Analysis of Identification Method for Bacterial Species and Antibiotic Resistance Genes Using Optical Data From DNA Oligomers. - Related Documents




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974501.0000Analysis of Identification Method for Bacterial Species and Antibiotic Resistance Genes Using Optical Data From DNA Oligomers. Bacterial antibiotic resistance is becoming a significant health threat, and rapid identification of antibiotic-resistant bacteria is essential to save lives and reduce the spread of antibiotic resistance. This paper analyzes the ability of machine learning algorithms (MLAs) to process data from a novel spectroscopic diagnostic device to identify antibiotic-resistant genes and bacterial species by comparison to available bacterial DNA sequences. Simulation results show that the algorithms attain from 92% accuracy (for genes) up to 99% accuracy (for species). This novel approach identifies genes and species by optically reading the percentage of A, C, G, T bases in 1000s of short 10-base DNA oligomers instead of relying on conventional DNA sequencing in which the sequence of bases in long oligomers provides genetic information. The identification algorithms are robust in the presence of simulated random genetic mutations and simulated random experimental errors. Thus, these algorithms can be used to identify bacterial species, to reveal antibiotic resistance genes, and to perform other genomic analyses. Some MLAs evaluated here are shown to be better than others at accurate gene identification and avoidance of false negative identification of antibiotic resistance.202032153541
974410.9997PARGT: a software tool for predicting antimicrobial resistance in bacteria. With the ever-increasing availability of whole-genome sequences, machine-learning approaches can be used as an alternative to traditional alignment-based methods for identifying new antimicrobial-resistance genes. Such approaches are especially helpful when pathogens cannot be cultured in the lab. In previous work, we proposed a game-theory-based feature evaluation algorithm. When using the protein characteristics identified by this algorithm, called 'features' in machine learning, our model accurately identified antimicrobial resistance (AMR) genes in Gram-negative bacteria. Here we extend our study to Gram-positive bacteria showing that coupling game-theory-identified features with machine learning achieved classification accuracies between 87% and 90% for genes encoding resistance to the antibiotics bacitracin and vancomycin. Importantly, we present a standalone software tool that implements the game-theory algorithm and machine-learning model used in these studies.202032620856
511120.9997Antimicrobial Resistance Prediction for Gram-Negative Bacteria via Game Theory-Based Feature Evaluation. The increasing prevalence of antimicrobial-resistant bacteria drives the need for advanced methods to identify antimicrobial-resistance (AMR) genes in bacterial pathogens. With the availability of whole genome sequences, best-hit methods can be used to identify AMR genes by differentiating unknown sequences with known AMR sequences in existing online repositories. Nevertheless, these methods may not perform well when identifying resistance genes with sequences having low sequence identity with known sequences. We present a machine learning approach that uses protein sequences, with sequence identity ranging between 10% and 90%, as an alternative to conventional DNA sequence alignment-based approaches to identify putative AMR genes in Gram-negative bacteria. By using game theory to choose which protein characteristics to use in our machine learning model, we can predict AMR protein sequences for Gram-negative bacteria with an accuracy ranging from 93% to 99%. In order to obtain similar classification results, identity thresholds as low as 53% were required when using BLASTp.201931597945
382430.9997Screening for novel antibiotic resistance genes. Knowledge of novel antibiotic resistance genes aids in the understanding of how antibiotics function and how bacteria fight them. This knowledge also allows future generations of an antibiotic or antibiotic group to be altered to allow the greatest efficacy. The method described here is very simple in theory. The bacterial strains are screened for antibiotic resistance. Cultures of the strain are grown, and DNA is extracted. A partial digest of the extraction is cloned into Escherichia coli, and the transformants are plated on selective media. Any colony that grows will possess the antibiotic resistance gene and can be further examined. In actual practice, however, this technique can be complicated. The detailed protocol will need to be optimized for each bacterial strain, vector, and cell line chosen.201020830570
511240.9997Genome-Based Prediction of Bacterial Antibiotic Resistance. Clinical microbiology has long relied on growing bacteria in culture to determine antimicrobial susceptibility profiles, but the use of whole-genome sequencing for antibiotic susceptibility testing (WGS-AST) is now a powerful alternative. This review discusses the technologies that made this possible and presents results from recent studies to predict resistance based on genome sequences. We examine differences between calling antibiotic resistance profiles by the simple presence or absence of previously known genes and single-nucleotide polymorphisms (SNPs) against approaches that deploy machine learning and statistical models. Often, the limitations to genome-based prediction arise from limitations of accuracy of culture-based AST in addition to an incomplete knowledge of the genetic basis of resistance. However, we need to maintain phenotypic testing even as genome-based prediction becomes more widespread to ensure that the results do not diverge over time. We argue that standardization of WGS-AST by challenge with consistently phenotyped strain sets of defined genetic diversity is necessary to compare the efficacy of methods of prediction of antibiotic resistance based on genome sequences.201930381421
