12 results on '"Eshaw Vidyaprakash"'
Search Results
2. Evaluation of whole and core genome multilocus sequence typing allele schemes for Salmonella enterica outbreak detection in a national surveillance network, PulseNet USA
- Author
-
Molly M. Leeper, Beth M. Tolar, Taylor Griswold, Eshaw Vidyaprakash, Kelley B. Hise, Grant M. Williams, Sung B. Im, Jessica C. Chen, Hannes Pouseele, and Heather A. Carleton
- Subjects
Salmonella ,cgMLST ,wgMLST ,hqSNP ,surveillance ,epidemiology ,Microbiology ,QR1-502 - Abstract
Salmonella enterica is a leading cause of bacterial foodborne and zoonotic illnesses in the United States. For this study, we applied four different whole genome sequencing (WGS)-based subtyping methods: high quality single-nucleotide polymorphism (hqSNP) analysis, whole genome multilocus sequence typing using either all loci [wgMLST (all loci)] and only chromosome-associated loci [wgMLST (chrom)], and core genome multilocus sequence typing (cgMLST) to a dataset of isolate sequences from 9 well-characterized Salmonella outbreaks. For each outbreak, we evaluated the genomic and epidemiologic concordance between hqSNP and allele-based methods. We first compared pairwise genomic differences using all four methods. We observed discrepancies in allele difference ranges when using wgMLST (all loci), likely caused by inflated genetic variation due to loci found on plasmids and/or other mobile genetic elements in the accessory genome. Therefore, we excluded wgMLST (all loci) results from any further comparisons in the study. Then, we created linear regression models and phylogenetic tanglegrams using the remaining three methods. K-means analysis using the silhouette method was applied to compare the ability of the three methods to partition outbreak and sporadic isolate sequences. Our results showed that pairwise hqSNP differences had high concordance with cgMLST and wgMLST (chrom) allele differences. The slopes of the regressions for hqSNP vs. allele pairwise differences were 0.58 (cgMLST) and 0.74 [wgMLST (chrom)], and the slope of the regression was 0.77 for cgMLST vs. wgMLST (chrom) pairwise differences. Tanglegrams showed high clustering concordance between methods using two statistical measures, the Baker’s gamma index (BGI) and cophenetic correlation coefficient (CCC), where 9/9 (100%) of outbreaks yielded BGI values ≥ 0.60 and CCCs were ≥ 0.97 across all nine outbreaks and all three methods. K-means analysis showed separation of outbreak and sporadic isolate groups with average silhouette widths ≥ 0.87 for outbreak groups and ≥ 0.16 for sporadic groups. This study demonstrates that Salmonella isolates clustered in concordance with epidemiologic data using three WGS-based subtyping methods and supports using cgMLST as the primary method for national surveillance of Salmonella outbreak clusters.
- Published
- 2023
- Full Text
- View/download PDF
3. Benchmark datasets for SARS-CoV-2 surveillance bioinformatics
- Author
-
Lingzi Xiaoli, Jill V. Hagey, Daniel J. Park, Christopher A. Gulvik, Erin L. Young, Nabil-Fareed Alikhan, Adrian Lawsin, Norman Hassell, Kristen Knipe, Kelly F. Oakeson, Adam C. Retchless, Migun Shakya, Chien-Chi Lo, Patrick Chain, Andrew J. Page, Benjamin J. Metcalf, Michelle Su, Jessica Rowell, Eshaw Vidyaprakash, Clinton R. Paden, Andrew D. Huang, Dawn Roellig, Ketan Patel, Kathryn Winglee, Michael R. Weigand, and Lee S. Katz
- Subjects
Standardization ,sha256 ,Benchmarking ,WGS ,COVID-19 ,Medicine ,Biology (General) ,QH301-705.5 - Abstract
Background Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the cause of coronavirus disease 2019 (COVID-19), has spread globally and is being surveilled with an international genome sequencing effort. Surveillance consists of sample acquisition, library preparation, and whole genome sequencing. This has necessitated a classification scheme detailing Variants of Concern (VOC) and Variants of Interest (VOI), and the rapid expansion of bioinformatics tools for sequence analysis. These bioinformatic tools are means for major actionable results: maintaining quality assurance and checks, defining population structure, performing genomic epidemiology, and inferring lineage to allow reliable and actionable identification and classification. Additionally, the pandemic has required public health laboratories to reach high throughput proficiency in sequencing library preparation and downstream data analysis rapidly. However, both processes can be limited by a lack of a standardized sequence dataset. Methods We identified six SARS-CoV-2 sequence datasets from recent publications, public databases and internal resources. In addition, we created a method to mine public databases to identify representative genomes for these datasets. Using this novel method, we identified several genomes as either VOI/VOC representatives or non-VOI/VOC representatives. To describe each dataset, we utilized a previously published datasets format, which describes accession information and whole dataset information. Additionally, a script from the same publication has been enhanced to download and verify all data from this study. Results The benchmark datasets focus on the two most widely used sequencing platforms: long read sequencing data from the Oxford Nanopore Technologies platform and short read sequencing data from the Illumina platform. There are six datasets: three were derived from recent publications; two were derived from data mining public databases to answer common questions not covered by published datasets; one unique dataset representing common sequence failures was obtained by rigorously scrutinizing data that did not pass quality checks. The dataset summary table, data mining script and quality control (QC) values for all sequence data are publicly available on GitHub: https://github.com/CDCgov/datasets-sars-cov-2. Discussion The datasets presented here were generated to help public health laboratories build sequencing and bioinformatics capacity, benchmark different workflows and pipelines, and calibrate QC thresholds to ensure sequencing quality. Together, improvements in these areas support accurate and timely outbreak investigation and surveillance, providing actionable data for pandemic management. Furthermore, these publicly available and standardized benchmark data will facilitate the development and adjudication of new pipelines.
