Identification Of Antibiotic Resistance Research Articles

Machine Learning in FTIR Spectrum for the Identification of Antibiotic Resistance: A Demonstration with Different Species of Microorganisms.

Recent studies introduced the importance of using machine learning algorithms in research focused on the identification of antibiotic resistance. In this study, we highlight the importance of building solid machine learning foundations to differentiate antimicrobial resistance among microorganisms. Using advanced machine learning algorithms, we established a methodology capable of analyzing the FTIR structural profile of the samples of Streptococcus pyogenes and Streptococcus mutans (Gram-positive), as well as Escherichia coli and Klebsiella pneumoniae (Gram-negative), demonstrating cross-sectional applicability in this focus on different microorganisms. The analysis focuses on specific biomolecules-Carbohydrates, Fatty Acids, and Proteins-in FTIR spectra, providing a multidimensional database that transcends microbial variability. The results highlight the ability of the method to consistently identify resistance patterns, regardless of the Gram classification of the bacteria and the species involved, reinforcing the premise that the structural characteristics identified are universal among the microorganisms tested. By validating this approach in four distinct species, our study proves the versatility and precision of the methodology used, in addition to bringing support to the development of an innovative protocol for the rapid and safe identification of antimicrobial resistance. This advance is crucial for optimizing treatment strategies and avoiding the spread of resistance. This emphasizes the relevance of specialized machine learning bases in effectively differentiating between resistance profiles in Gram-negative and Gram-positive bacteria to be implemented in the identification of antibiotic resistance. The obtained result has a high potential to be applied to clinical procedures.

Revolutionizing the probiotic functionality, biochemical activity, antibiotic resistance and specialty genes of Pediococcus acidilactici BCB1H via in-vitro and in-silico approaches.

This study presents a comprehensive genomic exploration, biochemical characterization, and the identification of antibiotic resistance and specialty genes of Pediococcus acidilactici BCB1H strain. The functional characterization, genetic makeup, biological activities, and other considerable parameters have been investigated in this study with a prime focus on antibiotic resistance and specialty gene profiles. The results of this study revealed the unique susceptibility patterns for antibiotic resistance and specialty genes. BCB1H had good invitro probiotic properties, which survived well in simulated artificial gastrointestinal fluid, and exhibited acid and bile salt resistance. BCB1H didn't produce hemolysis and had certain antibiotic sensitivity, making it a relatively safe LAB strain. Simultaneously, it had good self-coagulation characteristics and antioxidant activity. The EPS produced by BCB1H also had certain antioxidant activity and hypoglycemic function. Moreover, the genome with a 42.4 % GC content and a size of roughly 1.92 million base pairs was analyzed in the genomic investigations. The genome annotation identified 192 subsystems and 1,895 genes, offering light on the metabolic pathways and functional categories found in BCB1H. The identification of specialty genes linked to the metabolism of carbohydrates, stress response, pathogenicity, and amino acids highlighted the strain's versatility and possible uses. This study establishes the groundwork for future investigations by highlighting the significance of using multiple strains to investigate genetic diversity and experimental validation of predicted genes. The results provide a roadmap for utilizing P.acidilactici BCB1H's genetic traits for industrial and medical applications, opening the door to real-world uses in industries including food technology and medicine.

Draft genome of novel cyanobacteria Sphaerothrix Gracilis isolated from coastal microplastics reveal insights to chemical ecology, bloom and plastic-utilization potential.

Cyanobacteria are oxygenic photosynthetic organisms which are found across many ecosystems, including freshwater and marine habitats. They are also found on natural and artificial surfaces. In this study, we cultured and characterise a novel cyanobacterium from the surfaces of foam microplastics of tropical coastal waters. We study the chemical ecology of this cyanobacterium, Sphaerothrix gracilis gen. et sp. nov., together with its potential to form harmful cyanobacterial blooms and bioremediation applications to combat plastic pollution. The genome of S. gracilis spanned 6.7 Mbp, with identification of antibiotic resistance, nitrogen-fixation, plastic-degrading and genes involved in harmful metabolite production. The transport of potentially harmful S. gracilis in coastal environments could have severe implications on human health and food security, especially in times of a cyanobacterial bloom.

