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.

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.

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.

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/.