Emphasizing the Role of Long Non-Coding RNAs (lncRNA), Circular RNA (circRNA), and Micropeptides (miPs) in Plant Biotic Stress Tolerance.

Biotic stress tolerance in plants is complex as it relies solely on specific innate immune responses from different plant species combating diverse pathogens. Each component of the plant immune system is crucial to comprehend the molecular basis underlying sustainable resistance response. Among many other regulatory components, long non-coding RNAs (lncRNAs) and circular RNAs (circRNAs) have recently emerged as novel regulatory control switches in plant development and stress biology. Besides, miPs, the small peptides (100-150 amino acids long) encoded by some of the non-coding portions of the genome also turned out to be paramount regulators of plant stress. Although some studies have been performed in deciphering the role of miPs in abiotic stress tolerance, their function in regulating biotic stress tolerance is still largely elusive. Hence, the present review focuses on the roles of long non-coding RNAs (lncRNAs) and circular RNAs (circRNAs) in combating biotic stress in plants. The probable role of miPs in plant-microbe interaction is also comprehensively highlighted. This review enhances our current understanding of plant lncRNAs, circRNAs, and miPs in biotic stress tolerance and raises intriguing questions worth following up.

The captivating role of calcium in plant-microbe interaction.

Plant immune response is fascinating due to the complete absence of a humoral system. The adaptive immune response in plants relies on the intracellular orchestration of signalling molecules or intermediates associated with transcriptional reprogramming. Plant disease response phenomena largely depend on pathogen recognition, signal perception, and intracellular signal transduction. The pathogens possess specific pathogen-associated molecular patterns (PAMP) or microbe-associated molecular patterns (MAMP), which are first identified by pattern recognition receptors (PRRs) of host plants for successful infection. After successful pathogen recognition, the defence response is initiated within plants. The first line of non-specific defence response is called PAMP-triggered immunity (PTI), followed by the specific robust signalling is called effector-triggered immunity (ETI). Calcium plays a crucial role in both PTI and ETI. The biphasic induction of reactive oxygen species (ROS) is inevitable in any plant-microbe interaction. Calcium ions play crucial roles in the initial oxidative burst and ROS induction. Different pathogens can induce calcium accumulation in the cytosol ([Ca2+]Cyt), called calcium signatures. These calcium signatures further control the diverse defence-responsive proteins in the intracellular milieu. These calcium signatures then activate calcium-dependent protein kinases (CDPKs), calcium calmodulins (CaMs), calcineurin B-like proteins (CBLs), etc., to impart intricate defence signalling within the cell. Decoding this calcium ionic map is imperative to unveil any plant microbe interplay and modulate defence-responsive pathways. Hence, the present review is unique in developing concepts of calcium signature in plants and their subsequent decoding mechanism. This review also intends to articulate early sensing of calcium oscillation, signalling events, and comprehensive mechanistic roles of calcium within plants during pathogenic ingression. This will accumulate and summarize the exciting roles of calcium ions in plant immunity and provide the foundation for future research.

Natural therapeutics against SARS CoV2: the potentiality and challenges.

The incidence of the COVID-19 pandemic completely reoriented global socio-economic parameters and human civilization have experienced the worst situation in the recent past. The rapid mutation rates in viruses have continuously been creating emerging variants of concerns (VOCs) which devastated different parts of the world with subsequent waves of infection. Although, series of antiviral drugs and vaccines were formulated but cent percent effectiveness of these drugs is still awaited. Many of these drugs have different side effects which necessitate proper trial before release. Plants are the storehouse of antimicrobial metabolites which have also long been utilized as traditional medicines against different viral infections. Although, proper mechanism of action of these traditional medicines are unknown, they may be a potential source of effective anti-COVID drug for future implications. Advanced bioinformatic applications have opened up a new arena in predicting these repurposed drugs as a potential COVID mitigator. The present review summarizes brief accounts of the corona virus with their possible entry mechanism. This study also tries to classify different possible anti COVID-19 plant-derived metabolites based on their probable mode of action. This review will surely provide useful information on repurposed drugs to combat COVID-19 in this critical situation.