Identification ofantibiotic resistance genes inEscherichia coli from subclinical mastitis milk indairy cows and goats, East Java Province.

Antibiotics are still used totreat mastitis indairy cows inIndonesia. This study aimed toanalyse antibiotic resistance genes inEscherichia coli (E.coli) from subclinical mastitis milk inEast Java Province, Indonesia. Thesamples consisted ofsubclinical mastitis milk from cows and goats. Atotal of592-quarter cow's milk and 71goat's milk samples from both halves ofthe udder were collected from 67farms inLumajang, Banyuwangi, Malang, Sidoarjo, Jember, Pasuruan, Probolinggo, and Mojokerto. Subclinical mastitis samples were screened using the California mastitis test (CMT). E.coli was identified byphenotypic and genotypic methods. E.coli wasconfirmed with aprimer specific tothe polymerase chain reaction (PCR) technique. Gene resistance ofE.coli was tested using the multiplex-PCR (mPCR) technique with primers encoding the genes temoneira enzyme (TEM), oxacillinase (OXA), sulfhydryl variable (SHV), and cefotaximase-munich IV (CTX-M IV). These genes were chosen because mastitis treatment generally uses oxacilline and β-lactam antibiotics. All data obtained were analysed descriptively. Theresults show that six isolates ofE.coli (46.15%) carried asingle resistance gene (TEM orSHV) and two isolates (33.33%) were confirmed asmultiple drug-resistant organisms (MDROs) (TEM and SHV). Theresistance genes were found insamples originating from Blitar, Banyuwangi, Lumajang, and Pasuruan Regencies. This research implies that antibiotic-resistance genes found inE.coli oncertain farms are dangerous and may allow gene transmission toother bacteria that make treatment for mastitis orother bacterial infections ineffective.

Analysis of Whole-Genome Sequences of Pathogenic Gram-Positive and Gram-Negative Isolates from the Same Hospital Environment to Investigate Common Evolutionary Trends Associated with Horizontal Gene Exchange, Mutations and DNA Methylation Patterning.

Hospital-acquired infections are a generally recognized problem for healthcare professionals. Clinical variants of Gram-negative and Gram-positive pathogens are characterized with enhanced antibiotic resistance and virulence due to mutations and the horizontal acquisition of respective genetic determinants. In this study, two Escherichia coli, two Klebsiella pneumoniae, three Pseudomonas aeruginosa, two Staphylococcus aureus, one Staphylococcus epidermidis and one Streptococcus pneumoniae showing broad spectra of antibiotic resistance were isolated from patients suffering from nosocomial infections in a local hospital in Almaty, Kazakhstan. The aim of the study was to compare general and species-specific pathways of the development of virulence and antibiotic resistance through opportunistic pathogens causing hospital-acquired infections. The whole-genome PacBio sequencing of the isolates allowed for the genotyping and identification of antibiotic resistance and virulence genetic determinants located in the chromosomes, plasmids and genomic islands. It was concluded that long-read sequencing is a useful tool for monitoring the epidemiological situation in hospitals. Marker antibiotic resistance mutations common for different microorganisms were identified, which were acquired due to antibiotic-selective pressure in the same clinical environment. The genotyping and identification of strain-specific DNA methylation motifs were found to be promising in estimating the risks associated with hospital infection outbreaks and monitoring the distribution and evolution of nosocomial pathogens.

