Whole genome based identification of BAHD acyltransferase gene involved in piperine biosynthetic pathway in black pepper.

Black pepper (Piper nigrum L.), a crop of the genus Piper, is an important spice that has both economic and ecological significance. It is widely regarded as the "King of Spices" because of its pungency, attributed to the presence of piperine. BAHD acyl transferase, the crucial enzyme involved in the final step in piperine biosynthesis was the focus of our study and the aim was to identify the candidate isoform involved in biosynthesis of piperine. Reference genome-based analysis of black pepper identified six BAHD-AT isoforms and mapping of these sequences revealed that the isoforms were situated on six distinct chromosomes. By using specific primers for each of these transcripts, qPCR analysis was done in different tissues as well as berry stages to obtain detectable amplification products. Expression profiles of isoforms from chromosome 6 correlated well with piperine content compared to other five isoforms, across tissues and was therefore assumed to be involved in biosynthesis of piperine. In addition to this, we could also identify the binding sites of MYB transcription factor in the cis-regulatory regions of the isoforms. We also used in-silico docking and molecular dynamics simulation to calculate the binding free energy of the ligand and confirmed that among all the isoforms, BAHD-AT from chromosome 6 had the lowest free binding energy and highest affinity towards the ligand. Our findings are expected to aid the identification of new genes connecting enzymes involved in the biosynthetic pathway of piperine, which will have major implications for future research in metabolic engineering.Communicated by Ramaswamy H. Sarma.

New insights into bacterial Zn homeostasis and molecular architecture of the metal resistome in soil polluted with nano zinc oxide.

Accumulation of nano ZnO (nZnO) in soils could be toxic to bacterial communities through disruption of Zn homeostasis. Under such conditions, bacterial communities strive to maintain cellular Zn levels by accentuation of appropriate cellular machinery. In this study, soil was exposed to a gradient (50-1000 mg Zn kg-1) of nZnO for evaluating their effects on genes involved in Zn homeostasis (ZHG). The responses were compared with similar levels of its bulk counterpart (bZnO). It was observed that ZnO (as nZnO or bZnO) induced a plethora of influx and efflux transporters as well as metallothioneins (MTs) and metallochaperones mediated by an array of Zn sensitive regulatory proteins. Major influx system identified was the ZnuABC transporter, while important efflux transporters identified were CzcCBA, ZntA, YiiP and the major regulator was Zur. The response of communities was dose- dependent at lower concentrations (<500 mg Zn kg-1 as nZnO or bZnO). However, at 1000 mg Zn kg-1, a size-dependent threshold of gene/gene family abundances was evident. Under nZnO, a poor adaptation to toxicity induced anaerobic conditions due to deployment of major influx and secondary detoxifying systems as well as poor chelation of free Zn ions was evident. Moreover, Zn homeostasis related link with biofilm formation and virulence were accentuated under nZnO than bZnO. While these findings were verified by PCoA and Procrustes analysis, Network analysis and taxa vs ZHG associations also substantiated that a stronger Zn shunting mechanism was induced under nZnO due to higher toxicity. Molecular crosstalks with systems governing Cu and Fe homeostasis were also evident. Expression analysis of important resistance genes by qRT-PCR showed good alignment with the predictive metagenome data, thereby validating our findings. From the study it was evident that the induction of detoxifying and resistant genes was greatly lowered under nZnO, which markedly hampered Zn homeostasis among the soil bacterial communities.

Soil polluted with nano ZnO reveals unstable bacterial communities and decoupling of taxonomic and functional diversities.

Due to relentless production and disposal of nano zinc oxide (nZnO), it has become critical to comprehend the serious risks large-scale accumulation of nZnO pose to bacterial communities in soil. The primary objective was to evaluate the changes in bacterial community structure and associated functional pathways through predictive metagenomic profiling and subsequent validation through Quantitative Realtime PCR in soil spiked with nZnO (0, 50, 200, 500 and 1000 mg Zn kg-1) and similar levels of bulk ZnO (bZnO). The results revealed that soil microbial biomass-C, -N, -P, soil respiration and enzyme activities decreased markedly at higher ZnO levels. The alpha diversity decreased with increasing ZnO level, with more impact under nZnO, while beta diversity analyses indicated a distinct dose- dependent separation of bacterial communities. The dominant taxa including Proteobacteria, Bacterioidetes, Acidobacteria and Planctomycetes significantly increased in abundance, while Firmicutes, Actinobacteria and Chloroflexi decreased in abundance with elevated nZnO and bZnO levels. Redundancy analysis indicated that changes in bacterial community structure instilled a greater dose- rather than size- specific response on key microbial parameters. Predicted key functions did not show a dose- specific response, and at 1000 mg Zn kg-1, methane metabolism as well as starch and sucrose metabolism were attenuated, while functions involving two component systems and bacterial secretion systems were enhanced under bZnO indicating better stress avoidance mechanism than under nZnO. Realtime PCR and microbial endpoint assays confirmed the metagenome derived taxonomic and functional data, respectively. Taxa and functions that varied substantially under stress were established as bioindicators to predict nZnO toxicity in soils. Taxon-function decoupling indicated that the soil bacterial communities deployed adaptive mechanisms under high ZnO, with lesser buffering capacity and resilience of communities under nZnO.

