Int J Mol Sci

Phage-displayed peptide selections generate complex repertoires of several hundred thousand peptides as revealed by next-generation sequencing (NGS). In repeated peptide selections, however, even in identical experimental in vitro conditions, only a very small number of common peptides are found. The repertoire complexities are evidence of the difficulty of distinguishing between effective selections of specific peptide binders to exposed targets and the potential high background noise. Such investigation is even more relevant when considering the plethora of in vivo expressed targets on cells, in organs or in the entire organism to define targeting peptide agents. In the present study, we compare the published NGS data of three peptide repertoires that were obtained by phage display under identical experimental in vitro conditions. By applying the recently developed tool PepSimili we evaluate the calculated similarities of the individual peptides from each of these three repertoires and perform their mappings on the human proteome. The peptide-to-peptide mappings reveal high similarities among the three repertoires, confirming the desired reproducibility of phage-displayed peptide selections

ANASTASIA: An Automated Metagenomic Analysis Pipeline for Novel Enzyme Discovery Exploiting Next Generation Sequencing Data

Metagenomic analysis of environmental samples provides deep insight into the enzymatic mixture of the corresponding niches, capable of revealing peptide sequences with novel functional properties exploiting the high performance of next-generation sequencing (NGS) technologies. At the same time due to their ever increasing complexity, there is a compelling need for ever larger computational configurations to ensure proper bioinformatic analysis, and fine annotation. With the aiming to address the challenges of such an endeavor, we have developed a novel web-based application named ANASTASIA (automated nucleotide aminoacid sequences translational plAtform for systemic interpretation and analysis). ANASTASIA provides a rich environment of bioinformatic tools, either publicly available or novel, proprietary algorithms, integrated within numerous automated algorithmic workflows, and which enables versatile data processing tasks for (meta)genomic sequence datasets. ANASTASIA was initially developed in the framework of the European FP7 project HotZyme, whose aim was to perform exhaustive analysis of metagenomes derived from thermal springs around the globe and to discover new enzymes of industrial interest. ANASTASIA has evolved to become a stable and extensible environment for diversified, metagenomic, functional analyses for a range of applications overarching industrial biotechnology to biomedicine, within the frames of the ELIXIR-GR project. As a showcase, we report the successful in silico mining of a novel thermostable esterase termed “EstDZ4” from a metagenomic sample collected from a hot spring located in Krisuvik, Iceland

Decitabine-induced DNA methylation-mediated transcriptomic reprogramming in human breast cancer cell lines; the impact of DCK overexpression

Decitabine (DAC), a DNA methyltransferase (DNMT) inhibitor, is tested in combination with conventional anticancer drugs as a treatment option for various solid tumors. Although epigenome modulation provides a promising avenue in treating resistant cancer types, more studies are required to evaluate its safety and ability to normalize the aberrant transcriptional profiles. As deoxycytidine kinase (DCK)-mediated phosphorylation is a rate-limiting step in DAC metabolic activation, we hypothesized that its intracellular overexpression could potentiate DAC’s effect on cell methylome and thus increase its therapeutic efficacy. Therefore, two breast cancer cell lines, JIMT-1 and T-47D, differing in their molecular characteristics, were transfected with a DCK expression vector and exposed to low-dose DAC (approximately IC20). Although transfection resulted in a significant DCK expression increase, further enhanced by DAC exposure, no transfection-induced changes were found at the global DNA methylation level or in cell viability. In parallel, an integrative approach was applied to decipher DAC-induced, methylation-mediated, transcriptomic reprogramming. Besides large-scale hypomethylation, accompanied by up-regulation of gene expression across the entire genome, DAC also induced hypermethylation and down-regulation of numerous genes in both cell lines. Interestingly, TET1 and TET2 expression halved in JIMT-1 cells after DAC exposure, while DNMTs’ changes were not significant. The protein digestion and absorption pathway, containing numerous collagen and solute carrier genes, ranking second among membrane transport proteins, was the top enriched pathway in both cell lines when hypomethylated and up-regulated genes were considered. Moreover, the calcium signaling pathway, playing a significant role in drug resistance, was among the top enriched in JIMT-1 cells. Although low-dose DAC demonstrated its ability to normalize the expression of tumor suppressors, several oncogenes were also up-regulated, a finding, that supports previously raised concerns regarding its broad reprogramming potential. Importantly, our research provides evidence about the involvement of active demethylation in DAC-mediated transcriptional reprogramming.publishedVersio

