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Background: Evolutionary divergence and genetic variation are often linked to differences in microbial community structure and diversity. While environmental factors and diet heavily influence gut microbial communities, host species contributions are harder to quantify. Closely related species living in sympatry provide a unique opportunity to investigate species differences without the confounding effects of habitat and dietary variation. We therefore compared and contrasted the gut microbiota of three sympatric plover species: the widespread Kittlitz's and white-fronted plovers (Anarhynchus pecuarius and A. marginatus) and the endemic and vulnerable Madagascar plover (A. thoracicus)., Results: We found no significant differences in the beta diversity (composition) of the gut microbiota of the three species. However, A. thoracicus exhibited higher intraspecific compositional similarity (i.e. lower pairwise distances) than the other two species; this pattern was especially pronounced among juveniles. By contrast, microbial alpha diversity varied significantly among the species, being highest in A. pecuarius, intermediate in A. marginatus and lowest in A. thoracicus. This pattern was again stronger among juveniles. Geographical distance did not significantly affect the composition of the gut microbiota, but genetic relatedness did., Conclusion: While patterns of microbial diversity varied across species, the lack of compositional differences suggests that habitat and diet likely exert a strong influence on the gut microbiota of plovers. This may be enhanced by their precocial, ground-dwelling nature, which could facilitate the horizontal transmission of microbes from the environment. We hypothesise that gut microbiota diversity in plovers primarily reflects the ecological pool of microbiota, which is subsequently modified by host-specific factors including genetics. The reduced microbial and genetic diversity of the endemic A. thoracicus may hinder its ability to adapt to environmental changes, highlighting the need for increased conservation efforts for this vulnerable species., Competing Interests: Declarations. Ethics approval and consent to participate: Sampling of the three species of Madagascar plovers was approved by the Direction des Aires Protégées, des Ressources Naturellement Renouvelables et des Ecosystèmes from Madagascar (permits n $$^{\circ }$$ ∘ 386/21 and 054/21/MEDD/SG/DGGE/DAPRNE/SCBE.Re). Consent for publication: Not applicable. Completing interests: The authors declare no competing interests., (© 2024. The Author(s).)

Background: Advances in metagenome sequencing data continue to enable new methods for analyzing biological systems. When handling microbial profile data, metagenome sequencing has proven to be far more comprehensive than traditional methods such as 16s rRNA data, which rely on partial sequences. Microbial community profiling can be used to obtain key biological insights that pave the way for more accurate understanding of complex systems that are critical for advancing biomedical research and healthcare. However, such attempts have mostly used partial or incomplete data to accurately capture those associations., Methods: This study introduces a novel computational approach for the identification of co-occurring microbial communities using the abundance and functional roles of species-level microbiome data. The proposed approach is then used to identify signature pathways associated with inflammatory bowel disease (IBD). Furthermore, we developed a computational pipeline to identify microbial species co-occurrences from metagenome data at various granularity levels., Results: When comparing the IBD group to a control group, we show that certain co-occurring communities of species are enriched for potential pathways. We also show that the identified co-occurring microbial species operate as a community to facilitate pathway enrichment., Conclusions: The obtained findings suggest that the proposed network model, along with the computational pipeline, provide a valuable analytical tool to analyze complex biological systems and extract pathway signatures that can be used to diagnose certain health conditions., Competing Interests: Declarations. Ethics approval and consent to participate: Not applicable. Consent for publication: Not applicable. Competing interests: The authors declare that they have no competing interests., (© 2024. The Author(s).)

Background: Hashimoto's thyroiditis (HT) is an autoimmune disorder with unclear molecular mechanisms. While current diagnosis is well-established, understanding of the gut-thyroid axis in HT remains limited. This study aimed to uncover novel molecular signatures in HT by integrating gut metagenome and host transcriptome data (miRNA/mRNA), potentially elucidating disease pathogenesis and identifying new therapeutic targets., Methods: We recruited 31 early HT patients and 30 healthy controls in a two-stage study (discovery and validation). Blood and fecal samples underwent RNA and metagenomic sequencing, respectively. Integrative analysis included differential expression, weighted correlation network, correlation and random forest analyses. Regression models and ROC curve analysis were used to evaluate the significance of identified molecular signatures in HT., Results: Integrative analysis revealed subtle changes in gut microbiota diversity and composition in early HT, increased abundance of Bacillota_A and Spirochaetota at the phylum level, and significant differences in 24 genera and 67 species. Ecological network analysis indicated an imbalance in the gut microbiota with reduced inhibitory interactions against pathogenic genera in HT. Functional analysis showed changes in infection- and immune-related pathways. Three characteristic species (Salaquimonas_sp002400845, Clostridium_AI_sp002297865, and Enterocloster_citroniae) were identified as most relevant to HT. Analysis of miRNA and mRNA expression profiles uncovered pathways related to immune response, inflammation, infection, metabolism, proliferation, and thyroid cancer in HT. Based on correlations with HT and interactions between them, six characteristic RNAs (hsa-miR-548aq-3p, hsa-miR-374a-5p, GADD45A, IRS2, SMAD6, WWTR1) were identified. Furthermore, our study uncovered significant gut microbiota-host transcriptome interactions in HT, revealing enrichment in metabolic, immune, and cancer-related pathways, particularly with strong associations among those 9 key molecular signatures. The validation stage confirmed improved HT classification accuracy by combining these signatures (AUC = 0.95, ACC = 0.85), suggesting their potential significance in understanding HT pathogenesis., Conclusion: Our study reveals novel molecular signatures linking gut microbiome and host transcriptome in HT, providing new insights into the disease pathogenesis. These findings not only enhance our understanding of the gut-thyroid axis but also suggest potential new directions for therapeutic interventions in HT., Competing Interests: Declarations Ethics approval and consent to participate Ethics approval was obtained from the the Medical Ethics Committees of both the Second Affiliated Hospital of Xi'an Jiaotong University and Qilu Hospital of Shandong University. All participants gave informed written consent. Consent for publication Not applicable. Competing interests The authors report no biomedical financial interests or potential conflicts of interest., (© 2024. The Author(s).)

We investigated the efficiency of target-enriched long-read sequencing (TELSeq) for detecting antimicrobial resistance genes (ARGs) and mobile genetic elements (MGEs) within complex matrices. We aimed to overcome limitations associated with traditional antimicrobial resistance (AMR) detection methods, including short-read shotgun metagenomics, which can lack sensitivity, specificity, and the ability to provide detailed genomic context. By combining biotinylated probe-based enrichment with long-read sequencing, we facilitated the amplification and sequencing of ARGs, eliminating the need for bioinformatic reconstruction. Our experimental design included replicates of human fecal microbiota transplant material, bovine feces, pristine prairie soil, and a mock human gut microbial community, allowing us to examine variables including genomic DNA input and probe set composition. Our findings demonstrated that TELSeq markedly improves the detection rates of ARGs and MGEs compared to traditional sequencing methods, underlining its potential for accurate AMR monitoring. A key insight from our research is the importance of incorporating mobilome profiles to better predict the transferability of ARGs within microbial communities, prompting a recommendation for the use of combined ARG-MGE probe sets for future studies. We also reveal limitations for ARG detection from low-input workflows, and describe the next steps for ongoing protocol refinement to minimize technical variability and expand utility in clinical and public health settings. This effort is part of our broader commitment to advancing methodologies that address the global challenge of AMR., (© 2024 Slizovskiy et al.; Published by Cold Spring Harbor Laboratory Press.)

Background: Advanced-stage non-small cell lung cancer (NSCLC) poses treatment challenges, with immune checkpoint inhibitors (ICIs) as the main therapy. Emerging evidence suggests the gut microbiome significantly influences ICI efficacy. This study explores the link between the gut microbiome and ICI outcomes in NSCLC patients, using metatranscriptomic (MTR) signatures., Methods: We utilized a de novo assembly-based MTR analysis on fecal samples from 29 NSCLC patients undergoing ICI therapy, segmented according to progression-free survival (PFS) into long (> 6 months) and short (≤ 6 months) PFS groups. Through RNA sequencing, we employed the Trinity pipeline for assembly, MMSeqs2 for taxonomic classification, DESeq2 for differential expression (DE) analysis. We constructed Random Forest (RF), Support Vector Machine (SVM), and Extreme Gradient Boosting (XGBoost) machine learning (ML) algorithms and comprehensive microbial profiles., Results: We detected no significant differences concerning alpha-diversity, but we revealed a biologically relevant separation between the two patient groups in beta-diversity. Actinomycetota was significantly overrepresented in patients with short PFS (vs long PFS, 36.7% vs. 5.4%, p < 0.001), as was Euryarchaeota (1.3% vs. 0.002%, p = 0.009), while Bacillota showed higher prevalence in the long PFS group (66.2% vs. 42.3%, p = 0.007), when comparing the abundance of corresponding RNA reads. Among the 120 significant DEGs identified, cluster analysis clearly separated a large set of genes more active in patients with short PFS and a smaller set of genes more active in long PFS patients. Protein Domain Families (PFAMs) were analyzed to identify pathways enriched in patient groups. Pathways related to DNA synthesis and Translesion were more enriched in short PFS patients, while metabolism-related pathways were more enriched in long PFS patients. E. coli-derived PFAMs dominated in patients with long PFS. RF, SVM and XGBoost ML models all confirmed the predictive power of our selected RNA-based microbial signature, with ROC AUCs all greater than 0.84. Multivariate Cox regression tested with clinical confounders PD-L1 expression and chemotherapy history underscored the influence of n = 6 key RNA biomarkers on PFS., Conclusion: According to ML models specific gut microbiome MTR signatures' associate with ICI treated NSCLC outcomes. Specific gene clusters and taxa MTR gene expression might differentiate long vs short PFS., Competing Interests: Declarations Ethics approval and consent to participate In the current study, we adhered to the Helsinki Declaration’s study criteria established by the World Medical Association. The study was formally approved by the national ethics committee, specifically the Hungarian Scientific and Research Ethics Committee of the Medical Research Council (ETTTUKEB- 50302-2/2017/EKU). Participation in the study was contingent upon the provision of permission by all patients involved. To maintain confidentiality, patient IDs were removed after the collection of clinicopathological data, thereby preventing direct or indirect identification of patients. Consent for publication All authors agree to submit the article for publication. Competing interests The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (© 2024. The Author(s).)

