Identification Of Bacterial Pathogens Research Articles

Use of proteomic-based MALDI-TOF mass spectra for identification of bacterial pathogens in aquaculture: a review

Use of proteomic-based MALDI-TOF mass spectra for identification of bacterial pathogens in aquaculture: a review

Bacterial enrichment prior to third-generation metagenomic sequencing improves detection of BRD pathogens and genetic determinants of antimicrobial resistance in feedlot cattle.

Bovine respiratory disease (BRD) is one of the most important animal health problems in the beef industry. While bacterial culture and antimicrobial susceptibility testing have been used for diagnostic testing, the common practice of examining one isolate per species does not fully reflect the bacterial population in the sample. In contrast, a recent study with metagenomic sequencing of nasal swabs from feedlot cattle is promising in terms of bacterial pathogen identification and detection of antimicrobial resistance genes (ARGs). However, the sensitivity of metagenomic sequencing was impeded by the high proportion of host biomass in the nasal swab samples. This pilot study employed a non-selective bacterial enrichment step before nucleic acid extraction to increase the relative proportion of bacterial DNA for sequencing. Non-selective bacterial enrichment increased the proportion of bacteria relative to host sequence data, allowing increased detection of BRD pathogens compared with unenriched samples. This process also allowed for enhanced detection of ARGs with species-level resolution, including detection of ARGs for bacterial species of interest that were not targeted for culture and susceptibility testing. The long-read sequencing approach enabled ARG detection on individual bacterial reads without the need for assembly. Metagenomics following non-selective bacterial enrichment resulted in substantial agreement for four of six comparisons with culture for respiratory bacteria and substantial or better correlation with qPCR. Comparison between isolate susceptibility results and detection of ARGs was best for macrolide ARGs in Mannheimia haemolytica reads but was also substantial for sulfonamide ARGs within M. haemolytica and Pasteurella multocida reads and tetracycline ARGs in Histophilus somni reads. By increasing the proportion of bacterial DNA relative to host DNA through non-selective enrichment, we demonstrated a corresponding increase in the proportion of sequencing data identifying BRD-associated pathogens and ARGs in deep nasopharyngeal swabs from feedlot cattle using long-read metagenomic sequencing. This method shows promise as a detection strategy for BRD pathogens and ARGs and strikes a balance between processing time, input costs, and generation of on-target data. This approach could serve as a valuable tool to inform antimicrobial management for BRD and support antimicrobial stewardship.

Advancing metagenome-assembled genome-based pathogen identification: unraveling the power of long-read assembly algorithms in Oxford Nanopore sequencing.

Oxford Nanopore sequencing is one of the high-throughput sequencing technologies that facilitates the reconstruction of metagenome-assembled genomes (MAGs). This study aimed to assess the potential of long-read assembly algorithms in Oxford Nanopore sequencing to enhance the MAG-based identification of bacterial pathogens using both simulated and mock communities. Simulated communities were generated to mimic those on fresh spinach and in surface water. Long reads were produced using R9.4.1+SQK-LSK109 and R10.4 + SQK-LSK112, with 0.5, 1, and 2 million reads. The simulated bacterial communities included multidrug-resistant Salmonella enterica serotypes Heidelberg, Montevideo, and Typhimurium in the fresh spinach community individually or in combination, as well as multidrug-resistant Pseudomonas aeruginosa in the surface water community. Real data sets of the ZymoBIOMICS HMW DNA Standard were also studied. A bioinformatic pipeline (MAGenie, freely available at https://github.com/jackchen129/MAGenie) that combines metagenome assembly, taxonomic classification, and sequence extraction was developed to reconstruct draft MAGs from metagenome assemblies. Five assemblers were evaluated based on a series of genomic analyses. Overall, Flye outperformed the other assemblers, followed by Shasta, Raven, and Unicycler, while Canu performed least effectively. In some instances, the extracted sequences resulted in draft MAGs and provided the locations and structures of antimicrobial resistance genes and mobile genetic elements. Our study showcases the viability of utilizing the extracted sequences for precise phylogenetic inference, as demonstrated by the consistent alignment of phylogenetic topology between the reference genome and the extracted sequences. R9.4.1+SQK-LSK109 was more effective in most cases than R10.4+SQK-LSK112, and greater sequencing depths generally led to more accurate results.IMPORTANCEBy examining diverse bacterial communities, particularly those housing multiple Salmonella enterica serotypes, this study holds significance in uncovering the potential of long-read assembly algorithms to improve metagenome-assembled genome (MAG)-based pathogen identification through Oxford Nanopore sequencing. Our research demonstrates that long-read assembly stands out as a promising avenue for boosting precision in MAG-based pathogen identification, thus advancing the development of more robust surveillance measures. The findings also support ongoing endeavors to fine-tune a bioinformatic pipeline for accurate pathogen identification within complex metagenomic samples.

