BraneMF: integration of biological networks for functional analysis of proteins.

MOTIVATION: The cellular system of a living organism is composed of interacting bio-molecules that control cellular processes at multiple levels. Their correspondences are represented by tightly regulated molecular networks. The increase of omics technologies has favored the generation of large-scale disparate data and the consequent demand for simultaneously using molecular and functional interaction networks: gene co-expression, protein-protein interaction (PPI), genetic interaction and metabolic networks. They are rich sources of information at different molecular levels, and their effective integration is essential to understand cell functioning and their building blocks (proteins). Therefore, it is necessary to obtain informative representations of proteins and their proximity, that are not fully captured by features extracted directly from a single informational level. We propose BraneMF, a novel random walk-based matrix factorization method for learning node representation in a multilayer network, with application to omics data integration. RESULTS: We test BraneMF with PPI networks of Saccharomyces cerevisiae, a well-studied yeast model organism. We demonstrate the applicability of the learned features for essential multi-omics inference tasks: clustering, function and PPI prediction. We compare it to the state-of-the-art integration methods for multilayer networks. BraneMF outperforms baseline methods by achieving high prediction scores for a variety of downstream tasks. The robustness of results is assessed by an extensive parameter sensitivity analysis. AVAILABILITY AND IMPLEMENTATION: BraneMF's code is freely available at: https://github.com/Surabhivj/BraneMF, along with datasets, embeddings and result files. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

BRANEnet: embedding multilayer networks for omics data integration.

BACKGROUND: Gene expression is regulated at different molecular levels, including chromatin accessibility, transcription, RNA maturation, and transport. These regulatory mechanisms have strong connections with cellular metabolism. In order to study the cellular system and its functioning, omics data at each molecular level can be generated and efficiently integrated. Here, we propose BRANENET, a novel multi-omics integration framework for multilayer heterogeneous networks. BRANENET is an expressive, scalable, and versatile method to learn node embeddings, leveraging random walk information within a matrix factorization framework. Our goal is to efficiently integrate multi-omics data to study different regulatory aspects of multilayered processes that occur in organisms. We evaluate our framework using multi-omics data of Saccharomyces cerevisiae, a well-studied yeast model organism. RESULTS: We test BRANENET on transcriptomics (RNA-seq) and targeted metabolomics (NMR) data for wild-type yeast strain during a heat-shock time course of 0, 20, and 120 min. Our framework learns features for differentially expressed bio-molecules showing heat stress response. We demonstrate the applicability of the learned features for targeted omics inference tasks: transcription factor (TF)-target prediction, integrated omics network (ION) inference, and module identification. The performance of BRANENET is compared to existing network integration methods. Our model outperforms baseline methods by achieving high prediction scores for a variety of downstream tasks.

Genome-Wide TSS Distribution in Three Related Clostridia with Normalized Capp-Switch Sequencing.

Transcription initiation is a tightly regulated process that is crucial for many aspects of prokaryotic physiology. High-throughput transcription start site (TSS) mapping can shed light on global and local regulation of transcription initiation, which in turn may help us understand and predict microbial behavior. In this study, we used Capp-Switch sequencing to determine the TSS positions in the genomes of three model solventogenic clostridia: Clostridium acetobutylicum ATCC 824, C. beijerinckii DSM 6423, and C. beijerinckii NCIMB 8052. We first refined the approach by implementing a normalization pipeline accounting for gene expression, yielding a total of 12,114 mapped TSSs across the species. We further compared the distributions of these sites in the three strains. Results indicated similar distribution patterns at the genome scale, but also some sharp differences, such as for the butyryl-CoA synthesis operon, particularly when comparing C. acetobutylicum to the C. beijerinckii strains. Lastly, we found that promoter structure is generally poorly conserved between C. acetobutylicum and C. beijerinckii. A few conserved promoters across species are discussed, showing interesting examples of how TSS determination and comparison can improve our understanding of gene expression regulation at the transcript level. IMPORTANCE Solventogenic clostridia have been employed in industry for more than a century, initially being used in the acetone-butanol-ethanol (ABE) fermentation process for acetone and butanol production. Interest in these bacteria has recently increased in the context of green chemistry and sustainable development. However, our current understanding of their genomes and physiology limits their optimal use as industrial solvent production platforms. The gene regulatory mechanisms of solventogenesis are still only partly understood, impeding efforts to increase rates and yields. Genome-wide mapping of transcription start sites (TSSs) for three model solventogenic Clostridium strains is an important step toward understanding mechanisms of gene regulation in these industrially important bacteria.

