Tissue-specific transcriptional biomarkers in medicinal plants: Application of large-scale meta-analysis and computational systems biology

© 2019 Elsevier BV. This manuscript version is made available under the CC-BY-NC-ND 4.0 license: http://creativecommons.org/licenses/by-nc-nd/4.0/ This author accepted manuscript is made available following 12 month embargo from date of publication (January 2019) in accordance with the publisher’s archiving policyBiosynthesis of secondary metabolites in plant is a complex process, regulated by many genes and influenced by several factors. In recent years, the next-generation sequencing (NGS) technology and advanced statistical analysis such as meta-analysis and computational systems biology have provided novel opportunities to overcome biological complexity. Here, we performed a meta-analysis on publicly available transcriptome datasets of twelve economically significant medicinal plants to identify differentially expressed genes (DEGs) between shoot and root tissues and to find the key molecular features which may be effective in the biosynthesis of secondary metabolites. Meta-analysis identified a total of 880 genes with differential expression between two tissues. Functional enrichment and KEGG pathway analysis indicated that the functions of those DEGs are highly associated with the developmental process, starch metabolic process, response to stimulus, porphyrin and chlorophyll metabolism, biosynthesis of secondary metabolites and phenylalanine metabolism. In addition, systems biology analysis of the DEGs was applied to find protein–protein interaction network and discovery of significant modules. The detected modules were associated with hormone signal transduction, transcription repressor activity, response to light stimulus and epigenetic processes. Finally, analysis was extended to search for putative miRNAs that are associated with DEGs. A total of 31 miRNAs were detected which belonged to 16 conserved families. The present study provides a comprehensive view to better understand the tissue-specific expression of genes and mechanisms involved in secondary metabolites synthesis and may provide candidate genes for future researches to improve yield of secondary metabolites

Crosstalk between short- and long-term calorie restriction transcriptomic signatures with anxiety-like behavior, aging, and neurodegeneration: implications for drug repurposing

Calorie restriction (CR) is considered an effective intervention for anxiety, aging, and obesity. We investigated the effects of short- and long-term CR on behavior as well as transcriptome profiles in the hypothalamus, amygdala, prefrontal cortex, pituitary, and adrenal glands of Hooded Wistar and Long Evans male rats. A reduction in anxiety-like behavior, as assessed via the elevated plus maze, was observed in both short- and long-term CR. Despite this, short- and long-term CR regulated different sets of genes, leading to distinct transcriptomic signatures. The employed models were able to simultaneously analyze categorical and numerical variables, evaluating the effect of tissue type along with expression data. In all tissues, transcription factors, zinc finger protein 45-like and zinc finger BTB domain-containing two, were the top selected genes by the models in short and long-term CR treatments, respectively. Text mining identified associations between genes of the short-term CR signature and neurodegeneration, stress, and obesity and between genes of the long-term signature and the nervous system. Literature mining-based drug repurposing showed that alongside known CR mimetics such as resveratrol and rapamycin, candidates not typically associated with CR mimetics may be repurposed based on their interaction with transcriptomic signatures of CR. This study goes some way to unravelling the global effects of CR and opens new avenues for treatment for emotional disorders, neurodegeneration, and obesity

Unified Transcriptomic Signature of Arbuscular Mycorrhiza Colonization in Roots of Medicago truncatula by Integration of Machine Learning, Promoter Analysis, and Direct Merging Meta-Analysis

Plant root symbiosis with Arbuscular mycorrhizal (AM) fungi improves uptake of water and mineral nutrients, improving plant development under stressful conditions. Unraveling the unified transcriptomic signature of a successful colonization provides a better understanding of symbiosis. We developed a framework for finding the transcriptomic signature of Arbuscular mycorrhiza colonization and its regulating transcription factors in roots of Medicago truncatula. Expression profiles of roots in response to AM species were collected from four separate studies and were combined by direct merging meta-analysis. Batch effect, the major concern in expression meta-analysis, was reduced by three normalization steps: Robust Multi-array Average algorithm, Z-standardization, and quartiling normalization. Then, expression profile of 33685 genes in 18 root samples of Medicago as numerical features, as well as study ID and Arbuscular mycorrhiza type as categorical features, were mined by seven models: RELIEF, UNCERTAINTY, GINI INDEX, Chi Squared, RULE, INFO GAIN, and INFO GAIN RATIO. In total, 73 genes selected by machine learning models were up-regulated in response to AM (Z-value difference > 0.5). Feature weighting models also documented that this signature is independent from study (batch) effect. The AM inoculation signature obtained was able to differentiate efficiently between AM inoculated and non-inoculated samples. The AP2 domain class transcription factor, GRAS family transcription factors, and cyclin-dependent kinase were among the highly expressed meta-genes identified in the signature. We found high correspondence between the AM colonization signature obtained in this study and independent RNA-seq experiments on AM colonization, validating the repeatability of the colonization signature. Promoter analysis of upregulated genes in the transcriptomic signature led to the key regulators of AM colonization, including the essential transcription factors for endosymbiosis establishment and development such as NF-YA factors. The approach developed in this study offers three distinct novel features: (I) it improves direct merging meta-analysis by integrating supervised machine learning models and normalization steps to reduce study-specific batch effects; (II) seven attribute weighting models assessed the suitability of each gene for the transcriptomic signature which contributes to robustness of the signature (III) the approach is justifiable, easy to apply, and useful in practice. Our integrative framework of meta-analysis, promoter analysis, and machine learning provides a foundation to reveal the transcriptomic signature and regulatory circuits governing Arbuscular mycorrhizal symbiosis and is transferable to the other biological settings

