Racial disparities in metastatic colorectal cancer outcomes revealed by tumor microbiome and transcriptome analysis with bevacizumab treatment. - Related Documents




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818701.0000Racial disparities in metastatic colorectal cancer outcomes revealed by tumor microbiome and transcriptome analysis with bevacizumab treatment. Background: Metastatic colorectal cancer (mCRC) is a heterogeneous disease, often associated with poor outcomes and resistance to therapies. The racial variations in the molecular and microbiological profiles of mCRC patients, however, remain under-explored. Methods: Using RNA-SEQ data, we extracted and analyzed actively transcribing microbiota within the tumor milieu, ensuring that the identified bacteria were not merely transient inhabitants but engaged in the tumor ecosystem. Also, we independently acquired samples from 12 mCRC patients, specifically, 6 White individuals and 6 of Black or African American descent. These samples underwent 16S rRNA sequencing. Results: Our study revealed notable racial disparities in the molecular signatures and microbiota profiles of mCRC patients. The intersection of these data showcased the potential modulating effects of specific bacteria on gene expression. Particularly, the bacteria Helicobacter cinaedi and Sphingobium herbicidovorans emerged as significant influencers, with strong correlations to the genes SELENBP1 and SNORA38, respectively. Discussion: These findings underscore the intricate interplay between host genomics and actively transcribing tumor microbiota in mCRC's pathogenesis. The identified correlations between specific bacteria and genes highlight potential avenues for targeted therapies and a more personalized therapeutic approach.202338357363
769710.9983Impact of sample multiplexing on detection of bacteria and antimicrobial resistance genes in pig microbiomes using long-read sequencing. The effects of sample multiplexing on the detection sensitivity of antimicrobial resistance genes (ARGs) and pathogenic bacteria in metagenomic sequencing remain underexplored in newer sequencing technologies such as Oxford Nanopore Technologies (ONT), despite its critical importance for surveillance applications. Here, we evaluate how different multiplexing levels (four and eight samples per flowcell) on two ONT platforms, GridION and PromethION, influence the detection of ARGs, bacterial taxa and pathogens. While overall resistome and bacterial community profiles remained comparable across multiplexing levels, ARG detection was more comprehensive in the four-plex setting with low-abundance genes. Similarly, pathogen detection was more sensitive in the four-plex, identifying a broader range of low abundant bacterial taxa compared to the eight-plex. However, triplicate sequencing of the same microbiomes revealed that these differences were primarily due to sequencing variability rather than multiplexing itself, as similar inconsistencies were observed across replicates. Given that eight-plex sequencing is more cost-effective while still capturing the overall resistome and bacterial community composition, it may be the preferred option for general surveillance. Lower multiplexing levels may be advantageous for applications requiring enhanced sensitivity, such as detailed pathogen research. These findings highlight the trade-off between multiplexing efficiency, sequencing depth, and cost in metagenomic studies.202540611965
464220.9982Characterization of antibiotic resistance and host-microbiome interactions in the human upper respiratory tract during influenza infection. BACKGROUND: The abundance and diversity of antibiotic resistance genes (ARGs) in the human respiratory microbiome remain poorly characterized. In the context of influenza virus infection, interactions between the virus, the host, and resident bacteria with pathogenic potential are known to complicate and worsen disease, resulting in coinfection and increased morbidity and mortality of infected individuals. When pathogenic bacteria acquire antibiotic resistance, they are more difficult to treat and of global health concern. Characterization of ARG expression in the upper respiratory tract could help better understand the role antibiotic resistance plays in the pathogenesis of influenza-associated bacterial secondary infection. RESULTS: Thirty-seven individuals participating in the Household Influenza Transmission Study (HITS) in Managua, Nicaragua, were selected for this study. We performed metatranscriptomics and 16S rRNA gene sequencing analyses on nasal and throat swab samples, and host transcriptome profiling on blood samples. Individuals clustered into two groups based on their microbial gene expression profiles, with several microbial pathways enriched with genes differentially expressed between groups. We also analyzed antibiotic resistance gene expression and determined