Dataset describing biodegradation of individual polychlorinated biphenyl congeners (PCBs) by Paraburkholderia xenovorans LB400 in presence and absence of sediment slurry.
Data Brief
; 35: 106821, 2021 Apr.
Article
in En
| MEDLINE
| ID: mdl-33604434
ABSTRACT
This dataset describes the biodegradation of polychlorinated biphenyl (PCB) congeners by Paraburkholderia xenovorans LB400 in absence and presence of PCB-contaminated sediment slurry, over time [1]. In absence of sediment, PCBs were extracted from aqueous bioreactors by liquid-liquid extraction (LLE) with hexane. In presence of sediment, the extraction method used was a modification of U.S. EPA Method 3545 [3]. Sediment slurry samples were extracted from bioreactors using pressurized fluid extraction (Accelerated Solvent Extractor; Dionex ASE-200) with equal parts acetone and hexane. GC-MS/MS triple quadrapole technology in multiple reaction monitoring mode (MRM) was used for identification and quantification of 209 PCBs as 174 chromatographic peaks. Samples were processed in batches of five along with one method blank per batch. All materials used in sample extraction had either been triple rinsed with solvent (methanol, acetone, and hexane) or combusted overnight at 450⯰C to prevent background PCB contamination. Results from the method blanks were used to determine the limit of quantification (LOQ) as the upper limit of the 95% confidence interval (average mass plus two times the standard deviation). PCB congener masses were corrected for surrogate recoveries less than 100%. The PCB concentration dataset was dichotomized at the threshold of the congener specific LOQ. Concentrations of congeners below the LOQ were treated as zero. During analysis, PCB concentration data was filtered to include only congeners belonging to the commercial PCB mixture, Aroclor 1248. LOQ corrected data can inform future experimental design and be reused by other researchers for further analysis and / or interpretive insights.
Full text:
1
Collection:
01-internacional
Database:
MEDLINE
Language:
En
Journal:
Data Brief
Year:
2021
Document type:
Article
Affiliation country:
United States