Transcriptional dynamics in source-sink tissues identifies molecular factors regulating the corm development process in saffron (Crocus sativus L.).

AIMS: Geophytic plants have evolved to develop underground storage organs (USO) in the active growing season to withstand harsh environments as well as to coordinate growth and reproduction when conditions are favourable. Saffron is an autumn flowering geophyte and an expensive spice crop restricted to certain geographical locations in the world. Saffron, being sterile, does not produce seeds and thus propagates only through corms, the quality of which determines its yield. Corm development in saffron is unexplored and the underlying molecular mechanism is still elusive. In this study, we performed an extensive characterisation of the transcriptional dynamics in the source (leaf) and sink (corm) tissues during corm development in saffron. KEY RESULTS: Via morphological and transcriptome studies, we identified molecular factors regulating corm development process in saffron, which defined corm development into three stages: the initiation stage demonstrates enhanced vegetative growth aboveground and swelling of shoot base belowground due to active cell division & carbohydrate storage; the bulking stage comprises of increased source and sink strength, active photosynthesis, circadian gating and starch accumulation; the maturation stage represents reduced source and sink strength, lowered photosynthesis, sugar transport, starch synthesis and cell cycle arrest. UTILITY: The global view of transcriptional changes in source and sink identifies similar and new molecular factors involved in the saffron corm development process compared to USO formation in other geophytes and provides a valuable resource for dissecting the molecular network underlying the corm development. We propose a hypothetical model based on data analysis, of how molecular factors via environmental cues can regulate the corm development process in saffron.

Advances in machine intelligence-driven virtual screening approaches for big-data.

Virtual screening (VS) is an integral and ever-evolving domain of drug discovery framework. The VS is traditionally classified into ligand-based (LB) and structure-based (SB) approaches. Machine intelligence or artificial intelligence has wide applications in the drug discovery domain to reduce time and resource consumption. In combination with machine intelligence algorithms, VS has emerged into revolutionarily progressive technology that learns within robust decision orders for data curation and hit molecule screening from large VS libraries in minutes or hours. The exponential growth of chemical and biological data has evolved as "big-data" in the public domain demands modern and advanced machine intelligence-driven VS approaches to screen hit molecules from ultra-large VS libraries. VS has evolved from an individual approach (LB and SB) to integrated LB and SB techniques to explore various ligand and target protein aspects for the enhanced rate of appropriate hit molecule prediction. Current trends demand advanced and intelligent solutions to handle enormous data in drug discovery domain for screening and optimizing hits or lead with fewer or no false positive hits. Following the big-data drift and tremendous growth in computational architecture, we presented this review. Here, the article categorized and emphasized individual VS techniques, detailed literature presented for machine learning implementation, modern machine intelligence approaches, and limitations and deliberated the future prospects.

Systematic analyses with genomic and metabolomic insights reveal a new species, Ophiocordyceps indica sp. nov. from treeline area of Indian Western Himalayan region.

Ophiocordyceps is a species-rich genus in the order Hypocreales (Sordariomycetes, Ascomycota) depicting a fascinating relationship between microbes and insects. In the present study, a new species, Ophiocordyceps indica sp. nov., is discovered infecting lepidopteran larvae from tree line locations (2,202-2,653 m AMSL) of the Kullu District, Himachal Pradesh, Indian Western Himalayan region, using combinations of morphological and molecular phylogenetic analyses. A phylogeny for Ophiocordyceps based on a combined multigene (nrSSU, nrLSU, tef-1α, and RPB1) dataset is provided, and its taxonomic status within Ophiocordycipitaceae is briefly discussed. Its genome size (~59 Mb) revealed 94% genetic similarity with O. sinensis; however, it differs from other extant Ophiocordyceps species based on morphological characteristics, molecular phylogenetic relationships, and genetic distance. O. indica is identified as the second homothallic species in the family Ophiocordycipitaceae, after O. sinensis. The presence of targeted marker components, viz. nucleosides (2,303.25 µg/g), amino acids (6.15%), mannitol (10.13%), and biological activity data, suggests it to be a new potential source of nutraceutical importance. Data generated around this economically important species will expand our understanding regarding the diversity of Ophiocordyceps-like taxa from new locations, thus providing new research avenues.

