mSystems最新文献

{"title":"Marine biofilms: cyanobacteria factories for the global oceans.","authors":"Cheng Zhong, Shun Yamanouchi, Yingdong Li, Jiawei Chen, Tong Wei, Ruojun Wang, Kun Zhou, Aifang Cheng, Weiduo Hao, Hongbin Liu, Kurt O Konhauser, Wataru Iwasaki, Pei-Yuan Qian","doi":"10.1128/msystems.00317-24","DOIUrl":"https://doi.org/10.1128/msystems.00317-24","url":null,"abstract":"<p><p>Marine biofilms were newly revealed as a giant microbial diversity pool for global oceans. However, the cyanobacterial diversity in marine biofilms within the upper seawater column and its ecological and evolutionary implications remains undetermined. Here, we reconstructed a full picture of modern marine cyanobacteria habitats by re-analyzing 9.3 terabyte metagenomic data sets and 2,648 metagenome-assembled genomes (MAGs). The abundances of cyanobacteria lineages exclusively detected in marine biofilms were up to ninefold higher than those in seawater at similar sample size. Analyses revealed that cyanobacteria in marine biofilms are specialists with strong geographical and environmental constraints on their genome and functional adaption, which is in stark contrast to the generalistic features of seawater-derived cyanobacteria. Molecular dating suggests that the important diversifications in biofilm-forming cyanobacteria appear to coincide with the Great Oxidation Event (GOE), \"boring billion\" middle Proterozoic, and the Neoproterozoic Oxidation Event (NOE). These new insights suggest that marine biofilms are large and important cyanobacterial factories for the global oceans.</p><p><strong>Importance: </strong>Cyanobacteria, highly diverse microbial organisms, play a crucial role in Earth's oxygenation and biogeochemical cycling. However, their connection to these processes remains unclear, partly due to incomplete surveys of oceanic niches. Our study uncovered significant cyanobacterial diversity in marine biofilms, showing distinct niche differentiation compared to seawater counterparts. These patterns reflect three key stages of marine cyanobacterial diversification, coinciding with major geological events in the Earth's history.</p>","PeriodicalId":18819,"journal":{"name":"mSystems","volume":null,"pages":null},"PeriodicalIF":5.0,"publicationDate":"2024-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142470283","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":"Microbial diversification is maintained in an experimentally evolved synthetic community.","authors":"Zahraa Al-Tameemi, Alejandra Rodríguez-Verdugo","doi":"10.1128/msystems.01053-24","DOIUrl":"https://doi.org/10.1128/msystems.01053-24","url":null,"abstract":"<p><p>Microbial communities are incredibly diverse. Yet, the eco-evolutionary processes originating and maintaining this diversity remain understudied. Here, we investigate the patterns of diversification for <i>Pseudomonas putida</i> evolving in isolation and with <i>Acinetobacter johnsonii</i> leaking resources used by <i>P. putida</i>. We experimentally evolved four experimental replicates in monoculture and co-culture for 200 generations. We observed that <i>P. putida</i> diversified into two distinct morphotypes that differed from their ancestor by single-point mutations. One of the most prominent mutations hit the <i>fleQ</i> gene encoding the master regulator of flagella and biofilm formation. We experimentally confirmed that <i>fleQ</i> mutants were unable to swim and formed less biofilm than their ancestor, but they also produced higher yields. Interestingly, the <i>fleQ</i> genotype and other mutations swept to fixation in monocultures but not in co-cultures. In co-cultures, the two lineages stably coexisted for approximately 150 generations. We hypothesized that <i>A. johnsonii</i> modulates the coexistence of the two lineages through frequency-dependent selection. However, invasion experiments with two genotypes in monoculture and co-culture did not support this hypothesis. Finally, we conducted an evolutionary \"replay\" experiment to assess whether the presence or absence of <i>A. johnsonii</i> influenced the coexistence of morphotypes at the population level. Interestingly, <i>A. johnsonii</i> had a stabilizing effect on the co-culture. Overall, our study suggests that interspecies interactions play an important role in shaping patterns of diversification in microbial communities.