively allows for the clarification of the impact of marine microbiome methodological options across a wide range of protocols, including large-scale variations in sampled volume.

StrainIQ: A Novel n-Gram-Based Method for Taxonomic Profiling of Human Microbiota at the Strain Level

The emergence of next-generation sequencing (NGS) technology has greatly influenced microbiome research and led to the development of novel bioinformatics tools to deeply analyze metagenomics datasets. Identifying strain-level variations in microbial communities is important to understanding the onset and progression of diseases, host-pathogen interrelationships, and drug resistance, in addition to designing new therapeutic regimens. In this study, we developed a novel tool called StrainIQ (strain identification and quantification) based on a new n-gram-based (series of n number of adjacent nucleotides in the DNA sequence) algorithm for predicting and quantifying strain-level taxa from whole-genome metagenomic sequencing data. We thoroughly evaluated our method using simulated and mock metagenomic datasets and compared its performance with existing methods. On average, it showed 85.8% sensitivity and 78.2% specificity on simulated datasets. It also showed higher specificity and sensitivity using n-gram models built from reduced reference genomes and on models with lower coverage sequencing data. It outperforms alternative approaches in genus- and strain-level prediction and strain abundance estimation. Overall, the results show that StrainIQ achieves high accuracy by implementing customized model-building and is an efficient tool for site-specific microbial community profiling.

Commensal bacteria promote azathioprine therapy failure in inflammatory bowel disease via decreasing 6-mercaptopurine bioavailability

Azathioprine (AZA) therapy failure, though not the primary cause, contributes to disease relapse and progression in inflammatory bowel disease (IBD). However, the role of gut microbiota in AZA therapy failure remains poorly understood. We found a high prevalence of Blautia wexlerae in patients with IBD with AZA therapy failure, associated with shorter disease flare survival time. Colonization of B. wexlerae increased inflammatory macrophages and compromised AZA's therapeutic efficacy in mice with intestinal colitis. B. wexlerae colonization reduced 6-mercaptopurine (6-MP) bioavailability by enhancing selenium-dependent xanthine dehydrogenase (sd-XDH) activity. The enzyme sd-XDH converts 6-MP into its inactive metabolite, 6-thioxanthine (6-TX), thereby impairing its ability to inhibit inflammation in mice. Supplementation with Bacillus (B.) subtilis enriched in hypoxanthine phosphoribosyltransferase (HPRT) effectively mitigated B. wexlerae-induced AZA treatment failure in mice with intestinal colitis. These findings emphasize the need for tailored management strategies based on B. wexlerae levels in patients with IBD.

Donor-recipient specificity and age-dependency in fecal microbiota therapy and probiotic resolution of gastrointestinal symptoms

Fecal microbiota transplantation (FMT) has proven to be an effective treatment for recurrent Clostridioides difficile infection (rCDI) in both adult and pediatric patients. However, as microbiome development is a critical factor in children, it remains unclear whether adult fecal donors can provide age-appropriate functional restoration in pediatric patients. To address this issue, we conducted an integrated systems approach and found that concordant donor strain engraftment, along with metabolite restoration, are associated with FMT outcomes in both adult and pediatric rCDI patients. Although functional restoration after FMT is not strain-specific, specialized metabolic functions are retained in pediatric patients when adult fecal donors are used. Furthermore, we demonstrated broad utility of high-resolution variant-calling by linking probiotic-strain engraftment with improved gastrointestinal symptoms in adults with irritable bowel syndrome and in children with autism spectrum disorder. Our findings emphasize the importance of strain-level identification when assessing the efficacy of probiotics and microbiota-based therapeutics.

Genus-wide genomic characterization of Macrococcus: insights into evolution, population structure, and functional potential

Introduction

Macrococcus species have been isolated from a range of mammals and mammal-derived food products. While they are largely considered to be animal commensals, Macrococcus spp. can be opportunistic pathogens in both veterinary and human clinical settings. This study aimed to provide insight into the evolution, population structure, and functional potential of the Macrococcus genus, with an emphasis on antimicrobial resistance (AMR) and virulence potential.