Real-time 3D tracking of swimming microbes using digital holographic microscopy and deep learning.

The three-dimensional swimming tracks of motile microorganisms can be used to identify their species, which holds promise for the rapid identification of bacterial pathogens. The tracks also provide detailed information on the cells' responses to external stimuli such as chemical gradients and physical objects. Digital holographic microscopy (DHM) is a well-established, but computationally intensive method for obtaining three-dimensional cell tracks from video microscopy data. We demonstrate that a common neural network (NN) accelerates the analysis of holographic data by an order of magnitude, enabling its use on single-board computers and in real time. We establish a heuristic relationship between the distance of a cell from the focal plane and the size of the bounding box assigned to it by the NN, allowing us to rapidly localise cells in three dimensions as they swim. This technique opens the possibility of providing real-time feedback in experiments, for example by monitoring and adapting the supply of nutrients to a microbial bioreactor in response to changes in the swimming phenotype of microbes, or for rapid identification of bacterial pathogens in drinking water or clinical samples.

IDENTIFICATION OF THE MAIN DISEASES OF WALNUT IN THE SOUTHERN FRUIT-GROWING ZONE OF KAZAKHSTAN

Industrial cultivation of nut crops in the Republic of Kazakhstan is promoted by favourable soil and climate conditions, especially in the southern region, which makes it possible to obtain high yields of this valuable plant in the future. Significant damage to the yield of nut crops is caused by diseases, protection of plantations from which is one of the main measures aimed at increasing their productivity. The most important issue in cultivation of nut crops is its protection from bacterial and fungal pathogens. In Kazakhstan purposeful researches on studying species diversity of diseases and pests of nut crops have not been carried out. The novelty of the conducted research is in the fact that for the first time in Kazakhstan fungal and bacterial diseases of walnut in the conditions of the southern zone of fruit growing on the basis of microbiological and molecular-genetic methods were identified.
 The results of research showed that the majority of isolated pathogens are fungi, as well as several species of bacteria causing diseases of walnut. In total, 4 genera of fungi were isolated: Alternaria, Fusarium as causative agents of fungal diseases; Aspergillus, Penicillium as secondary infestation; also 2 genera of bacteria: Pantoea, Pseudomonas as causative agents of bacterial diseases. Molecular identification of fungal and bacterial pathogens by PCR based on genomic DNA showed that the studied walnut samples were identified as phytopathogenic fungi: Alternaria alternata, Fusarium solani, as well as phytopathogenic bacteria: Pantoea agglomerans, Pseudomonas syringae, Pseudomonas oryzahabitans. The conducted research results will allow to make up a system of protection of walnut from harmful diseases in order to increase the productivity of plantations.

Rapid Detection of Bacterial Pathogens Causing Lower Respiratory Tract Infections via Microfluidic-Chip-Based Loop-Mediated Isothermal Amplification.

Respiratory tract infections (RTIs) are among the most common problems in clinical settings. Rapid and accurate identification of bacterial pathogens will provide practical guidelines for managing and treating RTIs. This study describes a method for rapidly detecting bacterial pathogens that cause respiratory tract infections via multi-channel loop-mediated isothermal amplification (LAMP). LAMP is a sensitive and specific diagnostic tool that rapidly detects bacterial nucleic acids with high accuracy and reliability. The proposed method offers a significant advantage over traditional bacterial culturing methods, which are time-consuming and often require greater sensitivity for detecting low levels of bacterial nucleic acids. This article presents representative results of K. pneumoniae infection and its multiple co-infections using LAMP to detect samples (sputum, bronchial lavage fluid, and alveolar lavage fluid) from the lower respiratory tract. In summary, the multi-channel LAMP method provides a rapid and efficient means of identifying single and multiple bacterial pathogens in clinical samples, which can help prevent the spread of bacterial pathogens and aid in the appropriate treatment of RTIs.

