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The standard use of antibiotics in newborns to empirically treat early-onset sepsis can adversely affect the neonatal gut microbiome, with potential long-term health impacts. Research into the escalating issue of antimicrobial resistance in preterm infants and antibiotic practices in neonatal intensive care units is limited. A deeper understanding of the effects of early antibiotic intervention on antibiotic resistance in preterm infants is crucial. This retrospective study employed metagenomic sequencing to evaluate antibiotic resistance genes (ARGs) in the meconium and subsequent stool samples of preterm infants enrolled in the Routine Early Antibiotic Use in Symptomatic Preterm Neonates study. Microbial metagenomics was conducted using a subset of fecal samples from 30 preterm infants for taxonomic profiling and ARG identification. All preterm infants exhibited ARGs, with 175 unique ARGs identified, predominantly associated with beta-lactam, tetracycline, and aminoglycoside resistance. Notably, 23% of ARGs was found in preterm infants without direct or intrapartum antibiotic exposure. Post-natal antibiotic exposure increases beta-lactam/tetracycline resistance while altering mechanisms that aid bacteria in withstanding antibiotic pressure. Microbial profiling revealed 774 bacterial species, with antibiotic-naive infants showing higher alpha diversity ( P = 0.005) in their microbiota and resistome compared with treated infants, suggesting a more complex ecosystem. High ARG prevalence in preterm infants was observed irrespective of direct antibiotic exposure and intensifies with age. Prolonged membrane ruptures and maternal antibiotic use during gestation and delivery are linked to alterations in the preterm infant resistome and microbiome, which are pivotal in shaping the ARG profiles in the neonatal gut.This study is registered with ClinicalTrials.gov as NCT02784821., Importance: A high burden of antibiotic resistance in preterm infants poses significant challenges to neonatal health. The presence of antibiotic resistance genes, along with alterations in signaling, energy production, and metabolic mechanisms, complicates treatment strategies for preterm infants, heightening the risk of ineffective therapy and exacerbating outcomes for these vulnerable neonates. Despite not receiving direct antibiotic treatment, preterm infants exhibit a concerning prevalence of antibiotic-resistant bacteria. This underscores the complex interplay of broader influences, including maternal antibiotic exposure during and beyond pregnancy and gestational complications like prolonged membrane ruptures. Urgent action, including cautious antibiotic practices and enhanced antenatal care, is imperative to protect neonatal health and counter the escalating threat of antimicrobial resistance in this vulnerable population., Competing Interests: The authors declare no conflict of interest.

Escherichia coli, a commensal species of the human gut, is an opportunistic pathogen that can reach extra-intestinal compartments, including the bloodstream and the bladder, among others. In non-immunosuppressed patients, purifying or neutral evolution of E. coli populations has been reported in the gut. Conversely, it has been suggested that when migrating to extra-intestinal compartments, E. coli genomes undergo diversifying selection as supported by strong evidence for adaptation. The level of genomic polymorphism and the size of the populations translocating from gut to extra-intestinal compartments is largely unknown. To gain insights into the pathophysiology of these translocations, we investigated the level of polymorphism and the evolutionary forces acting on the genomes of 77 E. coli isolated from various compartments in three immunosuppressed patients. Each patient had a unique strain, which was a mutator in one case. In all instances, we observed that translocation encompasses much of the genomic diversity present in the gut. The same signature of selection, whether purifying or diversifying, and as anticipated, neutral for mutator isolates, was observed in both the gut and bloodstream. Additionally, we found a limited number of non-specific mutations among compartments for non-mutator isolates. In all cases, urine isolates were dominated by neutral selection. These findings indicate that substantial proportions of populations are undergoing translocation and that they present a complex compartment-specific pattern of selection at the patient level.IMPORTANCEIt has been suggested that intra and extra-intestinal compartments differentially constrain the evolution of E. coli strains. Whether host particular conditions, such as immunosuppression, could affect the strain evolutionary trajectories remains understudied. We found that, in immunosuppressed patients, large fractions of E. coli gut populations are translocating with variable modifications of the signature of selection for commensal and pathogenic isolates according to the compartment and/or the patient. Such multiple site sampling should be performed in large cohorts of patients to gain a better understanding of E. coli extra-intestinal diseases., Competing Interests: The authors declare no conflict of interest.

We have previously demonstrated an association between increased abundance of Phascolarctobacterium and colorectal cancer (CRC) and adenomas in two independent Norwegian cohorts. Here we seek to verify our previous findings using new cohorts and methods. In addition, we characterize lifestyle and sex specificity, the functional potential of the Phascolarctobacterium species, and their interaction with other microbial species. We analyze Phascolarctobacterium with 16S rRNA sequencing, shotgun metagenome sequencing, and species-specific qPCR, using 2350 samples from three Norwegian cohorts-CRCAhus, NORCCAP, and CRCbiome-and a large publicly available data set, curatedMetagenomicData. Using metagenome-assembled genomes from the CRCbiome study, we explore the genomic characteristics and functional potential of the Phascolarctobacterium pangenome. Three species of Phascolarctobacterium associated with adenoma/CRC were consistently detected by qPCR and sequencing. Positive associations with adenomas/CRC were verified for Phascolarctobacterium succinatutens and negative associations were shown for Phascolarctobacterium faecium and adenoma in curatedMetagenomicData. Men show a higher prevalence of P. succinatutens across cohorts. Co-occurrence among Phascolarctobacterium species was low (<6%). Each of the three species shows distinct microbial composition and forms distinct correlation networks with other bacterial taxa, although Dialister invisus was negatively correlated to all investigated Phascolarctobacterium species. Pangenome analyses showed P. succinatutens to be enriched for genes related to porphyrin metabolism and degradation of complex carbohydrates, whereas glycoside hydrolase enzyme 3 was specific to P. faecium .IMPORTANCEUntil now Phascolarctobacterium has been going under the radar as a CRC-associated genus despite having been noted, but overseen, as such for over a decade. We found not just one, but two species of Phascolarctobacterium to be associated with CRC- Phascolarctobacterium succinatutens was more abundant in adenoma/CRC, while Phascolarctobacterium faecium was less abundant in adenoma. Each of them represents distinct communities, constituted by specific microbial partners and metabolic capacities-and they rarely occur together in the same patients. We have verified that P. succinatutens is increased in adenoma and CRC and this species should be recognized among the most important CRC-associated bacteria., Competing Interests: The authors declare no conflict of interest.

This study provides a comprehensive assessment of how urban-rural divides influence gut microbial diversity and composition across the distinct geographical landscapes of Kazakhstan, elucidating the intricate interplay between lifestyle, environment, and gut microbiome. In this prospective cohort study, we enrolled 651 participants from urban centers and rural settlements across Kazakhstan, following ethical approval and informed consent. Comprehensive demographic, dietary, and stool sample data were collected. 16S rRNA gene sequencing and shotgun metagenomics techniques were employed to delineate the intricate patterns of the gut microbiome. A rigorous statistical framework dissected the interplay between urbanization gradients, geography, dietary lifestyles, and microbial dynamics. Our findings demonstrate a stark microbial divide between urban and rural gut ecosystems. The study found significant differences in gut microbiome diversity and composition between urban and rural populations in Kazakhstan. Urban microbiomes exhibited reduced diversity, higher Firmicutes/Bacteroidetes ratios, and increased prevalence of genera Coprococcus and Parasutterella . In contrast, rural populations had greater microbial diversity and abundance of Ligilactobacillus , Sutterella , and Paraprevotella . Urbanization also influenced dietary patterns, with urban areas consuming more salt, cholesterol, and protein, while rural areas had diets richer in carbohydrates and fiber. The study also identified distinct patterns in the prevalence of antibiotic resistance genes and virulence factors between urban and rural gut microbiomes. This study sheds light on how urbanization may be deeply involved in shaping the intricate mosaic of the gut microbiome across Kazakhstan's diverse geographical and dietary landscapes, underscoring the complex interplay between environmental exposures, dietary lifestyles, and the microbial residents inhabiting our intestines., Importance: The study examined gut microbiome composition across diverse geographical locations in Kazakhstan, spanning urban centers and rural settlements. This allows for thoroughly investigating how urbanization gradients and geographic factors shape the gut microbiome. The study's examination of the gut resistome and prevalence of virulence-associated genes provide essential insights into the public health implications of urbanization-driven microbiome alterations. Collecting comprehensive demographic, dietary, and stool sample data enables the researchers to better understand the relationships between urbanization, nutritional patterns, and gut microbiome composition. The findings have important implications for understanding how urbanization-driven microbiome changes may impact human health and well-being, paving the way for tailored interventions to restore a balanced gut microbial ecology., Competing Interests: The authors declare no conflict of interest.

A key challenge in the analysis of microbiome data is the integration of multi-omic datasets and the discovery of interactions between microbial taxa, their expressed genes, and the metabolites they consume and/or produce. In an effort to improve the state of the art in inferring biologically meaningful multi-omic interactions, we sought to address some of the most fundamental issues in causal inference from longitudinal multi-omics microbiome data sets. We developed METALICA, a suite of tools and techniques that can infer interactions between microbiome entities. METALICA introduces novel unrolling and de-confounding techniques used to uncover multi-omic entities that are believed to act as confounders for some of the relationships that may be inferred using standard causal inferencing tools. The results lend support to predictions about biological models and processes by which microbial taxa interact with each other in a microbiome. The unrolling process helps identify putative intermediaries (genes and/or metabolites) to explain the interactions between microbes; the de-confounding process identifies putative common causes that may lead to spurious relationships to be inferred. METALICA was applied to the networks inferred by existing causal discovery, and network inference algorithms were applied to a multi-omics data set resulting from a longitudinal study of IBD microbiomes. The most significant unrollings and de-confoundings were manually validated using the existing literature and databases., Importance: We have developed a suite of tools and techniques capable of inferring interactions between microbiome entities. METALICA introduces novel techniques called unrolling and de-confounding that are employed to uncover multi-omic entities considered to be confounders for some of the relationships that may be inferred using standard causal inferencing tools. To evaluate our method, we conducted tests on the inflammatory bowel disease (IBD) dataset from the iHMP longitudinal study, which we pre-processed in accordance with our previous work. From this dataset, we generated various subsets, encompassing different combinations of metagenomics, metabolomics, and metatranscriptomics datasets. Using these multi-omics datasets, we demonstrate how the unrolling process aids in the identification of putative intermediaries (genes and/or metabolites) to explain the interactions between microbes. Additionally, the de-confounding process identifies potential common causes that may give rise to spurious relationships to be inferred. The most significant unrollings and de-confoundings were manually validated using the existing literature and databases., Competing Interests: The authors declare no conflict of interest.