507750.9997Development of a new integrated diagnostic test for identification and characterization of pathogens. Animal diseases directly cause multi-million dollar losses world-wide. Therefore a rapid, highly specific, cost-effective diagnostic test for detecting a large set of bacterial virulence and antimicrobial resistance genes simultaneously is necessary. Hence, our group, the BCBG (Bacterial Chips Bacterial Genes) group, proposes developing a powerful molecular tool (DNA microarray) to detect a broad range of infectious agents, their endogenous main virulence factors and antibiotic resistance genes simultaneously. Effectively, a 70-mer oligonucleotide microarray capable of detecting the presence or absence of 169 Escherichia coli virulence genes or virulence marker genes as well as their variants, in addition to 30 principal antimicrobial resistance genes previously characterized in E. coli strains was developed by our group. This microarray was validated with a large collection of well characterized pathogenic and reference E. coli strains. Moreover, we are developing a new powerful clinical diagnostic microarray tool, to identify pathogenic bacteria of veterinary interest. The commercialization of this assay would allow same day diagnosis of infectious agents and their antibiotic resistance resulting in early treatment. In addition, this technology is also applicable to microbial quality control of food and water.200617058497
507560.9997Fast and Economic Microarray-Based Detection of Species-, Resistance-, and Virulence-Associated Genes in Clinical Strains of Vancomycin-Resistant Enterococci (VRE). Today, there is a continuous worldwide battle against antimicrobial resistance (AMR) and that includes vancomycin-resistant enterococci (VRE). Methods that can adequately and quickly detect transmission chains in outbreaks are needed to trace and manage this problem fast and cost-effectively. In this study, DNA-microarray-based technology was developed for this purpose. It commenced with the bioinformatic design of specific oligonucleotide sequences to obtain amplification primers and hybridization probes. Microarrays were manufactured using these synthesized oligonucleotides. A highly parallel and stringent labeling and hybridization protocol was developed and employed using isolated genomic DNA from previously sequenced (referenced) clinical VRE strains for optimal sensitivity and specificity. Microarray results showed the detection of virulence, resistance, and species-specific genes in the VRE strains. Theoretical predictions of the microarray results were also derived from the sequences of the same VRE strain and were compared to array results while optimizing protocols until the microarray result and theoretical predictions were a match. The study concludes that DNA microarray technology can be used to quickly, accurately, and economically detect specifically and massively parallel target genes in enterococci.202439409516
507970.9997Development of a Rapid, Culture-Free, Universal Microbial Identification System Using Internal Transcribed Spacer Targeting Primers. The indiscriminate administration of broad-spectrum antibiotics is a primary contributor to the increasing prevalence of antibiotic resistance. Unfortunately, culture, the gold standard for bacterial identification is a time intensive process. Due to this extended diagnostic period, broad-spectrum antibiotics are generally prescribed to prevent poor outcomes. To overcome the deficits of culture-based methods, we have developed a rapid universal bacterial identification system. The platform uses a unique universal polymerase chain reaction primer set that targets the internal transcribed spacer regions between conserved bacterial genes, creating a distinguishable amplicon signature for every bacterial species. Bioinformatic simulation demonstrates that nearly every bacteria in a set of 45 commonly isolated pathogenic species can be uniquely identified using this approach. We experimentally confirmed these predictions on a representative set of pathogenic bacterial species. We further showed that the system can determine the corresponding concentration of each pathogen. Finally, we validated performance in clinical urinary tract infection samples.202539503259
489780.9996Rapid diagnosis of tuberculosis. Detection of drug resistance mechanisms. Tuberculosis is still a serious public health problem, with 10.8 million new cases and 1.8 million deaths worldwide in 2015. The diversity among members of the Mycobacterium tuberculosis complex, the causal agent of tuberculosis, is conducive to the design of different methods for rapid diagnosis. Mutations in the genes involved in resistance mechanisms enable the bacteria to elude the treatment. We have reviewed the methods for the rapid diagnosis of M. tuberculosis complex and the detection of susceptibility to drugs, both of which are necessary to prevent the onset of new resistance and to establish early, appropriate treatment.201728318570
