# | Rank | Similarity | Title + Abs. | Year | PMID |
|---|---|---|---|---|---|
| 0 | 1 | 2 | 3 | 4 | 5 |
| 9555 | 0 | 0.9971 | Bacteria.guru: Comparative Transcriptomics and Co-Expression Database for Bacterial Pathogens. While bacteria can be beneficial to our health, their deadly pathogenic potential has been an ever-present concern exacerbated by the emergence of drug-resistant strains. As such, there is a pressing urgency for an enhanced understanding of their gene function and regulation, which could mediate the development of novel antimicrobials. Transcriptomic analyses have been established as insightful and indispensable to the functional characterization of genes and identification of new biological pathways, but in the context of bacterial studies, they remain limited to species-specific datasets. To address this, we integrated the genomic and transcriptomic data of the 17 most notorious and researched bacterial pathogens, creating bacteria.guru, an interactive database that can identify, visualize, and compare gene expression profiles, coexpression networks, functionally enriched clusters, and gene families across species. Through illustrating antibiotic resistance mechanisms in P. aeruginosa, we demonstrate that bacteria.guru could potentially aid in discovering multi-faceted antibiotic targets and, overall, facilitate future bacterial research. AVAILABILITY: The database and coexpression networks are freely available from https://bacteria.guru/. Sample annotations can be found in the supplemental data. | 2022 | 34838806 |
| 6668 | 1 | 0.9969 | Complexities in understanding antimicrobial resistance across domesticated animal, human, and environmental systems. Antimicrobial resistance (AMR) is a significant threat to both human and animal health. The spread of AMR bacteria and genes across systems can occur through a myriad of pathways, both related and unrelated to agriculture, including via wastewater, soils, manure applications, direct exchange between humans and animals, and food exposure. Tracing origins and drivers of AMR bacteria and genes is challenging due to the array of contexts and the complexity of interactions overlapping health practice, microbiology, genetics, applied science and engineering, as well as social and human factors. Critically assessing the diverse and sometimes contradictory AMR literature is a valuable step in identifying tractable mitigation options to stem AMR spread. In this article we review research on the nonfoodborne spread of AMR, with a focus on domesticated animals and the environment and possible exposures to humans. Attention is especially placed on delineating possible sources and causes of AMR bacterial phenotypes, including underpinning the genetics important to human and animal health. | 2019 | 30924539 |
| 8409 | 2 | 0.9968 | Comparative 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. | 2025 | 40547794 |
| 9674 | 3 | 0.9968 | Global epistasis in plasmid-mediated antimicrobial resistance. Antimicrobial resistance (AMR) in bacteria is a major public health threat and conjugative plasmids play a key role in the dissemination of AMR genes among bacterial pathogens. Interestingly, the association between AMR plasmids and pathogens is not random and certain associations spread successfully at a global scale. The burst of genome sequencing has increased the resolution of epidemiological programs, broadening our understanding of plasmid distribution in bacterial populations. Despite the immense value of these studies, our ability to predict future plasmid-bacteria associations remains limited. Numerous empirical studies have recently reported systematic patterns in genetic interactions that enable predictability, in a phenomenon known as global epistasis. In this perspective, we argue that global epistasis patterns hold the potential to predict interactions between plasmids and bacterial genomes, thereby facilitating the prediction of future successful associations. To assess the validity of this idea, we use previously published data to identify global epistasis patterns in clinically relevant plasmid-bacteria associations. Furthermore, using simple mechanistic models of antibiotic resistance, we illustrate how global epistasis patterns may allow us to generate new hypotheses on the mechanisms associated with successful plasmid-bacteria associations. Collectively, we aim at illustrating the relevance of exploring global epistasis in the context of plasmid biology. | 2024 | 38409539 |
| 5101 | 4 | 0.9968 | Identification 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. | 2025 | 40671232 |
