Multi-omics Data Integration, Interpretation, and Its Application.

To study complex biological processes holistically, it is imperative to take an integrative approach that combines multi-omics data to highlight the interrelationships of the involved biomolecules and their functions. With the advent of high-throughput techniques and availability of multi-omics data generated from a large set of samples, several promising tools and methods have been developed for data integration and interpretation. In this review, we collected the tools and methods that adopt integrative approach to analyze multiple omics data and summarized their ability to address applications such as disease subtyping, biomarker prediction, and deriving insights into the data. We provide the methodology, use-cases, and limitations of these tools; brief account of multi-omics data repositories and visualization portals; and challenges associated with multi-omics data integration.

FusionHub: A unified web platform for annotation and visualization of gene fusion events in human cancer.

Gene fusion is a chromosomal rearrangement event which plays a significant role in cancer due to the oncogenic potential of the chimeric protein generated through fusions. At present many databases are available in public domain which provides detailed information about known gene fusion events and their functional role. Existing gene fusion detection tools, based on analysis of transcriptomics data usually report a large number of fusion genes as potential candidates, which could be either known or novel or false positives. Manual annotation of these putative genes is indeed time-consuming. We have developed a web platform FusionHub, which acts as integrated search engine interfacing various fusion gene databases and simplifies large scale annotation of fusion genes in a seamless way. In addition, FusionHub provides three ways of visualizing fusion events: circular view, domain architecture view and network view. Design of potential siRNA molecules through ensemble method is another utility integrated in FusionHub that could aid in siRNA-based targeted therapy. FusionHub is freely available at https://fusionhub.persistent.co.in.

Elucidating mechanistic insights into drug action for atopic dermatitis: a systems biology approach.

BACKGROUND: Topical Betamethasone (BM) and Pimecrolimus (PC) are widely used drugs in the treatment of atopic dermatitis (AD). Though the biomolecules and biological pathways affected by the drugs are known, the causal inter-relationships among these pathways in the context of skin is not available. We aim to derive this insight by using transcriptomic data of AD skin samples treated with BM and PC using systems biology approach. METHODS: Transcriptomic datasets of 10 AD patients treated with Betamethasone and Pimecrolimus were obtained from GEO datasets. We used a novel computational platform, eSkIN ( www.persistent.com/eskin ), to perform pathway enrichment analysis for the given datasets. eSkIN consists of 35 skin specific pathways, thus allowing skin-centric analysis of transcriptomic data. Fisher's exact test was used to compute the significance of the pathway enrichment. The enriched pathways were further analyzed to gain mechanistic insights into the action of these drugs. RESULTS: Our analysis highlighted the molecular details of the mechanism of action of the drugs and corroborated the known facts about these drugs i.e. BM is more effective in triggering anti-inflammatory response but also causes more adverse effect on skin barrier than PC. In particular, eSkIN helped enunciate the biological pathways activated by these drugs to trigger anti-inflammatory response and its effect on skin barrier. BM suppresses pathways like TNF and TLRs, thus inhibiting NF-κB while PC targets inflammatory genes like IL13 and IL6 via known calcineurin-NFAT pathway. Furthermore, we show that the reduced skin barrier function by BM is due to the suppression of activators like AP1 transcription factors, CEBPs. CONCLUSION: We thus demonstrate the detailed mechanistic insight into drug action of AD using a novel computational approach.

CGDV: a webtool for circular visualization of genomics and transcriptomics data.

BACKGROUND: Interpretation of large-scale data is very challenging and currently there is scarcity of web tools which support automated visualization of a variety of high throughput genomics and transcriptomics data and for a wide variety of model organisms along with user defined karyotypes. Circular plot provides holistic visualization of high throughput large scale data but it is very complex and challenging to generate as most of the available tools need informatics expertise to install and run them. RESULT: We have developed CGDV (Circos for Genomics and Transcriptomics Data Visualization), a webtool based on Circos, for seamless and automated visualization of a variety of large scale genomics and transcriptomics data. CGDV takes output of analyzed genomics or transcriptomics data of different formats, such as vcf, bed, xls, tab limited matrix text file, CNVnator raw output and Gene fusion raw output, to plot circular view of the sample data. CGDV take cares of generating intermediate files required for circos. CGDV is freely available at https://cgdv-upload.persistent.co.in/cgdv/ . CONCLUSION: The circular plot for each data type is tailored to gain best biological insights into the data. The inter-relationship between data points, homologous sequences, genes involved in fusion events, differential expression pattern, sequencing depth, types and size of variations and enrichment of DNA binding proteins can be seen using CGDV. CGDV thus helps biologists and bioinformaticians to visualize a variety of genomics and transcriptomics data seamlessly.