Application of a maximal-clique based community detection algorithm to gut microbiome data reveals driver microbes during influenza A virus infection.

Influenza A Virus (IAV) infection followed by bacterial pneumonia often leads to hospitalization and death in individuals from high risk groups. Following infection, IAV triggers the process of viral RNA replication which in turn disrupts healthy gut microbial community, while the gut microbiota plays an instrumental role in protecting the host by evolving colonization resistance. Although the underlying mechanisms of IAV infection have been unraveled, the underlying complex mechanisms evolved by gut microbiota in order to induce host immune response following IAV infection remain evasive. In this work, we developed a novel Maximal-Clique based Community Detection algorithm for Weighted undirected Networks (MCCD-WN) and compared its performance with other existing algorithms using three sets of benchmark networks. Moreover, we applied our algorithm to gut microbiome data derived from fecal samples of both healthy and IAV-infected pigs over a sequence of time-points. The results we obtained from the real-life IAV dataset unveil the role of the microbial families Ruminococcaceae, Lachnospiraceae, Spirochaetaceae and Prevotellaceae in the gut microbiome of the IAV-infected cohort. Furthermore, the additional integration of metaproteomic data enabled not only the identification of microbial biomarkers, but also the elucidation of their functional roles in protecting the host following IAV infection. Our network analysis reveals a fast recovery of the infected cohort after the second IAV infection and provides insights into crucial roles of Desulfovibrionaceae and Lactobacillaceae families in combating Influenza A Virus infection. Source code of the community detection algorithm can be downloaded from https://github.com/AniBhar84/MCCD-WN.

Is it possible to ensure COVID19 vaccine supply by using plants?

Any disease that spreads quickly and crossed the geographical barrier is termed as pandemic. After the initial occurrence of Covid-19 from China, World Health Organization had declared novel corona viral outbreak as pandemic on March, 2020. Since then, COVID-19 continued to devastate people all around the world. Human civilization has witnessed one of its greatest crises by facing 180 million of confirmed cases with 38.9 lakh deaths across the world till end of June 2021. India alone contributes 30 million of positive cases and has lost 3.92 lakh valuable lives (data as on 24th of June 2021 from CSSEGIS and Data (http://github.com/CSSEGISandData/COVID-19); (the number increases in each day). Bio-medical experts from all around the world are working tirelessly to limit the disease and find potential cures for this viral infection. Vaccination is the most effective strategy to prevent the spread of any viral disease. Virologists have developed some effective vaccines, but production or supply lags far behind the present demand across the globe. Plant-derived vaccines (PDVs) based on modified virus like particles (VLPs) can be a feasible alternative in this case. A summarized account about the efficacy of the first plant-derived Covid 19 vaccine, CoVLP is discussed. PDVs and VLPs are also reviewed briefly, along with their benefits and drawbacks.

Plant Responses to Biotic Stress: Old Memories Matter.

Plants are fascinating organisms present in most ecosystems and a model system for studying different facets of ecological interactions on Earth. In the environment, plants constantly encounter a multitude of abiotic and biotic stresses. The zero-avoidance phenomena make them more resilient to such environmental odds. Plants combat biotic stress or pathogenic ingression through a complex orchestration of intracellular signalling cascades. The plant-microbe interaction primarily relies on acquired immune response due to the absence of any specialised immunogenic cells for adaptive immune response. The generation of immune memory is mainly carried out by T cells as part of the humoral immune response in animals. Recently, prodigious advancements in our understanding of epigenetic regulations in plants invoke the "plant memory" theory afresh. Current innovations in cutting-edge genomic tools have revealed stress-associated genomic alterations and strengthened the idea of transgenerational memory in plants. In plants, stress signalling events are transferred as genomic imprints in successive generations, even without any stress. Such immunogenic priming of plants against biotic stresses is crucial for their eco-evolutionary success. However, there is limited literature capturing the current knowledge of the transgenerational memory of plants boosting biotic stress responses. In this context, the present review focuses on the general concept of memory in plants, recent advancements in this field and comprehensive implications in biotic stress tolerance with future perspectives.

Transcriptomic dissection reveals wide spread differential expression in chickpea during early time points of Fusarium oxysporum f. sp. ciceri Race 1 attack.