that approximately 25% of the sequence reads that corresponded to antibiotic resistance genes mapped to Streptococcus pneumoniae and Staphylococcus aureus. Following construction of an integrated network of ARG expression with host gene co-expression, we identified several host key regulators involved in the host response to influenza virus and bacterial infections, and host gene pathways associated with specific antibiotic resistance genes. CONCLUSIONS: This study indicates the host response to influenza infection could indirectly affect antibiotic resistance gene expression in the respiratory tract by impacting the microbial community structure and overall microbial gene expression. Interactions between the host systemic responses to influenza infection and antibiotic resistance gene expression highlight the importance of viral-bacterial co-infection in acute respiratory infections like influenza. Video abstract.202032178738
428930.9982Microbes of the human eye: Microbiome, antimicrobial resistance and biofilm formation. BACKGROUND: The review focuses on the bacteria associated with the human eye using the dual approach of detecting cultivable bacteria and the total microbiome using next generation sequencing. The purpose of this review was to highlight the connection between antimicrobial resistance and biofilm formation in ocular bacteria. METHODS: Pubmed was used as the source to catalogue culturable bacteria and ocular microbiomes associated with the normal eyes and those with ocular diseases, to ascertain the emergence of anti-microbial resistance with special reference to biofilm formation. RESULTS: This review highlights the genetic strategies used by microorganisms to evade the lethal effects of anti-microbial agents by tracing the connections between candidate genes and biofilm formation. CONCLUSION: The eye has its own microbiome which needs to be extensively studied under different physiological conditions; data on eye microbiomes of people from different ethnicities, geographical regions etc. are also needed to understand how these microbiomes affect ocular health.202133549582
960340.9981Resistance signatures manifested in early drug response across cancer types and species. Aim: Growing evidence points to non-genetic mechanisms underlying long-term resistance to cancer therapies. These mechanisms involve pre-existing or therapy-induced transcriptional cell states that confer resistance. However, the relationship between early transcriptional responses to treatment and the eventual emergence of resistant states remains poorly understood. Furthermore, it is unclear whether such early resistance-associated transcriptional responses are evolutionarily conserved. In this study, we examine the similarity between early transcriptional responses and long-term resistant states, assess their clinical relevance, and explore their evolutionary conservation across species. Methods: We integrated datasets on early drug responses and long-term resistance from multiple cancer cell lines, bacteria, and yeast to identify early transcriptional changes predictive of long-term resistance and assess their evolutionary conservation. Using genome-wide CRISPR-Cas9 knockout screens, we evaluated the impact of genes associated with resistant transcriptional states on drug sensitivity. Clinical datasets were analyzed to explore the prognostic value of the identified resistance-associated gene signatures. Results: We found that transcriptional states observed in drug-naive cells and shortly after treatment overlapped with those seen in fully resistant populations. Some of these shared features appear to be evolutionarily conserved. Knockout of genes marking resistant states sensitized ovarian cancer cells to Prexasertib. Moreover, early resistance gene signatures effectively distinguished therapy responders from non-responders in multiple clinical cancer trials and differentiated premalignant breast lesions that progressed to malignancy from those that remained benign. Conclusion: Early cellular transcriptional responses to therapy exhibit key similarities to fully resistant states across different drugs, cancer types, and species. Gene signatures defining these early resistance states have prognostic value in clinical settings.202541019980
