{"database":"GNPS","file_versions":[{"headers":{"Content-Type":["application/json"]},"body":{"files":{"Other":["ftp://massive-ftp.ucsd.edu/v01/MSV000078960/"]},"type":"primary"},"statusCode":"OK","statusCodeValue":200}],"scores":{"citationCount":1,"reanalysisCount":0,"viewCount":0,"searchCount":0},"additional":{"omics_type":["Metabolomics"],"submitter":["Rolf Mueller"],"instrument_platform":["maXis 4G"],"species":["Sorangium Cellulosum So Ce38","Sorangium Cellulosum So Cegt47"],"full_dataset_link":["https://massive.ucsd.edu/ProteoSAFe/dataset.jsp?task=534f4de52be541fc8c8dc42d64564831"],"sample_protocol":[""],"repository":["GNPS"],"file_size":["201"],"ptm_modification":["none"],"data_protocol":[""],"pubmed_abstract":["Tandem mass spectrometry is a widely applied and highly sensitive technique for the discovery and characterization of microbial natural products such as secondary metabolites from myxobacteria. Here, a data mining workflow based on MS/MS precursor lists targeting only signals related to bacterial metabolism is established using LC-MS data of crude extracts from shaking flask fermentations. The devised method is not biased toward specific compound classes or structural features and is capable of increasing the information content of LC-MS/MS analyses by directing fragmentation events to signals of interest. The approach is thus contrary to typical auto-MS(2) setups where precursor ions are usually selected according to signal intensity, which is regarded as a drawback for metabolite discovery applications when samples contain many overlapping signals and the most intense signals do not necessarily represent compounds of interest. In line with this, the method described here achieves improved MS/MS scan coverage for low-abundance precursor ions not captured by auto-MS(2) experiments and thereby facilitates the search for new secondary metabolites in complex biological samples. To underpin the effectiveness of the approach, the identification and structure elucidation of two new myxobacterial secondary metabolite classes is reported."],"pubmed_title":["Improving natural products identification through targeted LC-MS/MS in an untargeted secondary metabolomics workflow."],"pubmed_authors":["Hoffmann Thomas T, Krug Daniel D, Hüttel Stephan S, Müller Rolf R"],"citation_count":["1"],"additional_accession":[]},"is_claimable":false,"name":"GNPS_Sorangium cellulosum So ce38 and So ceGT47, various media, auto-MS2 and SPL-MS2","description":"MS2 data set resulting from the SPL-MS2 method development as described in the publication mentioned below. The data set is based on triplicate measurements (technical) of various extracts. Extracts are mixtures of three biological replicates (see publication for explanation). In addition, blank extracts of complex cultivation medium were prepared and measured.\nFor each extract auto-MS2 data and SPL-MS2 data is available. ","dates":{"publication":"Sun Dec 07 18:48:00 GMT 2014"},"accession":"MSV000078960","cross_references":{"pubmed":["25280058"]}}