@article {115259, title = {Exploring the medicinally important secondary metabolites landscape through the lens of transcriptome data in fenugreek (Trigonella foenum graecum L.).}, journal = {Sci Rep}, volume = {12}, year = {2022}, month = {2022 Aug 08}, pages = {13534}, abstract = {

Fenugreek (Trigonella foenum-graecum L.) is a self-pollinated leguminous crop belonging to the Fabaceae family. It is a multipurpose crop used as herb, spice, vegetable and forage. It is a traditional medicinal plant in India attributed with several nutritional and medicinal properties including antidiabetic and anticancer. We have performed a combined transcriptome assembly from RNA sequencing data derived from leaf, stem and root tissues. Around 209,831 transcripts were deciphered from the assembly of 92\% completeness and an N50 of 1382 bases. Whilst secondary metabolites of medicinal value, such as trigonelline, diosgenin, 4-hydroxyisoleucine and quercetin, are distributed in several tissues, we report transcripts that bear sequence signatures of enzymes involved in the biosynthesis of such metabolites and are highly expressed in leaves, stem and roots. One of the antidiabetic alkaloid, trigonelline and its biosynthesising enzyme, is highly abundant in leaves. These findings are of value to nutritional and the pharmaceutical industry.

}, keywords = {Diosgenin, Hypoglycemic Agents, Plant Extracts, Plants, Medicinal, Transcriptome, Trigonella}, issn = {2045-2322}, doi = {10.1038/s41598-022-17779-8}, author = {Naika, Mahantesha B N and Sathyanarayanan, Nitish and Sajeevan, Radha Sivarajan and Bhattacharyya, Teerna and Ghosh, Pritha and Iyer, Meenakshi S and Jarjapu, Mahita and Joshi, Adwait G and Harini, K and Shafi, K Mohamed and Kalmankar, Neha and Karpe, Snehal D and Mam, Bhavika and Pasha, Shaik Naseer and Sowdhamini, Ramanathan} } @article {78096, title = {Dataset for the combined transcriptome assembly of and functional annotation.}, journal = {Data Brief}, volume = {30}, year = {2020}, month = {2020 Jun}, pages = {105416}, abstract = {

In this paper, we present the data acquired during transcriptome analysis of the Moringa oleifera [1] from five different tissues (root, stem, leaf, flower and seed) by RNA sequencing. A total of 271 million reads were assembled with an N50 of 2094 bp. The combined transcriptome was assessed for transcript abundance across five tissues. The protein coding genes identified from the transcripts were annotated and used for orthology analysis. Further, enzymes involved in the biosynthesis of select medicinally important secondary metabolites, vitamins and ion transporters were identified and their expression levels across tissues were examined. The data generated by RNA sequencing has been deposited to NCBI public repository under the accession number PRJNA394193 (https://www.ncbi.nlm.nih.gov/bioproject/PRJNA394193).

}, issn = {2352-3409}, doi = {10.1016/j.dib.2020.105416}, author = {Shafi, K Mohamed and Joshi, Adwait G and Meenakshi, Iyer and Pasha, Shaik Naseer and Harini, K and Mahita, Jarjapu and Sajeevan, Radha Sivarajan and Karpe, Snehal D and Ghosh, Pritha and Nitish, Sathyanarayanan and Gandhimathi, A and Mathew, Oommen K and Prasanna, Subramanian Hari and Malini, Manoharan and Mutt, Eshita and Naika, Mahantesha and Ravooru, Nithin and Rao, Rajas M and Shingate, Prashant N and Sukhwal, Anshul and Sunitha, Margaret S and Upadhyay, Atul K and Vinekar, Rithvik S and Sowdhamini, Ramanathan} } @article {83641, title = {A knowledge-driven protocol for prediction of proteins of interest with an emphasis on biosynthetic pathways.}, journal = {MethodsX}, volume = {7}, year = {2020}, month = {2020}, pages = {101053}, abstract = {

This protocol describes a stepwise process to identify proteins of interest from a query proteome derived from NGS data. We implemented this protocol on transcriptome to identify proteins involved in secondary metabolite and vitamin biosynthesis and ion transport. This knowledge-driven protocol identifies proteins using an integrated approach involving sensitive sequence search and evolutionary relationships. We make use of functionally important residues (FIR) specific for the query protein family identified through its homologous sequences and literature. We screen protein hits based on the clustering with true homologues through phylogenetic tree reconstruction complemented with the FIR mapping. The protocol was validated for the protein hits through qRT-PCR and transcriptome quantification. Our protocol demonstrated a higher specificity as compared to other methods, particularly in distinguishing cross-family hits. This protocol was effective in transcriptome data analysis of as described in Pasha et al.{\textbullet}Knowledge-driven protocol to identify secondary metabolite synthesizing protein in a highly specific manner.{\textbullet}Use of functionally important residues for screening of true hits.{\textbullet}Beneficial for metabolite pathway reconstruction in any (species, metagenomics) NGS data.