Integrated Computational Solution for Predicting Skin Sensitization Potential of Molecules.

INTRODUCTION: Skin sensitization forms a major toxicological endpoint for dermatology and cosmetic products. Recent ban on animal testing for cosmetics demands for alternative methods. We developed an integrated computational solution (SkinSense) that offers a robust solution and addresses the limitations of existing computational tools i.e. high false positive rate and/or limited coverage. RESULTS: The key components of our solution include: QSAR models selected from a combinatorial set, similarity information and literature-derived sub-structure patterns of known skin protein reactive groups. Its prediction performance on a challenge set of molecules showed accuracy = 75.32%, CCR = 74.36%, sensitivity = 70.00% and specificity = 78.72%, which is better than several existing tools including VEGA (accuracy = 45.00% and CCR = 54.17% with 'High' reliability scoring), DEREK (accuracy = 72.73% and CCR = 71.44%) and TOPKAT (accuracy = 60.00% and CCR = 61.67%). Although, TIMES-SS showed higher predictive power (accuracy = 90.00% and CCR = 92.86%), the coverage was very low (only 10 out of 77 molecules were predicted reliably). CONCLUSIONS: Owing to improved prediction performance and coverage, our solution can serve as a useful expert system towards Integrated Approaches to Testing and Assessment for skin sensitization. It would be invaluable to cosmetic/ dermatology industry for pre-screening their molecules, and reducing time, cost and animal testing.

Network analyses based on comprehensive molecular interaction maps reveal robust control structures in yeast stress response pathways.

Cellular stress responses require exquisite coordination between intracellular signaling molecules to integrate multiple stimuli and actuate specific cellular behaviors. Deciphering the web of complex interactions underlying stress responses is a key challenge in understanding robust biological systems and has the potential to lead to the discovery of targeted therapeutics for diseases triggered by dysregulation of stress response pathways. We constructed large-scale molecular interaction maps of six major stress response pathways in Saccharomyces cerevisiae (baker's or budding yeast). Biological findings from over 900 publications were converted into standardized graphical formats and integrated into a common framework. The maps are posted at http://www.yeast-maps.org/yeast-stress-response/ for browse and curation by the research community. On the basis of these maps, we undertook systematic analyses to unravel the underlying architecture of the networks. A series of network analyses revealed that yeast stress response pathways are organized in bow-tie structures, which have been proposed as universal sub-systems for robust biological regulation. Furthermore, we demonstrated a potential role for complexes in stabilizing the conserved core molecules of bow-tie structures. Specifically, complex-mediated reversible reactions, identified by network motif analyses, appeared to have an important role in buffering the concentration and activity of these core molecules. We propose complex-mediated reactions as a key mechanism mediating robust regulation of the yeast stress response. Thus, our comprehensive molecular interaction maps provide not only an integrated knowledge base, but also a platform for systematic network analyses to elucidate the underlying architecture in complex biological systems.

Identification of optimum sequencing depth especially for de novo genome assembly of small genomes using next generation sequencing data.

Next Generation Sequencing (NGS) is a disruptive technology that has found widespread acceptance in the life sciences research community. The high throughput and low cost of sequencing has encouraged researchers to undertake ambitious genomic projects, especially in de novo genome sequencing. Currently, NGS systems generate sequence data as short reads and de novo genome assembly using these short reads is computationally very intensive. Due to lower cost of sequencing and higher throughput, NGS systems now provide the ability to sequence genomes at high depth. However, currently no report is available highlighting the impact of high sequence depth on genome assembly using real data sets and multiple assembly algorithms. Recently, some studies have evaluated the impact of sequence coverage, error rate and average read length on genome assembly using multiple assembly algorithms, however, these evaluations were performed using simulated datasets. One limitation of using simulated datasets is that variables such as error rates, read length and coverage which are known to impact genome assembly are carefully controlled. Hence, this study was undertaken to identify the minimum depth of sequencing required for de novo assembly for different sized genomes using graph based assembly algorithms and real datasets. Illumina reads for E.coli (4.6 MB) S.kudriavzevii (11.18 MB) and C.elegans (100 MB) were assembled using SOAPdenovo, Velvet, ABySS, Meraculous and IDBA-UD. Our analysis shows that 50X is the optimum read depth for assembling these genomes using all assemblers except Meraculous which requires 100X read depth. Moreover, our analysis shows that de novo assembly from 50X read data requires only 6-40 GB RAM depending on the genome size and assembly algorithm used. We believe that this information can be extremely valuable for researchers in designing experiments and multiplexing which will enable optimum utilization of sequencing as well as analysis resources.