Methods

All high-quality, publicly available Macrococcus genomes (n = 104, accessed 27 August 2022), plus six South African genomes sequenced here (two strains from bovine clinical mastitis cases and four strains from beef products), underwent taxonomic assignment (using four different approaches), AMR determinant detection (via AMRFinderPlus), and virulence factor detection (using DIAMOND and the core Virulence Factor Database).

Results

Overall, the 110 Macrococcus genomes were of animal commensal, veterinary clinical, food-associated (including food spoilage), and environmental origins; five genomes (4.5%) originated from human clinical cases. Notably, none of the taxonomic assignment methods produced identical results, highlighting the potential for Macrococcus species misidentifications. The most common predicted antimicrobial classes associated with AMR determinants identified across Macrococcus included macrolides, beta-lactams, and aminoglycosides (n = 81, 61, and 44 of 110 genomes; 73.6, 55.5, and 40.0%, respectively). Genes showing homology to Staphylococcus aureus exoenzyme aureolysin were detected across multiple species (using 90% coverage, n = 40 and 77 genomes harboring aureolysin-like genes at 60 and 40% amino acid [AA] identity, respectively). S. aureus Panton-Valentine leucocidin toxin-associated lukF-PV and lukS-PV homologs were identified in eight M. canis genomes (≥40% AA identity, >85% coverage). Using a method that delineates populations using recent gene flow (PopCOGenT), two species (M. caseolyticus and M. armenti) were composed of multiple within-species populations. Notably, M. armenti was partitioned into two populations, which differed in functional potential (e.g., one harbored beta-lactamase family, type II toxin-antitoxin system, and stress response proteins, while the other possessed a Type VII secretion system; PopCOGenT p < 0.05).

Discussion

Overall, this study leverages all publicly available Macrococcus genomes in addition to newly sequenced genomes from South Africa to identify genomic elements associated with AMR or virulence potential, which can be queried in future experiments.

Evidence of cospeciation between termites and their gut bacteria on a geological time scale

Termites host diverse communities of gut microbes, including many bacterial lineages only found in this habitat. The bacteria endemic to termite guts are transmitted via two routes: a vertical route from parent colonies to daughter colonies and a horizontal route between colonies sometimes belonging to different termite species. The relative importance of both transmission routes in shaping the gut microbiota of termites remains unknown. Using bacterial marker genes derived from the gut metagenomes of 197 termites and one Cryptocercus cockroach, we show that bacteria endemic to termite guts are mostly transferred vertically. We identified 18 lineages of gut bacteria showing cophylogenetic patterns with termites over tens of millions of years. Horizontal transfer rates estimated for 16 bacterial lineages were within the range of those estimated for 15 mitochondrial genes, suggesting that horizontal transfers are uncommon and vertical transfers are the dominant transmission route in these lineages. Some of these associations probably date back more than 150 million years and are an order of magnitude older than the cophylogenetic patterns between mammalian hosts and their gut bacteria. Our results suggest that termites have cospeciated with their gut bacteria since first appearing in the geological record.

More than mcr: canonical plasmid- and transposon-encoded mobilized colistin resistance genes represent a subset of phosphoethanolamine transferases

