mulea: An R package for enrichment analysis using multiple ontologies and empirical false discovery rate.

Traditional gene set enrichment analyses are typically limited to a few ontologies and do not account for the interdependence of gene sets or terms, resulting in overcorrected p-values. To address these challenges, we introduce mulea, an R package offering comprehensive overrepresentation and functional enrichment analysis. mulea employs a progressive empirical false discovery rate (eFDR) method, specifically designed for interconnected biological data, to accurately identify significant terms within diverse ontologies. mulea expands beyond traditional tools by incorporating a wide range of ontologies, encompassing Gene Ontology, pathways, regulatory elements, genomic locations, and protein domains. This flexibility enables researchers to tailor enrichment analysis to their specific questions, such as identifying enriched transcriptional regulators in gene expression data or overrepresented protein domains in protein sets. To facilitate seamless analysis, mulea provides gene sets (in standardised GMT format) for 27 model organisms, covering 22 ontology types from 16 databases and various identifiers resulting in almost 900 files. Additionally, the muleaData ExperimentData Bioconductor package simplifies access to these pre-defined ontologies. Finally, mulea's architecture allows for easy integration of user-defined ontologies, or GMT files from external sources (e.g., MSigDB or Enrichr), expanding its applicability across diverse research areas. mulea is distributed as a CRAN R package downloadable from https://cran.r-project.org/web/packages/mulea/ and https://github.com/ELTEbioinformatics/mulea . It offers researchers a powerful and flexible toolkit for functional enrichment analysis, addressing limitations of traditional tools with its progressive eFDR and by supporting a variety of ontologies. Overall, mulea fosters the exploration of diverse biological questions across various model organisms.

Hippocampal extracellular matrix levels and stochasticity in synaptic protein expression increase with age and are associated with age-dependent cognitive decline.

Age-related cognitive decline is a serious health concern in our aging society. Decreased cognitive function observed during healthy brain aging is most likely caused by changes in brain connectivity and synaptic dysfunction in particular brain regions. Here we show that aged C57BL/6J wild-type mice have hippocampus-dependent spatial memory impairments. To identify the molecular mechanisms that are relevant to these memory deficits, we investigated the temporal profile of mouse hippocampal synaptic proteome changes at 20, 40, 50, 60, 70, 80, 90, and 100 weeks of age. Extracellular matrix proteins were the only group of proteins that showed robust and progressive up-regulation over time. This was confirmed by immunoblotting and histochemical analysis, which indicated that the increased levels of hippocampal extracellular matrix might limit synaptic plasticity as a potential cause of age-related cognitive decline. In addition, we observed that stochasticity in synaptic protein expression increased with age, in particular for proteins that were previously linked with various neurodegenerative diseases, whereas low variance in expression was observed for proteins that play a basal role in neuronal function and synaptic neurotransmission. Together, our findings show that both specific changes and increased variance in synaptic protein expression are associated with aging and may underlie reduced synaptic plasticity and impaired cognitive performance in old age.

Analysis of ELP4, SRPX2, and interacting genes in typical and atypical rolandic epilepsy.

Rolandic epilepsy (RE) and its atypical variants (atypical rolandic epilepsy, ARE) along the spectrum of epilepsy-aphasia disorders are characterized by a strong but largely unknown genetic basis. Two genes with a putative (ELP4) or a proven (SRPX2) function in neuronal migration were postulated to confer susceptibility to parts of the disease spectrum: the ELP4 gene to centrotemporal spikes and SRPX2 to ARE. To reexamine these findings, we investigated a cohort of 280 patients of European ancestry with RE/ARE for the etiological contribution of these genes and their close interaction partners. We performed next-generation sequencing and single-nucleotide polymorphism (SNP)-array based genotyping to screen for sequence and structural variants. In comparison to European controls we could not detect an enrichment of rare deleterious variants of ELP4, SRPX2, or their interaction partners in affected individuals. The previously described functional p.N327S variant in the X chromosomal SRPX2 gene was detected in two affected individuals (0.81%) and also in controls (0.26%), with some preponderance of male patients. We did not detect an association of SNPs in the ELP4 gene with centrotemporal spikes as previously reported. In conclusion our data do not support a major role of ELP4 and SRPX2 in the etiology of RE/ARE.