- Published
- 2022
- Full Text
- View/download PDF
4. Agritourism and Kidding Season: A Large Outbreak of Human Shiga Toxin-Producing Escherichia coli O157 (STEC O157) Infections Linked to a Goat Dairy Farm—Connecticut, 2016
- Author
-
Megin C. Nichols, Paul Gacek, Quyen Phan, Kelly J. Gambino-Shirley, Lauren M. Gollarza, Morgan N. Schroeder, Alexandra Mercante, Jocelyn Mullins, Anna Blackstock, Mark E. Laughlin, Samantha M. Olson, Eugene Pizzo, Tu Ngoc Nguyen, Laurn Mank, Kimberly Holmes-Talbot, Alycia McNutt, Diane Noel, Anthony Muyombwe, Jafar H. Razeq, Mary Jane Lis, Bruce Sherman, Wayne Kasacek, Laura Whitlock, Nancy Strockbine, Haley Martin, Eshaw Vidyaprakash, Patrick McCormack, and Matthew Cartter
- Subjects
E. coli–Escherichia coli ,goat ,outbreak ,agritourism ,diarrhea ,Shiga toxin (Stx) producing Escherichia coli (STEC) ,Veterinary medicine ,SF600-1100 - Abstract
The objective of this study was to determine sources of Shiga toxin-producing Escherichia coli O157 (STEC O157) infection among visitors to Farm X and develop public health recommendations. A case-control study was conducted. Case-patients were defined as the first ill child (aged
- Published
- 2021
- Full Text
- View/download PDF
5. Evaluation of core genome and whole genome multilocus sequence typing schemes for Campylobacter jejuni and Campylobacter coli outbreak detection in the USA
- Author
-
Lavin A. Joseph, Taylor Griswold, Eshaw Vidyaprakash, Sung B. Im, Grant M. Williams, Hannes A. Pouseele, Kelley B. Hise, and Heather A. Carleton
- Subjects
General Medicine - Abstract
Campylobacter is a leading causing of bacterial foodborne and zoonotic illnesses in the USA. Pulsed-field gene electrophoresis (PFGE) and 7-gene multilocus sequence typing (MLST) have been historically used to differentiate sporadic from outbreak Campylobacter isolates. Whole genome sequencing (WGS) has been shown to provide superior resolution and concordance with epidemiological data when compared with PFGE and 7-gene MLST during outbreak investigations. In this study, we evaluated epidemiological concordance for high-quality SNP (hqSNP), core genome (cg)MLST and whole genome (wg)MLST to cluster or differentiate outbreak-associated and sporadic Campylobacter jejuni and Campylobacter coli isolates. Phylogenetic hqSNP, cgMLST and wgMLST analyses were also compared using Baker’s gamma index (BGI) and cophenetic correlation coefficients. Pairwise distances comparing all three analysis methods were compared using linear regression models. Our results showed that 68/73 sporadic C. jejuni and C. coli isolates were differentiated from outbreak-associated isolates using all three methods. There was a high correlation between cgMLST and wgMLST analyses of the isolates; the BGI, cophenetic correlation coefficient, linear regression model R 2 and Pearson correlation coefficients were >0.90. The correlation was sometimes lower comparing hqSNP analysis to the MLST-based methods; the linear regression model R 2 and Pearson correlation coefficients were between 0.60 and 0.86, and the BGI and cophenetic correlation coefficient were between 0.63 and 0.86 for some outbreak isolates. We demonstrated that C. jejuni and C. coli isolates clustered in concordance with epidemiological data using WGS-based analysis methods. Discrepancies between allele and SNP-based approaches may reflect the differences between how genomic variation (SNPs and indels) are captured between the two methods. Since cgMLST examines allele differences in genes that are common in most isolates being compared, it is well suited to surveillance: searching large genomic databases for similar isolates is easily and efficiently done using allelic profiles. On the other hand, use of an hqSNP approach is much more computer intensive and not scalable to large sets of genomes. If further resolution between potential outbreak isolates is needed, wgMLST or hqSNP analysis can be used.