Background: Gut microbiome plays a significant role in longevity, and dysbiosis is indeed one of the hallmarks of aging. However, the causal relationship between gut microbiota and human longevity or aging remains elusive., Methods: Our study assessed the causal relationships between gut microbiome and longevity using Mendelian Randomization (MR). Summary statistics for the gut microbiome were obtained from four genome-wide association study (GWAS) meta-analysis of the MiBioGen consortium (N = 18,340), Dutch Microbiome Project (N = 7738), German individuals (N = 8956), and Finland individuals (N = 5959). Summary statistics for Longevity were obtained from Five GWAS meta-analysis, including Human healthspan (N = 300,447), Longevity (N = 36,745), Lifespans (N = 1,012,240), Parental longevity (N = 389,166), and Frailty (one of the primary aging-linked physiological hallmarks, N = 175,226)., Results: Our findings reveal several noteworthy associations, including a negative correlation between Bacteroides massiliensis and longevity, whereas the genus Subdoligranulum and Alistipes, as well as species Alistipes senegalensis and Alistipes shahii, exhibited positive associations with specific longevity traits. Moreover, the microbial pathway of coenzyme A biosynthesis I, pyruvate fermentation to acetate and lactate II, and pentose phosphate pathway exhibited positive associations with two or more traits linked to longevity. Conversely, the TCA cycle VIII (helicobacter) pathway consistently demonstrated a negative correlation with lifespan and parental longevity., Conclusions: Our findings of this MR study indicated many significant associations between gut microbiome and longevity. These microbial taxa and pathways may potentially play a protective role in promoting longevity or have a suppressive effect on lifespan., Competing Interests: Declarations Ethics approval and concern to participate Not applicable. Consent for publication Not applicable. Competing interests No conflicts of interest to declare., (© 2024. The Author(s).)

Primary biliary cholangitis (PBC) and gut microbiota (GM) are epidemiologically correlated but the causal inter-relationships remain poorly understood. We aim to explore the causal relationships between GM and PBC. Using the MiBioGen consortium, GWAS data for GM at the species level and the largest publicly available PBC GWAS data to date, we performed a bidirectional two-sample Mendelian randomization by the inverse variance weighted, MR-Egger, weighted median, weighted model and MR-PRESSO to elucidate the potential causal role of GM in PBC. To measure the heterogeneity of instrumental variables (IV), Cochran's Q statistic and MR-Egger intercept test were used. Genetically instrumented order Coriobacteriales (odds ratio [OR] = 2.18, 95% confidence interval [CI] 1.30-3.66, P = 0.004) significantly increased the risk for PBC, while genetically driven class Deltaproteobacteria (OR = 0.52, 95% CI 0.36-0.74, P = 0.002) causally decrease the NAFLD risk. Reverse MR analysis showed no significant association between PBC and the two specific GM. However, it indicated that PBC progression significantly increases the abundance of the class Bacteroidia, order Bacteroidales, and phylum Bacteroidetes (OR = 1.02, 95% CI 1.002-1.03, P = 0.026), while decreasing the abundance of the genus Lachnospiraceae UCG010 (OR = 0.98, 95% CI 0.96-0.995, P = 0.026). Our study demonstrated that genetically driven order Coriobacteriales and class Deltaproteobacteria were causally related to PBC risk. This causality provided a new perspective on ameliorating PBC by modulating GM. Our study demonstrated that genetically driven order Coriobacteriales and class Deltaproteobacteria were causally related to PBC risk. PBC was causally related to the abundance of four GM taxa(class Bacteroidia, order Bacteroidales, phylum Bacteroidetes and genus Lachnospiraceae UCG010). This causality provided a new perspective on ameliorating PBC by modulating GM., Competing Interests: Declarations Competing interests The authors declare no competing interests., (© 2024. The Author(s).)

Previous research has demonstrated a close connection between the development of bone neoplasms and variations in the abundance of specific gut microbiota. It remains unclear, however, how the gut microbiota and bone neoplasms are causally related. Hence, in our study, we aim to clarify this relationship between gut microbiota and 2 neoplasms, malignant neoplasm of bone and articular cartilage (MNBAC) and benign neoplasm of bone and articular cartilage (BNBAC), by employing a two-sample Mendelian randomization (MR) approach. In this study, single nucleotide polymorphisms (SNPs) from genome-wide association studies-pooled data related to bone neoplasms and gut microbiota abundance were evaluated. The inverse variance weighted was employed as the major method for assessing the aforementioned causal relationship. Furthermore, the horizontal multiplicity was evaluated utilizing the Mendelian randomization pleiotropy residual sum and outlier and the MR-Egger intercept test. Finally, inverse MR analysis was performed to assess reverse causality. Inverse variance weighted results indicate a potential genetic relationship between 4 gut microbiota and MNBAC, and 3 gut microbiota and BNBAC. On the one hand, Eubacterium eligens group (OR = 0.16, 95% CI = 0.04-0.67, P = .01), Odoribacter (OR = 0.23, 95% CI = 0.06-0.84, P = .03), Slackia (OR = 0.35, 95% CI = 0.13-0.93, P = .04), and Tyzzerella3 (OR = 0.44, 95% CI = 0.24-0.82, P = .01) exhibited a protective effect against MNBAC. On the other hand, of the 3 gut microbes identified as potentially causally related to BNBAC, Oscillibacter (OR = 0.79, 95% CI = 0.63-0.98, P = .03) and Ruminococcus torques group (OR = 0.62, 95% CI = 0.39-0.98, P = .04) were regarded as protective strains of B, while Eubacterium ruminantium group (OR = 1.24, 95% CI = 1.04-1.47, P = .02) was considered to be a risk factor for increasing the incidence of BNBAC. Additionally, the bone neoplasms were not found to have a reverse causal relationship with the above 7 gut microbiota taxa. Four gut microbiota showed causal effects on MNBAC, and 3 gut microbiota demonstrated causality in BNBAC, providing insights into the design of future interventions to reduce the burden of neoplasms., Competing Interests: The authors have no funding and conflicts of interest to disclose., (Copyright © 2024 the Author(s). Published by Wolters Kluwer Health, Inc.)

Objective: The influence of different faecal collection methods on metagenomic analyses remains under discussion, and there is no general agreement on which collection method is preferable for gut microbiome research. We compared faecal samples collected in tubes without preservatives with those containing 10 mL of 96% ethanol for gut microbiome research when the timeframe from defecation to freezing at - 80 °C was up to 24 h. We aimed to compare the collection methods on faeces from participants with inflammatory and non-inflammatory gastrointestinal disorders and healthy controls to investigate the most suitable method when considering data yield, human fraction of sequencing reads, and ease of use. We also examined the faecal sample homogeneity., Results: Faeces collected in tubes without preservatives resulted in more sequencing reads compared to faeces collected in tubes with 96% ethanol and were also easier to handle. The human fraction of total reads in faeces collected in ethanol from participants with inflammatory bowel disease was higher than all other samples. DNA extraction and sequencing from two different locations in the same faecal sample gave similar results and showed sample homogeneity., Competing Interests: Declarations Ethics approval and consent to participate The study was performed in accordance with the Revised Declaration of Helsinki. The study was registered at www.clinicaltrials.gov as NCT04808271 and NCT04842149. All participants provided written informed consent to participate after verbal and written information was given. Consent for publication Not applicable. Competing interests The authors declare no competing interests., (© 2024. The Author(s).)

Antibacterial resistance in wild animals has been increasingly reported worldwide, even though they are usually not directly exposed to clinically relevant antibiotics. Crested ibis, one of the rarest birds in the world, usually forages in paddy fields and prefer to nest and breed near villages that is greatly influenced by anthropogenic activities. We sampled the feces of crested ibises, as well as their habitat environment samples, to explore the pollution characteristics of heavy metals, antibiotics and antibiotic resistance genes (ARGs). Results showed that the pollution characteristics of heavy metals, antibiotic, ARGs and gut microbiota of crested ibis were more related by host lifestyle and habitats. Captive ibises had higher relative abundances of the total ARGs and tetracycline concentrations compared with feralization and wild ibises, while the heavy metal contents had shown the opposite result. The Characteristics of pollutants in the corresponding environmental samples also exhibited high similarity with the results of fecal samples. The relative abundances of Proteobacteria and Actinobacteria were significantly different between captive and wild individuals, while the abundance of majority bacterial genera was generally higher in wild populations. The concentrations of heavy metals in soil (Cd, Cu and Zn) and water (Cd, Cu, Zn and Cr) were both exceeded the background soil levels or surface water quality standards, suggesting multi-element contamination in the habitat. Ecological risk assessments of soils by I geo and E r showed that the habitats of wild ibises were heavily and moderately contaminated by Cd, which would possibly pose a threat to the health of ibises. PLS-PM analysis indicated that microbial compositions and residual antibiotics had the most substantial impact on the dynamic changes in ARGs of ibis. Overall, this work provides a comprehensive understanding of the characteristics, risks of those contaminations, and their effects on the ARGs in the habitat of crested ibis., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Inc. All rights reserved.)