Host-associated microbiota form complex microbial communities that are increasingly associated with host behavior and disease. While these microbes include bacterial, archaeal, viral, and eukaryotic constituents, most studies have focused on bacteria due to their dominance in the human host and available tools for investigation. Accumulating evidence suggests microbial eukaryotes in the microbiome play pivotal roles in host health, but our understandings of these interactions are limited to a few readily identifiable taxa because of technical limitations in unbiased eukaryote exploration. Here, we combined cell sorting, optimized eukaryotic cell lysis, and shotgun sequencing to accelerate metagenomic discovery and analysis of host-associated microbial eukaryotes. Using synthetic communities with a 1% microbial eukaryote representation, the eukaryote-optimized cell lysis and DNA recovery method alone yielded a 38-fold increase in eukaryotic DNA. Automated sorting of eukaryotic cells from stool samples of healthy adults increased the number of microbial eukaryote reads in metagenomic pools by up to 28-fold compared to commercial kits. Read frequencies for identified fungi increased by 10,000× on average compared to the Human Microbiome Project and allowed for the identification of novel taxa, de novo assembly of contigs from previously unknown microbial eukaryotes, and gene prediction from recovered genomic segments. These advances pave the way for the unbiased inclusion of microbial eukaryotes in deciphering determinants of health and disease in the host-associated microbiome.IMPORTANCEMicrobial eukaryotes are common constituents of the human gut where they can contribute to local ecology and host health, but they are often overlooked in microbiome studies. The lack of attention is due to current technical limitations that are heavily biased or poorly recovered DNA from microbial eukaryotes. We developed a method to increase the representation of these eukaryotes in metagenomic sequencing of microbiome samples that allows to improve their detection compared to prior methods and allows for the identification of new species. Application of the technique to gut microbiome samples improved detection of fungi, protists, and helminths. New eukaryotic taxa and their encoded genes could be identified by sequencing a small number of samples. This approach can improve the inclusion of eukaryotes into microbiome research., Competing Interests: M.Z.A. is a board member of the Native BioData Consortium.

Although antibiotics induce sizable perturbations in the human microbiome, we lack a systematic and quantitative method to measure and predict the microbiome's response to specific antibiotics. Here, we introduce such a method, which takes the form of a microbiome response index (MiRIx) for each antibiotic. Antibiotic-specific MiRIx values quantify the overall susceptibility of the microbiota to an antibiotic, based on databases of bacterial phenotypes and published data on intrinsic antibiotic susceptibility. We applied our approach to five published microbiome studies that carried out antibiotic interventions with vancomycin, metronidazole, ciprofloxacin, amoxicillin, and doxycycline. We show how MiRIx can be used in conjunction with existing microbiome analytical approaches to gain a deeper understanding of the microbiome response to antibiotics. Finally, we generate antibiotic response predictions for the oral, skin, and gut microbiome in healthy humans. Our approach is implemented as open-source software and is readily applied to microbiome data sets generated by 16S rRNA marker gene sequencing or shotgun metagenomics., Importance: Antibiotics are potent influencers of the human microbiome and can be a source for enduring dysbiosis and antibiotic resistance in healthcare. Existing microbiome data analysis methods can quantify perturbations of bacterial communities but cannot evaluate whether the differences are aligned with the expected activity of a specific antibiotic. Here, we present a novel method to quantify and predict antibiotic-specific microbiome changes, implemented in a ready-to-use software package. This has the potential to be a critical tool to broaden our understanding of the relationship between the microbiome and antibiotics., Competing Interests: The authors declare no conflict of interest.

Gut microbe dysbiosis increases repetitive inflammatory responses, leading to an increase in the incidence of colorectal cancer. Recent studies have revealed that specific microbial species directly instigate mutations in the host nucleus DNA, thereby accelerating the progression of colorectal cancer. Given the well-established role of mitochondrial dysfunction in promoting colorectal cancer, it is reasonable to postulate that gut microbes may induce mitochondrial gene mutations, thereby inducing mitochondrial dysfunction. In this review, we focus on gut microbial genotoxins and their known and potential targets in mitochondrial genes. Consequently, we propose that targeted disruption of genotoxin transport pathways may effectively reduce the rate of mitochondrial gene mutations and yield substantial benefits for the prevention of colorectal carcinogenesis., Competing Interests: The authors declare no conflict of interest.

Mexican Americans are disproportionally affected by metabolic dysfunction-associated steatotic liver disease (MASLD), which often co-occurs with diabetes. Despite extensive evidence on the causative role of the gut microbiome in MASLD, studies determining the involvement of the gut phageome are scarce. In this cross-sectional study, we characterized the gut phageome in Mexican Americans of South Texas by stool shotgun metagenomic sequencing of 340 subjects, concurrently screened for liver steatosis by transient elastography. Inter-individual variations in the phageome were associated with gender, country of birth, diabetes, and liver steatosis. The phage signatures for diabetes and liver steatosis were subsequently determined. Enrichment of Inoviridae was associated with both diabetes and liver steatosis. Diabetes was further associated with the enrichment of predominantly temperate Escherichia phages, some of which possessed virulence factors. Liver steatosis was associated with the depletion of Lactococcus phages r1t and BK5-T, and enrichment of the globally prevalent Crassvirales phages, including members of genus cluster IX ( Burzaovirus coli , Burzaovirus faecalis ) and VI ( Kahnovirus oralis ). The Lactococcus phages showed strong correlations and co-occurrence with Lactococcus lactis , while the Crassvirales phages, B. coli , B. faecalis , and UAG-readthrough crAss clade correlated and co-occurred with Prevotella copri . In conclusion, we identified the gut phageome signatures for two closely linked metabolic diseases with significant global burden. These phage signatures may have utility in risk modeling and disease prevention in this high-risk population, and identification of potential bacterial targets for phage therapy.IMPORTANCEPhages influence human health and disease by shaping the gut bacterial community. Using stool samples from a high-risk Mexican American population, we provide insights into the gut phageome changes associated with diabetes and liver steatosis, two closely linked metabolic diseases with significant global burden. Common to both diseases was an enrichment of Inoviridae , a group of phages that infect bacterial hosts chronically without lysis, allowing them to significantly influence bacterial growth, virulence, motility, biofilm formation, and horizontal gene transfer. Diabetes was additionally associated with the enrichment of Escherichia coli -infecting phages, some of which contained virulence factors. Liver steatosis was additionally associated with the depletion of Lactococcus lactis -infecting phages, and enrichment of Crassvirales phages, a group of virulent phages with high global prevalence and persistence across generations. These phageome signatures may have utility in risk modeling, as well as identify potential bacterial targets for phage therapy., Competing Interests: The authors declare no conflict of interest.

The widespread sulfonamide resistance genes sul1 , sul2 , and sul3 in food and gut bacteria have attracted considerable attention. In this study, we assessed the in vivo fitness of sul gene-dependent sulfonamide-resistant Escherichia coli , using a murine model. High fitness costs were incurred for sul1 and sul3 gene-dependent E. coli strains in vivo . A fitness advantage was found in three of the eight mice after intragastric administration of sul2 gene-dependent E. coli strains. We isolated three compensatory mutant strains (CMSs) independently from three mice that outcompeted the parent strain P2 in vivo . Whole-genome sequencing revealed seven identical single nucleotide polymorphism (SNP) mutations in the three CMSs compared with strain P2, an additional SNP mutation in strain S2-2, and two additional SNP mutations in strain S2-3. Furthermore, tandem mass tag-based quantitative proteomic analysis revealed abundant differentially expressed proteins (DEPs) in the CMSs compared with P2. Of these, seven key fitness-related DEPs distributed in two-component systems, galactose and tryptophan metabolism pathways, were verified using parallel reaction monitoring analysis. The DEPs in the CMSs influenced bacterial motility, environmental stress tolerance, colonization ability, carbohydrate utilization, cell morphology maintenance, and chemotaxis to restore fitness costs and adapt to the mammalian gut environment.IMPORTANCESulfonamides are traditional synthetic antimicrobial agents used in clinical and veterinary medical settings. Their long-term excessive overuse has resulted in widespread microbial resistance, limiting their application for medical interventions. Resistance to sulfonamides is primarily conferred by the alternative genes sul1 , sul2 , and sul3 encoding dihydropteroate synthase in bacteria. Studying the potential fitness cost of these sul genes is crucial for understanding the evolution and transmission of sulfonamide-resistant bacteria. In vitro studies have been conducted on the fitness cost of sul genes in bacteria. In this study, we provide critical insights into bacterial adaptation and transmission using an in vivo approach., Competing Interests: The authors declare no conflict of interest.

Mechanistic understanding of interactions in many host-microbe systems, including the honey bee microbiome, is limited by a lack of easy-to-use genome engineering approaches. To this end, we demonstrate a one-step genome engineering approach for making gene deletions and insertions in the chromosomes of honey bee gut bacterial symbionts. Electroporation of linear or non-replicating plasmid DNA containing an antibiotic resistance cassette flanked by regions with homology to a symbiont genome reliably results in chromosomal integration. This lightweight approach does not require expressing any exogenous recombination machinery. The high concentrations of large DNAs with long homology regions needed to make the process efficient can be readily produced using modern DNA synthesis and assembly methods. We use this approach to knock out genes, including genes involved in biofilm formation, and insert fluorescent protein genes into the chromosome of the betaproteobacterial bee gut symbiont Snodgrassella alvi . We are also able to engineer the genomes of multiple strains of S. alvi and another species, Snodgrassella communis , which is found in the bumble bee gut microbiome. Finally, we use the same method to engineer the chromosome of another bee symbiont, Bartonella apis , which is an alphaproteobacterium. As expected, gene knockout in S. alvi using this approach is recA -dependent, suggesting that this straightforward procedure can be applied to other microbes that lack convenient genome engineering methods., Importance: Honey bees are ecologically and economically important crop pollinators with bacterial gut symbionts that influence their health. Microbiome-based strategies for studying or improving bee health have utilized wild-type or plasmid-engineered bacteria. We demonstrate that a straightforward, single-step method can be used to insert cassettes and replace genes in the chromosomes of multiple bee gut bacteria. This method can be used for investigating the mechanisms of host-microbe interactions in the bee gut community and stably engineering symbionts that benefit pollinator health., Competing Interests: S.P.L., J.E.B., and N.A.M. have a patent (US11382989B2) on the use of engineered symbionts to improve bee health.

Microbiome studies have revealed gut microbiota's potential impact on complex diseases. However, many studies often focus on one disease per cohort. We developed a meta-analysis workflow for gut microbiome profiles and analyzed shotgun metagenomic data covering 11 diseases. Using interpretable machine learning and differential abundance analysis, our findings reinforce the generalization of binary classifiers for Crohn's disease (CD) and colorectal cancer (CRC) to hold-out cohorts and highlight the key microbes driving these classifications. We identified high microbial similarity in disease pairs like CD vs ulcerative colitis (UC), CD vs CRC, Parkinson's disease vs type 2 diabetes (T2D), and schizophrenia vs T2D. We also found strong inverse correlations in Alzheimer's disease vs CD and UC. These findings, detected by our pipeline, provide valuable insights into these diseases., Importance: Assessing disease similarity is an essential initial step preceding a disease-based approach for drug repositioning. Our study provides a modest first step in underscoring the potential of integrating microbiome insights into the disease similarity assessment. Recent microbiome research has predominantly focused on analyzing individual diseases to understand their unique characteristics, which by design excludes comorbidities in individuals. We analyzed shotgun metagenomic data from existing studies and identified previously unknown similarities between diseases. Our research represents a pioneering effort that utilizes both interpretable machine learning and differential abundance analysis to assess microbial similarity between diseases., Competing Interests: The authors declare no conflict of interest.