IHM-DB: a curated collection of metagenomics data from the Indian Himalayan Region, and automated pipeline for 16S rRNA amplicon-based analysis (AutoQii2).

Indian Himalayan metagenome database (IHM-DB) is a web-based database consisting of information on metagenomic datasets from various databases and publications that are specifically reported from the Indian Himalayan Region (IHR). The online interface allows users to view or download the dataset-specific information for the respective states, category-wise, or according to the hypervariable region. The IHM-DB also provides an opportunity for the users to access the metagenomic publications from the IHR as well as upload their microbiome information to the website. Additionally, an open-source 16S rRNA amplicon-based automated bioinformatics pipeline, AutoQii2, allows users to analyze the single-end and paired-end raw reads. AutoQii2 provides an automated approach for performing analysis such as quality check, adapter and chimera removal and exploits the latest ribosomal database project classifier for taxonomic assignments. The source code of the AutoQii2 pipeline is available at https://gitlab.com/khatriabhi2319/autoqii2. Database URL https://ham.ihbt.res.in/ihmdb and https://fgcsl.ihbt.res.in/ihmdb.

Effector protein structures: a tale of evolutionary relationship.

Effector proteins are highly diverse, often lacking similarity in their protein sequences, making it challenging to determine their biological function. Using AlphaFold2 (AF2), Seong and Krasileva recently found that effector structures, but not sequences, share commonality. This helps further understanding of effector evolution across fungal species and reveals unique sequence-unrelated, structurally similar, effector families.

Machine intelligence-guided selection of optimized inhibitor for human immunodeficiency virus (HIV) from natural products.

The human immunodeficiency virus (HIV) connects to the cluster of differentiation (CD4) and any of the entry co-receptors (CCR5 and CXCR4); followed by unloading the viral genome, reverse transcriptase, and integrase enzymes within the host cell. The co-receptors facilitate the entry of virus and vital enzymes, leading to replication and pre-maturation of viral particles within the host. The protease enzyme transforms the immature viral vesicles into the mature virion. The pivotal role of co-receptors and enzymes in homeostasis and growth makes the crucial target for anti-HIV drug discovery, and the availability of X-ray crystal structures is an asset. Here, we used the machine intelligence-driven framework (A-HIOT) to identify and optimize target-based potential hit molecules for five significant protein targets from the ZINC15 database (natural products dataset). Following validation with dynamic motion behavior analysis and molecular dynamics simulation, the optimized hits were evaluated using in silico ADMET filtration. Furthermore, three molecules were screened, optimized, and validated: ZINC00005328058 for CCR5 and protease, ZINC000254014855 for CXCR4 and integrase, and ZINC000000538471 for reverse transcriptase. In clinical trials, the ZINC000254014855 and ZINC000254014855 were passed in primary screens for vif-HIV-1, and we reported the specific receptor as well as interactions. As a result, the validated molecules may be investigated further in experimental studies targeting specific receptors in order to design and synergize an anti-HIV regimen.

Deep learning based protocol to construct an immune-related gene network of host-pathogen interactions in plants.

Investigating network behavior from host-pathogen interactions is challenging. Here, we present the deep-learning-based protocol to construct an immune-related gene network and list the genes involved in the defense response of host to specific biotic stress. The protocol includes the steps to pre-process the interaction pairs and expression profile of plants treated with pathogen/control, feed as input for DLNet algorithm to rank genes based on their contribution to data classification. The top-ranked genes are subjected to module and enrichment analysis. For complete details on the use and execution of this protocol, please refer to Kumar et al. (2022).1.

Finite flame thickness effects on Kolmogorov-Petrovsky-Piskunov turbulent burning velocities.