Plants' reaction to underground microorganisms is complex as sessile nature of plants compels them to prioritize their responses to diverse microorganisms both pathogenic and symbiotic. Roots of important crops are directly exposed to diverse microorganisms, but investigations involving root pathogens are significantly less. Thus, more studies involving root pathogens and their target crops are necessitated to enrich the understanding of underground interactions. Present study reported the molecular complexities in chickpea during Fusarium oxysporum f. sp. ciceri Race 1 (Foc1) infection. Transcriptomic dissections using RNA-seq showed significantly differential expression of molecular transcripts between infected and control plants of both susceptible and resistant genotypes. Radar plot analyses showed maximum expressional undulations after infection in both susceptible and resistant plants. Gene ontology and functional clustering showed large number of transcripts controlling basic metabolism of plants. Network analyses demonstrated defense components like peptidyl cis/trans isomerase, MAP kinase, beta 1,3 glucanase, serine threonine kinase, patatin like protein, lactolylglutathione lyase, coproporphyrinogen III oxidase, sulfotransferases; reactive oxygen species regulating components like respiratory burst oxidase, superoxide dismutases, cytochrome b5 reductase, glutathione reductase, thioredoxin reductase, ATPase; metabolism regulating components, myo inositol phosphate, carboxylate synthase; transport related gamma tonoplast intrinsic protein, and structural component, ubiquitins to serve as important nodals of defense signaling network. These nodal molecules probably served as hub controllers of defense signaling. Functional characterization of these hub molecules would not only help in developing better understanding of chickpea-Foc1 interaction but also place them as promising candidates for resistance management programs against vascular wilt of legumes.

Multiobjective triclustering of time-series transcriptome data reveals key genes of biological processes.

BACKGROUND: Exploratory analysis of multi-dimensional high-throughput datasets, such as microarray gene expression time series, may be instrumental in understanding the genetic programs underlying numerous biological processes. In such datasets, variations in the gene expression profiles are usually observed across replicates and time points. Thus mining the temporal expression patterns in such multi-dimensional datasets may not only provide insights into the key biological processes governing organs to grow and develop but also facilitate the understanding of the underlying complex gene regulatory circuits. RESULTS: In this work we have developed an evolutionary multi-objective optimization for our previously introduced triclustering algorithm δ-TRIMAX. Its aim is to make optimal use of δ-TRIMAX in extracting groups of co-expressed genes from time series gene expression data, or from any 3D gene expression dataset, by adding the powerful capabilities of an evolutionary algorithm to retrieve overlapping triclusters. We have compared the performance of our newly developed algorithm, EMOA- δ-TRIMAX, with that of other existing triclustering approaches using four artificial dataset and three real-life datasets. Moreover, we have analyzed the results of our algorithm on one of these real-life datasets monitoring the differentiation of human induced pluripotent stem cells (hiPSC) into mature cardiomyocytes. For each group of co-expressed genes belonging to one tricluster, we identified key genes by computing their membership values within the tricluster. It turned out that to a very high percentage, these key genes were significantly enriched in Gene Ontology categories or KEGG pathways that fitted very well to the biological context of cardiomyocytes differentiation. CONCLUSIONS: EMOA- δ-TRIMAX has proven instrumental in identifying groups of genes in transcriptomic data sets that represent the functional categories constituting the biological process under study. The executable file can be found at http://www.bioinf.med.uni-goettingen.de/fileadmin/download/EMOA-delta-TRIMAX.tar.gz .

"Upstream Analysis": An Integrated Promoter-Pathway Analysis Approach to Causal Interpretation of Microarray Data.

A strategy is presented that allows a causal analysis of co-expressed genes, which may be subject to common regulatory influences. A state-of-the-art promoter analysis for potential transcription factor (TF) binding sites in combination with a knowledge-based analysis of the upstream pathway that control the activity of these TFs is shown to lead to hypothetical master regulators. This strategy was implemented as a workflow in a comprehensive bioinformatic software platform. We applied this workflow to gene sets that were identified by a novel triclustering algorithm in naphthalene-induced gene expression signatures of murine liver and lung tissue. As a result, tissue-specific master regulators were identified that are known to be linked with tumorigenic and apoptotic processes. To our knowledge, this is the first time that genes of expression triclusters were used to identify upstream regulators.

