Integrating transcriptome and metabolome reveals molecular networks involved in genetic and environmental variation in tobacco

Proteomic and metabolomic revealed the effect of shading treatment on cigar tobacco

Shading or low light conditions are essential cultivation techniques for cigar wrapper tobacco leaves production, yet their impact on protein and metabolic regulatory networks is not well understood. In this study, we integrated proteomic and metabolomic analyses to uncover the potential molecular mechanisms affecting cigar tobacco leaves under shading treatment. Our findings include: (1) Identification of 780 significantly differentially expressed proteins (DEPs) in the cigar wrapper tobacco leaves, comprising 560 up-regulated and 220 down-regulated proteins, predominantly located in the chloroplast, cytoplasm, and nucleus, collectively accounting for 50.01%. (2) Discovery of 254 significantly differentially expressed metabolites (DEMs), including 148 up-regulated and 106 down-regulated metabolites. (3) KEGG pathway enrichment analysis revealed that the mevalonate (MVA) pathway within 'Terpenoid backbone biosynthesis' was inhibited, leading to a down-regulation of 'Sesquiterpenoid and triterpenoid biosynthesis'. Conversely, the 2-C-methyl-D-erythritol 4-phosphate (MEP) pathway was enhanced, resulting in an up-regulation of 'Monoterpenoid biosynthesis', 'Diterpenoid biosynthesis', and 'Carotenoid biosynthesis', thereby promoting the synthesis of terpenoids such as carotenoids and chlorophylls. Simultaneously, the Calvin cycle in 'Carbon fixation in photosynthetic organisms' was amplified, increasing photosynthetic efficiency. These results suggest that under low light conditions, cigar tobacco optimizes photosynthetic efficiency by reconfiguring its energy metabolism and terpenoid biosynthesis. This study contributes valuable insights into protein and metabolic analyses, paving the way for future functional studies on plant responses to low light.

Multi-Omics Analysis of a Chromosome Segment Substitution Line Reveals a New Regulation Network for Soybean Seed Storage Profile

Soybean, a major source of oil and protein, has seen an annual increase in consumption when used in soybean-derived products and the broadening of its cultivation range. The demand for soybean necessitates a better understanding of the regulatory networks driving storage protein accumulation and oil biosynthesis to broaden its positive impact on human health. In this study, we selected a chromosome segment substitution line (CSSL) with high protein and low oil contents to investigate the underlying effect of donor introgression on seed storage through multi-omics analysis. In total, 1479 differentially expressed genes (DEGs), 82 differentially expressed proteins (DEPs), and 34 differentially expressed metabolites (DEMs) were identified in the CSSL compared to the recurrent parent. Based on Gene Ontology (GO) term analysis and the Kyoto Encyclopedia of Genes and Genomes enrichment (KEGG), integrated analysis indicated that 31 DEGs, 24 DEPs, and 13 DEMs were related to seed storage functionality. Integrated analysis further showed a significant decrease in the contents of the seed storage lipids LysoPG 16:0 and LysoPC 18:4 as well as an increase in the contents of organic acids such as L-malic acid. Taken together, these results offer new insights into the molecular mechanisms of seed storage and provide guidance for the molecular breeding of new favorable soybean varieties.

Transcriptomics of Lactobacillus paracasei: metabolism patterns and cellular responses under high-density culture conditions