323. Comparing Two Whole Genome Sequencing Bioinformatic Software for Identifying Enterococcal Antibiotic-Resistant Genes

Abstract Background Enterococci are leading causes of infections, and many strains are multidrug-resistant. Identification of antibiotic resistance can be achieved either phenotypically using Clinical & Laboratory Standards Institute (CLSI) minimum inhibitory concentration (MIC) cut-offs, or genotypically using whole genome sequencing (WGS). Here we compare the output from two software pipelines: EPISEQ CSTM (BIOMÉRIEUX, Marcy l ‘Etoile, France) and ResFinder to understand the similarities and differences in their ability to identify antibiotic resistance genes. Methods We performed WGS on 89 clinical isolates of Enterococci (both E. faecalis and faecium) from two distinct tertiary care Detroit hospitals admitted to 16 intensive care units (ICU) and non-ICU wards between 2017-2019. WGS was performed using the NextSeq (Illumina Inc., CA) and analyzed using two bioinformatics pipelines mentioned above. The antibiotic resistance outputs were compared to identify both similarities and differences. Results There was a significant difference in the genetic mutation output from both software. EPISEQ was able to identify 13 & 15 different genetic mutations for Enterococcus faecalis and faecium respectively which were not identified by ResFinder (Table 1). There were 9 & 12 common genetic mutations for Enterococcus faecalis and faecium respectively which were identified by both software. ResFinder was able to identify only two different gene mutations which were not identified by EPISEQ. Table 1:Genetic mutations identified by EPISEQ and ResFinder arranged by resistance to its respective drug class. Conclusion The ability to identify different genetic mutations by both software products likely depends on databases used to determine the antibiotic resistant genes. EPISEQ CS uses 4 different databases (including ResFinder) as well as other proprietary databases making it more sensitive, thereby able to identify more genetic mutations compared to ResFinder alone. The costs for analyzing the WGS data through proprietary software is steep compared to open-source software. Standards metrics and methods for interpretations are needed before these methods can be adapted for clinical applications. Further studies are needed to understand the value of identifying these additional genes by comparing it to phenotypic susceptibilities. Disclosures Piyali Chatterjee, PhD, AHRQ Grant # 1R03HS027667-01: Grant/Research Support|AHRQ Grant # 1R03HS027667-01: Central Texas Veterans Health Care System Keith S. Kaye, MD, MPH, Allecra: Advisor/Consultant|GlaxoSmithKline plc.: Receiving symposia honoraria|GlaxoSmithKline plc.: GlaxoSmithKline plc.-sponsored study 212502|Merck: Advisor/Consultant|qpex: Advisor/Consultant|Shionogi: Grant/Research Support|Spero: Advisor/Consultant Chetan Jinadatha, MD, MPH, AHRQ R01 Grant-5R01HS025598: Grant/Research Support|EOS Surfaces: Copper Coupons and materials for testing.

“Omic” Approaches to Bacteria and Antibiotic Resistance Identification

The quick and accurate identification of microorganisms and the study of resistance to antibiotics is crucial in the economic and industrial fields along with medicine. One of the fastest-growing identification methods is the spectrometric approach consisting in the matrix-assisted laser ionization/desorption using a time-of-flight analyzer (MALDI-TOF MS), which has many advantages over conventional methods for the determination of microorganisms presented. Thanks to the use of a multiomic approach in the MALDI-TOF MS analysis, it is possible to obtain a broad spectrum of data allowing the identification of microorganisms, understanding their interactions and the analysis of antibiotic resistance mechanisms. In addition, the literature data indicate the possibility of a significant reduction in the time of the sample preparation and analysis time, which will enable a faster initiation of the treatment of patients. However, it is still necessary to improve the process of identifying and supplementing the existing databases along with creating new ones. This review summarizes the use of “-omics” approaches in the MALDI TOF MS analysis, including in bacterial identification and antibiotic resistance mechanisms analysis.

Identification of antibiotic resistance and virulence-encoding factors in Klebsiella pneumoniae by Raman spectroscopy and deep learning.

