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840901.0000Comparative genomics reveals key adaptive mechanisms in pathogen host-niche specialization. INTRODUCTION: Understanding the key factors that enable bacterial pathogens to adapt to new hosts is crucial, as host-microbe interactions not only influence host health but also drive bacterial genome diversification, thereby enhancing pathogen survival in various ecological niches. METHODS: We conducted a comparative genomic analysis of 4,366 high-quality bacterial genomes isolated from various hosts and environments. Bioinformatics databases and machine learning approaches were used to identify genomic differences in functional categories, virulence factors, and antibiotic resistance genes across different ecological niches. RESULTS: Significant variability in bacterial adaptive strategies was observed. Human-associated bacteria, particularly from the phylum Pseudomonadota, exhibited higher detection rates of carbohydrate-active enzyme genes and virulence factors related to immune modulation and adhesion, indicating co-evolution with the human host. In contrast, bacteria from environmental sources, particularly those from the phyla Bacillota and Actinomycetota, showed greater enrichment in genes related to metabolism and transcriptional regulation, highlighting their high adaptability to diverse environments. Bacteria from clinical settings had higher detection rates of antibiotic resistance genes, particularly those related to fluoroquinolone resistance. Animal hosts were identified as important reservoirs of resistance genes. Key host-specific bacterial genes, such as hypB, were found to potentially play crucial roles in regulating metabolism and immune adaptation in human-associated bacteria. DISCUSSION: These findings highlight niche-specific genomic features and adaptive mechanisms of bacterial pathogens. This study provides valuable insights into the genetic basis of host-pathogen interactions and offers evidence to inform pathogen transmission control, infection management, and antibiotic stewardship.202540547794
841010.9999Unveiling the role of phages in shaping the periodontal microbial ecosystem. The oral microbiome comprises various species and plays a crucial role in maintaining the oral ecosystem and host health. Phages are an important component of the periodontal microbiome, yet our understanding of periodontal phages remains limited. Here, we investigated oral periodontal phages using various advanced bioinformatics tools based on genomes of key periodontitis pathogens. Prophages were found to encode various auxiliary genes that potentially enhance host survival and pathogenicity, including genes involved in carbohydrate metabolism, antibiotic resistance, and immune modulation. We observed cross-species transmission among prophages with a complex network of phage-bacteria interactions. Our findings suggest that prophages play a crucial role in shaping the periodontal microbial ecosystem, influencing microbial community dynamics and the progression of periodontitis.IMPORTANCEIn the context of periodontitis, the ecological dynamics of the microbiome are largely driven by interactions between bacteria and their phages. While the impact of prophages on regulating oral pathogens has been increasingly recognized, their role in modulating periodontal disease remains underexplored. This study reveals that prophages within key periodontitis pathogens contribute significantly to virulence factor dissemination, antibiotic resistance, and host metabolism. By influencing the metabolic capabilities and survival strategies of their bacterial hosts, prophages may act as critical regulators of microbial communities in the oral cavity. Understanding these prophage-mediated interactions is essential not only for unraveling the mechanisms of periodontal disease progression but also for developing innovative therapeutic approaches that target the microbial ecosystem at the genetic level. These insights emphasize the need for more comprehensive studies on the ecological risks posed by prophages in shaping microbial pathogenicity and resistance.202540152610
965720.9998Machine Learning Leveraging Genomes from Metagenomes Identifies Influential Antibiotic Resistance Genes in the Infant Gut Microbiome. Antibiotic resistance in pathogens is extensively studied, and yet little is known about how antibiotic resistance genes of typical gut bacteria influence microbiome dynamics. Here, we leveraged genomes from metagenomes to investigate how genes of the premature infant gut resistome correspond to the ability of bacteria to survive under certain environmental and clinical conditions. We found that formula feeding impacts the resistome. Random forest models corroborated by statistical tests revealed that the gut resistome of formula-fed infants is enriched in class D beta-lactamase genes. Interestingly, Clostridium difficile strains harboring this gene are at higher abundance in formula-fed infants than C. difficile strains lacking this gene. Organisms