mSystems最新文献

{"title":"Alterations in purine and pyrimidine metabolism associated with latent tuberculosis infection: insights from gut microbiome and metabolomics analyses.","authors":"Boyi Yang, Xiaojing Guo, Chongyu Shi, Gang Liu, Xiaoling Qin, Shiyi Chen, Li Gan, Dongxu Liang, Kai Shao, Ruolan Xu, Jieqing Zhong, Yujie Mo, Hai Li, Dan Luo","doi":"10.1128/msystems.00812-24","DOIUrl":"10.1128/msystems.00812-24","url":null,"abstract":"<p><p>Individuals with latent tuberculosis infection (LTBI) account for almost 30% of the population worldwide and have the potential to develop active tuberculosis (ATB). Despite this, the current understanding of the pathogenesis of LTBI is limited. The gut microbiome can be altered in tuberculosis patients, and an understanding of the changes associated with the progression from good health to LTBI to ATB can provide novel perspectives for understanding the pathogenesis of LTBI by identifying microbial and molecular biomarkers associated therewith. In this study, fecal samples from healthy controls (HC), individuals with LTBI and ATB patients were collected for gut microbiome and metabolomics analyses. Compared to HC and LTBI subjects, participants with ATB showed a significant decrease in gut bacterial α-diversity. Additionally, there were significant differences in gut microbial communities and metabolism among the HC, LTBI, and ATB groups. PICRUSt2 analysis revealed that microbiota metabolic pathways involving the degradation of purine and pyrimidine metabolites were upregulated in LTBI and ATB individuals relative to HCs. Metabolomic profiling similarly revealed that purine and pyrimidine metabolite levels were decreased in LTBI and ATB samples relative to those from HCs. Further correlation analyses revealed that the levels of purine and pyrimidine metabolites were negatively correlated with those of gut microbial genera represented by <i>Ruminococcus_gnavus_group</i> (<i>R. gnavus</i>), and the levels of <i>R. gnavus</i> were also positively correlated with adenosine nucleotide degradation II, which is a purine degradation pathway. Moreover, a combined signature including hypoxanthine and xanthine was found to effectively distinguish between LTBI and HC samples (area under the curve [AUC] of training set = 0.796; AUC of testing set = 0.924). Therefore, through gut microbiome and metabolomic analyses, these findings provide valuable clues regarding how alterations in gut purine and pyrimidine metabolism are linked to the pathogenesis of LTBI.IMPORTANCEThis study provides valuable insight into alterations in the gut microbiome and metabolomic profiles in a cohort of adults with LTBI and ATB. Perturbed gut purine and pyrimidine metabolism in LTBI was associated with the compositional alterations of gut microbiota, which may be an impetus for developing novel diagnostic strategies and interventions targeting LTBI.</p>","PeriodicalId":18819,"journal":{"name":"mSystems","volume":" ","pages":"e0081224"},"PeriodicalIF":5.0,"publicationDate":"2024-11-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11575419/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142470273","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Integrated analysis of metabolome and microbiome in a rat model of perimenopausal syndrome.","authors":"Yanqiu Wei, Juanjuan Shi, Jianhua Wang, Zongyan Hu, Min Wang, Wen Wang, Xiujuan Cui","doi":"10.1128/msystems.00623-24","DOIUrl":"10.1128/msystems.00623-24","url":null,"abstract":"<p><p>The objectives of this study are to examine the disparities in serum and intestinal tissue metabolites between a perimenopausal rat model and control rats and to analyze the diversity and functionality of intestinal microorganisms to determine the potential correlation between intestinal flora and metabolites. We established a rat model of perimenopausal syndrome (PMS) and performed an integrated analysis of metabolome and microbiome. Orthogonal partial least-squares discriminant analysis scores and replacement tests indicated distinct separations of anion and cation levels between serum and intestinal samples of the model and control groups. Furthermore, lipids and lipid-like molecules constituted the largest percentage of HMDB compounds in both serum and intestinal tissues, followed by organic acids and derivatives, and organoheterocyclic compounds, with other compounds showing significant variability. Moreover, analysis of diversity and functional enrichment of the intestinal microflora and correlation analysis with metabolites revealed significant variability in the composition of the intestinal flora between the normal control and perimenopausal groups, with these differentially expressed intestinal flora strongly correlated with their metabolites. The findings of this study are expected to contribute to understanding the indications and contraindications for estrogen application in perimenopausal women and to aid in the development of appropriate therapeutic agents.