SWATH-MS based quantitative proteomics analysis to evaluate the antileishmanial effect of Commiphora wightii- Guggul and amphotericin B on a clinical isolate of Leishmania donovani.

Drug resistance and relapse after treatment of visceral leishmaniasis (VL) with the chemotherapeutic drugs has impeded the VL elimination programme especially, in the endemic region of Bihar, India. Currently, Antimonials (Sbv) have been rendered obsolete (Bihar) as frequent treatment failure and relapse in Sbv treated patient's warrants greater vigilance and attention to the limited drugs. A clinical isolate of L.donovani obtained from an Amphotericin B (AmB) relapse patient was evaluated for its susceptibility to AmB and a hyperlipidemic drug Guggul. The evaluation of susceptibility or resistance to any drug still relies on in vitro assay on promastigote and amastigote stages of Leishmania spp. as there are no validated markers which can ascertain drug resistance in Leishmania. The anti-promastigote effect of AmB and Guggul were demonstrated by significant cellular and morphological changes exhibiting apoptosis-mediated cell death. To further illustrate the molecular mechanism of the parasite's response upon exposure to either AmB and Guggul, sequential window acquisition of all theoretical fragment ion spectra mass spectrometry (SWATH-MS) for quantitative proteomics analysis was performed along with computational data analysis; revealing considerable differences in the proteome profiles which could be regarded as putative markers for resistance or drug targets for development of therapeutic antileishmanials.

Construction, analysis and validation of co-expression network to understand stress adaptation in Deinococcus radiodurans R1.

Systems biology based approaches have been effectively utilized to mine high throughput data. In the current study, we have performed system-level analysis for Deinococcus radiodurans R1 by constructing a gene co-expression network based on several microarray datasets available in the public domain. This condition-independent network was constructed by Weighted Gene Co-expression Network Analysis (WGCNA) with 61 microarray samples from 9 different experimental conditions. We identified 13 co-expressed modules, of which, 11 showed functional enrichments of one or more pathway/s or biological process. Comparative analysis of differentially expressed genes and proteins from radiation and desiccation stress studies with our co-expressed modules revealed the association of cyan with radiation response. Interestingly, two modules viz darkgreen and tan was associated with radiation as well as desiccation stress responses. The functional analysis of these modules showed enrichment of pathways important for adaptation of radiation or desiccation stress. To decipher the regulatory roles of these stress responsive modules, we identified transcription factors (TFs) and then calculated a Biweight mid correlation between modules hub gene and the identified TFs. We obtained 7 TFs for radiation and desiccation responsive modules. The expressions of 3 TFs were validated in response to gamma radiation using qRT-PCR. Along with the TFs, selected close neighbor genes of two important TFs, viz., DR_0997 (CRP) and DR_2287 (AsnC family transcriptional regulator) in the darkgreen module were also validated. In our network, among 13 hub genes associated with 13 modules, the functionality of 5 hub genes which are annotated as hypothetical proteins (hypothetical hub genes) in D. radiodurans genome has been revealed. Overall the study provided a better insight of pathways and regulators associated with relevant DNA damaging stress response in D. radiodurans.

SWATH-MS based quantitative proteomics analysis to evaluate the antileishmanial effect of Commiphora wightii- Guggul and Amphotericin B on a clinical isolate of Leishmania donovani.

The present study provides comprehensive proteomics analyses of the response of L. donovani parasite to pharamacological stress in vitro. Identification of differentially expressed proteins with associated molecular functions and metabolic pathways, clearly provides an insight into the potential mechanism of the antileishmanial effects as well as a comparative response of the parasite to Guggul and AmB. Treatment of parasite with AmB results in an enhanced modulatory mechanism to counteract the drug induced stress which may have contributed to relapse. In the case of Guggul treatment, an effective antipromastigote activity was observed, which is being reported for the first time. Thus, a deeper understanding of the molecular pathways in the Leishmania parasite in response to pharmacological stress would help in designing novel and effective strategies in targeting the key molecules essential for parasite survival. It will also help in screening of new lead molecules targeting these vital pathways which could be used as an adjunct therapy along with the limited repertoire of antileishmanial drugs.