Microbial Communities in the Surface Mucopolysaccharide Layer and the Black Band Microbial Mat of Black Band-Diseased Siderastrea siderea

Microbial community profiles and species composition associated with two black band-diseased colonies of the coral Siderastrea siderea were studied by 16S rRNA-targeted gene cloning, sequencing, and amplicon-length heterogeneity PCR (LH-PCR). Bacterial communities associated with the surface mucopolysaccharide layer (SML) of apparently healthy tissues of the infected colonies, together with samples of the black band disease (BBD) infections, were analyzed using the same techniques for comparison. Gene sequences, ranging from 424 to 1,537 bp, were retrieved from all positive clones (n = 43 to 48) in each of the four clone libraries generated and used for comparative sequence analysis. In addition to LH-PCR community profiling, all of the clone sequences were aligned with LH-PCR primer sequences, and the theoretical lengths of the amplicons were determined. Results revealed that the community profiles were significantly different between BBD and SML samples. The SML samples were dominated by γ-proteobacteria (53 to 64%), followed by β-proteobacteria (18 to 21%) and α-proteobacteria (5 to 11%). In contrast, both BBD clone libraries were dominated by α-proteobacteria (58 to 87%), followed by verrucomicrobia (2 to 10%) and 0 to 6% each of δ-proteobacteria, bacteroidetes, firmicutes, and cyanobacteria. Alphaproteobacterial sequence types related to the bacteria associated with toxin-producing dinoflagellates were observed in BBD clone libraries but were not found in the SML libraries. Similarly, sequences affiliated with the family Desulfobacteraceae and toxin-producing cyanobacteria, both believed to be involved in BBD pathogenesis, were found only in BBD libraries. These data provide evidence for an association of numerous toxin-producing heterotrophic microorganisms with BBD of corals

Proteomic Contributions to Personalized Cancer Care*

Cancer impacts each patient and family differently. Our current understanding of the disease is primarily limited to clinical hallmarks of cancer, but many specific molecular mechanisms remain elusive. Genetic markers can be used to determine predisposition to tumor development, but molecularly targeted treatment strategies that improve patient prognosis are not widely available for most cancers. Individualized care plans, also described as personalized medicine, still must be developed by understanding and implementing basic science research into clinical treatment. Proteomics holds great promise in contributing to the prevention and cure of cancer because it provides unique tools for discovery of biomarkers and therapeutic targets. As such, proteomics can help translate basic science discoveries into the clinical practice of personalized medicine. Here we describe how biological mass spectrometry and proteome analysis interact with other major patient care and research initiatives and present vignettes illustrating efforts in discovery of diagnostic biomarkers for ovarian cancer, development of treatment strategies in lung cancer, and monitoring prognosis and relapse in multiple myeloma patients

GSK3 Alpha and Beta Are New Functionally Relevant Targets of Tivantinib in Lung Cancer Cells

Tivantinib has been described as a potent and highly selective inhibitor of the receptor tyrosine kinase c-MET and is currently in advanced clinical development for several cancers including non-small cell lung cancer (NSCLC). However, recent studies suggest that tivantinib’s anticancer properties are unrelated to c-MET inhibition. Consistently, in determining tivantinib’s activity profile in a broad panel of NSCLC cell lines, we found that, in contrast to several more potent c-MET inhibitors, tivantinib reduces cell viability across most of these cell lines. Applying an unbiased, mass-spectrometry-based, chemical proteomics approach, we identified glycogen synthase kinase 3 (GSK3) alpha and beta as novel tivantinib targets. Subsequent validation showed that tivantinib displayed higher potency for GSK3α than for GSK3β and that pharmacological inhibition or simultaneous siRNA-mediated loss of GSK3α and GSK3β caused apoptosis. In summary, GSK3α and GSK3β are new kinase targets of tivantinib that play an important role in its cellular mechanism-of-action in NSCLC