KPP (Kolmogorov-Petrovsky-Piskunov) solutions of the reaction-diffusion equation have application in various physical phenomena occurring in biology, ecology, and reacting flows. In particular, these solutions are commonly used in turbulent combustion to scale turbulent burning velocities. Subject to certain conditions on reaction rate profile through the flame brush and turbulent diffusivity, this theory relates the turbulent burning velocity to the derivative of the reaction rate (ω[over ̃]) at the leading edge of the flame brush (dω[over ̃]/dc[over ̃]|_{c[over ̃]=0}). Such waves are often referred to as "pulled fronts." However, turbulent flames never actually satisfy the KPP conditions for a pulled front, as the turbulent flame brush, parametrized here by the thickness δ_{t}, consists of an ensemble of laminar flamelets of thickness δ, where ε=δ/δ_{t}≪1 is very small, but nonzero, and dω[over ̃]/dc[over ̃] tends to zero at the brush leading edge for high activation energy, combustion-type kinetics. This paper analyzes these effects on KPP wave solutions, parametrized by ε=δ/δ_{t} and Zeldovich number Ze focusing on whether turbulent flames retain their pulled front character and what the correction to the KPP wave speed is. Variational solutions of the reaction-diffusion equation show that the solution can be expanded in powers of 1/|lnε|. Both numerical and asymptotic results are presented, showing that the wave still exhibits pulled front solutions but with significant corrections to the KPP result. The leading order correction is of the form |lnε|^{-2} and independent of Ze. Higher order corrections are function of both ε and Ze. However, the dominant factor influencing the wave speed correction is due to the finite ε, with Ze exhibiting a weaker effect.

Machine intelligence-driven framework for optimized hit selection in virtual screening.

Virtual screening (VS) aids in prioritizing unknown bio-interactions between compounds and protein targets for empirical drug discovery. In standard VS exercise, roughly 10% of top-ranked molecules exhibit activity when examined in biochemical assays, which accounts for many false positive hits, making it an arduous task. Attempts for conquering false-hit rates were developed through either ligand-based or structure-based VS separately; however, nonetheless performed remarkably well. Here, we present an advanced VS framework-automated hit identification and optimization tool (A-HIOT)-comprises chemical space-driven stacked ensemble for identification and protein space-driven deep learning architectures for optimization of an array of specific hits for fixed protein receptors. A-HIOT implements numerous open-source algorithms intending to integrate chemical and protein space leading to a high-quality prediction. The optimized hits are the selective molecules which we retrieve after extreme refinement implying chemical space and protein space modules of A-HIOT. Using CXC chemokine receptor 4, we demonstrated the superior performance of A-HIOT for hit molecule identification and optimization with tenfold cross-validation accuracies of 94.8% and 81.9%, respectively. In comparison with other machine learning algorithms, A-HIOT achieved higher accuracies of 96.2% for hit identification and 89.9% for hit optimization on independent benchmark datasets for CXCR4 and 86.8% for hit identification and 90.2% for hit optimization on independent test dataset for androgen receptor (AR), thus, shows its generalizability and robustness. In conclusion, advantageous features impeded in A-HIOT is making a reliable approach for bridging the long-standing gap between ligand-based and structure-based VS in finding the optimized hits for the desired receptor. The complete resource (framework) code is available at https://gitlab.com/neeraj-24/A-HIOT .

Deep learning uncovers distinct behavior of rice network to pathogens response.

Rice, apart from abiotic stress, is prone to attack from multiple pathogens. Predominantly, the two rice pathogens, bacterial Xanthomonas oryzae (Xoo) and hemibiotrophic fungus, Magnaporthe oryzae, are extensively well explored for more than the last decade. However, because of lack of holistic studies, we design a deep learning-based rice network model (DLNet) that has explored the quantitative differences resulting in the distinct rice network architecture. Validation studies on rice in response to biotic stresses show that DLNet outperforms other machine learning methods. The current finding indicates the compactness of the rice PTI network and the rise of independent modules in the rice ETI network, resulting in similar patterns of the plant immune response. The results also show more independent network modules and minimum structural disorderness in rice-M. oryzae as compared to the rice-Xoo model revealing the different adaptation strategies of the rice plant to evade pathogen effectors.

