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516400.9985Genome sequencing analysis of the pncA, rpsA and panD genes responsible for pyrazinamide resistance of Mycobacterium tuberculosis from Indonesian isolates. BACKGROUND: Developing the most suitable treatment against tuberculosis based on resistance profiles is imperative to effectively cure tuberculosis patients. Whole-genome sequencing is a molecular method that allows for the rapid and cost-effective detection of mutations in multiple genes associated with anti-tuberculosis drug resistance. This sequencing approach addresses the limitations of culture-based methods, which may not apply to certain anti-TB drugs, such as pyrazinamide, because of their specific culture medium requirements, potentially leading to biased resistance culture results. METHODS: Thirty-four M. tuberculosis isolates were subcultured on a Lowenstein-Jensen medium. The genome of these bacteria was subsequently isolated using cetyltrimethylammonium bromide. Genome sequencing was performed with Novaseq Illumina 6000 (Illumina), and the data were analysed using the GenTB and Mykrobe applications. We also conducted a de novo analysis to compare the two methods and performed mutation analysis of other genes encoding pyrazinamide resistance, namely rpsA and panD. RESULTS: The results revealed mutations in the pncA gene, which were identified based on the databases accessed through GenTB and Mykrobe. Two discrepancies between the drug susceptibility testing and sequencing results may suggest potential instability in the drug susceptibility testing culture, specifically concerning PZA. Meanwhile, the results of the de novo analysis showed the same result of pncA mutation to the GenTB or Mykrobe; meanwhile, there were silent mutations in rpsA in several isolates and a point mutation; no mutations were found in the panD gene. However, the mutations in the genes encoding pyrazinamide require further and in-depth study to understand their relationship to the phenotypic profile. CONCLUSIONS: Compared to the conventional culture method, the whole-genome sequencing method has advantages in determining anti-tuberculosis resistance profiles, especially in reduced time and bias.202439397216
511610.9985Prediction of Antimicrobial Resistance in Gram-Negative Bacteria From Whole-Genome Sequencing Data. BACKGROUND: Early detection of antimicrobial resistance in pathogens and prescription of more effective antibiotics is a fast-emerging need in clinical practice. High-throughput sequencing technology, such as whole genome sequencing (WGS), may have the capacity to rapidly guide the clinical decision-making process. The prediction of antimicrobial resistance in Gram-negative bacteria, often the cause of serious systemic infections, is more challenging as genotype-to-phenotype (drug resistance) relationship is more complex than for most Gram-positive organisms. METHODS AND FINDINGS: We have used NCBI BioSample database to train and cross-validate eight XGBoost-based machine learning models to predict drug resistance to cefepime, cefotaxime, ceftriaxone, ciprofloxacin, gentamicin, levofloxacin, meropenem, and tobramycin tested in Acinetobacter baumannii, Escherichia coli, Enterobacter cloacae, Klebsiella aerogenes, and Klebsiella pneumoniae. The input is the WGS data in terms of the coverage of known antibiotic resistance genes by shotgun sequencing reads. Models demonstrate high performance and robustness to class imbalanced datasets. CONCLUSION: Whole genome sequencing enables the prediction of antimicrobial resistance in Gram-negative bacteria. We present a tool that provides an in silico antibiogram for eight drugs. Predictions are accompanied with a reliability index that may further facilitate the decision making process. The demo version of the tool with pre-processed samples is available at https://vancampn.shinyapps.io/wgs2amr/. The stand-alone version of the predictor is available at https://github.com/pieterjanvc/wgs2amr/.202032528441