with genes for major facilitator superfamily drug efflux pumps have higher replication rates under all conditions, even in the absence of antibiotic therapy. Using a machine learning approach, we identified genes that are predictive of an organism's direction of change in relative abundance after administration of vancomycin and cephalosporin antibiotics. The most accurate results were obtained by reducing annotated genomic data to five principal components classified by boosted decision trees. Among the genes involved in predicting whether an organism increased in relative abundance after treatment are those that encode subclass B2 beta-lactamases and transcriptional regulators of vancomycin resistance. This demonstrates that machine learning applied to genome-resolved metagenomics data can identify key genes for survival after antibiotics treatment and predict how organisms in the gut microbiome will respond to antibiotic administration. IMPORTANCE The process of reconstructing genomes from environmental sequence data (genome-resolved metagenomics) allows unique insight into microbial systems. We apply this technique to investigate how the antibiotic resistance genes of bacteria affect their ability to flourish in the gut under various conditions. Our analysis reveals that strain-level selection in formula-fed infants drives enrichment of beta-lactamase genes in the gut resistome. Using genomes from metagenomes, we built a machine learning model to predict how organisms in the gut microbial community respond to perturbation by antibiotics. This may eventually have clinical applications.201829359195
972930.9998Omics technology draws a comprehensive heavy metal resistance strategy in bacteria. The rapid industrial revolution significantly increased heavy metal pollution, becoming a major global environmental concern. This pollution is considered as one of the most harmful and toxic threats to all environmental components (air, soil, water, animals, and plants until reaching to human). Therefore, scientists try to find a promising and eco-friendly technique to solve this problem i.e., bacterial bioremediation. Various heavy metal resistance mechanisms were reported. Omics technologies can significantly improve our understanding of heavy metal resistant bacteria and their communities. They are a potent tool for investigating the adaptation processes of microbes in severe conditions. These omics methods provide unique benefits for investigating metabolic alterations, microbial diversity, and mechanisms of resistance of individual strains or communities to harsh conditions. Starting with genome sequencing which provides us with complete and comprehensive insight into the resistance mechanism of heavy metal resistant bacteria. Moreover, genome sequencing facilitates the opportunities to identify specific metal resistance genes, operons, and regulatory elements in the genomes of individual bacteria, understand the genetic mechanisms and variations responsible for heavy metal resistance within and between bacterial species in addition to the transcriptome, proteome that obtain the real expressed genes. Moreover, at the community level, metagenome, meta transcriptome and meta proteome participate in understanding the microbial interactive network potentially novel metabolic pathways, enzymes and gene species can all be found using these methods. This review presents the state of the art and anticipated developments in the use of omics technologies in the investigation of microbes used for heavy metal bioremediation.202438709343
768140.9998Amoebae contribute to the diversity and fate of antibiotic resistance genes in drinking water system. Free-living amoebae represent a significant eukaryotic group that thrives in drinking water systems, posing considerable risks to water quality due to their inherent pathogenicity and associations with various microorganisms. However, the symbiotic microbial profiles of different amoeba species and the impact of amoeba-bacteria interactions on the antibiotic resistome within drinking water systems remain poorly understood. In this study, we obtained 24 amoeba isolates from tap water, encompassing diverse phyla within the amoeba lineage. Through metagenome sequencing, we uncovered variations in symbiotic microbiome composition across different amoeba species and strains. Notably, amoebae acted as vectors for human pathogens, including bacteria and viruses. The majority of symbionts carried multiple antibiotic-resistance genes and virulence factors. Furthermore, dominant symbiotic species could be cultured independently, underscoring the critical role of amoebae in preserving and transmitting antibiotic-resistant opportunistic pathogens in drinking water systems. Disinfection experiments demonstrated highly diverse viability of amoebae and their protective capabilities for symbionts against chlorine disinfection. Our findings expand the germplasm bank for amoebae and symbiotic bacteria derived from tap water and emphasize the necessity for further research on amoeba-bacteria symbiosis to ensure drinking water quality and public health safety.202541101029