Summary Klebsiella pneumoniae has become the number one bacterial pathogen that causes high mortality in clinical settings worldwide. Clinical K. pneumoniae strains with carbapenem resistance and/or hypervirulent phenotypes cause higher mortality comparing with classical K. pneumoniae strains. Rapid differentiation of clinical K. pneumoniae with high resistance/hypervirulence from classical K. pneumoniae would allow us to develop rational and timely treatment plans. In this study, we developed a convolution neural network (CNN) as a prediction method using Raman spectra raw data for rapid identification of ARGs, hypervirulence‐encoding factors and resistance phenotypes from K. pneumoniae strains. A total of 71 K. pneumoniae strains were included in this study. The minimum inhibitory concentrations (MICs) of 15 commonly used antimicrobial agents on K. pneumoniae strains were determined. Seven thousand four hundred fifty‐five spectra were obtained using the InVia Reflex confocal Raman microscope and used for deep learning‐based and machine learning (ML) algorithms analyses. The quality of predictors was estimated in an independent data set. The results of antibiotic resistance and virulence‐encoding factors identification showed that the CNN model not only simplified the classification system for Raman spectroscopy but also provided significantly higher accuracy to identify K. pneumoniae with high resistance and virulence when compared with the support vector machine (SVM) and logistic regression (LR) models. By back‐testing the Raman‐CNN platform on 71 K. pneumoniae strains, we found that Raman spectroscopy allows for highly accurate and rationally designed treatment plans against bacterial infections within hours. More importantly, this method could reduce healthcare costs and antibiotics misuse, limiting the development of antimicrobial resistance and improving patient outcomes.

Utilization of Antibiotics and Identification of Antibiotic Resistance in Different Microbes

The inappropriate use of antibiotics contributes to the development of resistant bacteria and has a significant influence on the treatment failure. The increasing rapid development and spread of ABR (Antibiotic Resistance) has become a big issue through worldwide during the past few decades. The main objective is to identify most prescribing antibiotics in clinical practice. To evaluate the prescribing pattern of antibiotics for different microbial infection. It is a prospective observational study of antibiotic prescribing patterns conducted over 6 months in outpatient and inpatient departments of Narayana General Hospital, Nellore. Collected data was analysed based on demographics like age, gender, monotherapy, dual therapy, triple therapy and quadrupole therapy. In 614 antibiotic prescribed patients, utilization of antibiotic is more in 45+years. The mono, dual, triple & quadruple therapy of antibiotics was observed as 79.8%, 17.2%, 2.6% & 0.3% respectively. The most commonly prescribed antibiotics are Cefuroxime and Metronidazole (5%), Ceftriaxone and Doxycycline (6%), Ciprofloxacin (7%), Cefixime (11%), Ceftriaxone (13%), Cefpodoxime (14%), Amoxicillin (24%). Utilization of antibiotics is more in general medicine, followed by surgery departments. Most of the infections are due to Escherichia coli (54%) and Klebsiella species (34%) and were mostly isolated from urine and blood specimens. Antibiotics which are highly prescribing in clinics were Amoxicillin, Ciprofloxacin, Ceftriaxone and Cefuroxime. Most of the isolated bacterial species in the community had developed resistance to above antibiotics. Re-evaluation and advancement in antibiotic therapy is strongly recommended to overcome antibiotic resistance.

An Outbreak of Carbapenem-Resistant and Hypervirulent Klebsiella pneumoniae in an Intensive Care Unit of a Major Teaching Hospital in Wenzhou, China.