| 9667 | 5 | 0.9968 | Novel resistance functions uncovered using functional metagenomic investigations of resistance reservoirs. Rates of infection with antibiotic-resistant bacteria have increased precipitously over the past several decades, with far-reaching healthcare and societal costs. Recent evidence has established a link between antibiotic resistance genes in human pathogens and those found in non-pathogenic, commensal, and environmental organisms, prompting deeper investigation of natural and human-associated reservoirs of antibiotic resistance. Functional metagenomic selections, in which shotgun-cloned DNA fragments are selected for their ability to confer survival to an indicator host, have been increasingly applied to the characterization of many antibiotic resistance reservoirs. These experiments have demonstrated that antibiotic resistance genes are highly diverse and widely distributed, many times bearing little to no similarity to known sequences. Through unbiased selections for survival to antibiotic exposure, functional metagenomics can improve annotations by reducing the discovery of false-positive resistance and by allowing for the identification of previously unrecognizable resistance genes. In this review, we summarize the novel resistance functions uncovered using functional metagenomic investigations of natural and human-impacted resistance reservoirs. Examples of novel antibiotic resistance genes include those highly divergent from known sequences, those for which sequence is entirely unable to predict resistance function, bifunctional resistance genes, and those with unconventional, atypical resistance mechanisms. Overcoming antibiotic resistance in the clinic will require a better understanding of existing resistance reservoirs and the dissemination networks that govern horizontal gene exchange, informing best practices to limit the spread of resistance-conferring genes to human pathogens. | 2013 | 23760651 |
| 9483 | 6 | 0.9968 | Ecological and evolutionary mechanisms driving within-patient emergence of antimicrobial resistance. The ecological and evolutionary mechanisms of antimicrobial resistance (AMR) emergence within patients and how these vary across bacterial infections are poorly understood. Increasingly widespread use of pathogen genome sequencing in the clinic enables a deeper understanding of these processes. In this Review, we explore the clinical evidence to support four major mechanisms of within-patient AMR emergence in bacteria: spontaneous resistance mutations; in situ horizontal gene transfer of resistance genes; selection of pre-existing resistance; and immigration of resistant lineages. Within-patient AMR emergence occurs across a wide range of host niches and bacterial species, but the importance of each mechanism varies between bacterial species and infection sites within the body. We identify potential drivers of such differences and discuss how ecological and evolutionary analysis could be embedded within clinical trials of antimicrobials, which are powerful but underused tools for understanding why these mechanisms vary between pathogens, infections and individuals. Ultimately, improving understanding of how host niche, bacterial species and antibiotic mode of action combine to govern the ecological and evolutionary mechanism of AMR emergence in patients will enable more predictive and personalized diagnosis and antimicrobial therapies. | 2024 | 38689039 |
| 3785 | 7 | 0.9968 | A network approach to decipher the dynamics of Lysobacteraceae plasmid gene sharing. Plasmids provide an efficient vehicle for gene sharing among bacterial populations, playing a key role in bacterial evolution. Network approaches are particularly suitable to represent multipartite relationships and are useful tools to characterize plasmid-mediated gene sharing events. The bacterial family Lysobacteraceae includes plant commensal, plant pathogenic and opportunistic human pathogens for which plasmid-mediated adaptation has been reported. We searched for homologues of plasmid gene sequences from this family in the entire diversity of available bacterial genome sequences and built a network of plasmid gene sharing from the results. While plasmid genes are openly shared between the bacteria of the family Lysobacteraceae, taxonomy strongly defined the boundaries of these exchanges, which only barely reached other families. Most inferred plasmid gene sharing events involved a few genes only, and evidence of full plasmid transfers were restricted to taxonomically closely related taxa. We detected multiple plasmid-chromosome gene transfers, including the known sharing of a heavy metal resistance transposon. In the network, bacterial lifestyles shaped substructures of isolates colonizing specific ecological niches and harbouring specific types of resistance genes. Genes associated with pathogenicity or antibiotic and metal resistance were among those that most importantly structured the network, highlighting the imprints of human-mediated selective pressure on pathogenic populations. A massive sequencing effort on environmental Lysobacteraceae is therefore required to refine our understanding of how this reservoir fuels the emergence and the spread of genes among this family and its potential impact on plant, animal and human health. | 2023 | 35593155 |
| 8410 | 8 | 0.9968 | Unveiling 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. | 2025 | 40152610 |