582520.9983Polymerase Chain Reaction (PCR) Profiling of Extensively Drug-Resistant (XDR) Pathogenic Bacteria in Pulmonary Tuberculosis Patients. Introduction Pulmonary tuberculosis (TB) remains a global health concern, exacerbated by the emergence of extensively drug-resistant (XDR) strains of Mycobacterium tuberculosis. This study employs advanced molecular techniques, specifically polymerase chain reaction (PCR) profiling, to comprehensively characterize the genetic landscape of XDR pathogenic bacteria in patients diagnosed with pulmonary TB. The objective of the study is to elucidate the genes that are associated with drug resistance in pulmonary TB strains through the application of PCR and analyze specific genetic loci that contribute to the development of resistance against multiple drugs. Materials and methods A total of 116 clinical samples suspected of TB were collected from the tertiary healthcare setting of Saveetha Medical College and Hospitals for the identification of MTB, which includes sputum (n = 35), nasal swabs (n = 17), blood (n = 44), and bronchoalveolar lavage (BAL) (n = 20). The collected specimens were processed and subjected to DNA extraction. As per the protocol, reconstitution of the DNA pellet was carried out. The reconstituted DNA was stored at -20 °C for the PCR assay. From the obtained positive sample specimens, XDR pulmonary TB specimens were focused on the targeted genes, specifically the rpoB gene for rifampicin resistance, inhA, and katG gene for thepromoter region for isoniazid resistance. Results Out of a total of 116 samples obtained, 53 tested positive for pulmonary TB, indicative of a mycobacterial infection. Among these positive cases, 43 patients underwent treatment at a tertiary healthcare facility. Subsequently, a PCR assay was performed with the extracted DNA for the target genes rpoB, inhA, and katG. Specifically, 22 sputum samples exhibited gene expression for rpoB, inhA, and katG, while nine nasal swabs showed expression of the rpoB and inhA genes. Additionally, rpoB gene expression was detected in seven blood specimens, and both rpoB and inhA genes were expressed in five BAL samples. Conclusion The swift diagnosis and efficient treatment of XDR-TB can be facilitated by employing advanced and rapid molecular tests and oral medication regimens. Utilizing both newly developed and repurposed anti-TB drugs like pretomanid, bedaquiline, linezolid, and ethionamide. Adhering to these current recommendations holds promise for managing XDR-TB effectively. Nevertheless, it is significant to conduct well-designed clinical trials and studies to further evaluate the efficacy of new agents and shorter treatment regimens, thus ensuring continuous improvement in the management of this challenging condition.202438953074
511130.9983Antimicrobial 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
584240.9983Draft Genome Sequence and Biofilm Production of a Carbapenemase-Producing Klebsiella pneumoniae (KpR405) Sequence Type 405 Strain Isolated in Italy. Rapid identification and characterization of multidrug-resistant Klebsiella pneumoniae strains is essential to diagnose severe infections in patients. In clinical routine practice, K. pneumoniae is frequently identified and characterized for outbreak investigation. Pulsed-field gel electrophoresis or multilocus sequence typing could be used, but, unfortunately, these methods are time-consuming, laborious, expensive, and do not provide any information about the presence of resistance and virulence genes. In recent years, the decreasing cost of next-generation sequencing and its easy use have led to it being considered a useful method, not only for outbreak surveillance but also for rapid identification and evaluation, in a single step, of virulence factors and resistance genes. Carbapenem-resistant strains of K. pneumoniae have become endemic in Italy, and in these strains the ability to form biofilms, communities of bacteria fixed in an extracellular matrix, can defend the pathogen from the host immune response as well as from antibiotics, improving its persistence in epithelial tissues and on medical device surfaces.202134064924
507950.9983Development 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
511060.9983Surveillance of carbapenem-resistant organisms using next-generation sequencing. The genomic data generated from next-generation sequencing (NGS) provides nucleotide-level resolution of bacterial genomes which is critical for disease surveillance and the implementation of prevention strategies to interrupt the spread of antimicrobial resistance (AMR) bacteria. Infection with AMR bacteria, including Gram-negative Carbapenem-Resistant Organisms (CRO), may be acute and recurrent-once they have colonized a patient, they are notoriously difficult to eradicate. Through phylogenetic tools that assess the single nucleotide polymorphisms (SNPs) within a pathogen genome dataset, public health scientists can estimate the genetic identity between isolates. This information is used as an epidemiologic proxy