Analyze Diet
Data in brief2021; 38; 107402; doi: 10.1016/j.dib.2021.107402

Dataset of single nucleotide polymorphisms and comprehensive proteomic analysis of Streptococcus equi subsp. equi ATCC 39506.

Abstract: subspecies () is an opportunistic pathogen and a major causative agent of equine strangles, a contagious respiratory infection in horses and other equines. In this study, we provide the dataset associated with our research publication "-derived extracellular vesicles as a vaccine candidate against infections" [1]. We describe the genomic differences between 4047 and ATCC 39506 and outline the comprehensive proteome information of various fractions, including the whole cell lysate, membrane proteome, secretory proteome, and extracellular vesicle proteome. In addition, we included a dataset of highly immunoreactive proteins identified through immunoprecipitation. The specifications table provides a detailed summary of the gene annotation and quantitative information obtained for each proteome. The proteomics data were analyzed using shotgun proteomics with LTQ Velos and Q Exactive mass spectrometry in the data-dependent acquisition mode. We have deposited the acquired data, including the mass spectrometry raw files and exported MASCOT search results, in the PRIDE public repository under the accession numbers PXD025152 and PXD025527.
Publication Date: 2021-09-23 PubMed ID: 34621931PubMed Central: PMC8479396DOI: 10.1016/j.dib.2021.107402Google Scholar: Lookup
The Equine Research Bank provides access to a large database of publicly available scientific literature. Inclusion in the Research Bank does not imply endorsement of study methods or findings by Mad Barn.
  • Journal Article

Summary

This research summary has been generated with artificial intelligence and may contain errors and omissions. Refer to the original study to confirm details provided. Submit correction.

This research paper includes comprehensive proteomic and genetic data for Streptococcus equi subsp. equi ATCC 39506, a bacteria causing respiratory tract infections in horses. The paper aims to provide a deep dive into the protein and genetic structure of the bacteria, with a view towards developing effective vaccines.

About the Research

  • This research focuses on Streptococcus equi subsp. equi ATCC 39506 (S. equi ATCC 39506), an opportunistic pathogen that primarily affects horses causing a condition called equine strangles, a highly contagious respiratory infection.
  • The study is related to another research publication where S. equi-derived extracellular vesicles are considered as potential vaccine candidates against these type of bacterial infections.

Genomic and Proteomic Analysis

  • The research quantitatively maps out the genomic variances between two strains of the same species: S. equi 4047 and S. equi ATCC 39506. This comparative genomic analysis can shed insights into the differences in pathogenicity, resistance, and virulence factors among the two.
  • Additionally, the study provides a comprehensive view of the proteome information of different fractions of the bacteria. The researchers have investigated the whole cell lysate, membrane proteome, secretory proteome, and extracellular vesicle proteome of this species.
  • The proteome represents the entire protein content produced by the organism. Understanding the proteome can provide valuable information on the biological processes and molecular mechanisms.

Immunoreactive Proteins and Proteomics Data Analysis

  • The research includes a dataset of highly immunoreactive proteins identified through immunoprecipitation, a technique used to isolate a specific protein from a complex mixture using an antibody. These proteins stimulate an immune response and might be used as vaccine candidates.
  • The proteomics data were analyzed using shotgun proteomics with LTQ Velos and Q Exactive mass spectrometry in the data-dependent acquisition mode. Shotgun proteomics is a method used to study the proteins in a complex mixture. It involves breaking down proteins into peptides, separating them according to their masses, and then sequencing them to identify each protein.

Data Repository

  • The comprehensive data set, including the mass spectrometry raw files and the results of a MASCOT search, has been deposited in the PRIDE public repository, a platform for storing and sharing proteomics data.
  • The data can be accessed with the accession numbers PXD025152 and PXD025527, facilitating further research by other scientists in the field.

Cite This Article

APA
Lee H, Yun SH, Hyon JY, Lee SY, Yi YS, Choi CW, Jun S, Park EC, Kim SI. (2021). Dataset of single nucleotide polymorphisms and comprehensive proteomic analysis of Streptococcus equi subsp. equi ATCC 39506. Data Brief, 38, 107402. https://doi.org/10.1016/j.dib.2021.107402

Publication

ISSN: 2352-3409
NlmUniqueID: 101654995
Country: Netherlands
Language: English
Volume: 38
Pages: 107402
PII: 107402

Researcher Affiliations

Lee, Hayoung
  • Research Center for Bioconvergence Analysis, Korea Basic Science Institute (KBSI), Ochang 28119, Republic of Korea.
  • Center for Convergent Research of Emerging Virus Infection, Korea Research Institute of Chemical Technology (KRICT), Daejeon 34114, Republic of Korea.
  • Department of Bio-Analytical Science, University of Science and Technology, Daejeon 34113, Republic of Korea.
Yun, Sung Ho
  • Center for Research Equipment, Korea Basic Science Institute, Ochang 28119, Republic of Korea.
Hyon, Ju-Yong
  • Research Center for Bioconvergence Analysis, Korea Basic Science Institute (KBSI), Ochang 28119, Republic of Korea.
Lee, Sang-Yeop
  • Research Center for Bioconvergence Analysis, Korea Basic Science Institute (KBSI), Ochang 28119, Republic of Korea.
  • Center for Convergent Research of Emerging Virus Infection, Korea Research Institute of Chemical Technology (KRICT), Daejeon 34114, Republic of Korea.
Yi, Yoon-Sun
  • Center for Research Equipment, Korea Basic Science Institute, Ochang 28119, Republic of Korea.
Choi, Chi-Won
  • KBNP Technology Institute, KBNP, INC., Heungan-daero 415, Dongan-Gu, Anyang, Gyeonggi, Republic of Korea.
Jun, Sangmi
  • Center for Research Equipment, Korea Basic Science Institute, Ochang 28119, Republic of Korea.
Park, Edmond Changkyun
  • Research Center for Bioconvergence Analysis, Korea Basic Science Institute (KBSI), Ochang 28119, Republic of Korea.
  • Center for Convergent Research of Emerging Virus Infection, Korea Research Institute of Chemical Technology (KRICT), Daejeon 34114, Republic of Korea.
  • Department of Bio-Analytical Science, University of Science and Technology, Daejeon 34113, Republic of Korea.
Kim, Seung Il
  • Research Center for Bioconvergence Analysis, Korea Basic Science Institute (KBSI), Ochang 28119, Republic of Korea.
  • Center for Convergent Research of Emerging Virus Infection, Korea Research Institute of Chemical Technology (KRICT), Daejeon 34114, Republic of Korea.
  • Department of Bio-Analytical Science, University of Science and Technology, Daejeon 34113, Republic of Korea.

