Structure of higher-order interactions in social-ecological networks through Q-analysis of their neighbourhood and clique complex.

This paper studies higher-order interactions in social-ecological networks, which formally represent interactions within the social and ecological units of an ecosystem. Many real-world social ecosystems exhibit not only pairwise interactions but also higher-order interactions among their units. Therefore, the conventional graph-theoretic description of networks falls short of capturing these higher-order interactions due to the inherent limitations of the graph definition. In this work, a mathematical framework for capturing the higher-order interactions of a social-ecological system has been given by incorporating notions from combinatorial algebraic topology. In order to achieve this, two different simplicial complexes, the clique and the neighbourhood complex, have been constructed from a pairwise social-ecological network. As a case study, the Q-analysis and a structural study of the interactions in the rural agricultural system of southern Madagascar have been done at various structural levels denoted by q. The results obtained by calculating all the structural vectors for both simplicial complexes, along with exciting results about the participation of facets of the clique complex at different q-levels, have been discussed. This work also establishes significant theorems concerning the dimension of the neighbourhood complex and clique complex obtained from the parent pairwise network.

Abiotic Stress-Responsive miRNA and Transcription Factor-Mediated Gene Regulatory Network in Oryza sativa: Construction and Structural Measure Study.

Climate changes and environmental stresses have a consequential association with crop plant growth and yield, meaning it is necessary to cultivate crops that have tolerance toward the changing climate and environmental disturbances such as water stress, temperature fluctuation, and salt toxicity. Recent studies have shown that trans-acting regulatory elements, including microRNAs (miRNAs) and transcription factors (TFs), are emerging as promising tools for engineering naive improved crop varieties with tolerance for multiple environmental stresses and enhanced quality as well as yield. However, the interwoven complex regulatory function of TFs and miRNAs at transcriptional and post-transcriptional levels is unexplored in Oryza sativa. To this end, we have constructed a multiple abiotic stress responsive TF-miRNA-gene regulatory network for O. sativa using a transcriptome and degradome sequencing data meta-analysis approach. The theoretical network approach has shown the networks to be dense, scale-free, and small-world, which makes the network stable. They are also invariant to scale change where an efficient, quick transmission of biological signals occurs within the network on extrinsic hindrance. The analysis also deciphered the existence of communities (cluster of TF, miRNA, and genes) working together to help plants in acclimatizing to multiple stresses. It highlighted that genes, TFs, and miRNAs shared by multiple stress conditions that work as hubs or bottlenecks for signal propagation, for example, during the interaction between stress-responsive genes (TFs/miRNAs/other genes) and genes involved in floral development pathways under multiple environmental stresses. This study further highlights how the fine-tuning feedback mechanism works for balancing stress tolerance and how timely flowering enable crops to survive in adverse conditions. This study developed the abiotic stress-responsive regulatory network, APRegNet database (http://lms.snu.edu.in/APRegNet), which may help researchers studying the roles of miRNAs and TFs. Furthermore, it advances current understanding of multiple abiotic stress tolerance mechanisms.

Abiotic stress induced miRNA-TF-gene regulatory network: A structural perspective.

MicroRNAs (miRNAs) and transcription factors (TFs) are the largest families of trans-acting gene regulatory species, which are pivotal players in a complex regulatory network. Recently, extensive research on miRNAs and TFs in agriculture has identified these trans-acting regulatory species, as an effective tool for engineering new crop cultivars to increase yield and quality as well tolerance to environmental stresses but our knowledge of regulatory network is still not sufficient to decipher the exact mechanism. In the current work, stress-specific TF-miRNA-gene network was built for Arabidopsis under drought, cold, salt and waterlogging stress using data from reliable publically available databases; and transcriptome and degradome sequence data analysis by meta-analysis approach. Further network analysis elucidated significantly dense, scale-free, small world and hierarchical backbone of interactions. The various centrality measures highlighted several genes/TF/miRNAs as potential targets for tolerant variety cultivation. This comprehensive regulatory information will accelerate the advancement of current understanding on stress specific transcriptional and post-transcriptional regulatory mechanism and has promising utilizations for experimental biologist who are intended to improve plant crop performance under multiple Abiotic stress environments.

Comparative transcriptome meta-analysis of Arabidopsis thaliana under drought and cold stress.

Multiple environmental stresses adversely affect plant growth and development. Plants under multiple stress condition trigger cascade of signals and show response unique to specific stress as well as shared responses, common to individual stresses. Here, we aim to identify common and unique genetic components during stress response mechanisms liable for cross-talk between stresses. Although drought and cold stress have been widely studied, insignificant information is available about how their combination affects plants. To that end, we performed meta-analysis and co-expression network comparison of drought and cold stress response in Arabidopsis thaliana by analyzing 390 microarray samples belonging to 29 microarray studies. We observed 6120 and 7079 DEGs (differentially expressed genes) under drought and cold stress respectively, using Rank Product methodology. Statistically, 28% (2890) DEGs were found to be common in both the stresses (i.e.; drought and cold stress) with most of them having similar expression pattern. Further, gene ontology-based enrichment analysis have identified shared biological processes and molecular mechanisms such as-'photosynthesis', 'respiratory burst', 'response to hormone', 'signal transduction', 'metabolic process', 'response to water deprivation', which were affected under cold and drought stress. Forty three transcription factor families were found to be expressed under both the stress conditions. Primarily, WRKY, NAC, MYB, AP2/ERF and bZIP transcription factor family genes were highly enriched in all genes sets and were found to regulate 56% of common genes expressed in drought and cold stress. Gene co-expression network analysis by WGCNA (weighted gene co-expression network analysis) revealed 21 and 16 highly inter-correlated gene modules with specific expression profiles under drought and cold stress respectively. Detection and analysis of gene modules shared between two stresses revealed the presence of four consensus gene modules.

Innovative techniques to discover novel antimalarials.

Malaria a global pandemic has engulfed nearly 0.63 million people globally. It is high time that a cure for malaria is required to stop its ever increasing menace. Our commentary discusses the advent and contribution of genetic algorithm (GA) in the drug discovery efforts towards developing cure for malaria. GAs are computational models of Darwinian evolution, ideally capture and mimic the principles of genetic variation and natural selection to evolve good solutions through multiple iterations on the space of all possible candidate solutions, called the search space, to a given optimization problem. Herein we will discuss the applications, advantages, disadvantages and future directions of GA with respect to malaria.

Network measures for chemical library design.

In this overview, we examine recent developments in network approaches to drug design. A brief overview of networks is followed by a discussion of how chemical similarity networks and their properties address challenges in drug design. Multiple methods used to assess or enhance chemical diversity for early-stage drug discovery are discussed, as well as methods that can be used for drug repositioning and ligand polypharmacology.