- Published
- 2023
6. SneakerNet: A modular quality assurance and quality check workflow for primary genomic and metagenomic read data.
- Author
-
Taylor Griswold, Curtis Kapsak, Jessica C. Chen, Henk C. den Bakker, Grant Williams, Alyssa Kelley, Eshaw Vidyaprakash, and Lee S. Katz
- Published
- 2021
- Full Text
- View/download PDF
7. Multistate outbreak of Salmonella Mbandaka infections linked to sweetened puffed wheat cereal – United States, 2018
- Author
-
Amelia A. Keaton, Colin A. Schwensohn, Joshua M. Brandenburg, Evelyn Pereira, Brandon Adcock, Selam Tecle, Rachel Hinnenkamp, Jeff Havens, Kim Bailey, Brad Applegate, Pamela Whitney, Deborah Gibson, Kathy Manion, Michelle Griffin, Joy Ritter, Carrie Biskupiak, Kadri Ajileye, Mugdha Golwalkar, Michael Gosciminski, Brendalee Viveiros, Genevieve Caron, Laine McCullough, Lori Smith, Eshaw Vidyaprakash, Matthew Doyle, Cerise Hardy, Elisa L. Elliot, and Laura B. Gieraltowski
- Subjects
Infectious Diseases ,Epidemiology - Abstract
In May of 2018, PulseNet, the national molecular subtyping network for enteric pathogens, detected a multistate cluster of illnesses caused by an uncommon molecular subtype of Salmonella serovar Mbandaka. A case was defined as an illness in a person infected with the outbreak strain of Salmonella Mbandaka with illness onset on or after 3 March 2018 and before 1 September 2018. One-hundred thirty-six cases from 36 states were identified; 35 hospitalisations and no deaths were reported. Ill people ranged in age from Salmonella Mbandaka that was closely genetically related to other isolates in the outbreak. This investigation highlights the ability of Salmonella to survive in low-moisture environments, and the potential for prolonged outbreaks linked to products with long shelf lives and large distribution areas.
- Published
- 2022
8. Agritourism and Kidding Season: A Large Outbreak of Human Shiga Toxin-Producing Escherichia coli O157 (STEC O157) Infections Linked to a Goat Dairy Farm—Connecticut, 2016
- Author
-
Paul Gacek, Anthony Muyombwe, Matthew L. Cartter, Jafar Razeq, Mary Jane Lis, Lauren M. Gollarza, Morgan N Schroeder, Nancy Strockbine, Tu Ngoc Nguyen, Eshaw Vidyaprakash, Bruce Sherman, Mark E. Laughlin, Kelly Gambino-Shirley, Eugene Pizzo, Quyen Phan, Alexandra Mercante, Patrick McCormack, Haley Martin, Anna J. Blackstock, Samantha M. Olson, Alycia McNutt, Jocelyn Mullins, Laura Whitlock, Kimberly Holmes-Talbot, Megin Nichols, Wayne Kasacek, Diane Noel, and Laurn Mank
- Subjects
medicine.medical_specialty ,Veterinary medicine ,E. coli–Escherichia coli ,animal diseases ,diarrhea ,Biology ,Serology ,fluids and secretions ,Hand sanitizer ,children ,SF600-1100 ,medicine ,Feces ,Original Research ,outbreak ,General Veterinary ,Public health ,goat ,Shiga toxin (Stx) producing Escherichia coli (STEC) ,agritourism ,Outbreak ,Diarrhea ,hemolytic uremic syndrome ,Hay ,Veterinary Science ,medicine.symptom ,Barn (unit) - Abstract
The objective of this study was to determine sources of Shiga toxin-producing Escherichia coli O157 (STEC O157) infection among visitors to Farm X and develop public health recommendations. A case-control study was conducted. Case-patients were defined as the first ill child (aged ; of these, 62% (18 of 29) yielded STEC O157 highly related by WGS to patient isolates. STEC O157 environmental contamination and fecal shedding by goats at Farm X was extensive. Farms should provide handwashing stations with soap, running water, and disposable towels. Access to animal areas, including animal pens and enclosures, should be limited for young children who are at risk for severe outcomes from STEC O157 infection. National recommendations should be adopted to reduce disease transmission.