Isolation and identification of bacterial pathogens causing ice-ice disease in Eucheuma cottonii seaweed at Seira Island Waters, Tanimbar Islands District, Maluku, Indonesia

Abstract. Tuhumury NC, Sahetapy JMF, Matakupan J. 2024. Isolation and identification of bacterial pathogens causing ice-ice disease in Eucheuma cottonii seaweed at Seira Island Waters, Tanimbar Islands District, Maluku, Indonesia. Biodiversitas 25: 964-970. Seaweed cultivation has proven to be beneficial and enhances the well-being of communities. Production of seaweed in the waters of Maluku has increased despite facing the problem of ice-ice disease. Therefore, this research aimed to isolate and identify bacteria on the Eucheuma cottonii seaweed species affected by ice-ice disease in the waters of Seira Island, Tanimbar Islands District, Maluku. It was conducted in August 2023 at three observation stations, and water quality samples were collected in situ at all three stations, including temperature, salinity, pH, dissolved oxygen (DO), and turbidity. Furthermore, bacterial isolation and identification were carried out at the Laboratory of Marine Aquaculture, Ambon. Bacteria isolation and purification were performed on TCBS media using the streak plate technique, while identification used the API 20E test. The results showed that water quality parameters supported seaweed growth. Four bacteria that caused ice-ice disease in the waters of Seira were identified as Vibrio alginolyticus, Vibrio fluvalis, Vibrio cholerae, and Aeromonas caviae. Moreover, all four bacteria found were gram-negative and pathogenic. Bacteria belonging to the genera Vibrio and Aeromonas have been proven to cause infections in marine organisms, including seaweed. In conclusion, four types of bacteria were identified in seaweed affected by ice-ice disease.

Pattern of antibiotic resistance in surgical site infections in a tertiary care hospital of Nepal

Background: Surgical site infection (SSI) is the second most common hospital-acquired infection. The identification of bacterial pathogens and their antibiotic susceptibility pattern is required for the successful treatment of SSI and curb antimicrobial resistance, which is a major threat globally. This study aimed to assess the microbial profile of the organisms causing SSI and their antibiogram in a tertiary care hospital. Methods: This cross-sectional study was conducted at Microbiology Laboratory of tertiary care hospital, from March 2023 to August 2023. Swab or aspirate specimens were collected aseptically from the surgical site and processed for bacterial isolation following standard bacteriological techniques. Gram’s staining and biochemical tests were performed to identify the organisms at the species level. Antimicrobial susceptibility tests were done following Kirby–Bauer’s disc diffusion method. Statistical analysis was performed using SPSS software version16.0. Results: Out of 405 samples, 92 (22.7%) yielded bacterial growth. Eighty-three culture positive cases (90.2%) were monomicrobial while nine (15.7%) had mixed growth of at least two different bacteria. Out of 108 isolates, 43 (39.8%) were gram-positive and 65 (60.2%) were gram-negative bacteria. Escherichia coli (39.8%) was the most commonly isolated organism. All gram-negative isolates were resistant to ceftriaxone followed by amoxicillin-clavulanic acid (94.0%), amoxicillin (94.0%), cefixime (90.7%), and cefepime (89.8%). Similarly, none of the gram-positive isolates were susceptible to ampicillin, amoxicillin, and ampicillin/sulbactam. The most effective drugs against E. coli were imipenem (100%), followed by tigecycline (96%), meropenem (95.1%), chloramphenicol (84%), amikacin (81.5%), and gentamicin (81.5%). Overall prevalence of MDR was 59.3%. Conclusion: Our study demonstrates increased resistance of both gram-positive and gram-negative organisms to commonly used drugs like cephalosporins and even quinolones. Continued surveillance of antimicrobial susceptibility results at local level, dissemination of data, and prescribing the antibiotics accordingly based on culture and sensitivity results are necessary to ameliorate antimicrobial resistance.