940590.9996Functional Metagenomic Screening for Antimicrobial Resistance in the Oral Microbiome. A large proportion of bacteria, from a multitude of environments, are not yet able to be grown in the laboratory, and therefore microbiological and molecular biological investigations of these bacteria are challenging. A way to circumvent this challenge is to analyze the metagenome, the entire collection of DNA molecules that can be isolated from a particular environment or sample. This collection of DNA molecules can be sequenced and assembled to determine what is present and infer functional potential, or used as a PCR template to detect known target DNA and potentially unknown regions of DNA nearby those targets; however assigning functions to new or conserved hypothetical, functionally cryptic, genes is difficult. Functional metagenomics allows researchers to determine which genes are responsible for selectable phenotypes, such as resistance to antimicrobials and metabolic capabilities, without the prerequisite needs to grow the bacteria containing those genes or to already know which genes are of interest. It is estimated that a third of the resident species of the human oral cavity is not yet cultivable and, together with the ease of sample acquisition, makes this metagenome particularly suited to functional metagenomic studies. Here we describe the methodology related to the collection of saliva samples, extraction of metagenomic DNA, construction of metagenomic libraries, as well as the description of functional assays that have previously led to the identification of new genes conferring antimicrobial resistance.202134410638
9566100.9996Computational resources in the management of antibiotic resistance: Speeding up drug discovery. This article reviews more than 50 computational resources developed in past two decades for forecasting of antibiotic resistance (AR)-associated mutations, genes and genomes. More than 30 databases have been developed for AR-associated information, but only a fraction of them are updated regularly. A large number of methods have been developed to find AR genes, mutations and genomes, with most of them based on similarity-search tools such as BLAST and HMMER. In addition, methods have been developed to predict the inhibition potential of antibiotics against a bacterial strain from the whole-genome data of bacteria. This review also discuss computational resources that can be used to manage the treatment of AR-associated diseases.202133892146
6310110.9996Use of the lambda Red recombinase system to produce recombinant prophages carrying antibiotic resistance genes. BACKGROUND: The Red recombinase system of bacteriophage lambda has been used to inactivate chromosomal genes in E. coli K-12 through homologous recombination using linear PCR products. The aim of this study was to induce mutations in the genome of some temperate Shiga toxin encoding bacteriophages. When phage genes are in the prophage state, they behave like chromosomal genes. This enables marker genes, such as antibiotic resistance genes, to be incorporated into the stx gene. Once the phages' lytic cycle is activated, recombinant Shiga toxin converting phages are produced. These phages can transfer the marker genes to the bacteria that they infect and convert. As the Red system's effectiveness decreased when used for our purposes, we had to introduce significant variations to the original method. These modifications included: confirming the stability of the target stx gene increasing the number of cells to be transformed and using a three-step PCR method to produce the amplimer containing the antibiotic resistance gene. RESULTS: Seven phages carrying two different antibiotic resistance genes were derived from phages that are directly involved in the pathogenesis of Shiga toxin-producing strains, using this modified protocol. CONCLUSION: This approach facilitates exploration of the transduction processes and is a valuable tool for studying phage-mediated horizontal gene transfer.200616984631
4624120.9996Deciphering 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
9313130.9996Towards an accurate identification of mosaic genes and partial horizontal gene transfers. Many bacteria and viruses adapt to varying environmental conditions through the acquisition of mosaic genes. A mosaic gene is composed of alternating sequence polymorphisms either belonging to the host original allele or derived from the integrated donor DNA. Often, the integrated sequence contains a selectable genetic marker (e.g. marker allowing for antibiotic resistance). An effective identification of mosaic genes and detection of corresponding partial horizontal gene transfers (HGTs) are among the most important challenges posed by evolutionary biology. We developed a method for detecting partial HGT events and related intragenic recombination giving rise to the formation of mosaic genes. A bootstrap procedure incorporated in our method is used to assess the support of each predicted partial gene transfer. The proposed method can be also applied to confirm or discard complete (i.e. traditional) horizontal gene transfers detected by any HGT inferring method. While working on a full-genome scale, the new method can be used to assess the level of mosaicism in the considered genomes as well as the rates of complete and partial HGT underlying their evolution.201121917854
9470140.9996Practical Method for Isolation of Phage Deletion Mutants. The growing concern about multi-drug resistant pathogenic bacteria has led to a renewed interest in the study of bacteriophages as antimicrobials and as therapeutic agents against infectious diseases (phage therapy). Phages to be used for this purpose have to be subjected to in-depth genomic characterization. It is essential to ascribe specific functions to phage genes, which will give information to unravel phage biology and to ensure the lack of undesirable genes, such as virulence and antibiotic resistance genes. Here, we describe a simple protocol for the selection of phage mutants carrying random deletions along the phage genome. Theoretically, any DNA region might be removed with the only requirement that the phage particle viability remains unaffected. This technique is based on the instability of phage particles in the presence of chelating compounds. A fraction of the phage population naturally lacking DNA segments will survive the treatment. Within the context of phages as antimicrobials, this protocol is useful to select lytic variants from temperate phages. In terms of phage efficiency, virulent phages are preferred over temperate ones to remove undesirable bacteria. This protocol has been used to obtain gene mutations that are involved in the lysogenic cycle of phages infecting Gram-positive bacteria (Staphylococcus and Lactobacillus).201831164553