Shotgun metagenomics allows comprehensive sampling of the genomic information of microbes in a given environment and is a tool of choice for studying complex microbial systems. Mapping sequencing reads against a set of reference or metagenome-assembled genomes is in principle a simple and powerful approach to define the species-level composition of the microbial community under investigation. However, despite the widespread use of this approach, there is no established way to properly interpret the alignment results, with arbitrary relative abundance thresholds being routinely used to discriminate between present and absent species. Such an approach can be affected by significant biases, especially in the identification of rare species. Therefore, it is important to develop new metrics to overcome these biases. Here, we present Metapresence, a new tool to perform reliable identification of the species in metagenomic samples based on the distribution of mapped reads on the reference genomes. The analysis is based on two metrics describing the breadth of coverage and the genomic distance between consecutive reads. We demonstrate the high precision and wide applicability of the tool using data from various synthetic communities, a real mock community, and the gut microbiome of healthy individuals and antibiotic-associated-diarrhea patients. Overall, our results suggest that the proposed approach has a robust performance in hard-to-analyze microbial communities containing contaminated or closely related genomes in low abundance.IMPORTANCEDespite the prevalent use of genome-centric alignment-based methods to characterize microbial community composition, there lacks a standardized approach for accurately identifying the species within a sample. Currently, arbitrary relative abundance thresholds are commonly employed for this purpose. However, due to the inherent complexity of genome structure and biases associated with genome-centric approaches, this practice tends to be imprecise. Notably, it introduces significant biases, particularly in the identification of rare species. The method presented here addresses these limitations and contributes significantly to overcoming inaccuracies in precisely defining community composition, especially when dealing with rare members., Competing Interests: The authors declare no conflict of interest.

Clostridia are abundant in the human gut and comprise families associated with host health such as Oscillospiraceae, which has been correlated with leanness. However, culturing bacteria within this family is challenging, leading to their detection primarily through 16S rRNA amplicon sequencing, which has a limited ability to unravel diversity at low taxonomic levels, or by shotgun metagenomics, which is hindered by its high costs and complexity. In this cross-sectional study involving 114 Colombian adults, we used an amplicon-based sequencing strategy with alternative markers-gyrase subunit B ( gyrB ) and DNA K chaperone heat protein 70 ( dnaK )-that evolve faster than the 16S rRNA gene. Comparing the diversity and abundance observed with the three markers in our cohort, we found a reduction in the diversity of Clostridia , particularly within Lachnospiraceae and Oscillospiraceae among obese individuals [as measured by the body mass index (BMI)]. Within Lachnospiraceae , the diversity of Ruminococcus&#95;A negatively correlated with BMI. Within Oscillospiraceae , the genera CAG-170 and Vescimonas also exhibited this negative correlation. In addition, the abundance of Vescimonas was negatively correlated with BMI. Leveraging shotgun metagenomic data, we conducted a phylogenetic and genomic characterization of 120 metagenome-assembled genomes from Vescimonas obtained from a larger sample of the same cohort. We identified 17 of the 72 reported species. The functional annotation of these genomes showed the presence of multiple carbohydrate-active enzymes, particularly glycosyl transferases and glycoside hydrolases, suggesting potential beneficial roles in fiber degradation, carbohydrate metabolism, and butyrate production., Importance: The gut microbiota is diverse across various taxonomic levels. At the intra-species level, it comprises multiple strains, some of which may be host-specific. However, our understanding of fine-grained diversity has been hindered by the use of the conserved 16S rRNA gene. While shotgun metagenomics offers higher resolution, it remains costly, may fail to identify specific microbes in complex samples, and requires extensive computational resources and expertise. To address this, we employed a simple and cost-effective analysis of alternative genetic markers to explore diversity within Clostridia , a crucial group within the human gut microbiota whose diversity may be underestimated. We found high intra-species diversity for certain groups and associations with obesity. Notably, we identified Vescimonas , an understudied group. Making use of metagenomic data, we inferred functionality, uncovering potential beneficial roles in dietary fiber and carbohydrate degradation, as well as in short-chain fatty acid production., Competing Interests: While engaged in this project, L.S.-J. and J.S.E. were employed by a research center belonging to a food company (Grupo Empresarial Nutresa), and M.C. received economic support from the same research center. J.D.L.C.-Z., L.A.C., R.E.L., and A.R. had no conflict of interest. This work was funded by Grupo Empresarial Nutresa, Universidad de los Andes, and Max Planck Institute. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript; or in the decision to publish the results.

The gut microbiome has the potential to buffer temporal variations in resource availability and consumption, which may play a key role in the ability of animals to adapt to a broad range of habitats. We investigated the temporal composition and function of the gut microbiomes of wild common marmosets ( Callithrix jacchus ) exploiting a hot, dry environment-Caatinga-in northeastern Brazil. We collected fecal samples during two time periods (July-August and February-March) for 2 years from marmosets belonging to eight social groups. We used 16S rRNA gene amplicon sequencing, metagenomic sequencing, and butyrate RT-qPCR to assess changes in the composition and potential function of their gut microbiomes. Additionally, we identified the plant, invertebrate, and vertebrate components of the marmosets' diet via DNA metabarcoding. Invertebrate, but not plant or vertebrate, consumption varied across the year. However, gut microbiome composition and potential function did not markedly vary across study periods or as a function of diet composition. Instead, the gut microbiome differed markedly in both composition and potential function across marmosets residing in different social groups. We highlight the likely role of factors, such as behavior, residence, and environmental heterogeneity, in modulating the structure of the gut microbiome., Importance: In a highly socially cohesive and cooperative primate, group membership more strongly predicts gut microbiome composition and function than diet., Competing Interests: The authors declare no conflict of interest.

Characterizing microbial communities at high resolution and with absolute quantification is crucial to unravel the complexity and diversity of microbial ecosystems. This can be achieved with PCR assays, which enable highly selective detection and absolute quantification of microbial DNA. However, a major challenge that has hindered PCR applications in microbiome research is the design of highly specific primer sets that exclusively amplify intended targets. Here, we introduce Phylogenetically Unique Primers in python (PUPpy), a fully automated pipeline to design microbe- and group-specific primers within a given microbial community. PUPpy can be executed from a user-friendly graphical user interface, or two simple terminal commands, and it only requires coding sequence files of the community members as input. PUPpy-designed primers enable the detection of individual microbes and quantification of absolute microbial abundance in defined communities below the strain level. We experimentally evaluated the performance of PUPpy-designed primers using two bacterial communities as benchmarks. Each community comprises 10 members, exhibiting a range of genetic similarities that spanned from different phyla to substrains. PUPpy-designed primers also enable the detection of groups of bacteria in an undefined community, such as the detection of a gut bacterial family in a complex stool microbiota sample. Taxon-specific primers designed with PUPpy showed 100% specificity to their intended targets, without unintended amplification, in each community tested. Lastly, we show the absolute quantification of microbial abundance using PUPpy-designed primers in droplet digital PCR, benchmarked against 16S rRNA and shotgun sequencing. Our data shows that PUPpy-designed microbe-specific primers can be used to quantify substrain-level absolute counts, providing more resolved and accurate quantification in defined communities than short-read 16S rRNA and shotgun sequencing., Importance: Profiling microbial communities at high resolution and with absolute quantification is essential to uncover hidden ecological interactions within microbial ecosystems. Nevertheless, achieving resolved and quantitative investigations has been elusive due to methodological limitations in distinguishing and quantifying highly related microbes. Here, we describe Phylogenetically Unique Primers in python (PUPpy), an automated computational pipeline to design taxon-specific primers within defined microbial communities. Taxon-specific primers can be used to selectively detect and quantify individual microbes and larger taxa within a microbial community. PUPpy achieves substrain-level specificity without the need for computationally intensive databases and prioritizes user-friendliness by enabling both terminal and graphical user interface applications. Altogether, PUPpy enables fast, inexpensive, and highly accurate perspectives into microbial ecosystems, supporting the characterization of bacterial communities in both in vitro and complex microbiota settings., Competing Interests: The authors declare no conflict of interest.

Gut microbiota of the bumblebee is critical as it modulates the health and fitness of the host. However, the mechanisms underlying the formation and maintenance of the diversity of bumblebee gut bacteria over a long period of evolution have yet to be elucidated. In particular, the gut bacterial diversity and community assembly processes of Bombus pyrosoma across the Chinese border remain unclear. In this study, we systematically carried out unprecedented sampling of 513 workers of the species Bombus pyrosoma across the Chinese landscape and used full-length 16S rRNA gene sequencing to examine their gut microbiota diversity and biogeography. The gut microbiota composition and community structure of Bombus pyrosoma from different geographical locations were diverse. On the whole, the gut bacteria Gilliamella and Snodgrassella are dominant in bumblebees, but opportunistic pathogens Serratia and Pseudomonas are dominant in some sampling sites such as Hb15, Gs1, Gs45, Qhs15, and Ssx35. All or part of environmental factors such as latitude, annual mean temperature, elevation, human footprint, population density, and annual precipitation can affect the alpha diversity and community structure of gut bacteria. Further analysis showed that the assembly and shift of bumblebee gut bacterial communities under geographical variation were mainly driven by the stochastic drift of the neutral process rather than by variable selection of niche differentiation. In conclusion, our unprecedented sampling uncovers bumblebee gut microbiome diversity and shifts over evolutionary time., Importance: The microbiotas associated with organisms facilitates host health and fitness, and the homeostasis status of gut microbiota also reflects the habitat security faced by the host. In addition, managing gut microbiota is important to improve bumblebee health by understanding the ecological process of the gut microbiome. Thus, we first carried out an runprecedented sampling of 513 workers of the species Bombus pyrosoma across the Chinese landscape and used full-length 16S rRNA gene sequencing to uncover their gut microbiota diversity and biogeography. Our study provides new insights into the understanding of gut microbiome diversity and shifts for Chinese Bumblebee over evolutionary time., Competing Interests: The authors declare no conflict of interest.