Decitabine potentiates efficacy of doxorubicin in a preclinical trastuzumab-resistant HER2-positive breast cancer models

Acquired drug resistance and metastasis in breast cancer (BC) are coupled with epigenetic deregulation of gene expression. Epigenetic drugs, aiming to reverse these aberrant transcriptional patterns and sensitize cancer cells to other therapies, provide a new treatment strategy for drug-resistant tumors. Here we investigated the ability of DNA methyltransferase (DNMT) inhibitor decitabine (DAC) to increase the sensitivity of BC cells to anthracycline antibiotic doxorubicin (DOX). Three cell lines representing different molecular BC subtypes, JIMT-1, MDA-MB-231 and T-47D, were used to evaluate the synergy of sequential DAC + DOX treatment in vitro. The cytotoxicity, genotoxicity, apoptosis, and migration capacity were tested in 2D and 3D cultures. Moreover, genome-wide DNA methylation and transcriptomic analyses were employed to understand the differences underlying DAC responsiveness. The ability of DAC to sensitize trastuzumab-resistant HER2-positive JIMT-1 cells to DOX was examined in vivo in an orthotopic xenograft mouse model. DAC and DOX synergistic effect was identified in all tested cell lines, with JIMT-1 cells being most sensitive to DAC. Based on the whole-genome data, we assume that the aggressive behavior of JIMT-1 cells can be related to the enrichment of epithelial-to-mesenchymal transition and stemness-associated pathways in this cell line. The four-week DAC + DOX sequential administration significantly reduced the tumor growth, DNMT1 expression, and global DNA methylation in xenograft tissues. The efficacy of combination therapy was comparable to effect of pegylated liposomal DOX, used exclusively for the treatment of metastatic BC. This work demonstrates the potential of epigenetic drugs to modulate cancer cells' sensitivity to other forms of anticancer therapy.publishedVersio

Escherichia coli genome-wide promoter analysis: Identification of additional AtoC binding target elements

<p>Abstract</p> <p>Background</p> <p>Studies on bacterial signal transduction systems have revealed complex networks of functional interactions, where the response regulators play a pivotal role. The AtoSC system of <it>E. coli </it>activates the expression of <it>atoDAEB </it>operon genes, and the subsequent catabolism of short-chain fatty acids, upon acetoacetate induction. Transcriptome and phenotypic analyses suggested that <it>atoSC </it>is also involved in several other cellular activities, although we have recently reported a palindromic repeat within the <it>atoDAEB </it>promoter as the single, <it>cis</it>-regulatory binding site of the AtoC response regulator. In this work, we used a computational approach to explore the presence of yet unidentified AtoC binding sites within other parts of the <it>E. coli </it>genome.</p> <p>Results</p> <p>Through the implementation of a computational <it>de novo </it>motif detection workflow, a set of candidate motifs was generated, representing putative AtoC binding targets within the <it>E. coli </it>genome. In order to assess the biological relevance of the motifs and to select for experimental validation of those sequences related robustly with distinct cellular functions, we implemented a novel approach that applies Gene Ontology Term Analysis to the motif hits and selected those that were qualified through this procedure. The computational results were validated using Chromatin Immunoprecipitation assays to assess the <it>in vivo </it>binding of AtoC to the predicted sites. This process verified twenty-two additional AtoC binding sites, located not only within intergenic regions, but also within gene-encoding sequences.</p> <p>Conclusions</p> <p>This study, by tracing a number of putative AtoC binding sites, has indicated an AtoC-related cross-regulatory function. This highlights the significance of computational genome-wide approaches in elucidating complex patterns of bacterial cell regulation.</p

Control of anterior GRadient 2 (AGR2) dimerization links endoplasmic reticulum proteostasis to inflammation

