gc-based-detection-aldononitrile-acetate-derivatized-glucosamine

GC-based Detection of Aldononitrile Acetate Derivatized Glucosamine and Muramic Acid for Microbial Residue Determination in Soil

Quantitative approaches to characterizing microorganisms are crucial for a broader understanding of the microbial status and function within ecosystems. ...

a-lipid-extraction-analysis-method-for-characterizing-soil-microbes

A Lipid Extraction and Analysis Method for Characterizing Soil Microbes in Experiments with Many Samples

Microbial communities are important drivers and regulators of ecosystem processes. To understand how management of ecosystems may affect microbial ...

University of Wisconsin, Madison

University of Wisconsin - Madison

Toxicity results from submitochondrial particle (SMP) bioassays were compared to results from multiple human-cell-based assays to evaluate the SMP tests' ability to indicate cellular toxicity. Correlation analyses between cell-based and SMP responses were conducted on a series of diverse chemicals of human toxicologic interest chosen in the Multicentre Evaluation of In vitro Cytotoxicity (MEIC) study and suggest a high degree of ordering. The r(2) correlation coefficient obtained when comparing the log-transformed SMP results to the average cellular response for all compounds was 0.75 (n=42). When specific mitochondrial inhibitors (to which SMP arc extremely sensitive) and toxic metals (which SMP modeled poorly) were removed, the correlation improved to 0.91 (n=34). When the SMP assay of each individual cell-based assay was compared to the average toxic response of all the cell-based assays for these 34 compounds, the SMP r(2) was greater than the median r(2) of the cell-based assays, indicating its ability to predict cell-based toxic responses with a high degree of accuracy. Comparisons of the SMP data to the human toxicity data are similar to the cell line assays, where removal of the specific mitochondrial toxicants and metals greatly improves the relationship.

Comparisons of human-cell-based and submitochondrial particle bioassay responses to the MEIC compounds in reference to human toxicity data.

The muramic acid (MurA) assay is a powerful tool for the detection and quantification of bacteria with no need to enrich samples by culturing. However, the analysis of MurA in mixed biological and environmental matrices is potentially more complex than analysis in isolated bacterial cells. In this study, we employed one commonly used procedure for extraction of MurA from environmental samples and found that the presence of streptomycin interfered with the determination of MurA by creating chemical species that coeluted with the aldononitrile derivative of MurA prepared in this method. On a molar basis, streptomycin yields a signal that is approximately 0.67 times that of MurA. Mass spectrometry analysis confirmed that the interference from hydrolyzed streptomycin is not actually by MurA, but rather is likely to be N-methyl glucosamine. Because streptomycin is widely applied for selective growth of eukaryotes both in situ and in vitro, our findings may have implications for the significance of results from MurA assays. We conclude that MurA remains an effectual bacterial biomarker due to its unique bacterial origin, but care must be applied in interpreting results from the assay when performed in the presence of streptomycin.

Harry W. Read

Department of Soil Science

University of Wisconsin, Madison

GC-based Detection of Aldononitrile Acetate Derivatized Glucosamine and Muramic Acid for Microbial Residue Determination in Soil

A Lipid Extraction and Analysis Method for Characterizing Soil Microbes in Experiments with Many Samples

Harry W. Read

.css-o250i3{font-size:18px;font-family:Open Sans,sans-serif;line-height:21.6px;}Department of Soil Science

University of Wisconsin, Madison

GC-based Detection of Aldononitrile Acetate Derivatized Glucosamine and Muramic Acid for Microbial Residue Determination in Soil

A Lipid Extraction and Analysis Method for Characterizing Soil Microbes in Experiments with Many Samples

Department of Soil Science