Carbapenem-resistant, hypervirulent Klebsiella pneumoniae (CR-hvKP) has recently emerged as a significant threat to public health. In this study, 29 K. pneumoniae isolates were isolated from eight patients admitted to the intensive care unit (ICU) of a comprehensive teaching hospital located in China from March 2017 to January 2018. Clinical information of patients was the basis for the further analyses of the isolates including antimicrobial susceptibility tests, identification of antibiotic resistance and virulence gene determinants, multilocus sequence typing (MLST), XbaI-macrorestriction by pulsed-field gel electrophoresis (PFGE). Selected isolates representing distinct resistance profiles and virulence phenotypes were screened for hypervirulence in a Galleria mellonella larvae infection model. In the course of the outbreak, the overall mortality rate of patients was 100% (n = 8) attributed to complications arising from CR-hvKP infections. All isolates except one (28/29, 96.6%) were resistant to multiple antimicrobial agents, and harbored diverse resistance determinants that included the globally prevalent carbapenemase blaKPC−2. Most isolates had hypervirulent genotypes being positive for 19 virulence-associated genes, including iutA (25/29, 86.2%), rmpA (27/29, 93.1%), ybtA (27/29, 93.1%), entB (29/29, 100%), fimH (29/29, 100%), and mrkD (29/29, 100%). MLST revealed ST11 for the majority of isolates (26/29, 89,7%). Infection assays demonstrated high mortality in the Galleria mellonella model with the highest LD50 values for three isolates (<105 CFU/mL) demonstrating the degree of hypervirulence of these CR-hvKP isolates, and is discussed relative to previous outbreaks of CR-hvKP.

Whole-genome sequencing and characterization of an antibiotic resistant Neisseria meningitidis B isolate from a military unit in Vietnam

BackgroundInvasive meningococcal disease (IMD) persists in military units in Vietnam despite the availability of antibiotics and vaccines. A hindrance to reducing the incidence of IMD in Vietnam is a lack of molecular data from isolates of the causative agent, Neisseria meningitidis from this country. Here, we characterized key genetic and epidemiological features of an invasive N. meningitidis isolate from a military unit in Vietnam using whole-genome sequencing.MethodsNeisseria meningitidis was isolated from a conscript admitted for meningitis and tested against seven antibiotics. DNA from the isolate was extracted and sequenced using the Illumina HiSeq platform. Denovo assembly and scaffolding were performed to construct a draft genome assembly, from which genes were predicted and functionally annotated. Genome analysis included epidemiological characterization, genomic composition and identification of antibiotic resistance genes.ResultsSusceptibility testing of the isolate showed high levels of resistance to chloramphenicol and diminished susceptibility to ampicillin and rifampicin. A draft genome of ~ 2.1 Mb was assembled, containing 2451 protein coding sequences, 49 tRNAs and 3 rRNAs. Fifteen coding sequences sharing ≥ 84% identity with known antibiotic resistance genes were identified. Genome analysis revealed abundant repetitive DNAs and two prophages. Epidemiological typing revealed newly described sequence type, antigenic finetype and Bexsero® Antigen Sequence Typing (BAST). The BAST profile showed no coverage by either Bexsero® or Trumenba®.ConclusionsOur results present the first genome assembly of an invasive N. meningitidis isolate from a military unit in Vietnam. This study illustrates the usefulness of whole genome sequencing (WGS) analysis for epidemiological and antibiotic resistance studies and surveillance of IMD in Vietnam.

Determination of antibiotic resistance patterns of Vibrio parahaemolyticus from shrimp and shellfish in Selangor, Malaysia

High consumer demand for seafood has led to the need for large-scale, reliable supply through aquaculture farming. However, bacterial infections - which can spread rapidly among the dense farming area pose a major threat to this industry. The farmers therefore often resort to extensive use of antibiotics, both prophylactically and therapeutically, in order to protect their stocks. The extensive use of antibiotics in aquaculture has been postulated to represent a major contributing factor in the rising incidence of antimicrobial resistant pathogenic bacteria in seafood; which may then lead to the spread of antimicrobial resistant bacteria in the environment as well as posing a significant threat to human health. This study aimed to characterize antibiotic resistance of Vibrio parahaemolyticus from shrimp and shellfish in Selangor, Malaysia. The antibiotic susceptibility of 385 V. parahaemolyticus isolates was investigated against 14 antibiotics followed by plasmid profiling and plasmid curing to determine the antibiotic mediation. A large number of isolates showed resistance to ampicillin (85%), amikacin (66.8%), and kanamycin (50.1%). A notable resistance pattern was also observed to the third generation cephalosporins (cefotaxime 55.8% and ceftazidime 34%). Only 338 V. parahaemolyticus isolates had 1-7 different plasmids and could be categorized into 27 patterns based on the number and pattern of plasmid present. Interestingly, there was no correlation between the number of plasmids and antibiotic resistant patterns seen in the isolates. The antibiotic resistance was mediated by both chromosomal and plasmid mediation among the resistant isolates. In summary, our results demonstrate that incidence of pathogenic V. parahaemolyticus in seafood in Selangor remains in relatively assuring levels, however the identification of antibiotic resistance among the isolates does rises a public health concern and warrants for continuous surveillance.