Mobilized colistin resistance genes (mcr) may confer resistance to the last-resort antimicrobial colistin and can often be transmitted horizontally. mcr encode phosphoethanolamine transferases (PET), which are closely related to chromosomally encoded, intrinsic lipid modification PET (i-PET; e.g., EptA, EptB, CptA). To gain insight into the evolution of mcr within the context of i-PET, we identified 69,814 MCR-like proteins present across 256 bacterial genera (obtained by querying known MCR family representatives against the National Center for Biotechnology Information [NCBI] non-redundant protein database via protein BLAST). We subsequently identified 125 putative novel mcr-like genes, which were located on the same contig as (i) ≥1 plasmid replicon and (ii) ≥1 additional antimicrobial resistance gene (obtained by querying the PlasmidFinder database and NCBI's National Database of Antibiotic Resistant Organisms, respectively, via nucleotide BLAST). At 80% amino acid identity, these putative novel MCR-like proteins formed 13 clusters, five of which represented putative novel MCR families. Sequence similarity and a maximum likelihood phylogeny of mcr, putative novel mcr-like, and ipet genes indicated that sequence similarity was insufficient to discriminate mcr from ipet genes. A mixed-effect model of evolution (MEME) indicated that site- and branch-specific positive selection played a role in the evolution of alleles within the mcr-2 and mcr-9 families. MEME suggested that positive selection played a role in the diversification of several residues in structurally important regions, including (i) a bridging region that connects the membrane-bound and catalytic periplasmic domains, and (ii) a periplasmic loop juxtaposing the substrate entry tunnel. Moreover, eptA and mcr were localized within different genomic contexts. Canonical eptA genes were typically chromosomally encoded in an operon with a two-component regulatory system or adjacent to a TetR-type regulator. Conversely, mcr were represented by single-gene operons or adjacent to pap2 and dgkA, which encode a PAP2 family lipid A phosphatase and diacylglycerol kinase, respectively. Our data suggest that eptA can give rise to "colistin resistance genes" through various mechanisms, including mobilization, selection, and diversification of genomic context and regulatory pathways. These mechanisms likely altered gene expression levels and enzyme activity, allowing bona fide eptA to evolve to function in colistin resistance.

Impaired flux of bile acids from the liver to the gut reveals microbiome-immune interactions associated with liver damage

Currently, there is evidence that alteration in the gut ecosystem contributes to the development of liver diseases, however, the complex mechanisms involved are still unclear. We induced cholestasis in mice by bile duct ligation (BDL), mirroring the phenotype of a bile duct obstruction, to understand how gut microbiota alterations caused by an impaired flow of bile acid to the gut contribute to the pathogenesis and progression of liver disease. We performed longitudinal stool, heart, and liver sampling using mice receiving BDL and controls receiving sham operation (ShamOP). Shotgun metagenomics profiling using fecal samples taken before and on day 1, day 3, and day 7 after surgery was performed, and the cytokines and clinical chemistry profiles from heart blood, as well as the liver bile acids profile, were measured. The BDL surgery reshaped the microbiome of mice, resulting in highly distinct characteristics compared to the ShamOP. Our analysis of the microbiome pathways and ECs revealed that BDL reduces the production of hepatoprotective compounds in the gut, such as biotin, spermidine, arginine, and ornithine, which were negatively associated with inflammatory cytokines (IL-6, IL-23, MCP-1). The reduction of the functional potential of the gut microbiota in producing those hepatoprotective compounds is associated with the decrease of beneficial bacteria species from Anaerotruncus, Blautia, Eubacterium, and Lachnoclostridium genera, as well as the increase of disease-associated bacteria e.g., Escherichia coli and Entercoccus faecalis. Our findings advances our knowledge of the gut microbiome-bile acids-liver triangle, which may serve as a potential therapeutic strategy for liver diseases.

Ecology of Endozoicomonadaceae in three coral genera across the Pacific Ocean

Health and resilience of the coral holobiont depend on diverse bacterial communities often dominated by key marine symbionts of the Endozoicomonadaceae family. The factors controlling their distribution and their functional diversity remain, however, poorly known. Here, we study the ecology of Endozoicomonadaceae at an ocean basin-scale by sampling specimens from three coral genera (Pocillopora, Porites, Millepora) on 99 reefs from 32 islands across the Pacific Ocean. The analysis of 2447 metabarcoding and 270 metagenomic samples reveals that each coral genus harbored a distinct new species of Endozoicomonadaceae. These species are composed of nine lineages that have distinct biogeographic patterns. The most common one, found in Pocillopora, appears to be a globally distributed symbiont with distinct metabolic capabilities, including the synthesis of amino acids and vitamins not produced by the host. The other lineages are structured partly by the host genetic lineage in Pocillopora and mainly by the geographic location in Porites. Millepora is more rarely associated to Endozoicomonadaceae. Our results show that different coral genera exhibit distinct strategies of host-Endozoicomonadaceae associations that are defined at the bacteria lineage level.