770350.9981The impact of antibiotic exposure on antibiotic resistance gene dynamics in the gut microbiota of inflammatory bowel disease patients. BACKGROUND: While antibiotics are commonly used to treat inflammatory bowel disease (IBD), their widespread application can disturb the gut microbiota and foster the emergence and spread of antibiotic resistance. However, the dynamic changes to the human gut microbiota and direction of resistance gene transmission under antibiotic effects have not been clearly elucidated. METHODS: Based on the Human Microbiome Project, a total of 90 fecal samples were collected from 30 IBD patients before, during and after antibiotic treatment. Through the analysis workflow of metagenomics, we described the dynamic process of changes in bacterial communities and resistance genes pre-treatment, during and post-treatment. We explored potential consistent relationships between gut microbiota and resistance genes, and established gene transmission networks among species before and after antibiotic use. RESULTS: Exposure to antibiotics can induce alterations in the composition of the gut microbiota in IBD patients, particularly a reduction in probiotics, which gradually recovers to a new steady state after cessation of antibiotics. Network analyses revealed intra-phylum transfers of resistance genes, predominantly between taxonomically close organisms. Specific resistance genes showed increased prevalence and inter-species mobility after antibiotic cessation. CONCLUSION: This study demonstrates that antibiotics shape the gut resistome through selective enrichment and promotion of horizontal gene transfer. The findings provide insights into ecological processes governing resistance gene dynamics and dissemination upon antibiotic perturbation of the microbiota. Optimizing antibiotic usage may help limit unintended consequences like increased resistance in gut bacteria during IBD management.202438694799
510160.9981Identification 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
840970.9981Comparative 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
841380.9981Investigating mechanisms underlying genetic resistance to Salmon Rickettsial Syndrome in Atlantic salmon using RNA sequencing. BACKGROUND: Salmon Rickettsial Syndrome (SRS), caused by Piscirickettsia salmonis, is one of the primary causes of morbidity and mortality in Atlantic salmon aquaculture, particularly in Chile. Host resistance is a heritable trait, and functional genomic studies have highlighted genes and pathways important in the response of salmon to the bacteria. However, the functional mechanisms underpinning genetic resistance are not yet well understood. In the current study, a large population of salmon pre-smolts were challenged with P. salmonis, with mortality levels recorded and samples taken for genotyping. In parallel, head kidney and liver samples were taken from animals of the same population with high and low genomic breeding values for resistance, and used for RNA-Sequencing to compare their transcriptome profile both pre and post infection. RESULTS: A significant and moderate heritability (h(2) = 0.43) was shown for the trait of binary survival. Genome-wide association analyses using 38 K imputed SNP genotypes across 2265 animals highlighted that resistance is a polygenic trait. Several thousand genes were identified as differentially expressed between controls and infected samples, and enriched pathways related to the host immune response were highlighted. In addition, several networks with significant correlation with SRS resistance breeding values were identified, suggesting their involvement in mediating genetic resistance. These included apoptosis, cytoskeletal organisation, and the inflammasome. CONCLUSIONS: While resistance to SRS is a polygenic trait, this study has highlighted several relevant networks and genes that are likely to play a role in mediating genetic resistance. These genes may be future targets for functional studies, including genome editing, to further elucidate their role underpinning genetic variation in host resistance.202133676414
770790.9981Exploring the dynamics of gut microbiota, antibiotic resistance, and chemotherapy impact in acute leukemia patients: A comprehensive metagenomic analysis. Leukemia poses significant challenges to its treatment, and understanding its complex pathogenesis is crucial. This study used metagenomic sequencing to investigate the interplay between chemotherapy, gut microbiota, and antibiotic resistance in patients with acute leukemia (AL). Pre- and post-chemotherapy stool samples from patients revealed alterations in microbial richness, taxa, and antibiotic resistance genes (ARGs). The analysis revealed a decreased alpha diversity, increased dispersion in post-chemotherapy samples, and changes in the abundance of specific bacteria. Key bacteria such as Enterococcus, Klebsiella, and Escherichia coli have been identified as prevalent ARG carriers. Correlation analysis between gut microbiota and blood indicators revealed potential links between microbial species and inflammatory biomarkers, including C-reactive protein (CRP) and adenosine deaminase (ADA). This study investigated the impact of antibiotic dosage on microbiota and ARGs, revealing networks connecting co-occurring ARGs with microbial species (179 nodes, 206 edges), and networks associated with ARGs and antibiotic dosages (50 nodes, 50 edges). Antibiotics such as cephamycin and sulfonamide led to multidrug-resistant Klebsiella colonization. Our analyses revealed distinct microbial profiles with Salmonella enterica elevated post-chemotherapy in NF patients and Akkermansia muciniphila elevated pre-chemotherapy. These microbial signatures could inform strategies to modulate the gut microbiome, potentially mitigating the risk of neutropenic fever in patients undergoing chemotherapy. Finally, a comprehensive analysis of KEGG modules shed light on disrupted metabolic pathways after chemotherapy, providing insights into potential targets for managing side effects. Overall, this study revealed intricate relationships between gut microbiota, chemotherapy, and antibiotic resistance, providing new insights into improving therapy and enhancing patient outcomes.202439620486