Antibiotic usage, residues and resistance genes from food animals to human and environment: An Indian scenario

Antibiotics are majorly used in food animals for growth promotion and prophylactic purposes in public health and environment. The aim of this review is mainly to discuss about the antibiotics usage in poultry, livestock and aquaculture sectors, particularly in India, and the identification of antibiotic resistance in animals, their corresponding antibiotic resistance genes (ARGs) (if investigated) and their dissemination among environmental compartments in various parts of the country. It also discusses about the classification and mechanism of action of different antibiotics. It reports the risks, benefits, ARGs development mechanisms from food animals to humans and to the environment. Most of the current studies are done in the medical field on regulating/restricting antibiotic usage and tracking the propagation of ARGs in bacterial samples of sick patients and also report the identification of antibiotics and ARGs in wastewater treatment plant effluents across various countries. This study mainly reviews the evolution and transportation of ARGs in detail for Indian scenario.

Detection of Pathogens and Ampicillin-resistance Genes Using Multiplex Padlock Probes.

Diagnostic assays for pathogen identification and characterization are limited either by the number of simultaneously detectable targets, which rely on multiplexing methods, or by time constraints due to cultivation-based techniques. We recently presented a 100-plex method for human pathogen characterization to identify 75 bacterial and fungal species as well as 33 clinically relevant β-lactamases ( Barišić et al., 2016 ). By using 16S rRNA gene sequences as barcode elements in the padlock probes, and two different fluorescence channels for species and antibiotic resistance identification, we managed to cut the number of microarray probes needed by half. Consequently, we present here the protocol of an assay with a runtime of approx. 8 h and a detection limit of 105 cfu ml-1. A total of 89% of β-lactamases and 93.7% of species were identified correctly.

MOLECULAR DETECTION OF ANTIBIOTIC-RESISTANCE DETERMINANTS IN ESCHERICHIA COLI ISOLATED FROM THE ENDANGERED AUSTRALIAN SEA LION (NEOPHOCA CINEREA).

Greater interaction between humans and wildlife populations poses significant risks of anthropogenic impact to natural ecosystems, especially in the marine environment. Understanding the spread of microorganisms at the marine interface is therefore important if we are to mitigate adverse effects on marine wildlife. We investigated the establishment of Escherichia coli in the endangered Australian sea lion (Neophoca cinerea) by comparing fecal isolation from wild and captive sea lion populations. Fecal samples were collected from wild colonies March 2009-September 2010 and from captive individuals March 2011-May 2013. Using molecular screening, we assigned a phylotype to E. coli isolates and determined the presence of integrons, mobile genetic elements that capture gene cassettes conferring resistance to antimicrobial agents common in fecal coliforms. Group B2 was the most abundant phylotype in all E. coli isolates (n = 37), with groups A, B1, and D also identified. Integrons were not observed in E. coli (n = 21) isolated from wild sea lions, but were identified in E. coli from captive animals (n = 16), from which class I integrases were detected in eight isolates. Sequencing of gene cassette arrays identified genes conferring resistance to streptomycin-spectinomycin (aadA1) and trimethoprim (dfrA17, dfrB4). Class II integrases were not detected in the E. coli isolates. The frequent detection in captive sea lions of E. coli with resistance genes commonly identified in human clinical cases suggests that conditions experienced in captivity may contribute to establishment. Identification of antibiotic resistance in the microbiota of Australian sea lions provides crucial information for disease management. Our data will inform conservation management strategies and provide a mechanism to monitor microorganism dissemination to sensitive pinniped populations.