Lactobacillus paracasei has significant potential for development and application in the environmental field, particularly in addressing malodor pollution. This study aims to investigate the cellular response of L. paracasei B1 under high-density culture conditions. The selected strain has previously shown effective deodorizing and bacteriostatic abilities. Transcriptomics techniques are employed to dissect the nutrient metabolism pattern of L. paracasei B1 and its response mechanism under environmental stress. The study characterizes the functions of key differentially expressed genes during growth before and after optimizing the culture conditions. The optimization of fermentation culture conditions provides a suitable growth environment for L. paracasei B1, inducing an enhancement of its phosphotransferase system for sugar source uptake and maintaining high levels of glycolysis and pyruvate metabolism. Consequently, the strain is able to grow and multiply rapidly. Under acid stress conditions, glycolysis and pyruvate metabolism are inhibited, and L. paracasei B1 generates additional energy through aerobic respiration to meet the energy demand. The two-component system and quorum sensing play roles in the response and regulation of L. paracasei B1 to adverse environments. The strain mitigates oxygen stress damage through glutathione metabolism, cysteine and methionine metabolism, base excision repair, and purine and pyrimidine metabolism. Additionally, the strain enhances lysine synthesis, the alanine, aspartate, and glutamate metabolic pathways, and relies on the ABC transport system to accumulate amino acid-compatible solutes to counteract acid stress and osmotic stress during pH regulation. These findings establish a theoretical basis for the further development and application of L. paracasei B1 for its productive properties.

Soil microbiota plays a key regulatory role in the outbreak of tobacco root rot

Introduction

Root rot caused by the fungal pathogen Fusarium sp. poses significant challenges to tobacco cultivation in China, leading to major economic setbacks. The interplay between this pathogen and the wider soil microbial community remains poorly understood.

Methods

High-throughput sequencing technology was utilized to evaluate soil prokaryotic, fungal, and protistan communities. We compared microbial communities in infected soils to those in healthy soils from the same field. Additionally, the influence of pH on the microbial communities was assessed.

Results

Infected soils displayed elevated levels of soil nutrients but diminished observed richness across prokaryotic, fungal, and protistan groups. The pathogenic fungi Fusarium solani f sp. eumartii's abundance was notably increased in infected soils. Infection with F. solani significantly altered the soil's microbial community structure and interactions, manifested as a decrease in network scale and the number of keystone species. An evaluation of prokaryotes' role in F. solani's invasion revealed an increased number of connecting nodes in infected soils. Additionally, relationships between predatory protists and fungi were augmented, whereas predation on F. solani declined.

Discussion

The study underscores the significance of comprehending the interactions among soil microorganisms and brings to light the susceptibility of soil microbial communities to pathogen invasion. It offers insights into the multifaceted relationships and potential vulnerabilities within the soil ecosystem in the context of Fusarium sp. invasion.

Clonostachys rosea 'omics profiling: identification of putative metabolite-gene associations mediating its in vitro antagonism against Fusarium graminearum

BACKGROUND

Clonostachys rosea is an established biocontrol agent. Selected strains have either mycoparasitic activity against known pathogens (e.g. Fusarium species) and/or plant growth promoting activity on various crops. Here we report outcomes from a comparative 'omics analysis leveraging a temporal variation in the in vitro antagonistic activities of C. rosea strains ACM941 and 88-710, toward understanding the molecular mechanisms underpinning mycoparasitism.

RESULTS

Transcriptomic data highlighted specialized metabolism and membrane transport related genes as being significantly upregulated in ACM941 compared to 88-710 at a time point when the ACM941 strain had higher in vitro antagonistic activity than 88-710. In addition, high molecular weight specialized metabolites were differentially secreted by ACM941, with accumulation patterns of some metabolites matching the growth inhibition differences displayed by the exometabolites of the two strains. In an attempt to identify statistically relevant relationships between upregulated genes and differentially secreted metabolites, transcript and metabolomic abundance data were associated using IntLIM (Integration through Linear Modeling). Of several testable candidate associations, a putative C. rosea epidithiodiketopiperazine (ETP) gene cluster was identified as a prime candidate based on both co-regulation analysis and transcriptomic-metabolomic data association.

CONCLUSIONS

Although remaining to be validated functionally, these results suggest that a data integration approach may be useful for identification of potential biomarkers underlying functional divergence in C. rosea strains.