4712100.9981The chicken gut metagenome and the modulatory effects of plant-derived benzylisoquinoline alkaloids. BACKGROUND: Sub-therapeutic antibiotics are widely used as growth promoters in the poultry industry; however, the resulting antibiotic resistance threatens public health. A plant-derived growth promoter, Macleaya cordata extract (MCE), with effective ingredients of benzylisoquinoline alkaloids, is a potential alternative to antibiotic growth promoters. Altered intestinal microbiota play important roles in growth promotion, but the underlying mechanism remains unknown. RESULTS: We generated 1.64 terabases of metagenomic data from 495 chicken intestinal digesta samples and constructed a comprehensive chicken gut microbial gene catalog (9.04 million genes), which is also the first gene catalog of an animal's gut microbiome that covers all intestinal compartments. Then, we identified the distinctive characteristics and temporal changes in the foregut and hindgut microbiota. Next, we assessed the impact of MCE on chickens and gut microbiota. Chickens fed with MCE had improved growth performance, and major microbial changes were confined to the foregut, with the predominant role of Lactobacillus being enhanced, and the amino acids, vitamins, and secondary bile acids biosynthesis pathways being upregulated, but lacked the accumulation of antibiotic-resistance genes. In comparison, treatment with chlortetracycline similarly enriched some biosynthesis pathways of nutrients in the foregut microbiota, but elicited an increase in antibiotic-producing bacteria and antibiotic-resistance genes. CONCLUSION: The reference gene catalog of the chicken gut microbiome is an important supplement to animal gut metagenomes. Metagenomic analysis provides insights into the growth-promoting mechanism of MCE, and underscored the importance of utilizing safe and effective growth promoters.201830482240
9657110.9980Machine 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
8410120.9980Unveiling 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
2541130.9980Increased antibiotic resistance in preterm neonates under early antibiotic use. The standard use of antibiotics in newborns to empirically treat early-onset sepsis can adversely affect the neonatal gut microbiome, with potential long-term health impacts. Research into the escalating issue of antimicrobial resistance in preterm infants and antibiotic practices in neonatal intensive care units is limited. A deeper understanding of the effects of early antibiotic intervention on antibiotic resistance in preterm infants is crucial. This retrospective study employed metagenomic sequencing to evaluate antibiotic resistance genes (ARGs) in the meconium and subsequent stool samples of preterm infants enrolled in the Routine Early Antibiotic Use in Symptomatic Preterm Neonates study. Microbial metagenomics was conducted using a subset of fecal samples from 30 preterm infants for taxonomic profiling and ARG identification. All preterm infants exhibited ARGs, with 175 unique ARGs identified, predominantly associated with beta-lactam, tetracycline, and aminoglycoside resistance. Notably, 23% of ARGs was found in preterm infants without direct or intrapartum antibiotic exposure. Post-natal antibiotic exposure increases beta-lactam/tetracycline resistance while altering mechanisms that aid bacteria in withstanding antibiotic pressure. Microbial profiling revealed 774 bacterial species, with antibiotic-naive infants showing higher alpha diversity (P = 0.005) in their microbiota and resistome compared with treated infants, suggesting a more complex ecosystem. High ARG prevalence in preterm infants was observed irrespective of direct antibiotic exposure and intensifies with age. Prolonged membrane ruptures and maternal antibiotic use during gestation and delivery are linked to alterations in the preterm infant resistome and microbiome, which are pivotal in shaping the ARG profiles in the neonatal gut.This study is registered with ClinicalTrials.gov as NCT02784821. IMPORTANCE: A high burden of antibiotic resistance in preterm infants poses significant challenges to neonatal health. The presence of antibiotic resistance