Comparative transcriptome and tissue-specific expression analysis of genes reveal tissue-cultured plants as an alternative source for phenylethanoids and phenylpropanoids in Rhodiola imbricata (Edgew.).

Rhodiola imbricata (Crassulaceae) is a traditional trans-Himalayan endangered medicinal herb with immense therapeutic applications. Over the years, over-exploitation, un-managed harvesting, and lack of captive cultivation procedures persuaded threat to its wild habitat. Plant tissue culture and RNA-Seq-based molecular bioprospection of key regulatory genes aid the understanding of molecular dynamics involved in specialized metabolites (phenylethanoids and phenylpropanoids) biosynthesis and its sustainable production. Hence, comparative transcriptomic analysis was performed using leaf and root tissues from the wild and tissue-cultured plants, revealing tissue-specific production of salidroside and rosavin. The transcriptome profiling resulted in 345 million high-quality reads yielding 92,380 unique transcripts with an N50 of 1260 bp. Tissue-specific gene expression analysis revealed that both phenylethanoids and phenylpropanoids biosynthesis are predominantly associated with the shikimate pathway. In addition to RNA-Seq data, the downstream biosynthesis pathways genes viz., phospho-2-dehydro-3-deoxyheptonate aldolase (DAHPS), 3-dehydroquinate synthase (DHQS), shikimate kinase (SK), chorismate mutase (CM), arogenate dehydrogenase (TYRAAT), aromatic-L-amino-acid decarboxylase (TDC), phenylalanine ammonia-lyase (PAL), 4-coumarate-CoA ligase (4-CL), cinnamoyl-CoA reductase (CCR), and cinnamyl alcohol dehydrogenase (CAD) showed higher expression pattern in wild plant tissues compared to tissue-cultured plants. The transcript fold expression determined by RT-qPCR results followed similar patterns as those observed in RNA-seq and targeted metabolite profiling data. Salidroside and rosavin content in wild plants exhibited 2.40 fold and 1.77 fold increase accumulation compared to the tissue-cultured plant. The present investigation explained the tissue and condition-specific significant differences between the expression of proposed biosynthetic pathway genes and salidroside and rosavin content. Additionally, NAC, bHLH, and ARF were the most abundant transcription factor families found in the transcriptomic analysis of R. imbricata. The generated transcriptome dataset provides a valuable gene(s)/transcription factors hub that can be used for the sustainable production of salidroside and rosavin in R. imbricata under tissue culture conditions.

Swertia purpurascens Wall ethanolic extract mitigates hepatic fibrosis and restores hepatic hepcidin levels via inhibition of TGFß/SMAD/NFκB signaling in rats.