International audienceAnterior gradient 2 (AGR2) is a dimeric protein disulfide isomerase family member involved in the regulation of protein quality control in the endoplasmic reticulum (ER). Mouse AGR2 deletion increases intestinal inflammation and promotes the development of inflammatory bowel disease (IBD). Although these biological effects are well established, the underlying molecular mechanisms of AGR2 function toward inflammation remain poorly defined. Here, using a protein-protein interaction screen to identify cellular regulators of AGR2 dimerization, we unveiled specific enhancers, including TMED2, and inhibitors of AGR2 dimerization, that control AGR2 functions. We demonstrate that modulation of AGR2 dimer formation, whether enhancing or inhibiting the process, yields pro-inflammatory phenotypes, through either autophagy-dependent processes or secretion of AGR2, respectively. We also demonstrate that in IBD and specifically in Crohn's disease, the levels of AGR2 dimerization modulators are selectively deregulated, and this correlates with severity of disease. Our study demonstrates that AGR2 dimers act as sensors of ER homeostasis which are disrupted upon ER stress and promote the secretion of AGR2 monomers. The latter might represent systemic alarm signals for pro-inflammatory responses

Application of systems biology methods to the study of the regulatory mechanisms of organisms with biotechnological interest

The scope of the present thesis is the study of regulatory mechanisms of two organisms of great biotechnological interest, the plant rapeseed and the bacterium Escherichia coli, by applying Systems Biology methodologies. In order to understand a biological mechanism as a system, it is necessary to examine the biological structures and their dynamic properties in a holistic manner and in different levels of organization (genomic, cellular, tissue etc.), instead of investigating the properties of isolated components. Firstly, the development of a large-scale computational model is presented, which describes the central metabolism of the rapeseed embryo (Brassica napus) that is considered as a cellular factory of production of oil with high added value. The computational modeling permits the simulation of the systematic application of perturbations and the subsequent investigation of their effect. The developed computational model was subjected to mathematical methods for complexity reduction in order to reduce the metabolic network properties to a small number of important regulatory reactions. Therefore, the quantification of the regulatory role of the enzymatic activities was achieved, resulting to the highlight of the most important potential enzymatic targets for the regulation of metabolism, with emphasis to lipid biosynthesis. The computational simulations of seed development were consistent with experimental measurements from the literature and they hence confirmed the model functionality as well as its usefulness to the study of the regulatory role of transcription factors. Further, potential enzymatic targets for lipid biosynthesis regulation were investigated by applying computational simulations of genetic modifications. In the second part, a computational procedure is presented, which performs automatic detection of transcription factor binding sites in the level of the whole genome of the bacterium Escherichia coli. The transcription factors are the main mechanism of gene expression regulation and signal transduction in the cell. A particular category of transcription factors, the response regulators, control the transcriptional response of the bacterial cells to external environmental stimuli, as parts of Two-Component Systems. The study of these systems is important to Biotechnology as they are behind the molecular basis of main bacterial properties (chemiotaxis, resistance to antibiotics, biosynthesis of high added-value products etc). The developed computational procedure permits the automatic detection of multiple transcription factor binding sites and the subsequent statistical analysis of Gene Ontology Terms, in order to correlate the binding sites with biochemical pathways. The procedure was applied to the study of the Two-Component System AtoSC and detected many potential gene targets, 21 of which were experimentally confirmed. Thus, the presented computational procedure not only revealed the molecular basis of AtoSC functions, but it also represents an important contribution to the examination of networks of bacterial signal transduction regulatory mechanisms, by statistically correlating biological functions with weakly conserved regulatory DNA sequence

A Machine-Learning Approach for theof Enzymatic Activity of Proteins in Metagenomic Samples

Part 3: Medical Informatics and Biomedical EngineeringInternational audienceIn this work, a machine-learning approach was developed, which performs the prediction of the putative enzymatic function of unknown proteins, based on the PFAM protein domain database and the Enzyme Commission (EC) numbers that describe the enzymatic activities. The classifier was trained with well annotated protein datasets from the Uniprot database, in order to define the characteristic domains of each enzymatic sub-category in the class of Hydrolases. As a conclusion, the machine-learning procedure based on Hmmer3 scores against the PFAM database can accurately predict the enzymatic activity of unknown proteins as a part of metagenomic analysis workflows

Application of systems biology methods to the study of the regulatory mechanisms of organisms with biotechnological interest