</p><p><strong>Importance: </strong>In this work, we employed 16S ribosomal RNA gene sequencing to analyze the gut microbes in stool samples. In addition, we conducted an ultra-high-performance liquid chromatography-tandem mass spectrometry-based metabolomics approach on gut tissue and serum obtained from rats with perimenopausal syndrome (PMS) and healthy controls. By characterizing the composition and metabolomic properties of gut microbes in PMS rats, we aim to enhance our understanding of their role in women's health, emphasizing the significance of regulating gut microbes in the context of menopausal women's well-being. We aim to provide a theoretical basis for the prevention and treatment of PMS in terms of gut microflora as well as metabolism.</p>","PeriodicalId":18819,"journal":{"name":"mSystems","volume":" ","pages":"e0062324"},"PeriodicalIF":5.0,"publicationDate":"2024-11-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11575230/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142470281","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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 choice of 16S rRNA gene sequence analysis impacted characterization of highly variable surface microbiota in dairy processing environments.","authors":"Sarah E Daly, Jingzhang Feng, Devin Daeschel, Jasna Kovac, Abigail B Snyder","doi":"10.1128/msystems.00620-24","DOIUrl":"10.1128/msystems.00620-24","url":null,"abstract":"<p><p>Accurate knowledge of the microbiota collected from surfaces in food processing environments is important for food quality and safety. This study assessed discrepancies in taxonomic composition and alpha and beta diversity values generated from eight different bioinformatic workflows for the analysis of 16S rRNA gene sequences extracted from the microbiota collected from surfaces in dairy processing environments. We found that the microbiota collected from environmental surfaces varied widely in density (0-9.09 log₁₀ CFU/cm²) and Shannon alpha diversity (0.01-3.40). Consequently, depending on the sequence analysis method used, characterization of low-abundance genera (i.e., below 1% relative abundance) and the number of genera identified (114-173 genera) varied considerably. Some low-abundance genera, including <i>Listeria</i>, varied between the amplicon sequence variant (ASV) and operational taxonomic unit (OTU) methods. Centered log-ratio transformation inflated alpha and beta diversity values compared to rarefaction. Furthermore, the ASV method also inflated alpha and beta diversity values compared to the OTU method (<i>P</i> < 0.05). Therefore, for sparse, uneven, low-density data sets, the OTU method and rarefaction are better for taxonomic and ecological characterization of surface microbiota.IMPORTANCECulture-dependent environmental monitoring programs are used by the food industry to identify foodborne pathogens and spoilage biota on surfaces in food processing environments. The use of culture-independent 16S rRNA amplicon sequencing to characterize this surface microbiota has been proposed as a tool to enhance environmental monitoring. However, there is no consensus on the most suitable bioinformatic analyses to accurately capture the diverse levels and types of bacteria on surfaces in food processing environments. Here, we quantify the impact of different bioinformatic analyses on the results and interpretation of 16S rRNA amplicon sequences collected from three cultured dairy facilities in New York State. This study provides guidance for the selection of appropriate 16S rRNA analysis procedures for studying environmental microbiota in dairy processing environments.</p>","PeriodicalId":18819,"journal":{"name":"mSystems","volume":" ","pages":"e0062024"},"PeriodicalIF":5.0,"publicationDate":"2024-11-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11575208/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142470285","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Stable, multigenerational transmission of the bean seed microbiome despite abiotic stress.","authors":"Abby Sulesky-Grieb, Marie Simonin, A Fina Bintarti, Brice Marolleau, Matthieu Barret, Ashley Shade","doi":"10.1128/msystems.00951-24","DOIUrl":"10.1128/msystems.00951-24","url":null,"abstract":"<p><p>Microbiota that originate in the seed can have consequences for the education of the plant immune system, competitive exclusion of pathogens from the host tissue, and host access to critical nutrients. Our research objective was to