Unravelling the molecular mechanism underlying drought stress response in chickpea via integrated multi-omics analysis

Drought stress affects growth and productivity significantly in chickpea. An integrated multi-omics analysis can provide a better molecular-level understanding of drought stress tolerance. In the present study, comparative transcriptome, proteome and metabolome analyses of two chickpea genotypes with contrasting responses to drought stress, ICC 4958 (drought-tolerant, DT) and ICC 1882 (drought-sensitive, DS), was performed to gain insights into the molecular mechanisms underlying drought stress response/tolerance. Pathway enrichment analysis of differentially abundant transcripts and proteins suggested the involvement of glycolysis/gluconeogenesis, galactose metabolism, and starch and sucrose metabolism in the DT genotype. An integrated multi-omics analysis of transcriptome, proteome and metabolome data revealed co-expressed genes, proteins and metabolites involved in phosphatidylinositol signaling, glutathione metabolism and glycolysis/gluconeogenesis pathways, specifically in the DT genotype under drought. These stress-responsive pathways were coordinately regulated by the differentially abundant transcripts, proteins and metabolites to circumvent the drought stress response/tolerance in the DT genotype. The QTL-hotspot associated genes, proteins and transcription factors may further contribute to improved drought tolerance in the DT genotype. Altogether, the multi-omics approach provided an in-depth understanding of stress-responsive pathways and candidate genes involved in drought tolerance in chickpea.

Grapevine scion gene expression is driven by rootstock and environment interaction

BACKGROUND

Grafting is a horticultural practice used widely across woody perennial crop species to fuse together the root and shoot system of two distinct genotypes, the rootstock and the scion, combining beneficial traits from both. In grapevine, grafting is used in nearly 80% of all commercial vines to optimize fruit quality, regulate vine vigor, and enhance biotic and abiotic stress-tolerance. Rootstocks have been shown to modulate elemental composition, metabolomic profiles, and the shape of leaves in the scion, among other traits. However, it is currently unclear how rootstock genotypes influence shoot system gene expression as previous work has reported complex and often contradictory findings.

RESULTS

In the present study, we examine the influence of grafting on scion gene expression in leaves and reproductive tissues of grapevines growing under field conditions for three years. We show that the influence from the rootstock genotype is highly tissue and time dependent, manifesting only in leaves, primarily during a single year of our three-year study. Further, the degree of rootstock influence on scion gene expression is driven by interactions with the local environment.

CONCLUSIONS

Our results demonstrate that the role of rootstock genotype in modulating scion gene expression is not a consistent, unchanging effect, but rather an effect that varies over time in relation to local environmental conditions.

Transcriptome and anatomical studies reveal alterations in leaf thickness under long-term drought stress in tobacco

Drought is one of the foremost environmental factors that limit the growth of plants. Leaf thickness (LT) is an important quantitative trait in plant physiology. The experiment was carried out in a growth room and the plants were divided into two groups such as well-watered and drought-stressed. This work investigated leaf growth in terms of leaf surface growth and expansion rate, leaf stomata traits, LT, anticlinal growth, and leaf cell layers. The results showed that the leaf area and leaf surface expansion rate were decreased by drought stress (DS). Similarly, LT, anticlinal expansion rate, palisade and spongy tissue thickness, and their related expansion rates were also decreased at different days' time points (DTP) of DS. However, a steady increase was observed in the aforementioned parameters after 12 DTP of DS. The stomatal density increased while stomata size decreased at 3 DTP and 12 DTP (low leaf water potential and relative leaf water content at these time points) and vice versa at 24 DTP compared with the well-watered plants indicating adaptations in these traits in response to DS, and thus the leaf water status played a role in the regulation of leaf stomata traits. The cell length decreased in the upper epidermis, palisade and spongy tissues by DS up to 12 DTP led to lower LT while an increase was observed after 12 DTP that resulted in higher LT. The increase in the LT was supported by the upregulation of starch and sucrose metabolism, glycerolipid metabolism, protein processing in endoplasmic reticulum pathways at 18 DTP along with the differentially expressed genes induced that were related to cell wall remodeling (cellulose, expansin, xyloglucans) and cell expansion (auxin response factors and aquaporin). The results explain the response of leaf thickness to drought stress and show alterations in LT and leaf stomatal traits. This study might serve as a valuable source of gene information for functional studies and provide a theoretical basis to understand leaf growth in terms of leaf anatomy and leaf stomatal traits under drought stress.

