NSAID targets SIRT3 to trigger mitochondrial dysfunction and gastric cancer cell death.

Gastric cancer (GC) is a deadly malignancy that demands effective therapeutic intervention capitalizing unique drug target/s. Here, we report that indomethacin, a cyclooxygenase non-selective non-steroidal anti-inflammatory drug, arrests GC cell growth by targeting mitochondrial deacetylase Sirtuin 3 (SIRT3). Interaction study revealed that indomethacin competitively inhibited SIRT3 by binding to nicotinamide adenine dinucleotide (NAD)-binding site. The Cancer Genome Atlas data meta-analysis indicated poor prognosis associated with high SIRT3 expression in GC. Further, transcriptome sequencing data of human gastric adenocarcinoma cells revealed that indomethacin treatment severely downregulated SIRT3. Indomethacin-induced SIRT3 downregulation augmented SOD2 and OGG1 acetylation, leading to mitochondrial redox dyshomeostasis, mtDNA damage, respiratory chain failure, bioenergetic crisis, mitochondrial fragmentation, and apoptosis via blocking the AMPK/PGC1α/SIRT3 axis. Indomethacin also downregulated SIRT3 regulators ERRα and PGC1α. Further, SIRT3 knockdown aggravated indomethacin-induced mitochondrial dysfunction as well as blocked cell-cycle progression to increase cell death. Thus, we reveal how indomethacin induces GC cell death by disrupting SIRT3 signaling.

LncRTPred: Predicting RNA-RNA mode of interaction mediated by lncRNA.

Long non-coding RNAs (lncRNAs) play a significant role in various biological processes. Hence, it is utmost important to elucidate their functions in order to understand the molecular mechanism of a complex biological system. This versatile RNA molecule has diverse modes of interaction, one of which constitutes lncRNA-mRNA interaction. Hence, identifying its target mRNA is essential to understand the function of an lncRNA explicitly. Existing lncRNA target prediction tools mainly adopt thermodynamics approach. Large execution time and inability to perform real-time prediction limit their usage. Further, lack of negative training dataset has been a hindrance in the path of developing machine learning (ML) based lncRNA target prediction tools. In this work, we have developed a ML-based lncRNA-mRNA target prediction model- 'LncRTPred'. Here we have addressed the existing problems by generating reliable negative dataset and creating robust ML models. We have identified the non-interacting lncRNA and mRNAs from the unlabelled dataset using BLAT. It is further filtered to get a reliable set of outliers. LncRTPred provides a cumulative_model_score as the final output against each query. In terms of prediction accuracy, LncRTPred outperforms other popular target prediction protocols like LncTar. Further, we have tested its performance against experimentally validated disease-specific lncRNA-mRNA interactions. Overall, performance of LncRTPred is heavily dependent on the size of the training dataset, which is highly reflected by the difference in its performance for human and mouse species. Its performance for human species shows better as compared to that for mouse when applied on an unknown data due to smaller size of the training dataset in case of mouse compared to that of human. Availability of increased number of lncRNA-mRNA interaction data for mouse will improve the performance of LncRTPred in future. Both webserver and standalone versions of LncRTPred are available. Web server link: http://bicresources.jcbose.ac.in/zhumur/lncrtpred/index.html. Github Link: https://github.com/zglabDIB/LncRTPred.

Nur77 influences immunometabolism to regulate the release of proinflammatory cytokines and the formation of lipid bodies during Mycobacterium tuberculosis infection of macrophages.

Infection of macrophages with Mycobacterium tuberculosis induces innate immune responses designed to clear the invading bacterium. However, bacteria often survive within the intracellular environment by exploiting these responses triggered by macrophages. Here, the role of the orphan nuclear receptor Nur77 (Nr4a1) in regulating the response of macrophages infected with M. tuberculosis (Mtb) has been delineated. Nur77 is induced early during infection, regulates metabolism by binding directly at the promoter of the TCA cycle enzyme, isocitrate dehydrogenase 2 (IDH2), to act as its repressor, and shifts the balance from a proinflammatory to an anti-inflammatory phenotype. Depletion of Nur77 increased transcription of IDH2 and, consequently, the levels of intracellular succinate, leading to enhanced levels of the proinflammatory cytokine IL-1ß. Further, Nur77 inhibited the production of antibacterial nitric oxide and IL-1ß in a succinate dehydrogenase (SDH)-dependent manner, suggesting that its induction favors bacterial survival by suppressing bactericidal responses. Indeed, depletion of Nur77 inhibited the intracellular survival of Mtb. On the other hand, depletion of Nur77 enhanced lipid body formation, suggesting that the fall in Nur77 levels as infection progresses likely favors foamy macrophage formation and long-term survival of Mtb in the host milieu.