investigate the consequences of the environmental conditions of the parent plant for bacterial seed microbiome assembly and transmission across plant generations. Using a fully factorial, three-generational experimental design, we investigated endophytic seed bacterial communities of common bean lines (<i>Phaseolus vulgaris</i> L.) grown in the growth chamber and exposed to either control conditions, drought, or excess nutrients at each generation. We applied 16S rRNA microbiome profiling to the seed endophytes and measured plant health outcomes. We discovered stable transmission of 22 bacterial members, regardless of the parental plant condition. This study shows the maintenance of bacterial members of the plant microbiome across generations, even under environmental stress. Overall, this work provides insights into the ability of plants to safeguard microbiome members, which has implications for crop microbiome management in the face of climate change.IMPORTANCESeed microbiomes initiate plant microbiome assembly and thus have critical implications for the healthy development and performance of crops. However, the consequences of environmental conditions of the parent plant for seed microbiome assembly and transmission are unknown, but this is critical information, given the intensifying stressors that crops face as the climate crisis accelerates. This study provides insights into the maintenance of plant microbiomes across generations, with implications for durable plant microbiome maintenance in agriculture on the changing planet.</p>","PeriodicalId":18819,"journal":{"name":"mSystems","volume":" ","pages":"e0095124"},"PeriodicalIF":5.0,"publicationDate":"2024-11-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11575401/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142546357","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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 for Kwan et al., \"Gut phageome in Mexican Americans: a population at high risk for metabolic dysfunction-associated steatotic liver disease and diabetes\".","authors":"Suet-Ying Kwan, Caroline M Sabotta, Lorenzo R Cruz, Matthew C Wong, Nadim J Ajami, Joseph B McCormick, Susan P Fisher-Hoch, Laura Beretta","doi":"10.1128/msystems.01297-24","DOIUrl":"10.1128/msystems.01297-24","url":null,"abstract":"","PeriodicalId":18819,"journal":{"name":"mSystems","volume":" ","pages":"e0129724"},"PeriodicalIF":5.0,"publicationDate":"2024-11-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11575141/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142470275","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Development and evaluation of statistical and artificial intelligence approaches with microbial shotgun metagenomics data as an untargeted screening tool for use in food production.","authors":"Kristen L Beck, Niina Haiminen, Akshay Agarwal, Anna Paola Carrieri, Matthew Madgwick, Jennifer Kelly, Victor Pylro, Ban Kawas, Martin Wiedmann, Erika Ganda","doi":"10.1128/msystems.00840-24","DOIUrl":"10.1128/msystems.00840-24","url":null,"abstract":"<p><p>The increasing knowledge of microbial ecology in food products relating to quality and safety and the established usefulness of machine learning algorithms for anomaly detection in multiple scenarios suggests that the application of microbiome data in food production systems for anomaly detection could be a valuable approach to be used in food systems. These methods could be used to identify ingredients that deviate from their typical microbial composition, which could indicate food fraud or safety issues. The objective of this study was to assess the feasibility of using shotgun sequencing data as input into anomaly detection algorithms using fluid milk as a model system. Contrastive principal component analysis (PCA), cluster-based methods, and explainable artificial intelligence (AI) were evaluated for the detection of two anomalous sample classes using longitudinal metagenomic profiling of fluid milk compared to baseline (BL) samples collected under comparable circumstances. Traditional methods (alpha and beta diversity, clustering-based contrastive PCA, multidimensional scaling, and dendrograms) failed to differentiate anomalous sample classes; however, explainable AI was able to classify anomalous vs baseline samples and indicate microbial drivers in association with antibiotic use. We validated the potential for explainable AI to classify different milk sources using larger publicly available fluid milk 16S rDNA sequencing data sets and demonstrated that explainable AI is able to differentiate between milk storage methods, processing stages, and seasons. Our results indicate that the application of artificial intelligence continues to hold promise in the realm of microbiome data analysis and could present further opportunities for downstream analytic automation to aid in food safety and quality.