Integrated metabolite profiling and transcriptome analysis reveal candidate genes involved in the formation of yellow Nelumbo nucifera

As a worldwide major ornamental flower and a edible plant, lotus (Nelumbo nucifera) is also used as medicine and tea beverage. Here, transcriptome and metabolites of yellow (MLQS) and white (YGB) lotus cultivars during five key flower coloration stages were profiled. 2014 differentially expressed genes were detected with 11 carotenoids in lotus were identified for the first time. Then, regulatory networks between and within functional modules was reconstructed, and the correlation between module-metabolites and gene-metabolites was conducted within 3 core modules. 18 candidate genes related to the formation of yellow flower were screened out and a gene regulatory model for the flower color difference between MLQS and YGB were speculated as follows: The substrate competition between F3'H and F3'5'H and substrate specificity of FLS, together with differential expression of CCD4a and CCD4b were contribute to the differences in flavonoids and carotenoids. Besides, UGT73C2, UGT91C1-2 and SGTase, and regulation of UGTs by transcription factors PLATZ, MADS, NAC031, and MYB308 may also play a role in the upstream regulation. The following verification results indicated that functional differences existed in the coding sequences of NnCCD4b and promoters of NnCCD4a of MLQS and YGB. In all, this study preliminarily reveals the mechanism of yellow flower coloration in lotus and provides new ideas for the study of complex ornamental characters of other plants.

INTEGRATE: Model-based multi-omics data integration to characterize multi-level metabolic regulation

Metabolism is directly and indirectly fine-tuned by a complex web of interacting regulatory mechanisms that fall into two major classes. On the one hand, the expression level of the catalyzing enzyme sets the maximal theoretical flux level (i.e., the net rate of the reaction) for each enzyme-controlled reaction. On the other hand, metabolic regulation controls the metabolic flux through the interactions of metabolites (substrates, cofactors, allosteric modulators) with the responsible enzyme. High-throughput data, such as metabolomics and transcriptomics data, if analyzed separately, do not accurately characterize the hierarchical regulation of metabolism outlined above. They must be integrated to disassemble the interdependence between different regulatory layers controlling metabolism. To this aim, we propose INTEGRATE, a computational pipeline that integrates metabolomics and transcriptomics data, using constraint-based stoichiometric metabolic models as a scaffold. We compute differential reaction expression from transcriptomics data and use constraint-based modeling to predict if the differential expression of metabolic enzymes directly originates differences in metabolic fluxes. In parallel, we use metabolomics to predict how differences in substrate availability translate into differences in metabolic fluxes. We discriminate fluxes regulated at the metabolic and/or gene expression level by intersecting these two output datasets. We demonstrate the pipeline using a set of immortalized normal and cancer breast cell lines. In a clinical setting, knowing the regulatory level at which a given metabolic reaction is controlled will be valuable to inform targeted, truly personalized therapies in cancer patients.

Mechanism of Intermittent Deep Tillage and Different Depths Improving Crop Growth From the Perspective of Rhizosphere Soil Nutrients, Root System Architectures, Bacterial Communities, and Functional Profiles