Risk assessment and pathogen profile of surgical site infections in traumatic brain injury patients undergoing emergency craniotomy: A retrospective study.

Emergency craniotomy in patients with traumatic brain injury poses a significant risk for surgical site infections (SSIs). Understanding the risk factors and pathogenic characteristics of SSIs in this context is crucial for improving outcomes. This comprehensive retrospective analysis spanned from February 2020 to February 2023 at our institution. We included 25 patients with SSIs post-emergency craniotomy and a control group of 50 patients without SSIs. Data on various potential risk factors were collected, including demographic information, preoperative conditions, and intraoperative details. The BACT/ALERT3D Automated Bacterial Culture and Detection System was utilized for rapid bacterial pathogen identification. Statistical analyses included univariate and multivariate logistic regression to identify significant risk factors for SSIs. The study identified Klebsiella pneumoniae, Escherichia coli, and Staphylococcus aureus as the most prevalent pathogens in SSIs. Significant risk factors for SSIs included the lack of preoperative antibiotic use, postoperative drainage tube placement, diabetes mellitus, and the incorporation of invasive procedures, all of which showed a significant association with SSIs in the univariate analysis. The multivariate analysis further highlighted the protective effect of preoperative antibiotics and the increased risks associated with anaemia, diabetes mellitus, postoperative drainage tube placement, and the incorporation of invasive procedures. Our research underscores the critical role of factors like insufficient preoperative antibiotics, postoperative drainage, invasive techniques, anaemia, and diabetes mellitus in elevating the risk of surgical site infections in traumatic brain injury patients undergoing emergency craniotomy. Enhanced focus on these areas is essential for improving surgical outcomes.

Microscopic identification of foodborne bacterial pathogens based on deep learning method

Accurate and rapid detection of foodborne bacterial pathogens is critical for food quality control. Nowadays, tracking morphological bacterial properties using microscope is still a priority at the grass-roots food supervision department due to its simplicity and low cost. However, the method requires highly professional personnel and there are certain misjudgments in the process of analysis. Automatically recognizing foodborne pathogen using deep learning algorithm to replace manual microscopy will not only reduce expert cost, artificial misjudgment, and operation time in detection, but also provide more objective and accurate identification. Here, we firstly constructed a high-quality and large-scale dataset of foodborne pathogenic bacteria, allowing the deep learning-based model to be efficiently trained and achieve accurate identification. The deep convolutional neural network-based model is capable of identifying six common foodborne pathogens, including Escherichia coli (O157:H7), Vibrio parahaemolyticus, Staphylococcus aureus, Bacillus cereus, Salmonella typhi, and Streptococcus hemolyticus, with accuracy rates of 90%–100%. This method can assist or replace the manual microscopic inspection step in traditional detection methods, and is promising to break through the traditional approach that heavily relies on manual judgment, greatly reduce the cost of experts and human errors, and provide rapid, accurate, and powerful discriminatory results in large quantities for detection.

Unravelling the genomic secrets of bacterial fish pathogens: a roadmap to aquaculture sustainability.

In the field of aquaculture, bacterial pathogens pose significant challenges to fish health and production. Advancements in genomic technologies have revolutionized our understanding of bacterial fish pathogens and their interactions with their host species. This review explores the application of genomic approaches in the identification, classification, and characterization of bacterial fish pathogens. Through an extensive analysis of the literature, we have compiled valuable data on 79 bacterial fish pathogens spanning 13 different phyla, encompassing their whole genome sequences. By leveraging high-throughput sequencing techniques, researchers have gained valuable insights into the genomic makeup of these pathogens, enabling a deeper understanding of their virulence factors and mechanisms of host interaction. Furthermore, genomic approaches have facilitated the discovery of potential vaccine and drug targets, opening up new avenues for the development of effective interventions against fish pathogens. Additionally, the utilization of genomics in fish disease resistance and control in aquaculture has shown promising results, enabling the identification of genetic markers associated with disease resistance traits. This review highlights the significant contributions of genomics to the field of fish pathogen research and underscores its potential for improving disease management strategies and enhancing the sustainability of aquaculture practices.