147 σ.Αντικείμενο της παρούσης διδακτορικής διατριβής είναι η μελέτη των μηχανισμών ρύθμισης δυο οργανισμών βιοτεχνολογικού ενδιαφέροντος, του φυτού της ελαιοκράμβης και του βακτηρίου Escherichia coli, με μεθοδολογίες Βιολογίας Συστημάτων. Προκειμένου οι βιολογικοί μηχανισμοί να γίνουν κατανοητοί με την έννοια του συστήματος, είναι απαραίτητη η ολιστική εξέταση των βιολογικών δομών σε διάφορα επίπεδα οργάνωσης (γονιδιώματος, κυττάρου, ιστού κ.α.) καθώς και των δυναμικών ιδιοτήτων τους, αντί για τη μελέτη των χαρακτηριστικών των μεμονωμένων μερών ενός κυττάρου ή ενός οργανισμού. Αρχικά, παρουσιάζεται η ανάπτυξη υπολογιστικού μοντέλου μεγάλης κλίμακας του κεντρικού μεταβολισμού του εμβρύου της ελαιοκράμβης (Brassica napus) που θεωρείται κυτταρικό εργοστάσιο παραγωγής ελαίου υψηλής προστιθέμενης αξίας. Η ανάπτυξη μοντέλων για την εφαρμογή προσομοιώσεων επιτρέπει τη συστηματική εισαγωγή διαταραχών και συνεπακόλουθη μελέτη των επιπτώσεών τους. Στο υπολογιστικό μοντέλο εφαρμόστηκαν μαθηματικές μέθοδοι μείωσης της πολυπλοκότητας έτσι ώστε οι ιδιότητες του μεταβολικού δικτύου να αναχθούν σε μικρό αριθμό σημαντικών ρυθμιστικών αντιδράσεων. Συνεπώς, επετεύχθη η ποσοτικοποίηση του ρυθμιστικού ρόλου των ενζυμικών δραστικοτήτων και αναδείχθηκαν οι πιο σημαντικοί εν δυνάμει ενζυμικοί στόχοι για την ρύθμιση του μεταβολισμού, με έμφαση στη βιοσύνθεση των λιπιδίων. Οι υπολογιστικές προσομοιώσεις της ανάπτυξης του εμβρύου που πραγματοποιήθηκαν, ήταν σύμφωνες με πειραματικές παρατηρήσεις από τη βιβλιογραφία και απέδειξαν τη λειτουργικότητα του μοντέλου αλλά και τη χρησιμότητά του για τη μελέτη του ρυθμιστικού ρόλου μεταγραφικών παραγόντων. Επίσης, πιθανοί ενζυμικοί στόχοι για την ρύθμιση της βιοσύνθεσης των λιπιδίων εξετάστηκαν μέσω της εφαρμογής υπολογιστικής προσομοίωσης γενετικών τροποποιήσεων. Στο δεύτερο μέρος της διατριβής παρουσιάζεται η ανάπτυξη μιας υπολογιστικής διαδικασίας πρόβλεψης στόχων μεταγραφικών παραγόντων, σε επίπεδο ολόκληρου γονιδιώματος του βακτηρίου Escherichia coli. Οι μεταγραφικοί παράγοντες αποτελούν το κύριο μέσο ρύθμισης της έκφρασης των γονιδίων και μετάδοσης σήματος στο κύτταρο. Μια κατηγορία μεταγραφικών παραγόντων, οι ρυθμιστές απόκρισης, αποτελούν μέρη των συστημάτων δυο συστατικών και ελέγχουν την μεταγραφική απόκριση των βακτηριακών κυττάρων στα εξωτερικά ερεθίσματα του περιβάλλοντος. Η μελέτη των συστημάτων δυο συστατικών παρουσιάζει ιδιαίτερο ενδιαφέρον στη Βιοτεχνολογία, καθώς αυτά αποτελούν τη μοριακή βάση μιας σειράς βασικών βακτηριακών ιδιοτήτων (χημειόταξη, αντίσταση στα αντιβιοτικά, βιοσύνθεση μεταβολικών προϊόντων υψηλής προστιθέμενης αξίας κ.α). Η υπολογιστική διαδικασία που αναπτύχθηκε στα πλαίσια της διατριβής επιτρέπει την αυτόματη ανίχνευση πολλαπλών θέσεων πρόσδεσης μεταγραφικών παραγόντων και συνεπακόλουθης στατιστικής ανάλυσης Όρων Γονιδιακών Οντολογιών, με σκοπό τη σύνδεση των θέσεων πρόσδεσης με βιοχημικά μονοπάτια. Η διαδικασία αυτή εφαρμόστηκε στη μελέτη του συστήματος δυο συστατικών AtoSC και ανέδειξε πιθανούς γονιδιακούς στόχους, εκ των οποίων 21 επιβεβαιώθηκαν και πειραματικά. Συνεπώς, η υπολογιστική διαδικασία που παρουσιάζεται, εκτός από την ανάδειξη της μοριακής βάσης λειτουργιών του AtoSC, αποτελεί συμβολή στη διαλεύκανση των πολύπλοκων δικτύων των βακτηριακών σηματοδοτικών μηχανισμών ρύθμισης, μέσω της στατιστικής σύνδεσης βιολογικών μονοπατιών με ελάχιστα διατηρημένες ρυθμιστικές αλληλουχίες DNA.The scope of the present thesis is the study of regulatory mechanisms of two organisms of great biotechnological interest, the plant rapeseed and the bacterium Escherichia coli, by applying Systems Biology methodologies. In order to understand a biological mechanism as a system, it is necessary to examine the biological structures and their dynamic properties in a holistic manner and in different levels of organization (genomic, cellular, tissue etc.), instead of investigating the properties of isolated components. Firstly, the development of a large-scale computational model is presented, which describes