The gut microbiota is a treasure trove of carbohydrate-active enzymes (CAZymes). To explore novel and efficient CAZymes, we analyzed the 4,142 metagenome-assembled genomes (MAGs) of the horse gut microbiota and found the MAG117.bin13 genome (Bacteroides fragilis) contains the highest number of polysaccharide utilisation loci sites (PULs), indicating its high capability for carbohydrate degradation. Bioinformatics analysis indicate that the PULs region of the MAG117.bin13 genome encodes many hypothetical proteins, which are important sources for exploring novel CAZymes. Interestingly, we discovered a hypothetical protein (595 amino acids). This protein exhibits potential CAZymes activity and has a lower similarity to CAZymes, we named it BfLac2275. We purified the protein using prokaryotic expression technology and studied its enzymatic function. The hydrolysis experiment of the polysaccharide substrate showed that the BfLac2275 protein has the ability to degrade α-lactose (156.94 U/mg), maltose (92.59 U/mg), raffinose (86.81 U/mg), and hyaluronic acid (5.71 U/mg). The enzyme activity is optimal at pH 5.0 and 30 ℃, indicating that the hypothetical protein BfLac2275 is a novel and multifunctional CAZymes in the glycoside hydrolases (GHs). These properties indicate that BfLac2275 has broad application prospects in many fields such as plant polysaccharide decomposition, food industry, animal feed additives and enzyme preparations. This study not only serves as a reference for exploring novel CAZymes encoded by gut microbiota but also provides an example for further studying the functional annotation of hypothetical genes in metagenomic assembly genomes., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

In conservation strategies, getting precise and repeatable information on the species' diet and health without relying on invasive or laborious methods is challenging. Here, we developed an efficient and non-invasive workflow for the sequencing and analysis of four taxonomic markers from fecal DNA to characterize the gut microbiota, parasites, and plants and lichens composing the winter diet of caribou (Rangifer tarandus), Canada's most iconic endangered species. Sequencing of the 18S rRNA gene of eukaryotes from seven locations in Manitoba and Saskatchewan, Canada, allowed for the detection of five genera of parasites in caribou feces (including Nematodirella and Parelaphostrongylus) with variable frequency of occurrence depending on sampling location and sex. Our workflow also revealed a rich winter plant and lichen diet in caribou, with respectively 29 and 18 genera identified across all samples through plant and fungal ITS2 sequencing. Relationships between the gut microbiota and both the diet and parasite richness were also identified. Of note, the Central Saskatchewan sampling location was characterized by a clearly distinct gut microbiota which could be linked to an epiphytic lichen-rich diet. Overall, our results showed the potential of this multi-marker DNA metabarcoding workflow as an efficient tool to provide insights into the species biology and ecology., Competing Interests: Declarations Competing interests The authors declare no competing interests., (© 2024. His Majesty the King in Right of Canada as represented by the Minister of Natural Resources and Arnaud Droit, Paul Wilson, Gigi Pittoello, Susan Kutz.)

Population studies have shown that the infant's microbiome and metabolome undergo significant changes in early childhood. However, no previous study has investigated how diverse these changes are across subjects and whether the subject-specific dynamics of some microbes correlate with the over-time dynamics of specific metabolites. Using mixed-effects models, and data from the ABC study, we investigated the early childhood dynamics of fecal microbiome and metabolome and identified 83 amplicon sequence variants (ASVs) and 753 metabolites with seemingly coordinated trajectories. Enrichment analysis of these microbes and molecules revealed eight ASV families and 23 metabolite groups involving 1032 ASV-metabolite pairs with their presence-absence changing in a coordinated fashion. Members of the Lachnospiraceae (464/1032) and metabolites related to cholestane steroids (309/1032) dominated proportional shifts within the fecal microbiome and metabolome as infants aged., Competing Interests: Competing interests The authors declare no competing interests. Ethics approval and consent to participate The study was approved by the University of Michigan Institutional Review Board (HUM00103575). Mothers gave written informed consent for themselves and their infants. All ethical regulations relevant to human research participants were followed., (© 2024. The Author(s).)

Here, we describe "obelisks," a class of heritable RNA elements sharing several properties: (1) apparently circular RNA ∼1 kb genome assemblies, (2) predicted rod-like genome-wide secondary structures, and (3) open reading frames encoding a novel "Oblin" protein superfamily. A subset of obelisks includes a variant hammerhead self-cleaving ribozyme. Obelisks form their own phylogenetic group without detectable similarity to known biological agents. Surveying globally, we identified 29,959 distinct obelisks (clustered at 90% sequence identity) from diverse ecological niches. Obelisks are prevalent in human microbiomes, with detection in ∼7% (29/440) and ∼50% (17/32) of queried stool and oral metatranscriptomes, respectively. We establish Streptococcus sanguinis as a cellular host of a specific obelisk and find that this obelisk's maintenance is not essential for bacterial growth. Our observations identify obelisks as a class of diverse RNAs of yet-to-be-determined impact that have colonized and gone unnoticed in human and global microbiomes., Competing Interests: Declaration of interests The authors declare no competing interests., (Copyright © 2024 Elsevier Inc. All rights reserved.)

During the coronavirus disease 2019 (COVID-19) pandemic, the exploration of microecology has been essential for elucidating the intricacies of infection mechanisms and the recovery of afflicted individuals. To decipher the interplay of microorganisms between the intestinal and respiratory tracts, we collected sputum and throat swabs and feces from COVID-19 patients and explored the mutual migration among intestinal and respiratory microorganisms. Using next-generation sequencing (NGS) technology, we investigated intestinal and respiratory microorganism intermigration in two patients with severe COVID-19 during their hospitalization. Notably, we observed an expedited recovery of microecological equilibrium in one patient harboring Mycobacterium avium. Comparative analyses between 32 healthy controls and 110 COVID-19 patients with different disease severities revealed alterations in predominant microorganisms inhabiting the respiratory and intestinal tracts of COVID-19 patients. Among the alterations, intestinal Bacteroides vulgatus (BV) was identified as a noteworthy microorganism that exhibited marked enrichment in patients with severe COVID-19. BV, when highly abundant, may inhibit the transitional growth of Escherichia coli/Enterococcus, indirectly prevent the overgrowth of salivary streptococci, and maintain lung/intestinal microecology stability. In summary, this study elucidates the bidirectional microbial intermigration between the intestinal and respiratory tracts in COVID-19 patients. These findings are expected to provide new ideas for the treatment and management of COVID-19, underscoring the essential role of microecology in infectious diseases. Nevertheless, a systematic study of the roles of BV in recovery from infection is required to gain a deeper understanding of the mechanisms of microbial migration., Competing Interests: Competing interests The authors declare no competing interests. Ethics statement This study conformed to the provisions of the Helsinki Declaration of 1975 (as revised in 2008) concerning human rights and was approved by the ethics committee at the First Affiliated Hospital of Guangzhou Medical University, China (ethical approval number: 2020-36). All patients provided written informed consent and volunteered to participate in the scientific research., (© 2024. The Author(s).)

The functions of non-coding small RNAs (sRNAs) within the human microbiome remain largely unexplored. In this Cell Host & Microbe issue, El Mouali et al. identify Segatella RNA colonization factor (SrcF), a sRNA from a prevalent gut bacterium Segatella copri. SrcF promotes colonization of S. copri by regulating bacterial degradation of complex dietary carbohydrates., Competing Interests: Declaration of interests M.S.D. works as a consultant and an advisory board member at Theralution GmbH, Germany., (Copyright © 2024 Elsevier Inc. All rights reserved.)

The bacterium Segatella copri is a prevalent member of the human gut microbiota associated with health and disease states. However, the intrinsic factors that determine its ability to colonize the gut effectively remain largely unknown. By extensive transcriptome mapping of S. copri and examining human-derived samples, we discover a small RNA, which we name Segatella RNA colonization factor (SrcF), and show that SrcF is essential for S. copri gut colonization in gnotobiotic mice. SrcF regulates genes involved in nutrient acquisition, and complex carbohydrates, particularly fructans, control its expression. Furthermore, SrcF expression is strongly influenced by human microbiome composition and by the breakdown of fructans by cohabitating commensals, suggesting that the breakdown of complex carbohydrates mediates interspecies signaling among commensals beyond its established function in generating energy. Together, this study highlights the contribution of a small RNA as a critical regulator in gut colonization., Competing Interests: Declaration of interests The authors declare no competing interests., (Copyright © 2024 The Author(s). Published by Elsevier Inc. All rights reserved.)

Background: Despite the growing number of studies investigating the connection between host genetics and the rumen microbiota, there remains a dearth of systematic research exploring the composition, function, and metabolic traits of highly heritable rumen microbiota influenced by host genetics. Furthermore, the impact of these highly heritable subsets on lactation performance in cows remains unknown. To address this gap, we collected and analyzed whole-genome resequencing data, rumen metagenomes, rumen metabolomes and short-chain fatty acids (SCFAs) content, and lactation performance phenotypes from a cohort of 304 dairy cows., Results: The results indicated that the proportions of highly heritable subsets (h 2  ≥ 0.2) of the rumen microbial composition (55%), function (39% KEGG and 28% CAZy), and metabolites (18%) decreased sequentially. Moreover, the highly heritable microbes can increase energy-corrected milk (ECM) production by reducing the rumen acetate/propionate ratio, according to the structural equation model (SEM) analysis (CFI = 0.898). Furthermore, the highly heritable enzymes involved in the SCFA synthesis metabolic pathway can promote the synthesis of propionate and inhibit the acetate synthesis. Next, the same significant SNP variants were used to integrate information from genome-wide association studies (GWASs), microbiome-GWASs, metabolome-GWASs, and microbiome-wide association studies (mWASs). The identified single nucleotide polymorphisms (SNPs) of rs43470227 and rs43472732 on SLC30A9 (Zn 2+ transport) (P < 0.05/nSNPs) can affect the abundance of rumen microbes such as Prevotella&#95;sp., Prevotella&#95;sp.&#95;E15-22, Prevotella&#95;sp.&#95;E13-27, which have the oligosaccharide-degradation enzymes genes, including the GH10, GH13, GH43, GH95, and GH115 families. The identified SNPs of chr25:11,177 on 5s&#95;rRNA (small ribosomal RNA) (P < 0.05/nSNPs) were linked to ECM, the abundance alteration of Pseudobutyrivibrio&#95;sp. (a genus that was also showed to be linked to the ECM production via the mWASs analysis), GH24 (lysozyme), and 9,10,13-TriHOME (linoleic acid metabolism). Moreover, ECM, and the abundances of Pseudobutyrivibrio sp., GH24, and 9,10,13-TRIHOME were significantly greater in the GG genotype than in the AG genotype at chr25:11,177 (P < 0.05). By further the SEM analysis, GH24 was positively correlated with Pseudobutyrivibrio sp., which was positively correlated with 9,10,13-triHOME and subsequently positively correlated with ECM (CFI = 0.942)., Conclusion: Our comprehensive study revealed the distinct heritability patterns of rumen microbial composition, function, and metabolism. Additionally, we shed light on the influence of host SNP variants on the rumen microbes with carbohydrate metabolism and their subsequent effects on lactation performance. Collectively, these findings offer compelling evidence for the host-microbe interactions, wherein cows actively modulate their rumen microbiota through SNP variants to regulate their own lactation performance. Video Abstract., Competing Interests: Declarations Ethics approval and consent to participate This experiment was conducted at the Animal Research and Technology Centre of Northwest A&F University (Yangling, Shaanxi, China). All analyses were performed in accordance with the guidelines recommended by the Administration of Affairs Concerning Experimental Animals (Ministry of Science and Technology, China, revised 2004). The protocol was approved by the Institutional Animal Care and Use Committee of Northwest A&F University. Consent for publication Not applicable. Competing interests The authors declare no competing interests., (© 2024. The Author(s).)