Spuriously high prevalence of prediabetes diagnosed by HbA(1c) in young indians partly explained by hematological factors and iron deficiency anemia.

OBJECTIVE: To examine the influence of glycemic and nonglycemic parameters on HbA(1c) concentrations in young adults, the majority of whom had normal glucose tolerance. RESEARCH DESIGN AND METHODS: We compared the diagnosis of normal glucose tolerance, prediabetes, and diabetes between a standard oral glucose tolerance test (OGTT; World Health Organization 2006 criteria) and HbA(1c) concentrations (American Diabetes Association [ADA] 2009 criteria) in 116 young adults (average age 21.6 years) from the Pune Children's Study. We also studied the contribution of glycemic and nonglycemic determinants to HbA(1c) concentrations. RESULTS: The OGTT showed that 7.8% of participants were prediabetic and 2.6% were diabetic. By ADA HbA(1c) criteria, 23.3% were prediabetic and 2.6% were diabetic. The negative predictive value of HbA(1c) was 93% and the positive predictive value was 20% (only 20% had prediabetes or diabetes according to the OGTT; this figure was 7% in anemic participants). Of participants, 34% were anemic, 37% were iron deficient (ferritin <15 ng/mL), 40% were vitamin B(12) deficient (<150 pmol/L), and 22% were folate deficient (<7 nmol/L). On multiple linear regression analysis, HbA(1c) was predicted by higher 2-h glucose (R(2) = 25.6%) and lower hemoglobin (R(2) = 7.7%). When hematological parameters were replaced by ferritin, vitamin B(12), and folate, HbA(1c) was predicted by higher glycemia (R(2) = 25.6%) and lower ferritin (R(2) = 4.3%). CONCLUSIONS: The use of HbA(1c) to diagnose prediabetes and diabetes in iron-deficient populations may lead to a spuriously exaggerated prevalence. Further investigation is required before using HbA(1c) as a screening tool in nutritionally compromised populations.

Role of HIV-1 Nef protein for virus replication in vitro.

The Nef protein of primate lentiviruses (simian and human immunodeficiency viruses; SIV/HIVs) appears to be multi-functional and plays a pivotal role in viral persistence and pathogenesis in vivo. Of its numerous functions reported to date, the ability to enhance virion infectivity in indicator cell lines and to augment viral replication in peripheral blood mononuclear cells (PBMCs) and lymphocytes (PBLs) is very well conserved among various SIV/HIVs. This review summarizes and organizes current knowledge of HIV-1 Nef with respect to this particularly virological activity for understanding the basis of its in vivo function.

HIV-1 reverse transcriptase connection subdomain mutations reduce template RNA degradation and enhance AZT excision.

We previously proposed that mutations in the connection subdomain (cn) of HIV-1 reverse transcriptase increase AZT resistance by altering the balance between nucleotide excision and template RNA degradation. To test the predictions of this model, we analyzed the effects of previously identified cn mutations in combination with thymidine analog mutations (D67N, K70R, T215Y, and K219Q) on in vitro RNase H activity and AZT monophosphate (AZTMP) excision. We found that cn mutations G335C/D, N348I, A360I/V, V365I, and A376S decreased primary and secondary RNase H cleavages. The patient-derived cns increased ATP- and PPi-mediated AZTMP excision on an RNA template compared with a DNA template. One of 5 cns caused an increase in ATP-mediated AZTMP excision on a DNA template, whereas three cns showed a higher ratio of ATP- to PPi-mediated excision, indicating that some cn mutations also affect excision on a DNA substrate. Overall, the results strongly support the model that cn mutations increase AZT resistance by reducing template RNA degradation, thereby providing additional time for RT to excise AZTMP.