4249150.9996Detection of essential genes in Streptococcus pneumoniae using bioinformatics and allelic replacement mutagenesis. Although the emergence and spread of antimicrobial resistance in major bacterial pathogens for the past decades poses a growing challenge to public health, discovery of novel antimicrobial agents from natural products or modification of existing antibiotics cannot circumvent the problem of antimicrobial resistance. The recent development of bacterial genomics and the availability of genome sequences allow the identification of potentially novel antimicrobial agents. The cellular targets of new antimicrobial agents must be essential for the growth, replication, or survival of the bacterium. Conserved genes among different bacterial genomes often turn out to be essential (1, 2). Thus, the combination of comparative genomics and the gene knock-out procedure can provide effective ways to identify the essential genes of bacterial pathogens (3). Identification of essential genes in bacteria may be utilized for the development of new antimicrobial agents because common essential genes in diverse pathogens could constitute novel targets for broad-spectrum antimicrobial agents.200818392984
9417160.9996General aspects of virus drug resistance with special reference to herpes simplex virus. The features of virus drug resistance are reviewed with examples from studies of herpes simplex virus drug-resistant mutants. Virus drug resistance, compared with drug resistance of bacteria or eukaryotes, is distinguished by its ability to provide information on drug selectivity. Identification of genes in which mutations arise to confer drug resistance defines gene products which contribute to antiviral selectivity. The gene products can then be dissected functionally with the aid of these mutations. Laboratory studies of the frequency of mutation to drug resistance and the features of drug-resistant mutants may have predictive value for the clinic.19863025148
4632170.9996Development and application of the active surveillance of pathogens microarray to monitor bacterial gene flux. BACKGROUND: Human and animal health is constantly under threat by emerging pathogens that have recently acquired genetic determinants that enhance their survival, transmissibility and virulence. We describe the construction and development of an Active Surveillance of Pathogens (ASP) oligonucleotide microarray, designed to 'actively survey' the genome of a given bacterial pathogen for virulence-associated genes. RESULTS: The microarray consists of 4958 reporters from 151 bacterial species and include genes for the identification of individual bacterial species as well as mobile genetic elements (transposons, plasmid and phage), virulence genes and antibiotic resistance genes. The ASP microarray was validated with nineteen bacterial pathogens species, including Francisella tularensis, Clostridium difficile, Staphylococcus aureus, Enterococcus faecium and Stenotrophomonas maltophilia. The ASP microarray identified these bacteria, and provided information on potential antibiotic resistance (eg sufamethoxazole resistance and sulfonamide resistance) and virulence determinants including genes likely to be acquired by horizontal gene transfer (e.g. an alpha-haemolysin). CONCLUSION: The ASP microarray has potential in the clinic as a diagnostic tool, as a research tool for both known and emerging pathogens, and as an early warning system for pathogenic bacteria that have been recently modified either naturally or deliberately.200818844996
9404180.9996The Application of Transposon Insertion Sequencing in Identifying Essential Genes in B. fragilis. Essential genes are those that are indispensable for the survival of organism under specific growth conditions. Investigating essential genes in pathogenic bacteria not only helps to understand vital biological networks but also provides novel targets for drug development. Availability of genetic engineering tools and high-throughput sequencing methods has enabled essential genes identification in many pathogenic gram-positive and gram-negative bacteria. Bacteroides fragilis is one of the major bacteria specific of human gastrointestinal microbiota. When B. fragilis moves out of its niche, it turns into deadly pathogen. Here, we describe detailed method for the essential gene identification in B. fragilis. Generated transposon mutant pool can be used for other applications such as identification of genes responsible for drug resistance in B. fragilis.202234709623
4061190.9996Beyond serial passages: new methods for predicting the emergence of resistance to novel antibiotics. Market launching of a new antibiotic requires knowing in advance its benefits and possible risks, and among them how rapidly resistance will emerge and spread among bacterial pathogens. This information is not only useful from a public health point of view, but also for pharmaceutical industry, in order to reduce potential waste of resources in the development of a compound that might be discontinued at the short term because of resistance development. Most assays currently used for predicting the emergence of resistance are based on culturing the target bacteria by serial passages in the presence of increasing concentrations of antibiotics. Whereas these assays may be valuable for identifying mutations that might cause resistance, they are not useful to establish how fast resistance might appear, neither to address the risk of spread of resistance genes by horizontal gene transfer. In this article, we review recent information pertinent for a more accurate prediction on the emergence and dispersal of antibiotic resistance.201121835695