Metagenomics indicates abundance of biofilm related genes and horizontal transfer of multidrug resistant genes among bacterial communities in nano zinc oxide polluted soil.

The unsafe and reckless disposal of metal oxide nanoparticles like ZnO (nZnO) into the soil could seriously impact bacterial behavioural responses and functions. Under such stress, biofilm formation is considered to be a robust mechanism for bacterial survival in soil. We examined the response of bacterial metagenomes in soils exposed to varying levels of Zn (50, 200, 500 and 1000 mg kg-1) as nano Zn oxide (nZnO) in terms of biofilm genesis and regulation and their co-occurrences with multidrug resistance genes (MDRGs) and mobile genetic elements (MGEs). The size-specific effects of nZnO were verified using its bulk counterpart (bZnO). Both nZnO and bZnO facilitated profusion of biofilm related genes (BGs) especially at higher Zn levels (500 and 1000 mg kg-1 Zn), though maximum abundance was registered at a comparatively lower level under nZnO. In general, nZnO favoured an enhancement of genes involved in exopolysaccharide biosynthesis and attachment, while bZnO favoured genes related to capsule formation, chemotaxis and biofilm dispersion. Co-occurrence network analysis revealed significant positive correlations between abundances of BGs, MDRGs and MGEs, indicating an enhanced probability for horizontal gene transfer of MDRGs in nZnO polluted soils.

Transcriptomic meta-analysis reveals biomarker pairs and key pathways in Tetralogy of Fallot.

Tetralogy of Fallot (TOF) is a cyanotic congenital condition contributed by genetic, epigenetic as well as environmental factors. We applied sparse machine learning algorithms to RNAseq and sRNAseq data to select the prospective biomarker candidates. Furthermore, we applied filtering techniques to identify a subset of biomarker pairs in TOF. Differential expression analysis disclosed 2757 genes and 214 miRNAs, which are dysregulated. Weighted gene co-expression network analysis on the differentially expressed genes extracted five significant modules that are enriched in GO terms, extracellular matrix, signaling and calcium ion binding. Also, voomNSC selected two genes and five miRNAs and transformed PLDA-predicted 72 genes and 38 miRNAs as prognostic biomarkers. Out of the selected biomarkers, miRNA target analysis revealed 14 miRNA-gene interactions. Also, 10 out of 14 pairs were oppositely expressed and four out of 10 oppositely expressed biomarker pairs shared common pathways of focal adhesion and P13K-Akt signaling. In conclusion, our study demonstrated the concept of biomarker pairs, which may be considered for clinical validation due to the high literature as well as experimental support.

Dataset of De Novo hybrid berry transcriptome profiling and characterization of Piper species (Piper nigrum and Piper longum) using Illumina and Nanopore sequencing.

Piper nigrum and Piper longum are the most popular and economically essential spice crops globally valued for their aromatic alkaloids, especially Piperine. However, Piperine synthesis pathway mechanisms are not yet well known. This work was aimed to generate the full-length comparative berry transcriptome analysis dataset of P. nigrum and P. longum by Illumina and Nanopore sequencing platforms. While short-read sequencing technology is widely using to capture transcriptome profiles, there are still some limitations due to the read length. We used Oxford Nanopore technology for long reads and the Illumina sequencing platform for short reads to generate a hybrid transcriptome assembly from half matured and fully matured berries of P. nigrum and P. longum. From P. nigrum and P. longum 37.3 million and 38.1 million raw reads were generated respectively. A total of 308369 contigs from P. nigrum and 267715 contigs from P. longum were obtained and successfully annotated. The transcriptome data revealed gene families involved in piperine and other secondary metabolite biosynthetic pathways. The raw data were uploaded to NCBI database. This dataset shed light on the further exploration of the piperine biosynthetic pathway, its transcriptomic changes, and evolution. Data generated has been submitted to SRA of NCBI with Bio samples accession: (SAMN13981803, SAMN22826456).