TarpiD, a database of putative and validated targets of piRNAs.

Piwi-interacting RNAs (piRNAs) are a novel class of 18-36 nts long small non-coding single-stranded RNAs that play crucial roles in a wide array of critical biological activities besides maintaining genome integrity by transposon silencing. piRNAs influence biological processes and pathways by regulating gene expression at transcriptional and post-transcriptional level. Studies have reported that piRNAs silence various endogenous genes post-transcriptionally by binding to respective mRNAs through interaction with the PIWI proteins. Several thousands of piRNAs have been discovered in animals, but their functions remain largely undiscovered owing to a lack of proper guiding principles of piRNA targeting or diversity in targeting patterns amongst piRNAs from the same or different species. Identification of piRNA targets is essential for deciphering their functions. There are a few tools and databases on piRNAs, but there are no systematic and exclusive repositories to obtain information on target genes regulated by piRNAs and other related information. Hence, we developed a user-friendly database named TarpiD (Targets of piRNA Database) that offers comprehensive information on piRNA and its targets, including their expression, methodologies (high-throughput or low-throughput) for target identification/validation, cells/tissue types, diseases, target gene regulation types, target binding regions, and key functions driven by piRNAs through target gene interactions. The contents of TarpiD are curated from the published literature and enable users to search and download the targets of a particular piRNA or the piRNAs that target a specific gene for use in their research. This database harbours 28 682 entries of piRNA-target interactions supported by 15 methodologies reported in hundreds of cell types/tissues from 9 species. TarpiD will be a valuable resource for a better understanding of the functions and gene-regulatory mechanisms mediated by piRNAs. TarpiD is freely accessible for academic use at https://tarpid.nitrkl.ac.in/tarpid_db/.

MicroRNA mediated gene regulatory circuits leads to machine learning based preliminary detection of acute myeloid leukemia.

Acute Myeloid Leukemia (AML) can be detected based on morphology, cytochemistry, immunological markers, and cytogenetics. MicroRNAs (miRNAs) influence key biological pathways in multiple haematological malignancies including AML. In this work, we have analysed the miRNome and the transcriptome of normal and AML samples and have identified the significant set of miRNA-target mRNA pairs present within AML- Peripheral Blood and AML- Bone Marrow samples from both tissue and cell lines. The miRNA target genes are further filtered based on their functional significance in AML system. These filtered genes constitute the set of selected miRNA target features, which have been finally used for developing machine learning based prediction tool, 'TbAMLPred' for preliminary detection of AML. This model implements both unsupervised clustering and supervised classification algorithms that would increase the reliability of prediction. Our results show that the selected miRNA target-based features can separate the control and disease samples linearly. Overall, we put forward 'TbAMLPred' for a non-invasive mode of preliminary AML diagnosis in future. Github link for accessing TbAMLPred: https://github.com/zglabDIB/TbAMLPred.

Honokiol, an inducer of sirtuin-3, protects against non-steroidal anti-inflammatory drug-induced gastric mucosal mitochondrial pathology, apoptosis and inflammatory tissue injury.

