mSystems最新文献

{"title":"Preparation of functional metagenomic libraries from low biomass samples using METa assembly and their application to capture antibiotic resistance genes.","authors":"H M Allman, E P Bernate, E Franck, F J Oliaro, E M Hartmann, T S Crofts","doi":"10.1128/msystems.01039-25","DOIUrl":"https://doi.org/10.1128/msystems.01039-25","url":null,"abstract":"<p><p>A significant challenge in the field of microbiology is the functional annotation of novel genes from microbiomes. The increasing pace of sequencing technology development has made solving this challenge in a high-throughput manner even more important. Functional metagenomics offers a sequence-naive and cultivation-independent solution. Unfortunately, most methods for constructing functional metagenomic libraries require large input masses of metagenomic DNA, putting many sample types out of reach. Here, we show that our functional metagenomic library preparation method, METa assembly, can be used to prepare useful libraries from much lower input DNA quantities. Standard methods of functional metagenomic library preparation generally call for 5-60 µg of input metagenomic DNA. We demonstrate that the threshold for input DNA mass can be lowered at least to 30.5 ng, a 3-log decrease from prior art. We prepared functional metagenomic libraries using between 30.5 ng and 100 ng of metagenomic DNA and found that despite their limited input mass, they were sufficient to link MFS transporters lacking substrate-specific annotations to tetracycline resistance and capture a gene encoding a novel GNAT family acetyltransferase that represents a new streptothricin acetyltransferase, <i>satB</i>. Our preparation of functional metagenomic libraries from aquatic samples and a human stool swab demonstrates that METa assembly can be used to prepare functional metagenomic libraries from microbiomes that were previously incompatible with this approach.IMPORTANCEBacterial genes in microbial communities, including those that give resistance to antibiotics, are often so novel that sequencing-based approaches cannot predict their functions. Functional metagenomic libraries offer a high-throughput, sequence-naive solution to this problem, but their use is often held back due to their need for large quantities of metagenomic DNA. We demonstrate that our functional metagenomic library preparation method, METa assembly, can prepare these libraries using as little as ~30 ng of DNA, approximately 1,000-fold less than other methods. We use METa assembly to prepare functional metagenomic libraries from low-biomass aquatic and fecal swab microbiomes and show that they are home to novel tetracycline efflux pumps and a new family of streptothricin resistance gene, respectively. The efficiency of the METa assembly library preparation method makes many otherwise off-limits, low-biomass microbiome samples compatible with functional metagenomics.</p>","PeriodicalId":18819,"journal":{"name":"mSystems","volume":" ","pages":"e0103925"},"PeriodicalIF":4.6,"publicationDate":"2025-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145030366","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":"Use of the CHM13-T2T genome improves metagenomic analysis by minimizing host DNA contamination.","authors":"Donglai Liu, Jinjun Hu, Dan Zhang, Shanshan Ren, Lanqing Zhao, Hongyan Gao, Songnian Hu, Sihong Xu, Guanxiang Liang","doi":"10.1128/msystems.00840-25","DOIUrl":"https://doi.org/10.1128/msystems.00840-25","url":null,"abstract":"<p><p>Human-associated metagenomic data often contain human nucleic acid information, which can affect the accuracy of microbial classification or raise ethical concerns. These reads are typically removed through alignment to the human genome using various metagenomic mapping tools or human reference genomes, followed by filtration before metagenomic analysis. In this study, we conducted a comprehensive analysis to identify the optimal combination of alignment software and human reference genomes using benchmarking data. Our findings show that the combination of bwa-mem and the telomere-to-telomere human genome (CHM13-T2T) is the most effective in removing human reads in simulated data. We also analyzed CHM13-T2T-derived sequences in RefSeq to understand how CHM13-T2T reduces false positive results. Finally, we assessed clinical samples and found that CHM13-T2T effectively reduces host-derived contamination, particularly in low microbial biomass samples. This study provides a thorough overview of the application of CHM13-T2T in metagenomic analysis and highlights its significance in improving microbial classification accuracy.IMPORTANCEHuman gene sequences account for a large proportion of metagenomic sequences. To gain accurate and precise microbiome information, effective host-derived contamination removal methods are required. Both the alignment algorithm and the reference genome could influence the effectiveness of this process. The telomere-to-telomere human genome (CHM13-T2T) is a state-of-the-art human genome with 216 Mbp of additional new sequences compared with the commonly used GRCh38.p14. Our findings show the optimal dehosting effect of CHM13-T2T combined with the bwa-mem software in metagenomic analysis. We also investigate the reasons for the superiority of CHM13-T2T. Our study provides insights into optimal strategies for host sequence removal from metagenomic data. A standard reference is proposed for future metagenomic analysis, which can improve the accuracy of microbial identification.