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Rise of Clinical Microbial Proteogenomics: A Multiomics Approach to Nontuberculous Mycobacterium—The Case of Mycobacterium abscessus UC22

Overview of attention for article published in OMICS: A Journal of Integrative Biology, January 2019
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Article details
Title
Rise of Clinical Microbial Proteogenomics: A Multiomics Approach to Nontuberculous Mycobacterium—The Case of Mycobacterium abscessus UC22
Published in
OMICS: A Journal of Integrative Biology, January 2019
DOI 10.1089/omi.2018.0116
Pubmed ID
Authors
Abstract

Nontuberculous mycobacterial (NTM) species present a major challenge for global health with serious clinical manifestations ranging from pulmonary to skin infections. Multiomics research and its applications toward clinical microbial proteogenomics offer veritable potentials in this context. For example, the Mycobacterium abscessus, a highly pathogenic NTM, causes bronchopulmonary infection and chronic pulmonary disease. The rough variant of the M. abscessus UC22 strain is extremely virulent and causes lung upper lobe fibrocavitary disease. Although several whole-genome next-generation sequencing studies have characterized the genes in the smooth variant of M. abscessus, a reference genome sequence for the rough variant was generated only recently and calls for further clinical applications. We carried out whole-genome sequencing and proteomic analysis for a clinical isolate of M. abscessus UC22 strain obtained from a pulmonary tuberculosis patient. We identified 5506 single-nucleotide variations (SNVs), 63 insertions, and 76 deletions compared with the reference genome. Using a high-resolution LC-MS/MS-based approach (liquid chromatography tandem mass spectrometry), we obtained protein coding evidence for 3601 proteins, representing 71% of the total predicted genes in this genome. Application of proteogenomic approach further revealed seven novel protein-coding genes and enabled refinement of six computationally derived gene models. We also identified 30 variant peptides corresponding to 16 SNVs known to be associated with drug resistance. These new observations offer promise for clinical applications of microbial proteogenomics and next-generation sequencing, and provide a resource for future global health applications for NTM species.

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Mendeley demographics

Mendeley demographics

The data shown below were compiled from readership statistics for 37 Mendeley readers of this research output. Click here to see the associated Mendeley record.
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Geographical breakdown

Geographical breakdown
Country Count As %
Unknown 37 100%

Demographic breakdown

Readers by professional status
Readers by professional status Count As %
Student > Ph. D. Student 5 14%
Student > Master 5 14%
Student > Bachelor 4 11%
Researcher 4 11%
Other 2 5%
Other 4 11%
Unknown 13 35%
Readers by discipline
Readers by discipline Count As %
Medicine and Dentistry 7 19%
Immunology and Microbiology 5 14%
Biochemistry, Genetics and Molecular Biology 2 5%
Agricultural and Biological Sciences 2 5%
Nursing and Health Professions 1 3%
Other 3 8%
Unknown 17 46%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 13 September 2018.
All research outputs
#23,577,572
of 29,646,466 outputs
Outputs from OMICS: A Journal of Integrative Biology
#529
of 734 outputs
Outputs of similar age
#339,519
of 459,276 outputs
Outputs of similar age from OMICS: A Journal of Integrative Biology
#7
of 13 outputs
Altmetric has tracked 29,646,466 research outputs across all sources so far. This one is in the 17th percentile – i.e., 17% of other outputs scored the same or lower than it.
So far Altmetric has tracked 734 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 7.6. This one is in the 22nd percentile – i.e., 22% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 459,276 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 22nd percentile – i.e., 22% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 13 others from the same source and published within six weeks on either side of this one. This one is in the 38th percentile – i.e., 38% of its contemporaries scored the same or lower than it.