Conservation patterns of HIV-1 RT connection and RNase H domains: identification of new mutations in NRTI-treated patients.

BACKGROUND: Although extensive HIV drug resistance information is available for the first 400 amino acids of its reverse transcriptase, the impact of antiretroviral treatment in C-terminal domains of Pol (thumb, connection and RNase H) is poorly understood. METHODS AND FINDINGS: We wanted to characterize conserved regions in RT C-terminal domains among HIV-1 group M subtypes and CRF. Additionally, we wished to identify NRTI-related mutations in HIV-1 RT C-terminal domains. We sequenced 118 RNase H domains from clinical viral isolates in Brazil, and analyzed 510 thumb and connection domain and 450 RNase H domain sequences collected from public HIV sequence databases, together with their treatment status and histories. Drug-naïve and NRTI-treated datasets were compared for intra- and inter-group conservation, and differences were determined using Fisher's exact tests. One third of RT C-terminal residues were found to be conserved among group M variants. Three mutations were found exclusively in NRTI-treated isolates. Nine mutations in the connection and 6 mutations in the RNase H were associated with NRTI treatment in subtype B. Some of them lay in or close to amino acid residues which contact nucleic acid or near the RNase H active site. Several of the residues pointed out herein have been recently associated to NRTI exposure or increase drug resistance to NRTI. CONCLUSIONS: This is the first comprehensive genotypic analysis of a large sequence dataset that describes NRTI-related mutations in HIV-1 RT C-terminal domains in vivo. The findings into the conservation of RT C-terminal domains may pave the way to more rational drug design initiatives targeting those regions.

Molecular analysis of gp41 sequences of HIV type 1 subtype C from India.

Sequence polymorphism in HIV type 1 env gene is quite high, and there are little data available for subtype C env gp41 sequences from India. We have presented a molecular sequence analysis for gp41 region of env gene from HIV type 1 subtype C-infected individuals. The samples were obtained from 3 acute seroconverters and 5 seropositive individuals from India, one of whom was a minor. Heteroduplex mobility analysis using V3V5 and gp41 confirmed subtype C infection in all the study subjects. The sequences were analyzed for heterogeneity, polymorphism, and epitope recognition. The phylogenetic and SimPlot analysis showed the monophyletic lineage of Indian sequences. The phylogenetic tree constructed for the 286- to 506-bp region is highly variable and clearly distinguishes the subtype C sequences. The interpatient sequence comparison revealed high genetic diversity ranging from 0.0623 to 2.18 (median, 0.119). This supports the phylogeny where sequences belonging to the 8 study subjects form subclusters within Indian subtype C. A majority of the functional domains of gp41 are well conserved for the seroconverter and seropositive sequences. However, sequence polymorphism is high for the sequences obtained from the minor. The sequences of gp41 would provide valuable information regarding the diversity and its diagnostic implications in HIV/AIDS research.

Subtype B and subtype C HIV type 1 recombinants in the northeastern state of Manipur, India.

The predominant HIV-1 strain circulating in India is subtype C. However, subtype A and B strains of HIV-1 have also been reported in India. In 1999, the first A/C recombinant strain was reported from Pune in India. Intravenous drug users (IVDUs) from the northeastern region of India have a high HIV-1 seroprevalence. Studies carried out in intravenous drug users in the northeastern region of India have shown that HIV-1 subtype C is the predominant strain infecting IVDUs. Fourteen blood samples were collected from HIV-1-infected individuals from the northeastern region of India and screened by env and gag heteroduplex mobility assays (HMA). Where the env and gag HMA results from a sample yielded different subtypes, sequencing of env and gag PCR products was carried out to confirm the presence of HIV-1 recombinants. Of the 14 samples subtyped, nine samples belonged HIV-1 subtype C (gag C/env C), one to HIV-1 subtype B (gag B/env B), and the remaining were B/C recombinants (gag C/env B). This is the first report of HIV-1 B/C recombinants from India.

Determination of HIV-1 infectivity by lymphocytic cell lines with integrated luciferase gene.