</p><p><strong>Importance: </strong>We evaluated the feasibility of using untargeted metagenomic sequencing of raw milk for detecting anomalous food ingredient content with artificial intelligence methods in a study specifically designed to test this hypothesis. We also show through analysis of publicly available fluid milk microbial data that our artificial intelligence approach is able to successfully predict milk in different stages of processing. The approach could potentially be applied in the food industry for safety and quality control.</p>","PeriodicalId":18819,"journal":{"name":"mSystems","volume":" ","pages":"e0084024"},"PeriodicalIF":5.0,"publicationDate":"2024-11-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11575248/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142470277","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"E.PathDash, pathway activation analysis of publicly available pathogen gene expression data.","authors":"Lily Taub, Thomas H Hampton, Sharanya Sarkar, Georgia Doing, Samuel L Neff, Carson E Finger, Kiyoshi Ferreira Fukutani, Bruce A Stanton","doi":"10.1128/msystems.01030-24","DOIUrl":"10.1128/msystems.01030-24","url":null,"abstract":"<p><p>E.PathDash facilitates re-analysis of gene expression data from pathogens clinically relevant to chronic respiratory diseases, including a total of 48 studies, 548 samples, and 404 unique treatment comparisons. The application enables users to assess broad biological stress responses at the KEGG pathway or gene ontology level and also provides data for individual genes. E.PathDash reduces the time required to gain access to data from multiple hours per data set to seconds. Users can download high-quality images such as volcano plots and boxplots, differential gene expression results, and raw count data, making it fully interoperable with other tools. Importantly, users can rapidly toggle between experimental comparisons and different studies of the same phenomenon, enabling them to judge the extent to which observed responses are reproducible. As a proof of principle, we invited two cystic fibrosis scientists to use the application to explore scientific questions relevant to their specific research areas. Reassuringly, pathway activation analysis recapitulated results reported in original publications, but it also yielded new insights into pathogen responses to changes in their environments, validating the utility of the application. All software and data are freely accessible, and the application is available at scangeo.dartmouth.edu/EPathDash.</p><p><strong>Importance: </strong>Chronic respiratory illnesses impose a high disease burden on our communities and people with respiratory diseases are susceptible to robust bacterial infections from pathogens, including <i>Pseudomonas aeruginosa</i> and <i>Staphylococcus aureus</i>, that contribute to morbidity and mortality. Public gene expression datasets generated from these and other pathogens are abundantly available and an important resource for synthesizing existing pathogenic research, leading to interventions that improve patient outcomes. However, it can take many hours or weeks to render publicly available datasets usable; significant time and skills are needed to clean, standardize, and apply reproducible and robust bioinformatic pipelines to the data. Through collaboration with two microbiologists, we have shown that E.PathDash addresses this problem, enabling them to elucidate pathogen responses to a variety of over 400 experimental conditions and generate mechanistic hypotheses for cell-level behavior in response to disease-relevant exposures, all in a fraction of the time.</p>","PeriodicalId":18819,"journal":{"name":"mSystems","volume":" ","pages":"e0103024"},"PeriodicalIF":5.0,"publicationDate":"2024-11-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11575265/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142470278","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Metabolomic profiles of stony coral species from the Dry Tortugas National Park display inter- and intraspecies variation.","authors":"Jessica M Deutsch, Alyssa M Demko, Olakunle A Jaiyesimi, Gabriel Foster, Adelaide Kindler, Kelly A Pitts, Tessa Vekich, Gareth J Williams, Brian K Walker, Valerie J Paul, Neha Garg","doi":"10.1128/msystems.00856-24","DOIUrl":"10.1128/msystems.00856-24","url":null,"abstract":"<p><p>Coral reefs are experiencing unprecedented loss in coral cover due to increased incidence of disease and bleaching events. Thus, understanding mechanisms of disease susceptibility and