genes, along with alterations in signaling, energy production, and metabolic mechanisms, complicates treatment strategies for preterm infants, heightening the risk of ineffective therapy and exacerbating outcomes for these vulnerable neonates. Despite not receiving direct antibiotic treatment, preterm infants exhibit a concerning prevalence of antibiotic-resistant bacteria. This underscores the complex interplay of broader influences, including maternal antibiotic exposure during and beyond pregnancy and gestational complications like prolonged membrane ruptures. Urgent action, including cautious antibiotic practices and enhanced antenatal care, is imperative to protect neonatal health and counter the escalating threat of antimicrobial resistance in this vulnerable population.202439373498
7704140.9980Temporal development and potential interactions between the gut microbiome and resistome in early childhood. Antimicrobial resistance-associated infections have become a major threat to global health. The gut microbiome serves as a major reservoir of bacteria with antibiotic resistance genes; whereas, the temporal development of gut resistome during early childhood and the factors influencing it remain unclear. Moreover, the potential interactions between gut microbiome and resistome still need to be further explored. In this study, we found that antibiotic treatment led to destabilization of the gut microbiome and resistome structural communities, exhibiting a greater impact on the resistome than on the microbiome. The composition of the gut resistome at various developmental stages was influenced by the abundance and richness of different core microbes. First exposure to antibiotics led to a dramatic increase in the number of opportunistic pathogens carrying multidrug efflux pump encoding genes. Multiple factors could influence the gut microbiome and resistome formation. The data may provide new insights into early-life research.IMPORTANCEIn recent years, the irrational or inappropriate use of antibiotics, an important life-saving medical intervention, has led to the emergence and increase of drug-resistant and even multidrug-resistant bacteria. It remains unclear how antibiotic exposure affects various developmental stages of early childhood and how gut core microbes under antibiotic exposure affect the structural composition of the gut resistome. In this study, we focused on early antibiotic exposure and analyzed these questions in detail using samples from infants at various developmental stages. The significance of our research is to elucidate the impact of early antibiotic exposure on the dynamic patterns of the gut resistome in children and to provide new insights for early-life studies.202438193687
9457150.9980Exploring the role of gut microbiota in antibiotic resistance and prevention. BACKGROUND/INTRODUCTION: Antimicrobial resistance (AMR) and the evolution of multiple drug-resistant (MDR) bacteria is of grave public health concern. To combat the pandemic of AMR, it is necessary to focus on novel alternatives for drug development. Within the host, the interaction of the pathogen with the microbiome plays a pivotal role in determining the outcome of pathogenesis. Therefore, microbiome-pathogen interaction is one of the potential targets to be explored for novel antimicrobials. MAIN BODY: This review focuses on how the gut microbiome has evolved as a significant component of the resistome as a source of antibiotic resistance genes (ARGs). Antibiotics alter the composition of the native microbiota of the host by favouring resistant bacteria that can manifest as opportunistic infections. Furthermore, gut dysbiosis has also been linked to low-dosage antibiotic ingestion or subtherapeutic antibiotic treatment (STAT) from food and the environment. DISCUSSION: Colonization by MDR bacteria is potentially acquired and maintained in the gut microbiota. Therefore, it is pivotal to understand microbial diversity and its role in adapting pathogens to AMR. Implementing several strategies to prevent or treat dysbiosis is necessary, including faecal microbiota transplantation, probiotics and prebiotics, phage therapy, drug delivery models, and antimicrobial stewardship regulation.202540096354
9360160.9980Invertible promoters mediate bacterial phase variation, antibiotic resistance, and host adaptation in the gut. Phase variation, the reversible alternation between genetic states, enables infection by pathogens and colonization by commensals. However, the diversity of phase variation remains underexplored. We developed the PhaseFinder algorithm to quantify DNA inversion-mediated phase variation. A systematic search of 54,875 bacterial genomes identified 4686 intergenic invertible DNA regions (invertons), revealing an enrichment in host-associated bacteria. Invertons containing promoters often regulate extracellular products, underscoring the importance of surface diversity for gut colonization. We found invertons containing promoters regulating antibiotic resistance genes that shift to the ON orientation after antibiotic treatment in human metagenomic data and in vitro, thereby mitigating the cost of antibiotic resistance. We observed that the orientations of some invertons diverge after fecal microbiota transplant, potentially as a result of individual-specific selective forces.201930630933