Bacteroides species are abundant, prevalent, and stable members of the human gut microbiota, making them a promising chassis for developing long-term interventions for chronic diseases. Engineering Bacteroides as in situ bio-factories, however, requires efficient protein secretion tools, which are currently lacking. Here, we systematically investigate methods to enable heterologous protein secretion in Bacteroides. We identify a collection of secretion carriers that can export functional proteins across multiple Bacteroides species at high titers. To understand the mechanistic drivers of Bacteroides secretion, we characterize signal peptide sequence features, post-secretion extracellular fate, and the size limit of protein cargo. To increase titers and enable flexible control of protein secretion, we develop a strong, self-contained, inducible expression circuit. Finally, we validate the functionality of our secretion carriers in vivo in a mouse model. This toolkit promises to enable expanded development of long-term living therapeutic interventions for chronic gastrointestinal disease., Competing Interests: Competing interests Y.H.Y. and S.J.S. have filed a patent application on the molecular toolkit developed in this study for heterologous protein secretion across Bacteroides species (PCT/US2023/083131). Other authors claim no competing interests., (© 2024. The Author(s).)

Crosstalk between the microbiome and gut mucosa-resident immune cells plays a pivotal role in modulating immune responses to pathogens, including responses to HIV infection. However, how these interactions may differ between young men who have sex with men (YMSM) disproportionately impacted by HIV, as compared with older adult MSM (AMSM), is not well understood. A broad analysis of associations between the microbiome and rectal transcriptome revealed 10 microbial families/genera correlated with immunologic gene pathways. Specifically, the rectal transcriptome of YMSM was characterized by upregulation of T cell activation/differentiation pathways and signaling from multiple cytokine families compared with AMSM. The microbiome of YMSM was enriched with pathogenic genera, including Peptostreptococcus, shown to be positively correlated with type I IFN pathways important for antiviral immunity. These findings demonstrate that YMSM have a unique immune phenotype and rectal microenvironment and support further evaluation of biological factors that influence rectal HIV transmission.

Assembly of the mammalian gut microbiota during early life is known to shape key aspects of organismal development, including immunity, metabolism and behaviour. While house mice (Mus musculus) are the major laboratory model organism for gut microbiota research, their artificial lab-based lifestyle could fundamentally alter ecological processes of microbiota assembly and dynamics, in ways that affect their usefulness as a model system. To examine this, here we directly compared patterns of gut microbiota assembly in house mice from the lab and from the wild, making use of a tractable, individually-marked wild population where we could examine patterns of gut microbiota assembly during early life. Despite lab and wild mice harbouring taxonomically distinct communities, we identify striking similarities in multiple patterns of their gut microbiota assembly. Specifically, age-related changes in both alpha and beta diversity, as well as the abundance of predominant phyla and aerotolerance of the microbiota followed parallel trajectories in both settings. These results suggest some degree of intrinsic programme in gut microbiota assembly that transcends variation in taxonomic profiles, and the genetic and environmental background of the host. They further support the notion that despite their artificial environment, lab mice can provide meaningful insights into natural microbiota ecological dynamics in early life and their interplay with host development., (© 2024. The Author(s).)

While the ruminant gut archaeome regulates the gut microbiota and hydrogen balance, it is also a major producer of the greenhouse gas methane. However, ruminant gut archaeome diversity within the gastrointestinal tract (GIT) of ruminant animals worldwide remains largely underexplored. Here, we construct a catalogue of 998 unique archaeal genomes recovered from the GITs of ruminants, utilizing 2270 metagenomic samples across 10 different ruminant species. Most of the archaeal genomes (669/998 = 67.03%) belong to Methanobacteriaceae and Methanomethylophilaceae (198/998 = 19.84%). We recover 47/279 previously undescribed archaeal genomes at the strain level with completeness of >80% and contamination of <5%. We also investigate the archaeal gut biogeography across various ruminants and demonstrate that archaeal compositional similarities vary significantly by breed and gut location. The catalogue contains 42,691 protein clusters, and the clustering and methanogenic pathway analysis reveal strain- and host-specific dependencies among ruminant animals. We also find that archaea potentially carry antibiotic and metal resistance genes, mobile genetic elements, virulence factors, quorum sensors, and complex archaeal viromes. Overall, this catalogue is a substantial repository for ruminant archaeal recourses, providing potential for advancing our understanding of archaeal ecology and discovering strategies to regulate methane production in ruminants., (© 2024. The Author(s).)

The rapid advancements in sequencing technologies and bioinformatics have enabled metagenomic research of complex microbial systems, but reliable results depend on consistent laboratory and bioinformatics approaches. Current efforts to identify best practices often focus on optimizing specific steps, making it challenging to understand the influence of each stage on microbial population analysis and compare data across studies. This study evaluated DNA extraction, library construction methodologies, sequencing platforms, and computational approaches using a dog stool sample, two synthetic microbial community mixtures, and various sequencing data sources. Our work, the most comprehensive evaluation of metagenomic methods to date. We developed a software tool, termed minitax, which provides consistent results across the range of platforms and methodologies. Our findings showed that the Zymo Research Quick-DNA HMW MagBead Kit, Illumina DNA Prep library preparation method, and the minitax bioinformatics tool were the most effective for high-quality microbial diversity analysis. However, the effectiveness of pipelines or method combinations is sample-specific, making it difficult to identify a universally optimal approach. Therefore, employing multiple approaches is crucial for obtaining reliable outcomes in microbial systems., (© 2024. The Author(s).)

Mounting evidence has revealed the association between gut microbiota and both chronic obstructive pulmonary disease (COPD) and asthma; however, the causal association between gut microbiota and specific disease phenotypes remains to be determined. This study employed bidirectional two-sample Mendelian randomization (MR) analyses to investigate the potential causal relationship between gut microbiota and these conditions. The research utilized genome-wide association study (GWAS) data from the MiBioGen consortium for gut microbiota and the integrative epidemiology unit (IEU) Open GWAS for these conditions. Four MR analysis methods were employed: the inverse variance weighted (IVW) test, MR-Egger, weighted median, and weighted mode methods. The IVW method results are considered the primary findings. Sensitivity analyses, including heterogeneity tests, horizontal pleiotropy analysis, and leave-one-out analysis, were used to enhance robustness. Our MR study identified eight gut microbiota taxa potentially associated with the risk of different types of COPD and asthma. These include two taxa for early-onset COPD: Streptococcaceae [odds ratio (OR) = 1.315, 95% confidence interval (CI) = 1.071-1.616, P = 0.009] and Holdemanella (OR = 1.199, 95% CI = 1.063-1.352, P = 0.003); three for later-onset COPD: Acidaminococcaceae (OR = 1.312, 95% CI = 1.098-1.567, P = 0.003), Holdemania (OR = 1.165, 95% CI = 1.039-1.305, P = 0.009), and Marvinbryantia (OR = 0.814, 95% CI = 0.697-0.951, P = 0.009); one for allergic asthma: Butyricimonas (OR = 0.794, 95% CI = 0.693-0.908, P = 0.001); and two for non-allergic asthma: Clostridia (OR = 1.255, 95% CI = 1.043-1.511, P = 0.016) and Clostridiales (OR = 1.256, 95% CI = 1.048-1.506, P = 0.014).IMPORTANCEIndividuals with diverse phenotypes of chronic obstructive pulmonary disease (COPD) and asthma exhibit different responses to the conventional "one treatment fits all" approach. Recent research has revealed the significant role of the gut-lung axis in both COPD and asthma. However, the specific impact of gut microbiota on different subtypes of these conditions remains poorly understood. Our study has identified eight gut microbiota that may be associated with the risk of different types of COPD and asthma. These findings provide evidence suggesting a potential causal relationship between gut microbiota and various phenotypes of COPD and asthma. This offers a new perspective on the origins of different disease phenotypes and points toward future exploration of phenotype-specific and personalized therapies., Competing Interests: The authors declare no conflict of interest.