</p><p><strong>Importance: </strong>In nature, bacteria live in microbial communities and interact with other species, for example, through the exchange of resources leaked into the external environment (i.e., cross-feeding interactions). The role that these cross-feeding interactions play in shaping patterns of diversification remains understudied. Using a simple bacterial system in which one species cross-feeds resources to a second species (commensal species), we showed that the commensal species diversified into two subpopulations that persisted only when the cross-feeder partner was present. We further observed loss-of-function mutations in flagellar genes that were fixed in monocultures but not in co-cultures. Our findings suggest that cross-feeding species influence patterns of diversification of other species. Given that nutrient leakage is pervasive in microbial communities, the findings from this study have the potential to extend beyond our specific bacterial system. Importantly, our study has contributed to answering the larger question of whether species evolved differently in isolation versus when interacting with other species.</p>","PeriodicalId":18819,"journal":{"name":"mSystems","volume":null,"pages":null},"PeriodicalIF":5.0,"publicationDate":"2024-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142470284","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":"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":"https://doi.org/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":null,"pages":null},"PeriodicalIF":5.0,"publicationDate":"2024-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","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":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Expanded genome and proteome reallocation in a novel, robust <i>Bacillus coagulans</i> strain capable of utilizing pentose and hexose sugars.","authors":"David Dooley, Seunghyun Ryu, Richard J Giannone, Jackson Edwards, Bruce S Dien, Patricia J Slininger, Cong T Trinh","doi":"10.1128/msystems.00952-24","DOIUrl":"https://doi.org/10.1128/msystems.00952-24","url":null,"abstract":"&lt;p&gt;&lt;p&gt;&lt;i&gt;Bacillus coagulans,&lt;/i&gt; a Gram-positive thermophilic bacterium, is recognized for its probiotic properties and recent development as a microbial cell factory. Despite its importance for biotechnological applications, the current understanding of &lt;i&gt;B. coagulans&lt;/i&gt;' robustness is limited, especially for undomesticated strains. To fill this knowledge gap, we characterized the metabolic capability and performed functional genomics and systems analysis of a novel, robust strain, &lt;i&gt;B. coagulans&lt;/i&gt; B-768. Genome sequencing revealed that B-768 has the largest &lt;i&gt;B. coagulans&lt;/i&gt; genome known to date (3.94 Mbp), about 0.63 Mbp larger than the average genome of sequenced &lt;i&gt;B. coagulans&lt;/i&gt; strains, with expanded carbohydrate metabolism and mobilome. Functional genomics identified a well-equipped genetic portfolio for utilizing a wide range of C5 (xylose, arabinose), C6 (glucose, mannose, galactose), and C12 (cellobiose) sugars present in biomass hydrolysates, which was validated experimentally. For growth on individual xylose and glucose, the dominant sugars in biomass hydrolysates, B-768 exhibited distinct phenotypes and proteome profiles. Faster growth and glucose uptake rates resulted in lactate overflow metabolism, which makes &lt;i&gt;B. coagulans&lt;/i&gt; a lactate overproducer; however, slower growth and xylose uptake diminished overflow metabolism due to the high energy demand for sugar assimilation. Carbohydrate Transport and Metabolism (COG-G), Translation (COG-J), and Energy Conversion and Production (COG-C) made up 60%-65% of the measured proteomes but were allocated differently when growing on xylose and glucose. The trade-off in proteome reallocation, with high investment in COG-C over COG-G, explains the xylose growth phenotype with significant upregulation of xylose metabolism, pyruvate metabolism, and tricarboxylic acid (TCA) cycle. Strain B-768 tolerates and effectively utilizes inhibitory biomass hydrolysates containing mixed sugars and exhibits hierarchical sugar utilization with glucose as the preferential substrate.IMPORTANCEThe robustness of &lt;i&gt;B. coagulans&lt;/i&gt; makes it a valuable microorganism for biotechnology applications; yet, this phenotype is not well understood at the cellular level. Through phenotypic characterization and systems analysis, this study elucidates the functional genomics and robustness