}, issn = {2215-0161}, doi = {10.1016/j.mex.2020.101053}, author = {Joshi, Adwait G and Harini, K and Meenakshi, Iyer and Shafi, K Mohamed and Pasha, Shaik Naseer and Mahita, Jarjapu and Sajeevan, Radha Sivarajan and Karpe, Snehal D and Ghosh, Pritha and Nitish, Sathyanarayanan and Gandhimathi, A and Mathew, Oommen K and Prasanna, Subramanian Hari and Malini, Manoharan and Mutt, Eshita and Naika, Mahantesha and Ravooru, Nithin and Rao, Rajas M and Shingate, Prashant N and Sukhwal, Anshul and Sunitha, Margaret S and Upadhyay, Atul K and Vinekar, Rithvik S and Sowdhamini, Ramanathan} } @article {57789, title = {The transcriptome enables the identification of candidate genes behind medicinal value of Drumstick tree (Moringa oleifera).}, journal = {Genomics}, volume = {112}, year = {2020}, month = {01/2020}, pages = {621-628}, abstract = {

Moringa oleifera is a plant well-known for its nutrition value, drought resistance and medicinal properties. cDNA libraries from five different tissues (leaf, root, stem, seed and flower) of M. oleifera cultivar Bhagya were generated and sequenced. We developed a bioinformatics pipeline to assemble transcriptome, along with the previously published M. oleifera genome, to predict 17,148 gene models. Few candidate genes related to biosynthesis of secondary metabolites, vitamins and ion transporters were identified. Expressions were further confirmed by real-time quantitative PCR experiments for few promising leads. Quantitative estimation of metabolites, as well as elemental analysis, was also carried out to support our observations. Enzymes in the biosynthesis of vitamins and metabolites like quercetin and kaempferol are highly expressed in leaves, flowers and seeds. The expression of iron transporters and calcium storage proteins were observed in root and leaves. In general, leaves retain the highest amount of small molecules of interest.

}, issn = {1089-8646}, doi = {10.1016/j.ygeno.2019.04.014}, author = {Pasha, Shaik Naseer and Shafi, K Mohamed and Joshi, Adwait G and Meenakshi, Iyer and Harini, K and Mahita, Jarjapu and Sajeevan, Radha Sivarajan and Karpe, Snehal D and Ghosh, Pritha and Nitish, Sathyanarayanan and Gandhimathi, A and Mathew, Oommen K and Prasanna, Subramanian Hari and Malini, Manoharan and Mutt, Eshita and Naika, Mahantesha and Ravooru, Nithin and Rao, Rajas M and Shingate, Prashant N and Sukhwal, Anshul and Sunitha, Margaret S and Upadhyay, Atul K and Vinekar, Rithvik S and Sowdhamini, Ramanathan} } @article {8107, title = {Genome-wide survey and phylogeny of S-Ribosylhomocysteinase (LuxS) enzyme in bacterial genomes.}, journal = {BMC Genomics}, volume = {17}, year = {2016}, month = {2016}, pages = {742}, abstract = {

BACKGROUND: The study of survival and communication of pathogenic bacteria is important to combat diseases caused by such micro-organisms. Bacterial cells communicate with each other using a density-dependent cell-cell communication process called Quorum Sensing (QS). LuxS protein is an important member of interspecies quorum-sensing system, involved in the biosynthesis of Autoinducer-2 (AI-2), and has been identified as a drug target. Despite the above mentioned significance, their evolution has not been fully studied, particularly from a structural perspective.

RESULTS: Search for LuxS in the non-redundant database of protein sequences yielded 3106 sequences. Phylogenetic analysis of these sequences revealed grouping of sequences into five distinct clusters belonging to different phyla and according to their habitat. A majority of the neighbouring genes of LuxS have been found to be hypothetical proteins. However, gene synteny analyses in different bacterial genomes reveal the presence of few interesting gene neighbours. Moreover, LuxS gene was found to be a component of an operon in only six out of 36 genomes. Analysis of conserved motifs in representative LuxS sequences of different clusters revealed the presence of conserved motifs common to sequences of all the clusters as well as motifs unique to each cluster. Homology modelling of LuxS protein sequences of each cluster revealed few structural features unique to protein of each cluster. Analyses of surface electrostatic potentials of the homology models of each cluster showed the interactions that are common to all the clusters, as well as cluster-specific potentials and therefore interacting partners, which may be unique to each cluster.

CONCLUSIONS: LuxS protein evolved early during the course of bacterial evolution, but has diverged into five subtypes. Analysis of sequence motifs and homology models of representative members reveal cluster-specific structural properties of LuxS. Further, it is also shown that LuxS protein may be involved in various protein-protein or protein-RNA interactions, which may regulate the activity of LuxS proteins in bacteria.

