• Analysis of gene expression data from non-small cell lung carcinoma cell lines reveals distinct sub-classes from those identified at the phenotype level.

      Dalby, Andrew R; Emam, Ibrahim; Franke, Raimo; Helmholtz Centre for infection research, Inhoffenstr. 7, 38124 Braunschweig, Germany. (2012)
      Microarray data from cell lines of Non-Small Cell Lung Carcinoma (NSCLC) can be used to look for differences in gene expression between the cell lines derived from different tumour samples, and to investigate if these differences can be used to cluster the cell lines into distinct groups. Dividing the cell lines into classes can help to improve diagnosis and the development of screens for new drug candidates. The micro-array data is first subjected to quality control analysis and then subsequently normalised using three alternate methods to reduce the chances of differences being artefacts resulting from the normalisation process. The final clustering into sub-classes was carried out in a conservative manner such that sub-classes were consistent across all three normalisation methods. If there is structure in the cell line population it was expected that this would agree with histological classifications, but this was not found to be the case. To check the biological consistency of the sub-classes the set of most strongly differentially expressed genes was be identified for each pair of clusters to check if the genes that most strongly define sub-classes have biological functions consistent with NSCLC.
    • Single-cell phenotypic characterization of Staphylococcus aureus with fluorescent triazole urea activity-based probes.

      Chen, Linhai; Keller, Laura J; Cordasco, Edward A; Bogyo, Matthew; Lentz, Christian S; HZI, Helmholtz Zentrum für Infektionsforschung GmbH, Inhoffenstr. 7, 38124 Braunschweig Germany. (Wiley-Blackwell, 2019-02-15)
      Phenotypically distinct cellular (sub)populations are clinically relevant for virulence and antibiotic resistance of a bacterial pathogen, but functionally different cells are usually indistinguishable from each other. Here, we introduce fluorescent activity-based probes as chemical tools for single-cell phenotypic characterization of enzyme activity levels in Staphylococcus aureus. We screened a 1,2,3-triazole urea library to identify selective inhibitors of fluorophosphonate-binding serine hydrolases and lipases in S. aureus and synthesized target-selective activity-based probes. Molecular imaging and activity-based protein profiling studies with these probes revealed a dynamic network within this enzyme family involving compensatory regulation of specific family members and exposed single-cell phenotypic heterogeneity. We propose chemical probe labeling of enzymatic activities as a generalizable method for phenotyping of bacterial cells at the population and single-cell level.