Ligand binding properties of human galanin receptors.

The galanin receptor family comprises of three members, GalR1, GalR2 and GalR3, all belonging to the G-protein-couple receptor superfamily. All three receptors bind the peptide hormone galanin, but show distinctly different binding properties to other molecules and effects on intracellular signaling. To gain insight on the molecular basis of receptor subtype specificity, we have generated a three-dimensional model for each of the galanin receptors based on its homologs in the same family. We found significant differences in the organization of the binding pockets among the three types of receptors, which might be the key for specific molecular recognition of ligands. Through docking of fragments of the galanin peptide and a number of ligands, we investigated the involvement of transmembrane and loop residues in ligand interaction.

The C-terminal cavity of the Na,K-ATPase analyzed by docking and electrophysiology.

The Na,K-ATPase is essential to all animals, since it maintains the electrochemical gradients that energize the plasma membrane. Naturally occurring inhibitors of the pump from plants have been used pharmaceutically in cardiac treatment for centuries. The inhibitors block the pump by binding on its extracellular side and thereby locking it. To explore the possibilities for designing an alternative way of targeting the pump function, we have examined the structural requirements for binding to a pocket that accommodates the two C-terminal residues, YY, in the crystal structures of the pump. To cover the sample space of two residues, we first performed docking studies with the 400 possible dipeptides. For validation of the in silico predictions, pumps with 13 dipeptide sequences replacing the C-terminal YY were expressed in Xenopus laevis oocytes and examined with electrophysiology. Our data show a significant correlation between the docking scores from two different methods and the experimentally determined sodium affinities, which strengthens the previous hypothesis that sodium binding is coupled to docking of the C-terminus. From the dipeptides that dock the best and better than wild-type YY, it may therefore be possible to develop specific drugs targeting a previously unexplored binding pocket in the sodium pump.

The complement regulator CD46 is bactericidal to Helicobacter pylori and blocks urease activity.

BACKGROUND & AIMS: CD46 is a C3b/C4b binding complement regulator and a receptor for several human pathogens. We examined the interaction between CD46 and Helicobacter pylori (a bacterium that colonizes the human gastric mucosa and causes gastritis), peptic ulcers, and cancer. METHODS: Using gastric epithelial cells, we analyzed a set of H pylori strains and mutants for their ability to interact with CD46 and/or influence CD46 expression. Bacterial interaction with full-length CD46 and small CD46 peptides was evaluated by flow cytometry, fluorescence microscopy, enzyme-linked immunosorbent assay, and bacterial survival analyses. RESULTS: H pylori infection caused shedding of CD46 into the extracellular environment. A soluble form of CD46 bound to H pylori and inhibited growth, in a dose- and time-dependent manner, by interacting with urease and alkyl hydroperoxide reductase, which are essential bacterial pathogenicity-associated factors. Binding of CD46 or CD46-derived synthetic peptides blocked the urease activity and ability of bacteria to survive in acidic environments. Oral administration of one CD46 peptide eradicated H pylori from infected mice. CONCLUSIONS: CD46 is an antimicrobial agent that can eradicate H pylori. CD46 peptides might be developed to treat H pylori infection.

Intermediates in the protein folding process: a computational model.

The paper presents a model for simulating the protein folding process in silico. The two-step model (which consists of the early stage-ES and the late stage-LS) is verified using two proteins, one of which is treated (according to experimental observations) as the early stage and the second as an example of the LS step. The early stage is based solely on backbone structural preferences, while the LS model takes into account the water environment, treated as an external hydrophobic force field and represented by a 3D Gauss function. The characteristics of 1ZTR (the ES intermediate, as compared with 1ENH, which is the LS intermediate) confirm the link between the gradual disappearance of ES characteristics in LS structural forms and the simultaneous emergence of LS properties in the 1ENH protein. Positive verification of ES and LS characteristics in these two proteins (1ZTR and 1ENH respectively) suggest potential applicability of the presented model to in silico protein folding simulations.