Analysis of root proteome unravels differential molecular responses during compatible and incompatible interaction between chickpea (Cicer arietinum L.) and Fusarium oxysporum f. sp. ciceri Race1 (Foc1).

BACKGROUND: Vascular wilt caused by Fusarium oxysporum f. sp. ciceri Race 1 (Foc1) is a serious disease of chickpea (Cicer arietinum L.) accounting for approximately 10-15% annual crop loss. The fungus invades the plant via roots, colonizes the xylem vessels and prevents the upward translocation of water and nutrients, finally resulting in wilting of the entire plant. Although comparative transcriptomic profiling have highlighted some important signaling molecules, but proteomic studies involving chickpea-Foc1 are limited. The present study focuses on comparative root proteomics of susceptible (JG62) and resistant (WR315) chickpea genotypes infected with Foc1, to understand the mechanistic basis of susceptibility and/or resistance. RESULTS: The differential and unique proteins of both genotypes were identified at 48 h, 72 h, and 96 h post Foc1 inoculation. 2D PAGE analyses followed by MALDI-TOF MS and MS/MS identified 100 differentially (>1.5 fold<, p<0.05) or uniquely expressed proteins. These proteins were further categorized into 10 functional classes and grouped into GO (gene ontology) categories. Network analyses of identified proteins revealed intra and inter relationship of these proteins with their neighbors as well as their association with different defense signaling pathways. qRT-PCR analyses were performed to correlate the mRNA and protein levels of some proteins of representative classes. CONCLUSIONS: The differential and unique proteins identified indicate their involvement in early defense signaling of the host. Comparative analyses of expression profiles of obtained proteins suggest that albeit some common components participate in early defense signaling in both susceptible and resistant genotypes, but their roles and regulation differ in case of compatible and/or incompatible interactions. Thus, functional characterization of identified PR proteins (PR1, BGL2, TLP), Trypsin protease inhibitor, ABA responsive protein, cysteine protease, protein disulphide isomerase, ripening related protein and albumins are expected to serve as important molecular components for biotechnological application and development of sustainable resistance against Foc1.

Fusarium oxysporum f.sp. ciceri race 1 induced redox state alterations are coupled to downstream defense signaling in root tissues of chickpea (Cicer arietinum L.).

Reactive oxygen species are known to play pivotal roles in pathogen perception, recognition and downstream defense signaling. But, how these redox alarms coordinate in planta into a defensive network is still intangible. Present study illustrates the role of Fusarium oxysporum f.sp ciceri Race1 (Foc1) induced redox responsive transcripts in regulating downstream defense signaling in chickpea. Confocal microscopic studies highlighted pathogen invasion and colonization accompanied by tissue damage and deposition of callose degraded products at the xylem vessels of infected roots of chickpea plants. Such depositions led to the clogging of xylem vessels in compatible hosts while the resistant plants were devoid of such obstructions. Lipid peroxidation assays also indicated fungal induced membrane injury. Cell shrinkage and gradual nuclear adpression appeared as interesting features marking fungal ingress. Quantitative real time polymerase chain reaction exhibited differential expression patterns of redox regulators, cellular transporters and transcription factors during Foc1 progression. Network analysis showed redox regulators, cellular transporters and transcription factors to coordinate into a well orchestrated defensive network with sugars acting as internal signal modulators. Respiratory burst oxidase homologue, cationic peroxidase, vacuolar sorting receptor, polyol transporter, sucrose synthase, and zinc finger domain containing transcription factor appeared as key molecular candidates controlling important hubs of the defense network. Functional characterization of these hub controllers may prove to be promising in understanding chickpea-Foc1 interaction and developing the case study as a model for looking into the complexities of wilt diseases of other important crop legumes.

Coexpression and coregulation analysis of time-series gene expression data in estrogen-induced breast cancer cell.