of a putative outbreak. Pathogens with minimal to no differences in SNPs are likely to be the same strain attributable to a common source or transmission between cases. These genomic comparisons enhance public health response by prompting targeted intervention and infection control measures. This methodology overview demonstrates the utility of phenotypic and molecular assays, antimicrobial susceptibility testing (AST), NGS, publicly available genomics databases, and open-source bioinformatics pipelines for a tiered workflow to detect resistance genes and potential clusters of illness. These methods, when used in combination, facilitate a genomic surveillance workflow for detecting potential AMR bacterial outbreaks to inform epidemiologic investigations. Use of this workflow helps to target and focus epidemiologic resources to the cases with the highest likelihood of being related.202337255756
582670.9983Rapid and accurate sepsis diagnostics via a novel probe-based multiplex real-time PCR system. Sepsis is a critical clinical emergency that requires prompt diagnosis and intervention. Its prevalence has increased due to the aging population and increased antibiotic resistance. Early identification and the use of innovative technologies are crucial for improving patient outcomes. Modern methodologies are needed to minimize the turnaround time for diagnosis and improve outcomes. Rapid diagnostic tests and multiplex PCR are effective but have limitations in identifying a range of pathogens and target genes. Our study evaluated two novel probe-based multiplex real-time PCR systems: the SEPSI ID and SEPSI DR panels. These systems can quickly identify bacterial and fungal pathogens, alongside antibiotic resistance genes. The assays cover 29 microorganisms (gram-negative bacteria, gram-positive bacteria, yeast, and mold species), alongside 23 resistance genes and four virulence factors. A streamlined workflow uses 2 µL of broth from positive blood cultures (BCs) without nucleic acid extraction and provides results in approximately 1 h. We present the results from an evaluation of 228 BCs and 22 isolates previously characterized by whole-genome sequencing. In comparison to the reference methods, the SEPSI ID panel demonstrated a sensitivity of 96.88%, a specificity of 100%, and a PPV of 100%, whereas the SEPSI DR panel showed a sensitivity of 97.8%, a PPV of 89.7%, and a specificity of 96.7%. Both panels also identified additional pathogens and resistance-related targets not detected by conventional methods. This assay shows promise for rapidly and accurately diagnosing sepsis. Future studies should validate its performance in various clinical settings to enhance sepsis management and improve patient outcomes.IMPORTANCEWe present a new diagnostic method that enables the quick and precise identification of pathogens and resistance genes from positive blood cultures, eliminating the need for nucleic acid extraction. This technique can also be used on fresh pathogen cultures. It has the potential to greatly improve treatment protocols, leading to better patient outcomes, more responsible antibiotic use, and more efficient management of healthcare resources.202541025980
511280.9983Genome-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
505790.9983Genomic investigation unveils colistin resistance mechanism in carbapenem-resistant Acinetobacter baumannii clinical isolates. Colistin resistance in Acinetobacter baumannii is mediated by multiple mechanisms. Recently, mutations within pmrABC two-component system and overexpression of eptA gene due to upstream insertion of ISAba1 have been shown to play a major role. Thus, the aim of our study is to characterize colistin resistance mechanisms among the clinical isolates of A. baumannii in India. A total of 207 clinical isolates of A. baumannii collected from 2016 to 2019 were included in this study. Mutations within lipid A biosynthesis and pmrABC genes were characterized by whole-genome shotgun sequencing. Twenty-eight complete genomes were further characterized by hybrid assembly approach to study insertional inactivation of lpx genes and the association of ISAba1-eptA. Several single point mutations (SNPs), like M12I in pmrA, A138T and A444V in pmrB, and E117K in lpxD, were identified. We are the first to report two novel SNPs (T7I and V383I) in the pmrC gene. Among the five colistin-resistant A. baumannii isolates where complete genome was available, the analysis showed that three of the five isolates had ISAba1 insertion upstream of