Regulatory control of the symbiotic enhanced soybean bHLH transcription factor, GmSAT1.

GmSAT1 is a basic Helix-Loop-Helix (bHLH) DNA binding transcription factor expressed in soybean root nodules. GmSAT1 is a unique protein, in that it is localised on cellular membranes including the symbiosome membrane, which encircles nitrogen-fixing bacteroids in soybean nodules. Its role in the regulation of gene transcription in nodules or in other plant tissues is poorly understood. In this study, GmSAT1’s functional activity was investigated through a series of studies that investigated the link between gene activities to functional phenotypes. This analysis included the influence of symbiotic partnerships with rhizobia and AM fungi and non-symbiotic root tissues. In this context, an evaluation of changes in gene transcription with or without GmSAT1 expression (RNAi-based silencing of GmSAT1) was explored at the individual and global gene levels. The data indicates that GmSAT1;1 and a close relative GmSAT1;2, are both expressed in roots and nodules but GmSAT1;1 displayed an overall enhancement in the symbiotic root nodule. Expression of both genes was reduced with external nitrogen supply to the nodule and inoculated root. Both genes were up-regulated in root and nodule tissues when plants were supplied low levels of phosphate. Using an improved method for transgenic hairy roots, developed as part of this thesis project, GmSAT1 was silenced using a RNAi construct. Tissues (roots and nodules) were analysed for changes in global gene expression using microarray analysis, the impact on symbiotic relationships (rhizobia and AM fungi) and genetic and biochemical responses to phosphorus supply. Transcriptome analysis identified networks that GmSAT1;1 may be associated with, including a suite of putatively active circadian clock regulators operating in nodules, phosphorus responsive genes in roots, cell wall maintenance and or stress defence signaling pathways, nitrogen transport and metabolism and genes linked to auxin and gibberellin regulatory pathways. The influence of phosphorus and the AM fungal symbiosis was investigated in more detail. Loss of GmSAT1 activity altered AM colonisation, causing a reduction in root colonisation when grown at reduced external P. At higher P levels, colonisation remained unchanged. Shoot P content was significantly increased at both low and high external P supply in the GmSAT1 silenced plants, indicating a potential role of GmSAT1 in mediating P homeostasis. The impact of gibberellins (GA₃) on GmSAT1 expression and activity was also investigated. Using both qPCR and native promoter:GUS fusion constructs in transformed soybean hairy roots and nodules the expression of GmSAT1;1 in roots and nodules decreased with external supply of GA₃. In parallel experiments, RNAi SAT1-silenced plants showed similar responses with GA₃ treated plants, where nodule number and weight decreased while plant height significantly increased. Furthermore, microarray analysis indicated GmSAT1 negatively interacts with known gibberellin-responsive genes, including GASA6, GAMA-TIP, CLE2, MTO3, GIP1, TPS11, and GBF1. The overall findings of this study have shown that GmSAT1 is an important TF to soybean with a broad transcriptional imprint which influences both root nodule symbiosis and AM fungal symbioses. Its activity appears to be linked to multiple genetic signaling networks that involve phosphorus and nitrogen metabolism, hormone activity and regulation of the circadian clock.Thesis (Ph.D.) -- University of Adelaide, School of Agriculture, Food and Wine, 201

Evaluation of the Effectiveness of Herbal Components Based on Their Regulatory Signature on Carcinogenic Cancer Cells

Predicting cancer cells’ response to a plant-derived agent is critical for the drug discovery process. Recently transcriptomes advancements have provided an opportunity to identify regulatory signatures to predict drug activity. Here in this study, a combination of meta-analysis and machine learning models have been used to determine regulatory signatures focusing on differentially expressed transcription factors (TFs) of herbal components on cancer cells. In order to increase the size of the dataset, six datasets were combined in a meta-analysis from studies that had evaluated the gene expression in cancer cell lines before and after herbal extract treatments. Then, categorical feature analysis based on the machine learning methods was applied to examine transcription factors in order to find the best signature/pattern capable of discriminating between control and treated groups. It was found that this integrative approach could recognize the combination of TFs as predictive biomarkers. It was observed that the random forest (RF) model produced the best combination rules, including AIP/TFE3/VGLL4/ID1 and AIP/ZNF7/DXO with the highest modulating capacity. As the RF algorithm combines the output of many trees to set up an ultimate model, its predictive rules are more accurate and reproducible than other trees. The discovered regulatory signature suggests an effective procedure to figure out the efficacy of investigational herbal compounds on particular cells in the drug discovery process