Prediction of functional sites based on the fuzzy oil drop model.

A description of many biological processes requires knowledge of the 3-D structure of proteins and, in particular, the defined active site responsible for biological function. Many proteins, the genes of which have been identified as the result of human genome sequencing, and which were synthesized experimentally, await identification of their biological activity. Currently used methods do not always yield satisfactory results, and new algorithms need to be developed to recognize the localization of active sites in proteins. This paper describes a computational model that can be used to identify potential areas that are able to interact with other molecules (ligands, substrates, inhibitors, etc.). The model for active site recognition is based on the analysis of hydrophobicity distribution in protein molecules. It is shown, based on the analyses of proteins with known biological activity and of proteins of unknown function, that the region of significantly irregular hydrophobicity distribution in proteins appears to be function related.

Effect of Cabbage Wraps on the Reduction of Post-Traumatic Knee Exudates in Men.

OBJECTIVES: The study investigates measurable effects of cabbage leaf wraps on post-traumatic knee injury exudate absorption in men. DESIGN: Case-control experiment on the same group of patients (before and after treatment). SETTINGS/LOCATION: One academic center and two hospitals. SUBJECTS: The study was carried out on a group of patients with different degrees of injury severity in the acute stage of the knee injury who were divided into three groups based on the width of suprapatellar recess gap (3-5 mm in group 1, 6-10 mm in group 2, and 11 mm or more in group 3) as assessed by ultrasonography. INTERVENTIONS: Each group of patients was divided into two subgroups, one of which comprised patients whose knees were treated with wraps containing cabbage leaves with ice (cases) and the others comprised patients treated with wraps without cabbage leaves, with cooling dressing only (controls). RESULTS: Significant progression in knee fluid uptake was observed in the acute stage of the knee injuries treated with cabbage wraps compared with control groups (p < 0.05). It was shown that the time, type of wraps, and a degree of severity of post-traumatic exudative knee inflammation affect the process of knee recovery (Friedman test for repeated measures p < 0.05). The most significant results were observed within first 24 h after the injury. Further decrease in the width of the recess gap after 5 days was observed. CONCLUSIONS: Application of cabbage wraps with ice to the knee in men may promote a reduction of swelling (by accelerating absorption of knee exudates) if applied during the acute stage of the knee injury.

Exome-wide analysis of mutational burden in patients with typical and atypical Rolandic epilepsy.

Rolandic epilepsy (RE) is the most common focal epilepsy in childhood. To date no hypothesis-free exome-wide mutational screen has been conducted for RE and atypical RE (ARE). Here we report on whole-exome sequencing of 194 unrelated patients with RE/ARE and 567 ethnically matched population controls. We identified an exome-wide significantly enriched burden for deleterious and loss-of-function variants only for the established RE/ARE gene GRIN2A. The statistical significance of the enrichment disappeared after removing ARE patients. For several disease-related gene-sets, an odds ratio >1 was detected for loss-of-function variants.

Rare coding variants in genes encoding GABAA receptors in genetic generalised epilepsies: an exome-based case-control study.

