Microbiome最新文献

{"title":"Disruption and adaptation: infant gut microbiota's dynamic response to SARS-CoV-2 infection.","authors":"Li-Ting Zhu, Lei Zhao, Yue Zhu, Xue-Li Xu, Jing-Jing Lin, Yi-Fang Duan, Lu Long, Yang-Yu Wu, Wen-Juan Xu, Jing-Yu Chen, Yu-Han Yin, Alex Ujong Obeten, Qiansheng Huang","doi":"10.1186/s40168-025-02029-6","DOIUrl":"10.1186/s40168-025-02029-6","url":null,"abstract":"<p><strong>Background: </strong>The responses of the infant gut microbiota to infection significantly disrupt the natural intrahost evolutionary processes of the microbiome. Here, we collected a 16-month longitudinal cohort of infant gut microbiomes affected by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Then, we developed a multicriteria approach to identify core interaction network driving community dynamics under environmental disturbances, which we termed the Conserved Variated Interaction Group (CVIgroup).</p><p><strong>Results: </strong>The CVIgroup showed significant advantages on pinpointing a sparse set associated with the disturbances, as validated both our own and publicly available datasets. Leveraging the Oxford Nanopore Technology, we found this group facilitates the ecosystem's adaptation to environmental disruptions by enhancing the mobility of mobile genetic elements, including the reinforcement of the twin-arginine translocation pathway in response to increased virulence factors. Furthermore, the CVIgroup serves as an effective indicator of ecosystem health. The timescale for the gut microbiota's adaptation extends beyond 10 months. Members of the CVIgroup, such as Bacteroides thetaiotaomicron and Faecalibacterium, exhibit varying degrees of genomic structural variants, which contribute to guiding the community toward a new stable state rather than returning to its original configuration.</p><p><strong>Conclusions: </strong>Collectively, the CVIgroup offers a snapshot of the gut microbiota's adaptive response to environmental disturbances. The disruption and subsequent adaptation of the gut microbiota in infants after COVID-19 infection underscores the necessity of re-evaluating reference standards in the context of the post-pandemic era. Video Abstract.</p>","PeriodicalId":18447,"journal":{"name":"Microbiome","volume":"13 1","pages":"72"},"PeriodicalIF":13.8,"publicationDate":"2025-03-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11895207/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143604889","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Comprehensive profiling of genomic invertons in defined gut microbial community reveals associations with intestinal colonization and surface adhesion.","authors":"Xiaofan Jin, Alice G Cheng, Rachael B Chanin, Feiqiao B Yu, Alejandra Dimas, Marissa Jasper, Allison Weakley, Jia Yan, Ami S Bhatt, Katherine S Pollard","doi":"10.1186/s40168-025-02052-7","DOIUrl":"10.1186/s40168-025-02052-7","url":null,"abstract":"<p><strong>Background: </strong>Bacteria use invertible genetic elements known as invertons to generate heterogeneity among a population and adapt to new and changing environments. In human gut bacteria, invertons are often found near genes associated with cell surface modifications, suggesting key roles in modulating dynamic processes such as surface adhesion and intestinal colonization. However, comprehensive testing of this hypothesis across complex bacterial communities like the human gut microbiome remains challenging. Metagenomic sequencing holds promise for detecting inversions without isolation and culturing, but ambiguity in read alignment limits the accuracy of the resulting inverton predictions.</p><p><strong>Results: </strong>Here, we developed a customized bioinformatic workflow-PhaseFinderDC-to identify and track invertons in metagenomic data. Applying this method to a defined yet complex gut community (hCom2) across different growth environments over time using both in vitro and in vivo metagenomic samples, we detected invertons in most hCom2 strains. These include invertons whose orientation probabilities change over time and are statistically associated with environmental conditions. We used motif enrichment to identify putative inverton promoters and predict genes regulated by inverton flipping during intestinal colonization and surface adhesion. Analysis of inverton-proximal genes also revealed candidate invertases that may regulate flipping of specific invertons.</p><p><strong>Conclusions: </strong>Collectively, these findings suggest that surface adhesion and intestinal colonization in complex gut communities directly modulate inverton dynamics, offering new insights into the genetic mechanisms underlying these processes. Video Abstract.