Analysis of selection signatures reveals important insights into the adaptability of high-altitude Indian sheep breed Changthangi.

Changthangi is a high-altitude sheep breed of India that is adapted to cold and hypoxic climate of Himalayas. In the present study, we analysed population structure of Changthangi and contrasted it with selected Indian and European commercial sheep breeds to detect genomic regions under positive selection. The Illumina OvineSNP50v1 genotype data on 292 animals from seven different sheep breeds i.e., Changthangi (n = 29), Garole (n = 26), Deccani (n = 24), Tibetan (n = 37), Rambouillet (n = 102) and Australian Merino (n = 50) was used. European Mouflon (n = 24) was used as an out-group for studying the stratification and phylogenetic lineage. While the principal component analysis (PCA) revealed Changthangi to cluster with Tibetan sheep; TREEMIX and ADMIXTURE results also detected the introgression of lowland Indian sheep inheritance in Changthangi. Changthangi sheep were compared with other breed groups as reference i.e., commercial (Australian Merino and Rambouillet), Indian (Deccani, Garole and Tibetan) and breeds inhabiting plains (Australian Merino, Rambouillet, Deccani and Garole). Genomic comparisons of Changthangi using cross population extended haplotype homozygosity (XP-EHH) showed multiple functional regions present on Ovis aries (Oar) chromosomes 2, 3, 6 and 18 to be under selection in Changthangi sheep. These regions were related with adaptation to climatic and hypoxic stressors, fleece characteristics and functioning of immune and reproductive systems. UCP genes, associated with adaptation to cold and hypoxic conditions, were the main loci under positive selection in Changthangi sheep population. The selection signals in Indian and European commercial sheep breeds were mainly associated with body weight and carcass traits. Furthermore, selection signals found in different comparisons were found to be part of different quantitative trait loci (QTLs) associated with important traits in different breed classes. The genes present in these regions are suitable candidates for future studies on the genetic mechanisms underlying high-altitude adaptation.

Integrated regulatory network based on lncRNA-miRNA-mRNA-TF reveals key genes and sub-networks associated with dilated cardiomyopathy.

Dilated Cardiomyopathy (DCM) is a multifactorial condition often leading to heart failure in many clinical cases. Due to the high number of DCMincidence reported as familial, a gene level network based study was conducted utilizing high throughput next generation sequencing data. We exploited the exome and transcriptome sequencing data in NCBI-SRA database to construct a high confidence scale-free regulatory network consisting of lncRNA, miRNA, mRNA and Transcription Factors (TFs). Analysis of RNA-Seq data revealed 477 differentially expressed coding transcripts and 77 lncRNAs. 268 miRNAs regulated either lncRNAs or mRNAs. Out of the 477 coding transcripts that are deregulated, 82 were TFs. We identified three major hub nodeslncRNA (XIST), miRNA (hsa-miR-195-5p) and mRNA (NOVA1) from the network. We also found putative disease associations of DCM with diabetes and DCM with hypoventillation syndrome. Five highly connected modules were also identified from the network. The hubs showed significant connectivity with the modules.Through this study we were able to gain insights into the underlying lncRNA-miRNA-mRNA-TF network. From a high throughput dataset we have isolated a handful of probable targets that may be utilized for studying the mechanisms of DCM development and progression to heart failure.

Two way network construction and analysis of mRNA, miRNA and lncRNA reveals critical regulators and regulatory modules in cardiovascular diseases.

BACKGROUND: Cardiovascular diseases contribute to the leading cause of deaths (31%) in the world population. OBJECTIVE: The objective of this study is to compile non-coding RNA-gene interaction into a core regulatory network whose dysregulation might play an important role in disease progression. METHOD: We applied a structured approach to reconstruct the interaction network of lncRNAs, miRNAs and genes involved in cardiovascular diseases. For network construction, we used 'diseasome to interactome' and 'interactome to diseasome' approaches and developed two regulatory networks in heart disorders. In diseasome to interactome approach, starting from a disease-centric network we, expanded the data into an interaction network. However in interactome to diseasome, we used a set of guide genes, miRNAs and lncRNAs to arrive at the common diseases. The disease-centric network in combination with the interaction network will shed light on the interconnected components in a huge diseasome network implicated in heart disorders and manifested through small sub-networks while progressing. Using the above networks we created a sub-networks consisting only of hub genes, miRNAs and lncRNAs on both approaches. The dysregulation of any one of the hubs can lead to a disease condition. RESULTS: The top ranking hubs common in both the sub-networks were found to be VEGFA, MALAT1, HOTAIR, H19 and hsa-miR-15a. Our network based study reveals an entanglement of regulatory sub-network of miRNAs, lncRNAs and genes in multiple conditions. CONCLUSION: The identification of hubs in the core triple node network of elements in disease development and progression demonstrates a promising role for network based approaches in targeting critical molecules for drug development.