We have established lymphocytic cell lines H9 and M8166 that contain integrated copy of luciferase gene under the control of human immunodeficiency virus type 1 (HIV-1) long terminal repeat (LTR). While H9 is known to be non-permissive for or insensitive to some particular mutant strains of HIV/simian immunodeficiency virus (SIV), M8166 is one of the most susceptible lines to various HIV/SIVs. The luciferase gene driven by HIV-1 LTR was transfected into H9 and M8166 cells with the neo gene, and cell lines were selected by G418. The indicator cell lines thus obtained were designated H9/H1luc and M8166/H1luc, and monitored for their susceptibility to various HIV clones including in vitro-constructed mutants. Both cell lines, particularly M8166/H1luc, were found to be exquisitely sensitive to HIV-1 and HIV-2. Furthermore, they exhibited the response to infections by various viral clones exactly as expected from the characteristics of the original cell lines. These results indicated that our new indicator cell lines H9/H1luc and M8166/H1luc are eminently useful for a variety of molecular virological studies on HIV/SIV.

Generation and characterization of HIV-1 clones chimeric for subtypes B and C nef.

The impact of human immunodeficiency virus type 1 (HIV-1) Nef on viral infectivity was evaluated by characterization of chimeric clones. Chimera with respect to the nef gene were constructed between subtypes B and C, and monitored for their replication in human peripheral blood mononuclear cells. The parental clones used were pNL432 (subtype B) and pIndie-C1 (Indian subtype C), which show considerable sequence heterogeneity in nef and distinct viral growth phenotype. While an enhancing effect of Nef on viral infectivity was noted, no significant growth difference was observed between the parental and chimeric clones. The difference in growth potential of the two subtype clones was mainly ascribable to viral sequence(s) other than nef. Our results here clearly showed that HIV-1 Nef does not significantly affect the in vitro viral infectivity in natural target cells.

Functional analysis of HIV-1 vif genes derived from Japanese long-term nonprogressors and progressors for AIDS.

We analyzed the function of human immunodeficiency virus type 1 (HIV-1) vif gene from Japanese long-term nonprogressors (LTNPRs) and progressors (PRs) for acquired immunodeficiency syndrome (AIDS). We constructed a basic HIV-1 infectious clone, which facilitated the incorporation and evaluation of vif from infected individuals. Proviral reporter clones carrying vif from six Japanese LTNPRs and seven PRs were then generated and their in vitro growth kinetics were analyzed. The vif clones, which could confer infectivity on reporter viruses, were considered active, and the ratio of the active clones to the number of clones examined per individual was determined. For the majority of LTNPRs, there was no correlation between presence or absence of functional vif with long-term nonprogression for AIDS. There was one exception in which all the clones examined had inactive vif, suggesting a probable association of inactive vif with the nonprogression. All PRs with high viral load had a high ratio of active vif clones. Our results suggest that the presence of functional vif would influence HIV-1 infectivity and disease progression in infected individuals.

Genetic analysis of Indian HIV-1 nef: subtyping, variability and implications.

HIV-1 subtype C is predominant in India and globally. In the present study, we analyze HIV-1 subtype C regulatory protein Nef sequences from five recent Indian seroconverters and five long-term survivors (LTSs) for variability at crucial functional domains. Sequence analysis suggested the possibility of using regulatory gene sequences for viral subtyping and evolutionary studies apart from structural genes. In the phylogenetic tree, Indian nef sequences segregated away from other reported subtype C sequences, forming an Indian subclade within subtype C. Our studies also suggested no evidence for the association of truncated Nef with slow progression of disease, as all LTSs had intact Nef. We could identify some variations in juxtapositions to crucial functional domains, especially in seroconverter sequences, when comparing them with others. In phylogenetic analysis, specifically for the base-pair regions 411-428 and 478-525, our seroconverter sequences segregated away from those reported earlier in the literature, indicating specific evolutionary changes in these conserved regions of nef in currently circulating viruses. But the dN/dS ratio for our samples was less than one on comparing them with reported subtype C and representative sequences of different clades, strongly emphasizing the necessity of sequence conservation at different disease stages and even across clades. HLA-I binding epitope predictions for common Indian HLAs indicated that specific mutations in seroconverter Nef may alter the intensity of epitope binding, which may alter the outcome of the immune response. Hence these data would be useful in designing Nef epitopes to be included in multi-epitope HIV-1 vaccine for the Indian population and would also be of immense help in HIV-1 evolutionary studies.