Metagenomic next generation sequencing for studying antibiotic resistance genes in the environment

Bacterial antimicrobial resistance (AMR) is a persisting and growing threat to human health. Characterization of antibiotic resistance genes (ARGs) in the environment is important to understand and control ARG-associated microbial risks. Numerous challenges exist in monitoring ARGs in the environment, due to the extraordinary diversity of ARGs, low abundance of ARGs with respect to the complex environmental microbiomes, difficulties in linking ARGs with bacterial hosts by molecular methods, difficulties in achieving quantification and high throughput simultaneously, difficulties in assessing mobility potential of ARGs, and difficulties in determining the specific AMR determinant genes. Advances in the next generation sequencing (NGS) technologies and related computational and bioinformatic tools are facilitating rapid identification and characterization ARGs in genomes and metagenomes from environmental samples. This chapter discusses NGS-based strategies, including amplicon-based sequencing, whole genome sequencing, bacterial population-targeted metagenome sequencing, metagenomic NGS, quantitative metagenomic sequencing, and functional/phenotypic metagenomic sequencing. Current bioinformatic tools for analyzing sequencing data for studying environmental ARGs are also discussed.

Bacterial catabolism of membrane phospholipids links marine biogeochemical cycles

In marine systems, the availability of inorganic phosphate can limit primary production leading to bacterial and phytoplankton utilization of the plethora of organic forms available. Among these are phospholipids that form the lipid bilayer of all cells as well as released extracellular vesicles. However, information on phospholipid degradation is almost nonexistent despite their relevance for biogeochemical cycling. Here, we identify complete catabolic pathways for the degradation of the common phospholipid headgroups phosphocholine (PC) and phosphorylethanolamine (PE) in marine bacteria. Using Phaeobacter sp. MED193 as a model, we provide genetic and biochemical evidence that extracellular hydrolysis of phospholipids liberates the nitrogen-containing substrates ethanolamine and choline. Transporters for ethanolamine (EtoX) and choline (BetT) are ubiquitous and highly expressed in the global ocean throughout the water column, highlighting the importance of phospholipid and especially PE catabolism in situ. Thus, catabolic activation of the ethanolamine and choline degradation pathways, subsequent to phospholipid metabolism, specifically links, and hence unites, the phosphorus, nitrogen, and carbon cycles.

Gut microbiome and atrial fibrillation-results from a large population-based study

BACKGROUND

Atrial fibrillation (AF) is an important heart rhythm disorder in aging populations. The gut microbiome composition has been previously related to cardiovascular disease risk factors. Whether the gut microbial profile is also associated with the risk of AF remains unknown.

METHODS

We examined the associations of prevalent and incident AF with gut microbiota in the FINRISK 2002 study, a random population sample of 6763 individuals. We replicated our findings in an independent case-control cohort of 138 individuals in Hamburg, Germany.

FINDINGS

Multivariable-adjusted regression models revealed that prevalent AF (N = 116) was associated with nine microbial genera. Incident AF (N = 539) over a median follow-up of 15 years was associated with eight microbial genera with false discovery rate (FDR)-corrected P < 0.05. Both prevalent and incident AF were associated with the genera Enorma and Bifidobacterium (FDR-corrected P < 0.001). AF was not significantly associated with bacterial diversity measures. Seventy-five percent of top genera (Enorma, Paraprevotella, Odoribacter, Collinsella, Barnesiella, Alistipes) in Cox regression analyses showed a consistent direction of shifted abundance in an independent AF case-control cohort that was used for replication.