</p>","PeriodicalId":18819,"journal":{"name":"mSystems","volume":" ","pages":"e0084025"},"PeriodicalIF":4.6,"publicationDate":"2025-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145030324","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":"Metagenomic research on the structural difference of plaque microbiome from different caries stages and the construction of a caries diagnostic model.","authors":"Lei Dong, Jiazhen Yang, Hui Wu, Yanfei Sun, Jiang Liu, Hao Yuan, Mingchao Wang, Yajie Dai, Fei Teng, Gongchao Jing, Fang Yang","doi":"10.1128/msystems.00044-25","DOIUrl":"https://doi.org/10.1128/msystems.00044-25","url":null,"abstract":"<p><p>Development of dental caries is a dynamic process; yet, there is limited knowledge on microbial differences at various stages of caries at higher resolution. To investigate the shifting microbiome profiles across different caries stages, 30 children were enrolled in this study, including 15 caries-active patients and 15 caries-free individuals. Plaque samples were collected from the buccal surface of caries-free subjects, defined as confident health (CH; <i>n</i> = 15). For caries-active individuals, plaque samples were collected from non-cavitated surfaces (defined as relative health [RH], <i>n</i> = 15), enamel caries (EC; <i>n</i> = 15), and dentin caries samples (DC; <i>n</i> = 15). All the above samples were sequenced through the 2bRAD sequencing platform to reveal the microbial community structures in each group. We identified significant differences in microbial community structures from different caries stages. First, the CH group showed the highest species richness (<i>P</i> < 0.05), and then followed by the RH and EC groups with lower richness, and the lowest richness was found in the DC group, yet no significant difference was found among the last three groups (<i>P</i> > 0.05). Second, the microbial structure exhibited the greatest difference between CH and DC groups, followed by the distance between RH/EC and DC groups, and the smallest difference was found between RH and EC groups. Third, specific species were found with a significant difference during the different caries stages. Therefore, we developed a diagnostic model using deep learning methods based on neural networks to diagnose different caries stages with an AUC of over 98%. This may provide methodological support for the understanding of the etiological factor in the pathological progression of dental caries.IMPORTANCEThe diagnosis and treatment of dental caries are crucial for human oral health. Previous studies have focused on the microbial differences between caries and healthy teeth, but there was not enough knowledge on the microbial differences at different stages of dental caries. Our findings could provide a high-resolution understanding of the microbial divergencies among different stages of dental caries and thus build microbial-based diagnostic models for differentiating dental caries status using deep learning methods with an accuracy of over 98%. This may provide methodological support for the understanding of the etiological factor in the pathological progression of dental caries.</p>","PeriodicalId":18819,"journal":{"name":"mSystems","volume":" ","pages":"e0004425"},"PeriodicalIF":4.6,"publicationDate":"2025-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145030394","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":"Comparative analysis of colonization and survival strategies of regionally predominant LA-MRSA clones ST398 and ST9.","authors":"Xing Ji, Yaxin Wang, Tao He, Henrike Krüger-Haker, Yang Wang, Congming Wu, Stefan Schwarz, Chengtao Sun","doi":"10.1128/msystems.00397-25","DOIUrl":"https://doi.org/10.1128/msystems.00397-25","url":null,"abstract":"<p><p>Livestock-associated methicillin-resistant <i>Staphylococcus aureus</i> (LA-MRSA) displays distinct geographical distribution patterns, with ST398 predominating in Europe and ST9 being the dominant lineage in Asia, particularly China. However, the mechanisms underlying these differences remain poorly understood. In this study, we evaluated the cell adhesion capacity, anti-phagocytic properties, and porcine nasal colonization potential of ST9 and ST398 strains isolated from China and Germany. Colonization dynamics