Serovar-level identification of bacterial foodborne pathogens from full-length 16S rRNA gene sequencing.

The resolution of variation within species is critical for interpreting and acting on many microbial measurements. In the key foodborne pathogens Salmonella and Escherichia coli, the primary subspecies classification scheme used is serotyping: differentiating variants within these species by surface antigen profiles. Serotype prediction from whole-genome sequencing (WGS) of isolates is now seen as comparable or preferable to traditional laboratory methods where WGS is available. However, laboratory and WGS methods depend on an isolation step that is time-consuming and incompletely represents the sample when multiple strains are present. Community sequencing approaches that skip the isolation step are, therefore, of interest for pathogen surveillance. Here, we evaluated the viability of amplicon sequencing of the full-length 16S rRNA gene for serotyping Salmonella enterica and E. coli. We developed a novel algorithm for serotype prediction, implemented as an R package (Seroplacer), which takes as input full-length 16S rRNA gene sequences and outputs serovar predictions after phylogenetic placement into a reference phylogeny. We achieved over 89% accuracy in predicting Salmonella serotypes on in silico test data and identified key pathogenic serovars of Salmonella and E. coli in isolate and environmental test samples. Although serotype prediction from 16S rRNA gene sequences is not as accurate as serotype prediction from WGS of isolates, the potential to identify dangerous serovars directly from amplicon sequencing of environmental samples is intriguing for pathogen surveillance. The capabilities developed here are also broadly relevant to other applications where intraspecies variation and direct sequencing from environmental samples could be valuable.IMPORTANCEIn order to prevent and stop outbreaks of foodborne pathogens, it is important that we can detect when pathogenic bacteria are present in a food or food-associated site and identify connections between specific pathogenic bacteria present in different samples. In this work, we develop a new computational technology that allows the important foodborne pathogens Escherichia coli and Salmonella enterica to be serotyped (a subspecies level classification) from sequencing of a single-marker gene, and the 16S rRNA gene often used to surveil bacterial communities. Our results suggest current limitations to serotyping from 16S rRNA gene sequencing alone but set the stage for further progress that we consider likely given the rapid advance in the long-read sequencing technologies and genomic databases our work leverages. If this research direction succeeds, it could enable better detection of foodborne pathogens before they reach the public and speed the resolution of foodborne pathogen outbreaks.

Recovering high-quality bacterial genomes from cross-contaminated cultures: a case study of marine Vibrio campbellii

BackgroundEnvironmental monitoring of bacterial pathogens is critical for disease control in coastal marine ecosystems to maintain animal welfare and ecosystem function and to prevent significant economic losses. This requires accurate taxonomic identification of environmental bacterial pathogens, which often cannot be achieved by commonly used genetic markers (e.g., 16S rRNA gene), and an understanding of their pathogenic potential based on the information encoded in their genomes. The decreasing costs of whole genome sequencing (WGS), combined with newly developed bioinformatics tools, now make it possible to unravel the full potential of environmental pathogens, beyond traditional microbiological approaches. However, obtaining a high-quality bacterial genome, requires initial cultivation in an axenic culture, which is a bottleneck in environmental microbiology due to cross-contamination in the laboratory or isolation of non-axenic strains.ResultsWe applied WGS to determine the pathogenic potential of two Vibrio isolates from coastal seawater. During the analysis, we identified cross-contamination of one of the isolates and decided to use this dataset to evaluate the possibility of bioinformatic contaminant removal and recovery of bacterial genomes from a contaminated culture. Despite the contamination, using an appropriate bioinformatics workflow, we were able to obtain high quality and highly identical genomes (Average Nucleotide Identity value 99.98%) of one of the Vibrio isolates from both the axenic and the contaminated culture. Using the assembled genome, we were able to determine that this isolate belongs to a sub-lineage of Vibrio campbellii associated with several diseases in marine organisms. We also found that the genome of the isolate contains a novel Vibrio plasmid associated with bacterial defense mechanisms and horizontal gene transfer, which may offer a competitive advantage to this putative pathogen.ConclusionsOur study shows that, using state-of-the-art bioinformatics tools and a sufficient sequencing effort, it is possible to obtain high quality genomes of the bacteria of interest and perform in-depth genomic analyses even in the case of a contaminated culture. With the new isolate and its complete genome, we are providing new insights into the genomic characteristics and functional potential of this sub-lineage of V. campbellii. The approach described here also highlights the possibility of recovering complete bacterial genomes in the case of non-axenic cultures or obligatory co-cultures.