</p>","PeriodicalId":18447,"journal":{"name":"Microbiome","volume":"13 1","pages":"71"},"PeriodicalIF":13.8,"publicationDate":"2025-03-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11892184/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143586269","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Correction: Seed microbiomes promote Astragalus mongholicus seed germination through pathogen suppression and cellulose degradation.","authors":"Da Li, Weimin Chen, Wen Luo, Haofei Zhang, Yang Liu, Duntao Shu, Gehong Wei","doi":"10.1186/s40168-025-02057-2","DOIUrl":"10.1186/s40168-025-02057-2","url":null,"abstract":"","PeriodicalId":18447,"journal":{"name":"Microbiome","volume":"13 1","pages":"70"},"PeriodicalIF":13.8,"publicationDate":"2025-03-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11889854/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143586270","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Rumen microbiome associates with postpartum ketosis development in dairy cows: a prospective nested case-control study.","authors":"Fanlin Kong, Shuo Wang, Yijia Zhang, Chen Li, Dongwen Dai, Cheng Guo, Yajing Wang, Zhijun Cao, Hongjian Yang, Yanliang Bi, Wei Wang, Shengli Li","doi":"10.1186/s40168-025-02072-3","DOIUrl":"10.1186/s40168-025-02072-3","url":null,"abstract":"<p><strong>Background: </strong>Approximately, one-third of dairy cows suffer from postpartum diseases. Ketosis is considered an important inducer of other postpartum diseases by disrupting energy metabolism. Although the rumen microbiome may be involved in the etiology of ketosis by supplying volatile fatty acids, the rumen environmental dynamics of ketosis cows are unclear. Using multi-omics, this study aimed to elucidate changes in the rumen microbiome during parturition of ketosis cows and the association between the rumen microbiome and host energy metabolism. The study included 810 rumen content samples and 789 serum samples from day - 21 and 21 relative to calving day from 61 ketosis cows and 84 healthy cows.</p><p><strong>Results: </strong>In ketosis cows, the rumen bacterial composition after parturition changed dramatically and needed a longer time to restore. The molar proportions of propionate were lower in ketosis cows than those in healthy cows on days 3 and 7 and negatively correlated with the serum β-hydroxybutyrate (BHBA) levels. The fermentation sub-pathway of propionate metabolism and partial glucogenic amino acid pathways were downregulated on day 3. Prevotella, UBA1066, and microbiota diversity indices regulate serum BHBA and glucose (GLU) levels via arginine, alanine, glycine, or propionate. Propionate administration to ketosis cows potentially decreased the serum BHBA concentration.</p><p><strong>Conclusions: </strong>Collectively, we found rumen disruption happened after calving among ketosis cows, and insufficient glycogenic substrates, such as propionate, may be related to ketosis development. The study findings have implications for the relationship between rumen microbiome dynamics and host energy metabolism, which lays the foundation for the future rumen microbiome investigation for improving postpartum management in cows. Video Abstract.</p>","PeriodicalId":18447,"journal":{"name":"Microbiome","volume":"13 1","pages":"69"},"PeriodicalIF":13.8,"publicationDate":"2025-03-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11889851/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143586276","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The universal accumulation of p-aminophenol during the microbial degradation of analgesic and antipyretic acetaminophen in WWTPs: a novel metagenomic perspective.","authors":"Chao-Fan Yin, Piaopiao Pan, Tao Li, Xin Song, Ying Xu, Ning-Yi Zhou","doi":"10.1186/s40168-025-02065-2","DOIUrl":"10.1186/s40168-025-02065-2","url":null,"abstract":"<p><strong>Background: </strong>Acetaminophen, a widely used analgesic and antipyretic drug, has become a significant aquatic micro-pollutant due to its extensive global production and increased consumption, particularly during the COVID-19 pandemic. Its high-water solubility leads to its pervasive presence in wastewater treatment plants (WWTPs), posing substantial risks to the environment and human health. Biological treatment is one of the promising approaches to remove such pollutants. Although previous studies have isolated acetaminophen-degrading pure cultures and proposed catabolic pathways, the interactions between microbiotas and acetaminophen, the distribution feature of acetaminophen degradation genes, and the gene-driven fate of acetaminophen in the real-world environment remain largely unexplored.</p><p><strong>Results: </strong>Among the water samples from 20 WWTPs across China, acetaminophen was detected from 19 samples at concentrations ranging from 0.06 to 29.20 nM. However, p-aminophenol, a more toxic metabolite, was detected in all samples at significantly higher concentrations (23.93 to 108.68 nM), indicating the presence of a catabolic bottleneck in WWTPs. Metagenomic analysis from both the above 20 samples and global datasets revealed a consistently higher abundance of initial acetaminophen amidases compared to downstream enzymes, potentially having explained the reason for the bottleneck. Meanwhile, a close correlation between initial amidases and Actinomycetota revealed by genome-based taxonomy suggests a species-dependent degradation pattern. Additionally, a distinct amidase ApaA was characterized by newly isolated Rhodococcus sp. NyZ502 (Actinomycetota), represents a predominant category of amidase in WWTPs. Significant phylogenetic and structural diversity observed among putative amidases suggest versatile acetaminophen hydrolysis potential in WWTPs.