ETHNOPHARMACOLOGICAL RELEVANCE: Swertia purpurascens Wall belongs to a well-known genus in traditional systems of medicine worldwide. In folklore, it is used to treat various ailments, including hepatic disorders, as an alternative to the endangered species Swertia chirayita. However, the therapeutic potential of Swertia purpurascens Wall against hepatic fibrosis has not been validated yet. AIM OF THE STUDY: The present study was planned to evaluate the efficacy of the Swertia purpurascens Wall extract (SPE) against hepatic fibrosis and elucidate the underlying mechanism of action. MATERIALS AND METHODS: The metabolite profiling of the SPE was done using UHPLC-QTOF-MS/MS. The acute oral toxicity study of SPE at 2 g/kg BW dose was done in rats. Further, the liver fibrosis was induced by the CCl4 intoxication, and the efficacy of SPE at three doses (100, 200 and 400 mg/kg BW) was evaluated by studying biochemical parameters, histopathology, immunohistochemistry, qRT-PCR, western blotting and in silico analysis. RESULTS: UHPLC-QTOF-MS/MS analysis revealed the presence of a total of 23 compounds in SPE. Acute oral toxicity study of SPE at 2 g/kg BW showed no harmful effects in rats. Further, the liver fibrosis was induced by the CCl4 administration, and the efficacy of SPE was evaluated at three doses (100, 200 and 400 mg/kg BW). SPE treatment significantly improved the body weight gain, the relative liver weight, serum liver injury markers and endogenous antioxidant enzyme levels in the CCl4-treated rats. SPE also recovered the altered liver histology and effectively reduced the fibrotic tissue deposition in the hepatic parenchyma. Further, SPE significantly inhibited the fibrotic (TGFß, αSMA, SMADs and Col1A), proinflammatory markers (NFκB, TNFα and IL1ß) and apoptosis in the liver tissue. Interestingly, SPE treatment also restored the altered hepcidin levels in the liver tissue. In silico study revealed the potential of various metabolites as drug candidates and their interaction with target proteins. CONCLUSION: Altogether, SPE showed its therapeutic potential against CCl4-induced hepatic fibrosis by restoring the hepatic hepcidin levels and inhibiting TGFß/SMAD/NFκB signaling in rats.

DNA damage response proteins synergistically affect the cancer prognosis and resistance.

Amplification of oxidative stress can be utilized as a strategy to attenuate cancer progression by instigating apoptosis. However, the duration of positive response to such therapies is limited, as cancer cells eventually develop resistance. The underlying molecular mechanisms of cancer cells to escape apoptosis under oxidative stress is unknown. Employing big data, and its integration with transcriptome, proteome and network analysis in six cancer types revealed system-level interactions between DNA damage response (DDR) proteins, including; DNA damage repair, cell cycle checkpoints and anti-apoptotic proteins. Cancer system biology is used to elucidate mechanisms for cancer progression, but networks defining mechanisms causing resistance is less explored. Using system biology, we identified DDR hubs between G1-S and M phases that were associated with bad prognosis. The increased expression of DDR network was involved in resistance under high oxidative stress. We validated our findings by combining H2O2 induced oxidative stress and DDR inhibitors in human lung cancer cells to conclude the necessity of targeting a 'disease-causing network'. Collectively, our work provides insights toward designing strategies for network pharmacology to combat resistance in cancer research.

De novo transcriptome analysis provides insights into formation of in vitro adventitious root from leaf explants of Arnebia euchroma.

BACKGROUND: Adventitious root formation is considered a major developmental step during the propagation of difficult to root plants, especially in horticultural crops. Recently, adventitious roots induced through plant tissue culture methods have also been used for production of phytochemicals such as flavonoids, anthocyanins and anthraquinones. It is rather well understood which horticultural species will easily form adventitious roots, but the factors affecting this process at molecular level or regulating the induction process in in vitro conditions are far less known. The present study was conducted to identify transcripts involved in in vitro induction and formation of adventitious roots using Arnebia euchroma leaves at different time points (intact leaf (control), 3 h, 12 h, 24 h, 3 d, 7 d, 10 d and 15 d). A. euchroma is an endangered medicinal Himalayan herb whose root contains red naphthoquinone pigments. These phytoconstituents are widely used as an herbal ingredient in Asian traditional medicine as well as natural colouring agent in food and cosmetics. RESULTS: A total of 137.93 to 293.76 million raw reads were generated and assembled to 54,587 transcripts with average length of 1512.27 bps and N50 of 2193 bps, respectively. In addition, 50,107 differentially expressed genes were identified and found to be involved in plant hormone signal transduction, cell wall modification and wound induced mitogen activated protein kinase signalling. The data exhibited dominance of auxin responsive (AUXIN RESPONSE FACTOR8, IAA13, GRETCHEN HAGEN3.1) and sucrose translocation (BETA-31 FRUCTOFURANOSIDASE and MONOSACCHARIDE-SENSING protein1) genes during induction phase. In the initiation phase, the expression of LATERAL ORGAN BOUNDARIES DOMAIN16, EXPANSIN-B15, ENDOGLUCANASE25 and LEUCINE-rich repeat EXTENSION-like proteins was increased. During the expression phase, the same transcripts, with exception of LATERAL ORGAN BOUNDARIES DOMAIN16 were identified. Overall, the transcriptomic analysis revealed a similar patterns of genes, however, their expression level varied in subsequent phases of in vitro adventitious root formation in A. euchroma. CONCLUSION: The results presented here will be helpful in understanding key regulators of in vitro adventitious root development in Arnebia species, which may be deployed in the future for phytochemical production at a commercial scale.