403650.9998Man-made microbial resistances in built environments. Antimicrobial resistance is a serious threat to global public health, but little is known about the effects of microbial control on the microbiota and its associated resistome. Here we compare the microbiota present on surfaces of clinical settings with other built environments. Using state-of-the-art metagenomics approaches and genome and plasmid reconstruction, we show that increased confinement and cleaning is associated with a loss of microbial diversity and a shift from Gram-positive bacteria, such as Actinobacteria and Firmicutes, to Gram-negative such as Proteobacteria. Moreover, the microbiome of highly maintained built environments has a different resistome when compared to other built environments, as well as a higher diversity in resistance genes. Our results highlight that the loss of microbial diversity correlates with an increase in resistance, and the need for implementing strategies to restore bacterial diversity in certain built environments.201930814504
966460.9998Distribution of Genetic Determinants Associated with CRISPR-Cas Systems and Resistance to Antibiotics in the Genomes of Archaea and Bacteria. The CRISPR-Cas system represents an adaptive immune mechanism found across diverse Archaea and Bacteria, allowing them to defend against invading genetic elements such as viruses and plasmids. Despite its broad distribution, the prevalence and complexity of CRISPR-Cas systems differ significantly between these domains. This study aimed to characterize and compare the genomic distribution, structural features, and functional implications of CRISPR-Cas systems and associated antibiotic resistance genes in 30 archaeal and 30 bacterial genomes. Through bioinformatic analyses of CRISPR arrays, cas gene architectures, direct repeats (DRs), and thermodynamic properties, we observed that Archaea exhibit a higher number and greater complexity of CRISPR loci, with more diverse cas gene subtypes exclusively of Class 1. Bacteria, in contrast, showed fewer CRISPR loci, comprising a mix of Class 1 and Class 2 systems, with Class 1 representing the majority (~75%) of the detected systems. Notably, Bacteria lacking CRISPR-Cas systems displayed a higher prevalence of antibiotic resistance genes, suggesting a possible inverse correlation between the presence of these immune systems and the acquisition of such genes. Phylogenetic and thermodynamic analyses further highlighted domain-specific adaptations and conservation patterns. These findings support the hypothesis that CRISPR-Cas systems play a dual role: first, as a defense mechanism preventing the integration of foreign genetic material-reflected in the higher complexity and diversity of CRISPR loci in Archaea-and second, as a regulator of horizontal gene transfer, evidenced by the lower frequency of antibiotic resistance genes in organisms with active CRISPR-Cas systems. Together, these results underscore the evolutionary and functional diversification of CRISPR-Cas systems in response to environmental and selective pressures.202540572209
966070.9998Interkingdom Gut Microbiome and Resistome of the Cockroach Blattella germanica. Cockroaches are intriguing animals with two coexisting symbiotic systems, an endosymbiont in the fat body, involved in nitrogen metabolism, and a gut microbiome whose diversity, complexity, role, and developmental dynamics have not been fully elucidated. In this work, we present a metagenomic approach to study Blattella germanica populations not treated, treated with kanamycin, and recovered after treatment, both naturally and by adding feces to the diet, with the aim of better understanding the structure and function of its gut microbiome along the development as well as the characterization of its resistome.IMPORTANCE For the first time, we analyze the interkingdom hindgut microbiome of this species, including bacteria, fungi, archaea, and viruses. Network analysis reveals putative cooperation between core bacteria that could be key for ecosystem equilibrium. We also show how antibiotic treatments alter microbiota diversity and function, while both features are restored after one untreated generation. Combining data from B. germanica treated with three antibiotics, we have characterized this species' resistome. It includes genes involved in resistance to several broad-spectrum antibiotics frequently used in the clinic. The presence of genetic elements involved in DNA mobilization indicates that they can be transferred among microbiota partners. Therefore, cockroaches can be considered reservoirs of antibiotic resistance genes (ARGs) and potential transmission vectors.202133975971