Identification of Diverse Multiple Drugs Resistant Bacterial Pathogens using Microscan Panel

Bacterial isolates from clinical sources have increased resistance to antimicrobial agents available and routinely used in developing countries like Ethiopia. One of the control measures of antimicrobial resistance is to know the susceptibility of pathogenic bacteria from clinical specimens and treat patients accordingly. Therefore the objective of the present study is to isolate bacterial pathogens from different clinical specimens and determine their antimicrobial susceptibility patterns. Clinical samples (urine, blood, pus and discharges from different body sites were cultured and isolation of bacterial pathogens were done following standard bacteriological methods using media recommended by Cheesbrough. Identification of bacterial pathogens and antimicrobial susceptibility tests were done using Micro Scan Identification Panel method. The Panels were read by Micro Scan Auto Scan 4 reader after incubating for 18 to 24 hours at 35o c aerobically. The retrospective data of microbiological culture and antimicrobial susceptibility test results were analysed. A total of 995 clinical specimens were cultured at Bethzatha Bacteriology Lab., Bethzatha Hospital, from May 2021 to February 2022. The most frequent specimens were, urine 87 (32%), blood 77(28%), pus and discharges from different body sites 65(24%). Out of these, 273(27%) yielded different bacterial pathogens. The most dominant gram negative bacterial isolates from urine samples 43/87(49%), 6/87(7%), 7/87(8%) were E. coli, Acinetobacter and Klebsiella spp, respectively in that order. Klebsiella pneumoniae 12/77 (16%) were most frequently isolated from blood culture followed by diverse coagulase negative Staphylococci (CoNS) 26/77 (33.7%) and S. aureus 15/77(19.5%). The most frequent 20/65(31%) isolates from pus and discharges were S. aureus followed by 12/65(18.5%) CoNS. In the present study, most bacterial isolates from different clinical samples were multiply resistant to ampicillin, amoxicillin, trimethoprim sulphametoaxzole, levofloxacillin and ampicillin-sulbactam. On the other hand the most frequent Gram negative bacteria, E.coli and Klebsiella pneumonia were most susceptible to amikacin and ertapenem, and the gram positive isolates, S. aureus were most susceptible to levofloxacillin and gentamicin; whereas coagulase negative staphylococci (CoNS) were most susceptible to gentamicin, tecioplanin, rifampicin, vancomycin, daptomycin. Therefore clinicians should be guided by antimicrobial susceptibility test. In the absence of antimicrobial susceptibility test we suggest that the above mentioned drugs to be most appropriate for empirical treatment in the study hospitals and health settings in Addis Ababa. Furthermore critical measures need to be taken to curb the increasing spread of AMR bacteria.

Determination of Raman spectrum under different culture conditions: preliminary research on bacterial fish pathogens

The intensive labour and time required for conventional methods to identify bacterial fish pathogens have revealed the need to develop alternative methods. Raman spectroscopy has been used in the rapid optical identification of bacterial pathogens in recent years as an alternative method in microbiology. Strains of bacterial fish pathogens (Vibrio anguillarum, Lactococcus garvieae and Yersinia ruckeri) that often cause infectious diseases in fish were here identified and analyzed in terms of their biochemical structures in different media and at different incubation times, and the data were specified by using Raman spectroscopy. The results demonstrated that Raman spectroscopy presents species-specific Raman spectra of each disease-causing bacteria and that it would be more appropriate to choose general microbiological media over selective media for routine studies. Additionally, it was found that species-specific band regions did not differ in 24- and 48-hour cultures, but there could be a difference in peak intensity which may lead to difficult characterization of spectrum. The current study, conducted for the first time with bacterial fish pathogens under different incubation conditions, is believed to provide a basis for the routine use of Raman spectroscopy for quick pathogen identification and the precise determination of the methodology for further research.