BACKGROUND AND PURPOSE: Mitochondrial oxidative stress, inflammation and apoptosis primarily underlie gastric mucosal injury caused by the widely used non-steroidal anti-inflammatory drugs (NSAIDs). Alternative gastroprotective strategies are therefore needed. Sirtuin-3 pivotally maintains mitochondrial structural integrity and metabolism while preventing oxidative stress; however, its relevance to gastric injury was never explored. Here, we have investigated whether and how sirtuin-3 stimulation by the phytochemical, honokiol, could rescue NSAID-induced gastric injury. EXPERIMENTAL APPROACH: Gastric injury in rats induced by indomethacin was used to assess the effects of honokiol. Next-generation sequencing-based transcriptomics followed by functional validation identified the gastroprotective function of sirtuin-3. Flow cytometry, immunoblotting, qRT-PCR and immunohistochemistry were used measure effects on oxidative stress, mitochondrial dynamics, electron transport chain function, and markers of inflammation and apoptosis. Sirtuin-3 deacetylase activity was also estimated and gastric luminal pH was measured. KEY RESULTS: Indomethacin down-regulated sirtuin-3 to induce oxidative stress, mitochondrial hyperacetylation, 8-oxoguanine DNA glycosylase 1 depletion, mitochondrial DNA damage, respiratory chain defect and mitochondrial fragmentation leading to severe mucosal injury. Indomethacin dose-dependently inhibited sirtuin-3 deacetylase activity. Honokiol prevented mitochondrial oxidative damage and inflammatory tissue injury by attenuating indomethacin-induced depletion of both sirtuin-3 and its transcriptional regulators PGC1α and ERRα. Honokiol also accelerated gastric wound healing but did not alter gastric acid secretion, unlike lansoprazole. CONCLUSIONS AND IMPLICATIONS: Sirtuin-3 stimulation by honokiol prevented and reversed NSAID-induced gastric injury through maintaining mitochondrial integrity. Honokiol did not affect gastric acid secretion. Sirtuin-3 stimulation by honokiol may be utilized as a mitochondria-based, acid-independent novel gastroprotective strategy against NSAIDs.

Defense Surveillance System at the Interface: Response of Rice Towards Rhizoctonia solani During Sheath Blight Infection.

Sheath blight of rice caused by necrotrophic plant pathogen Rhizoctonia solani is one of the most common fungal diseases of rice leading to significant yield loss. Among the defense responses exhibited by the host plants towards fungal infections, those functional within the apoplast contribute significantly. Here, we have studied apoplastic defense response of rice towards R. solani during sheath blight infection. The transcriptome of R. solani-infected rice plants was compared with that of uninfected rice, to identify the set of defense genes that undergo differential expression and code for proteins with a predicted N-terminal signal peptide. Significant changes in the stress-responsive, molecular signal perception, protein modification, and metabolic process pathways represented by a group of differentially expressed genes were observed. Our data also revealed two secreted protease inhibitors from rice that exhibit increased expression during R. solani infection and induce disease resistance when expressed in Nicotiana benthamiana. [Formula: see text] Copyright © 2022 The Author(s). This is an open access article distributed under the CC BY-NC-ND 4.0 International license.

Heightened miR6024-NLR interactions facilitate necrotrophic pathogenesis in tomato.

KEY MESSAGE: miR6024 acts as a negative regulator of R genes, hence of Tomato plant immunity, and facilitates disease by the necrotrophic pathogen A. solani. Plant resistance genes or Nucleotide-binding leucine-rich repeat (NLR) genes, integral components of plant disease stress-signaling are targeted by variable groups of miRNAs. However, the significance of miRNA-mediated regulation of NLRs during a pathogen stress response, specifically for necrotrophic fungus, is poorly understood. A thorough examination of Tomato NLRs and miRNAs could map substantial interactions of which half the annotated NLRs were targets of Solanaceae-specific and conserved miRNAs, at the NB subdomain. The Solanaceae-specific miR6024 and its NLR targets analysed in different phytopathogenic stresses revealed differential and mutually antagonistic regulation. Interestingly, miR6024-targeted cleavage of a target NLR also triggered the generation of secondary phased siRNAs which could potentially amplify the defense signal. RNA-seq analysis of leaf tissues from miR6024 overexpressing Tomato plants evidenced a perturbation in the defense transcriptome with the transgenics showing unwarranted immune response-related genes' expression with or without infection with necrotrophic Alternaria solani, though no adverse effect could be observed in the growth and development of the transgenic plants. Transgenic plants exhibited constitutive downregulation of the target NLRs, aggravated disease phenotype with an enhanced lesion, greater ROS generation and hypersusceptibility to A. solani infection, thus establishing that miR6024 negatively impacts plant immune response during necrotrophic pathogenesis. Limited knowledge about the outcome of NLR-miRNA interaction during necrotrophic pathogenesis is a hindrance to the deployment of miRNAs in crop improvement programs. With the elucidation of the necrotrophic disease-synergistic role played by miR6024, it becomes a potent candidate for biotechnological manipulation for the rapid development of pathogen-tolerant solanaceous plants.