Bacteroides fragilis is a Gram-negative commensal bacterium commonly found in the human colon, which differentiates into two genomospecies termed divisions I and II. Through a comprehensive collection of 694 B. fragilis whole genome sequences, we identify novel features distinguishing these divisions. Our study reveals a distinct geographic distribution with division I strains predominantly found in North America and division II strains in Asia. Additionally, division II strains are more frequently associated with bloodstream infections, suggesting a distinct pathogenic potential. We report differences between the two divisions in gene abundance related to metabolism, virulence, stress response, and colonization strategies. Notably, division II strains harbor more antimicrobial resistance (AMR) genes than division I strains. These findings offer new insights into the functional roles of division I and II strains, indicating specialized niches within the intestine and potential pathogenic roles in extraintestinal sites., Importance: Understanding the distinct functions of microbial species in the gut microbiome is crucial for deciphering their impact on human health. Classifying division II strains as Bacteroides fragilis can lead to erroneous associations, as researchers may mistakenly attribute characteristics observed in division II strains to the more extensively studied division I B. fragilis . Our findings underscore the necessity of recognizing these divisions as separate species with distinct functions. We unveil new findings of differential gene prevalence between division I and II strains in genes associated with intestinal colonization and survival strategies, potentially influencing their role as gut commensals and their pathogenicity in extraintestinal sites. Despite the significant niche overlap and colonization patterns between these groups, our study highlights the complex dynamics that govern strain distribution and behavior, emphasizing the need for a nuanced understanding of these microorganisms., Competing Interests: The authors declare a conflict of interest.

The gastric microbial community plays a fundamental role in gastric cancer (GC), and the two main anatomical subtypes of GC, non-cardia and cardia GC, are associated with different risk factors ( Helicobacter pylori for non-cardia GC). To decipher the different microbial spatial communities of GC, we performed a multicenter retrospective analysis to characterize the gastric microbiota in 223 GC patients, including H. pylori -positive or -negative patients, with tumors and paired adjacent normal tissues, using third-generation sequencing. In the independent validation cohort, both dental plaque and GC tumoral tissue samples were collected and sequenced. The prevalence of H. pylori and oral-associated bacteria was verified using fluorescence in situ hybridization (FISH) assays in GC tumoral tissues and matched nontumoral tissues. We found that the vertical distribution of the gastric microbiota, at the upper, middle, and lower third sites of GC, was likely an important factor causing microbial diversity in GC tumor tissues. The oral-associated microbiota cluster, which included Veillonella parvula , Streptococcus oralis , and Prevotella intermedia , was more abundant in the upper third of the GC. However, H. pylori was more abundant in the lower third of the GC and exhibited a significantly high degree of microbial correlation. The oral-associated microbiota module was co-exclusive with H. pylori in the lower third site of the GC tumoral tissue. Importantly, H. pylori -negative GC patients with oral-associated gastric microbiota showed worse overall survival, while the increase in microbial abundance in H. pylori -positive GC patients showed no difference in overall survival. The prevalence of V. parvula in both the dental plaque and GC tissue samples was concordant in the independent validation phase. We showed that the oral-associated species V. parvula and S. oralis were correlated with overall survival. Our study highlights the roles of the oral-associated microbiota in the upper third of the GC. In addition, oral-associated species may serve as noninvasive screening tools for the management of GC and an independent prognostic factor for H. pylori -negative GCs., Importance: Our study highlights the roles of the oral-associated microbiota in the upper third of gastric cancer (GC).We showed that the oral-associated species Veillonella parvula and Streptococcus oralis were correlated with overall survival. In addition, oral-associated species may serve as noninvasive screening tools for the management of GC and an independent prognostic factor for Helicobacter pylori -negative GCs., Competing Interests: The authors declare no conflict of interest.

Some lactic acid bacteria (LAB) can provide significant health benefits, which are critically important for the conservation of endangered animals, such as giant pandas. However, little is known about the diversity and culturability of LAB in the giant panda gut microbiota. To understand the roles of LAB in giant panda conservation, it is critical to culture bacterial strains of interest. In this study, we established a pipeline to culture bacterial strains using enrichment of target bacteria with different liquid media and growth conditions. Then, the strains were isolated in solid media to study their functions. Using 210 samples from the culture enrichment method and 138 culture-independent samples, we obtained 1120 amplicon sequencing variants (ASVs) belonging to Lactobacillales . Out of the 1120 ASVs, 812 ASVs from the culture enrichment approach were twofold more diverse than 336 ASVs from the culture-independent approach. Many ASVs of interest were not detected in the culture-independent approach. Using this pipeline, we isolated many relevant bacterial strains and established a giant panda gut bacteria strain collection that included strains with low-abundance in culture-independent samples and included most of the giant panda LAB described by other researchers. The strain collection consisted of 60 strains representing 35 species of 12 genera. Thus, our pipeline is powerful and provides guidance in culturing gut microbiota of interest in hosts such as the giant panda.IMPORTANCECultivation is necessary to screen strains to experimentally investigate microbial traits, and to confirm the activities of novel genes through functional characterization studies. In the long-term, such work can aid in the identification of potential health benefits conferred by bacteria and this could aid in the identification of bacterial candidate strains that can be applied as probiotics. In this study, we developed a pipeline with low-cost and user-friendly culture enrichment to reveal the diversity of LAB in giant pandas. We compared the difference between culture-independent and culture enrichment methods, screened strains of interest that produced high concentrations of short-chain fatty acids (SCFAs), and we investigated the catalog of virulence factors, antibiotic resistance, butyrate and lactate synthesis genes of the strains at a genomic level. This study will provide guidance for microbiota cultivation and a foundation for future research aiming to understand the functions of specific strains., Competing Interests: The authors declare no conflict of interest.

Current microbiome signatures for chronic diseases such as diabetic kidney disease (DKD) are mainly based on low-resolution taxa such as genus or phyla and are often inconsistent among studies. In microbial ecosystems, bacterial functions are strain specific, and taxonomically different bacteria tend to form co-abundance functional groups called guilds. Here, we identified guild-level signatures for DKD by performing in-depth metagenomic sequencing and conducting genome-centric and guild-based analysis on fecal samples from 116 DKD patients and 91 healthy subjects. Redundancy analysis on 1,543 high-quality metagenome-assembled genomes (HQMAGs) identified 54 HQMAGs that were differentially distributed among the young healthy control group, elderly healthy control group, early-stage DKD patients (EDG), and late-stage DKD patients (LDG). Co-abundance network analysis classified the 54 HQMAGs into two guilds. Compared to guild 2, guild 1 contained more short-chain fatty acid biosynthesis genes and fewer genes encoding uremic toxin indole biosynthesis, antibiotic resistance, and virulence factors. Guild indices, derived from the total abundance of guild members and their diversity, delineated DKD patients from healthy subjects and between different severities of DKD. Age-adjusted partial Spearman correlation analysis showed that the guild indices were correlated with DKD disease progression and with risk indicators of poor prognosis. We further validated that the random forest classification model established with the 54 HQMAGs was also applicable for classifying patients with end-stage renal disease and healthy subjects in an independent data set. Therefore, this genome-level, guild-based microbial analysis strategy may identify DKD patients with different severity at an earlier stage to guide clinical interventions., Importance: Traditionally, microbiome research has been constrained by the reliance on taxonomic classifications that may not reflect the functional dynamics or the ecological interactions within microbial communities. By transcending these limitations with a genome-centric and guild-based analysis, our study sheds light on the intricate and specific interactions between microbial strains and diabetic kidney disease (DKD). We have unveiled two distinct microbial guilds with opposite influences on host health, which may redefine our understanding of microbial contributions to disease progression. The implications of our findings extend beyond mere association, providing potential pathways for intervention and opening new avenues for patient stratification in clinical settings. This work paves the way for a paradigm shift in microbiome research in DKD and potentially other chronic kidney diseases, from a focus on taxonomy to a more nuanced view of microbial ecology and function that is more closely aligned with clinical outcomes., Competing Interests: L.Z. is a co-founder of Notitia Biotechnologies Company.

Environmental enteric dysfunction (EED) is a subclinical syndrome of altered small intestinal function postulated to be an important contributor to childhood undernutrition. The role of small intestinal bacterial communities in the pathophysiology of EED is poorly defined due to a paucity of studies where there has been a direct collection of small intestinal samples from undernourished children. Sixty-three members of a Pakistani cohort identified as being acutely malnourished between 3 and 6 months of age and whose wasting (weight-for-length Z -score [WLZ]) failed to improve after a 2-month nutritional intervention underwent esophagogastroduodenoscopy (EGD). Paired duodenal luminal aspirates and duodenal mucosal biopsies were obtained from 43 children. Duodenal microbiota composition was characterized by sequencing bacterial 16S rRNA gene amplicons. Levels of bacterial taxa (amplicon sequence variants [ASVs]) were referenced to anthropometric indices, histopathologic severity in biopsies, expression of selected genes in the duodenal mucosa, and fecal levels of an immunoinflammatory biomarker (lipocalin-2). A "core" group of eight bacterial ASVs was present in the duodenal samples of 69% of participants. Streptococcus anginosus was the most prevalent, followed by Streptococcus sp., Gemella haemolysans , Streptococcus australis , Granulicatella elegans , Granulicatella adiacens, and Abiotrophia defectiva . At the time of EGD, none of the core taxa were significantly correlated with WLZ. Statistically significant correlations were documented between the abundances of Granulicatella elegans and Granulicatella adiacens and the expression of duodenal mucosal genes involved in immune responses (dual oxidase maturation factor 2, serum amyloid A, and granzyme H). These results suggest that a potential role for members of the oral microbiota in pathogenesis, notably Streptococcus , Gemella, and Granulicatella species, warrants further investigation.IMPORTANCEUndernutrition among women and children is a pressing global health problem. Environmental enteric dysfunction (EED) is a disease of the small intestine (SI) associated with impaired gut mucosal barrier function and reduced capacity for nutrient absorption. The cause of EED is ill-defined. One emerging hypothesis is that alterations in the SI microbiota contribute to EED. We performed a culture-independent analysis of the SI microbiota of a cohort of Pakistani children with undernutrition who had failed a standard nutritional intervention, underwent upper gastrointestinal tract endoscopy, and had histologic evidence of EED in their duodenal mucosal biopsies. The results revealed a shared group of bacterial taxa in their duodenums whose absolute abundances were correlated with levels of the expression of genes in the duodenal mucosa that are involved in inflammatory responses. A number of these bacterial taxa are more typically found in the oral microbiota, a finding that has potential physiologic and therapeutic implications., Competing Interests: The authors declare no conflict of interest.