eptA. No mcr genes were identified among the isolates. We mapped the SNPs on the respective protein structures to understand the effect on the protein activity. We found that majority of the SNPs had little effect on the putative protein function; however, some SNPs might destabilize the local structure. Our study highlights the diversity of colistin resistance mechanisms occurring in A. baumannii, and ISAba1-driven eptA overexpression is responsible for colistin resistance among the Indian isolates.IMPORTANCEAcinetobacter baumannii is a Gram-negative, emerging and opportunistic bacterial pathogen that is often associated with a wide range of nosocomial infections. The treatment of these infections is hindered by increase in the occurrence of A. baumannii strains that are resistant to most of the existing antibiotics. The current drug of choice to treat the infection caused by A. baumannii is colistin, but unfortunately, the bacteria started to show resistance to the last-resort antibiotic. The loss of lipopolysaccharides and mutations in lipid A biosynthesis genes are the main reasons for the colistin resistance. The present study characterized 207 A. baumannii clinical isolates and constructed complete genomes of 28 isolates to recognize the mechanisms of colistin resistance. We showed the mutations in the colistin-resistant variants within genes essential for lipid A biosynthesis and that cause these isolates to lose the ability to produce lipopolysaccharides.202438214512
4759100.9983Recent advances in rapid antimicrobial susceptibility testing systems. INTRODUCTION: Until recently antimicrobial susceptibility testing (AST) methods based on the demonstration of phenotypic susceptibility in 16-24 h remained largely unchanged. AREAS COVERED: Advances in rapid phenotypic and molecular-based AST systems. EXPERT OPINION: AST has changed over the past decade, with many rapid phenotypic and molecular methods developed to demonstrate phenotypic or genotypic resistance, or biochemical markers of resistance such as β-lactamases associated with carbapenem resistance. Most methods still require isolation of bacteria from specimens before both legacy and newer methods can be used. Bacterial identification by MALDI-TOF mass spectroscopy is now widely used and is often key to the interpretation of rapid AST results. Several PCR arrays are available to detect the most frequent pathogens associated with bloodstream infections and their major antimicrobial resistance genes. Many advances in whole-genome sequencing of bacteria and fungi isolated by culture as well as directly from clinical specimens have been made but are not yet widely available. High cost and limited throughput are the major obstacles to uptake of rapid methods, but targeted use, continued development and decreasing costs are expected to result in more extensive use of these increasingly useful methods.202133926351
5823110.9982Comparing Patient Risk Factor-, Sequence Type-, and Resistance Locus Identification-Based Approaches for Predicting Antibiotic Resistance in Escherichia coli Bloodstream Infections. Rapid diagnostic tests for antibiotic resistance that identify the presence or absence of antibiotic resistance genes/loci are increasingly being developed. However, these approaches usually neglect other sources of predictive information which could be identified over shorter time periods, including patient epidemiologic risk factors for antibiotic resistance and markers of lineage. Using a data set of 414 Escherichia coli isolates recovered from separate episodes of bacteremia at a single academic institution in Toronto, Ontario, Canada, between 2010 and 2015, we compared the potential predictive ability of three approaches (epidemiologic risk factor-, pathogen sequence type [ST]-, and resistance gene identification-based approaches) for classifying phenotypic resistance to three antibiotics representing classes of broad-spectrum antimicrobial therapy (ceftriaxone [a 3rd-generation cephalosporin], ciprofloxacin [a fluoroquinolone], and gentamicin [an aminoglycoside]). We used logistic regression models to generate model receiver operating characteristic (ROC) curves. Predictive discrimination was measured using apparent and corrected (bootstrapped) areas under the curves (AUCs). Epidemiologic risk factor-based models based on two simple risk factors (prior antibiotic exposure and recent prior susceptibility of Gram-negative bacteria) provided a modest predictive discrimination, with AUCs ranging from 0.65 to 