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Diagnosing inflammation and infection in the urinary system via proteomics
BACKGROUND: Current methodology for the diagnosis of diseases in the urinary system includes patient symptomology, urine analysis and urine culture. Asymptomatic bacteriuria from urethral colonization or indwelling catheters, sample contamination from perineal or vaginal sources, and non-infectious...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2015
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4396075/ https://www.ncbi.nlm.nih.gov/pubmed/25889401 http://dx.doi.org/10.1186/s12967-015-0475-3 |
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author | Yu, Yanbao Sikorski, Patricia Bowman-Gholston, Cynthia Cacciabeve, Nicolas Nelson, Karen E Pieper, Rembert |
author_facet | Yu, Yanbao Sikorski, Patricia Bowman-Gholston, Cynthia Cacciabeve, Nicolas Nelson, Karen E Pieper, Rembert |
author_sort | Yu, Yanbao |
collection | PubMed |
description | BACKGROUND: Current methodology for the diagnosis of diseases in the urinary system includes patient symptomology, urine analysis and urine culture. Asymptomatic bacteriuria from urethral colonization or indwelling catheters, sample contamination from perineal or vaginal sources, and non-infectious inflammatory conditions can mimic UTIs, leading to uncertainty on medical treatment decisions. METHODS: Innovative shotgun metaproteomic methods were used to analyze urine sediments from 120 patients also subjected to conventional urinalysis for various clinical reasons including suspected UTIs. The proteomic data were simultaneously searched for the presence of microbial agents, inflammation, immune responses against pathogens, and evidence of urothelial tissue injury. Hierarchical clustering analysis was performed to identify host protein patterns discerning UTI from urethral colonization and vaginal contamination of urine samples. RESULTS: Organisms causing more than 98% of all UTIs and commensal microbes of the urogenital and perineal area were identified from 76 urine sediments with detection sensitivities estimated to be similar to urine culture. Proteomic data permitted a thorough evaluation of inflammatory and antimicrobial immune responses. Hierarchical clustering of the data revealed that high abundances of proteins from activated neutrophils were associated with pathogens in most cases, and correlated well with leukocyte esterase activities and leukocyte counts via microscopy. Proteomic data also allowed assessments of urothelial injury, by quantifying proteins highly expressed in red blood cells and contributing to the acute phase response. Lactobacillus and Gardnerella vaginalis were frequently identified suggesting urethral colonization and/or vaginal contamination of urine. CONCLUSIONS: A metaproteomic approach of interest for routine urine clinical diagnostics is presented. As compared to urinalysis and urine culture methods, the data are derived from a single experiment for a given sample and provide additional insights into presence or absence of inflammatory responses and vaginal contamination of urine specimens. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12967-015-0475-3) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-4396075 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-43960752015-04-14 Diagnosing inflammation and infection in the urinary system via proteomics Yu, Yanbao Sikorski, Patricia Bowman-Gholston, Cynthia Cacciabeve, Nicolas Nelson, Karen E Pieper, Rembert J Transl Med Research BACKGROUND: Current methodology for the diagnosis of diseases in the urinary system includes patient symptomology, urine analysis and urine culture. Asymptomatic bacteriuria from urethral colonization or indwelling catheters, sample contamination from perineal or vaginal sources, and non-infectious inflammatory conditions can mimic UTIs, leading to uncertainty on medical treatment decisions. METHODS: Innovative shotgun metaproteomic methods were used to analyze urine sediments from 120 patients also subjected to conventional urinalysis for various clinical reasons including suspected UTIs. The proteomic data were simultaneously searched for the presence of microbial agents, inflammation, immune responses against pathogens, and evidence of urothelial tissue injury. Hierarchical clustering analysis was performed to identify host protein patterns discerning UTI from urethral colonization and vaginal contamination of urine samples. RESULTS: Organisms causing more than 98% of all UTIs and commensal microbes of the urogenital and perineal area were identified from 76 urine sediments with detection sensitivities estimated to be similar to urine culture. Proteomic data permitted a thorough evaluation of inflammatory and antimicrobial immune responses. Hierarchical clustering of the data revealed that high abundances of proteins from activated neutrophils were associated with pathogens in most cases, and correlated well with leukocyte esterase activities and leukocyte counts via microscopy. Proteomic data also allowed assessments of urothelial injury, by quantifying proteins highly expressed in red blood cells and contributing to the acute phase response. Lactobacillus and Gardnerella vaginalis were frequently identified suggesting urethral colonization and/or vaginal contamination of urine. CONCLUSIONS: A metaproteomic approach of interest for routine urine clinical diagnostics is presented. As compared to urinalysis and urine culture methods, the data are derived from a single experiment for a given sample and provide additional insights into presence or absence of inflammatory responses and vaginal contamination of urine specimens. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12967-015-0475-3) contains supplementary material, which is available to authorized users. BioMed Central 2015-04-08 /pmc/articles/PMC4396075/ /pubmed/25889401 http://dx.doi.org/10.1186/s12967-015-0475-3 Text en © Yu et al.; licensee BioMed Central. 2015 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Research Yu, Yanbao Sikorski, Patricia Bowman-Gholston, Cynthia Cacciabeve, Nicolas Nelson, Karen E Pieper, Rembert Diagnosing inflammation and infection in the urinary system via proteomics |
title | Diagnosing inflammation and infection in the urinary system via proteomics |
title_full | Diagnosing inflammation and infection in the urinary system via proteomics |
title_fullStr | Diagnosing inflammation and infection in the urinary system via proteomics |
title_full_unstemmed | Diagnosing inflammation and infection in the urinary system via proteomics |
title_short | Diagnosing inflammation and infection in the urinary system via proteomics |
title_sort | diagnosing inflammation and infection in the urinary system via proteomics |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4396075/ https://www.ncbi.nlm.nih.gov/pubmed/25889401 http://dx.doi.org/10.1186/s12967-015-0475-3 |
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