</p><p><strong>Conclusions: </strong>This study enhances our understanding of acetaminophen's environmental fate and highlights the possible occurrence of ecological risks driven by imbalanced genes in the process of acetaminophen degradation in global WWTPs. Video Abstract.</p>","PeriodicalId":18447,"journal":{"name":"Microbiome","volume":"13 1","pages":"68"},"PeriodicalIF":13.8,"publicationDate":"2025-03-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11887370/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143586279","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Challenges in capturing the mycobiome from shotgun metagenome data: lack of software and databases.","authors":"Ekaterina Avershina, Arfa Irej Qureshi, Hanne C Winther-Larsen, Trine B Rounge","doi":"10.1186/s40168-025-02048-3","DOIUrl":"10.1186/s40168-025-02048-3","url":null,"abstract":"<p><strong>Background: </strong>The mycobiome, representing the fungal component of microbial communities, is increasingly acknowledged as an integral part of the gut microbiome. However, research in this area remains relatively limited. The characterization of mycobiome taxa from metagenomic data is heavily reliant on the quality of the software and databases. In this study, we evaluated the feasibility of mycobiome profiling using existing bioinformatics tools on simulated fungal metagenomic data.</p><p><strong>Results: </strong>We identified seven tools claiming to perform taxonomic assignment of fungal shotgun metagenomic sequences. One of these was outdated and required substantial modifications of the code to be functional and was thus excluded. To evaluate the accuracy of identification and relative abundance of the remaining tools (Kraken2, MetaPhlAn4, EukDetect, FunOMIC, MiCoP, and HumanMycobiomeScan), we constructed 18 mock communities of varying species richness and abundance levels. The mock communities comprised up to 165 fungal species belonging to the phyla Ascomycota and Basidiomycota, commonly found in gut microbiomes. Of the tools, FunOMIC and HumanMycobiomeScan needed source code modifications to run. Notably, only one species, Candida orthopsilosis, was consistently identified by all tools across all communities where it was included. Increasing community richness improved precision of Kraken2 and the relative abundance accuracy of all tools on species, genus, and family levels. MetaPhlAn4 accurately identified all genera present in the communities and FunOMIC identified most species. The top three tools for overall accuracy in both identification and relative abundance estimation were EukDetect, MiCoP, and FunOMIC, respectively. Adding 90% and 99% bacterial background did not significantly impact these tools' performance. Among the whole genome reference tools (Kraken2, HMS, and MiCoP), MiCoP exhibited the highest accuracy when the same reference database was used.</p><p><strong>Conclusion: </strong>Our survey of mycobiome-specific software revealed a very limited selection of such tools and their poor robustness due to error-prone software, along with a significant lack of comprehensive databases enabling characterization of the mycobiome. None of the implemented tools fully agreed on the mock community profiles. FunOMIC recognized most of the species, but EukDetect and MiCoP provided predictions that were closest to the correct compositions. The bacterial background did not impact these tools' performance. Video Abstract.</p>","PeriodicalId":18447,"journal":{"name":"Microbiome","volume":"13 1","pages":"66"},"PeriodicalIF":13.8,"publicationDate":"2025-03-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11887097/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143586267","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"DRAMMA: a multifaceted machine learning approach for novel antimicrobial resistance gene detection in metagenomic data.","authors":"Ella Rannon, Sagi Shaashua, David Burstein","doi":"10.1186/s40168-025-02055-4","DOIUrl":"10.1186/s40168-025-02055-4","url":null,"abstract":"<p><strong>Background: </strong>Antibiotics are essential for medical procedures, food security, and public health. However, ill-advised usage leads to increased pathogen resistance to antimicrobial substances, posing a threat of fatal infections and limiting the benefits of antibiotics. Therefore, early detection of antimicrobial resistance genes (ARGs), especially in pathogens, is crucial for human health. Most computational methods for ARG detection rely on homology to a predefined gene database and therefore are limited in their ability to discover novel genes.