0.74. Sequence type-based models demonstrated strong discrimination (AUCs, 0.83 to 0.94) across all three antibiotic classes. The addition of epidemiologic risk factors to sequence type significantly improved the ability to predict resistance for all antibiotics (P < 0.05). Resistance gene identification-based approaches provided the highest degree of discrimination (AUCs, 0.88 to 0.99), with no statistically significant benefit being achieved by adding the patient epidemiologic predictors. In summary, sequence type or other lineage-based approaches could produce an excellent discrimination of antibiotic resistance and may be improved by incorporating readily available patient epidemiologic predictors but are less discriminatory than identification of the presence of known resistance loci.201930894438
4452120.9982Whole-Genome Analysis of Acinetobacter baumannii Strain AB43 Containing a Type I-Fb CRISPR-Cas System: Insights into the Relationship with Drug Resistance. The CRISPR-Cas system is a bacterial and archaea adaptive immune system and is a newly recognized mechanism for controlling antibiotic resistance gene transfer. Acinetobacter baumannii (A. baumannii) is an important organism responsible for a variety of nosocomial infections. A. baumannii infections have become problematic worldwide because of the resistance of A. baumannii to multiple antibiotics. Thus, it is clinically significant to explore the relationship between the CRISPR-Cas system and drug resistance in A. baumannii. This study aimed to analyze the genomic characteristics of the A. baumannii strain AB3 containing the type I-Fb CRISPR-Cas system, which was isolated from a tertiary care hospital in China, and to investigate the relationship between the CRISPR-Cas system and antibiotic resistance in this strain. The whole-genome sequencing (WGS) of the AB43 strain was performed using Illumina and PacBio sequencing. The complete genome of AB43 consisted of a 3,854,806 bp chromosome and a 104,309 bp plasmid. The specific characteristics of the CRISPR-Cas system in AB43 are described as follows: (1) The strain AB43 carries a complete type I-Fb CRISPR-Cas system; (2) Homology analysis confirmed that the cas genes in AB43 share high sequence similarity with the same subtype cas genes; (3) A total of 28 of 105 A. baumannii AB43 CRISPR spacers matched genes in the bacteriophage genome database and the plasmid database, implying that the CRISPR-Cas system in AB43 provides immunity against invasive bacteriophage and plasmids; (4) None of the CRISPR spacers in A. baumannii AB43 were matched with antimicrobial resistance genes in the NCBI database. In addition, we analyzed the presence of antibiotic resistance genes and insertion sequences in the AB43 strain and found that the number of antibiotic resistance genes was not lower than in the "no CRISPR-Cas system" strain. This study supports the idea that the CRISPR-Cas system may inhibit drug-resistance gene expression via endogenous gene regulation, except to the published mechanism that the CRISPR-Cas system efficiently limits the acquisition of antibiotic resistance genes that make bacteria sensitive to antibiotics.202236080431
1789130.9982Genomic and phylogenetic analysis of a multidrug-resistant Burkholderia contaminans strain isolated from a patient with ocular infection. OBJECTIVES: The genus Burkholderia comprises rod-shaped, non-spore-forming, obligately aerobic Gram-negative bacteria that is found across diverse ecological niches. Burkholderia contaminans, an emerging pathogen associated with cystic fibrosis, is frequently isolated from contaminated medical devices in hospital settings. The aim of this study was to understand the genomic characteristics, antimicrobial resistance profile and virulence determinants of B. contaminans strain SBC01 isolated from the eye of a patient hit by a cow's tail. METHODS: A hybrid sequence of isolate SBC01 was generated using Illumina HiSeq and Oxford Nanopore Technology platforms. Unicycler was used to assemble the hybrid genomic sequence. The draft genome was annotated using the NCBI Prokaryotic Genome Annotation Pipeline. Antimicrobial susceptibility testing was performed by VITEK®2. Antimicrobial resistance and virulence genes were identified using validated bioinformatics tools. RESULTS: The assembled genome size is 8 841 722 bp with a G+C content of 66.33% distributed in 19 contigs. Strain SBC01 was found to possess several antimicrobial resistance and efflux pump genes. The isolate was susceptible to tetracyclines, meropenem and ceftazidime. Many genes encoding potential virulence factors were identified. CONCLUSION: Burkholderia contaminans SBC01 belonging to sequence type 482 (ST482) is a multidrug-resistant strain containing diverse antimicrobial resistance genes, revealing the risks associated with infections by new Burkholderia spp. The large G+C-rich genome has a myriad of virulence factors, highlighting its pathogenic potential. Thus, while providing insights into the antimicrobial resistance and virulence potential of this uncommon species, the present analysis will aid in understanding the evolution and speciation in the Burkholderia genus.202133965629