964880.9998The highly diverse Antarctic Peninsula soil microbiota as a source of novel resistance genes. The rise of multiresistant bacterial pathogens is currently one of the most critical threats to global health, encouraging a better understanding of the evolution and spread of antimicrobial resistance. In this regard, the role of the environment as a source of resistance mechanisms remains poorly understood. Moreover, we still know a minimal part of the microbial diversity and resistome present in remote and extreme environments, hosting microbes that evolved to resist harsh conditions and thus a potentially rich source of novel resistance genes. This work demonstrated that the Antarctic Peninsula soils host a remarkable microbial diversity and a widespread presence of autochthonous antibiotic-resistant bacteria and resistance genes. We observed resistance to a wide array of antibiotics among isolates, including Pseudomonas resisting ten or more different compounds, with an overall increased resistance in bacteria from non-intervened areas. In addition, genome analysis of selected isolates showed several genes encoding efflux pumps, as well as a lack of known resistance genes for some of the resisted antibiotics, including colistin, suggesting novel uncharacterized mechanisms. By combining metagenomic approaches based on analyzing raw reads, assembled contigs, and metagenome-assembled genomes, we found hundreds of widely distributed genes potentially conferring resistance to different antibiotics (including an outstanding variety of inactivation enzymes), metals, and biocides, hosted mainly by Polaromonas, Pseudomonas, Streptomyces, Variovorax, and Burkholderia. Furthermore, a proportion of these genes were found inside predicted plasmids and other mobile elements, including a putative OXA-like carbapenemase from Polaromonas harboring conserved key residues and predicted structural features. All this evidence indicates that the Antarctic Peninsula soil microbiota has a broad natural resistome, part of which could be transferred horizontally to pathogenic bacteria, acting as a potential source of novel resistance genes.202234856283
378290.9998CRISPR spacers acquired from plasmids primarily target backbone genes, making them valuable for predicting potential hosts and host range. In recent years, there has been a surge in metagenomic studies focused on identifying plasmids in environmental samples. Although these studies have unearthed numerous novel plasmids, enriching our understanding of their environmental roles, a significant gap remains: the scarcity of information regarding the bacterial hosts of these newly discovered plasmids. Furthermore, even when plasmids are identified within bacterial isolates, the reported host is typically limited to the original isolate, with no insights into alternative hosts or the plasmid's potential host range. Given that plasmids depend on hosts for their existence, investigating plasmids without the knowledge of potential hosts offers only a partial perspective. This study introduces a method for identifying potential hosts and host ranges for plasmids through alignment with CRISPR spacers. To validate the method, we compared the PLSDB plasmids database with the CRISPR spacers database, yielding host predictions for 46% of the plasmids. When compared with reported hosts, our predictions achieved 84% concordance at the family level and 99% concordance at the phylum level. Moreover, the method frequently identified multiple potential hosts for a plasmid, thereby enabling predictions of alternative hosts and the host range. Notably, we found that CRISPR spacers predominantly target plasmid backbone genes while sparing functional genes, such as those linked to antibiotic resistance, aligning with our hypothesis that CRISPR spacers are acquired from plasmid-specific regions rather than insertion elements from diverse sources. Finally, we illustrate the network of connections among different bacterial taxa through plasmids, revealing potential pathways for horizontal gene transfer.IMPORTANCEPlasmids are notorious for their role in distributing antibiotic resistance genes, but they may also carry and distribute other environmentally important genes. Since plasmids are not free-living entities and rely on host bacteria for survival and propagation, predicting their hosts is essential. This study presents a method for predicting potential hosts for plasmids and offers insights into the potential paths for spreading functional genes between different bacteria. Understanding plasmid-host relationships is crucial for comprehending the ecological and clinical impact of plasmids and implications for various biological processes.202439508585