BACKGROUND: Genetic generalised epilepsy is the most common type of inherited epilepsy. Despite a high concordance rate of 80% in monozygotic twins, the genetic background is still poorly understood. We aimed to investigate the burden of rare genetic variants in genetic generalised epilepsy. METHODS: For this exome-based case-control study, we used three different genetic generalised epilepsy case cohorts and three independent control cohorts, all of European descent. Cases included in the study were clinically evaluated for genetic generalised epilepsy. Whole-exome sequencing was done for the discovery case cohort, a validation case cohort, and two independent control cohorts. The replication case cohort underwent targeted next-generation sequencing of the 19 known genes encoding subunits of GABAA receptors and was compared to the respective GABAA receptor variants of a third independent control cohort. Functional investigations were done with automated two-microelectrode voltage clamping in Xenopus laevis oocytes. FINDINGS: Statistical comparison of 152 familial index cases with genetic generalised epilepsy in the discovery cohort to 549 ethnically matched controls suggested an enrichment of rare missense (Nonsyn) variants in the ensemble of 19 genes encoding GABAA receptors in cases (odds ratio [OR] 2·40 [95% CI 1·41-4·10]; pNonsyn=0·0014, adjusted pNonsyn=0·019). Enrichment for these genes was validated in a whole-exome sequencing cohort of 357 sporadic and familial genetic generalised epilepsy cases and 1485 independent controls (OR 1·46 [95% CI 1·05-2·03]; pNonsyn=0·0081, adjusted pNonsyn=0·016). Comparison of genes encoding GABAA receptors in the independent replication cohort of 583 familial and sporadic genetic generalised epilepsy index cases, based on candidate-gene panel sequencing, with a third independent control cohort of 635 controls confirmed the overall enrichment of rare missense variants for 15 GABAA receptor genes in cases compared with controls (OR 1·46 [95% CI 1·02-2·08]; pNonsyn=0·013, adjusted pNonsyn=0·027). Functional studies for two selected genes (GABRB2 and GABRA5) showed significant loss-of-function effects with reduced current amplitudes in four of seven tested variants compared with wild-type receptors. INTERPRETATION: Functionally relevant variants in genes encoding GABAA receptor subunits constitute a significant risk factor for genetic generalised epilepsy. Examination of the role of specific gene groups and pathways can disentangle the complex genetic architecture of genetic generalised epilepsy. FUNDING: EuroEPINOMICS (European Science Foundation through national funding organisations), Epicure and EpiPGX (Sixth Framework Programme and Seventh Framework Programme of the European Commission), Research Unit FOR2715 (German Research Foundation and Luxembourg National Research Fund).

Increased transcriptional and metabolic capacity for lipid metabolism in the peripheral zone of the prostate may underpin its increased susceptibility to cancer.

The human prostate gland comprises three distinct anatomical glandular zones, namely the peripheral, central and transitional zones. Although prostate cancer can arise throughout the prostate, it is more frequent in the peripheral zone. In contrast, hyperplasia occurs most frequently in the transitional zone. In this paper, we test the hypothesis that peripheral and transitional zones have distinct metabolic adaptations that may underlie their different inherent predispositions to cancer and hyperplasia. In order to do this, we undertook RNA sequencing and high-throughput metabolic analyses of non-cancerous tissue from the peripheral and transitional zones of patients undergoing prostatectomy. Integrated analysis of RNAseq and metabolomic data revealed that transcription of genes involved in lipid biosynthesis is higher in the peripheral zone, which was mirrored by an increase in fatty acid metabolites, such as lysolipids. The peripheral zone also exhibited increased fatty acid catabolic activity and contained higher level of neurotransmitters. Such increased capacity for de novo lipogenesis and fatty acid oxidation, which is characteristic of prostate cancer, can potentially provide a permissive growth environment within the peripheral zone for cancer growth and also transmit a metabolic growth advantage to newly emerging clones themselves. This lipo-rich priming may explain the observed susceptibility of the peripheral zone to oncogenesis.

Introducing the Brassica Information Portal: Towards integrating genotypic and phenotypic Brassica crop data.

The Brassica Information Portal (BIP) is a centralised repository for brassica phenotypic data. The site hosts trait data associated with brassica research and breeding experiments conducted on brassica crops, that are used as oilseeds, vegetables, livestock forage and fodder and for biofuels. A key feature is the explicit management of meta-data describing the provenance and relationships between experimental plant materials, as well as trial design and trait descriptors. BIP is an open access and open source project, built on the schema of CropStoreDB, and as such can provide trait data management strategies for any crop data. A new user interface and programmatic submission/retrieval system helps to simplify data access for researchers, breeders and other end-users. BIP opens up the opportunity to apply integrative, cross-project analyses to data generated by the Brassica Research Community. Here, we present a short description of the current status of the repository.