}, issn = {1471-2164}, doi = {10.1186/s12864-016-3002-x}, author = {Rao, Rajas M and Pasha, Shaik Naseer and Sowdhamini, Ramanathan} } @article {7679, title = {Revisiting Myosin Families Through Large-scale Sequence Searches Leads to the Discovery of New Myosins.}, journal = {Evol Bioinform Online}, volume = {12}, year = {2016}, month = {2016}, pages = {201-11}, abstract = {

Myosins are actin-based motor proteins involved in many cellular movements. It is interesting to study the evolutionary patterns and the functional attributes of various types of myosins. Computational search algorithms were performed to identify putative myosin members by phylogenetic analysis, sequence motifs, and coexisting domains. This study is aimed at understanding the distribution and the likely biological functions of myosins encoded in various taxa and available eukaryotic genomes. We report here a phylogenetic analysis of around 4,064 myosin motor domains, built entirely from complete or near-complete myosin repertoires incorporating many unclassified, uncharacterized sequences and new myosin classes, with emphasis on myosins from Fungi, Haptophyta, and other Stramenopiles, Alveolates, and Rhizaria (SAR). The identification of large classes of myosins in Oomycetes, Cellular slime molds, Choanoflagellates, Pelagophytes, Eustigmatophyceae, Fonticula, Eucoccidiorida, and Apicomplexans with novel myosin motif variants that are conserved and thus presumably functional extends our knowledge of this important family of motor proteins. This work provides insights into the distribution and probable function of myosins including newly identified myosin classes.

}, issn = {1176-9343}, doi = {10.4137/EBO.S39880}, author = {Pasha, Shaik Naseer and Meenakshi, Iyer and Sowdhamini, Ramanathan} } @article {161, title = {Genome sequencing of herb Tulsi (Ocimum tenuiflorum) unravels key genes behind its strong medicinal properties.}, journal = {BMC Plant Biol}, volume = {15}, year = {2015}, month = {2015}, pages = {212}, abstract = {

BACKGROUND: Krishna Tulsi, a member of Lamiaceae family, is a herb well known for its spiritual, religious and medicinal importance in India. The common name of this plant is {\textquoteright}Tulsi{\textquoteright} (or {\textquoteright}Tulasi{\textquoteright} or {\textquoteright}Thulasi{\textquoteright}) and is considered sacred by Hindus. We present the draft genome of Ocimum tenuiflurum L (subtype Krishna Tulsi) in this report. The paired-end and mate-pair sequence libraries were generated for the whole genome sequenced with the Illumina Hiseq 1000, resulting in an assembled genome of 374~Mb, with a genome coverage of 61~\% (612~Mb estimated genome size). We have also studied transcriptomes (RNA-Seq) of two subtypes of O. tenuiflorum, Krishna and Rama Tulsi and report the relative expression of genes in both the varieties.

RESULTS: The pathways leading to the production of medicinally-important specialized metabolites have been studied in detail, in relation to similar pathways in Arabidopsis thaliana and other plants. Expression levels of anthocyanin biosynthesis-related genes in leaf samples of Krishna Tulsi were observed to be relatively high, explaining the purple colouration of Krishna Tulsi leaves. The expression of six important genes identified from genome data were validated by performing q-RT-PCR in different tissues of five different species, which shows the high extent of urosolic acid-producing genes in young leaves of the Rama subtype. In addition, the presence of eugenol and ursolic acid, implied as potential drugs in the cure of many diseases including cancer was confirmed using mass spectrometry.

CONCLUSIONS: The availability of the whole genome of O.tenuiflorum and our sequence analysis suggests that small amino acid changes at the functional sites of genes involved in metabolite synthesis pathways confer special medicinal properties to this herb.

}, issn = {1471-2229}, doi = {10.1186/s12870-015-0562-x}, author = {Upadhyay, Atul K and Chacko, Anita R and Gandhimathi, A and Ghosh, Pritha and Harini, K and Joseph, Agnel P and Joshi, Adwait G and Karpe, Snehal D and Kaushik, Swati and Kuravadi, Nagesh and Lingu, Chandana S and Mahita, J and Malarini, Ramya and Malhotra, Sony and Malini, Manoharan and Mathew, Oommen K and Mutt, Eshita and Naika, Mahantesha and Nitish, Sathyanarayanan and Pasha, Shaik Naseer and Raghavender, Upadhyayula S and Rajamani, Anantharamanan and Shilpa, S and Shingate, Prashant N and Singh, Heikham Russiachand and Sukhwal, Anshul and Sunitha, Margaret S and Sumathi, Manojkumar and Ramaswamy, S and Gowda, Malali and Sowdhamini, Ramanathan} }