Escherichia coli ( E. coli ) is reported to be an important pathogen associated with calf diarrhea. Antibiotic resistance genes (ARGs) and virulence factor genes (VFGs) pose a considerable threat to both animal and human health. However, little is known about the characterization of ARGs and VFGs presented in the gut microbiota of diarrheic calves caused by E. coli . In this study, we used multi-omics strategy to analyze the ARG and VFG profiles of Simmental calves with diarrhea caused by E. coli K99. We found that gut bacterial composition and their microbiome metabolic functions varied greatly in diarrheic calves compared to healthy calves. In total, 175 ARGs were identified, and diarrheal calves showed a significantly higher diversity and abundance of ARGs than healthy calves. Simmental calves with diarrhea showed higher association of VFGs with pili function, curli assembly, and ferrienterobactin transport of E. coli . Co-occurrence patterns based on Pearson correlation analysis revealed that E. coli had a highly significant ( P < 0.0001) correlation coefficient (>0.8) with 16 ARGs and 7 VFGs. Metabolomics analysis showed that differentially expressed metabolites in Simmental calves with diarrhea displayed a high correlation with the aforementioned ARGs and VFGs. Phylotype analysis of E. coli genomes showed that the predominant phylogroup B1 in diarrheic Simmental calves was associated with 10 ARGs and 3 VFGs. These findings provide an overview of the diversity and abundance of the gut microbiota in diarrheic calves caused by E. coli and pave the way for further studies on the mechanisms of antibiotic resistance and virulence in the calves affected with diarrhea.IMPORTANCESimmental is a well-recognized beef cattle breed worldwide. They also suffer significant economic losses due to diarrhea. In this study, fecal metagenomic analysis was applied to characterize the antibiotic resistance gene (ARG) and virulence factor gene (VFG) profiles of diarrheic Simmental calves. We identified key ARGs and VFGs correlated with Escherichia coli isolated from Simmental calves. Additionally, metabolomics analysis showed that differentially expressed metabolites in Simmental calves with diarrhea displayed a high correlation with the aforementioned ARGs and VFGs. Our findings provide an insight into the diversity and abundance of the gut microbiota in diarrheic calves caused by Escherichia coli and pave the way for further studies on the mechanisms of antibiotic resistance and virulence in the diarrheal calves from cattle hosts., Competing Interests: The authors declare no conflict of interest.

The gut microbiome affects the health status of the host through complex interactions with the host's intestinal wall. These host-microbiome interactions may spatially vary along the physical and chemical environment of the intestine, but these changes remain unknown. This study investigated these intricate relationships through a gene co-expression network analysis based on dual transcriptome profiling of different intestinal sites-cecum, transverse colon, and rectum-of the primate common marmoset. We proposed a gene module extraction algorithm based on the graph theory to find tightly interacting gene modules of the host and the microbiome from a vast co-expression network. The 27 gene modules identified by this method, which include both host and microbiome genes, not only produced results consistent with previous studies regarding the host-microbiome relationships, but also provided new insights into microbiome genes acting as potential mediators in host-microbiome interplays. Specifically, we discovered associations between the host gene FBP1 , a cancer marker, and polysaccharide degradation-related genes ( pfkA and fucI ) coded by Bacteroides vulgatus , as well as relationships between host B cell-specific genes ( CD19 , CD22 , CD79B , and PTPN6 ) and a tryptophan synthesis gene ( trpB ) coded by Parabacteroides distasonis . Furthermore, our proposed module extraction algorithm surpassed existing approaches by successfully defining more functionally related gene modules, providing insights for understanding the complex relationship between the host and the microbiome.IMPORTANCEWe unveiled the intricate dynamics of the host-microbiome interactions along the colon by identifying closely interacting gene modules from a vast gene co-expression network, constructed based on simultaneous profiling of both host and microbiome transcriptomes. Our proposed gene module extraction algorithm, designed to interpret inter-species interactions, enabled the identification of functionally related gene modules encompassing both host and microbiome genes, which was challenging with conventional modularity maximization algorithms. Through these identified gene modules, we discerned previously unrecognized bacterial genes that potentially mediate in known relationships between host genes and specific bacterial species. Our findings underscore the spatial variations in host-microbiome interactions along the colon, rather than displaying a uniform pattern throughout the colon., Competing Interests: The authors declare no conflict of interest.

Preeclampsia (PE), a pregnancy-specific syndrome, has been associated with the gut bacteriome. Here, to investigate the impact of the gut virome on the development of PE, we identified over 8,000 nonredundant viruses from the fecal metagenomes of 40 early-onset PE and 37 healthy pregnant women and profiled their abundances. Comparison and correlation analysis showed that PE-enriched viruses frequently connected to Blautia species enriched in PE. By contrast, bacteria linked to PE-depleted viruses were often the Bacteroidaceae members such as Bacteroides spp., Phocaeicola spp., Parabacteroides spp., and Alistipes shahii . In terms of viral function, PE-depleted viruses had auxiliary metabolic genes that participated in the metabolism of simple and complex polysaccharides, sulfur metabolism, lipopolysaccharide biosynthesis, and peptidoglycan biosynthesis, while PE-enriched viruses had a gene encoding cyclic pyranopterin monophosphate synthase, which seemed to be special, that participates in the biosynthesis of the molybdenum cofactor. Furthermore, the classification model based on gut viral signatures was developed to discriminate PE patients from healthy controls and showed an area under the receiver operating characteristic curve of 0.922 that was better than that of the bacterium-based model. This study opens up new avenues for further research, providing valuable insights into the PE gut virome and offering potential directions for future mechanistic and therapeutic investigations, with the ultimate goal of improving the diagnosis and management of PE.IMPORTANCEThe importance of this study lies in its exploration of the previously overlooked but potentially critical role of the gut virome in preeclampsia (PE). While the association between PE and the gut bacteriome has been recognized, this research takes a pioneering step into understanding how the gut virome, represented by over 8,000 nonredundant viruses, contributes to this condition. The findings reveal intriguing connections between PE-enriched viruses and specific gut bacteria, such as the prevalence of Blautia species in individuals with PE, contrasting with bacteria linked to PE-depleted viruses, including members of the Bacteroidaceae family. These viral interactions and associations provide a deeper understanding of the complex dynamics at play in PE., Competing Interests: The authors declare no conflict of interest.

The human gut microbiota is a dynamic community of microorganisms that undergo variable changes over the entire life span. To thoroughly investigate the possible fluctuations of the microbiota throughout human life, we performed a pooled analysis of healthy fecal samples across different age groups covering the entire human life span. Our study integrated data from 79 publicly available studies and new stool samples from an Italian cohort, i.e., the Parma Microbiota project, resulting in 6,653 samples processed through the shotgun metagenomic approach. This approach has allowed species-level taxonomic reconstruction of the gut microbiota and investigation of its metabolic potential across the human life span. From a taxonomic point of view, our findings confirmed and detailed at species-level accuracy that the microbial richness of the gut microbiota gradually increases in the first stage of life, becoming relatively stable during adolescence. Moreover, the analysis identified the potential core microbiota representative of distinct age groups, revealing age-related bacterial patterns and the continuous rearrangement of the microbiota in terms of relative abundances across the life span rather than the acquisition and loss of taxa. Furthermore, the shotgun approach provided insights into the functional contribution of the human gut microbiome. The metagenomic analysis revealed functional age-related differences, particularly in carbohydrate and fiber metabolism, suggesting a co-evolution of the microbiome assembly with diet. Additionally, we identified correlations between vitamin synthesis, such as thiamine and niacin, and early life, suggesting a potential role of the microbiome in human physiology, in particular in the functions of the host's nervous and immune systems., Importance: In this study, we provided comprehensive insights into the dynamic nature of the human gut microbiota across the human life span. In detail, we analyzed a large data set based on a shotgun metagenomic approach, combining public data sets and new samples from the Parma Microbiota project and obtaining a detailed overview of the possible relationship between gut microbiota development and aging. Our findings confirmed the main stages in microbial richness development and revealed specific core microbiota associated with different age stages. Moreover, the shotgun metagenomic approach allowed the disentangling of the functional changes in the microbiome across the human life span, particularly in diet-related metabolism, which is probably correlated to bacterial co-evolution with dietary habits. Notably, our study also uncovered positive correlations with vitamin synthesis in early life, suggesting a possible impact of the microbiota on human physiology., Competing Interests: The authors declare no conflict of interest.

Increasing levels of industrialization have been associated with changes in gut microbiome structure and loss of features thought to be crucial for maintaining gut ecological balance. The stability of gut microbial communities over time within individuals seems to be largely affected by these changes but has been overlooked among transitioning populations from low- to middle-income countries. Here, we used metagenomic sequencing to characterize the temporal dynamics in gut microbiomes of 24 individuals living an urban non-industrialized lifestyle in the Brazilian Amazon. We further contextualized our data with 165 matching longitudinal samples from an urban industrialized and a rural non-industrialized population. We show that gut microbiome composition and diversity have greater variability over time among non-industrialized individuals when compared to industrialized counterparts and that taxa may present diverse temporal dynamics across human populations. Enterotype classifications show that community types are generally stable over time despite shifts in microbiome structure. Furthermore, by tracking genomes over time, we show that levels of bacterial population replacements are more frequent among Amazonian individuals and that non-synonymous variants accumulate in genes associated with degradation of host dietary polysaccharides. Taken together, our results suggest that the stability of gut microbiomes is influenced by levels of industrialization and that tracking microbial population dynamics is important to understand how the microbiome will adapt to these transitions.IMPORTANCEThe transition from a rural or non-industrialized lifestyle to urbanization and industrialization has been linked to changes in the structure and function of the human gut microbiome. Understanding how the gut microbiomes changes over time is crucial to define healthy states and to grasp how the gut microbiome interacts with the host environment. Here, we investigate the temporal dynamics of gut microbiomes from an urban and non-industrialized population in the Amazon, as well as metagenomic data sets from urban United States and rural Tanzania. We showed that healthy non-industrialized microbiomes experience greater compositional shifts over time compared to industrialized individuals. Furthermore, bacterial strain populations are more frequently replaced in non-industrialized microbiomes, and most non-synonymous mutations accumulate in genes associated with the degradation of host dietary components. This indicates that microbiome stability is affected by transitions to industrialization, and that strain tracking can elucidate the ecological dynamics behind such transitions., Competing Interests: E.J.A. is a co-founder and shareholder of Finch Therapeutics, a company that specializes in microbiome-targeted therapeutics.