resilience, which vary by species, is important. In this regard, untargeted metabolomics serves as an important hypothesis-building tool enabling the delineation of molecular factors underlying disease susceptibility or resilience. In this study, we characterize metabolomes of four species of visually healthy stony corals, including <i>Meandrina meandrites</i>, <i>Orbicella faveolata</i>, <i>Colpophyllia natans</i>, and <i>Montastraea cavernosa</i>, collected at least a year before stony coral tissue loss disease reached the Dry Tortugas, Florida, and demonstrate that both symbiont and host-derived biochemical pathways vary by species. Metabolomes of <i>Meandrina meandrites</i> displayed minimal intraspecies variability and the highest biological activity against coral pathogens when compared to other species in this study. The application of advanced metabolite annotation methods enabled the delineation of several pathways underlying interspecies variability. Specifically, endosymbiont-derived vitamin E family compounds, betaine lipids, and host-derived acylcarnitines were among the top predictors of interspecies variability. Since several metabolite features that contributed to inter- and intraspecies variation are synthesized by the endosymbiotic Symbiodiniaceae, which could be a major source of these compounds in corals, our data will guide further investigations into these Symbiodiniaceae-derived pathways.</p><p><strong>Importance: </strong>Previous research profiling gene expression, proteins, and metabolites produced during thermal stress have reported the importance of endosymbiont-derived pathways in coral bleaching resistance. However, our understanding of interspecies variation in these pathways among healthy corals and their role in diseases is limited. We surveyed the metabolomes of four species of healthy corals with differing susceptibilities to the devastating stony coral tissue loss disease and applied advanced annotation approaches in untargeted metabolomics to determine the interspecies variation in host and endosymbiont-derived pathways. Using this approach, we propose the survey of immune markers such as vitamin E family compounds, acylcarnitines, and other metabolites to infer their role in resilience to coral diseases. As time-resolved multi-omics datasets are generated for disease-impacted corals, our approach and findings will be valuable in providing insight into the mechanisms of disease resistance.</p>","PeriodicalId":18819,"journal":{"name":"mSystems","volume":" ","pages":"e0085624"},"PeriodicalIF":5.0,"publicationDate":"2024-11-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142668040","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Gut and oral microbial compositional differences in women with breast cancer, women with ductal carcinoma <i>in situ</i>, and healthy women.","authors":"Emma McCune, Anukriti Sharma, Breanna Johnson, Tess O'Meara, Sarah Theiner, Maribel Campos, Diane Heditsian, Susie Brain, Jack A Gilbert, Laura Esserman, Michael J Campbell","doi":"10.1128/msystems.01237-24","DOIUrl":"10.1128/msystems.01237-24","url":null,"abstract":"<p><p>This study characterized and compared the fecal and oral microbiota from women with early-stage breast cancer (BC), women with ductal carcinoma <i>in situ</i> (DCIS), and healthy women. Fecal and oral samples were collected from newly diagnosed patients prior to any therapy and characterized using 16S rRNA sequencing. Measures of gut microbial alpha diversity were significantly lower in the BC vs healthy cohort. Beta diversity differed significantly between the BC or DCIS and healthy groups, and several differentially abundant taxa were identified. Clustering (non-negative matrix factorization) of the gut microbiota identified five bacterial guilds dominated by <i>Prevotella</i>, Enterobacteriaceae, <i>Akkermansia</i>, Clostridiales, or <i>Bacteroides</i>. The <i>Bacteroides</i> and Enterobacteriaceae guilds were significantly more abundant in the BC cohort compared to healthy controls, whereas the Clostridiales guild was more abundant in the healthy group. Finally, prediction of functional pathways identified 23 pathways that differed between the BC and healthy gut microbiota including lipopolysaccharide biosynthesis, glycan biosynthesis and metabolism, lipid metabolism, and sphingolipid metabolism. In contrast to the gut microbiomes, there were no significant differences in alpha or beta diversity in the oral microbiomes, and very few differentially abundant taxa were observed. Non-negative matrix factorization analysis of the oral microbiota samples identified seven guilds dominated by <i>Veillonella</i>, <i>Prevotella</i>, Gemellaceae, <i>Haemophilus</i>, <i>Neisseria</i>, <i>Propionibacterium</i>, and <i>Streptococcus</i>; however, none of these guilds were differentially associated with the different cohorts. Our results suggest that alterations in the gut microbiota may provide the basis for interventions targeting the gut microbiome to improve treatment outcomes and long-term prognosis.