5827140.9982Duplex dPCR System for Rapid Identification of Gram-Negative Pathogens in the Blood of Patients with Bloodstream Infection: A Culture-Independent Approach. Early and accurate detection of pathogens is important to improve clinical outcomes of bloodstream infections (BSI), especially in the case of drug-resistant pathogens. In this study, we aimed to develop a culture-independent digital PCR (dPCR) system for multiplex detection of major sepsiscausing gram-negative pathogens and antimicrobial resistance genes using plasma DNA from BSI patients. Our duplex dPCR system successfully detected nine targets (five bacteria-specific targets and four antimicrobial resistance genes) through five reactions within 3 hours. The minimum detection limit was 50 ag of bacterial DNA, suggesting that 1 CFU/ml of bacteria in the blood can be detected. To validate the clinical applicability, cell-free DNA samples from febrile patients were tested with our system and confirmed high consistency with conventional blood culture. This system can support early identification of some drug-resistant gram-negative pathogens, which can help improving treatment outcomes of BSI.202134528911
5467150.9982Whole genome sequencing-based classification of human-related Haemophilus species and detection of antimicrobial resistance genes. BACKGROUND: Bacteria belonging to the genus Haemophilus cause a wide range of diseases in humans. Recently, H. influenzae was classified by the WHO as priority pathogen due to the wide spread of ampicillin resistant strains. However, other Haemophilus spp. are often misclassified as H. influenzae. Therefore, we established an accurate and rapid whole genome sequencing (WGS) based classification and serotyping algorithm and combined it with the detection of resistance genes. METHODS: A gene presence/absence-based classification algorithm was developed, which employs the open-source gene-detection tool SRST2 and a new classification database comprising 36 genes, including capsule loci for serotyping. These genes were identified using a comparative genome analysis of 215 strains belonging to ten human-related Haemophilus (sub)species (training dataset). The algorithm was evaluated on 1329 public short read datasets (evaluation dataset) and used to reclassify 262 clinical Haemophilus spp. isolates from 250 patients (German cohort). In addition, the presence of antibiotic resistance genes within the German dataset was evaluated with SRST2 and correlated with results of traditional phenotyping assays. RESULTS: The newly developed algorithm can differentiate between clinically relevant Haemophilus species including, but not limited to, H. influenzae, H. haemolyticus, and H. parainfluenzae. It can also identify putative haemin-independent H. haemolyticus strains and determine the serotype of typeable Haemophilus strains. The algorithm performed excellently in the evaluation dataset (99.6% concordance with reported species classification and 99.5% with reported serotype) and revealed several misclassifications. Additionally, 83 out of 262 (31.7%) suspected H. influenzae strains from the German cohort were in fact H. haemolyticus strains, some of which associated with mouth abscesses and lower respiratory tract infections. Resistance genes were detected in 16 out of 262 datasets from the German cohort. Prediction of ampicillin resistance, associated with bla(TEM-1D), and tetracycline resistance, associated with tetB, correlated well with available phenotypic data. CONCLUSIONS: Our new classification database and algorithm have the potential to improve diagnosis and surveillance of Haemophilus spp. and can easily be coupled with other public genotyping and antimicrobial resistance databases. Our data also point towards a possible pathogenic role of H. haemolyticus strains, which needs to be further investigated.202235139905