INTERPRETATION

Our findings establish the basis for the use of microbiome profiles in AF risk prediction. However, extensive research is still warranted before microbiome sequencing can be used for prevention and targeted treatment of AF.

FUNDING

This study was funded by European Research Council, German Ministry of Research and Education, Academy of Finland, Finnish Medical Foundation, and the Finnish Foundation for Cardiovascular Research, the Emil Aaltonen Foundation, and the Paavo Nurmi Foundation.

Expanding known viral diversity in the healthy infant gut

The gut microbiome is shaped through infancy and impacts the maturation of the immune system, thus protecting against chronic disease later in life. Phages, or viruses that infect bacteria, modulate bacterial growth by lysis and lysogeny, with the latter being especially prominent in the infant gut. Viral metagenomes (viromes) are difficult to analyse because they span uncharted viral diversity, lacking marker genes and standardized detection methods. Here we systematically resolved the viral diversity in faecal viromes from 647 1-year-olds belonging to Copenhagen Prospective Studies on Asthma in Childhood 2010, an unselected Danish cohort of healthy mother-child pairs. By assembly and curation we uncovered 10,000 viral species from 248 virus family-level clades (VFCs). Most (232 VFCs) were previously unknown, belonging to the Caudoviricetes viral class. Hosts were determined for 79% of phage using clustered regularly interspaced short palindromic repeat spacers within bacterial metagenomes from the same children. Typical Bacteroides-infecting crAssphages were outnumbered by undescribed phage families infecting Clostridiales and Bifidobacterium. Phage lifestyles were conserved at the viral family level, with 33 virulent and 118 temperate phage families. Virulent phages were more abundant, while temperate ones were more prevalent and diverse. Together, the viral families found in this study expand existing phage taxonomy and provide a resource aiding future infant gut virome research.

Potential Auxiliary Metabolic Capabilities and Activities Reveal Biochemical Impacts of Viruses in Municipal Wastewater Treatment Plants

Viruses influence biogeochemical cycles in oceans, freshwater, soil, and human gut through infection and by modulating virocell metabolism through virus-encoded auxiliary metabolic genes (vAMGs). However, the geographical distribution, potential metabolic function, and engineering significance of vAMGs in wastewater treatment plants (WWTPs) remain to be explored. Here, 752 single-contig viral genomes with high confidence, 510 of which belonged to Caudovirales, were recovered from the activated sludge metagenomes of 32 geographically distributed WWTPs. A total of 101 vAMGs involved in various metabolic pathways were identified, the most common of which were the queuosine biosynthesis genes folE, queD, and queE and the sulfur metabolism gene cysH. Phylogenetic analysis and virus-host relationship prediction revealed the probable evolutionary histories of vAMGs involved in carbon (acpP and prsA), nitrogen (amoC), sulfur (cysH), and phosphate (phoH) metabolism, which potentially mediate microbial carbon and nutrient cycling. Notably, 11 of the 38 (28.3%) vAMGs identified in the metagenomes with corresponding metatranscriptomes were transcriptionally expressed, implying an active functional state. This meta-analysis provides the first broad catalog of vAMGs in municipal WWTPs and how they may assist in the basic physiological reactions of their microbial hosts or nutrient cycling in the WWTPs, and therefore, may have important effects on the engineering of wastewater treatment processes.