The circadian oscillation of gut microbiota plays vital roles in the normal physiology and health of the host. Although the diurnal oscillation of intestinal bacteria has been extensively studied, little relevant work has been done on intestinal fungi. Besides, the rhythmic correlations between bacterial and fungal microbes are also scarcely reported. Here, we investigated the diurnal oscillations of bacterial and fungal communities in male cynomolgus monkeys by performing 16S rRNA and ITS amplicon sequencing. As for bacterial genera, we found that the relative abundance of Prevotella , norank&#95;f&#95;Eubacterium&#95;coprostanoligenes&#95;group, and Peptococcus underwent significant changes at ZT12 (19:00) and exhibited obvious rhythmic oscillations. Consequently, most of the bacterial functions varied at ZT12 and were positively correlated with the bacterial genera norank&#95;f&#95;Eubacterium&#95;coprostanoligenes&#95;group and Prevotella . Among the fungal genera, the relative abundance of Aspergillus and Talaromyces decreased at ZT18 (1:00) and showed slight rhythmic oscillations. As for the fungal function, the undefined saprotroph showed slight rhythmic oscillation and was positively correlated with the fungal genus Aspergillus . Notably, we characterized the correlations between intestinal bacteria and fungi every 6 h over the course of a day and found that the bacterial and fungal microbes interacted closely, with the most bacteria-fungi interactions occurring at ZT12. Our study contributed to a more comprehensive understanding of the diurnal oscillation patterns of bacterial and fungal microbes in male cynomolgus monkeys and uncovered their correlations during a diurnal cycle., Importance: The rhythmic oscillation of gut microbiota can impact the physiology activity and disease susceptibility of the host. Until now, most of the studies are focused on bacterial microbes, ignoring other components of gut microbes, such as fungal microbes (mycobiota). Besides, only few studies have addressed the rhythmic correlations between gut bacteria and fungi. Here, we analyzed the rhythmic oscillations of bacterial and fungal communities in male cynomolgus monkeys by performing 16S rRNA and ITS amplicon sequencing. Apart from identifying the rhythmically oscillated bacterial and fungal microbes, we conducted the correlation analysis between these two microbial communities and found that the intestinal bacteria and fungi exhibited close interactions rhythmically, with the most interactions occurring at ZT12. Thus, our study not only investigated the rhythmic oscillations of gut bacterial and fungal communities in male cynomolgus monkeys but also uncovered their rhythmic interactions., Competing Interests: The authors declare no conflict of interest.

With the development of sequencing technology and analytic tools, studying within-species variations enhances the understanding of microbial biological processes. Nevertheless, most existing methods designed for strain-level analysis lack the capability to concurrently assess both strain proportions and genome-wide single nucleotide variants (SNVs) across longitudinal metagenomic samples. In this study, we introduce LongStrain, an integrated pipeline for the analysis of large-scale metagenomic data from individuals with longitudinal or repeated samples. In LongStrain, we first utilize two efficient tools, Kraken2 and Bowtie2, for the taxonomic classification and alignment of sequencing reads, respectively. Subsequently, we propose to jointly model strain proportions and shared haplotypes across samples within individuals. This approach specifically targets tracking a primary strain and a secondary strain for each subject, providing their respective proportions and SNVs as output. With extensive simulation studies of a microbial community and single species, our results demonstrate that LongStrain is superior to two genotyping methods and two deconvolution methods across a majority of scenarios. Furthermore, we illustrate the potential applications of LongStrain in the real data analysis of The Environmental Determinants of Diabetes in the Young study and a gastric intestinal metaplasia microbiome study. In summary, the proposed analytic pipeline demonstrates marked statistical efficiency over the same type of methods and has great potential in understanding the genomic variants and dynamic changes at strain level. LongStrain and its tutorial are freely available online at https://github.com/BoyanZhou/LongStrain., Importance: The advancement in DNA-sequencing technology has enabled the high-resolution identification of microorganisms in microbial communities. Since different microbial strains within species may contain extreme phenotypic variability (e.g., nutrition metabolism, antibiotic resistance, and pathogen virulence), investigating within-species variations holds great scientific promise in understanding the underlying mechanism of microbial biological processes. To fully utilize the shared genomic variants across longitudinal metagenomics samples collected in microbiome studies, we develop an integrated analytic pipeline (LongStrain) for longitudinal metagenomics data. It concurrently leverages the information on proportions of mapped reads for individual strains and genome-wide SNVs to enhance the efficiency and accuracy of strain identification. Our method helps to understand strains' dynamic changes and their association with genome-wide variants. Given the fast-growing longitudinal studies of microbial communities, LongStrain which streamlines analyses of large-scale raw sequencing data should be of great value in microbiome research communities., Competing Interests: The authors declare no conflict of interest.

Metagenome-assembled genomes (MAGs) have contributed to identifying non-culturable microorganisms and understanding their ecological functions. MAGs offer an advantage in investigating sporulation-associated genes, especially given the difficulty of isolating many species residing in the gut microbiota of multiple hosts. Bacterial sporulation is a key survival mechanism with implications for pathogenicity and biotechnology. Here, we investigate MAGs from vertebrate hosts, emphasizing taxonomic identification and identifying sporulation-associated genes in potential novel species within the Firmicutes phylum. We identified potential new species in the classes Clostridia ( Borkfalkiaceae , Lachnospiraceae , Monoglobaceae , and Oscillospiraceae families) and Bacilli ( Bacillaceae and Erysipelotrichaceae families) through phylogenetic and functional pathway analyses, highlighting their sporulation potential. Our study covers 146 MAGs, 124 of them without refined taxonomic assignments at the family level. We found that Clostridia and Bacilli have unique sporulation gene profiles in the refined family MAGs for cattle, swine, poultry, and human hosts. The presence of genes related to Spo0A regulon, engulfment, and spore cortex in MAGs underscores fundamental mechanisms in sporulation processes in currently uncharacterized species with sporulation potential from metagenomic dark matter. Furthermore, genomic analyses predict sporulation potential based on gene presence, genome size, and metabolic pathways involved in spore formation. We emphasize MAGs covering families not yet characterized through the phylogenetic analysis, and with extensive potential for spore-forming bacteria within Clostridia , Bacilli , UBA4882, and UBA994 classes. These findings contribute to exploring spore-forming bacteria, which provides evidence for novel species diversity in multiple hosts, their adaptive strategies, and potential applications in biotechnology and host health.IMPORTANCESpores are essential for bacterial survival in harsh environments, facilitating their persistence and adaptation. Exploring sporulation-associated genes in metagenome-assembled genomes (MAGs) from different hosts contributes to clinical and biotechnological domains. Our study investigated the extent of genes associated with bacterial sporulation in MAGs from poultry, swine, cattle, and humans, revealing these genes in uncultivated bacteria. We identified potential novel Firmicutes species with sporulation capabilities through phylogenetic and functional analyses. Notably, MAGs belonging to Clostridia , Bacilli , and unknown classes, namely UBA4882 and UBA994, remained uncharacterized at the family level, which raises the hypothesis that sporulation would also be present in these genomes. These findings contribute to our understanding of microbial adaptation and have implications for microbial ecology, underlining the importance of sporulation in Firmicutes across different hosts. Further studies into novel species and their sporulation capability can contribute to bacterial maintenance mechanisms in various organisms and their applications in biotechnology studies., Competing Interests: A.C.G. has recently received research funding and/or consultation fees from Enthasis, Eurofarma, MSD, Pfizer, Sandoz, and United Medical. Other authors have nothing to declare. This study was not financially supported by any Diagnostic/Pharmaceutical company.

Low-abundance members of microbial communities are difficult to study in their native habitats, including Escherichia coli, a minor but common inhabitant of the gastrointestinal tract, and key opportunistic pathogen of the urinary tract. While multi-omic analyses have detailed interactions between uropathogenic Escherichia coli (UPEC) and the bladder mediating urinary tract infection (UTI), little is known about UPEC in its pre-infection reservoir, the gastrointestinal tract, partly due to its low relative abundance (<1%). To sensitively explore the genomes and transcriptomes of diverse gut E. coli, we develop E. coli PanSelect, which uses probes designed to specifically capture E. coli's broad pangenome. We demonstrate its ability to enrich diverse E. coli by orders of magnitude, in a mock community and in human stool from a study investigating recurrent UTI (rUTI). Comparisons of transcriptomes between gut E. coli of women with and without history of rUTI suggest rUTI gut E. coli are responding to increased oxygen and nitrate, suggestive of mucosal inflammation, which may have implications for recurrent disease. E. coli PanSelect is well suited for investigations of in vivo E. coli biology in other low-abundance environments, and the framework described here has broad applicability to other diverse, low-abundance organisms., (© 2024. The Author(s).)

Background: Gastrointestinal symptoms are now detected early in the clinical course of many dementia patients, and studies of the microbiome-gut-brain axis have confirmed bidirectional interactions between the gut and the brain. However, the causal relationship between gut microbiota and cognitive impairment has not been fully established. Therefore, this study conducted a bidirectional Mendelian randomization study to elucidate the potential causal relationship of gut microbiota to cognitive impairment. Objective: Using Mendelian randomization to identify gut flora with a genetic causal effect on the development of cognitive impairment. Methods: This study utilized publicly available genome-wide association study summary data to perform MR analysis, with gut microbiota as the exposure and various cognitive function indicators as well as scores for Alzheimer's disease as outcomes. This study selected single nucleotide polymorphisms as instrumental variables based on p-values, F-statistics, and r 2 . Bidirectional Mendelian randomization was conducted using methods such as inverse variance weighted, MR-Egger, simple mode, and weighted mode to assess the causal relationship. Concurrently, this study carried out Cochran's Q test, MR-Egger intercept test, and leave-one-out analysis to identify potential heterogeneity and horizontal pleiotropy. Results: This study identified a total of 31 gut microbes that have a causal relationship with cognitive impairment, which include 1 phylum, 4 classes, 3 orders, 2 families, and 21 genera. Conclusions: This study unveiled specific gut microbiota associated with cognitive impairment, offering new insights and approaches for the prevention and treatment of cognitive impairment through gut microbiota such as Bifidobacterium and Ruminococcus gnavus group., Competing Interests: Declaration of conflicting interestsThe author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Background/aim: Host microbiota dysbiosis has been recognized as a key factor in lung cancer. However, the specific diversity and composition of microbiota in lung cancer patients remain unknown. This single-center prospective observational study analyzed both saliva and fecal samples from 74 participants [lung cancer (LC) patients: n=53; lung inflammation (LI) patients: n=11; healthy control (HC): n=10]., Patients and Methods: We performed 16S ribosomal RNA gene sequencing and analyzed the associations between oral and gut microbiota diversity and composition across the three groups., Results: Alpha diversity of the oral microbiota was significantly lower in the LC group than in the HC group (Chao 1, p=0.004; Simpson, p=0.018; Shannon, p=0.009). Beta diversity of both oral and gut microbiota showed significant differences among the three groups (PERMANOVA, oral: p=0.005; gut: p=0.002). Compositional differences in the oral microbiota were observed between the HC and LC or LI groups; in particular, Bacilli class, Streptococcaceae family, Streptococcus genus, Firmicutes phylum, and Lactobacillales order were more abundant in the LC group. Additionally, six oral-related microbiota showed significant abundance in the gut of the LC group (p=0.00182)., Conclusion: The oral microbiota in lung cancer patients is significantly different from that in healthy individuals. Specific changes in oral microbiota and oral-related gut microbiota compositions were evident in lung cancer patients. These findings might be useful for identifying novel biomarkers to predict the risk of lung cancer and prevent the disease., (Copyright © 2024 International Institute of Anticancer Research (Dr. George J. Delinasios), All rights reserved.)