4824160.9982Chemogenomic Screen for Imipenem Resistance in Gram-Negative Bacteria. Carbapenem-resistant Gram-negative bacteria are considered a major threat to global health. Imipenem (IMP) is used as a last line of treatment against these pathogens, but its efficacy is diminished by the emergence of resistance. We applied a whole-genome screen in Escherichia coli, Klebsiella pneumoniae, and Pseudomonas aeruginosa isolates that were submitted to chemical mutagenesis, selected for IMP resistance, and characterized by next-generation sequencing. A comparative analysis of IMP-resistant clones showed that most of the highly mutated genes shared by the three species encoded proteins involved in transcription or signal transduction. Of these, the rpoD gene was one of the most prevalent and an E. coli strain disrupted for rpoD displayed a 4-fold increase in resistance to IMP. E. coli and K. pneumoniae also specifically shared several mutated genes, most involved in membrane/cell envelope biogenesis, and the contribution in IMP susceptibility was experimentally proven for amidases, transferases, and transglycosidases. P. aeruginosa differed from the two Enterobacteriaceae isolates with two different resistance mechanisms, with one involving mutations in the oprD porin or, alternatively, in two-component systems. Our chemogenomic screen performed with the three species has highlighted shared and species-specific responses to IMP.IMPORTANCE Gram-negative carbapenem-resistant bacteria are a major threat to global health. The use of genome-wide screening approaches to probe for genes or mutations enabling resistance can lead to identification of molecular markers for diagnostics applications. We describe an approach called Mut-Seq that couples chemical mutagenesis and next-generation sequencing for studying resistance to imipenem in the Gram-negative bacteria Escherichia coli, Klebsiella pneumoniae, and Pseudomonas aeruginosa The use of this approach highlighted shared and species-specific responses, and the role in resistance of a number of genes involved in membrane biogenesis, transcription, and signal transduction was functionally validated. Interestingly, some of the genes identified were previously considered promising therapeutic targets. Our genome-wide screen has the potential to be extended outside drug resistance studies and expanded to other organisms.201931744905
4345170.9982Comprehensive identification of single nucleotide polymorphisms associated with beta-lactam resistance within pneumococcal mosaic genes. Traditional genetic association studies are very difficult in bacteria, as the generally limited recombination leads to large linked haplotype blocks, confounding the identification of causative variants. Beta-lactam antibiotic resistance in Streptococcus pneumoniae arises readily as the bacteria can quickly incorporate DNA fragments encompassing variants that make the transformed strains resistant. However, the causative mutations themselves are embedded within larger recombined blocks, and previous studies have only analysed a limited number of isolates, leading to the description of "mosaic genes" as being responsible for resistance. By comparing a large number of genomes of beta-lactam susceptible and non-susceptible strains, the high frequency of recombination should break up these haplotype blocks and allow the use of genetic association approaches to identify individual causative variants. Here, we performed a genome-wide association study to identify single nucleotide polymorphisms (SNPs) and indels that could confer beta-lactam non-susceptibility using 3,085 Thai and 616 USA pneumococcal isolates as independent datasets for the variant discovery. The large sample sizes allowed us to narrow the source of beta-lactam non-susceptibility from long recombinant fragments down to much smaller loci comprised of discrete or linked SNPs. While some loci appear to be universal resistance determinants, contributing equally to non-susceptibility for at least two classes of beta-lactam antibiotics, some play a larger role in resistance to particular antibiotics. All of the identified loci have a highly non-uniform distribution in the populations. They are enriched not only in vaccine-targeted, but also non-vaccine-targeted lineages, which may raise clinical concerns. Identification of single nucleotide polymorphisms underlying resistance will be essential for future use of genome sequencing to predict antibiotic sensitivity in clinical microbiology.201425101644