and characteristics were further explored using 16S rRNA gene sequencing and metatranscriptomic analysis. Our findings revealed that LA-MRSA ST398 strains exhibited superior colonization capabilities, including enhanced cell adhesion, increased resistance to macrophage-mediated killing, and a stronger impact on nasal microbiota stability. Transcriptomic analyses during colonization indicated that ST398 strains prioritized pathways related to genome repair and amino acid metabolism, whereas ST9 strains, particularly those isolated from China, focused on carbohydrate metabolism. Although ST9 strains showed relatively weaker colonization capacity, the epidemic Chinese ST9 isolates carried multiple resistance genes [<i>fexA</i>, <i>tet</i>(L), and <i>aadE-spw-lsa</i>(E)-<i>lnu</i>(B)], exhibiting broad resistance to clinically important antibiotics including tylosin, florfenicol, and tetracyclines. This suggests that their prevalence in China may be maintained through antimicrobial selection pressure. With the implementation of stricter antibiotic use regulations in Chinese livestock production, ST398, due to its robust colonization potential, is likely to replace ST9 as the dominant LA-MRSA clone gradually.IMPORTANCELivestock-associated methicillin-resistant <i>Staphylococcus aureus</i> (LA-MRSA) is a significant public health concern due to its zoonotic potential and resistance to antimicrobial agents. Despite its global presence, the geographical dominance of specific clones, such as ST398 in Europe and ST9 in Asia, remains poorly understood. This study sheds light on the distinct colonization strategies and metabolic adaptations of these LA-MRSA lineages. By demonstrating the superior colonization abilities and metabolic versatility of ST398 compared to ST9, we speculate that changes in antimicrobial usage policies may drive a shift in the dominance of LA-MRSA clones in China's livestock industry. These insights provide valuable guidance for managing LA-MRSA transmission and developing effective intervention strategies to mitigate its impact on animal and human health.</p>","PeriodicalId":18819,"journal":{"name":"mSystems","volume":" ","pages":"e0039725"},"PeriodicalIF":4.6,"publicationDate":"2025-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145023887","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":"Metabolic biochemical models of N₂ fixation for sulfide oxidizers, methanogens, and methanotrophs.","authors":"Meng Gao, Megan E Berberich, Reid Brown, David M Costello, James B Cotner, Julian Damashek, Leila Richards Kittu, Ada Pastor, Robinson W Fulweiler, J Thad Scott, Amy M Marcarelli, Keisuke Inomura","doi":"10.1128/msystems.00748-25","DOIUrl":"https://doi.org/10.1128/msystems.00748-25","url":null,"abstract":"<p><p>Dinitrogen (N₂) fixation provides bioavailable nitrogen to the biosphere. However, in some habitats (e.g., sediments), the metabolic pathways of organisms carrying out N₂ fixation are unclear. We present metabolic models representing various chemotrophic N₂ fixers, which simulate potential pathways of electron transport and energy flow, resulting in predictions of whole-cell stoichiometries. By balancing mass, electrons, and energy for metabolic half-reactions, we quantify the electron usage for nine N₂ fixers. Our results demonstrate that all modeled organisms fix sufficient N₂ for growth. Aerobic organisms allocate more electrons to N₂ fixation and growth, yielding more biomass and fixing more N₂, while methanogens using acetate and organisms using sulfate allocate fewer electrons. This work can be applied to investigate the depth distribution of N₂ fixers based on nutrient availability, complementing field measurements of biogeochemical processes and microbial communities.IMPORTANCEN₂ fixation is an important process in the global N cycle. Researchers have developed models for heterotrophic and photoautotrophic N₂ fixers, but there is a lack of modeling studies on chemoautotrophic N₂ fixers. Here, we built nine biochemical models for different chemoautotrophic N₂ fixers by combining different types of half-chemical reactions. We include three sulfide oxidizers using different electron acceptors (O₂, NO₃^-, and Fe³⁺), contributing to the sulfur, nitrogen, and iron cycles in the sediment. We have two methanogens using different substrates (H₂ and acetate) and four methanotrophs using different electron acceptors (O₂, NO₃^-, Fe³⁺, and SO₄^2-). By modeling these methane producers and users in the sediment and their N₂-fixing metabolic pathways, our work can provide insight for future carbon cycle studies. This study outlines various metabolic pathways that can facilitate N₂ fixation, with implications for where in the environment they might occur.