The microbes, nutrients and toxins that we are exposed to can have a profound effect on the composition and function of the gut microbiome. Thousands of peer-reviewed publications link microbiome composition and function to health from the moment of birth, right through to centenarians, generating a tantalizing glimpse of what might be possible if we could intervene rationally. Nevertheless, there remain relatively few real-world examples where successful microbiome engineering leads to beneficial health effects. Here we aim to provide a framework for the progress needed to turn gut microbiome engineering from a trial-and-error approach to a rational medical intervention. The workflow starts with truly understanding and accurately diagnosing the problems that we are trying to fix, before moving on to developing technologies that can achieve the desired changes., Competing Interests: Disclosure and competing interests statement European patent applications EP19177251 and EP22186078 are held by ES and MD. There are no other disclosures or competing financial interests., (© 2024. The Author(s).)

The rodent gut microbiota is a known reservoir of antimicrobial resistance, yet the distribution of antibiotic resistance genes (ARGs) within rodent cecal microbial communities and the specific bacterial species harboring these ARGs remain largely underexplored. This study employed high-throughput sequencing of 122 samples from five distinct rodent species to comprehensively profile the diversity and distribution of ARGs and to identify the bacterial hosts of these genes. A gene catalog of the rodent cecal microbiome was constructed, comprising 22,757,369 non-redundant genes. Analysis of the microbial composition and diversity revealed that Bacillota and Bacteroidota were the dominant bacterial phyla across different rodent species, with significant variations in species composition among the rodents. In total, 3703 putative antimicrobial resistance protein-coding genes were identified, corresponding to 392 unique ARG types classified into 32 resistance classes. The most enriched ARGs in the rodent cecal microbiome were associated with multidrug resistance, followed by glycopeptide and elfamycin antibiotics. Procrustes analysis demonstrated a correlation between the structure of the microbial community and the resistome. Metagenomic assembly-based host tracking indicated that most ARG-carrying contigs originated from the bacterial family Oscillospiraceae. Additionally, 130 ARGs showed significant correlations with mobile genetic elements. These findings provide new insights into the cecal microbiota and the prevalence of ARGs across five rodent species. Future research on a wider range of wild rodent species carrying ARGs will further elucidate the mechanisms underlying the transmission of antimicrobial resistance., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024. Published by Elsevier Inc.)

To ensure sustainable aquaculture, it is essential to understand the path 'from feed to fish', whereby the gut microbiome plays an important role in digestion and metabolism, ultimately influencing host health and growth. Previous work has reported the taxonomic composition of the Atlantic salmon (Salmo salar) gut microbiome; however, functional insights are lacking. Here we present the Salmon Microbial Genome Atlas consisting of 211 high-quality bacterial genomes, recovered by cultivation (n = 131) and gut metagenomics (n = 80) from wild and farmed fish both in freshwater and seawater. Bacterial genomes were taxonomically assigned to 14 different orders, including 35 distinctive genera and 29 previously undescribed species. Using metatranscriptomics, we functionally characterized key bacterial populations, across five phyla, in the salmon gut. This included the ability to degrade diet-derived fibres and release vitamins and other exometabolites with known beneficial effects, which was supported by genome-scale metabolic modelling and in vitro cultivation of selected bacterial species coupled with untargeted metabolomic studies. Together, the Salmon Microbial Genome Atlas provides a genomic and functional resource to enable future studies on salmon nutrition and health., (© 2024. The Author(s), under exclusive licence to Springer Nature Limited.)

Avian migration is an intrinsic biological phenomenon that involves trans-boundary movements to evade adverse ecological circumstances. During migration, avian gut bacterial taxa may serve as a potential source of bacterial dissemination via fecal contamination at stop-over sites. Therefore, bacterial taxa composition as well as diversities were investigated employing 16S rRNA sequencing in fecal samples collected from flocks of seven migratory avian species visiting southern districts of Khyber Pakhtunkhwa, Pakistan. The analysis revealed that Grus virgo exhibits the highest alpha diversity, followed by Aythya ferina while G. grus reflects lowest diversity among all the migratory avian fecal samples. The findings depicted significant variations in the bacterial beta diversities of migratory avifauna. At phylum level, Firmicutes, Proteobacteria, and Actinobacteriota showed the highest relative abundance in Plegadis falcinellus, Chlamydotis undulata and Aythya ferina respectively. Further exploration within phyla elucidates finer-scale taxonomic differences at the family and genus levels. This study identified potential pathogenic bacteria such as Staphylococcus, Streptococcus, Enterococcus, Proteus, Clostridium sensu stricto 1, Fusobacterium and Escherichia that offers valuable insight into the microbiological hazards associated with migratory birds. Although pathogenicity was not directly assessed, the observed relative abundance of opportunistic bacterial genera suggests continuous surveillance of gut bacterial community during migration to safeguard avian biodiversity and mitigate escalating threats of infection emergence and dissemination., Competing Interests: Declaration of competing interest The author has no conflict of interest exits in the submission of this manuscript and the authors have complied with journal ethical requirements. Moreover, manuscript is approved by all authors as well as all the authorities acknowledged for publication., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Crib-biting is a stereotyped oral behavior with poorly understood etiology and pathophysiology. The relationship between the gut microbiome and brain function has been described in behavioral disorders such as schizophrenia, depression and anxiety in humans. In horses, studies of behavioral problems and the microbiome are very limited. This study aimed to characterize the fecal microbiome and the predicted functional profile of horses with and without aerophagia. Fecal samples were collected from 12 Colombian Creole Horses of both sexes, divided into two groups: group 1, composed of six horses with crib-biting (3 females and 3 males), average body weight of 330 ± 10 kg, age of 7.0 ± 1.2 years and body condition score (BCS) of 5/9 ± 1 and group 2, consisting of six horses without crib-biting (3 females and 3 males), average body weight of 335 ± 5 kg, age 6.5 ± 1 years and BCS of 6/9 ± 1. From each horse in both groups fecal total DNA was obtained and 16S ribosomal RNA gene amplicons were sequenced to characterize the bacterial community structure. Community structure and differential abundance analyses revealed significant differences between the two conditions (p < 0.05). Specifically, the fecal microbiota at the family level in crib-biting horses, showing a decrease in Bacteroidales and an increase in Bacillota and Clostridia, differed from that of healthy horses without crib-biting, consistent with findings from previous studies. Furthermore, metagenome prediction suggests metabolic profile changes in bacterial communities between both conditions in horses. Further studies are required to validate the role of the microbiota-gut-brain axis in the etiology of crib-biting and other abnormal and stereotyped behaviors., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024. Published by Elsevier Inc.)

Colorectal cancer (CRC) ranks as the third most common cancer globally and the second leading cause of cancer-related deaths. Recent research highlights the pivotal role of the gut microbiota in CRC development and progression. Understanding the complex interplay between disease development and metagenomic data is essential for CRC diagnosis and treatment. Current computational models employ machine learning to identify metagenomic biomarkers associated with CRC, yet there is a need to improve their accuracy through a holistic biological knowledge perspective. This study aims to evaluate CRC-associated metagenomic data at species, enzymes, and pathway levels via conducting global and population-specific analyses. These analyses utilize relative abundance values from human gut microbiome sequencing data and robust classification models are built for disease prediction and biomarker identification. For global CRC prediction and biomarker identification, the features that are identified by SelectKBest (SKB), Information Gain (IG), and Extreme Gradient Boosting (XGBoost) methods are combined. Population-based analysis includes within-population, leave-one-dataset-out (LODO) and cross-population approaches. Four classification algorithms are employed for CRC classification. Random Forest achieved an AUC of 0.83 for species data, 0.78 for enzyme data and 0.76 for pathway data globally. On the global scale, potential taxonomic biomarkers include ruthenibacterium lactatiformanas; enzyme biomarkers include RNA 2' 3' cyclic 3' phosphodiesterase; and pathway biomarkers include pyruvate fermentation to acetone pathway. This study underscores the potential of machine learning models trained on metagenomic data for improved disease prediction and biomarker discovery. The proposed model and associated files are available at https://github.com/TemizMus/CCPRED., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Introduction: Previous studies have established a link between gut microbiota and polycystic ovary syndrome (PCOS), but little is known about their precise causal relationship. Therefore, this study aims to explore whether there are precise causal relationships between gut microbiota and PCOS., Material and Methods: We performed a bidirectional two-sample Mendelian randomization (MR) analysis. Datasets were from the largest published meta-analysis on gut microbiota composition and the FinnGen cohort of the IEU Open Genome-Wide Association Study Project database. Inverse variance weighted (IVW), MR-Egger, constrained maximum likelihood-based Mendelian randomization, weighted median, weighted mode, and simple mode were used. Cochran's Q and MR-Egger intercept tests were employed to measure the heterogeneity., Results: A total of 211 gut microbiota taxa were identified in MR analysis. Nine taxa of bacteria, including Alphaproteobacteria (0.55, 0.30-0.99, p = 0.04), Bacilli (1.76, 1.07-2.91, p = 0.03), Bilophila (0.42, 0.23-0.77, p < 0.01), Blautia (0.16, 0.03-0.79, p = 0.02), Burkholderiales (2.37, 1.22-4.62, p = 0.01), Candidatus Soleaferrea (0.65, 0.43-0.98, p = 0.04), Cyanobacteria (0.51, 0.31-0.83, p = 0.01), Holdemania (0.53, 0.35-0.81, p < 0.01), and Lachnospiraceae (1.86, 1.04-3.35, p = 0.03), were found to be associated with PCOS in the above MR methods included at least IVW method. Cochran's Q statistics and MR-Egger intercept test suggested no significant heterogeneity. In addition, 69 taxa were shown significant for at least the IVW method in reverse MR analysis, of these, 25 had a positive correlation, and 37 had a negative correlation. Additionally, Alphaproteobacteria and Lachnospiraceae (0.95, 0.91-0.98, p < 0.01; 0.97, 0.94-0.99, p = 0.02, respectively) were shown a bidirected causally association with PCOS., Conclusions: Our study provides evidence of the bidirectional causal association between gut microbiota and PCOS from a genetic perspective., (© 2024 The Author(s). Acta Obstetricia et Gynecologica Scandinavica published by John Wiley & Sons Ltd on behalf of Nordic Federation of Societies of Obstetrics and Gynecology (NFOG).)