Eriodictyol mediated selective targeting of the TNFR1/FADD/TRADD axis in cancer cells induce apoptosis and inhibit tumor progression and metastasis.

While the anti-inflammatory activities of Eriodictyol, a plant-derived flavonoid is well-known, reports on its anti-cancer efficacy and selective cytotoxicity in cancer cells are still emerging. However, little is known regarding its mechanism of selective anti-cancer activities. Here, we show the mechanism of selective cytotoxicity of Eriodictyol towards cancer cells compared to normal cells. Investigation reveals that Eriodictyol significantly upregulates TNFR1 expression in tumor cells (HeLa and SK-RC-45) while sparing the normal cells (HEK, NKE and WI-38), which display negligible TNFR1 expression, irrespective of the absence or presence of Eriodictyol. Further investigation of the molecular events reveal that Eriodictyol induces apoptosis through expression of the pro-apoptotic DISC components leading to activation of the caspase cascade. In addition, CRISPR-Cas9 mediated knockout of TNFR1 completely blocks apoptosis in HeLa cells in response to Eriodictyol, confirming that Eriodictyol induced cancer cell apoptosis is indeed TNFR1-dependent. Finally, in vivo data demonstrates that Eriodictyol not only impedes tumor growth and progression, but also inhibits metastasis in mice implanted with 4T1 breast cancer cells. Thus, our study has identified Eriodictyol as a compound with high selectivity towards cancer cells through TNFR1 and suggests that it can be further explored for its prospect in cancer therapeutics.

piRNAQuest V.2: an updated resource for searching through the piRNAome of multiple species.

PIWI interacting RNAs (piRNAs) have emerged as important gene regulators in recent times. Since the release of our first version of piRNAQuest in 2014, lots of novel piRNAs have been annotated in different species other than human, mouse and rat. Such new developments in piRNA research have led us to develop an updated database piRNAQuest V.2. It consists of 92,77,689 piRNA entries for 25 new species of different phylum along with human, mouse and rat. Besides providing primary piRNA features which include their genomic location, with further information on piRNAs overlapping with repeat elements, pseudogenes and syntenic regions, etc., the novel features of this version includes (i) density based cluster prediction, (ii) piRNA expression profile across various healthy and disease systems and (iii) piRNA target prediction. The concept of density-based piRNA cluster identification is robust as it does not consider parametric distribution in its model. The piRNA expression profile for 21 disease systems including cancer have been hosted in addition to 32 tissue specific piRNA expression profile for various species. Further, the piRNA target prediction section includes both predicted and curated piRNA targets within eight disease systems and developmental stages of mouse testis. Further, users can visualize the piRNA-target duplex structure and the ping-pong signature pattern for all the ping-pong piRNA partners in different species. Overall, piRNAQuest V.2 is an updated user-friendly database which will serve as a useful resource to survey, search and retrieve information on piRNAs for multiple species. This freely accessible database is available at http://dibresources.jcbose.ac.in/zhumur/pirnaquest2.

The Natural Antisense Transcript DONE40 Derived from the lncRNA ENOD40 Locus Interacts with SET Domain Protein ASHR3 During Inception of Symbiosis in Arachis hypogaea.

