dataset · Figshare · 2023
Proteomics protein function prediction.
Emily C. A. Goodall (9582758), Camila Azevedo Antunes (15361417), Jens Möller (427295), Vartul Sangal (157216), Von Vergel L. Torres (15361420), Jessica Gray (322897), Adam F. Cunningham (11874200), Paul A. Hoskisson (27575), Andreas Burkovski (68431), Ian R. Henderson (6930776)
Cited by 0Open access
Abstract
<div><p>Diphtheria is a respiratory disease caused by <i>Corynebacterium diphtheriae</i>. While the toxin-based vaccine has helped control outbreaks of the disease since the mid-20<sup>th</sup> century there has been an increase in cases in recent years, including systemic infections caused by non-toxigenic <i>C</i>. <i>diphtheriae</i> strains. Here we describe the first study of gene essentiality in <i>C</i>. <i>diphtheriae</i>, providing the most-dense <u>Tra</u>nsposon <u>D</u>irected <u>I</u>nsertion <u>S</u>equencing (TraDIS) library in the phylum Actinobacteriota. This high-density library has allowed the identification of conserved genes across the genus and phylum with essential function and enabled the elucidation of essential domains within the resulting proteins including those involved in cell envelope biogenesis. Validation of these data through protein mass spectrometry identified hypothetical and uncharacterized proteins in the proteome which are also represented in the vaccine. These data are an important benchmark and useful resource for the <i>Corynebacterium</i>, <i>Mycobacterium</i>, <i>Nocardia</i> and <i>Rhodococcus</i> research community. It enables the identification of novel antimicrobial and vaccine targets and provides a basis for future studies of Actinobacterial biology.</p></div>
Cite this paper
(9582758), E. C. A. G., (15361417), C. A. A., (427295), J. M., (157216), V. S., (15361420), V. V. L. T., (322897), J. G., (11874200), A. F. C., (27575), P. A. H., (68431), A. B., & (6930776), I. R. H. (2023). Proteomics protein function prediction. Figshare. https://doi.org/10.1371/journal.pgen.1010737.s006
(9582758), Emily C. A. Goodall, et al. “Proteomics protein function prediction.” Figshare, 2023, https://doi.org/10.1371/journal.pgen.1010737.s006.
(9582758), Emily C. A. Goodall, Camila Azevedo Antunes (15361417), Jens Möller (427295), Vartul Sangal (157216), Von Vergel L. Torres (15361420), Jessica Gray (322897), Adam F. Cunningham (11874200), Paul A. Hoskisson (27575), Andreas Burkovski (68431), and Ian R. Henderson (6930776). 2023. “Proteomics protein function prediction.” Figshare. https://doi.org/10.1371/journal.pgen.1010737.s006.
(9582758), E.C.A.G. et al. (2023) ‘Proteomics protein function prediction’, Figshare. Available at: https://doi.org/10.1371/journal.pgen.1010737.s006.
@misc{95827582023proteomics,
title = {{Proteomics protein function prediction.}},
author = {(9582758), Emily C. A. Goodall and (15361417), Camila Azevedo Antunes and (427295), Jens Möller and (157216), Vartul Sangal and (15361420), Von Vergel L. Torres and (322897), Jessica Gray and (11874200), Adam F. Cunningham and (27575), Paul A. Hoskisson and (68431), Andreas Burkovski and (6930776), Ian R. Henderson},
journal = {Figshare},
year = {2023},
doi = {10.1371/journal.pgen.1010737.s006}
}Made from the index record. Check names, capitalisation and page numbers against the paper. Need another style? AI for Research has over 10,000.