3783100.9998Ecology drives a global network of gene exchange connecting the human microbiome. Horizontal gene transfer (HGT), the acquisition of genetic material from non-parental lineages, is known to be important in bacterial evolution. In particular, HGT provides rapid access to genetic innovations, allowing traits such as virulence, antibiotic resistance and xenobiotic metabolism to spread through the human microbiome. Recent anecdotal studies providing snapshots of active gene flow on the human body have highlighted the need to determine the frequency of such recent transfers and the forces that govern these events. Here we report the discovery and characterization of a vast, human-associated network of gene exchange, large enough to directly compare the principal forces shaping HGT. We show that this network of 10,770 unique, recently transferred (more than 99% nucleotide identity) genes found in 2,235 full bacterial genomes, is shaped principally by ecology rather than geography or phylogeny, with most gene exchange occurring between isolates from ecologically similar, but geographically separated, environments. For example, we observe 25-fold more HGT between human-associated bacteria than among ecologically diverse non-human isolates (P = 3.0 × 10(-270)). We show that within the human microbiome this ecological architecture continues across multiple spatial scales, functional classes and ecological niches with transfer further enriched among bacteria that inhabit the same body site, have the same oxygen tolerance or have the same ability to cause disease. This structure offers a window into the molecular traits that define ecological niches, insight that we use to uncover sources of antibiotic resistance and identify genes associated with the pathology of meningitis and other diseases.201122037308
9004110.9998Shedding light on the bacterial resistance to toxic UV filters: a comparative genomic study. UV filters are toxic to marine bacteria that dominate the marine biomass. Ecotoxicology often studies the organism response but rarely integrates the toxicity mechanisms at the molecular level. In this study, in silico comparative genomics between UV filters sensitive and resistant bacteria were conducted in order to unravel the genes responsible for a resistance phenotype. The genomes of two environmentally relevant Bacteroidetes and three Firmicutes species were compared through pairwise comparison. Larger genomes were carried by bacteria exhibiting a resistant phenotype, favoring their ability to adapt to environmental stresses. While the antitoxin and CRISPR systems were the only distinctive features in resistant Bacteroidetes, Firmicutes displayed multiple unique genes that could support the difference between sensitive and resistant phenotypes. Several genes involved in ROS response, vitamin biosynthesis, xenobiotic degradation, multidrug resistance, and lipophilic compound permeability were shown to be exclusive to resistant species. Our investigation contributes to a better understanding of UV filters resistance phenotypes, by identifying pivotal genes involved in key pathways.202134760358
9661120.9998Pangenomes of human gut microbiota uncover links between genetic diversity and stress response. The genetic diversity of the gut microbiota has a central role in host health. Here, we created pangenomes for 728 human gut prokaryotic species, quadrupling the genes of strain-specific genomes. Each of these species has a core set of a thousand genes, differing even between closely related species, and an accessory set of genes unique to the different strains. Functional analysis shows high strain variability associates with sporulation, whereas low variability is linked with antibiotic resistance. We further map the antibiotic resistome across the human gut population and find 237 cases of extreme resistance even to last-resort antibiotics, with a predominance among Enterobacteriaceae. Lastly, the presence of specific genes in the microbiota relates to host age and sex. Our study underscores the genetic complexity of the human gut microbiota, emphasizing its significant implications for host health. The pangenomes and antibiotic resistance map constitute a valuable resource for further research.202439353429
9649130.9998Bacteria of the order Burkholderiales are original environmental hosts of type II trimethoprim resistance genes (dfrB). It is consensus that clinically relevant antibiotic resistance genes have their origin in environmental bacteria, including the large pool of primarily benign species. Yet, for the vast majority of acquired antibiotic resistance genes, the original environmental host(s) has not been identified to date. Closing this knowledge gap could improve our understanding of how antimicrobial resistance proliferates in the bacterial domain and shed light on the crucial step of initial resistance gene mobilization in particular. Here, we combine information from publicly available long- and short-read environmental metagenomes as well as whole-genome sequences to identify the original environmental hosts of dfrB, a family of genes conferring resistance to trimethoprim. Although this gene family stands in the shadow of the more widespread, structurally different dfrA, it has recently gained attention through the discovery of several new members. Based on the genetic context of dfrB observed in long-read metagenomes, we predicted bacteria of the order Burkholderiales to function as original environmental hosts of the predominant gene variants in both soil and freshwater. The predictions were independently confirmed by whole-genome datasets and statistical correlations between dfrB abundance and taxonomic composition of environmental bacterial communities. Our study suggests that Burkholderiales in general and the family Comamonadaceae in particular represent environmental origins of dfrB genes, some of which now contribute to the acquired resistome of facultative pathogens. We propose that our workflow centered on long-read environmental metagenomes allows for the identification of the original hosts of further clinically relevant antibiotic resistance genes.202439658215