ONION: Functional Approach for Integration of Lipidomics and Transcriptomics Data.

To date, the massive quantity of data generated by high-throughput techniques has not yet met bioinformatics treatment required to make full use of it. This is partially due to a mismatch in experimental and analytical study design but primarily due to a lack of adequate analytical approaches. When integrating multiple data types e.g. transcriptomics and metabolomics, multidimensional statistical methods are currently the techniques of choice. Typical statistical approaches, such as canonical correlation analysis (CCA), that are applied to find associations between metabolites and genes are failing due to small numbers of observations (e.g. conditions, diet etc.) in comparison to data size (number of genes, metabolites). Modifications designed to cope with this issue are not ideal due to the need to add simulated data resulting in a lack of p-value computation or by pruning of variables hence losing potentially valid information. Instead, our approach makes use of verified or putative molecular interactions or functional association to guide analysis. The workflow includes dividing of data sets to reach the expected data structure, statistical analysis within groups and interpretation of results. By applying pathway and network analysis, data obtained by various platforms are grouped with moderate stringency to avoid functional bias. As a consequence CCA and other multivariate models can be applied to calculate robust statistics and provide easy to interpret associations between metabolites and genes to leverage understanding of metabolic response. Effective integration of lipidomics and transcriptomics is demonstrated on publically available murine nutrigenomics data sets. We are able to demonstrate that our approach improves detection of genes related to lipid metabolism, in comparison to applying statistics alone. This is measured by increased percentage of explained variance (95% vs. 75-80%) and by identifying new metabolite-gene associations related to lipid metabolism.

DNA microarray integromics analysis platform.

BACKGROUND: The study of interactions between molecules belonging to different biochemical families (such as lipids and nucleic acids) requires specialized data analysis methods. This article describes the DNA Microarray Integromics Analysis Platform, a unique web application that focuses on computational integration and analysis of "multi-omics" data. Our tool supports a range of complex analyses, including - among others - low- and high-level analyses of DNA microarray data, integrated analysis of transcriptomics and lipidomics data and the ability to infer miRNA-mRNA interactions. RESULTS: We demonstrate the characteristics and benefits of the DNA Microarray Integromics Analysis Platform using two different test cases. The first test case involves the analysis of the nutrimouse dataset, which contains measurements of the expression of genes involved in nutritional problems and the concentrations of hepatic fatty acids. The second test case involves the analysis of miRNA-mRNA interactions in polysaccharide-stimulated human dermal fibroblasts infected with porcine endogenous retroviruses. CONCLUSIONS: The DNA Microarray Integromics Analysis Platform is a web-based graphical user interface for "multi-omics" data management and analysis. Its intuitive nature and wide range of available workflows make it an effective tool for molecular biology research. The platform is hosted at https://lifescience.plgrid.pl/.

Polycomb repressive complex PRC1 spatially constrains the mouse embryonic stem cell genome.

The Polycomb repressive complexes PRC1 and PRC2 maintain embryonic stem cell (ESC) pluripotency by silencing lineage-specifying developmental regulator genes. Emerging evidence suggests that Polycomb complexes act through controlling spatial genome organization. We show that PRC1 functions as a master regulator of mouse ESC genome architecture by organizing genes in three-dimensional interaction networks. The strongest spatial network is composed of the four Hox gene clusters and early developmental transcription factor genes, the majority of which contact poised enhancers. Removal of Polycomb repression leads to disruption of promoter-promoter contacts in the Hox gene network. In contrast, promoter-enhancer contacts are maintained in the absence of Polycomb repression, with accompanying widespread acquisition of active chromatin signatures at network enhancers and pronounced transcriptional upregulation of network genes. Thus, PRC1 physically constrains developmental transcription factor genes and their enhancers in a silenced but poised spatial network. We propose that the selective release of genes from this spatial network underlies cell fate specification during early embryonic development.