of a novel, undomesticated strain, &lt;i&gt;B. coagulans&lt;/i&gt; B-768, capable of utilizing inhibitory switchgrass biomass hydrolysates. The genome of B-768, enriched with carbohydrate metabolism genes, demonstrates high regulatory capacity. The coordination of proteome reallocation in Carbohydrate Transport and Metabolism (COG-G), Translation (COG-J), and Energy Conversion and Production (COG-C) is critical for effective cell growth, sugar utilization, and lactate production &lt;i&gt;via&lt;/i&gt; overflow metabolism. Overall, B-768 is a novel, robust, and promising &lt;i&gt;B. coagulans&lt;/i&gt; strain that can be harnessed as a microbial biomanufacturing p","PeriodicalId":18819,"journal":{"name":"mSystems","volume":null,"pages":null},"PeriodicalIF":5.0,"publicationDate":"2024-10-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142391906","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":"Protein aggregation is a consequence of the dormancy-inducing membrane toxin TisB in <i>Escherichia coli</i>.","authors":"Florian H Leinberger, Liam Cassidy, Daniel Edelmann, Nicole E Schmid, Markus Oberpaul, Patrick Blumenkamp, Sebastian Schmidt, Ana Natriashvili, Maximilian H Ulbrich, Andreas Tholey, Hans-Georg Koch, Bork A Berghoff","doi":"10.1128/msystems.01060-24","DOIUrl":"https://doi.org/10.1128/msystems.01060-24","url":null,"abstract":"<p><p>Bacterial dormancy is a valuable strategy to survive stressful conditions. Toxins from chromosomal toxin-antitoxin systems have the potential to halt cell growth, induce dormancy, and eventually promote a stress-tolerant persister state. Due to their potential toxicity when overexpressed, sophisticated expression systems are needed when studying toxin genes. Here, we present a moderate expression system for toxin genes based on an artificial 5' untranslated region. We applied the system to induce expression of the toxin gene <i>tisB</i> from the chromosomal type I toxin-antitoxin system <i>tisB/istR-1</i> in <i>Escherichia coli</i>. TisB is a small hydrophobic protein that targets the inner membrane, resulting in depolarization and ATP depletion. We analyzed TisB-producing cells by RNA-sequencing and revealed several genes with a role in recovery from TisB-induced dormancy, including the chaperone genes <i>ibpAB</i> and <i>spy</i>. The importance of chaperone genes suggested that TisB-producing cells are prone to protein aggregation, which was validated by an <i>in vivo</i> fluorescent reporter system. We moved on to show that TisB is an essential factor for protein aggregation upon DNA damage mediated by the fluoroquinolone antibiotic ciprofloxacin in <i>E. coli</i> wild-type cells. The occurrence of protein aggregates correlates with an extended dormancy duration, which underscores their importance for the life cycle of TisB-dependent persister cells.</p><p><strong>Importance: </strong>Protein aggregates occur in all living cells due to misfolding of proteins. In bacteria, protein aggregation is associated with cellular inactivity, which is related to dormancy and tolerance to stressful conditions, including exposure to antibiotics. In <i>Escherichia coli</i>, the membrane toxin TisB is an important factor for dormancy and antibiotic tolerance upon DNA damage mediated by the fluoroquinolone antibiotic ciprofloxacin. Here, we show that TisB provokes protein aggregation, which, in turn, promotes an extended state of cellular dormancy. Our study suggests that protein aggregation is a consequence of membrane toxins with the potential to affect the duration of dormancy and the outcome of antibiotic therapy.</p>","PeriodicalId":18819,"journal":{"name":"mSystems","volume":null,"pages":null},"PeriodicalIF":5.0,"publicationDate":"2024-10-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142391907","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":"NanoCore: core-genome-based bacterial genomic surveillance and outbreak detection in healthcare facilities from Nanopore and Illumina data.","authors":"Sebastian A Fuchs, Lisanna Hülse, Teresa Tamayo, Susanne Kolbe-Busch, Klaus Pfeffer, Alexander T Dilthey","doi":"10.1128/msystems.01080-24","DOIUrl":"10.1128/msystems.01080-24","url":null,"abstract":"&lt;p&gt;&lt;p&gt;Genomic surveillance enables the early detection of pathogen transmission in healthcare facilities and contributes to the reduction of substantial patient harm. Fast turnaround times, flexible multiplexing, and low capital requirements make Nanopore sequencing