Molecular identification of bacterial pathogen in suspected cases of respiratory tract infection from chicken

Molecular identification of bacterial pathogen in suspected cases of respiratory tract infection from chicken

Carbapenem Resistant Pseudomonas aeruginosa, Enterobacteriaceae, and Acinetobacter baumannii , Prevalence, Biochemical Identification and Clinical Characteristics in Karachi, Pakistan

Antibiotic resistant pathogens are affecting the community and healthcare institutions all over the world. Pakistan is a developing country and resistance to drugs is the main issue and is of great importance. Current study is focused on isolation and identification of bacterial pathogens, i.e. member of Enterobacteriaceae, Pseudomonas aeruginosa and Acinetobacter baumannii for the evaluation of prevalence, distribution of sensitivity and antibiogram of different antibiotics and carbapenem resistance isolates with phenotypic detection of resistant gene. Total 200 samples of different sources were collected and tested for bacterial pathogens. Out of 200 samples, 83 (41.5%) were found positive for different bacterial pathogens while 117 (58.5%) were negative. Among these 83 positive samples, Urine 43 (51.8%), Pus 22 (26.5%), Blood 8 (9.8%), Tissue 3 (3.6%), wound swab 2 (2.4%), Sputum 3 (3.6%) and HVS 2 (2.4%). E. coli 37 (44.6%), Klebsiella species 23 (27.7%), Proteus vulgaris 8 (9.6%), Ps. aeruginosa 4 (4.8%), Acinetobacter baumannii 4 (4.8%), C. freundii 2 (2.4%), S. typhi 2 (2.4%), P. mirabilis 1 (1.2%), M. morganii 1 (1.2%) and member of Enterobacteriaceae 1 (1.2%) were identified. Out of 83 (41.5%) positive samples there are 17 samples which showed resistance against Imipenem (IPM) and were further processed by phenotypic method Modified Hodge Test MHT. After Modified Hoge Test (MHT) among all these 17 samples there were only 07 (39%) positive and the remaining 11 (61%) were negative, its mean there was no gene involve in 11 samples.

Topical issues of antibiotic resistance: modern methods of identification of bacterial pathogens and determination of their qualities

One of the most urgent problems in medicine today is the problem of antibiotic resistance. Why this problem? After all, scientists around the world proclaimed victory over microorganisms in the 50-60s of the last century? And since the 70s already began to appear information about resistant strains. Everything turned out to be not so simple. Due to uncontrolled and irrational use of antibiotics, mankind is rapidly approaching the so-called "post-antibiotic era". How to stop this "approach"? It is necessary to clearly follow the principles of rational antibiotic therapy.
 Rational antibiotic therapy requires identifying the bacterial nature of the disease, determining the sensitivity of the microorganisms to the antibiotic and starting treatment as soon as possible. To comply with these principles, rapid and accurate methods of identification of microorganisms are necessary, because it is on the basis of these methods that the most effective antimicrobial agent is selected.
 There are standard methods of identification, which include the disk-diffusion method and the serial dilution method. The main disadvantage of these methods is the length of time it takes to obtain results.
 So what are the alternative methods available? There are many methods of microbial identification, but not all of them are suitable for widespread use due to the high cost, the need for expensive equipment.
 Of all the current methods, three methods are emphasized in this review: 16S rRNA gene sequencing, MALDI-TOF MS and EUCAST RAST. Sequencing of the 16S rRNA gene is based on decoding the region of the gene, which in bacteria carries information on resistance mechanisms and structure features. MALDI-TOF MS is a desorption method of "soft" ionization caused by exposure of the matrix with the analyzed substance to pulses of laser radiation. The EUCAST RAST method is an accelerated disk-diffusion method.
 This review describes the problem of antibiotic resistance, mechanisms of bacterial resistance, as well as modern and standard methods of bacterial identification and antibiotic sensitivity.
 The aim of this review was to compare routine methods of identification of species and qualitative properties of microorganisms, causative agents of nosocomial infections, with modern technologies of microbiological testing as an important step in solving the problem of priority selection of effective antimicrobial agents.
 So, the main question of this review is: can modern methods displace standard methods of microorganism identification?