Vitex negundo Linn. extract alleviates inflammatory aggravation and lung injury by modulating AMPK/PI3K/Akt/p38-NF-κB and TGF-ß/Smad/Bcl2/caspase/LC3 cascade and macrophages activation in murine model of OVA-LPS induced allergic asthma.

ETHNOPHARMACOLOGICAL RELEVANCE: There is growing inclination towards developing bioactive molecule-based strategies for the management of allergic airway inflammation associated respiratory diseases. Vitex negundo Linn., also known as Nirgundi, is one such medicinal plant enriched with phytochemicals and used for inflammatory and respiratory disorders including asthma in traditional system of medicine. Preliminary studies have claimed anti-tussive and bronchodilator potential of V. negundo Linn. However, its attributes as well as molecular mechanism (s) in modulation of asthma mediated by allergic inflammation are yet to be delineated scientifically. AIM OF THE STUDY: Present study attempted to assess the effectiveness of Vitex negundo leaf extract (VNLE) in mitigation of allergen induced inflammation associated asthmatic lung damage with emphasis to delineate its molecular mechanism (s). MATERIALS AND METHODS: Allergic lung inflammation was established in Balb/c mice using Ovalbumin-lipopolysaccharide (OVA-LPS). Several allergic inflammatory parameters, histopathological changes, alveolar macrophage activation and signalling pathways were assessed to examine protective effects of VNLE. UHPLC-DAD-QTOF-ESI-IMS was used to characterize VLNE. RESULTS: VNLE administration effectively attenuated LPS-induced oxi-inflammatory stress in macrophages suggesting its anti-inflammatory potential. Further, VNLE showed protective effect in mitigating asthmatic lung damage as evident by reversal of pathological changes including inflammatory cell influx, congestion, fibrosis, bronchial thickness and alveolar collapse observed in allergen group. VNLE suppressed expressions of inflammatory Th1/Th2 cytokines, chemokines, endopeptidases (MMPs), oxidative effector enzyme (iNOS), adhesion molecules, IL-4/IFN-γ release with simultaneous enhancement in levels of IL-10, IFN-γ, MUC3 and tight junction proteins. Subsequent mechanistic investigation revealed that OVA-LPS concomitantly enhanced phosphorylation of NF-κB, PI3K, Akt and p38MAPKs and downregulated AMPK which was categorically counteracted by VNLE treatment. VNLE also suppressed OVA-LPS induced fibrosis, apoptosis, autophagy and gap junction proteins which were affirmed by reduction in TGF-ß, Smad2/3/4, Caspase9/3, Bax, LC3A/B, connexin 50, connexin 43 and enhancement in Bcl2 expression. Additionally, suppression of alveolar macrophage activation, inflammatory cells in blood and elevation of splenic CD8+T cells was demonstrated. UHPLC-DAD-QTOF-ESI-IMS revealed presence of iridoids glycoside and phenolics which might contribute these findings. CONCLUSION: These findings confer protective effect of VNLE in attenuation of allergic lung inflammation and suggest that it could be considered as valuable medicinal source for developing safe natural therapeutics for mitigation of allergic inflammation during asthma.

Deciphering key regulators involved in epilepsy-induced cardiac damage through whole transcriptome and proteome analysis in a rat model.

