The complete genomic sequence of Streptomyces spectabilis NRRL-2792 and identification of secondary metabolite biosynthetic gene clusters.

This is the first report of a fully annotated genomic sequence of Streptomyces spectabilis NRRL-2792, isolated and identified by The Upjohn Company in 1961. The genome was assembled into a single scaffold for annotation and analysis. The chromosome is linear, 9.5 Mb in size which is one of the largest Streptomyces genomes yet described, has a G+C content of 72%, and encodes for approximately 7943 genes. Antibiotic Secondary Metabolite Analysis Shell (antiSMASH) and Basic Local Alignment Search Tool (BLAST) bioinformatics analyses identified six complete secondary metabolite biosynthetic gene clusters for ectoine, melanin, albaflavenone, spectinomycin, 2-methylisoborneol and coelichelin. Additionally, biosynthetic clusters were identified that shared ≥ 90% gene content with complestatin, hopene, neoaureothin, or undecylprodigiosin. Thirty-one other likely secondary metabolite gene clusters were identified by antiSMASH. BLAST identified two subsets of undecylprodigiosin biosynthetic genes at polar opposites of the chromosome; their duplication was subsequently confirmed by primer walking.

Segment and fit thresholding: a new method for image analysis applied to microarray and immunofluorescence data.

Experiments involving the high-throughput quantification of image data require algorithms for automation. A challenge in the development of such algorithms is to properly interpret signals over a broad range of image characteristics, without the need for manual adjustment of parameters. Here we present a new approach for locating signals in image data, called Segment and Fit Thresholding (SFT). The method assesses statistical characteristics of small segments of the image and determines the best-fit trends between the statistics. Based on the relationships, SFT identifies segments belonging to background regions; analyzes the background to determine optimal thresholds; and analyzes all segments to identify signal pixels. We optimized the initial settings for locating background and signal in antibody microarray and immunofluorescence data and found that SFT performed well over multiple, diverse image characteristics without readjustment of settings. When used for the automated analysis of multicolor, tissue-microarray images, SFT correctly found the overlap of markers with known subcellular localization, and it performed better than a fixed threshold and Otsu's method for selected images. SFT promises to advance the goal of full automation in image analysis.

Critical reagent considerations for immunogenicity assay development for bispecific biotherapeutic candidates.

Aim: To demonstrate the importance of critical reagent characterization for immunogenicity assay development for multi-specific drugs using two case studies. Methods: Bridging anti-drug antibody (ADA) assay with acid-dissociated samples were used for both cases. Results: In the first case study, the unexpected interference in an ADA assay from clinical samples was identified; a model was created to replicate the issue, and an anti-target antibody was identified to mitigate the target interference. In the second case study, an issue due to non-specific binding of a domain-specific confirmatory reagent was identified, and various mitigation techniques were evaluated. Conclusion: A thorough characterization of the critical reagents helped identify the issues with these ADA case studies and provided strategies for resolving them.

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Mesenchymal-like pancreatic cancer cells harbor specific genomic alterations more frequently than their epithelial-like counterparts.

The aggressiveness of pancreatic cancer is associated with the acquisition of mesenchymal characteristics by a subset of pancreatic cancer cells. The factors driving the development of this subset are not well understood. In this study, we tested the hypothesis that acquisition of a mesenchymal phenotype occurs selectively in tumor cells that harbor specific enabling genetic alterations. We obtained whole-genome comparative genomic hybridization (CGH) measurements on pancreatic cancer cell lines that have either an epithelial-like (17 cell lines) or a mesenchymal-like (9 cell lines) phenotype in vitro. The total amounts of amplifications and deletions were equivalent between the epithelial and mesenchymal groups, but 20 genes showed a major difference between the groups in prevalence of alterations. All 20 alterations (18 deletions and 2 amplifications) were more prevalent in the mesenchymal group, confirming the advanced nature of this cellular subtype. CDKN2A was altered in more than 50% of both groups, but co-deletions in neighboring genes, and concomitant loss of gene expression, were more prevalent in the mesenchymal group, suggesting that the size of the loss around CDKN2A affects cell phenotype. Whole-genome CGH on 11 primary cancer tissues revealed that the 20 genes were altered at a higher prevalence (up to 55% of the cases for certain genes) than randomly selected sets of 20 genes, with the same direction of alteration as in the cell lines. These findings support the concept that specific genetic alterations enable phenotype plasticity and provide promising candidate genes for further research.

Glycogene expression alterations associated with pancreatic cancer epithelial-mesenchymal transition in complementary model systems.

BACKGROUND: The ability to selectively detect and target cancer cells that have undergone an epithelial-mesenchymal transition (EMT) may lead to improved methods to treat cancers such as pancreatic cancer. The remodeling of cellular glycosylation previously has been associated with cell differentiation and may represent a valuable class of molecular targets for EMT. METHODOLOGY/PRINCIPAL FINDINGS: As a first step toward investigating the nature of glycosylation alterations in EMT, we characterized the expression of glycan-related genes in three in-vitro model systems that each represented a complementary aspect of pancreatic cancer EMT. These models included: 1) TGFß-induced EMT, which provided a look at the active transition between states; 2) a panel of 22 pancreatic cancer cell lines, which represented terminal differentiation states of either epithelial-like or mesenchymal-like; and 3) actively-migrating and stationary cells, which provided a look at the mechanism of migration. We analyzed expression data from a list of 587 genes involved in glycosylation (biosynthesis, sugar transport, glycan-binding, etc.) or EMT. Glycogenes were altered at a higher prevalence than all other genes in the first two models (p<0.05 and <0.005, respectively) but not in the migration model. Several functional themes were shared between the induced-EMT model and the cell line panel, including alterations to matrix components and proteoglycans, the sulfation of glycosaminoglycans; mannose receptor family members; initiation of O-glycosylation; and certain forms of sialylation. Protein-level changes were confirmed by Western blot for the mannose receptor MRC2 and the O-glycosylation enzyme GALNT3, and cell-surface sulfation changes were confirmed using Alcian Blue staining. CONCLUSIONS/SIGNIFICANCE: Alterations to glycogenes are a major component of cancer EMT and are characterized by changes to matrix components, the sulfation of GAGs, mannose receptors, O-glycosylation, and specific sialylated structures. These results provide leads for targeting aggressive and drug resistant forms of pancreatic cancer cells.