Conflict of Interest Statement

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

References

This article includes 11 references
  1. Lee H, Yun SH, Hyon JY, Lee SY, Yi YS, Choi CW, Jun S, Park EC, Kim SI. Streptococcus equi-derived extracellular vesicles as a vaccine candidate against Streptococcus equi infection.. Vet Microbiol 2021 Aug;259:109165.
    doi: 10.1016/j.vetmic.2021.109165pubmed: 34225054google scholar: lookup
  2. Perez-Riverol Y, Csordas A, Bai J, Bernal-Llinares M, Hewapathirana S, Kundu DJ, Inuganti A, Griss J, Mayer G, Eisenacher M, Pérez E, Uszkoreit J, Pfeuffer J, Sachsenberg T, Yilmaz S, Tiwary S, Cox J, Audain E, Walzer M, Jarnuczak AF, Ternent T, Brazma A, Vizcaíno JA. The PRIDE database and related tools and resources in 2019: improving support for quantification data.. Nucleic Acids Res 2019 Jan 8;47(D1):D442-D450.
    doi: 10.1093/nar/gky1106pmc: PMC6323896pubmed: 30395289google scholar: lookup
  3. Gardner SN, Slezak T, Hall BG. kSNP3.0: SNP detection and phylogenetic analysis of genomes without genome alignment or reference genome.. Bioinformatics 2015 Sep 1;31(17):2877-8.
    doi: 10.1093/bioinformatics/btv271pubmed: 25913206google scholar: lookup
  4. Choi CW, Park EC, Yun SH, Lee SY, Lee YG, Hong Y, Park KR, Kim SH, Kim GH, Kim SI. Proteomic characterization of the outer membrane vesicle of Pseudomonas putida KT2440.. J Proteome Res 2014 Oct 3;13(10):4298-309.
    doi: 10.1021/pr500411dpubmed: 25198519google scholar: lookup
  5. Lee SY, Yun SH, Lee YG, Choi CW, Leem SH, Park EC, Kim GH, Lee JC, Kim SI. Proteogenomic characterization of antimicrobial resistance in extensively drug-resistant Acinetobacter baumannii DU202.. J Antimicrob Chemother 2014 Jun;69(6):1483-91.
    doi: 10.1093/jac/dku008pubmed: 24486871google scholar: lookup
  6. Tyanova S, Temu T, Sinitcyn P, Carlson A, Hein MY, Geiger T, Mann M, Cox J. The Perseus computational platform for comprehensive analysis of (prote)omics data.. Nat Methods 2016 Sep;13(9):731-40.
    doi: 10.1038/nmeth.3901pubmed: 27348712google scholar: lookup
  7. Bertin GI, Sabbagh A, Guillonneau F, Jafari-Guemouri S, Ezinmegnon S, Federici C, Hounkpatin B, Fievet N, Deloron P. Differential protein expression profiles between Plasmodium falciparum parasites isolated from subjects presenting with pregnancy-associated malaria and uncomplicated malaria in Benin.. J Infect Dis 2013 Dec 15;208(12):1987-97.
    doi: 10.1093/infdis/jit377pubmed: 23901091google scholar: lookup
  8. Välikangas T, Suomi T, Elo LL. A comprehensive evaluation of popular proteomics software workflows for label-free proteome quantification and imputation.. Brief Bioinform 2018 Nov 27;19(6):1344-1355.
    doi: 10.1093/bib/bbx054pmc: PMC6291797pubmed: 28575146google scholar: lookup
  9. Tusher VG, Tibshirani R, Chu G. Significance analysis of microarrays applied to the ionizing radiation response.. Proc Natl Acad Sci U S A 2001 Apr 24;98(9):5116-21.
    doi: 10.1073/pnas.091062498pmc: PMC33173pubmed: 11309499google scholar: lookup
  10. Brosch M, Yu L, Hubbard T, Choudhary J. Accurate and sensitive peptide identification with Mascot Percolator.. J Proteome Res 2009 Jun;8(6):3176-81.
    doi: 10.1021/pr800982spmc: PMC2734080pubmed: 19338334google scholar: lookup
  11. Deutsch EW, Bandeira N, Sharma V, Perez-Riverol Y, Carver JJ, Kundu DJ, García-Seisdedos D, Jarnuczak AF, Hewapathirana S, Pullman BS, Wertz J, Sun Z, Kawano S, Okuda S, Watanabe Y, Hermjakob H, MacLean B, MacCoss MJ, Zhu Y, Ishihama Y, Vizcaíno JA. The ProteomeXchange consortium in 2020: enabling 'big data' approaches in proteomics.. Nucleic Acids Res 2020 Jan 8;48(D1):D1145-D1152.
    doi: 10.1093/nar/gkz984pmc: PMC7145525pubmed: 31686107google scholar: lookup

Citations

This article has been cited 0 times.