Genome-wide analysis of cytosolic and chloroplastic isoforms of glutathione reductase in plant cells

Abstract In recent years regarding the climate change and subsequent environmental stresses, there has been an increasing interest in finding and characterizing of new antioxidant enzymes. Glutathione reductase (GR) is an antioxidant enzyme with central role in maintaining the reduced glutathione pool during stress. So far, however, there has been little discussion on genome-wide analysis of this enzyme. In this study, different computational biology approaches (EST analysis, feature selection, and evolutionary analysis) were exploited to identify the key protein properties influencing on cytosolic and chloroplastic isoforms of glutathione reductase in plants. A specific targeting signal peptide was found in chloroplastic isoforms, while cytosolic isoforms carry a cytosolic domain. This domain may affect the biochemical properties of different GR isoforms. Moreover, specific its functionl motifs were discovered in cytosolic and chloroplastic isoforms implying a link between subcellular localization of GR and functional. Phylogenetic analysis of GR nucleotide and protein sequences showed that diversification of this gene family could be dated back to the early stage of plant evolution, possibly by duplication event before the divergence of monocot and dicot. A high degree of gene structure conservation of localized isoforms in the same subcellular compartment also reflects this process providing an evidence for a close relationship among proteins located in the same subcellular compartment. Study of glutathione reductase expression by EST analysis highlighted cytosolic isoforms as the main isoforrm responding to stress condition

Gut Microbiota and Behavioural Issues in Production, Performance, and Companion Animals: A Systematic Review

The literature has identified poor nutrition as the leading factor in the manifestation of many behavioural issues in animals, including aggression, hyperalertness, and stereotypies. Literature focused on all species of interest consistently reported that although there were no significant differences in the richness of specific bacterial taxa in the microbiota of individual subjects with abnormal behaviour (termed alpha diversity), there was variability in species diversity between these subjects compared to controls (termed beta diversity). As seen in humans with mental disorders, animals exhibiting abnormal behaviour often have an enrichment of pro-inflammatory and lactic acid-producing bacteria and a reduction in butyrate-producing bacteria. It is evident from the literature that an association exists between gut microbiota diversity (and by extension, the concurrent production of microbial metabolites) and abnormal behavioural phenotypes across various species, including pigs, dogs, and horses. Similar microbiota population changes are also evident in human mental health patients. However, there are insufficient data to identify this association as a cause or effect. This review provides testable hypotheses for future research to establish causal relationships between gut microbiota and behavioural issues in animals, offering promising potential for the development of novel therapeutic and/or preventative interventions aimed at restoring a healthy gut-brain-immune axis to mitigate behavioural issues and, in turn, improve health, performance, and production in animals

A Transcription Regulatory Sequence in the 5′ Untranslated Region of SARS-CoV-2 Is Vital for Virus Replication with an Altered Evolutionary Pattern against Human Inhibitory MicroRNAs

Our knowledge of the evolution and the role of untranslated region (UTR) in SARS-CoV-2 pathogenicity is very limited. Leader sequence, originated from UTR, is found at the 5′ ends of all encoded SARS-CoV-2 transcripts, highlighting its importance. Here, evolution of leader sequence was compared between human pathogenic and non-pathogenic coronaviruses. Then, profiling of microRNAs that can inactivate the key UTR regions of coronaviruses was carried out. A distinguished pattern of evolution in leader sequence of SARS-CoV-2 was found. Mining all available microRNA families against leader sequences of coronaviruses resulted in discovery of 39 microRNAs with a stable thermodynamic binding energy. Notably, SARS-CoV-2 had a lower binding stability against microRNAs. hsa-MIR-5004-3p was the only human microRNA able to target the leader sequence of SARS and to a lesser extent, also SARS-CoV-2. However, its binding stability decreased remarkably in SARS-COV-2. We found some plant microRNAs with low and stable binding energy against SARS-COV-2. Meta-analysis documented a significant (p < 0.01) decline in the expression of MIR-5004-3p after SARS-COV-2 infection in trachea, lung biopsy, and bronchial organoids as well as lung-derived Calu-3 and A549 cells. The paucity of the innate human inhibitory microRNAs to bind to leader sequence of SARS-CoV-2 can contribute to its high replication in infected human cells