The long noncoding RNA ENOD40 is required for cortical cell division during root nodule symbiosis (RNS) of legumes, though it is not essential for actinorhizal RNS. Our objective was to understand whether ENOD40 was required for aeschynomenoid nodule formation in Arachis hypogaea. AhENOD40 express from chromosome 5 (chr5) (AhENOD40-1) and chr15 (AhENOD40-2) during symbiosis, and RNA interference of these transcripts drastically affected nodulation, indicating the importance of ENOD40 in A. hypogaea. Furthermore, we demonstrated several distinct characteristics of ENOD40. (i) Natural antisense transcript (NAT) of ENOD40 was detected from the AhENOD40-1 locus (designated as NAT-AhDONE40). (ii) Both AhENOD40-1 and AhENOD40-2 had two exons, whereas NAT-AhDONE40 was monoexonic. Reverse-transcription quantitative PCR analysis indicated both sense and antisense transcripts to be present in both cytoplasm and nucleus, and their expression increased with the progress of symbiosis. (iii) RNA pull-down from whole cell extracts of infected roots at 4 days postinfection indicated NAT-AhDONE40 to interact with the SET (Su(var)3-9, enhancer of Zeste and Trithorax) domain containing absent small homeotic disc (ASH) family protein AhASHR3 and this interaction was further validated using RNA immunoprecipitation and electrophoretic mobility shift assay. (iv) Chromatin immunoprecipitation assays indicate deposition of ASHR3-specific histone marks H3K36me3 and H3K4me3 in both of the ENOD40 loci during the progress of symbiosis. ASHR3 is known for its role in optimizing cell proliferation and reprogramming. Because both ASHR3 and ENOD40 from legumes cluster away from those in actinorhizal plants and other nonlegumes in phylogenetic distance trees, we hypothesize that the interaction of DONE40 with ASHR3 could have evolved for adapting the nodule organogenesis program for legumes.[Formula: see text] Copyright © 2021 The Author(s). This is an open access article distributed under the CC BY-NC-ND 4.0 International license.

Repurposed drugs and nutraceuticals targeting envelope protein: A possible therapeutic strategy against COVID-19.

COVID-19 pandemic caused by SARS-CoV-2 has already claimed millions of lives worldwide due to the absence of a suitable anti-viral therapy. The CoV envelope (E) protein, which has not received much attention so far, is a 75 amino acid long integral membrane protein involved in assembly and release of the virus inside the host. Here we have used artificial intelligence (AI) and pattern recognition techniques for initial screening of FDA approved pharmaceuticals and nutraceuticals to target this E protein. Subsequently, molecular docking simulations have been performed between the ligands and target protein to screen a set of 9 ligand molecules. Finally, we have provided detailed insight into their mechanisms of action related to the varied symptoms of infected patients.

LncRBase V.2: an updated resource for multispecies lncRNAs and ClinicLSNP hosting genetic variants in lncRNAs for cancer patients.

The recent discovery of long non-coding RNA as a regulatory molecule in the cellular system has altered the concept of the functional aptitude of the genome. Since our publication of the first version of LncRBase in 2014, there has been an enormous increase in the number of annotated lncRNAs of multiple species other than Human and Mouse. LncRBase V.2 hosts information of 549,648 lncRNAs corresponding to six additional species besides Human and Mouse, viz. Rat, Fruitfly, Zebrafish, Chicken, Cow and C.elegans. It provides additional distinct features such as (i) Transcription Factor Binding Site (TFBS) in the lncRNA promoter region, (ii) sub-cellular localization pattern of lncRNAs (iii) lnc-pri-miRNAs (iv) Possible small open reading frames (sORFs) within lncRNA. (v) Manually curated information of interacting target molecules and disease association of lncRNA genes (vi) Distribution of lncRNAs across multiple tissues of all species. Moreover, we have hosted ClinicLSNP within LncRBase V.2. ClinicLSNP has a comprehensive catalogue of lncRNA variants present within breast, ovarian, and cervical cancer inferred from 561 RNA-Seq data corresponding to these cancers. Further, we have checked whether these lncRNA variants overlap with (i)Repeat elements,(ii)CGI, (iii)TFBS within lncRNA loci (iv)SNP localization in trait-associated Linkage Disequilibrium(LD) region, (v)predicted the potentially pathogenic variants and (vi)effect of SNP on lncRNA secondary structure. Overall, LncRBaseV.2 is a user-friendly database to survey, search and retrieve information about multi-species lncRNAs. Further, ClinicLSNP will serve as a useful resource for cancer specific lncRNA variants and their related information. The database is freely accessible and available at http://dibresources.jcbose.ac.in/zhumur/lncrbase2/.