OBJECTIVE: Sudden unexpected death in epilepsy (SUDEP) is a major outcome of cardiac dysfunction in patients with epilepsy. In continuation of our previous work, the present study was envisaged to explore the key regulators responsible for cardiac damage associated with chronic seizures using whole transcriptome and proteome analysis in a rat model of temporal lobe epilepsy. METHODS: A standard lithium-pilocarpine protocol was used to induce recurrent seizures in rats. The isolated rat heart tissue was subjected to transcriptomic and proteomic analysis. An integrated approach of RNA-Seq, proteomics, and system biology analysis was used to identify key regulators involved in seizure-linked cardiac changes. The analyzed differential expression patterns and network interactions were supported by gene and protein expression studies. RESULTS: Altogether, 1157 differentially expressed genes and 1264 proteins were identified in the cardiac tissue of epileptic animals through RNA-Seq and liquid chromatography with tandem mass spectrometry-based proteomic analysis, respectively. The network analysis revealed seven critical genes-STAT3, Myc, Fos, Erbb2, Erbb3, Notch1, and Mapk8-that could play a role in seizure-mediated cardiac changes. The LC-MS/MS analysis supported the activation of the transforming growth factor ß (TGF-ß) pathway in the heart of epileptic animals. Furthermore, our gene and protein expression studies established a key role of STAT3, Erbb, and Mapk8 to develop cardiac changes linked with recurrent seizures. SIGNIFICANCE: The present multi-omics study identified STAT3, Mapk8, and Erbb as key regulators involved in seizure-associated cardiac changes. It provided a deeper understanding of molecular, cellular, and network-level operations of the identified regulators that lead to cardiac changes in epilepsy.

Comparative transcriptome analysis infers bulb derived in vitro cultures as a promising source for sipeimine biosynthesis in Fritillaria cirrhosa D. Don (Liliaceae, syn. Fritillaria roylei Hook.) - High value Himalayan medicinal herb.

Fritillaria cirrhosa D. Don (Liliaceae, syn. Fritillaria roylei Hook.) is a critically endangered medicinal herb of immense importance due to its pharmaceutical bioactive compound, especially sipeimine, used for the treatment of chronic respiratory disorders. However, the industrial demand for sipeimine solely depends on its endangered natural habitat. Therefore; there is an utmost need for its biodiversity conservation as well as for the sustainable utilization of phytochemicals. Plant cell culture and transcriptomics-based molecular bioprospection of key regulatory genes involved in sipeimine biosynthesis as such will play a crucial role in exploring the unexplored traits, that are in supply crisis or nearly in extinction stage. De novo comparative transcriptome sequencing of the bulb (in vivo), callus, and regenerated plantlets (in vitro) resulted in more than 150 million high-quality paired-end clean reads that assembled into final 31,428 transcripts. Functional annotation and unigenes classification with multiple public databases such as KEGG, Refseq, Uniprot, TAIR, GO, and COG, etc. along with chemical structures and functional biocatalytic activity analysis of different steroidal alkaloids facilitated the identification of 30 unigenes specific to sipeimine biosynthesis. Additionally, ABC transporters and TFs like bHLH, MYC, MYB, and WRKY suggests their possible role in metabolite translocation and regulation in vivo as well as in vitro tissues. Differential gene expression and quantitative analysis revealed that the MVA pathway probably the predominant route for 5C intermediate (IPP & DMAPP) biosynthesis. Further, the genes involved in the downstream biosynthesis pathway viz. SQLE, CAS1, SMT1, SMO1, SMO2, SC5DL, DHCR7, DHCR24, CYP710A, 3ß-HSD, CYP90D2, and CYP374A6 shown similar expression pattern with RNA-Seq and qRT-PCR findings. The positive correlation between higher expression of proposed biosynthetic pathway genes and relatively higher accumulation of sipeimine in differentiated naturally grown bulb tissues (in vivo), undifferentiated cells (callus), and de-differentiated tissues i.e. regenerated plantlets (in vitro) has been evident from the present study. Comprehensive genomic resources created in F. cirrhosa will provide strong evidence of bulb derived in vitro culture as an alternative promising source for steroidal alkaloids biosynthesis and metabolite upscaling through genetic and metabolic engineering.