5824180.9982Evaluation of a micro/nanofluidic chip platform for the high-throughput detection of bacteria and their antibiotic resistance genes in post-neurosurgical meningitis. BACKGROUND: Post-neurosurgical meningitis (PNM) is one of the most severe hospital-acquired infections worldwide, and a large number of pathogens, especially those possessing multi-resistance genes, are related to these infections. Existing methods for detecting bacteria and measuring their response to antibiotics lack sensitivity and stability, and laboratory-based detection methods are inconvenient, requiring at least 24h to complete. Rapid identification of bacteria and the determination of their susceptibility to antibiotics are urgently needed, in order to combat the emergence of multi-resistant bacterial strains. METHODS: This study evaluated a novel, fast, and easy-to-use micro/nanofluidic chip platform (MNCP), which overcomes the difficulties of diagnosing bacterial infections in neurosurgery. This platform can identify 10 genus or species targets and 13 genetic resistance determinants within 1h, and it is very simple to operate. A total of 108 bacterium-containing cerebrospinal fluid (CSF) cultures were tested using the MNCP for the identification of bacteria and determinants of genetic resistance. The results were compared to those obtained with conventional identification and antimicrobial susceptibility testing methods. RESULTS: For the 108 CSF cultures, the concordance rate between the MNCP and the conventional identification method was 94.44%; six species attained 100% consistency. For the production of carbapenemase- and extended-spectrum beta-lactamase (ESBL)-related antibiotic resistance genes, both the sensitivity and specificity of the MNCP tests were high (>90.0%) and could fully meet the requirements of clinical diagnosis. CONCLUSIONS: The MNCP is fast, accurate, and easy to use, and has great clinical potential in the treatment of post-neurosurgical meningitis.201829559366
5839190.9982Computer Program for Detection and Analyzing the Porin-Mediated Antibiotic Resistance of Bacteria. The aim of this work was to develop a new software tool for identifying gene mutations that determine the porin-mediated resistance to antibiotics in gram-negative bacteria and to demonstrate the functionality of this program by detecting porin-mediated resistance to carbapenems in clinical isolates of Pseudomonas aeruginosa. MATERIALS AND METHODS: The proposed algorithm is based on searching for a correspondence between the reference and the studied genes. When the sought nucleotide sequence is found in the analyzed genome, it is compared with the reference one and analyzed. The genomic analysis is then verified by comparing between the amino acid sequences encoded by the reference and studied genes. The genes of the susceptible P. aeruginosa ATCC 27853 strain were used as the reference nucleotide sequences encoding for porins (OprD, OpdD, and OpdP) involved in the transport of carbapenems into the bacterial cell. The complete genomes of clinical P. aeruginosa isolates from the PATRIC database 3.6.9 and our own collection were used to test the functionality of the proposed program. The analyzed isolates were phenotypically characterized according to the CLSI standard. The search for carbapenemase genes in the studied genomes of P. aeruginosa was carried out using the ResFinder 4.1. RESULTS: The developed program for detecting the genetic determinants of non-plasmid antibiotic resistance made it possible to identify mutations of various types and significance in the porin genes of P. aeruginosa clinical isolates. These mutations led to modifications of the peptide structure of porin proteins. Single amino acid substitutions prevailed in the OpdD and OpdP porins of carbapenem-susceptible and carbapenem-resistant isolates. In the carbapenem-resistant strains, the gene encoding for OprD porin was found heavily modified, including insertions and/or deletions, which led to premature termination of porin synthesis. In several isolates resistant to meropenem, no mutations were detected in the gene encoding for OprD, which might be associated with alternative mechanisms of resistance to carbapenems. CONCLUSION: The proposed software product can become an effective tool for deciphering the molecular genetic mechanisms of bacterial chromosomal resistance to antibiotics. Testing the program revealed differences between the occurrences of mutations significant for carbapenem resistance in the oprD, opdD, and opdP genes.202135265355