4624170.9980Deciphering the distance to antibiotic resistance for the pneumococcus using genome sequencing data. Advances in genome sequencing technologies and genome-wide association studies (GWAS) have provided unprecedented insights into the molecular basis of microbial phenotypes and enabled the identification of the underlying genetic variants in real populations. However, utilization of genome sequencing in clinical phenotyping of bacteria is challenging due to the lack of reliable and accurate approaches. Here, we report a method for predicting microbial resistance patterns using genome sequencing data. We analyzed whole genome sequences of 1,680 Streptococcus pneumoniae isolates from four independent populations using GWAS and identified probable hotspots of genetic variation which correlate with phenotypes of resistance to essential classes of antibiotics. With the premise that accumulation of putative resistance-conferring SNPs, potentially in combination with specific resistance genes, precedes full resistance, we retrogressively surveyed the hotspot loci and quantified the number of SNPs and/or genes, which if accumulated would confer full resistance to an otherwise susceptible strain. We name this approach the 'distance to resistance'. It can be used to identify the creep towards complete antibiotics resistance in bacteria using genome sequencing. This approach serves as a basis for the development of future sequencing-based methods for predicting resistance profiles of bacterial strains in hospital microbiology and public health settings.201728205635
7696180.9980Noise reduction strategies in metagenomic chromosome confirmation capture to link antibiotic resistance genes to microbial hosts. The gut microbiota is a reservoir for antimicrobial resistance genes (ARGs). With current sequencing methods, it is difficult to assign ARGs to their microbial hosts, particularly if these ARGs are located on plasmids. Metagenomic chromosome conformation capture approaches (meta3C and Hi-C) have recently been developed to link bacterial genes to phylogenetic markers, thus potentially allowing the assignment of ARGs to their hosts on a microbiome-wide scale. Here, we generated a meta3C dataset of a human stool sample and used previously published meta3C and Hi-C datasets to investigate bacterial hosts of ARGs in the human gut microbiome. Sequence reads mapping to repetitive elements were found to cause problematic noise in, and may importantly skew interpretation of, meta3C and Hi-C data. We provide a strategy to improve the signal-to-noise ratio by discarding reads that map to insertion sequence elements and to the end of contigs. We also show the importance of using spike-in controls to quantify whether the cross-linking step in meta3C and Hi-C protocols has been successful. After filtering to remove artefactual links, 87 ARGs were assigned to their bacterial hosts across all datasets, including 27 ARGs in the meta3C dataset we generated. We show that commensal gut bacteria are an important reservoir for ARGs, with genes coding for aminoglycoside and tetracycline resistance being widespread in anaerobic commensals of the human gut.202337272920
9606190.9979Rapid identification of key antibiotic resistance genes in E. coli using high-resolution genome-scale CRISPRi screening. Bacteria possess a vast repertoire of genes to adapt to environmental challenges. Understanding the gene fitness landscape under antibiotic stress is crucial for elucidating bacterial resistance mechanisms and antibiotic action. To explore this, we conducted a genome-scale CRISPRi screen using a high-density sgRNA library in Escherichia coli exposed to various antibiotics. This screen identified essential genes under antibiotic-induced stress and offered insights into the molecular mechanisms underlying bacterial responses. We uncovered previously unrecognized genes involved in antibiotic resistance, including essential membrane proteins. The screen also underscored the importance of transcriptional modulation of essential genes in antibiotic tolerance. Our findings emphasize the utility of genome-wide CRISPRi screening in mapping the genetic landscape of antibiotic resistance. This study provides a valuable resource for identifying potential targets for antibiotics or antimicrobial strategies. Moreover, it offers a framework for exploring transcriptional regulatory networks and resistance mechanisms in E. coli and other bacterial pathogens.202540352728