The Caenorhabditis elegans Gene mfap-1 Encodes a Nuclear Protein That Affects Alternative Splicing

RNA splicing is a major regulatory mechanism for controlling eukaryotic gene expression. By generating various splice isoforms from a single pre–mRNA, alternative splicing plays a key role in promoting the evolving complexity of metazoans. Numerous splicing factors have been identified. However, the in vivo functions of many splicing factors remain to be understood. In vivo studies are essential for understanding the molecular mechanisms of RNA splicing and the biology of numerous RNA splicing-related diseases. We previously isolated a Caenorhabditis elegans mutant defective in an essential gene from a genetic screen for suppressors of the rubberband Unc phenotype of unc-93(e1500) animals. This mutant contains missense mutations in two adjacent codons of the C. elegans microfibrillar-associated protein 1 gene mfap-1. mfap-1(n4564 n5214) suppresses the Unc phenotypes of different rubberband Unc mutants in a pattern similar to that of mutations in the splicing factor genes uaf-1 (the C. elegans U2AF large subunit gene) and sfa-1 (the C. elegans SF1/BBP gene). We used the endogenous gene tos-1 as a reporter for splicing and detected increased intron 1 retention and exon 3 skipping of tos-1 transcripts in mfap-1(n4564 n5214) animals. Using a yeast two-hybrid screen, we isolated splicing factors as potential MFAP-1 interactors. Our studies indicate that C. elegans mfap-1 encodes a splicing factor that can affect alternative splicing.National Natural Science Foundation (China) (Grant 30971639)United States. National Institutes of Health (Grant GM24663

Barnase as a New Therapeutic Agent Triggering Apoptosis in Human Cancer Cells

RNases are currently studied as non-mutagenic alternatives to the harmful DNA-damaging anticancer drugs commonly used in clinical practice. Many mammalian RNases are not potent toxins due to the strong inhibition by ribonuclease inhibitor (RI) presented in the cytoplasm of mammalian cells.In search of new effective anticancer RNases we studied the effects of barnase, a ribonuclease from Bacillus amyloliquefaciens, on human cancer cells. We found that barnase is resistant to RI. In MTT cell viability assay, barnase was cytotoxic to human carcinoma cell lines with half-inhibitory concentrations (IC(50)) ranging from 0.2 to 13 microM and to leukemia cell lines with IC(50) values ranging from 2.4 to 82 microM. Also, we characterized the cytotoxic effects of barnase-based immunoRNase scFv 4D5-dibarnase, which consists of two barnase molecules serially fused to the single-chain variable fragment (scFv) of humanized antibody 4D5 that recognizes the extracellular domain of cancer marker HER2. The scFv 4D5-dibarnase specifically bound to HER2-positive cells and was internalized via receptor-mediated endocytosis. The intracellular localization of internalized scFv 4D5-dibarnase was determined by electronic microscopy. The cytotoxic effect of scFv 4D5-dibarnase on HER2-positive human ovarian carcinoma SKOV-3 cells (IC(50) = 1.8 nM) was three orders of magnitude greater than that of barnase alone. Both barnase and scFv 4D5-dibarnase induced apoptosis in SKOV-3 cells accompanied by internucleosomal chromatin fragmentation, membrane blebbing, the appearance of phosphatidylserine on the outer leaflet of the plasma membrane, and the activation of caspase-3.These results demonstrate that barnase is a potent toxic agent for targeting to cancer cells

Advances in structure elucidation of small molecules using mass spectrometry

The structural elucidation of small molecules using mass spectrometry plays an important role in modern life sciences and bioanalytical approaches. This review covers different soft and hard ionization techniques and figures of merit for modern mass spectrometers, such as mass resolving power, mass accuracy, isotopic abundance accuracy, accurate mass multiple-stage MS(n) capability, as well as hybrid mass spectrometric and orthogonal chromatographic approaches. The latter part discusses mass spectral data handling strategies, which includes background and noise subtraction, adduct formation and detection, charge state determination, accurate mass measurements, elemental composition determinations, and complex data-dependent setups with ion maps and ion trees. The importance of mass spectral library search algorithms for tandem mass spectra and multiple-stage MS(n) mass spectra as well as mass spectral tree libraries that combine multiple-stage mass spectra are outlined. The successive chapter discusses mass spectral fragmentation pathways, biotransformation reactions and drug metabolism studies, the mass spectral simulation and generation of in silico mass spectra, expert systems for mass spectral interpretation, and the use of computational chemistry to explain gas-phase phenomena. A single chapter discusses data handling for hyphenated approaches including mass spectral deconvolution for clean mass spectra, cheminformatics approaches and structure retention relationships, and retention index predictions for gas and liquid chromatography. The last section reviews the current state of electronic data sharing of mass spectra and discusses the importance of software development for the advancement of structure elucidation of small molecules

Cancer Biomarker Discovery: The Entropic Hallmark

Background: It is a commonly accepted belief that cancer cells modify their transcriptional state during the progression of the disease. We propose that the progression of cancer cells towards malignant phenotypes can be efficiently tracked using high-throughput technologies that follow the gradual changes observed in the gene expression profiles by employing Shannon's mathematical theory of communication. Methods based on Information Theory can then quantify the divergence of cancer cells' transcriptional profiles from those of normally appearing cells of the originating tissues. The relevance of the proposed methods can be evaluated using microarray datasets available in the public domain but the method is in principle applicable to other high-throughput methods. Methodology/Principal Findings: Using melanoma and prostate cancer datasets we illustrate how it is possible to employ Shannon Entropy and the Jensen-Shannon divergence to trace the transcriptional changes progression of the disease. We establish how the variations of these two measures correlate with established biomarkers of cancer progression. The Information Theory measures allow us to identify novel biomarkers for both progressive and relatively more sudden transcriptional changes leading to malignant phenotypes. At the same time, the methodology was able to validate a large number of genes and processes that seem to be implicated in the progression of melanoma and prostate cancer. Conclusions/Significance: We thus present a quantitative guiding rule, a new unifying hallmark of cancer: the cancer cell's transcriptome changes lead to measurable observed transitions of Normalized Shannon Entropy values (as measured by high-throughput technologies). At the same time, tumor cells increment their divergence from the normal tissue profile increasing their disorder via creation of states that we might not directly measure. This unifying hallmark allows, via the the Jensen-Shannon divergence, to identify the arrow of time of the processes from the gene expression profiles, and helps to map the phenotypical and molecular hallmarks of specific cancer subtypes. The deep mathematical basis of the approach allows us to suggest that this principle is, hopefully, of general applicability for other diseases