| 9375 | 9 | 0.9968 | Multistep diversification in spatiotemporal bacterial-phage coevolution. The evolutionary arms race between phages and bacteria, where bacteria evolve resistance to phages and phages retaliate with resistance-countering mutations, is a major driving force of molecular innovation and genetic diversification. Yet attempting to reproduce such ongoing retaliation dynamics in the lab has been challenging; laboratory coevolution experiments of phage and bacteria are typically performed in well-mixed environments and often lead to rapid stagnation with little genetic variability. Here, co-culturing motile E. coli with the lytic bacteriophage T7 on swimming plates, we observe complex spatiotemporal dynamics with multiple genetically diversifying adaptive cycles. Systematically quantifying over 10,000 resistance-infectivity phenotypes between evolved bacteria and phage isolates, we observe diversification into multiple coexisting ecotypes showing a complex interaction network with both host-range expansion and host-switch tradeoffs. Whole-genome sequencing of these evolved phage and bacterial isolates revealed a rich set of adaptive mutations in multiple genetic pathways including in genes not previously linked with phage-bacteria interactions. Synthetically reconstructing these new mutations, we discover phage-general and phage-specific resistance phenotypes as well as a strong synergy with the more classically known phage-resistance mutations. These results highlight the importance of spatial structure and migration for driving phage-bacteria coevolution, providing a concrete system for revealing new molecular mechanisms across diverse phage-bacterial systems. | 2022 | 36577749 |
| 9671 | 10 | 0.9968 | Genome-scale genetic manipulation methods for exploring bacterial molecular biology. Bacteria are diverse and abundant, playing key roles in human health and disease, the environment, and biotechnology. Despite progress in genome sequencing and bioengineering, much remains unknown about the functional organization of prokaryotes. For instance, roughly a third of the protein-coding genes of the best-studied model bacterium, Escherichia coli, currently lack experimental annotations. Systems-level experimental approaches for investigating the functional associations of bacterial genes and genetic structures are essential for defining the fundamental molecular biology of microbes, preventing the spread of antibacterial resistance in the clinic, and driving the development of future biotechnological applications. This review highlights recently introduced large-scale genetic manipulation and screening procedures for the systematic exploration of bacterial gene functions, molecular relationships, and the global organization of bacteria at the gene, pathway, and genome levels. | 2012 | 22517266 |
| 7674 | 11 | 0.9968 | Insights into gut microbiomes in stem cell transplantation by comprehensive shotgun long-read sequencing. The gut microbiome is a diverse ecosystem, dominated by bacteria; however, fungi, phages/viruses, archaea, and protozoa are also important members of the gut microbiota. Exploration of taxonomic compositions beyond bacteria as well as an understanding of the interaction between the bacteriome with the other members is limited using 16S rDNA sequencing. Here, we developed a pipeline enabling the simultaneous interrogation of the gut microbiome (bacteriome, mycobiome, archaeome, eukaryome, DNA virome) and of antibiotic resistance genes based on optimized long-read shotgun metagenomics protocols and custom bioinformatics. Using our pipeline we investigated the longitudinal composition of the gut microbiome in an exploratory clinical study in patients undergoing allogeneic hematopoietic stem cell transplantation (alloHSCT; n = 31). Pre-transplantation microbiomes exhibited a 3-cluster structure, characterized by Bacteroides spp. /Phocaeicola spp., mixed composition and Enterococcus abundances. We revealed substantial inter-individual and temporal variabilities of microbial domain compositions, human DNA, and antibiotic resistance genes during the course of alloHSCT. Interestingly, viruses and fungi accounted for substantial proportions of microbiome content in individual samples. In the course of HSCT, bacterial strains were stable or newly acquired. Our results demonstrate the disruptive potential of alloHSCTon the gut microbiome and pave the way for future comprehensive microbiome studies based on long-read metagenomics. | 2024 | 38374282 |
| 9606 | 12 | 0.9967 | Rapid 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. | 2025 | 40352728 |
| 6656 | 13 | 0.9967 | Understanding the Evolution and Transmission Dynamics of Antibiotic Resistance Genes: A Comprehensive Review. Antibiotic resistance poses a formidable challenge to global public health, necessitating comprehensive understanding and strategic interventions. This review explores the evolution and transmission dynamics of antibiotic resistance genes, with a focus on Bangladesh. The indiscriminate use of antibiotics, compounded by substandard formulations and clinical misdiagnosis, fuels the emergence and spread of resistance in the country. Studies reveal high resistance rates among common pathogens, emphasizing the urgent need for targeted interventions and rational antibiotic use. Molecular assessments uncover a diverse array of antibiotic resistance genes in environmental reservoirs, highlighting the complex interplay between human activities and resistance dissemination. Horizontal gene transfer mechanisms, particularly plasmid-mediated conjugation, facilitate the exchange of resistance determinants among bacterial populations, driving the evolution of multidrug-resistant strains. The review discusses clinical implications, emphasizing the interconnectedness of environmental and clinical settings in resistance dynamics. Furthermore, bioinformatic and experimental evidence elucidates novel mechanisms of resistance gene transfer, underscoring the dynamic nature of resistance evolution. In conclusion, combating antibiotic resistance requires a multifaceted approach, integrating surveillance, stewardship, and innovative research to preserve the efficacy of antimicrobial agents and safeguard public health. | 2024 | 39113256 |
