Isolation of Two Strong Poly (U) Binding Proteins from Moderate Halophile Halomonas eurihalina and Their Identification as Cold Shock Proteins

Cold shock proteins (Csp) are known to be expressed in response to sudden decrease in temperature. They are thought to be involved in a number of cellular processes viz., RNA chaperone activity, translation, transcription, nucleoid condensation. During our studies on ribosomal protein S1 in moderate halophile Halomonas eurihalina, we observed the presence of two strong poly (U) binding proteins in abundance in cell extracts from cells grown under normal growth conditions. The proteins can be isolated in a single step using Poly (U) cellulose chromatography. The proteins were identified as major cold shock proteins belonging to Csp A family by MALDI-TOF and bioinformatic analysis. Csp 12 kDa was found in both exponential and stationary phases whereas Csp 8 kDa is found only in exponential phase

Epigenotyping in Peripheral Blood Cell DNA and Breast Cancer Risk: A Proof of Principle Study

Background: Epigenetic changes are emerging as one of the most important events in carcinogenesis. Two alterations in the pattern of DNA methylation in breast cancer (BC) have been previously reported; active estrogen receptor-a (ER-a) is associated with decreased methylation of ER-a target (ERT) genes, and polycomb group target (PCGT) genes are more likely than other genes to have promoter DNA hypermethylation in cancer. However, whether DNA methylation in normal unrelated cells is associated with BC risk and whether these imprints can be related to factors which can be modified by the environment, is unclear.Methodology/Principal Findings: Using quantitative methylation analysis in a case-control study (n = 1,083) we found that DNA methylation of peripheral blood cell DNA provides good prediction of BC risk. We also report that invasive ductal and invasive lobular BC is characterized by two different sets of genes, the latter particular by genes involved in the differentiation of the mesenchyme (PITX2, TITF1, GDNF and MYOD1). Finally we demonstrate that only ERT genes predict ER positive BC; lack of peripheral blood cell DNA methylation of ZNF217 predicted BC independent of age and family history (odds ratio 1.49; 95% confidence interval 1.12-1.97; P = 0.006) and was associated with ER-a bioactivity in the corresponding serum.Conclusion/Significance: This first large-scale epigenotyping study demonstrates that DNA methylation may serve as a link between the environment and the genome. Factors that can be modulated by the environment (like estrogens) leave an imprint in the DNA of cells that are unrelated to the target organ and indicate the predisposition to develop a cancer. Further research will need to demonstrate whether DNA methylation profiles will be able to serve as a new tool to predict the risk of developing chronic diseases with sufficient accuracy to guide preventive measures

Methanotrophy, Methylotrophy, the Human Body and Disease

Methylotrophic Bacteria use one-carbon (C1) compounds as their carbon source. They have been known to be associated to the human body for almost 20 years as part of the normal flora and were identified as pathogens in the early 1990s in end-stage HIV patients and chemotherapy patients. In this chapter, I look at C1 compounds in the human body and exposure from the environment and then consider Methylobacterium spp. and Methylorubrum spp. in terms of infections, its role in breast and bowel cancers; Methylococcus capsulatus and its role in inflammatory bowel disease, and Brevibacterium casei and Hyphomicrobium sulfonivorans as part of the normal human flora. I also consider the abundance of methylotrophs from the Actinobacteria being identified in human studies and the potential bias of the ionic strength of culture media and the needs for future work. Within the scope of future work, I consider the need for the urgent assessment of the pathogenic, oncogenic, mutagenic and teratogenic potential of Methylobacterium spp. and Methylorubrum spp. and the need to handle them at higher containment levels until more data are available

Predicting RNA-Protein Interactions Using Only Sequence Information

<p>Abstract</p> <p>Background</p> <p>RNA-protein interactions (RPIs) play important roles in a wide variety of cellular processes, ranging from transcriptional and post-transcriptional regulation of gene expression to host defense against pathogens. High throughput experiments to identify RNA-protein interactions are beginning to provide valuable information about the complexity of RNA-protein interaction networks, but are expensive and time consuming. Hence, there is a need for reliable computational methods for predicting RNA-protein interactions.</p> <p>Results</p> <p>We propose <b><it>RPISeq</it></b>, a family of classifiers for predicting <b><it>R</it></b>NA-<b><it>p</it></b>rotein <b><it>i</it></b>nteractions using only <b><it>seq</it></b>uence information. Given the sequences of an RNA and a protein as input, <it>RPIseq </it>predicts whether or not the RNA-protein pair interact. The RNA sequence is encoded as a normalized vector of its ribonucleotide 4-mer composition, and the protein sequence is encoded as a normalized vector of its 3-mer composition, based on a 7-letter reduced alphabet representation. Two variants of <it>RPISeq </it>are presented: <it>RPISeq-SVM</it>, which uses a Support Vector Machine (SVM) classifier and <it>RPISeq-RF</it>, which uses a Random Forest classifier. On two non-redundant benchmark datasets extracted from the Protein-RNA Interface Database (PRIDB), <it>RPISeq </it>achieved an AUC (Area Under the Receiver Operating Characteristic (ROC) curve) of 0.96 and 0.92. On a third dataset containing only mRNA-protein interactions, the performance of <it>RPISeq </it>was competitive with that of a published method that requires information regarding many different features (e.g., mRNA half-life, GO annotations) of the putative RNA and protein partners. In addition, <it>RPISeq </it>classifiers trained using the PRIDB data correctly predicted the majority (57-99%) of non-coding RNA-protein interactions in NPInter-derived networks from <it>E. coli, S. cerevisiae, D. melanogaster, M. musculus</it>, and <it>H. sapiens</it>.</p> <p>Conclusions</p> <p>Our experiments with <it>RPISeq </it>demonstrate that RNA-protein interactions can be reliably predicted using only sequence-derived information. <it>RPISeq </it>offers an inexpensive method for computational construction of RNA-protein interaction networks, and should provide useful insights into the function of non-coding RNAs. <it>RPISeq </it>is freely available as a web-based server at <url>http://pridb.gdcb.iastate.edu/RPISeq/.</url></p