</p>","PeriodicalId":18819,"journal":{"name":"mSystems","volume":" ","pages":"e0074825"},"PeriodicalIF":4.6,"publicationDate":"2025-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145015836","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":"Mapping carbon utilization pathways in <i>Histoplasma capsulatum</i> through ¹³C-metabolic flux analysis.","authors":"Adrian Heckart, Jean-Christophe Cocuron, Stephanie C Ray, Gabriella F Matheny, Chad A Rappleye, Ana P Alonso","doi":"10.1128/msystems.00569-25","DOIUrl":"https://doi.org/10.1128/msystems.00569-25","url":null,"abstract":"<p><p><i>Histoplasma capsulatum</i> is a human fungal pathogen that survives and proliferates within phagocytic immune cells. To sustain growth in the nutrient-limited phagosome environment, the pathogenic yeast scavenges available carbon sources, which must be metabolized through central carbon metabolism for respiration and biomass synthesis. However, <i>Histoplasma</i> carbon metabolic pathways operating in the pathogenic yeast phase have not been extensively mapped. To address this gap, we employed a fluxomic platform using stable isotope tracers to quantify the cellular reaction rates of central carbon metabolism. This approach revealed that, in <i>Histoplasma</i> yeasts, carbon resides within five main reservoirs: fatty acids, proteins, mannitol, nucleic acids, and cell wall components. Carbon conversion efficiency, or biomass yield, was approximately 50%, indicating substantial CO₂ loss from supplemented carbon substrates, glucose, and glutamate. ¹³C-labeling analysis demonstrated simultaneous glycolysis and gluconeogenesis, and enriched serine labeling confirmed threonine aldolase activity in serine biosynthesis. Compartmentalization of pyruvate metabolism was evident from the labeling of amino acids derived from pyruvate, with the methylcitrate cycle identified as the primary source of labeled pyruvate. Notably, malic enzyme and pyruvate carboxylase exhibited negligible fluxes, while mitochondrial reactions, particularly CO₂-producing ones, were the most active. These results offer insight into key metabolic reactions, alternative pathways, and metabolite/enzyme compartmentalization in <i>Histoplasma</i> yeast metabolism. This foundational framework supports future studies aimed at identifying metabolic targets for novel histoplasmosis therapeutics.IMPORTANCETo our knowledge, this study represents the first application of ¹³C-metabolic flux analysis to a human fungal pathogen, where we identified carbon reservoirs and quantified the metabolic fluxes of pathogenic <i>Histoplasma</i> yeasts. Our findings demonstrated that <i>Histoplasma</i> metabolizes carbon toward cellular respiration to robustly produce CO₂ and energy but also uses alternative pathways within central metabolism for biosynthesis. Given the potential for other pathogenic fungi to share similar metabolic features, especially biomass, our study offers a comprehensive framework for deciphering fungal metabolism, providing insights into their infection-enabling metabolism and offering a foundation for identifying new therapeutic targets.</p>","PeriodicalId":18819,"journal":{"name":"mSystems","volume":" ","pages":"e0056925"},"PeriodicalIF":4.6,"publicationDate":"2025-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145015841","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":"GEMsembler: consensus model assembly and structural comparison of genome-scale metabolic models across tools improve functional performance.","authors":"Elena K Matveishina, Bartosz J Bartmanski, Sara Benito-Vaquerizo, Maria Zimmermann-Kogadeeva","doi":"10.1128/msystems.00574-25","DOIUrl":"https://doi.org/10.1128/msystems.00574-25","url":null,"abstract":"<p><p>Genome-scale metabolic models (GEMs) are widely used in systems biology to investigate metabolism and predict perturbation responses. Automatic GEM reconstruction tools generate GEMs with different properties and predictive capacities for the same organism. Since different models can excel at different tasks, combining them can increase metabolic network certainty and enhance model performance. Here, we introduce GEMsembler, a Python package designed to compare cross-tool GEMs, track the origin of model features, and build consensus models containing any subset of the input models. GEMsembler provides comprehensive analysis functionality, including identification and visualization of biosynthesis pathways, growth assessment, and an agreement-based curation workflow. GEMsembler-curated consensus models built from four <i>Lactiplantibacillus plantarum</i> and <i>Escherichia coli</i> automatically reconstructed models outperform the gold-standard models in auxotrophy and gene essentiality predictions. Optimizing gene-protein-reaction (GPR) combinations from consensus models improves gene essentiality predictions, even in the manually curated gold-standard models. GEMsembler explains model performance by highlighting relevant metabolic pathways and GPR alternatives, informing experiments to resolve model