DeepGeni: deep generalized interpretable autoencoder elucidates gut microbiota for better cancer immunotherapy

Recent studies revealed that gut microbiota modulates the response to cancer immunotherapy and fecal microbiota transplantation has clinical benefits in melanoma patients during treatment. Understanding how microbiota affects individual responses is crucial for precision oncology. However, it is challenging to identify key microbial taxa with limited data as statistical and machine learning models often lose their generalizability. In this study, DeepGeni, a deep generalized interpretable autoencoder, is proposed to improve the generalizability and interpretability of microbiome profiles by augmenting data and by introducing interpretable links in the autoencoder. DeepGeni-based machine learning classifier outperforms state-of-the-art classifier in the microbiome-driven prediction of responsiveness of melanoma patients treated with immune checkpoint inhibitors. Moreover, the interpretable links of DeepGeni elucidate the most informative microbiota associated with cancer immunotherapy response. DeepGeni not only improves microbiome-driven prediction of immune checkpoint inhibitor responsiveness but also suggests potential microbial targets for fecal microbiota transplant or probiotics improving the outcome of cancer immunotherapy.

Enrichment of oral-derived bacteria in inflamed colorectal tumors and distinct associations of Fusobacterium in the mesenchymal subtype

While the association between colorectal cancer (CRC) features and Fusobacterium has been extensively studied, less is known of other intratumoral bacteria. Here, we leverage whole transcriptomes from 807 CRC samples to dually characterize tumor gene expression and 74 intratumoral bacteria. Seventeen of these species, including 4 Fusobacterium spp., are classified as orally derived and are enriched among right-sided, microsatellite instability-high (MSI-H), and BRAF-mutant tumors. Across consensus molecular subtypes (CMSs), integration of Fusobacterium animalis (Fa) presence and tumor expression reveals that Fa has the most significant associations in mesenchymal CMS4 tumors despite a lower prevalence than in immune CMS1. Within CMS4, the prevalence of Fa is uniquely associated with collagen- and immune-related pathways. Additional Fa pangenome analysis reveals that stress response genes and the adhesion FadA are commonly expressed intratumorally. Overall, this study identifies oral-derived bacteria as enriched in inflamed tumors, and the associations of bacteria and tumor expression are context and species specific.

Deduplication Improves Cost-Efficiency and Yields of De Novo Assembly and Binning of Shotgun Metagenomes in Microbiome Research

In the last decade, metagenomics has greatly revolutionized the study of microbial communities. However, the presence of artificial duplicate reads raised mainly from the preparation of metagenomic DNA sequencing libraries and their impacts on metagenomic assembly and binning have never been brought to attention. Here, we explicitly investigated the effects of duplicate reads on metagenomic assemblies and binning based on analyses of five groups of representative metagenomes with distinct microbiome complexities. Our results showed that deduplication considerably increased the binning yields (by 3.5% to 80%) for most of the metagenomic data sets examined thanks to the improved contig length and coverage profiling of metagenome-assembled contigs, whereas it slightly decreased the binning yields of metagenomes with low complexity (e.g., human gut metagenomes). Specifically, 411 versus 397, 331 versus 317, 104 versus 88, and 9 versus 5 metagenome-assembled genomes (MAGs) were recovered from MEGAHIT assemblies of bioreactor sludge, surface water, lake sediment, and forest soil metagenomes, respectively. Noticeably, deduplication significantly reduced the computational costs of the metagenomic assembly, including the elapsed time (9.0% to 29.9%) and the maximum memory requirement (4.3% to 37.1%). Collectively, we recommend the removal of duplicate reads in metagenomes with high complexity before assembly and binning analyses, for example, the forest soil metagenomes examined in this study. IMPORTANCE Duplicated reads in shotgun metagenomes are usually considered technical artifacts. Their presence in metagenomes would theoretically not only introduce bias into the quantitative analysis but also result in mistakes in the coverage profile, leading to adverse effects on or even failures in metagenomic assembly and binning, as the widely used metagenome assemblers and binners all need coverage information for graph partitioning and assembly binning, respectively. However, this issue was seldom noticed, and its impacts on downstream essential bioinformatic procedures (e.g., assembly and binning) remained unclear. In this study, we comprehensively evaluated for the first time the implications of duplicate reads for the de novo assembly and binning of real metagenomic data sets by comparing the assembly qualities, binning yields, and requirements for computational resources with and without the removal of duplicate reads. It was revealed that deduplication considerably increased the binning yields of metagenomes with high complexity and significantly reduced the computational costs, including the elapsed time and the maximum memory requirement, for most of the metagenomes studied. These results provide empirical references for more cost-efficient metagenomic analyses in microbiome research.

