Severity: Warning
Message: file_get_contents(https://...@gmail.com&api_key=61f08fa0b96a73de8c900d749fcb997acc09&a=1): Failed to open stream: HTTP request failed! HTTP/1.1 429 Too Many Requests
Filename: helpers/my_audit_helper.php
Line Number: 176
Backtrace:
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 176
Function: file_get_contents
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 250
Function: simplexml_load_file_from_url
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 3122
Function: getPubMedXML
File: /var/www/html/application/controllers/Detail.php
Line: 575
Function: pubMedSearch_Global
File: /var/www/html/application/controllers/Detail.php
Line: 489
Function: pubMedGetRelatedKeyword
File: /var/www/html/index.php
Line: 316
Function: require_once
Denaturing HPLC (DHPLC) is used in a wide variety of genetic applications. Here we introduce a new application for this technique, the identification of bacteria. We combined the capability of DHPLC to detect sequence variation with the principles of rRNA genotyping analysis to develop a high-throughput method of identifying microorganisms. Thirty-nine bacterial species from a broad spectrum of genera were tested to determine if DHPLC could be usedfor identification. Most (36 of 39) species of bacteria had a unique peak profile that could be used as a molecular fingerprint. Furthermore, a blind panel of 65 different bacterial isolates was analyzed to demonstrate the diagnostic capability of this method to specifically identify Yersinia pestis and Bacillus anthracis. All the Y. pestis samples (10 of 10) and the majority of B. anthracis samples (12 of 14) were correctly identified. The procedure had an overall specificity of 100%, overall sensitivity of 91.7%, and a predictive value of 96.9%. The data suggest that DHPLC of products spanning regions of genetic variability will be a useful application for bacterial identification.
Download full-text PDF |
Source |
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http://dx.doi.org/10.2144/02332rr05 | DOI Listing |
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