MethFinder - A software package for prediction of human tissue-specific methylation status of CpG islands.

UNLABELLED: DNA methylation, the highly studied epigenetic mechanism which is involved in the regulatory events of various cellular processes like chromatin structure modifications, chromosomal inactivation, gene expressional patterns, embriyonic developments and transcriptional modification etc. Various high throughput techniques evolved for direct detection of methylation actions as well as information across the entire region. However, despite high throughput technological advances in experimental field, the development of software tools that has been dedicated to the prediction of epigenetic information from specific genome sequences is warranted. To this end we developed a tissue specific classifier MethFinder based on the frequency of novel sequence patterns across nine human tissues that was capable of discriminating methylation prone and methylation resistant CpG islands with an overall accuracy of 93%. AVAILABILITY: MethFinder is freely available at www.rgcb.res.in/methfinder.

Oncogenic microRNAs as biomarkers of oral tumorigenesis and minimal residual disease.

OBJECTIVES: Classical diagnostic methods are not sensitive enough in detecting oral lesions that may progress to cancer and in assessing minimal residual disease (MRD) in oral surgical margins. Altered expression of microRNAs (miRNAs) contributes to human cancer, including oral cancer. Although there are many studies on microRNAs in oral cancer, there is no reported study comparing the expression of microRNAs during oral tumor progression and in oral surgical margins. MATERIALS AND METHODS: This study analyzed the expression of 72 miRNAs that were reported (till June 2011) to be differentially expressed in oral cancer, during phases of oral cancer progression and in oral surgical margins. RESULTS: Of the 72 miRNAs analyzed, four (hsa-miR-125a, hsa-miR-184, hsa-miR16 and hsa-miR-96) showed a common pattern of expression in both sets of tissues. We further analyzed the downstream target genes of hsa-miR-16 BCL2 and CCND1. The in silico network analysis of these four microRNAs and their target genes revealed presence of genes involved in tumor progression and transcription factors. CONCLUSIONS: The findings suggest that the combinatorial regulation by these miRNAs and their target transcription factors might play a substantial role in oral tumorigenesis. Here we report for the first time that a decreased expression of hsa-miR-125a, hsa-miR-184 and hsa-miR-16 and an increased expression of hsa-miR-96 could be useful in predicting oral tumorigenesis and importantly in the detection of MRD and decision-making process for postoperative treatment modalities.

Proteomic profiling of high glucose primed monocytes identifies cyclophilin A as a potential secretory marker of inflammation in type 2 diabetes.

Hyperglycemia is widely recognized to be a potent stimulator of monocyte activity, which is a crucial event in the pathogenesis of atherosclerosis. We analyzed the monocyte proteome for potential markers that would enhance the ability to screen for early inflammatory status in Type 2 diabetes mellitus (T2DM), using proteomic technologies. Monocytic cells (THP-1) were primed with high glucose (HG), their protein profiles were analyzed using 2DE and the downregulated differentially expressed spots were identified using MALDI TOF/MS. We selected five proteins that were secretory in function with the help of bioinformatic programs. A predominantly downregulated protein identified as cyclophilin A (sequence coverage 98%) was further validated by immunoblotting experiments. The cellular mRNA levels of cyclophilin A in various HG-primed cells were studied using qRT-PCR assays and it was observed to decrease in a dose-dependent manner. LC-ESI-MS was used to identify this protein in the conditioned media of HG-primed cells and confirmed by Western blotting as well as ELISA. Cyclophilin A was also detected in the plasma of patients with diabetes. We conclude that cyclophilin A is secreted by monocytes in response to HG. Given the paracrine and autocrine actions of cyclophilin A, the secreted immunophilin could be significant for progression of atherosclerosis in type 2 diabetes. Our study also provides evidence that analysis of monocyte secretome is a viable strategy for identifying candidate plasma markers in diabetes.