Postglacial adaptations enabled colonization and quasi-clonal dispersal of ammonia-oxidizing archaea in modern European large lakes

Ammonia-oxidizing archaea (AOA) play a key role in the aquatic nitrogen cycle. Their genetic diversity is viewed as the outcome of evolutionary processes that shaped ancestral transition from terrestrial to marine habitats. However, current genome-wide insights into AOA evolution rarely consider brackish and freshwater representatives or provide their divergence timeline in lacustrine systems. An unbiased global assessment of lacustrine AOA diversity is critical for understanding their origins, dispersal mechanisms, and ecosystem roles. Here, we leveraged continental-scale metagenomics to document that AOA species diversity in freshwater systems is remarkably low compared to marine environments. We show that the uncultured freshwater AOA, "Candidatus Nitrosopumilus limneticus," is ubiquitous and genotypically static in various large European lakes where it evolved 13 million years ago. We find that extensive proteome remodeling was a key innovation for freshwater colonization of AOA. These findings reveal the genetic diversity and adaptive mechanisms of a keystone species that has survived clonally in lakes for millennia.

Human Gut Microbiota and Its Metabolites Impact Immune Responses in COVID-19 and Its Complications

BACKGROUND & AIMS

We investigate interrelationships between gut microbes, metabolites, and cytokines that characterize COVID-19 and its complications, and we validate the results with follow-up, the Japanese 4D (Disease, Drug, Diet, Daily Life) microbiome cohort, and non-Japanese data sets.

METHODS

We performed shotgun metagenomic sequencing and metabolomics on stools and cytokine measurements on plasma from 112 hospitalized patients with SARS-CoV-2 infection and 112 non-COVID-19 control individuals matched by important confounders.

RESULTS

Multiple correlations were found between COVID-19-related microbes (eg, oral microbes and short-chain fatty acid producers) and gut metabolites (eg, branched-chain and aromatic amino acids, short-chain fatty acids, carbohydrates, neurotransmitters, and vitamin B6). Both were also linked to inflammatory cytokine dynamics (eg, interferon γ, interferon λ3, interleukin 6, CXCL-9, and CXCL-10). Such interrelationships were detected highly in severe disease and pneumonia; moderately in the high D-dimer level, kidney dysfunction, and liver dysfunction groups; but rarely in the diarrhea group. We confirmed concordances of altered metabolites (eg, branched-chain amino acids, spermidine, putrescine, and vitamin B6) in COVID-19 with their corresponding microbial functional genes. Results in microbial and metabolomic alterations with severe disease from the cross-sectional data set were partly concordant with those from the follow-up data set. Microbial signatures for COVID-19 were distinct from diabetes, inflammatory bowel disease, and proton-pump inhibitors but overlapping for rheumatoid arthritis. Random forest classifier models using microbiomes can highly predict COVID-19 and severe disease. The microbial signatures for COVID-19 showed moderate concordance between Hong Kong and Japan.

CONCLUSIONS

Multiomics analysis revealed multiple gut microbe-metabolite-cytokine interrelationships in COVID-19 and COVID-19related complications but few in gastrointestinal complications, suggesting microbiota-mediated immune responses distinct between the organ sites. Our results underscore the existence of a gut-lung axis in COVID-19.