</p><p><strong>Importance: </strong>Emerging evidence suggests that the gut microbiota may play a role in breast cancer. Few studies have evaluated both the gut and oral microbiomes in women with breast cancer (BC), and none have characterized these microbiomes in women with ductal carcinoma <i>in situ</i> (DCIS). We surveyed the gut and oral microbiomes from women with BC or DCIS and healthy women and identified compositional and functional features of the gut microbiota that differed between these cohorts. In contrast, very few differential features were identified in the oral microbiota. Understanding the role of gut bacteria in BC and DCIS may open up new opportunities for the development of novel markers for early detection (or markers of susceptibility) as well as new strategies for prevention and/or treatment.</p>","PeriodicalId":18819,"journal":{"name":"mSystems","volume":" ","pages":"e0123724"},"PeriodicalIF":5.0,"publicationDate":"2024-11-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11575313/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142522474","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Functional analysis of cyclic diguanylate-modulating proteins in <i>Vibrio fischeri</i>.","authors":"Ruth Y Isenberg, Chandler S Holschbach, Jing Gao, Mark J Mandel","doi":"10.1128/msystems.00956-24","DOIUrl":"10.1128/msystems.00956-24","url":null,"abstract":"<p><p>As bacterial symbionts transition from a motile free-living state to a sessile biofilm state, they must coordinate behavior changes suitable to each lifestyle. Cyclic diguanylate (c-di-GMP) is an intracellular signaling molecule that can regulate this transition, and it is synthesized by diguanylate cyclase (DGC) enzymes and degraded by phosphodiesterase (PDE) enzymes. Generally, c-di-GMP inhibits motility and promotes biofilm formation. While c-di-GMP and the enzymes that contribute to its metabolism have been well studied in pathogens, considerably less focus has been placed on c-di-GMP regulation in beneficial symbionts. <i>Vibrio fischeri</i> is the sole beneficial symbiont of the Hawaiian bobtail squid (<i>Euprymna scolopes</i>) light organ, and the bacterium requires both motility and biofilm formation to efficiently colonize. c-di-GMP regulates swimming motility and cellulose exopolysaccharide production in <i>V. fischeri</i>. The genome encodes 50 DGCs and PDEs, and while a few of these proteins have been characterized, the majority have not undergone comprehensive characterization. In this study, we use protein overexpression to systematically characterize the functional potential of all 50 <i>V</i>. <i>fischeri</i> proteins. All 28 predicted DGCs and 10 of the 14 predicted PDEs displayed at least one phenotype consistent with their predicted function, and a majority of each displayed multiple phenotypes. Finally, active site mutant analysis of proteins with the potential for both DGC and PDE activities revealed potential activities for these proteins. This work presents a systems-level functional analysis of a family of signaling proteins in a tractable animal symbiont and will inform future efforts to characterize the roles of individual proteins during lifestyle transitions.IMPORTANCECyclic diguanylate (c-di-GMP) is a critical second messenger that mediates bacterial behaviors, and <i>Vibrio fischeri</i> colonization of its Hawaiian bobtail squid host presents a tractable model in which to interrogate the role of c-di-GMP during animal colonization. This work provides systems-level characterization of the 50 proteins predicted to modulate c-di-GMP levels. By combining multiple assays, we generated a rich understanding of which proteins have the capacity to influence c-di-GMP levels and behaviors. Our functional approach yielded insights into how proteins with domains to both synthesize and degrade c-di-GMP may impact bacterial behaviors. Finally, we integrated published data to provide a broader picture of each of the 50 proteins analyzed. This study will inform future work to define specific pathways by which c-di-GMP regulates symbiotic behaviors and transitions.</p>","PeriodicalId":18819,"journal":{"name":"mSystems","volume":" ","pages":"e0095624"},"PeriodicalIF":5.0,"publicationDate":"2024-11-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11575326/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142470280","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}