Intratumoral microbiota and host genes interact to promote gastrointestinal disorders, but how the two interact to influence host tumorigenesis remains unclear. Here, we utilized a machine learning-based framework to jointly dissect the paired intratumoral microbiome and host transcriptome profiles in patients with colon adenocarcinoma, hepatocellular carcinoma, and gastric cancer. We identified associations between intratumoral microbes and host genes that depict shared as well as cancer type-specific patterns. We found that a common set of host genes and pathways implicated in cell proliferation and energy metabolism are associated with cancer type-specific intratumoral microbes. In addition, we also found that intratumoral microbes that have been implicated in three gastrointestinal tumors, such as Lachnoclostridium , are correlated with different host pathways in each tumor, indicating that similar microbes can influence host tumorigenesis in a cancer type-specific manner by regulation of different host genes. Our study reveals patterns of association between intratumoral microbiota and host genes in gastrointestinal tumors, providing new insights into the biology of gastrointestinal tumors. NEW & NOTEWORTHY Our study constitutes a pivotal advancement in elucidating the intricate relationship between the intratumoral microbiome and host gene regulation, thereby gaining insights into the pivotal role that the intratumoral microbiome plays in the etiology of gastrointestinal tumors.

Background: The increasing incidence of antibiotic-associated diarrhoea (AAD) is a serious health care problem. Dysbiosis of the gut microbiota is suspected to play a role in the pathogenesis of AAD, but its impact on the clinical outcomes of patients remains unclear., Methods: Between May and October 2022, 210 patients with AAD admitted to a university hospital and 100 healthy controls were recruited. DNA extraction from stool specimens and shotgun sequencing were performed. Machine learning was conducted to assess profiling at different taxonomic levels and to select variables for multivariable analyses., Results: Patients were classified into two groups: Clostridioides difficile infection (CDI, n = 39) and non-CDI AAD (n = 171). The in-hospital mortality rate for the patients was 20.0%, but the presence of C. difficile in the gut microbiota was not associated with mortality. Machine learning showed that taxonomic profiling at the genus level best reflected patient prognosis. The in-hospital mortality of patients was associated with the relative abundance of specific gut microbial genera rather than alpha-diversity: each of the five genera correlated either positively (Enterococcus, Klebsiella, Corynebacterium, Pseudomonas, and Anaerofustis) or negatively (Bifidobacterium, Bacteroides, Streptococcus, Faecalibacterium, and Dorea). Genes for vancomycin resistance were significantly associated with in-hospital mortality in patients with AAD (adjusted hazard ratios, 2.45; 95% CI, 1.20-4.99)., Conclusion: This study demonstrates the potential utility of metagenomic studies of the gut microbial community as a biomarker for prognosis prediction in AAD patients., (Copyright © 2024 Elsevier Ltd and International Society of Antimicrobial Chemotherapy. All rights reserved.)

Understanding the emergence and spread of antibiotic resistance genes (ARGs) in wildlife is critical for the health of humans and animals from a "One Health" perspective. The gut microbiota serve as a reservoir for ARGs; however, it remains poorly understood how environmental and host genetic factors influence ARGs by affecting the gut microbiota. To elucidate this, we analyzed whole-genome resequencing data from 79 individuals of Brandt's vole in two geographic locations with different antibiotics usage, together with metabolomic data and shotgun sequencing data. A high diversity of ARGs (851 subtypes) was observed in vole's gut, with a large variation in ARG composition between individuals from Xilingol and Hulunbuir in China. The diversity and composition of ARGs were strongly correlated with variations in gut microbiota community structure. Genome-wide association studies revealed that 803 loci were significantly associated (P<5.05×10 -9 ) with 31 bacterial species, and bipartite networks identified 906 bacterial species-ARGs associations. Structural equation modeling analysis showed that host genetic factors, air temperature, and presence of pollutants (Bisphenol A) significantly affected gut microbiota community structure, which eventually regulated the diversity of ARGs. The present study advances our understanding of the complex host-environment interactions that underlie the spread of ARGs in the natural environments., (© 2024. Science China Press.)

Antimicrobial peptides (AMPs) offer a potential solution to the antibiotic crisis owing to their antimicrobial properties, and the human gut biome may be a source of these peptides. However, the potential AMPs and AMP resistance genes (AMPRGs) of gut microbes in different age groups have not been thoroughly assessed. Here, we investigated the potential development of AMPs and the distribution pattern of AMPRGs in the gut microbiome at different ages by analyzing the intestinal metagenomic data of healthy individuals at different life stages (CG: centenarians group n = 20; OAG: older adults group: n = 15; YG: young group: n = 15). Age-related increases were observed in the potential AMPs within the gut microbiome, with centenarians showing a greater diversity of these peptides. However, the gut microbiome of the CG group had a lower level of AMPRGs compared to that of the OAG group, and it was similar to the level found in the YG group. Additionally, conventional probiotic strains showed a significant positive correlation with certain potential AMPs and were associated with a lower detection of resistance genes. Furthermore, comparing potential AMPs with existing libraries revealed limited similarity, indicating that current machine learning models can identify novel peptides in the gut microbiota. These results indicate that longevity may benefit from the diversity of AMPs and lower resistance genes. Our findings help explain the age advantage of the centenarians and identify the potential for antimicrobial peptide biosynthesis in the human gut microbiome, offering insights into the development of antimicrobial peptide resistance and the screening of probiotic strains., (© The Author(s) 2024. Published by Oxford University Press on behalf of The Gerontological Society of America. All rights reserved. For commercial re-use, please contact reprints@oup.com for reprints and translation rights for reprints. All other permissions can be obtained through our RightsLink service via the Permissions link on the article page on our site—for further information please contact journals.permissions@oup.com.)

The spread of antibiotic resistance genes (ARGs), particularly those carried on plasmids, poses a major risk to global health. However, the extent and frequency of ARGs transfer in microbial communities among human, animal, and environmental sectors is not well understood due to a lack of effective tracking tools. We have developed a novel fluorescent tracing tool, CRISPR-AMRtracker, to study ARG transfer. It combines CRISPR/Cas9 fluorescence tagging, fluorescence-activated cell sorting, 16S rRNA gene sequencing, and microbial community analysis. CRISPR-AMRtracker integrates a fluorescent tag immediately downstream of ARGs, enabling the tracking of ARG transfer without compromising the host cell's antibiotic susceptibility, fitness, conjugation, and transposition. Notably, our experiments demonstrate that sfGFP-tagged plasmid-borne mcr-1 can transfer across diverse bacterial species within fecal samples. This innovative approach holds the potential to illuminate the dynamics of ARG dissemination and provide valuable insights to shape effective strategies in mitigating the escalating threat of antibiotic resistance., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Osteoporosis is a complex metabolic bone disease that severely undermines the quality of life and overall health of the elderly. While previous studies have established a close relationship between gut microbiome and host bone metabolism, the role of genetic factors has received less scrutiny. This research aims to identify potential taxa associated with various bone mineral density states, incorporating assessments of genetic factors. Fecal microbiome profiles from 605 individuals (334 females and 271 males) aged 55-65 from the Taizhou Imaging Study with osteopenia (n = 270, 170 women) or osteoporosis (n = 94, 85 women) or normal (n = 241, 79 women) were determined using shotgun metagenomic sequencing. The linear discriminant analysis was employed to identify differentially enriched taxa. Utilizing the Kyoto Encyclopedia of Genes and Genomes for annotation, functional pathway analysis was conducted to identify differentially metabolic pathways. Polygenic risk score for osteoporosis was estimated to represent genetic susceptibility to osteoporosis, followed by stratification and interaction analyses. Gut flora diversity did not show significant differences among various bone mineral groups. After multivariable adjustment, certain species, such as Clostridium leptum, Fusicatenibacter saccharivorans and Roseburia hominis, were enriched in osteoporosis patients. Statistically significant interactions between the polygenic risk score and taxa Roseburia faecis, Megasphaera elsdenii were observed (P for interaction = 0.005, 0.018, respectively). Stratified analyses revealed a significantly negative association between Roseburia faecis and bone mineral density in the low-genetic-risk group (β = -0.045, P < 0.05), while Turicimonas muris was positively associated with bone mineral density in the high-genetic-risk group (β = 4.177, P < 0.05) after multivariable adjustments. Functional predictions of the gut microbiome indicated an increase in pathways related to structural proteins in high-genetic-risk patients, while low-genetic-risk patients exhibited enrichment in enzyme-related pathways. This study emphasizes the association between gut microbes and bone mass, offering new insights into the interaction between genetic background and gut microbiome., Competing Interests: Declaration of competing interest The authors have no disclosures or conflicts of interest to declare., (Copyright © 2024 Elsevier Inc. All rights reserved.)