well suited for genomic surveillance purposes; the analysis of Nanopore data, however, can be challenging. We present NanoCore, a user-friendly method for Nanopore-based genomic surveillance in healthcare facilities, enabling the calculation and visualization of cgMLST-like (core-genome multilocus sequence typing) sample distances directly from unassembled Nanopore reads. NanoCore implements a mapping, variant calling, and multilevel filtering strategy and also supports the analysis of Illumina data. We validated NanoCore on two 24-isolate data sets of methicillin-resistant &lt;i&gt;Staphylococcus aureus&lt;/i&gt; (MRSA) and vancomycin-resistant &lt;i&gt;Enterococcus faecium&lt;/i&gt; (VRE). In the Nanopore-only mode, NanoCore-based pairwise distances between closely related isolates were near-identical to Illumina-based SeqSphere&lt;sup&gt;+&lt;/sup&gt; distances, a gold standard commercial method (average differences of 0.75 and 0.81 alleles for MRSA and VRE; sd = 0.98 and 1.00), and gave an identical clustering into closely related and non-closely related isolates. In the \"hybrid\" mode, in which only Nanopore data are used for some isolates and only Illumina data for others, increased average pairwise isolate distance differences were observed (average differences of 3.44 and 1.95 for MRSA and VRE, respectively; sd = 2.76 and 1.34), while clustering results remained identical. NanoCore is computationally efficient (&lt;15 hours of wall time for the analysis of a 24-isolate data set on a workstation), available as free software, and supports installation via conda. In conclusion, NanoCore enables the effective use of the Nanopore technology for bacterial pathogen surveillance in healthcare facilities.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Importance: &lt;/strong&gt;Genomic surveillance involves sequencing the genomes and measuring the relatedness of bacteria from different patients or locations in the same healthcare facility, enabling an improved understanding of pathogen transmission pathways and the detection of \"silent\" outbreaks that would otherwise go undetected. It has become an indispensable tool for the detection and prevention of healthcare-associated infections and is routinely applied by many healthcare institutions. The earlier an outbreak or transmission chain is detected, the better; in this context, the Oxford Nanopore sequencing technology has important potential advantages over traditionally used short-read sequencing technologies, because it supports \"real-time\" data generation and the cost-effective \"on demand\" sequencing of small numbers of bacterial isolates. The analysis of Nanopore sequencing data, however, can be challenging. We present NanoCore, a user-friendly software for genomic surveillance that works directly based on N","PeriodicalId":18819,"journal":{"name":"mSystems","volume":null,"pages":null},"PeriodicalIF":5.0,"publicationDate":"2024-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142381283","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":"Pan-genome-scale metabolic modeling of <i>Bacillus subtilis</i> reveals functionally distinct groups.","authors":"Maxwell Neal, William Brakewood, Michael Betenbaugh, Karsten Zengler","doi":"10.1128/msystems.00923-24","DOIUrl":"https://doi.org/10.1128/msystems.00923-24","url":null,"abstract":"<p><p><i>Bacillus subtilis</i> is an important industrial and environmental microorganism known to occupy many niches and produce many compounds of interest. Although it is one of the best-studied organisms, much of this focus including the reconstruction of genome-scale metabolic models has been placed on a few key laboratory strains. Here, we substantially expand these prior models to pan-genome-scale, representing 481 genomes of <i>B. subtilis</i> with 2,315 orthologous gene clusters, 1,874 metabolites, and 2,239 reactions. Furthermore, we incorporate data from carbon utilization experiments for eight strains to refine and validate its metabolic predictions. This comprehensive pan-genome model enables the assessment of strain-to-strain differences related to nutrient utilization, fermentation outputs, robustness, and other metabolic aspects. Using the model and phenotypic predictions, we divide <i>B. subtilis</i> strains into five groups with distinct patterns of behavior that correlate across these features. The pan-genome model offers deep insights into <i>B. subtilis'</i> metabolism as it varies across environments and provides an understanding as to how different strains have adapted to dynamic habitats.