Vladimir A. Ivanisenko

uORFs, reinitiation and alternative translation start sites in human mRNAs

It is known that eukaryotic ribosomes are able to translate small ORFs and reinitiate translation at downstream start codons. However, this mechanism is widely considered to be inefficient and it is not commonly taken into account. We compiled a sample of human mRNAs containing small upstream ORFs overlapping with annotated protein coding sequences. Statistical analysis supported the hypothesis on reinitiation of translation at downstream AUG codons and functional significance of potential alternative ORFs. It may be assumed that some 5′UTR‐located upstream ORFs can deliver ribosomes to alternative translation starts, and they should be taken into consideration in the prediction of human mRNA coding potential.

ANDVisio: A new tool for graphic visualization and analysis of literature mined associative gene networks in the ANDSystem

The ANDVisio tool is designed to reconstruct and analyze associative gene networks in the earlier developed Associative Network Discovery System (ANDSystem) software package. The ANDSystem incorporates utilities for automated extraction of knowledge from Pubmed published scientific texts, analysis of factographic databases, also the ANDCell database containing information on molecular-genetic events retrieved from texts and databases. ANDVisio is a new users interface to the ANDCell database stored in a remote server. ANDVisio provides graphic visualization, editing, search, also saving of associative gene networks in different formats resulting from users request. The associative gene networks describe semantic relationships between molecular-genetic objects (proteins, genes, metabolites and others), biological processes, and diseases. ANDVisio is provided with various tools to support filtering by object types, relationships between objects and information sources; graph layout; search of the shortest pathway; cycles in graphs.

Time-course human urine proteomics in space-flight simulation experiments

BackgroundLong-term space travel simulation experiments enabled to discover different aspects of human metabolism such as the complexity of NaCl salt balance. Detailed proteomics data were collected during the Mars105 isolation experiment enabling a deeper insight into the molecular processes involved.ResultsWe studied the abundance of about two thousand proteins extracted from urine samples of six volunteers collected weekly during a 105-day isolation experiment under controlled dietary conditions including progressive reduction of salt consumption. Machine learning using Self Organizing maps (SOM) in combination with different analysis tools was applied to describe the time trajectories of protein abundance in urine. The method enables a personalized and intuitive view on the physiological state of the volunteers. The abundance of more than one half of the proteins measured clearly changes in the course of the experiment. The trajectory splits roughly into three time ranges, an early (week 1-6), an intermediate (week 7-11) and a late one (week 12-15). Regulatory modes associated with distinct biological processes were identified using previous knowledge by applying enrichment and pathway flow analysis. Early protein activation modes can be related to immune response and inflammatory processes, activation at intermediate times to developmental and proliferative processes and late activations to stress and responses to chemicals.ConclusionsThe protein abundance profiles support previous results about alternative mechanisms of salt storage in an osmotically inactive form. We hypothesize that reduced NaCl consumption of about 6 g/day presumably will reduce or even prevent the activation of inflammatory processes observed in the early time range of isolation. SOM machine learning in combination with analysis methods of class discovery and functional annotation enable the straightforward analysis of complex proteomics data sets generated by means of mass spectrometry.

Detection of Renal Tissue and Urinary Tract Proteins in the Human Urine after Space Flight

The urine protein composition samples of ten Russian cosmonauts (male, aged of 35 up to 51) performed long flight missions and varied from 169 up to 199 days on the International Space Station (ISS) were analyzed. As a control group, urine samples of six back-up cosmonauts were analyzed. We used proteomic techniques to obtain data and contemporary bioinformatics approaches to perform the analysis. From the total number of identified proteins (238) in our data set, 129 were associated with a known tissue origin. Preflight samples contained 92 tissue-specific proteins, samples obtained on Day 1 after landing had 90 such proteins, while Day 7 samples offered 95 tissue-specific proteins. Analysis showed that consistently present proteins in urine (under physiological conditions and after space flight) are cubilin, epidermal growth factor, kallikrein-1, kininogen-1, megalin, osteopontin, vitamin K-dependent protein Z, uromodulin. Variably present proteins consists of: Na(+)/K(+) ATPase subunit gamma, β-defensin-1, dipeptidyl peptidase 4, maltasa-glucoamilasa, cadherin-like protein, neutral endopeptidase and vascular cell adhesion protein 1. And only three renal proteins were related to the space flight factors. They were not found in the pre-flight samples and in the back-up cosmonaut urine, but were found in the urine samples after space flight: AFAM (afamin), AMPE (aminopeptidase A) and AQP2 (aquaporin-2). This data related with physiological readaptation of water-salt balance. The proteomic analysis of urine samples in different phases of space missions with bioinformation approach to protein identification provides new data relative to biomechemical mechanism of kidney functioning after space flight.