Comparative genomics and molecular adaptational analysis of Arthrobacter from Sikkim Himalaya provided insights into its survivability under multiple high-altitude stress.

Arthrobacter is a dominant aerobic bacterium under the class Actinobacteria, known for its nutritionally versatile nature and wide prevalence in stressful environments. In the current study representative two strains of Arthrobacter, ERGS1:01 and ERGS4:06, with efficient survivability under high altitude stress conditions were selected for comparative genomic studies with their mesophilic counterparts. Physiological analysis and genome insights supported the survival of these strains under multiple high-altitude stress conditions. Molecular cold-adaptation and substitution analysis of the studied strains supported the incidence of more cold-adapted proteins for functionality at low temperatures. Studied strains preferred amino acids like serine, asparagine, lysine, tryptophan for favoring increased flexibility supporting their broad temperature survivability. To the best of our knowledge, this is the first molecular cold adaptation analysis performed for the genus Arthrobacter and has revealed that 'aromaticity', one of the cold-adaptor indicators, should be carefully considered while evaluating cold adaptation strategies in psychrotrophic/psychrophilic bacteria.

A Broad Temperature Active Lipase Purified From a Psychrotrophic Bacterium of Sikkim Himalaya With Potential Application in Detergent Formulation.

Bacterial lipases with activity spanning over a broad temperature and substrate range have several industrial applications. An efficient enzyme-producing bacterium Chryseobacterium polytrichastri ERMR1:04, previously reported from Sikkim Himalaya, was explored for purification and characterization of cold-adapted lipase. Optimum lipase production was observed in 1% (v/v) rice bran oil, pH 7 at 20°C. Size exclusion and hydrophobic interaction chromatography purified the enzyme up to 21.3-fold predicting it to be a hexameric protein of 250 kDa, with 39.8 kDa monomeric unit. MALDI-TOF-MS analysis of the purified lipase showed maximum similarity with alpha/beta hydrolase (lipase superfamily). Biochemical characterization of the purified enzyme revealed optimum pH (8.0), temperature (37°C) and activity over a temperature range of 5-65°C. The tested metals (except Cu2+ and Fe2+) enhanced the enzyme activity and it was tolerant to 5% (v/v) methanol and isopropanol. The Km and Vmax values were determined as 0.104 mM and 3.58 U/mg, respectively for p-nitrophenyl palmitate. Bioinformatics analysis also supported in vitro findings by predicting enzyme's broad temperature and substrate specificity. The compatibility of the purified lipase with regular commercial detergents, coupled with its versatile temperature and substrate range, renders the given enzyme a promising biocatalyst for potential detergent formulations.

Complete genome sequence of Pseudomonas frederiksbergensis ERDD5:01 revealed genetic bases for survivability at high altitude ecosystem and bioprospection potential.

Pseudomonas frederiksbergensis ERDD5:01 is a psychrotrophic bacteria isolated from the glacial stream flowing from East Rathong glacier in Sikkim Himalaya. The strain showed survivability at high altitude stress conditions like freezing, frequent freeze-thaw cycles, and UV-C radiations. The complete genome of 5,746,824 bp circular chromosome and a plasmid of 371,027 bp was sequenced to understand the genetic basis of its survival strategy. Multiple copies of cold-associated genes encoding cold active chaperons, general stress response, osmotic stress, oxidative stress, membrane/cell wall alteration, carbon storage/starvation and, DNA repair mechanisms supported its survivability at extreme cold and radiations corroborating with the bacterial physiological findings. The molecular cold adaptation analysis in comparison with the genome of 15 mesophilic Pseudomonas species revealed functional insight into the strategies of cold adaptation. The genomic data also revealed the presence of industrially important enzymes.