Non-alcoholic fatty liver disease (NAFLD) is a major public health problem due to the high incidence affecting approximately one-third of the world's population. NAFLD is usually linked to obesity and excessive weight. A subset of patients with NAFLD expresses normal or low body mass index; thus, the condition is called non-obese NAFLD or lean NAFLD. However, patients and healthcare professionals have little awareness and understanding of NAFLD in non-obese individuals. Furthermore, preclinical results from non-obese animal models with NAFLD are unclear. Gut microbiota and their metabolites in non-obese/lean-NAFLD patients differ from those in obese NAFLD patients. Therefore, we analyzed the biochemical indices, intestinal flora, and intestinal metabolites in a non-obese NAFLD mouse model established using a methionine-choline-deficient (MCD) diet. The significantly lean MCD mice had a remarkable fatty liver with lower serum triglyceride and free fatty acid levels, as well as higher alanine transaminase and aspartate transaminase levels than normal mice. 16S RNA sequencing of fecal DNA showed that the overall richness and diversity of the intestinal flora decreased in MCD mice, whereas the Firmicutes:Bacteroidota ratio was increased. g&#95; Tuzzerella , s&#95; Bifidobacterium pseudolongum , and s&#95; Faecalibaculum rodentium were the predominant species in non-obese NAFLD mice. Fecal metabolomics using liquid chromatography-tandem mass spectrometry revealed the potential biomarkers for the prognosis and diagnosis of non-obese NAFLD, including high levels of tyramine glucuronide, 9,12,13-TriHOME, and pantetheine 4'-phosphate, and low levels of 3-carbamoyl-2-phenylpropionaldehyde, N-succinyl-L,L-2,6-diaminopimelate, 4-methyl-5-thiazoleethanol, homogentisic acid, and estriol. Our findings could be useful to identify and develop drugs to treat non-obese NAFLD and lean NAFLD., Importance: Patients and healthcare professionals have little awareness and understanding of NAFLD in non-obese individuals. In fact, about 40% of people with NAFLD worldwide are non-obese, and nearly one-fifth are lean. Lean NAFLD unfortunately may be unnoticed for years and remains undetected until hepatic damage is advanced and the prognosis is compromised. This study focused on the lean NAFLD, screened therapeutic agents, and biomarkers for the prognosis and diagnosis using MCD-induced male C57BL/6J mice. The metabolites tyramine glucuronide, 9,12,13-TriHOME, and pantetheine 4'-phosphate, together with the predominant flora including g&#95; Tuzzerella , s&#95; Bifidobacterium pseudolongum , and s&#95; Faecalibaculum rodentium , were specific in non-obese NAFLD mice and might be used as targets for non-obese NAFLD drug exploration. This study is particularly significant for non-obese NAFLDs that need to be more actively noticed and vigilant., Competing Interests: The authors declare no conflict of interest.

Bumblebees are among the most abundant and important pollinators for sub-alpine and alpine flowering plant species in the Northern Hemisphere, but little is known about their adaptations to high elevations. In this article, we focused on two bumblebee species, Bombus friseanus and Bombus prshewalskyi , and their respective gut microbiota. The two species, distributed through the Hengduan Mountains of southwestern China, show species replacement at different elevations. We performed genome sequencing based on 20 worker bee samples of each species. Applying evolutionary population genetics and metagenomic approaches, we detected genes under selection and analyzed functional pathways between bumblebees and their gut microbes. We found clear genetic differentiation between the two host species and significant differences in their microbiota. Species replacement occurred in both hosts and their bacteria ( Snodgrassella ) with an increase in elevation. These extremely high-elevation bumblebees show evidence of positive selection related to diverse biological processes. Positively selected genes involved in host immune systems probably contributed to gut microbiota changes, while the butyrate generated by gut microbiota may influence both host energy metabolism and immune systems. This suggests a close association between the genomes of the host species and their microbiomes based on some degree of natural selection.IMPORTANCETwo closely related and dominant bumblebee species, distributed at different elevations through the Hengduan Mountains of southwestern China, showed a clear genomic signature of adaptation to elevation at the molecular level and significant differences in their respective microbiota. Species replacement occurred in both hosts and their bacteria ( Snodgrassella ) with an increase in elevation. Bumblebees' adaptations to higher elevations are closely associated with their gut microbiota through two biological processes: energy metabolism and immune response. Information allowing us to understand the adaptive mechanisms of species to extreme conditions is implicit if we are to conserve them as their environments change., Competing Interests: The authors declare no conflict of interest.

The crucial function of circulating microbial DNA (cmDNA) in peripheral blood is gaining recognition because of its importance in normal physiology and immunity in healthy individuals. Evidence suggests that cmDNA in peripheral blood is derived from highly abundant, translocating gut microbes. However, the associations with and differences between cmDNA in peripheral blood and the gut microbiome remain unclear. We collected blood, urine, and fecal samples from volunteers to compare their microbial information via 16S rDNA sequencing. The results revealed that, compared with gut microbial DNA, cmDNA in peripheral blood was associated with reduced diversity and a distinct microbiota composition. The cmDNA in the blood reflects the biochemical processes of microorganisms, including synthesis, energy conversion, degradation, and adaptability, surpassing that of fecal samples. Interestingly, cmDNA in blood showed a limited presence of DNA from anaerobes and gram-positive bacteria, which contrast with the trend observed in fecal samples. Furthermore, analysis of cmDNA revealed traits associated with mobile elements and potential pathologies, among others, which were minimal in stool samples. Notably, cmDNA analysis indicated similarities between the microbial functions and phenotypes in blood and urine samples, although greater diversity was observed in urine samples. Source Tracker analysis suggests that gut microbes might not be the main source of blood cmDNA, or a selective mechanism allows only certain microbial DNA into the bloodstream. In conclusion, our study highlights the composition and potential functions associated with cmDNA in peripheral blood, emphasizing its selective presence; however, further research is required to elucidate the mechanisms involved.IMPORTANCEOur research provides novel insights into the unique characteristics and potential functional implications of circulating microbial DNA (cmDNA) in peripheral blood. Unlike other studies that analyzed sequencing data from fecal or blood microbiota in different study cohorts, our comparative analysis of cmDNA from blood, urine, and fecal samples from the same group of volunteers revealed a distinct blood-specific cmDNA composition. We discovered a decreased diversity of microbial DNA in blood samples compared to fecal samples as well as an increased presence of biochemical processes microbial DNA in blood. Notably, we add to the existing knowledge by documenting a reduced abundance of anaerobes and gram-positive bacteria in blood compared to fecal samples according to the analysis of cmDNA and gut microbial DNA, respectively. This observation suggested that a potential selective barrier or screening mechanism might filter microbial DNA molecules, indicating potential selectivity in the translocation process which contrasts with the traditional view that cmDNA primarily originates from random translocation from the gut and other regions. By highlighting these differences, our findings prompt a reconsideration of the origin and role of cmDNA in blood circulation and suggest that selective processes involving more complex biological mechanisms may be involved., Competing Interests: The authors declare no conflict of interest.

Bifidobacteria are among the first microbial colonizers of the human gut, being frequently associated with human health-promoting activities. In the current study, an in silico methodology based on an ecological and phylogenomic-driven approach allowed the selection of a Bifidobacterium adolescentis prototype strain, i.e., B. adolescentis PRL2023, which best represents the overall genetic content and functional features of the B. adolescentis taxon. Such features were confirmed by in vitro experiments aimed at evaluating the ability of this strain to survive in the gastrointestinal tract of the host and its ability to interact with human intestinal cells and other microbial gut commensals. In this context, co-cultivation of B. adolescentis PRL2023 and several gut commensals revealed various microbe-microbe interactions and indicated co-metabolism of particular plant-derived glycans, such as xylan.IMPORTANCEThe use of appropriate bacterial strains in experimental research becomes imperative in order to investigate bacterial behavior while mimicking the natural environment. In the current study, through in silico and in vitro methodologies, we were able to identify the most representative strain of the Bifidobacterium adolescentis species. The ability of this strain, B. adolescentis PRL2023, to cope with the environmental challenges imposed by the gastrointestinal tract, together with its ability to switch its carbohydrate metabolism to compete with other gut microorganisms, makes it an ideal choice as a B. adolescentis prototype and a member of the healthy microbiota of adults. This strain possesses a genetic blueprint appropriate for its exploitation as a candidate for next-generation probiotics., Competing Interests: The authors declare no conflict of interest.

During the process of periodontitis-promoting oral squamous cell carcinoma (OSCC), the periodontitis microbiota can facilitate OSCC development by activating γδ T cells. Inhibiting γδ T cells through immunotherapy has been shown to significantly alleviate various types of cancer. However, the underlying mechanism by which inhibiting γδ T cells influenced cancer treatment has not been fully elucidated. In this study, a mouse model of OSCC with periodontitis was established, and γδ T cells were inhibited by antibodies. Gut samples from the mice were collected and analyzed by metabolomics, metagenomics, and 16S rRNA. Integrative analysis of the gut metabolome and microbiome revealed that targeting γδ T resulted in changes in the levels of metabolites associated with cancer in the gut. Although there was no difference in the α diversity of microbiota, β diversity was significantly different, with a more heterogeneous community structure in the mice receiving targeted γδ T immunotherapy. Statistical analysis of the gut microbiota at the species level revealed a significant enrichment of Lactobacillus murinus , which was significantly correlated with γδ T abundance. The functional analysis revealed that inhibiting γδ T could impact the functional gene. A comprehensive analysis revealed that L. murinus is especially associated with changes in adenine, which also had connection with the concentration of IL-17 and the abundance of γδ T.IMPORTANCEThis study revealed the effect of γδ T cells on gut microbial dysbiosis and identify potential links between gut microbiota and metabolism, providing new insights into the role of γδ T during the process of periodontitis-induced OSCC, and identifying relevant biomarkers for future research and clinical monitoring protocol development., Competing Interests: The authors declare no conflict of interest.

Animals and their associated microbiota share long evolutionary histories. However, it is not always clear how host genotype and microbiota interact to affect phenotype. We applied a hologenomic approach to explore how host-microbiota interactions shape lifetime growth and parasite infection in farmed Atlantic salmon ( Salmo salar ). Multi-omics data sets were generated from the guts of 460 salmon, 82% of which were naturally infected with an intestinal cestode. A single Mycoplasma bacterial strain, MAG01, dominated the gut metagenome of large, non-parasitized fish, consistent with previous studies showing high levels of Mycoplasma in the gut microbiota of healthy salmon. While small and/or parasitized salmon also had high abundance of MAG01, we observed increased alpha diversity in these individuals, driven by increased frequency of low-abundance Vibrionaceae and other Mycoplasma species that carried known virulence genes. Colonization by one of these cestode-associated Mycoplasma strains was associated with host individual genomic variation in long non-coding RNAs. Integrating the multi-omic data sets revealed coordinated changes in the salmon gut mRNA transcriptome and metabolome that correlated with shifts in the microbiota of smaller, parasitized fish. Our results suggest that the gut microbiota of small and/or parasitized fish is in a state of dysbiosis that partly depends on the host genotype, highlighting the value of using a hologenomic approach to incorporate the microbiota into the study of host-parasite dynamics.IMPORTANCEStudying host-microbiota interactions through the perspective of the hologenome is gaining interest across all life sciences. Intestinal parasite infections are a huge burden on human and animal health; however, there are few studies investigating the role of the hologenome during parasite infections. We address this gap in the largest multi-omics fish microbiota study to date using natural cestode infection of farmed Atlantic salmon. We find a clear association between cestode infection, salmon lifetime growth, and perturbation of the salmon gut microbiota. Furthermore, we provide the first evidence that the genetic background of the host may partly determine how the gut microbiota changes during parasite-associated dysbiosis. Our study therefore highlights the value of a hologenomic approach for gaining a more in-depth understanding of parasitism., Competing Interests: H.S. is employed at Lerøy Seafood Group, who produces, markets, and sells farmed Atlantic salmon, including the fish used in the current investigation. Furthermore, Lerøy Seafood Group provided parts of the funding for this study. All other authors declare they have no competing interests.