PSCRIdb: A database of regulatory interactions and networks of pluripotent stem cell lines.

Pluripotency in stem cells is regulated by a complex network between the transcription factors, signaling molecules, mRNAs, and epigenetic regulators like non-coding RNAs. Different pluripotent stem cell (PSC) lines were isolated and characterized to study the regulatory network topology to understand the mechanism that control developmental potential of pluripotent cells. PSCRIdb is a manually curated database of regulatory interactions including protein-protein, protein-DNA, gene-gene, and miRNA-mRNA interactions in mouse and human pluripotent stem cells including embryonic stem cells and embryonic carcinoma cells. At present, 22 different mouse and human pluripotent stem-cell-line-specific regulatory interactions are compiled in the database. Detailed information of the four types of interaction data are presented in tabular format and graphical network view in Cytoscape layout. The database is available at http://bicresources.jcbose.ac.in/ ssaha4/pscridb. The database contains 3037 entries of experimentally validated molecular interactions that can be useful for systematic study of pluripotency integrating multi-omics data. In summary, the database can be a useful resource for identification of regulatory networks present in different pluripotent stem cell lines.

Unraveling the role of H3K4 trimethylation and lncRNA HOTAIR in SATB1 and DUSP4-dependent survival of virulent Mycobacterium tuberculosis in macrophages.

The modification of chromatin influences host transcriptional programs during bacterial infection, at times skewing the balance in favor of pathogen survival. To test the role of chromatin modifications during Mycobacterium tuberculosis infection, we analysed genome-wide deposition of H3K4me3 marks in macrophages infected with either avirulent M. tuberculosis H37Ra or virulent H37Rv, by chromatin immunoprecipitation, followed by sequencing. We validated differences in association of H3K4me3 at the loci of special AT-rich sequence binding protein 1 (SATB1) and dual specificity MAP kinase phosphatase 4 (DUSP4) between H37Rv and H37Ra-infected macrophages, and demonstrated their role in regulating bacterial survival in macrophages as well as the expression of chemokines. SATB1 repressed gp91phox (an NADPH oxidase subunit) thereby regulating reactive oxygen species (ROS) generation during infection. Long non-coding RNA HOX transcript antisense RNA (HOTAIR) was upregulated in H37Ra-, but downregulated in H37Rv-infected macrophages. HOTAIR overexpression correlated with deposition of repressive H3K27me3 marks around the TSSs of DUSP4 and SATB1, suggesting that its downregulation favors the transcription of SATB1 and DUSP4. In summary, we have delineated histone modification- and lncRNA-dependent mechanisms regulating gene expression patterns facilitating survival of virulent M. tuberculosis. Our observations raise the possibility of harnessing histone-modifying enzymes to develop host-directed therapies for tuberculosis.

A Supervised Ensemble Approach for Sensitive microRNA Target Prediction.

MicroRNAs, a class of small non-coding RNAs, regulate important biological functions via post-transcriptional regulation of messenger RNAs (mRNAs). Despite rapid development in miRNA research, precise experimental methods to determine miRNA target interactions are still lacking. This motivated us to explore the in silico target interaction features and incorporate them in predictive modeling. We propose a systematic approach towards developing a sensitive miRNA target prediction model to explore the interplay of target recognition features. In the first step, we have employed a supervised ensemble under-sampling approach to address the problem of imbalance in the training dataset due to a larger number of negative instances. Various feature selection techniques were evaluated to obtain the optimal feature subset that best recognizes the true miRNA-mRNA targets. In the second step, we have built our optimal model, miRTPred, a novel blending ensemble-based approach that combines the predictions of the best performing traditional and classical ensemble models, through a weighted voting classifier, achieving a sensitivity of 87 percent and F1-score of 0.88 for 3'UTR region of the mRNA transcript. miRTPred outperforms popular machine learning (ML) and non-ML approaches to target prediction algorithms. miRTPred is freely available at http://bicresources.jcbose.ac.in/zhumur/mirtpred.

