Two-dimensional electrophoretic comparison of metastatic and non-metastatic human breast tumors using in vitro cultured epithelial cells derived from the cancer tissues

<p>Abstract</p> <p>Background</p> <p>Breast carcinomas represent a heterogeneous group of tumors diverse in behavior, outcome, and response to therapy. Identification of proteins resembling the tumor biology can improve the diagnosis, prediction, treatment selection, and targeting of therapy. Since the beginning of the post-genomic era, the focus of molecular biology gradually moved from genomes to proteins and proteomes and to their functionality. Proteomics can potentially capture dynamic changes in protein expression integrating both genetic and epigenetic influences.</p> <p>Methods</p> <p>We prepared primary cultures of epithelial cells from 23 breast cancer tissue samples and performed comparative proteomic analysis. Seven patients developed distant metastases within three-year follow-up. These samples were included into a metastase-positive group, the others formed a metastase-negative group. Two-dimensional electrophoretical (2-DE) gels in pH range 4–7 were prepared. Spot densities in 2-DE protein maps were subjected to statistical analyses (R/maanova package) and data-mining analysis (GUHA). For identification of proteins in selected spots, liquid chromatography-tandem mass spectrometry (LC-MS/MS) was employed.</p> <p>Results</p> <p>Three protein spots were significantly altered between the metastatic and non-metastatic groups. The correlations were proven at the 0.05 significance level. Nucleophosmin was increased in the group with metastases. The levels of 2,3-trans-enoyl-CoA isomerase and glutathione peroxidase 1 were decreased.</p> <p>Conclusion</p> <p>We have performed an extensive proteomic study of mammary epithelial cells from breast cancer patients. We have found differentially expressed proteins between the samples from metastase-positive and metastase-negative patient groups.</p

Biophysical and electrochemical studies of protein-nucleic acid interactions

This review is devoted to biophysical and electrochemical methods used for studying protein-nucleic acid (NA) interactions. The importance of NA structure and protein-NA recognition for essential cellular processes, such as replication or transcription, is discussed to provide background for description of a range of biophysical chemistry methods that are applied to study a wide scope of protein-DNA and protein-RNA complexes. These techniques employ different detection principles with specific advantages and limitations and are often combined as mutually complementary approaches to provide a complete description of the interactions. Electrochemical methods have proven to be of great utility in such studies because they provide sensitive measurements and can be combined with other approaches that facilitate the protein-NA interactions. Recent applications of electrochemical methods in studies of protein-NA interactions are discussed in detail

Human brain harbors single nucleotide somatic variations in functionally relevant genes possibly mediated by oxidative stress

Somatic variation in DNA can cause cells to deviate from the preordained genomic path in both disease and healthy conditions. Here, using exome sequencing of paired tissue samples, we show that the normal human brain harbors somatic single base variations measuring up to 0.48% of the total variations. Interestingly, about 64% of these somatic variations in the brain are expected to lead to non-synonymous changes, and as much as 87% of these represent G:C>T:A transversion events. Further, the transversion events in the brain were mostly found in the frontal cortex, whereas the corpus callosum from the same individuals harbors the reference genotype. We found a significantly higher amount of 8-OHdG (oxidative stress marker) in the frontal cortex compared to the corpus callosum of the same subjects (p<0.01), correlating with the higher G:C>T:A transversions in the cortex. We found significant enrichment for axon guidance and related pathways for genes harbouring somatic variations. This could represent either a directed selection of genetic variations in these pathways or increased susceptibility of some loci towards oxidative stress. This study highlights that oxidative stress possibly influence single nucleotide somatic variations in normal human brain

A brief history of learning classifier systems: from CS-1 to XCS and its variants

© 2015, Springer-Verlag Berlin Heidelberg. The direction set by Wilson’s XCS is that modern Learning Classifier Systems can be characterized by their use of rule accuracy as the utility metric for the search algorithm(s) discovering useful rules. Such searching typically takes place within the restricted space of co-active rules for efficiency. This paper gives an overview of the evolution of Learning Classifier Systems up to XCS, and then of some of the subsequent developments of Wilson’s algorithm to different types of learning

RNA-Seq of Human Neurons Derived from iPS Cells Reveals Candidate Long Non-Coding RNAs Involved in Neurogenesis and Neuropsychiatric Disorders