ANDSystem: an Associative Network Discovery System for automated literature mining in the field of biology

BackgroundSufficient knowledge of molecular and genetic interactions, which comprise the entire basis of the functioning of living systems, is one of the necessary requirements for successfully answering almost any research question in the field of biology and medicine. To date, more than 24 million scientific papers can be found in PubMed, with many of them containing descriptions of a wide range of biological processes. The analysis of such tremendous amounts of data requires the use of automated text-mining approaches. Although a handful of tools have recently been developed to meet this need, none of them provide error-free extraction of highly detailed information.ResultsThe ANDSystem package was developed for the reconstruction and analysis of molecular genetic networks based on an automated text-mining technique. It provides a detailed description of the various types of interactions between genes, proteins, microRNAs, metabolites, cellular components, pathways and diseases, taking into account the specificity of cell lines and organisms. Although the accuracy of ANDSystem is comparable to other well known text-mining tools, such as Pathway Studio and STRING, it outperforms them in having the ability to identify an increased number of interaction types.ConclusionThe use of ANDSystem, in combination with Pathway Studio and STRING, can improve the quality of the automated reconstruction of molecular and genetic networks. ANDSystem should provide a useful tool for researchers working in a number of different fields, including biology, biotechnology, pharmacology and medicine.

Visualization and analysis of a cardio vascular disease- and MUPP1-related biological network combining text mining and data warehouse approaches.

Detailed investigation of socially important diseases with modern experimental methods has resulted in the generation of large volume of valuable data. However, analysis and interpretation of this data needs application of efficient computational techniques and systems biology approaches. In particular, the techniques allowing the reconstruction of associative networks of various biological objects and events can be useful. In this publication, the combination of different techniques to create such a network associated with an abstract cell environment is discussed in order to gain insights into the functional as well as spatial interrelationships. It is shown that experimentally gained knowledge enriched with data warehouse content and text mining data can be used for the reconstruction and localization of a cardiovascular disease developing network beginning with MUPP1/MPDZ (multi-PDZ domain protein).

SUBCELLULAR LOCALIZATION CHARTS: A NEW VISUAL METHODOLOGY FOR THE SEMI-AUTOMATIC LOCALIZATION OF PROTEIN-RELATED DATA SETS

The CELLmicrocosmos PathwayIntegration (CmPI) was developed to support and visualize the subcellular localization prediction of protein-related data such as protein-interaction networks. From the start it was possible to manually analyze the localizations by using an interactive table. It was, however, quite complicated to compare and analyze the different localization results derived from data integration as well as text-mining-based databases. The current software release provides a new interactive visual workflow, the Subcellular Localization Charts. As an application case, a MUPP1-related protein-protein interaction network is localized and semi-automatically analyzed. It will be shown that the workflow was dramatically improved and simplified. In addition, it is now possible to use custom protein-related data by using the SBML format and get a view of predicted protein localizations mapped onto a virtual cell model.

Permanent proteins in the urine of healthy humans during the Mars-500 experiment

Urinary proteins serve as indicators of various conditions in human normal physiology and disease pathology. Using mass spectrometry proteome analysis, the permanent constituent of the urine was examined in the Mars-500 experiment (520 days isolation of healthy volunteers in a terrestrial complex with an autonomous life support system). Seven permanent proteins with predominant distribution in the liver and blood plasma as well as extracellular localization were identified. Analysis of the overrepresentation of the molecular functions and biological processes based on Gene Ontology revealed that the functional association among these proteins was low. The results showed that the identified proteins may be independent markers of the various conditions and processes in healthy humans and that they can be used as standards in determination of the concentration of other proteins in the urine.

The substitutions G245C and G245D in the Zn(2+)-binding pocket of the p53 protein result in differences of conformational flexibility of the DNA-binding domain.

Transcription activation of the proapoptotic target genes is a means by which the p53 protein implements its function of tumor suppression. Zn2+ is a known regulator of p53 binding to the target genes. We have previously obtained an evidence that amino acid substitutions in the p53 Zn2+-binding pocket can presumably exert an influence on Zn2+ position in the Zn2+-p53 complex and thereby affect p53 binding to DNA. With these background considerations, our aim was to estimate the effect of the putative changes in the Zn2+ position in its binding pocket due to the G245C and G245D substitutions on the conformation of the p53 DNA-binding motif. Statistical analysis of the molecular dynamics (MD) trajectories of the mutant p53-Zn2+ complexes was used to detect significant deviations in conformation of the mutant p53 forms. MD simulations demonstrated that (1) the two substitutions in the Zn2+-binding pocket caused changes in the conformation of the p53 DNA-binding motif, as compared with the wild-type (WT) p53; (2) binding of Zn2+ to the p53 mutant forms reduced the effect of the substitutions on conformational change; and (3) Zn2+ binding in the normal position compensated the effect of the mutations on the conformation in comparison to the altered Zn2+ position.