9663140.9998The structure of temperate phage-bacteria infection networks changes with the phylogenetic distance of the host bacteria. With their ability to integrate into the bacterial chromosome and thereby transfer virulence or drug-resistance genes across bacterial species, temperate phage play a key role in bacterial evolution. Thus, it is paramount to understand who infects whom to be able to predict the movement of DNA across the prokaryotic world and ultimately the emergence of novel (drug-resistant) pathogens. We empirically investigated lytic infection patterns among Vibrio spp. from distinct phylogenetic clades and their derived temperate phage. We found that across distantly related clades, infections occur preferentially within modules of the same clade. However, when the genetic distance of the host bacteria decreases, these clade-specific infections disappear. This indicates that the structure of temperate phage-bacteria infection networks changes with the phylogenetic distance of the host bacteria.201830429242
7683150.9998Antibiotic Resistomes in Plant Microbiomes. Microorganisms associated with plants may alter the traits of the human microbiome important for human health, but this alteration has largely been overlooked. The plant microbiome is an interface between plants and the environment, and provides many ecosystem functions such as improving nutrient uptake and protecting against biotic and abiotic stress. The plant microbiome also represents a major pathway by which humans are exposed to microbes and genes consumed with food, such as pathogenic bacteria, antibiotic-resistant bacteria, and antibiotic-resistance genes. In this review we highlight the main findings on the composition and function of the plant microbiome, and underline the potential of plant microbiomes in the dissemination of antibiotic resistance via food consumption or direct contact.201930890301
9654160.9998Studying the Association between Antibiotic Resistance Genes and Insertion Sequences in Metagenomes: Challenges and Pitfalls. Antibiotic resistance is an issue in many areas of human activity. The mobilization of antibiotic resistance genes within the bacterial community makes it difficult to study and control the phenomenon. It is known that certain insertion sequences, which are mobile genetic elements, can participate in the mobilization of antibiotic resistance genes and in the expression of these genes. However, the magnitude of the contribution of insertion sequences to the mobility of antibiotic resistance genes remains understudied. In this study, the relationships between insertion sequences and antibiotic resistance genes present in the microbiome were investigated using two public datasets. The first made it possible to analyze the effects of different antibiotics in a controlled mouse model. The second dataset came from a study of the differences between conventional and organic-raised cattle. Although it was possible to find statistically significant correlations between the insertion sequences and antibiotic resistance genes in both datasets, several challenges remain to better understand the contribution of insertion sequences to the motility of antibiotic resistance genes. Obtaining more complete and less fragmented metagenomes with long-read sequencing technologies could make it possible to understand the mechanisms favoring horizontal transfers within the microbiome with greater precision.202336671375
4051170.9998The human microbiome harbors a diverse reservoir of antibiotic resistance genes. The increasing levels of multi-drug resistance in human pathogenic bacteria are compromising our ability to treat infectious disease. Since antibiotic resistance determinants are readily exchanged between bacteria through lateral gene transfer, there is an increasing interest in investigating reservoirs of antibiotic resistance accessible to pathogens. Due to the high likelihood of contact and genetic exchange with pathogens during disease progression, the human microflora warrants special attention as perhaps the most accessible reservoir of resistance genes. Indeed, numerous previous studies have demonstrated substantial antibiotic resistance in cultured isolates from the human microflora. By applying metagenomic functional selections, we recently demonstrated that the functional repertoire of resistance genes in the human microbiome is much more diverse than suggested using previous culture-dependent methods. We showed that many resistance genes from cultured proteobacteria from human