Early Maternal Alcohol Consumption Alters Hippocampal DNA Methylation, Gene Expression and Volume in a Mouse Model

The adverse effects of alcohol consumption during pregnancy are known, but the molecular events that lead to the phenotypic characteristics are unclear. To unravel the molecular mechanisms, we have used a mouse model of gestational ethanol exposure, which is based on maternal ad libitum ingestion of 10% (v/v) ethanol for the first 8 days of gestation (GD 0.5-8.5). Early neurulation takes place by the end of this period, which is equivalent to the developmental stage early in the fourth week post-fertilization in human. During this exposure period, dynamic epigenetic reprogramming takes place and the embryo is vulnerable to the effects of environmental factors. Thus, we hypothesize that early ethanol exposure disrupts the epigenetic reprogramming of the embryo, which leads to alterations in gene regulation and life-long changes in brain structure and function. Genome-wide analysis of gene expression in the mouse hippocampus revealed altered expression of 23 genes and three miRNAs in ethanol-exposed, adolescent offspring at postnatal day (P) 28. We confirmed this result by using two other tissues, where three candidate genes are known to express actively. Interestingly, we found a similar trend of upregulated gene expression in bone marrow and main olfactory epithelium. In addition, we observed altered DNA methylation in the CpG islands upstream of the candidate genes in the hippocampus. Our MRI study revealed asymmetry of brain structures in ethanol-exposed adult offspring (P60): we detected ethanol-induced enlargement of the left hippocampus and decreased volume of the left olfactory bulb. Our study indicates that ethanol exposure in early gestation can cause changes in DNA methylation, gene expression, and brain structure of offspring. Furthermore, the results support our hypothesis of early epigenetic origin of alcohol-induced disorders: changes in gene regulation may have already taken place in embryonic stem cells and therefore can be seen in different tissue types later in life.Peer reviewe

Identification of genetic markers with synergistic survival effect in cancer

Peer reviewe

On computational properties of gene assembly in ciliates

Gene assembly in stichotrichous ciliates happening during sexual reproduction is one of the most involved DNA manipulation processes occurring in biology. This biological process is of high interest from the computational and mathematical points of view due to its close analogy with such concepts and notions in theoretical computer science as permutation and linked list sorting and string rewriting. Studies on computational properties of gene assembly in ciliates represent a good example of interdisciplinary research contributing to both computer science and biology. We review here a number of general results related both to the development of different computational methods enhancing our understanding on the nature of gene assembly, as well as to the development of new biologically motivated computational and mathematical models and paradigms. Those paradigms contribute in particular to combinatorics, formal languages and computability theories

Variants of Networks of Evolutionary Processors with Polarizations and a Small Number of Processors

International audienc

Solutions to Computational Problems through Gene Assembly

Gene assembly in ciliates is an impressive computational process. Ciliates have a unique way of storing their genetic information in two fundamentally different forms within their two types of nuclei. Micronuclear genes are broken into blocks (called MDSs), with MDSs shuffled and separated by non-coding material; some of the MDSs may even be inverted. During gene assembly, all MDSs are sorted in the correct order to yield the transcription-able macronuclear gene. Based on the intramolecular model for gene assembly, we prove in this paper that gene assembly may be used in principle to solve computational problems. We prove that any given instance of the hamiltonian path problem may be encoded in a suitable way in the form of an ‘artificial ’ gene so that gene assembly is successful on that gene-like pattern if and only if the given problem has an affirmative answer

Computational Completeness of Networks of Evolutionary Processors with Elementary Polarizations and a Small Number of Processors

Part 2: Contributed PapersInternational audienceWe improve previous results obtained for networks of evolutionary processors with elementary polarizations $-1,0,1$ by showing that only the very small number of seven processors is needed to obtain computational completeness. In the case of not requiring a special output node even only five processors are shown to be sufficient

Three models for gene assembly in ciliates: a comparison

We survey in this paper the main differences among three variants of an intramolecular model for gene assembly: the general, the simple, and the elementary models. We present all of them in terms of sorting signed permutations and compare their behavior with respect to: (i) completeness, (ii) confluence (with the notion defined in three different setups), (iii) decidability, (iv) characterization of the sortable permutations in each model, (v) sequential complexity, and (vi) experimental validation

NetControl4BioMed: a pipeline for biomedical data acquisition and analysis of network controllability

Abstract Background Network controllability focuses on discovering combinations of external interventions that can drive a biological system to a desired configuration. In practice, this approach translates into finding a combined multi-drug therapy in order to induce a desired response from a cell; this can lead to developments of novel therapeutic approaches for systemic diseases like cancer. Result We develop a novel bioinformatics data analysis pipeline called NetControl4BioMed based on the concept of target structural control of linear networks. Our pipeline generates novel molecular interaction networks by combining pathway data from various public databases starting from the user’s query. The pipeline then identifies a set of nodes that is enough to control a given, user-defined set of disease-specific essential proteins in the network, i.e., it is able to induce a change in their configuration from any initial state to any final state. We provide both the source code of the pipeline as well as an online web-service based on this pipeline http://combio.abo.fi/nc/net_control/remote_call.php. Conclusion The pipeline can be used by researchers for controlling and better understanding of molecular interaction networks through combinatorial multi-drug therapies, for more efficient therapeutic approaches and personalised medicine