uncertainty. Thus, GEMsembler facilitates building more accurate and biologically informed metabolic models for systems biology applications.IMPORTANCEGenome-scale metabolic models (GEMs) capture our knowledge of cellular metabolism as encoded in the genome, enabling us to describe and predict how cells function under different conditions. While several automated tools can generate these models directly from genome data, the resulting models often contain gaps and uncertainties, highlighting areas where our metabolic knowledge is incomplete. Here, we introduce a new tool called GEMsembler, which integrates GEMs constructed by different methods, evaluate model uncertainty, and build consensus models, harnessing the unique features of each approach. These consensus models more accurately reflect experimentally observed metabolic traits, such as nutrient requirements and condition-specific gene essentiality. GEMsembler facilitates comprehensive analysis of model structure and function, helping to pinpoint knowledge gaps and prioritize experiments to address them. By synthesizing information from diverse sources, GEMsembler accelerates the development of more reliable and biologically meaningful models, advancing research in metabolic engineering, pathogen biology, and microbial community studies.</p>","PeriodicalId":18819,"journal":{"name":"mSystems","volume":" ","pages":"e0057425"},"PeriodicalIF":4.6,"publicationDate":"2025-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145015889","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":"A hidden confounder for microbiome studies: medications used years before sample collection.","authors":"Oliver Aasmets, Nele Taba, Kertu Liis Krigul, Reidar Andreson, Elin Org","doi":"10.1128/msystems.00541-25","DOIUrl":"10.1128/msystems.00541-25","url":null,"abstract":"<p><p>Medication usage is a known contributor to the inter-individual variability of the gut microbiome. However, medications are often used repeatedly and for long periods, a notion yet unaccounted for in microbiome studies. Recently, we and others showed that not only the usage of antibiotics and antidepressants at sampling, but also past consumption, is associated with the gut microbiome. This effect can be \"additive\"-the more a medication is used, the stronger the impact on the microbiome. Here, by utilizing retrospective medication usage data from the electronic health records and the observational Estonian microbiome cohort shotgun metagenomics data set (<i>n</i> = 2,509), we systematically evaluate the long-term effects of antibiotics and human-targeted medications on the gut microbiome. We show that past usage of medications is associated with the gut microbiome. For example, the effects of antibiotics, psycholeptics, antidepressants, proton pump inhibitors, and beta-blockers are detectable several years after use. Furthermore, by analyzing a subcohort (<i>n</i> = 328) with a second microbiome characterization, we show that similar changes in the gut microbiome occur after treatment initiation or discontinuation, possibly indicating causal effects.IMPORTANCEThis is the first study using detailed retrospective medication usage data from electronic health records to systematically assess the long-term effects of medication usage on the gut microbiome. We identified carryover and additive effects on the gut microbiome for a range of antibiotics and non-antibiotic medications, such as benzodiazepine derivatives, antidepressants and glucocorticoids, among others. These findings highlight a collateral effect of diverse drug classes on the gut microbiome, which warrants accounting for long-term medication usage history when assessing disease-microbiome associations.</p>","PeriodicalId":18819,"journal":{"name":"mSystems","volume":" ","pages":"e0054125"},"PeriodicalIF":4.6,"publicationDate":"2025-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145001084","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":"Modeling reveals a metabolic basis of competition among <i>Dehalobacter</i> strains during tandem chloroform and dichloromethane metabolism.","authors":"Olivia Bulka, Elizabeth A Edwards, Radhakrishnan Mahadevan","doi":"10.1128/msystems.00847-25","DOIUrl":"https://doi.org/10.1128/msystems.00847-25","url":null,"abstract":"<p><p>SC05-UT is an anaerobic, heterogenous microbial enrichment culture that reduces chloroform to dichloromethane through reductive dechlorination, which it further mineralizes to carbon dioxide. This dichloromethane mineralization yields electron equivalents that are used to reduce chloroform without the addition of exogenous electron donor. By studying this self-feeding chloroform-amended culture and a dichloromethane-amended enrichment subculture (named DCME), we previously found the genomic potential to perform both biodegradation steps in two distinct <i>Dehalobacter</i> strains: <i>Dehalobacter