</p><p><strong>Results: </strong>We introduce DRAMMA, a machine learning method for predicting new ARGs with no sequence similarity to known ARGs or any annotated gene. DRAMMA utilizes various features, including protein properties, genomic context, and evolutionary patterns. The model demonstrated robust predictive performance both in cross-validation and an external validation set annotated by an empirical ARG database. Analyses of the high-ranking model-generated candidates revealed a significant enrichment of candidates within the Bacteroidetes/Chlorobi and Betaproteobacteria taxonomic groups.</p><p><strong>Conclusions: </strong>DRAMMA enables rapid ARG identification for global-scale genomic and metagenomic samples, thus holding promise for the discovery of novel ARGs that lack sequence similarity to any known resistance genes. Further, our model has the potential to facilitate early detection of specific ARGs, potentially influencing the selection of antibiotics administered to patients. Video Abstract.</p>","PeriodicalId":18447,"journal":{"name":"Microbiome","volume":"13 1","pages":"67"},"PeriodicalIF":13.8,"publicationDate":"2025-03-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11887096/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143586274","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Absolute quantification of the living skin microbiome overcomes relic-DNA bias and reveals specific patterns across volunteers.","authors":"Deepan Thiruppathy, Oriane Moyne, Clarisse Marotz, Michael Williams, Perris Navarro, Livia Zaramela, Karsten Zengler","doi":"10.1186/s40168-025-02063-4","DOIUrl":"10.1186/s40168-025-02063-4","url":null,"abstract":"<p><strong>Background: </strong>As the first line of defense against external pathogens, the skin and its resident microbiota are responsible for protection and eubiosis. Innovations in DNA sequencing have significantly increased our knowledge of the skin microbiome. However, current characterizations do not discriminate between DNA from live cells and remnant DNA from dead organisms (relic DNA), resulting in a combined readout of all microorganisms that were and are currently present on the skin rather than the actual living population of the microbiome. Additionally, most methods lack the capability for absolute quantification of the microbial load on the skin, complicating the extrapolation of clinically relevant information.</p><p><strong>Results: </strong>Here, we integrated relic-DNA depletion with shotgun metagenomics and bacterial load determination to quantify live bacterial cell abundances across different skin sites. Though we discovered up to 90% of microbial DNA from the skin to be relic DNA, we saw no significant effect of this on the relative abundances of taxa determined by shotgun sequencing. Relic-DNA depletion prior to sequencing strengthened underlying patterns between microbiomes across volunteers and reduced intraindividual similarity. We determined the absolute abundance and the fraction of population alive for several common skin taxa across body sites and found taxa-specific differential abundance of live bacteria across regions to be different from estimates generated by total DNA (live + dead) sequencing.</p><p><strong>Conclusions: </strong>Our results reveal the significant bias relic DNA has on the quantification of low biomass samples like the skin. The reduced intraindividual similarity across samples following relic-DNA depletion highlights the bias introduced by traditional (total DNA) sequencing in diversity comparisons across samples. The divergent levels of cell viability measured across different skin sites, along with the inconsistencies in taxa differential abundance determined by total vs live cell DNA sequencing, suggest an important hypothesis for certain sites being susceptible to pathogen infection. Overall, our study demonstrates a characterization of the skin microbiome that overcomes relic-DNA bias to provide a baseline for live microbiota that will further improve mechanistic studies of infection, disease progression, and the design of therapies for the skin. Video Abstract.</p>","PeriodicalId":18447,"journal":{"name":"Microbiome","volume":"13 1","pages":"65"},"PeriodicalIF":13.8,"publicationDate":"2025-03-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11877739/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143557250","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Virome landscape of wild rodents and shrews in Central China.","authors":"Nailou Zhang, Bing Hu, Li Zhang, Min Gan, Qingwen Ding, Kai Pan, Jinbo Wei, Wen Xu, Dan Chen, Shaolong Zheng, Kun Cai, Zhenhua Zheng","doi":"10.1186/s40168-025-02059-0","DOIUrl":"10.1186/s40168-025-02059-0","url":null,"abstract":"<p><strong>Background: </strong>Wild rodents and shrews serve as vital sentinel species for monitoring zoonotic viruses due to their close interaction with human environments and role as natural reservoirs for diverse viral pathogens. Although several studies have explored viral diversity and assessed pathogenic risks in wild rodents and shrews, the full extent of this diversity remains insufficiently understood.