Activating transcription factor 3 modulates the macrophage immune response to Mycobacterium tuberculosis infection via reciprocal regulation of inflammatory genes and lipid body formation.

Infection of macrophages by Mycobacterium tuberculosis elicits an immune response that clears the bacterium. However, the bacterium is able to subvert the innate immune response. Differential expression of transcription factors (TFs) is central to the dynamic balance of this interaction. Among other functions, TFs regulate the production of antibacterial agents such as nitric oxide, pro-inflammatory cytokines and neutral lipids which are stored in lipid bodies (LBs) and favour bacterial survival. Here, we demonstrate that the TF activating transcription factor 3 (ATF3) is upregulated early during infection of macrophages or mice. Depletion of ATF3 enhances mycobacterial survival in macrophages suggesting its host-protective role. ATF3 interacts with chromatin remodelling protein brahma-related gene 1 and both associate with the promoters of interleukin-12p40, interleukin-6 and nitric oxide synthase 2, to activate expression of these genes. Strikingly, ATF3 downregulates LB formation by associating at the promoters of positive regulators of LB formation such as cholesterol 25 hydroxylase and the microRNA-33 locus. ATF3 represses the association of the activating mark, acetyl histone H4 lysine 8 at the promoter of cholesterol 25 hydroxylase. Our study suggests opposing roles of ATF3 in regulation of distinct sets of macrophage genes during infection, converging on a host-protective immune response.

Elucidating the gene regulatory networks modulating cancer stem cells and non-stem cancer cells in high grade serous ovarian cancer.

The origin and pathogenesis of epithelial ovarian cancer have perplexed investigators for decades. The most prevalent type of it is the high-grade serous ovarian carcinoma (HGSOv) which is a highly aggressive disease with high relapse rates and insurgence of chemo-resistance at later stages of treatment. These are driven by a rare population of stem cell like cancer cells called cancer stem cells (CSCs). We have taken up a systems approach to find out the common gene interaction paths between non-CSC tumor cells (CCs) and CSCs in HGSOv. Detailed investigation reveals a set of 17 Transcription Factors (named as pivot-TFs) which can govern changes in the mode of gene regulation along these paths. Overall, this work highlights a divergent road map of functional information relayed by these common key players in the two cell states, which might aid towards designing novel therapeutic measures to target the CSCs for ovarian cancer therapy.

ParStream-seq: An improved method of handling next generation sequence data.

The exponential growth of next generation sequencing (NGS) data has put forward the challenge for its storage as well as its efficient and faster analysis. Storing the entire amount of data for a particular experiment and its alignment to the reference genome is an essential step for any quantitative analysis of NGS data. Here, we introduce streaming access technique 'ParStream-seq' that splits the bulk sequence data, accessed from a remote repository into short manageable packets followed by executing their alignment process in parallel in each of the compute core. The optimal packet size with fixed number of reads is determined in the stream that maximizes system utilization. Result shows a reduction in the execution time and improvement in the memory footprint. Overall, this streaming access technique provides means to overcome the hurdle of storing the entire volume of sequence data corresponding to a particular experiment, prior to its analysis.

A systemic insight into astrocytoma biology across different grades.

Astrocytomas are the most common type of brain tumors, which originate from glial cells, and are classified into specific grades based on their histopathological behavior. To develop precise therapeutic strategies for the disease, it is important to identify the molecular signatures specific to each grade as well as the key factors responsible for the transition from one grade to the next. In this study, we have taken a systems approach to investigate the gene expression profiles of each grades of the disease by mapping shortest paths of gene interaction in each grade and also between one grade and the next. Module core genes govern the topology of these networks and serve as important functional players in each grade as well as help in grade transition events. Shortlisted among these module core genes are well-characterized players of glioma as well as novel molecules (32 grade-specific genes and 15 grade transition-specific genes), which influence important prooncogenic functions but have not been linked to glioma biology yet. These module core genes provide interesting insight into the biology of astrocytic tumors and are potential therapeutic targets for astrocytoma.