| 9079 | 14 | 0.9967 | Review, Evaluation, and Directions for Gene-Targeted Assembly for Ecological Analyses of Metagenomes. Shotgun metagenomics has greatly advanced our understanding of microbial communities over the last decade. Metagenomic analyses often include assembly and genome binning, computationally daunting tasks especially for big data from complex environments such as soil and sediments. In many studies, however, only a subset of genes and pathways involved in specific functions are of interest; thus, it is not necessary to attempt global assembly. In addition, methods that target genes can be computationally more efficient and produce more accurate assembly by leveraging rich databases, especially for those genes that are of broad interest such as those involved in biogeochemical cycles, biodegradation, and antibiotic resistance or used as phylogenetic markers. Here, we review six gene-targeted assemblers with unique algorithms for extracting and/or assembling targeted genes: Xander, MegaGTA, SAT-Assembler, HMM-GRASPx, GenSeed-HMM, and MEGAN. We tested these tools using two datasets with known genomes, a synthetic community of artificial reads derived from the genomes of 17 bacteria, shotgun sequence data from a mock community with 48 bacteria and 16 archaea genomes, and a large soil shotgun metagenomic dataset. We compared assemblies of a universal single copy gene (rplB) and two N cycle genes (nifH and nirK). We measured their computational efficiency, sensitivity, specificity, and chimera rate and found Xander and MegaGTA, which both use a probabilistic graph structure to model the genes, have the best overall performance with all three datasets, although MEGAN, a reference matching assembler, had better sensitivity with synthetic and mock community members chosen from its reference collection. Also, Xander and MegaGTA are the only tools that include post-assembly scripts tuned for common molecular ecology and diversity analyses. Additionally, we provide a mathematical model for estimating the probability of assembling targeted genes in a metagenome for estimating required sequencing depth. | 2019 | 31749830 |
| 6508 | 15 | 0.9967 | Synergizing Ecotoxicology and Microbiome Data Is Key for Developing Global Indicators of Environmental Antimicrobial Resistance. The One Health concept recognises the interconnectedness of humans, plants, animals and the environment. Recent research strongly supports the idea that the environment serves as a significant reservoir for antimicrobial resistance (AMR). However, the complexity of natural environments makes efforts at AMR public health risk assessment difficult. We lack sufficient data on key ecological parameters that influence AMR, as well as the primary proxies necessary for evaluating risks to human health. Developing environmental AMR 'early warning systems' requires models with well-defined parameters. This is necessary to support the implementation of clear and targeted interventions. In this review, we provide a comprehensive overview of the current tools used globally for environmental AMR human health risk assessment and the underlying knowledge gaps. We highlight the urgent need for standardised, cost-effective risk assessment frameworks that are adaptable across different environments and regions to enhance comparability and reliability. These frameworks must also account for previously understudied AMR sources, such as horticulture, and emerging threats like climate change. In addition, integrating traditional ecotoxicology with modern 'omics' approaches will be essential for developing more comprehensive risk models and informing targeted AMR mitigation strategies. | 2024 | 39611949 |
| 9719 | 16 | 0.9967 | Dynamics of antibiotic resistance genes in plasmids and bacteriophages. This brief review explores the intricate interplay between bacteriophages and plasmids in the context of antibiotic resistance gene (ARG) dissemination. Originating from studies in the late 1950s, the review traces the evolution of knowledge regarding extrachromosomal factors facilitating horizontal gene transfer and adaptation in bacteria. Analyzing the gene repertoires of plasmids and bacteriophages, the study highlights their contributions to bacterial evolution and adaptation. While plasmids encode essential and accessory genes influencing host characteristics, bacteriophages carry auxiliary metabolic genes (AMGs) that augment host metabolism. The debate on phages carrying ARGs is explored through a critical evaluation of various studies, revealing contrasting findings from researchers. Additionally, the review addresses the interplay between prophages and plasmids, underlining their similarities and divergences. Based on the available literature evidence, we conclude that plasmids generally encode ARGs while bacteriophages typically do not contain ARGs. But extra-chromosomaly present prophages with plasmid characteristics can encode and disseminate ARGs. | 2025 | 38651513 |