Comprehensive evaluation of shotgun metagenomics, amplicon sequencing, and harmonization of these platforms for epidemiological studies

In a large cohort of 1,772 participants from the Hispanic Community Health Study/Study of Latinos with overlapping 16SV4 rRNA gene (bacterial amplicon), ITS1 (fungal amplicon), and shotgun sequencing data, we demonstrate that 16SV4 amplicon sequencing and shotgun metagenomics offer the same level of taxonomic accuracy for bacteria at the genus level even at shallow sequencing depths. In contrast, for fungal taxa, we did not observe meaningful agreements between shotgun and ITS1 amplicon results. Finally, we show that amplicon and shotgun data can be harmonized and pooled to yield larger microbiome datasets with excellent agreement (<1% effect size variance across three independent outcomes) using pooled amplicon/shotgun data compared to pure shotgun metagenomic analysis. Thus, there are multiple approaches to study the microbiome in epidemiological studies, and we provide a demonstration of a powerful pooling approach that will allow researchers to leverage the massive amount of amplicon sequencing data generated over the last two decades.

proGenomes3: approaching one million accurately and consistently annotated high-quality prokaryotic genomes

The interpretation of genomic, transcriptomic and other microbial 'omics data is highly dependent on the availability of well-annotated genomes. As the number of publicly available microbial genomes continues to increase exponentially, the need for quality control and consistent annotation is becoming critical. We present proGenomes3, a database of 907 388 high-quality genomes containing 4 billion genes that passed stringent criteria and have been consistently annotated using multiple functional and taxonomic databases including mobile genetic elements and biosynthetic gene clusters. proGenomes3 encompasses 41 171 species-level clusters, defined based on universal single copy marker genes, for which pan-genomes and contextual habitat annotations are provided. The database is available at http://progenomes.embl.de/.

Identification of representative species-specific genes for abundance measurements

Motivation

Metagenomic binning facilitates the reconstruction of genomes and identification of Metagenomic Species Pan-genomes or Metagenomic Assembled Genomes. We propose a method for identifying a set of de novo representative genes, termed signature genes, which can be used to measure the relative abundance and used as markers of each metagenomic species with high accuracy.

Results

An initial set of the 100 genes that correlate with the median gene abundance profile of the entity is selected. A variant of the coupon collector's problem was utilized to evaluate the probability of identifying a certain number of unique genes in a sample. This allows us to reject the abundance measurements of strains exhibiting a significantly skewed gene representation. A rank-based negative binomial model is employed to assess the performance of different gene sets across a large set of samples, facilitating identification of an optimal signature gene set for the entity. When benchmarked the method on a synthetic gene catalog, our optimized signature gene sets estimate relative abundance significantly closer to the true relative abundance compared to the starting gene sets extracted from the metagenomic species. The method was able to replicate results from a study with real data and identify around three times as many metagenomic entities.

Availability and implementation

The code used for the analysis is available on GitHub: https://github.com/trinezac/SG_optimization.

Supplementary information

Supplementary data are available at Bioinformatics Advances online.

Interactive Web-Based Services for Metagenomic Data Analysis and Comparisons

Recently, sequencing technologies have become readily available, and scientists are more motivated to conduct metagenomic research to unveil the potential of a myriad of ecosystems and biomes. Metagenomics studies the composition and functions of microbial communities and paves the way to multiple applications in medicine, industry, and ecology. Nonetheless, the immense amount of sequencing data of metagenomics research and the few user-friendly analysis tools and pipelines carry a new challenge to the data analysis.Web-based bioinformatics tools are now being developed to facilitate the analysis of complex metagenomic data without prior knowledge of any programming languages or special installation. Specialized web tools help answer researchers' main questions on the taxonomic classification, functional capabilities, discrepancies between two ecosystems, and the probable functional correlations between the members of a specific microbial community. With an Internet connection and a few clicks, researchers can conveniently and efficiently analyze the metagenomic datasets, summarize results, and visualize key information on the composition and the functional potential of metagenomic samples under study. This chapter provides a simple guide to a few of the fundamental web-based services used for metagenomic data analyses, such as BV-BRC, RDP, MG-RAST, MicrobiomeAnalyst, METAGENassist, and MGnify.