restrictus</i> SAD and <i>Candidatus</i> Dehalobacter alkaniphilus DAD. Though present in each enrichment culture, strain SAD is more abundant in the chloroform-fed subculture SC05-UT, while strain DAD is more prominent in the dichloromethane-fed subculture DCME. To understand if genomic differences between strains impact their metabolic mechanisms, the genome of each strain was curated to reconstruct genome-scale metabolic models of each strain, which were then constrained based on thermodynamic and experimental conditions. We demonstrate that metabolic differences between the two strains may allow <i>Dehalobacter</i> strain DAD to outcompete strain SAD in the absence of chloroform, while strain SAD exhibits an advantage in the presence of chloroform. Additionally, we predict electron cycling methods to reconcile cellular redox imbalances during tandem chloroform and dichloromethane dechlorination. This work highlights the importance of hydrogen and amino acid exchange in these microbial communities and contributes to the growing body of work surrounding organohalide syntrophy.IMPORTANCEChloroform and dichloromethane contaminate groundwater around the world but can be remediated by microbes capable of metabolizing these toxic compounds. Here, we study two distinct strains of <i>Dehalobacter</i> and show that while both strains can degrade both chloroform and dichloromethane, differences in their genetic makeup allow each strain to thrive under different environmental conditions. This has implications for understanding the fate of halogenated methanes in the environment and the application of <i>Dehalobacter</i> for bioremediation of chlorinated compounds.</p>","PeriodicalId":18819,"journal":{"name":"mSystems","volume":" ","pages":"e0084725"},"PeriodicalIF":4.6,"publicationDate":"2025-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145001081","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-derived <i>Faecalibaculum rodentium</i> exerts anti-cancer effects on colorectal cancer by modulating PDPN-CLEC-2 signaling pathway.","authors":"Xiaojuan Yang, Miao Liu, Ting Wang, Xinjuan Ma, Zhirong Guan, Bin Ma, Xiangguo Duan, Chunxia Su","doi":"10.1128/msystems.00148-25","DOIUrl":"10.1128/msystems.00148-25","url":null,"abstract":"<p><p>Dynamic changes in microbial composition are related to the progression of colorectal cancer (CRC); however, specific microbes with anti-CRC properties have not been identified. Here, we aimed to determine the effect of <i>Faecalibaculum rodentium</i> on CRC progression. In this study, the effect of <i>F. rodentium</i> was assessed in an azoxymethane (AOM)/dextran sulfate sodium salt (DSS)-induced CRC mouse model as well as in human CRC cell lines. Changes in anti-tumor immune responses were evaluated by flow cytometry. The functional metabolites produced by <i>F. rodentium</i> were identified by gas chromatography‒mass spectrometry (GC‒MS). The subcutaneously injected BALB/c mice with CT26 CRC cells were used to evaluate the effect of acetate produced by <i>F. rodentium</i>. We found that supplementation with <i>F. rodentium</i> suppressed CRC in an AOM/DSS-induced CRC mouse model as well as in the human CRC cell lines SW620 and HT-29. GC‒MS revealed that acetate is a functional tumor-suppressive metabolite produced by <i>F. rodentium</i>, and the tumor volume and tumor weight in the CRC model were inhibited by acetate administration. Mechanistically, <i>F. rodentium</i> produced acetate, which suppressed the expression of PDPN on CD8⁺ T cells and that of C-type lectin-like receptor 2 (CLEC-2) on tumor cells. As a consequence, CD8⁺ T-cell immunity was increased both <i>in vivo</i> and <i>in vitro</i>. In addition, we revealed that the acetate produced by <i>F. rodentium</i> can modulate podoplanin (PDPN)/CLEC-2/PI3K/AKT/mTOR signaling in CRC. In summary, <i>F. rodentium</i> produced acetate inhibits CRC by promoting CD8⁺ T-cell immunity and modulating the PDPN-CLEC-2 pathway. Our data indicate that <i>F. rodentium</i> is a potential probiotic for cancer prevention and treatment.IMPORTANCEThis study identified <i>Faecalibaculum rodentium</i> as a novel probiotic that suppresses colorectal cancer (CRC) via acetate, which enhances CD8⁺ T-cell immunity by blocking PDPN-CLEC-2 and induces tumor cell apoptosis through PI3K/AKT/mTOR pathway. These findings validated <i>F. rodentium</i> and acetate as dual-action therapeutic candidates through immune response activation and intrinsic tumor targeting by murine models and human CRC cell lines, thereby providing innovative strategies for CRC treatment.</p>","PeriodicalId":18819,"journal":{"name":"mSystems","volume":" ","pages":"e0014825"},"PeriodicalIF":4.6,"publicationDate":"2025-08-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12363190/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144691011","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}