Distribution and antibiotic resistance of bacteria isolated from cerebral spinal fluid in postoperative patients with traumatic brain injury: a surveillance

Objective To monitor epidemiological distribution and antibiotic resistance of bacteria isolated from cerebral spinal fluid in neurosurgically treated patients. Methods Bacteria isolated from cerebral spinal fluid specimens and antibiotic resistance identification results of patients admitted into our department from January 2003 to December 2007 were collected to analyze distribution and antibiotic resistance of the pathogens. Results Of 437 isolates, Gram-positive bacilli and Gram-negative bacilli accounted for 73.5% (321 isolates) and 26.5% ( 116 isolates), respectively. The first five most fre-quently isolated pathogens were staphylococcus epidermidis (55.6%), staphylococcus aurens (15. 3% ), enterobacter (6.6%), aeinetobacter (5.3%) and pseudomonas aeruginosa (3.0%). The anti-bacterials with highest susceptibility to Gram-negative bacilli were imipenem ( 83.9% ), amikacin ( 68. 8% ), ciprofloxacin and tobramycin (67.4%), cefepime (61.3%) and ceftazidime (69.2%). The other antibacterials had susceptibility of less than 60%. Conclusions The prevailing pathogens in post-operative intracranial infection are Gram-pnsitive bacilli, especially staphylococcus epidermidis and staphylococcus anreu. Data collected in present study may provide valuable information for prophylactic and empirical antibiotic use in post-operative intracranial infection. Key words: Brain injuries; Cerebrospinal fluid; Antibiotics; Infection

Genotypic detection of antibiotic resistance in Escherichia coli.: a classroom exercise

Bacterial antibiotic resistance remains a problem of clinical importance. Current microbiological methods fordetermining antibiotic resistance are based on culturing bacteria, and may require up to 48 hours to complete. Molecular methods are increasingly being developed to speed the identification of antibiotic resistance and to determine its mechanism. This paper describes a fast and robust method of determining whether and how a particular strain of E.coliis resistant to the antibiotic ampicillin, using the Polymerase Chain Reaction. This exercise is designed to help students learn about modern methods for determining antibiotic resistance.

A high-throughput genetic system for assessing the inhibition of proteins: identification of antibiotic resistance and virulence targets and their cognate inhibitors in Salmonella

This study describes the development of a high-throughput genetic system for producing oligopeptides that can be used to identify molecular interactions leading to inhibition of specific proteins. Using a pathogenic bacteria model, we screened a library of clones expressing intracellular oligopeptides in order to identify inhibitors of proteins involved in antibiotic resistance and virulence. This method involved transforming the pathogen with an oligopeptide-encoding plasmid library, constructed using polymerase chain reaction and an oligonucleotide template designed to produce random oligopeptides composed of 2–16 amino acids, and high-throughput screening for phenotype alterations in the pathogen. A subsequent complementation phase enabled the identification of the full-length bacterial protein inhibited by the oligopeptide. Using this method we were able to identify oligopeptides that inhibit virulence and/or drug resistance in Salmonella, Shigella, and Escherichia coli; specific virulence and/or drug resistance proteins of Salmonella, Shigella, and E. coli that are sensitive to inhibition; and putative oligopeptide-binding sites on the inhibited proteins. This system is versatile and can be extended to other pathogens for analogous studies and it can be modified for used in eukaryotic models for identifying protein interactions that can be targeted for inhibition. Additionally, this system can be used for identifying protein domains involved in any biomolecular interaction.