Bacteriological Profile and Antibiogram of Isolates Causing Bloodstream Infection in Children

Objective: (1) To identify and characterize bacterial isolates causing blood stream infection in children. (2) To determine the antibiotic sensitivity pattern of isolates obtained. Materials And Methods: Study design: Descriptive study. Study population: Blood samples collected from pediatric patients aged upto 12 years who are admitted in Government Medical College Kottayam, with clinical features of blood stream infection. Sampling methodology: The sample size of suspected blood stream infection is 345. All pediatric patients with clinical features suggestive of blood stream infection in the study period satisfying inclusion and exclusion criteria will be included in the study. The identification of bacterial pathogens and antimicrobial susceptibility tests were done by conventional and automated methods like VITEK system. Results: Out of 345 study sample population, 46 were culture positive, of which 21(45.7%) were Gram negative isolates and 20(43.4%) were Gram positive. Major isolates obtained were Klebsiella spp (15%), Methicillin Resistant Coagulase negative Staphylococci (15%), followed by Staphylococcus aureus (13%), Coagulase negative Staphylococci (8%) and Acinetobacter baumannii (8%). Klebsiella pneumoniae was resistant to most of the antibiotics tested except meropenem. All isolates of Coagulase negative Staphylococci and Staphylococcus aureus were susceptible to vancomycin and linezolid. Conclusion: Gram negative organisms were predominant pathogens in blood stream infections. Klebsiella pneumoniae, Coagulase negative Staphylococci, Staphylococcus aureus were the most commonly isolated pathogens. Amikacin along with the third generation cephalosporins should be used for empirical treatment of Gram negative sepsis. Vancomycin and linezolid can be used for Gram positive pathogens.

2072. Clinical Evaluation of the BioFire® Global Fever Special Pathogens Panel

Abstract Background BioFire Defense has developed the BioFire® Global Fever Special Pathogens Panel, in collaboration with the U.S. Department of Defense and NIAID (contract Nos. W911QY-13-D-0080 and HHSN272201600002C), as an in vitro diagnostic test for the simultaneous identification of viral, bacterial, and protozoan pathogens directly from whole blood in under an hour using the BioFire® FilmArray® platform. The BioFire Global Fever Special Pathogens Panel has been cleared by the U.S. FDA for the detection of chikungunya virus, Crimean-Congo hemorrhagic fever virus (CCHFV), dengue virus, (serotypes 1-4), Ebolavirus spp., Lassa virus, Marburg virus, West Nile virus (WNV), yellow fever virus (YFV), Bacillus anthracis, Francisella tularensis, Leptospira spp., Yersinia pestis, Leishmania spp., and Plasmodium spp. from individuals with signs and/or symptoms of acute febrile illness (AFI) and known or suspected exposure to target pathogens. Methods BioFire Defense performed a prospective clinical evaluation for the Global Fever Special Pathogens Panel at eleven geographically distinct sites across the globe. A total of 2139 prospective whole blood specimens were tested between March 2018 and March 2021. Results The Global Fever Special Pathogens Panel detected at least one analyte in 33.9% of specimens (725/2139). The most prevalent analyte was Plasmodium (29.0%, 118/407), followed by dengue virus (36.4%, 266/730). Chikungunya virus, Leptospira spp., Leishmania spp., CCHFV, and WNV were detected in fewer than 5% of specimens. Two or more analytes were detected in 4.3% (31/725) of positive specimens. All other analytes were not detected by the Global Fever Special Pathogens Panel. Positive percent agreement between the Global Fever Special Pathogens Panel and comparator testing ranged between 92.7-100%, and the negative percent agreement ranged between 99.2-100%. Conclusion The results show that the BioFire Global Fever Special Pathogens Panel could aid in rapid and actionable AFI diagnosis caused by multiple, sometimes co-occurring, pathogens. The Global Fever Special Pathogens Panel will be a valuable diagnostic tool to aid in national preparedness for disease outbreaks. Disclosures All Authors: No reported disclosures