</p><p><strong>Importance: </strong>As the volume of genomic data and computational power have increased, so has the number of genome-scale metabolic models. These models encapsulate the totality of metabolic functions for a given organism. <i>Bacillus subtilis</i> strain 168 is one of the first bacteria for which a metabolic network was reconstructed. Since then, several updated reconstructions have been generated for this model microorganism. Here, we expand the metabolic model for a single strain into a pan-genome-scale model, which consists of individual models for 481 <i>B. subtilis</i> strains. By evaluating differences between these strains, we identified five distinct groups of strains, allowing for the rapid classification of any particular strain. Furthermore, this classification into five groups aids the rapid identification of suitable strains for any application.</p>","PeriodicalId":18819,"journal":{"name":"mSystems","volume":null,"pages":null},"PeriodicalIF":5.0,"publicationDate":"2024-10-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142372285","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":"Advancing microbiome research in Māori populations: insights from recent literature exploring the gut microbiomes of underrepresented and Indigenous peoples.","authors":"Ella T Silk, Simone B Bayer, Meika Foster, Nicole C Roy, Michael W Taylor, Tommi Vatanen, Richard B Gearry","doi":"10.1128/msystems.00909-24","DOIUrl":"https://doi.org/10.1128/msystems.00909-24","url":null,"abstract":"<p><p>The gut microbiome plays vital roles in human health, including mediating metabolism, immunity, and the gut-brain axis. Many ethnicities remain underrepresented in gut microbiome research, with significant variation between Indigenous and non-Indigenous peoples due to dietary, socioeconomic, health, and urbanization differences. Although research regarding the microbiomes of Indigenous peoples is increasing, Māori microbiome literature is lacking despite widespread inequities that Māori populations face. These inequities likely contribute to gut microbiome differences that exacerbate negative health outcomes. Characterizing the gut microbiomes of underrepresented populations is necessary to inform efforts to address health inequities. However, for microbiome research to be culturally responsible and meaningful, study design must improve to better protect the rights and interests of Indigenous peoples. Here, we discuss barriers to Indigenous participation in research and the role disparities may play in shaping the gut microbiomes of Indigenous peoples, with a particular focus on implications for Māori and areas for improvement.</p>","PeriodicalId":18819,"journal":{"name":"mSystems","volume":null,"pages":null},"PeriodicalIF":5.0,"publicationDate":"2024-10-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142372284","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":"Correction for Noh et al., “Reduced and Nonreduced Genomes in Paraburkholderia Symbionts of Social Amoebas”","authors":"Suegene NohBenjamin J. CapodannoSongtao XuMarisa C. HamiltonJoan E. StrassmannDavid C. Queller","doi":"10.1128/msystems.01065-24","DOIUrl":"https://doi.org/10.1128/msystems.01065-24","url":null,"abstract":"mSystems, Ahead of Print. <br/>","PeriodicalId":18819,"journal":{"name":"mSystems","volume":null,"pages":null},"PeriodicalIF":6.4,"publicationDate":"2024-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142254201","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":"Semantic search using protein large language models detects class II microcins in bacterial genomes","authors":"Anastasiya V. KulikovaJennifer K. ParkerBryan W. DaviesClaus O. Wilke1Department of Integrative Biology, The University of Texas at Austin, Austin, Texas, USA2Department of Molecular Biosciences, The University of Texas at Austin, Austin, Texas, USA3John Ring LaMontagne Center for Infectious Diseases, The University of Texas at Austin, Austin, Texas, USAMarnix Medema","doi":"10.1128/msystems.01044-24","DOIUrl":"https://doi.org/10.1128/msystems.01044-24","url":null,"abstract":"mSystems, Ahead of Print. <br/>","PeriodicalId":18819,"journal":{"name":"mSystems","volume":null,"pages":null},"PeriodicalIF":6.4,"publicationDate":"2024-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142268941","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}