The human gut microbiome plays a vital role in preserving individual health and is intricately involved in essential functions. Imbalances or dysbiosis within the microbiome can significantly impact human health and are associated with many diseases. Several metaproteomics platforms are currently available to study microbial proteins within complex microbial communities. In this study, we attempted to develop an integrated pipeline to provide deeper insights into both the taxonomic and functional aspects of the cultivated human gut microbiomes derived from clinical colon biopsies. We combined a rapid peptide search by MSFragger against the Unified Human Gastrointestinal Protein database and the taxonomic and functional analyses with Unipept Desktop and MetaLab-MAG. Across seven samples, we identified and matched nearly 36,000 unique peptides to approximately 300 species and 11 phyla. Unipept Desktop provided gene ontology, InterPro entries, and enzyme commission number annotations, facilitating the identification of relevant metabolic pathways. MetaLab-MAG contributed functional annotations through Clusters of Orthologous Genes and Non-supervised Orthologous Groups categories. These results unveiled functional similarities and differences among the samples. This integrated pipeline holds the potential to provide deeper insights into the taxonomy and functions of the human gut microbiome for interrogating the intricate connections between microbiome balance and diseases., (© 2024 Wiley‐VCH GmbH.)

Liver cirrhosis is one of the most prevalent chronic liver disorders with high mortality. We aimed to explore changed gut microbiome and urine metabolome in compensatory liver cirrhosis (CLC) patients, thus providing novel diagnostic biomarkers for CLC. Forty fecal samples from healthy volunteers (control: 19) and CLC patients (patient: 21) were undertaken 16S rDNA sequencing. Chromatography-mass spectrometry was performed on 40 urine samples (20 controls and 20 patients). Microbiome and metabolome data were separately analyzed using corresponding bioinformatics approaches. The diagnostic model was constructed using the least absolute shrinkage and selection operator regression. The optimal diagnostic model was determined by five-fold cross-validation. Pearson correlation analysis was applied to clarify the relations among the diagnostic markers. 16S rDNA sequencing analyses showed changed overall alpha diversity and beta diversity in patient samples compared with those of controls. Similarly, we identified 841 changed metabolites. Pathway analysis revealed that the differential metabolites were mainly associated with pathways, such as tryptophan metabolism, purine metabolism, and steroid hormone biosynthesis. A 9-maker diagnostic model for CLC was determined, including 7 microorganisms and 2 metabolites. In this model, there were multiple correlations between microorganisms and metabolites. Subdoligranulum, Agathobacter, norank&#95;f&#95;Eubacterium&#95;coprostanoligenes&#95;group, Butyricicoccus, Lachnospiraceae&#95;UCG&#95;004, and L-2,3-Dihydrodipicolinate were elevated in CLC patients, whereas Blautia, Monoglobus, and 5-Acetamidovalerate were reduced. A novel diagnostic model for CLC was constructed and verified to be reliable, which provides new strategies for the diagnosis and treatment of CLC., (© 2023. The Author(s).)

Schizophrenia (SCZ) is a multifactorial mental illness, thus it will be beneficial for exploring this disease using multimodal data, including functional magnetic resonance imaging (fMRI), genes, and the gut microbiome. Previous studies reported combining multimodal data can offer complementary information for better depicting the abnormalities of SCZ. However, the existing multimodal-based methods have multiple limitations. First, most approaches cannot fully use the relationships among different modalities for the downstream tasks. Second, representing multimodal data by the modality-common and modality-specific components can improve the performance of multimodal analysis but often be ignored. Third, most methods conduct the model for classification or regression, thus a unified model is needed for finishing these tasks simultaneously. To this end, a multi-loss disentangled generative-discriminative learning (MDGDL) model was developed to tackle these issues. Specifically, using disentangled learning method, the genes and gut microbial biomarkers were represented and separated into two modality-specific vectors and one modality-common vector. Then, a generative-discriminative framework was introduced to uncover the relationships between fMRI features and these three latent vectors, further producing the attentive vectors, which can help fMRI features for the downstream tasks. To validate the performance of MDGDL, an SCZ classification task and a cognitive score regression task were conducted. Results showed the MDGDL achieved superior performance and identified the most important multimodal biomarkers for the SCZ. Our proposed model could be a supplementary approach for multimodal data analysis. Based on this method, we could analyze the SCZ by combining multimodal data, and further obtain some interesting findings.

Background: The symbiotic gut microbiota is pivotal for human health, with its composition linked to various diseases and metabolic disorders. Despite its significance, there remains a gap in systematically evaluating how host phenotypes, such as gender, age, and body mass index (BMI), influence gut microbiota., Methodology/principal Findings: We conducted an analysis of the gut microbiota of 185 Chinese adults based on whole-metagenome shotgun sequencing of fecal samples. Our investigation focused on assessing the effects of gender, age, and BMI on gut microbiota across three levels: diversity, gene/phylogenetic composition, and functional composition. Our findings suggest that these phenotypes have a minor impact on shaping the gut microbiome compared to enterotypes, they do not correlate significantly within- or between-sample diversity. We identified a substantial number of phenotype-associated genes and metagenomic linkage groups (MLGs), indicating variations in gut microflora composition. Specifically, we observed a decline in beneficial Firmicutes microbes, such as Eubacterium , Roseburia , Faecalibacterium and Ruminococcus spp., in both older individuals and those with higher BMI, while potentially harmful microbes like Erysipelotrichaceae , Subdoligranulum and Streptococcus spp. increased with age. Additionally, Blautia and Dorea spp. were found to increase with BMI, aligning with prior research. Surprisingly, individuals who were older or overweight exhibited a lack of Bacteroidetes, a dominant phylum in the human gut microbiota that includes opportunistic pathogens, while certain species of the well-known probiotics Bifidobacterium were enriched in these groups, suggesting a complex interplay of these bacteria warranting further investigation. Regarding gender, several gender-associated MLGs from Bacteroides , Parabacteroides , Clostridium and Akkermansia were enriched in females. Functional analysis revealed a multitude of phenotype-associated KEGG orthologs (KOs)., Conclusions/significance: Our study underscores the influence of gender, age, and BMI on gut metagenomes, affecting both phylogenetic and functional composition. However, further investigation is needed to elucidate the precise roles of these bacteria, including both pathogens and probiotics., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. The author(s) declared that they were an editorial board member of Frontiers, at the time of submission. This had no impact on the peer review process and the final decision., (Copyright © 2024 Li, Fan, Ma, Xia and Yan.)

Ruminants have the ability to digest human-inedible plant materials, due to the symbiotic relationship with the rumen microbiota. Rumen microbes supply short chain fatty acids, amino acids, and vitamins to dairy cows that are used for maintenance, growth, and lactation functions. The main goal of this study was to investigate gene-microbiome networks underlying feed efficiency traits by integrating genotypic, microbial, and phenotypic data from lactating dairy cows. Data consisted of dry matter intake (DMI), net energy secreted in milk, and residual feed intake (RFI) records, SNP genotype, and 16S rRNA rumen microbial abundances from 448 mid-lactation Holstein cows. We first assessed marginal associations between genotypes and phenotypic and microbial traits through genomic scans, and then, in regions with multiple significant hits, we assessed gene-microbiome-phenotype networks using causal structural learning algorithms. We found significant regions co-localizing the rumen microbiome and feed efficiency traits. Interestingly, we found three types of network relationships: (1) the cow genome directly affects both rumen microbial abundances and feed efficiency traits; (2) the cow genome (Chr3: 116.5 Mb) indirectly affects RFI, mediated by the abundance of Syntrophococcus, Prevotella, and an unknown genus of Class Bacilli; and (3) the cow genome (Chr7: 52.8 Mb and Chr11: 6.1-6.2 Mb) affects the abundance of Rikenellaceae RC9 gut group mediated by DMI. Our findings shed light on how the host genome acts directly and indirectly on the rumen microbiome and feed efficiency traits and the potential benefits of the inclusion of specific microbes in selection indexes or as correlated traits in breeding programs. Overall, the multistep approach described here, combining whole-genome scans and causal network reconstruction, allows us to reveal the relationship between genome and microbiome underlying dairy cow feed efficiency., (© 2024. The Author(s).)

This study aimed to comprehensively characterize the gut microbiota in diarrheal mink. We conducted Shotgun metagenomic sequencing on samples from five groups of diarrheal mink and five groups of healthy mink. The microbiota α-diversity and Kyoto Encyclopedia of Genes and Genomes (KEGG) orthology did not show significant differences between the groups. However, significant differences were observed in microbiota β-diversity and the function of carbohydrate-active enzymes (CAZymes) between diarrheal and healthy mink. Specifically, The relative abundance of Firmicutes was lower, whereas that of Bacteroidetes was higher in diarrheal mink. Fusobacteria were enriched as invasive bacteria in the gut of diarrheal mink compared with healthy mink. In addition, Escherichia albertii was identified as a new bacterium in diarrheal mink. Regarding functions, nicotinate and nicotinamide metabolism and glycoside hydrolases 2 (GH2) family were the enhanced KEGG orthology and CAZymes in diarrheal mink. Furthermore, the diversity and number of antibiotic-resistant genes were significantly higher in the diarrheal mink group than in the healthy group. These findings enhance our understanding of the gut microbiota of adult mink and may lead to new approaches to the diagnosis and treatment of mink diarrhea., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2024 Liu et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

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.