Sphingolipids serve as vital structural and signaling components of the cell membranes in both eukaryotes and prokaryotes. Within the gut microbiome, Bacteroides species have been identified as major producers of sphingolipids, and Bacteroides -produced sphingolipids have been shown to be modulators of host immune and metabolic functions. While Bacteroides species are a prominent feature of the gut microbiomes of populations living in industrialized countries, Prevotella copri , a member of the same phyla, albeit a different family, is the dominant feature across the remainder of the global population, although their sphingolipid-producing capabilities have not been as thoroughly investigated. To fill this gap, we examined the genomes of over 60 diverse isolates of P. copri and identified several key enzymes involved in sphingolipid synthesis in P. copri . Combining bioorthogonal labeling and liquid chromatography-mass spectrometry (LC-MS) based lipidomics, we functionally characterized the first step in P. copri de novo sphingolipid synthesis in addition to profiling the sphingolipidomes of P. copri strains, identifying key enzymes that may play roles in producing a diverse set of P. copri sphingolipids. Given the limited genetic engineering tools amenable for use in P. copri , our approach takes advantage of comparative genomics and phenotypic profiling to explore sphingolipid production in these understudied, yet highly prevalent, organisms.IMPORTANCESphingolipids are important signaling molecules for maintaining metabolic and immune homeostasis in the host. These lipids are also produced by gut commensals, most notably by Bacteroides species. Despite the global prevalence of Prevotella copri in gut microbiomes of individuals, little is known about the types of sphingolipids they produce and whether they are similar in composition and structure to those produced by Bacteroides . Given the varied associations of P. copri with diverse sphingolipid-related health outcomes, such as rheumatoid arthritis and glucose intolerance, it is important to first characterize the specific sphingolipids produced by individual strains of P. copri and to identify the genes involved in their pathways of production. This characterization of P. copri -derived sphingolipids provides further insight into how bacterial sphingolipid production can serve as a mechanism for microbial modulation of host phenotypes., Competing Interests: The authors declare no conflict of interest.

Parkinson's disease (PD) is characterized by motor symptoms and a loss of dopaminergic neurons, as well as a variety of non-motor symptoms, including constipation, depression, and anxiety. Recently, evidence has also accumulated for a link between gut microbiota and PD. Most PD patients are on dopamine replacement therapy, primarily a combination of L-DOPA and carbidopa; however, the effect of these medications on the microbiota and non-motor symptoms in PD is still unclear. In this study, we explored the effects of chronic oral treatment with L-DOPA plus carbidopa (LDCD) on the gut microbiota and non-motor symptoms in males of a transgenic mouse model of PD (dbl-PAC-Tg( SNCA A53T ); Snca -/-). To further test whether the effects of these PD medications were mediated by the gut microbiota, oral antibiotic treatment (Abx; vancomycin and neomycin) was included both with and without concurrent LDCD treatment. Post-treatment, the gastrointestinal, motor, and behavioral phenotypes were profiled, and fecal, ileal, and jejunal samples were analyzed for gut microbiota composition by 16S sequencing. LDCD treatment was found to improve symptoms of constipation and depression in this model, concurrent with increases in Turicibacter abundance in the ileum. Abx treatment worsened the symptoms of constipation, possibly through decreased levels of short-chain fatty acids and disrupted gut barrier function. LDCD + Abx treatment showed an interaction effect on behavioral symptoms that was also associated with ileal Turicibacter levels. This study demonstrates that, in a mouse model, PD medications and antibiotics affect PD-related non-motor symptoms potentially via the gut microbiota.IMPORTANCEThe motor symptoms of Parkinson's disease (PD) are caused by a loss of dopamine-producing neurons and are commonly treated with dopamine replacement therapy (L-DOPA plus carbidopa). PD has also been associated with altered gut microbiota composition. However, the effects of these PD medications on PD-related non-motor symptoms and the gut microbiota have not been well characterized. This study uses a transgenic mouse model of PD to help resolve medication-induced microbiota alterations from those that are potentially disease relevant within a PD context, and explores how long-term treatment may interact with the gut microbiota to impact non-motor symptoms., Competing Interests: The authors declare no conflict of interest.

Antimicrobial resistance (AMR) is a major global health concern, further complicated by its spread via the microbiome bacterial members. While mathematical models discuss AMR transmission through the symbiotic microbiome, experimental studies are scarce. Herein, we used a gregarious cockroach, Pycnoscelus surinamensis, as an in vivo animal model for AMR transmission investigations. We explored whether the effect of antimicrobial treatment is detectable with metagenomic sequencing, and whether AMR genes can be spread and established in unchallenged (not treated with antibiotics) individuals following contact with treated donors, and under various frequencies of interaction. Gut and soil substrate microbiomes were investigated by metagenomic sequencing for bacterial community composition and resistome profiling. We found that tetracycline treatment altered the treated gut microbiome by decreasing bacterial diversity and increasing the abundance of tetracycline resistance genes. Untreated cockroaches that interacted with treated donors also had elevated tetracycline resistance. The levels of resistance differed depending on the magnitude and frequency of donor transfer. Additionally, treated donors showed signs of microbiome recovery due to their interaction with the untreated ones. Similar patterns were also recorded in the soil substrate microbiomes. Our results shed light on how interacting microbiomes facilitate AMR gene transmission to previously unchallenged hosts, a dynamic influenced by the interaction frequencies, using an in vivo model to validate theoretical AMR transmission models.IMPORTANCEAntimicrobial resistance is a rising threat to human and animal health. The spread of resistance through the transmission of the symbiotic gut microbiome is of concern and has been explored in theoretical modeling studies. In this study, we employ gregarious insect populations to examine the emergence and transmission of antimicrobial resistance in vivo and validate modeling hypotheses. We find that antimicrobial treatment increases the levels of resistance in treated populations. Most importantly, we show that resistance increased in untreated populations after interacting with the treated ones. The level of resistance transmission was affected by the magnitude and frequency of population mixing. Our results highlight the importance of microbial transmission in the spread of antimicrobial resistance., Competing Interests: The authors declare no conflict of interest.

Importance: There are challenges in merging microbiome data from diverse research groups due to the intricate and multifaceted nature of such data. To address this, we utilized a combination of machine-learning (ML) models to analyze 16S sequencing data from a substantial set of gut microbiome samples, sourced from 12 distinct infant cohorts that were gathered prospectively. Our initial focus was on the mode of delivery due to its prior association with changes in infant gut microbiomes. Through ML analysis, we demonstrated the effective merging and comparison of various gut microbiome data sets, facilitating the identification of robust microbiome biomarkers applicable across varied study populations., Competing Interests: The authors declare no conflict of interest.

Importance: Most studies focused much on the change in abundance and often failed to explain the microbiome variation related to disease conditions, Herein, we argue that microbial genetic changes can precede the ecological changes associated with the host physiological changes and, thus, would offer a new information layer from metagenomic data for predictive modeling of diseases. Interestingly, we preliminarily found a few genetic biomarkers on SCFA production can cover most chronic diseases involved in the meta-analysis. In the future, it is of both scientific and clinical significance to further explore the dynamic interactions between adaptive evolution and ecology of gut microbiota associated with host health status., Competing Interests: The authors declare no conflict of interest.

Importance: Social bees are an important model for the ecology and evolution of gut microbiomes. These bees harbor ancient, specific, and beneficial gut microbiomes and are crucial pollinators. However, most of the research has concentrated on managed honeybees and bumblebees in the temperate zone. Here we used 16S rRNA gene sequencing to characterize gut microbiomes in wild neotropical bumblebee communities from Colombia. We also analyzed drivers of microbiome structure across our data and previously published data from temperate bumblebees. Our results show that lineages of neotropical bumblebees not only retained their ancient gut bacterial symbionts during dispersal from North America but also are prone to major disruption, a shift that is strongly associated with parasite infection. Finally, we also found that microbiomes are much more strongly structured by host phylogeny than by geography, despite the very different environmental conditions and plant communities in the two regions., Competing Interests: The authors declare no conflict of interest.

Gut bacteria-driven production of trimethylamine (TMA) is strongly associated with cardiovascular disease. Borton et al. (mBio 14:e01511-23, 2023, https://doi.org/10.1128/mbio.01511-23) introduce the Methylated Amine Gene Inventory of Catabolism database (MAGICdb), comprehensively cataloging pathways involved in TMA metabolism. By integrating transcriptomics, proteomics, and metagenomic data, this work identifies key bacterial players in the process and can link gut microbial gene content to fecal TMA concentrations. This work shows that methylated amine metabolism is a keystone microbiome process carried out by a small proportion of the community. Proatherogenic pathways are more widely distributed among the gut microbiota, and new TMA-reducing genera were identified that might offer new potential for probiotic strategies or targeted microbiome interventions. Remarkably, MAGICdb's power to predict cardiovascular disease risk matches an approach using more traditional lipid risk factors. This open source will be a valuable tool for the community to link methylated amine metabolism to gut microbiome-related human health conditions., Competing Interests: The authors declare no conflict of interest.

Importance: A major focus of host-microbe research is to understand how genetic differences, of various magnitudes, among hosts translate to differences in their microbiomes. This has been challenging for animal hosts, including humans, because it is difficult to control environmental variables tightly enough to isolate direct genetic effects on the microbiome. Our work in stickleback fish is a significant contribution because our experimental approach allowed strict control over environmental factors, including standardization of the microbiome from the earliest stage of development and unrestricted co-housing of fish in a truly common environment. Furthermore, we measured host genetic variation over 2,000 regions of the stickleback genome, comparing this information and microbiome composition data among fish from very similar and very different genetic backgrounds. Our findings highlight how differences in the host genome influence microbiome diversity and make a case for future manipulative microbiome experiments that use host systems with naturally occurring genetic variation., Competing Interests: The authors declare no conflict of interest.

Importance: Gastric cancer is a significant and growing health problem in China. Studies have revealed significant differences in gastric microbiota between patients with gastric cancer and non-cancerous patients, suggesting that microbiota may play a role in tumorigenesis. In this meta-analysis, existing 16S rRNA microbial data were analyzed to find combinations consisting of five genera, which had good efficacy in distinguishing gastric cancer from non-cancerous patients in multiple types of samples. These results lend support to the use of microbial markers in detecting gastric cancer. Moreover, these biomarkers are plausible candidates for further mechanistic research into the role of the microbiota in tumorigenesis., Competing Interests: The authors declare no conflict of interest.

Importance: Myrmecophagous mammals are specialized in the consumption of ants and/or termites. They do not share a direct common ancestor and evolved convergently in five distinct placental orders raising questions about the underlying adaptive mechanisms involved and the relative contribution of natural selection and phylogenetic constraints. Understanding how these species digest their prey can help answer these questions. More specifically, the role of their gut microbial symbionts in the digestion of the insect chitinous exoskeleton has not been investigated in all myrmecophagous orders. We generated 29 new gut metagenomes from nine myrmecophagous species to reconstruct more than 300 bacterial genomes in which we identified chitin-degrading enzymes. Studying the distribution of these chitinolytic bacteria among hosts revealed both shared and specific bacteria between ant-eating species. Overall, our results highlight the potential role of gut symbionts in the convergent dietary adaptation of myrmecophagous mammals and the evolutionary mechanisms shaping their gut microbiota., Competing Interests: The authors declare no conflict of interest.