the central metabolism of the rapeseed embryo (Brassica napus) that is considered as a cellular factory of production of oil with high added value. The computational modeling permits the simulation of the systematic application of perturbations and the subsequent investigation of their effect. The developed computational model was subjected to mathematical methods for complexity reduction in order to reduce the metabolic network properties to a small number of important regulatory reactions. Therefore, the quantification of the regulatory role of the enzymatic activities was achieved, resulting to the highlight of the most important potential enzymatic targets for the regulation of metabolism, with emphasis to lipid biosynthesis. The computational simulations of seed development were consistent with experimental measurements from the literature and they hence confirmed the model functionality as well as its usefulness to the study of the regulatory role of transcription factors. Further, potential enzymatic targets for lipid biosynthesis regulation were investigated by applying computational simulations of genetic modifications. In the second part, a computational procedure is presented, which performs automatic detection of transcription factor binding sites in the level of the whole genome of the bacterium Escherichia coli. The transcription factors are the main mechanism of gene expression regulation and signal transduction in the cell. A particular category of transcription factors, the response regulators, control the transcriptional response of the bacterial cells to external environmental stimuli, as parts of Two-Component Systems. The study of these systems is important to Biotechnology as they are behind the molecular basis of main bacterial properties (chemiotaxis, resistance to antibiotics, biosynthesis of high added-value products etc). The developed computational procedure permits the automatic detection of multiple transcription factor binding sites and the subsequent statistical analysis of Gene Ontology Terms, in order to correlate the binding sites with biochemical pathways. The procedure was applied to the study of the Two-Component System AtoSC and detected many potential gene targets, 21 of which were experimentally confirmed. Thus, the presented computational procedure not only revealed the molecular basis of AtoSC functions, but it also represents an important contribution to the examination of networks of bacterial signal transduction regulatory mechanisms, by statistically correlating biological functions with weakly conserved regulatory DNA sequences.Ελευθέριος Δ. Πιλάλη

Comparative Evaluation of Reproducibility of Phage-Displayed Peptide Selections and NGS Data, through High-Fidelity Mapping of Massive Peptide Repertoires

Phage-displayed peptide selections generate complex repertoires of several hundred thousand peptides as revealed by next-generation sequencing (NGS). In repeated peptide selections, however, even in identical experimental in vitro conditions, only a very small number of common peptides are found. The repertoire complexities are evidence of the difficulty of distinguishing between effective selections of specific peptide binders to exposed targets and the potential high background noise. Such investigation is even more relevant when considering the plethora of in vivo expressed targets on cells, in organs or in the entire organism to define targeting peptide agents. In the present study, we compare the published NGS data of three peptide repertoires that were obtained by phage display under identical experimental in vitro conditions. By applying the recently developed tool PepSimili we evaluate the calculated similarities of the individual peptides from each of these three repertoires and perform their mappings on the human proteome. The peptide-to-peptide mappings reveal high similarities among the three repertoires, confirming the desired reproducibility of phage-displayed peptide selections