| 4357 | 17 | 0.9967 | Comparative genomic analysis of 255 Oenococcus oeni isolates from China: unveiling strain diversity and genotype-phenotype associations of acid resistance. Oenococcus oeni, the only species of lactic acid bacteria capable of fully completing malolactic fermentation under challenging wine conditions, continues to intrigue researchers owing to its remarkable adaptability, particularly in combating acid stress. However, the mechanism underlying its superior adaptation to wine stresses still remains elusive due to the lack of viable genetic manipulation tools for this species. In this study, we conducted genomic sequencing and acid resistance phenotype analysis of 255 O. oeni isolates derived from diverse wine regions across China, aiming to elucidate their strain diversity and genotype-phenotype associations of acid resistance through comparative genomics. A significant correlation between phenotypes and evolutionary relationships was observed. Notably, phylogroup B predominantly consisted of acid-resistant isolates, primarily originating from Shandong and Shaanxi wine regions. Furthermore, we uncovered a noteworthy linkage between prophage genomic islands and acid resistance phenotype. Using genome-wide association studies, we identified key genes correlated with acid resistance, primarily involved in carbohydrates and amino acid metabolism processes. This study offers profound insights into the genetic diversity and genetic basis underlying adaptation mechanisms to acid stress in O. oeni.IMPORTANCEThis study provides valuable insights into the genetic basis of acid resistance in Oenococcus oeni, a key lactic acid bacterium in winemaking. By analyzing 255 isolates from diverse wine regions in China, we identified significant correlations between strain diversity, genomic islands, and acid resistance phenotypes. Our findings reveal that certain prophage-related genomic islands and specific genes are closely linked to acid resistance, offering a deeper understanding of how O. oeni adapts to acidic environments. These discoveries not only advance our knowledge of microbial stress responses but also pave the way for selecting and engineering acid-resistant strains, enhancing malolactic fermentation efficiency and wine quality. This research underscores the importance of genomics in improving winemaking practices and addressing challenges posed by high-acidity wines. | 2025 | 40261018 |
| 6669 | 18 | 0.9967 | ANTIBIOTIC RESISTANT BACTERIA IN WILDLIFE: PERSPECTIVES ON TRENDS, ACQUISITION AND DISSEMINATION, DATA GAPS, AND FUTURE DIRECTIONS. The proliferation of antibiotic-resistant bacteria in the environment has potential negative economic and health consequences. Thus, previous investigations have targeted wild animals to understand the occurrence of antibiotic resistance in diverse environmental sources. In this critical review and synthesis, we summarized important concepts learned through the sampling of wildlife for antibiotic-resistant indicator bacteria. These concepts are helpful for understanding dissemination of resistance through environmental pathways and helping to guide future research efforts. Our review begins by briefly introducing antibiotic resistance as it pertains to bacteria harbored in environmental sources such as wild animals. Next, we differentiate wildlife from other animals in the context of how diverse taxa provide different information on antibiotic resistance in the environment. In the third section of our review, we identify representative research and seminal works that illustrate important associations between the occurrence of antibiotic-resistant bacteria in wildlife and anthropogenic inputs into the environment. For example, we highlight numerous investigations that support the premise that anthropogenic inputs into the environment drive the occurrence of antibiotic resistance in bacteria harbored by free-ranging wildlife. Additionally, we summarize previous research demonstrating foraging as a mechanism by which wildlife may be exposed to anthropogenic antibiotic resistance contamination in the environment. In the fourth section of our review, we summarize molecular evidence for the acquisition and dissemination of resistance among bacteria harbored by wildlife. In the fifth section, we identify what we believe to be important data gaps and potential future directions that other researchers may find useful toward the development of efficient, informative, and impactful investigations of antibiotic-resistant bacteria in wildlife. Finally, we conclude our review by highlighting the need to move from surveys that simply identify antibiotic-resistant bacteria in wildlife toward hypothesis-driven investigations that: 1) identify point sources of antibiotic resistance; 2) provide information on risk to human and animal health; 3) identify interventions that may interrupt environmentally mediated pathways of antibiotic resistance acquisition and transmission; and 4) evaluate whether management practices are leading to desirable outcomes. | 2020 | 31567035 |
| 9729 | 19 | 0.9967 | Omics 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. | 2024 | 38709343 |