Genome-wide expression analysis using next generation sequencing (RNA-Seq) provides an opportunity for in-depth molecular profiling of fundamental biological processes, such as cellular differentiation and malignant transformation. Differentiating human neurons derived from induced pluripotent stem cells (iPSCs) provide an ideal system for RNA-Seq since defective neurogenesis caused by abnormalities in transcription factors, DNA methylation, and chromatin modifiers lie at the heart of some neuropsychiatric disorders. As a preliminary step towards applying next generation sequencing using neurons derived from patient-specific iPSCs, we have carried out an RNA-Seq analysis on control human neurons. Dramatic changes in the expression of coding genes, long non-coding RNAs (lncRNAs), pseudogenes, and splice isoforms were seen during the transition from pluripotent stem cells to early differentiating neurons. A number of genes that undergo radical changes in expression during this transition include candidates for schizophrenia (SZ), bipolar disorder (BD) and autism spectrum disorders (ASD) that function as transcription factors and chromatin modifiers, such as POU3F2 and ZNF804A, and genes coding for cell adhesion proteins implicated in these conditions including NRXN1 and NLGN1. In addition, a number of novel lncRNAs were found to undergo dramatic changes in expression, one of which is HOTAIRM1, a regulator of several HOXA genes during myelopoiesis. The increase we observed in differentiating neurons suggests a role in neurogenesis as well. Finally, several lncRNAs that map near SNPs associated with SZ in genome wide association studies also increase during neuronal differentiation, suggesting that these novel transcripts may be abnormally regulated in a subgroup of patients

Deciphering the Code for Retroviral Integration Target Site Selection

Upon cell invasion, retroviruses generate a DNA copy of their RNA genome and integrate retroviral cDNA within host chromosomal DNA. Integration occurs throughout the host cell genome, but target site selection is not random. Each subgroup of retrovirus is distinguished from the others by attraction to particular features on chromosomes. Despite extensive efforts to identify host factors that interact with retrovirion components or chromosome features predictive of integration, little is known about how integration sites are selected. We attempted to identify markers predictive of retroviral integration by exploiting Precision-Recall methods for extracting information from highly skewed datasets to derive robust and discriminating measures of association. ChIPSeq datasets for more than 60 factors were compared with 14 retroviral integration datasets. When compared with MLV, PERV or XMRV integration sites, strong association was observed with STAT1, acetylation of H3 and H4 at several positions, and methylation of H2AZ, H3K4, and K9. By combining peaks from ChIPSeq datasets, a supermarker was identified that localized within 2 kB of 75% of MLV proviruses and detected differences in integration preferences among different cell types. The supermarker predicted the likelihood of integration within specific chromosomal regions in a cell-type specific manner, yielding probabilities for integration into proto-oncogene LMO2 identical to experimentally determined values. The supermarker thus identifies chromosomal features highly favored for retroviral integration, provides clues to the mechanism by which retrovirus integration sites are selected, and offers a tool for predicting cell-type specific proto-oncogene activation by retroviruses

LINE-1 Evasion of Epigenetic Repression in Humans

Epigenetic silencing defends against LINE-1 (L1) retrotransposition in mammalian cells. However, the mechanisms that repress young L1 families and how L1 escapes to cause somatic genome mosaicism in the brain remain unclear. Here we report that a conserved Yin Yang 1 (YY1) transcription factor binding site mediates L1 promoter DNA methylation in pluripotent and differentiated cells. By analyzing 24 hippocampal neurons with three distinct single-cell genomic approaches, we characterized and validated a somatic L1 insertion bearing a 3' transduction. The source (donor) L1 for this insertion was slightly 5' truncated, lacked the YY1 binding site, and was highly mobile when tested in\ua0vitro. Locus-specific bisulfite sequencing revealed that the donor L1 and other young L1s with mutated YY1 binding sites were hypomethylated in embryonic stem cells, during neurodifferentiation, and in liver and brain tissue. These results explain how L1 can evade repression and retrotranspose in the human body

A Comprehensive Map of Mobile Element Insertion Polymorphisms in Humans

As a consequence of the accumulation of insertion events over evolutionary time, mobile elements now comprise nearly half of the human genome. The Alu, L1, and SVA mobile element families are still duplicating, generating variation between individual genomes. Mobile element insertions (MEI) have been identified as causes for genetic diseases, including hemophilia, neurofibromatosis, and various cancers. Here we present a comprehensive map of 7,380 MEI polymorphisms from the 1000 Genomes Project whole-genome sequencing data of 185 samples in three major populations detected with two detection methods. This catalog enables us to systematically study mutation rates, population segregation, genomic distribution, and functional properties of MEI polymorphisms and to compare MEI to SNP variation from the same individuals. Population allele frequencies of MEI and SNPs are described, broadly, by the same neutral ancestral processes despite vastly different mutation mechanisms and rates, except in coding regions where MEI are virtually absent, presumably due to strong negative selection. A direct comparison of MEI and SNP diversity levels suggests a differential mobile element insertion rate among populations