Severity: Warning
Message: file_get_contents(https://...@gmail.com&api_key=61f08fa0b96a73de8c900d749fcb997acc09): Failed to open stream: HTTP request failed! HTTP/1.1 429 Too Many Requests
Filename: helpers/my_audit_helper.php
Line Number: 143
Backtrace:
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 143
Function: file_get_contents
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 209
Function: simplexml_load_file_from_url
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 994
Function: getPubMedXML
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 3134
Function: GetPubMedArticleOutput_2016
File: /var/www/html/application/controllers/Detail.php
Line: 574
Function: pubMedSearch_Global
File: /var/www/html/application/controllers/Detail.php
Line: 488
Function: pubMedGetRelatedKeyword
File: /var/www/html/index.php
Line: 316
Function: require_once
This chapter provides step-by-step methods for building secondary metabolic pathway-targeted molecular networks to assess microbial natural product biosynthesis at a systems level and to aid in downstream natural product discovery efforts. Methods described include high-resolution mass spectrometry (HRMS)-based comparative metabolomics, pathway-targeted tandem MS (MS/MS) molecular networking, and isotopic labeling for the elucidation of natural products encoded by orphan biosynthetic pathways. The metabolomics network workflow covers the following six points: (1) method development, (2) bacterial culture growth and organic extraction, (3) HRMS data acquisition and analysis, (4) pathway-targeted MS/MS data acquisition, (5) mass spectral network building, and (6) network enhancement. This chapter opens with a discussion on the practical considerations of natural product extraction, chromatographic processing, and enhanced detection of the analytes of interest within complex organic mixtures using liquid chromatography (LC)-HRMS. Next, we discuss the utilization of a chemometric platform, focusing on Agilent Mass Profiler Professional software, to run MS-based differential analysis between sample groups and controls to acquire a unique set of molecular features that are dependent on the presence of a secondary metabolic pathway. Using this unique list of molecular features, the chapter then details targeted MS/MS acquisition for subsequent pathway-dependent network clustering through the online Global Natural Products Social Molecular Networking (GnPS) platform. Genetic information, ionization intensities, isotopic labeling, and additional experimental data can be mapped onto the pathway-dependent network, facilitating systems biosynthesis analyses. The finished product will provide a working molecular network to assess experimental perturbations and guide novel natural product discoveries.
Download full-text PDF |
Source |
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5049693 | PMC |
http://dx.doi.org/10.1007/978-1-4939-3375-4_12 | DOI Listing |
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