Finding biomarkers in non-model species: literature mining of transcription factors involved in bovine embryo development

BackgroundSince processes in well-known model organisms have specific features different from those in Bos taurus, the organism under study, a good way to describe gene regulation in ruminant embryos would be a species-specific consideration of closely related species to cattle, sheep and pig. However, as highlighted by a recent report, gene dictionaries in pig are smaller than in cattle, bringing a risk to reduce the gene resources to be mined (and so for sheep dictionaries). Bioinformatics approaches that allow an integration of available information on gene function in model organisms, taking into account their specificity, are thus needed. Besides these closely related and biologically relevant species, there is indeed much more knowledge of (i) trophoblast proliferation and differentiation or (ii) embryogenesis in human and mouse species, which provides opportunities for reconstructing proliferation and/or differentiation processes in other mammalian embryos, including ruminants. The necessary knowledge can be obtained partly from (i) stem cell or cancer research to supply useful information on molecular agents or molecular interactions at work in cell proliferation and (ii) mouse embryogenesis to supply useful information on embryo differentiation. However, the total number of publications for all these topics and species is great and their manual processing would be tedious and time consuming. This is why we used text mining for automated text analysis and automated knowledge extraction. To evaluate the quality of this “mining”, we took advantage of studies that reported gene expression profiles during the elongation of bovine embryos and defined a list of transcription factors (or TF, n = 64) that we used as biological “gold standard”. When successful, the “mining” approach would identify them all, as well as novel ones.MethodsTo gain knowledge on molecular-genetic regulations in a non model organism, we offer an approach based on literature-mining and score arrangement of data from model organisms. This approach was applied to identify novel transcription factors during bovine blastocyst elongation, a process that is not observed in rodents and primates. As a result, searching through human and mouse corpuses, we identified numerous bovine homologs, among which 11 to 14% of transcription factors including the gold standard TF as well as novel TF potentially important to gene regulation in ruminant embryo development. The scripts of the workflow are written in Perl and available on demand. They require data input coming from all various databases for any kind of biological issue once the data has been prepared according to keywords for the studied topic and species; we can provide data sample to illustrate the use and functionality of the workflow.ResultsTo do so, we created a workflow that allowed the pipeline processing of literature data and biological data, extracted from Web of Science (WoS) or PubMed but also from Gene Expression Omnibus (GEO), Gene Ontology (GO), Uniprot, HomoloGene, TcoF-DB and TFe (TF encyclopedia). First, the human and mouse homologs of the bovine proteins were selected, filtered by text corpora and arranged by score functions. The score functions were based on the gene name frequencies in corpora. Then, transcription factors were identified using TcoF-DB and double-checked using TFe to characterise TF groups and families. Thus, among a search space of 18,670 bovine homologs, 489 were identified as transcription factors. Among them, 243 were absent from the high-throughput data available at the time of the study. They thus stand so far for putative TF acting during bovine embryo elongation, but might be retrieved from a recent RNA sequencing dataset (Mamo et al. , 2012). Beyond the 246 TF that appeared expressed in bovine elongating tissues, we restricted our interpretation to those occurring within a list of 50 top-ranked genes. Among the transcription factors identified therein, half belonged to the gold standard (ASCL2, c-FOS, ETS2, GATA3, HAND1) and half did not (ESR1, HES1, ID2, NANOG, PHB2, TP53, STAT3).ConclusionsA workflow providing search for transcription factors acting in bovine elongation was developed. The model assumed that proteins sharing the same protein domains in closely related species had the same protein functionalities, even if they were differently regulated among species or involved in somewhat different pathways. Under this assumption, we merged the information on different mammalian species from different databases (literature and biology) and proposed 489 TF as potential participants of embryo proliferation and differentiation, with (i) a recall of 95% with regard to a biological gold standard defined in 2011 and (ii) an extension of more than 3 times the gold standard of TF detected so far in elongating tissues. The working capacity of the workflow was supported by the manual expertise of the biologists on the results. The workflow can serve as a new kind of bioinformatics tool to work on fused data sources and can thus be useful in studies of a wide range of biological processes.