- Published
- 2021
9. A Culture Collection of 50 Neisseria gonorrhoeae Isolates
- Author
-
Hsi Liu, Ellen N. Kersh, S St Cyr, Eshaw Vidyaprakash, Matthew W. Schmerer, and D. C. Pham
- Subjects
0301 basic medicine ,Spectinomycin ,Tetracycline ,business.industry ,030231 tropical medicine ,bacterial infections and mycoses ,Cefpodoxime ,medicine.disease_cause ,Microbiology ,Ciprofloxacin ,Penicillin ,03 medical and health sciences ,030104 developmental biology ,0302 clinical medicine ,Antibiotic resistance ,Culture Collections/Mutant Libraries ,Immunology and Microbiology (miscellaneous) ,Genetics ,medicine ,Neisseria gonorrhoeae ,business ,Molecular Biology ,Cefixime ,medicine.drug - Abstract
A culture collection of 50 Neisseria gonorrhoeae isolates is available from the CDC & FDA Antibiotic Resistance Isolate Bank. Associated data include antibiotic susceptibility information for azithromycin, cefixime, cefpodoxime, ceftriaxone, tetracycline, ciprofloxacin, penicillin, and spectinomycin and linked whole-genome sequences.
- Published
- 2020
10. Genomic Characterization of Neisseria gonorrhoeae Strains from 2016 U.S. Sentinel Surveillance Displaying Reduced Susceptibility to Azithromycin
- Author
-
Matthew W, Schmerer, A Jeanine, Abrams, Sandra, Seby, Jesse C, Thomas, John, Cartee, Sean, Lucking, Eshaw, Vidyaprakash, Cau D, Pham, Samera, Sharpe, Kevin, Pettus, Sancta B, St Cyr, Elizabeth A, Torrone, Ellen N, Kersh, Kim M, Gernert, and Tara, Henning
- Subjects
Locus (genetics) ,Microbial Sensitivity Tests ,Azithromycin ,Biology ,medicine.disease_cause ,Epidemiology and Surveillance ,Microbiology ,Gonorrhea ,03 medical and health sciences ,Antibiotic resistance ,23S ribosomal RNA ,Drug Resistance, Bacterial ,medicine ,Humans ,Pharmacology (medical) ,Alleles ,030304 developmental biology ,Pharmacology ,Molecular Epidemiology ,0303 health sciences ,Phylogenetic tree ,030306 microbiology ,Neisseria gonorrhoeae ,United States ,Anti-Bacterial Agents ,RNA, Ribosomal, 23S ,Infectious Diseases ,Reduced susceptibility ,Genetic Loci ,Sentinel Surveillance ,medicine.drug - Abstract
In 2016, the proportion of Neisseria gonorrhoeae isolates with reduced susceptibility to azithromycin rose to 3.6%. A phylogenetic analysis of 334 N. gonorrhoeae isolates collected in 2016 revealed a single, geographically diverse lineage of isolates with MICs of 2 to 16 μg/ml that carried a mosaic-like mtr locus, whereas the majority of isolates with MICs of ≥16 μg/ml appeared sporadically and carried 23S rRNA mutations.
- Published
- 2020
11. SneakerNet: A modular quality assurance and quality check workflow for primary genomic and metagenomic read data
- Author
-
Curtis Kapsak, Lee S. Katz, Alyssa Kelley, Grant Williams, Eshaw Vidyaprakash, Taylor Griswold, Henk C. den Bakker, and Jessica C. Chen
- Subjects
Computer science ,business.industry ,Modular design ,Python (programming language) ,Prolog ,Workflow ,Metagenomics ,QA/QC ,Perl ,business ,Software engineering ,computer ,Quality assurance ,computer.programming_language - Abstract
Laboratories that run Whole Genome Sequencing (WGS) produce a tremendous amount of data, up to 10 gigabytes for some common instruments. There is a need to standardize the quality assurance and quality control process (QA/QC). Therefore we have created SneakerNet to automate the QA/QC for WGS.
- Published
- 2021
12. Whole-Genome Sequencing of a Large Panel of Contemporary Neisseria gonorrhoeae Clinical Isolates Indicates that a Wild-Type mtrA Gene Is Common: Implications for Inducible Antimicrobial Resistance
- Author
-
Eshaw Vidyaprakash, David L. Trees, William M. Shafer, and A. Jeanine Abrams
- Subjects
0301 basic medicine ,Pharmacology ,Whole genome sequencing ,Genetics ,030106 microbiology ,Wild type ,Biology ,medicine.disease_cause ,Microbiology ,Bacterial protein ,03 medical and health sciences ,030104 developmental biology ,Infectious Diseases ,Antibiotic resistance ,Neisseria gonorrhoeae ,medicine ,Pharmacology (medical) ,Gene - Published
- 2017
Catalog
Discovery Service for Jio Institute Digital Library
For full access to our library's resources, please sign in.