Severity: Warning
Message: file_get_contents(https://...@pubfacts.com&api_key=b8daa3ad693db53b1410957c26c9a51b4908&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: 1034
Function: getPubMedXML
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 3152
Function: GetPubMedArticleOutput_2016
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
High-resolution two-dimensional gel electrophoresis and mass spectrometry has been used to identify the outer membrane (OM) subproteome of the Gram-negative bacterium Methylococcus capsulatus (Bath). Twenty-eight unique polypeptide sequences were identified from protein samples enriched in OMs. Only six of these polypeptides had previously been identified. The predictions from novel bioinformatic methods predicting beta-barrel outer membrane proteins (OMPs) and OM lipoproteins were compared to proteins identified experimentally. BOMP ( http://www.bioinfo.no/tools/bomp ) predicted 43 beta-barrel OMPs (1.45%) from the 2,959 annotated open reading frames. This was a lower percentage than predicted from other Gram-negative proteomes (1.8-3%). More than half of the predicted BOMPs in M. capsulatus were annotated as (conserved) hypothetical proteins with significant similarity to very few sequences in Swiss-Prot or TrEMBL. The experimental data and the computer predictions indicated that the protein composition of the M. capsulatus OM subproteome was different from that of other Gram-negative bacteria studied in a similar manner. A new program, Lipo, was developed that can analyse entire predicted proteomes and give a list of recognised lipoproteins categorised according to their lipo-box similarity to known Gram-negative lipoproteins ( http://www.bioinfo.no/tools/lipo ). This report is the first using a proteomics and bioinformatics approach to identify the OM subproteome of an obligate methanotroph.
Download full-text PDF |
Source |
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http://dx.doi.org/10.1007/s00203-005-0055-7 | DOI Listing |
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