</p><p><strong>Results: </strong>We conducted high-throughput sequencing on 1113 small mammals collected from 97 townships across seven cities in Hubei Province during 2021, supplemented by publicly available data from 2014 and 2016-2017. This analysis revealed a diverse array of novel viruses spanning several viral families, including Arenaviridae, Hepeviridae, Chuviridae, Paramyxoviridae, Arteriviridae, Nodaviridae, Rhabdoviridae, Dicistroviridae, Astroviridae, and Picornaviridae. Phylogenetic analysis and genome structure characterization highlighted the discovery of these novel viruses, enhancing our understanding of viral diversity and evolution. Key host species such as Chodsigoa smithii, Anourosorex squamipes, Niviventer niviventer, and Apodemus agrarius were identified as significant contributors to viral circulation, making them crucial targets for future surveillance. Additionally, the central Plain of Hubei Province was recognized as a critical geographic hub for viral transmission, underscoring its importance in monitoring and controlling viral spread. Machine learning models were employed to assess the zoonotic potential of the identified viruses, revealing that families such as Arenaviridae, Coronaviridae, Hantaviridae, Arteriviridae, Astroviridae, Hepeviridae, Lispiviridae, Nairoviridae, Nodaviridae, Paramyxoviridae, Rhabdoviridae, Picornaviridae, and Picobirnaviridae possess a high likelihood of infecting humans. Notably, rodent-derived Rotavirus A, HTNV, and SEOV displayed almost complete amino acid identity with their human-derived counterparts, indicating a significant risk for human outbreaks.</p><p><strong>Conclusion: </strong>This study provides a comprehensive virome landscape for wild rodents and shrews in Central China, highlighting novel viruses and the critical roles of specific host species and regions in viral transmission. By identifying key species and hotspots for viral spread and assessing the zoonotic potential of the discovered viruses, this research enhances our understanding of virus ecology and the factors driving zoonotic disease emergence. The findings emphasize the need for targeted surveillance and proactive strategies to mitigate the risks of zoonotic spillovers, contributing to global public health preparedness. Video Abstract.</p>","PeriodicalId":18447,"journal":{"name":"Microbiome","volume":"13 1","pages":"63"},"PeriodicalIF":13.8,"publicationDate":"2025-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11874709/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143542607","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Microbial network inference for longitudinal microbiome studies with LUPINE.","authors":"Saritha Kodikara, Kim-Anh Lê Cao","doi":"10.1186/s40168-025-02041-w","DOIUrl":"10.1186/s40168-025-02041-w","url":null,"abstract":"<p><strong>Background: </strong>The microbiome is a complex ecosystem of interdependent taxa that has traditionally been studied through cross-sectional studies. However, longitudinal microbiome studies are becoming increasingly popular. These studies enable researchers to infer taxa associations towards the understanding of coexistence, competition, and collaboration between microbes across time. Traditional metrics for association analysis, such as correlation, are limited due to the data characteristics of microbiome data (sparse, compositional, multivariate). Several network inference methods have been proposed, but have been largely unexplored in a longitudinal setting.</p><p><strong>Results: </strong>We introduce LUPINE (LongitUdinal modelling with Partial least squares regression for NEtwork inference), a novel approach that leverages on conditional independence and low-dimensional data representation. This method is specifically designed to handle scenarios with small sample sizes and small number of time points. LUPINE is the first method of its kind to infer microbial networks across time, while considering information from all past time points and is thus able to capture dynamic microbial interactions that evolve over time. We validate LUPINE and its variant, LUPINE_single (for single time point analysis) in simulated data and four case studies, where we highlight LUPINE's ability to identify relevant taxa in each study context, across different experimental designs (mouse and human studies, with or without interventions, and short or long time courses). To detect changes in the networks across time and groups or in response to external disturbances, we used different metrics to compare the inferred networks.</p><p><strong>Conclusions: </strong>LUPINE is a simple yet innovative network inference methodology that is suitable for, but not limited to, analysing longitudinal microbiome data. The R code and data are publicly available for readers interested in applying these new methods to their studies. Video Abstract.</p>","PeriodicalId":18447,"journal":{"name":"Microbiome","volume":"13 1","pages":"64"},"PeriodicalIF":13.8,"publicationDate":"2025-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11874778/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143542604","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}