Importance: Calf diarrhea is of great concern to the global dairy industry as it results in significant economic losses due to lower conception rates, reduced milk production, and early culling. Although there is evidence of an association between altered gut microbiota and diarrhea, remarkably little is known about the microbial and metabolic mechanisms underlying the link between gut microbiota dysbiosis and the occurrence of calf diarrhea. Here, we used fecal metagenomic and metabolomic analyses to demonstrate that gut microbiota-driven metabolic disorders of purine or arachidonic acid were associated with calf diarrhea. These altered gut microbiotas play vital roles in diarrhea pathogenesis and indicate that gut microbiota-targeted therapies could be useful for both prevention and treatment of diarrhea., Competing Interests: The authors declare no conflict of interest.

Colon cancer onset is strongly associated with the differences in microbial taxa in the gastrointestinal tract. Although recent studies highlight the role of individual taxa, the effect of a complex gut microbiome (GM) on the metabolome and host transcriptome is still unknown. We used a multi-omics approach to determine how differences in the GM affect the susceptibility to adenoma development in a rat model of human colon cancer. Ultra-high performance liquid chromatography mass spectrometry of feces collected prior to observable disease onset identified putative metabolite profiles that likely predict future disease severity. Transcriptome analyses performed after disease onset from normal colonic epithelium and tumor tissues show a correlation between GM and host gene expression. Integrated pathway analyses of the metabolome and transcriptome based on putatively identified metabolic features indicate that bile acid biosynthesis is enriched in rats with high tumors along with increased fatty acid metabolism and mucin biosynthesis. Targeted pyrosequencing of the Pirc allele indicates that the GM alters the mechanism of adenoma development and may drive an epigenetic pathway of tumor suppressor silencing. This study reveals how untargeted metabolomics identifies signatures of susceptibility and integrated analyses uncover pathways of differential mechanisms of loss of tumor suppressor gene function and for potential prevention and therapeutic intervention. IMPORTANCE The association between the gut microbiome and colon cancer is significant but difficult to test in model systems. This study highlights the association of differences in the pathogen-free gut microbiome to changes in the host transcriptome and metabolome that correlate with colon adenoma initiation and development in a rat genetic model of early colon cancer. The utilization of a multi-omics approach integrating metabolomics and transcriptomics reveals differences in pathways including bile acid biosynthesis and fatty acid metabolism. The study also shows that differences in gut microbiomes significantly alter the mechanism of adenoma formation, shifting from genetic changes to epigenetic changes that initiate the early loss of tumor suppressor function. These findings enhance our understanding of the gut microbiome's role in colon cancer susceptibility, offer insights into potential biomarkers and therapeutic targets, and may pave the way for future prevention and intervention strategies., Competing Interests: The authors declare no conflict of interest.

Next-generation sequencing (NGS) and metabarcoding approaches are increasingly applied to wild animal populations, but there is a disconnect between the widely applied generalized linear mixed model (GLMM) approaches commonly used to study phenotypic variation and the statistical toolkit from community ecology typically applied to metabarcoding data. Here, we describe the suitability of a novel GLMM-based approach for analyzing the taxon-specific sequence read counts derived from standard metabarcoding data. This approach allows decomposition of the contribution of different drivers to variation in community composition (e.g., age, season, individual) via interaction terms in the model random-effects structure. We provide guidance to implementing this approach and show how these models can identify how responsible specific taxonomic groups are for the effects attributed to different drivers. We applied this approach to two cross-sectional data sets from the Soay sheep population of St. Kilda. GLMMs showed agreement with dissimilarity-based approaches highlighting the substantial contribution of age and minimal contribution of season to microbiota community compositions, and simultaneously estimated the contribution of other technical and biological factors. We further used model predictions to show that age effects were principally due to increases in taxa of the phylum Bacteroidetes and declines in taxa of the phylum Firmicutes. This approach offers a powerful means for understanding the influence of drivers of community structure derived from metabarcoding data. We discuss how our approach could be readily adapted to allow researchers to estimate contributions of additional factors such as host or microbe phylogeny to answer emerging questions surrounding the ecological and evolutionary roles of within-host communities. IMPORTANCE NGS and fecal metabarcoding methods have provided powerful opportunities to study the wild gut microbiome. A wealth of data is, therefore, amassing across wild systems, generating the need for analytical approaches that can appropriately investigate simultaneous factors at the host and environmental scale that determine the composition of these communities. Here, we describe a generalized linear mixed-effects model (GLMM) approach to analyze read count data from metabarcoding of the gut microbiota, allowing us to quantify the contributions of multiple host and environmental factors to within-host community structure. Our approach provides outputs that are familiar to a majority of field ecologists and can be run using any standard mixed-effects modeling packages. We illustrate this approach using two metabarcoding data sets from the Soay sheep population of St. Kilda investigating age and season effects as worked examples., Competing Interests: The authors declare no conflict of interest.

In vitro studies of synthetic gut microbial communities (SGMCs) can provide valuable insights into the ecological structure and function of gut microbiota. However, the importance of the quantitative composition of an SGMC inoculum and its effect on the eventual stable in vitro microbial community has not been studied. To address this, we constructed two 114-member SGMCs differing only in their quantitative composition-one reflecting the average human fecal microbiome and another mixed in equal proportions based on cell counts. We inoculated each in an automated anaerobic multi-stage in vitro gut fermentor simulating two different colonic conditions, mimicking proximal and distal colons. We replicated this setup with two different nutrient media, periodically sampled the cultures for 27 days, and profiled their microbiome compositions using 16S rRNA gene amplicon sequencing. While nutrient medium explained 36% of the variance in microbiome composition, initial inoculum composition failed to show a statistically significant effect. Under all four conditions, paired fecal and equal SGMC inoculums converged to reach stable community compositions resembling each other. Our results have broad implications for simplifying in vitro SGMC investigations. IMPORTANCE In vitro cultivation of synthetic gut microbial communities (SGMCs) can provide valuable insights into the ecological structure and function of gut microbiota. However, it is currently not known whether the quantitative composition of the initial inoculum can influence the eventual stable in vitro community structure. Hence, using two SGMC inoculums consisting of 114 unique species mixed in either equal proportions (Eq inoculum) or resembling proportions in an average human fecal microbiome (Fec inoculum), we show that initial inoculum compositions did not influence the final stable community structure in a multi-stage in vitro gut fermentor. Under two different nutrient media and two different colon conditions (proximal and distal), both Fec and Eq communities converged to resemble each other's community structure. Our results suggest that the time-consuming preparation of SGMC inoculums may not be needed and has broad implications for in vitro SGMC studies., Competing Interests: The authors declare a conflict of interest. Manimozhiyan Arumugam has received speaking and/or consulting fees from Roche A/S, Lundbeck Pharma A/S, and SNIPR Biome ApS. These companies did not influence the design and outcome of this study.

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., Competing Interests: The authors declare no conflict of interest.

The interplay between the intestinal microbiota and host is critical to intestinal ontogeny and homeostasis. MicroRNAs (miRNAs) may be an underlying link. Intestinal miRNAs are microbiota-dependent and, when shed in the lumen, affect resident microorganisms. Yet, longitudinal relationships between intestinal tissue miRNAs, luminal miRNAs, and luminal microorganisms have not been elucidated, especially in early life. Here, we investigated the postnatal cecal miRNA and microbiota populations, their relationship, and their impact on intestinal maturation in specific pathogen-free mice; we also assessed if they can be modified by intervention with allochthonous probiotic lactobacilli. We report that cecal and cecal content miRNA and microbiota signatures are temporally regulated, correlated, and modifiable by probiotics with implications for intestinal maturation. These findings help understand causal relationships within the gut ecosystem and provide a basis for preventing and managing their alterations in diseases throughout life. IMPORTANCE The gut microbiota affects intestinal microRNA (miRNA) signatures and is modified by host-derived luminal miRNA. This suggests the existence of close miRNA-microbiota relationships that are critical to intestinal homeostasis. However, an integrative analysis of these relationships and their evolution during intestinal postnatal maturation is lacking. We provide a system-level longitudinal analysis of miRNA-microbiota networks in the intestine of mice at the weaning transition, including tissue and luminal miRNA and luminal microbiota. To address causality and move toward translational applications, we used allochthonous probiotic lactobacilli to modify these longitudinal relationships and showed that they are critical for intestinal maturation in early life. These findings contribute to understand mechanisms that underlie the maturation of the intestinal ecosystem and suggest that interventions aiming at maintaining, or restoring, homeostasis cannot prescind from considering relationships among its components., Competing Interests: E.M.C. has received research support from the Lallemand Health Solutions and Ocean Spray and has received consultant fees from Danone. All other authors declare no conflict of interests. The probiotic strains utilized in this study were provided by the Lallemand Health Solutions (LHS), Inc.

The pks island is one of the most prevalent pathogenicity islands among the Escherichia coli strains that colonize the colon of colorectal carcinoma (CRC) patients. This pathogenic island encodes the production of a nonribosomal polyketide-peptide named colibactin, which induces double-strand breaks in DNA molecules. Detection or even depletion of this pks -producing bacteria could help to understand the role of these strains in the context of CRC. In this work, we performed a large-scale in silico screening of the pks cluster in more than 6,000 isolates of E. coli . The results obtained reveal that not all the pks -detected strains could produce a functional genotoxin and, using antibodies against pks -specific peptides from surface cell proteins, a methodology for detection and depletion of pks + bacteria in gut microbiotas was proposed. With our method, we were able to deplete a human gut microbiota of this pks + strains, opening the door to strain-directed microbiota modification and intervention studies that allow us to understand the relation between these genotoxic strains and some gastrointestinal diseases. IMPORTANCE The human gut microbiome has also been hypothesized to play a crucial role in the development and progression of colorectal carcinoma (CRC). Between the microorganisms of this community, the Escherichia coli strains carrying the pks genomic island were shown to be capable of promoting colon tumorigenesis in a colorectal cancer mouse model, and their presence seems to be directly related to a distinct mutational signature in patients suffering CRC. This work proposes a novel method for the detection and depletion of pks -carrying bacteria in human gut microbiotas. In contrast to methods based on probes, this methodology allows the depletion of low-abundance bacterial strains maintaining the viability of both targeted and non-targeted fractions of the microbiota, allowing the study of the contribution of these pks -carrying strains to different diseases, such as CRC, and their role in other physiological, metabolic or immune processes., Competing Interests: Abelardo Margolles and Borja Sánchez are co-founders of Microviable Therapeutics SL. Abelardo Margolles is member of the scientific board of Microviable Therapeutics SL. Borja Sánchez is Minister of Science, Innovation and University of the Government of the Principality of Asturias. Results presented in this paper are protected under European Patent EP19383077 (WO2021110833A1 and US20230029322A1; Tools and methods to detect and isolate colibactin producing bacteria).