fecal samples are identical to resistance genes harbored by human pathogens, providing strong support for recent genetic exchange of this resistance machinery. In contrast, most of the resistance genes we identified with culture independent metagenomic sampling from the same samples were novel when compared to all known genes in public databases. While this clearly demonstrates that the antibiotic resistance reservoir of the large fraction of the human microbiome recalcitrant to culturing is severely under sampled, it may also suggest that barriers exist to lateral gene transfer between these bacteria and readily cultured human pathogens. If we hope to turn the tide against multidrug resistant infections, we must urgently commit to quantitatively characterizing the resistance reservoirs encoded by our diverse human microbiomes, with a particular focus on routes of exchange of these reservoirs with other microbial communities.201021178459
9723180.9997Deciphering the genetic network and programmed regulation of antimicrobial resistance in bacterial pathogens. Antimicrobial resistance (AMR) in bacteria is an important global health problem affecting humans, animals, and the environment. AMR is considered as one of the major components in the "global one health". Misuse/overuse of antibiotics in any one of the segments can impact the integrity of the others. In the presence of antibiotic selective pressure, bacteria tend to develop several defense mechanisms, which include structural changes of the bacterial outer membrane, enzymatic processes, gene upregulation, mutations, adaptive resistance, and biofilm formation. Several components of mobile genetic elements (MGEs) play an important role in the dissemination of AMR. Each one of these components has a specific function that lasts long, irrespective of any antibiotic pressure. Integrative and conjugative elements (ICEs), insertion sequence elements (ISs), and transposons carry the antimicrobial resistance genes (ARGs) on different genetic backbones. Successful transfer of ARGs depends on the class of plasmids, regulons, ISs proximity, and type of recombination systems. Additionally, phage-bacterial networks play a major role in the transmission of ARGs, especially in bacteria from the environment and foods of animal origin. Several other functional attributes of bacteria also get successfully modified to acquire ARGs. These include efflux pumps, toxin-antitoxin systems, regulatory small RNAs, guanosine pentaphosphate signaling, quorum sensing, two-component system, and clustered regularly interspaced short palindromic repeats (CRISPR) systems. The metabolic and virulence state of bacteria is also associated with a range of genetic and phenotypic resistance mechanisms. In spite of the availability of a considerable information on AMR, the network associations between selection pressures and several of the components mentioned above are poorly understood. Understanding how a pathogen resists and regulates the ARGs in response to antimicrobials can help in controlling the development of resistance. Here, we provide an overview of the importance of genetic network and regulation of AMR in bacterial pathogens.202236506027
5101190.9997Identification of Key Features Pivotal to the Characteristics and Functions of Gut Bacteria Taxa through Machine Learning Methods. BACKGROUND: Gut bacteria critically influence digestion, facilitate the breakdown of complex food substances, aid in essential nutrient synthesis, and contribute to immune system balance. However, current knowledge regarding intestinal bacteria remains insufficient. OBJECTIVE: This study aims to discover essential differences for different intestinal bacteria. METHODS: This study was conducted by investigating a total of 1478 gut bacterial samples comprising 235 Actinobacteria, 447 Bacteroidetes, and 796 Firmicutes, by utilizing sophisticated machine learning algorithms. By building on the dataset provided by Chen et al., we engaged sophisticated machine learning techniques to further investigate and analyze the gut bacterial samples. Each sample in the dataset was described by 993 unique features associated with gut bacteria, including 342 features annotated by the Antibiotic Resistance Genes Database, Comprehensive Antibiotic Research Database, Kyoto Encyclopedia of Genes and Genomes, and Virulence Factors of Pathogenic Bacteria. We employed incremental feature selection methods within a computational framework to identify the optimal features for classification. RESULTS: Eleven feature ranking algorithms selected several key features as pivotal to the characteristics and functions of gut bacteria. These features appear to facilitate the identification of specific gut bacterial species. Additionally, we established quantitative rules for identifying Actinobacteria, Bacteroidetes, and Firmicutes. CONCLUSION: This research underscores the significant potential of machine learning in studying gut microbes and enhances our understanding of the multifaceted roles of gut bacteria.202540671232