Severity: Warning
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File: /var/www/html/application/helpers/my_audit_helper.php
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Function: file_get_contents
File: /var/www/html/application/helpers/my_audit_helper.php
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Function: simplexml_load_file_from_url
File: /var/www/html/application/helpers/my_audit_helper.php
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Function: getPubMedXML
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Function: pubMedSearch_Global
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Function: pubMedGetRelatedKeyword
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Function: require_once
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File: /var/www/html/application/controllers/Detail.php
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Function: pubMedSearch_Global
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Function: pubMedGetRelatedKeyword
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Unlabelled: Chronic bacterial infections are often polymicrobial, comprising multiple bacterial species or variants of the same species. Because chronic infections may last for decades, they have the potential to generate high levels of intraspecific variation through within-host diversification over time, and the potential for superinfections to occur through the introduction of multiple pathogen populations to the ongoing infection. Traditional methods for identifying infective agents generally involve isolating one single colony from a given sample, usually after selecting for a specific pathogen or antibiotic resistance profile. Isolating a recognized virulent or difficult to treat pathogen is an important part of informing clinical treatment and correlative research; however, these reductive methods alone, do not provide researchers or healthcare providers with the potentially important perspective on the true pathogen population structure and dynamics over time. To begin to address this limitation, in this study, we compare findings on single colonies versus and pools of colonies taken from fresh sputum samples from three patients with cystic fibrosis to isolates collected from the same sputum samples and processed by the clinical microbiology laboratory. Phenotypic and genotypic analysis of isolated populations revealed coexisting lineages in two of three sputum samples as well as population structures that were not reflected in the single colony isolates. Altogether, our observations presented here demonstrate that clinically relevant diversity can be missed with standard sampling methods when assessing chronic infections. More broadly, this work outlines the potential impact that comprehensive population-level sampling may have for both research efforts and more effective treatment practices.
Data Summary: The authors confirm all supporting data, code and protocols have been provided within the article.
Download full-text PDF |
Source |
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11601312 | PMC |
http://dx.doi.org/10.1101/2024.11.16.623925 | DOI Listing |
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