Finding Diagnostically Useful Patterns in Quantitative Phenotypic Data.

Trio-based whole-exome sequence (WES) data have established confident genetic diagnoses in ∼40% of previously undiagnosed individuals recruited to the Deciphering Developmental Disorders (DDD) study. Here we aim to use the breadth of phenotypic information recorded in DDD to augment diagnosis and disease variant discovery in probands. Median Euclidean distances (mEuD) were employed as a simple measure of similarity of quantitative phenotypic data within sets of ≥10 individuals with plausibly causative de novo mutations (DNM) in 28 different developmental disorder genes. 13/28 (46.4%) showed significant similarity for growth or developmental milestone metrics, 10/28 (35.7%) showed similarity in HPO term usage, and 12/28 (43%) showed no phenotypic similarity. Pairwise comparisons of individuals with high-impact inherited variants to the 32 individuals with causative DNM in ANKRD11 using only growth z-scores highlighted 5 likely causative inherited variants and two unrecognized DNM resulting in an 18% diagnostic uplift for this gene. Using an independent approach, naive Bayes classification of growth and developmental data produced reasonably discriminative models for the 24 DNM genes with sufficiently complete data. An unsupervised naive Bayes classification of 6,993 probands with WES data and sufficient phenotypic information defined 23 in silico syndromes (ISSs) and was used to test a "phenotype first" approach to the discovery of causative genotypes using WES variants strictly filtered on allele frequency, mutation consequence, and evidence of constraint in humans. This highlighted heterozygous de novo nonsynonymous variants in SPTBN2 as causative in three DDD probands

Contrasting views on the role of mesenchymal stromal/stem cells in tumour growth : a systematic review of experimental design

The effect of mesenchymal stromal/stem cells (MSCs) on tumour growth remains controversial. Experimental evidence supports both an inhibitory and a stimulatory effect. We have assessed factors responsible for the contrasting effects of MSCs on tumour growth by doing a meta-analysis of existing literature between 2000 and May 2017. We assessed 183 original research articles comprising 338 experiments. We considered (a) in vivo and in vitro experiments, (b) whether in vivo studies were syngeneic or xenogeneic, and (c) if animals were immune competent or deficient. Furthermore, the sources and types of cancer cells and MSCs were considered together with modes of cancer induction and MSC administration. 56% of all 338 experiments reported that MSCs promote tumour growth. 78% and 79% of all experiments sourced human MSCs and cancer cells, respectively. MSCs were used in their naïve and engineered form in 86% and 14% of experiments, respectively, the latter to produce factors that could alter either their activity or that of the tumour. 53% of all experiments were conducted in vitro with 60% exposing cancer cells to MSCs via coculture. Of all in vivo experiments, 79% were xenogeneic and 63% were conducted in immune-competent animals. Tumour growth was inhibited in 80% of experiments that used umbilical cord-derived MSCs, whereas tumour growth was promoted in 64% and 57% of experiments that used bone marrow- and adipose tissue-derived MSCs, respectively. This contrasting effect of MSCs on tumour growth observed under different experimental conditions may reflect differences in experimental design. This analysis calls for careful consideration of experimental design given the large number of MSC clinical trials currently underway.The South African Medical Research Council in terms of the SAMRC’s Flagship Award Project SAMRC-RFA-UFSP-01-2013/STEM CELLS, the SAMRC Extramural Stem Cell Research and Therapy Unit, the National Research Foundation of South Africa (grant no. 86942), the National Health Laboratory Services Research Trust (grant no. 94453), the University of Pretoria Research Development Programme (A0Z778), the University of Pretoria Vice Chancellor’s Postdoctoral Fellowship and the Institute for Cellular and Molecular Medicine of the University of Pretoria.http://www.springer.comseries/5584hj2019ImmunologyOral Pathology and Oral Biolog