BACKGROUND: Estrogen is a chemical messenger that has an influence on many breast cancers as it helps cells to grow and divide. These cancers are often known as estrogen responsive cancers in which estrogen receptor occupies the surface of the cells. The successful treatment of breast cancers requires understanding gene expression, identifying of tumor markers, acquiring knowledge of cellular pathways, etc. In this paper we introduce our proposed triclustering algorithm δ-TRIMAX that aims to find genes that are coexpressed over subset of samples across a subset of time points. Here we introduce a novel mean-squared residue for such 3D dataset. Our proposed algorithm yields triclusters that have a mean-squared residue score below a threshold δ. RESULTS: We have applied our algorithm on one simulated dataset and one real-life dataset. The real-life dataset is a time-series dataset in estrogen induced breast cancer cell line. To establish the biological significance of genes belonging to resultant triclusters we have performed gene ontology, KEGG pathway and transcription factor binding site enrichment analysis. Additionally, we represent each resultant tricluster by computing its eigengene and verify whether its eigengene is also differentially expressed at early, middle and late estrogen responsive stages. We also identified hub-genes for each resultant triclusters and verified whether the hub-genes are found to be associated with breast cancer. Through our analysis CCL2, CD47, NFIB, BRD4, HPGD, CSNK1E, NPC1L1, PTEN, PTPN2 and ADAM9 are identified as hub-genes which are already known to be associated with breast cancer. The other genes that have also been identified as hub-genes might be associated with breast cancer or estrogen responsive elements. The TFBS enrichment analysis also reveals that transcription factor POU2F1 binds to the promoter region of ESR1 that encodes estrogen receptor α. Transcription factor E2F1 binds to the promoter regions of coexpressed genes MCM7, ANAPC1 and WEE1. CONCLUSIONS: Thus our integrative approach provides insights into breast cancer prognosis.

Understanding the molecular defence responses of host during chickpea-Fusarium interplay: where do we stand?

Fusarium oxysporum is known to cause vascular wilt and root rot of many important plants. Although extensive studies have been reported for the model plant Arabidopsis thaliana (L.) Heynh., the question of whether those experimental interpretations are extendable to other crop species requires experimentation. Chickpea is the most important crop legume of Indian subcontinent and ranks third in the world list of important legumes. However, productivity of this crop is severely curtailed by vascular wilt caused by Fusarium oxysporum f. sp. ciceri. Based on earlier reports, the present review discusses about the external manifestations of the disease, in planta fungal progression and establishment, and the molecular responses of chickpea that occur during Fusarium oxysporum f. sp. ciceri Race 1(Foc1) interaction. Foc1, known to enter the roots through the breaches of tap root, colonise the xylem vessels and block upward translocation of essential solutes causing wilt in compatible hosts. In contrast, pathogen invasion is readily perceived by the resistant host, which activates defence signalling cascades that are directed towards protecting its primary metabolism from the harmful consequences of pathogenic mayhem. Hence, understanding the dynamic complexities of chickpea-Foc1 interplay is prerequisite to providing sustainable solutions in wilt management programs.

Optimization of an Efficient Protein Extraction Protocol Compatible with Two-Dimensional Electrophoresis and Mass Spectrometry from Recalcitrant Phenolic Rich Roots of Chickpea (Cicer arietinum L.).

Two-dimensional electrophoresis and mass spectrometry are undoubtedly two essential tools popularly used in proteomic analyses. Utilization of these techniques however largely depends on efficient and optimized sample preparation, regarded as one of the most crucial steps for recovering maximum amount of reliable information. The present study highlights the optimization of an effective and efficient protocol, capable of extraction of root proteins from recalcitrant phenolic rich tissues of chickpea. The widely applicable TCA-acetone and phenol-based methods have been comparatively evaluated, amongst which the latter appeared to be better suited for the sample. The phenol extraction-based method further complemented with sodium dodecyl sulphate (SDS) and pulsatory treatments proved to be the most suitable method represented by greatest spot number, good resolution, and spot intensities. All the randomly selected spots showed successful identification when subjected to further downstream MALDI-TOF and MS/MS analyses. Hence, the information obtained collectively proposes the present protein extraction protocol to be an effective one that could be applicable for recalcitrant leguminous root samples.