Conformational subspace in simulation of early-stage protein folding.

A probability calculus was used to simulate the early stages of protein folding in ab initio structure prediction. The probabilities of particular phi and psi angles for each of 20 amino acids as they occur in crystal forms of proteins were used to calculate the amount of information necessary for the occurrence of given phi and psi angles to be predicted. It was found that the amount of information needed to predict phi and psi angles with 5 degrees precision is much higher than the amount of information actually carried by individual amino acids in the polypeptide chain. To handle this problem, a limited conformational space for the preliminary search for optimal polypeptide structure is proposed based on a simplified geometrical model of the polypeptide chain and on the probability calculus. These two models, geometric and probabilistic, based on different sources, yield a common conclusion concerning how a limited conformational space can represent an early stage of polypeptide chain-folding simulation. The ribonuclease molecule was used to test the limited conformational space as a tool for modeling early-stage folding.

Integrating pathways of Parkinson's disease in a molecular interaction map.

Parkinson's disease (PD) is a major neurodegenerative chronic disease, most likely caused by a complex interplay of genetic and environmental factors. Information on various aspects of PD pathogenesis is rapidly increasing and needs to be efficiently organized, so that the resulting data is available for exploration and analysis. Here we introduce a computationally tractable, comprehensive molecular interaction map of PD. This map integrates pathways implicated in PD pathogenesis such as synaptic and mitochondrial dysfunction, impaired protein degradation, alpha-synuclein pathobiology and neuroinflammation. We also present bioinformatics tools for the analysis, enrichment and annotation of the map, allowing the research community to open new avenues in PD research. The PD map is accessible at http://minerva.uni.lu/pd_map .

Detecting cellular reprogramming determinants by differential stability analysis of gene regulatory networks.

BACKGROUND: Cellular differentiation and reprogramming are processes that are carefully orchestrated by the activation and repression of specific sets of genes. An increasing amount of experimental results show that despite the large number of genes participating in transcriptional programs of cellular phenotypes, only few key genes, which are coined here as reprogramming determinants, are required to be directly perturbed in order to induce cellular reprogramming. However, identification of reprogramming determinants still remains a combinatorial problem, and the state-of-art methods addressing this issue rests on exhaustive experimentation or prior knowledge to narrow down the list of candidates. RESULTS: Here we present a computational method, without any preliminary selection of candidate genes, to identify reduced subsets of genes, which when perturbed can induce transitions between cellular phenotypes. The method relies on the expression profiles of two stable cellular phenotypes along with a topological analysis stability elements in the gene regulatory network that are necessary to cause this multi-stability. Since stable cellular phenotypes can be considered as attractors of gene regulatory networks, cell fate and cellular reprogramming involves transition between these attractors, and therefore current method searches for combinations of genes that are able to destabilize a specific initial attractor and stabilize the final one in response to the appropriate perturbations. CONCLUSIONS: The method presented here represents a useful framework to assist researchers in the field of cellular reprogramming to design experimental strategies with potential applications in the regenerative medicine and disease modelling.

Fuzzy oil drop model to interpret the structure of antifreeze proteins and their mutants.

Mutations in proteins introduce structural changes and influence biological activity: the specific effects depend on the location of the mutation. The simple method proposed in the present paper is based on a two-step model of in silico protein folding. The structure of the first intermediate is assumed to be determined solely by backbone conformation. The structure of the second one is assumed to be determined by the presence of a hydrophobic center. The comparable structural analysis of the set of mutants is performed to identify the mutant-induced structural changes. The changes of the hydrophobic core organization measured by the divergence entropy allows quantitative comparison estimating the relative structural changes upon mutation. The set of antifreeze proteins, which appeared to represent the hydrophobic core structure accordant with "fuzzy oil drop" model was selected for analysis.