Long-term conventional shallow tillage reduced soil quality and limited the agriculture development. Intermittent deep tillage could effectively promote agricultural production, through optimizing soil structure, underground ecology system, and soil fertility. However, the microecological mechanism of intermittent deep tillage promoting agriculture production has never been reported, and the effect of tillage depth on crop growth has not been explored in detail. In this study, three levels of intermittent deep tillage (30, 40, and 50 cm) treatments were conducted in an experimental field site with over 10 years of conventional shallow tillage (20 cm). Our results indicated that intermittent deep tillage practices helped to improve plant physiological growth status, chlorophyll a, and resistance to diseases, and the crop yield and value of output were increased with the deeper tillage practices. Crop yield (18.59%) and value of output (37.03%) were highest in IDT-50. There were three mechanisms of intermittent deep tillage practices that improved crop growth: (1) Intermittent deep tillage practices increased soil nutrients and root system architecture traits, which improved the fertility and nutrient uptake of crop through root system. (2) Changing rhizosphere environments, especially for root length, root tips, pH, and available potassium contributed to dissimilarity of bacterial communities and enriched plant growth-promoting species. (3) Functions associated with stress tolerance, including signal transduction and biosynthesis of other secondary metabolites were increased significantly in intermittent deep tillage treatments. Moreover, IDT-30 only increased soil characters and root system architecture traits compared with CK, but deeper tillage could also change rhizosphere bacterial communities and functional profiles. Plant height and stem girth in IDT-40 and IDT-50 were higher compared with IDT-30, and infection rates of black shank and black root rot in IDT-50 were even lower in IDT-40. The study provided a comprehensive explanation into the effects of intermittent deep tillage in plant production and suggested an optimal depth.

Systems biology for crop improvement

In recent years, generation of large-scale data from genome, transcriptome, proteome, metabolome, epigenome, and others, has become routine in several plant species. Most of these datasets in different crop species, however, were studied independently and as a result, full insight could not be gained on the molecular basis of complex traits and biological networks. A systems biology approach involving integration of multiple omics data, modeling, and prediction of the cellular functions is required to understand the flow of biological information that underlies complex traits. In this context, systems biology with multiomics data integration is crucial and allows a holistic understanding of the dynamic system with the different levels of biological organization interacting with external environment for a phenotypic expression. Here, we present recent progress made in the area of various omics studies-integrative and systems biology approaches with a special focus on application to crop improvement. We have also discussed the challenges and opportunities in multiomics data integration, modeling, and understanding of the biology of complex traits underpinning yield and stress tolerance in major cereals and legumes.

Combining targeted metabolite analyses and transcriptomics to reveal the specific chemical composition and associated genes in the incompatible soybean variety PI437654 infected with soybean cyst nematode HG1.2.3.5.7

BACKGROUND

Soybean cyst nematode, Heterodera glycines, is one of the most devastating pathogens of soybean and causes severe annual yield losses worldwide. Different soybean varieties exhibit different responses to H. glycines infection at various levels, such as the genomic, transcriptional, proteomic and metabolomic levels. However, there have not yet been any reports of the differential responses of incompatible and compatible soybean varieties infected with H. glycines based on combined metabolomic and transcriptomic analyses.

RESULTS

In this study, the incompatible soybean variety PI437654 and three compatible soybean varieties, Williams 82, Zhonghuang 13 and Hefeng 47, were used to clarify the differences in metabolites and transcriptomics before and after the infection with HG1.2.3.5.7. A local metabolite-calibrated database was used to identify potentially differential metabolites, and the differences in metabolites and metabolic pathways were compared between the incompatible and compatible soybean varieties after inoculation with HG1.2.3.5.7. In total, 37 differential metabolites and 20 KEGG metabolic pathways were identified, which were divided into three categories: metabolites/pathways overlapped in the incompatible and compatible soybeans, and metabolites/pathways specific to either the incompatible or compatible soybean varieties. Twelve differential metabolites were found to be involved in predicted KEGG metabolite pathways. Moreover, 14 specific differential metabolites (such as significantly up-regulated nicotine and down-regulated D-aspartic acid) and their associated KEGG pathways (such as the tropane, piperidine and pyridine alkaloid biosynthesis, alanine, aspartate and glutamate metabolism, sphingolipid metabolism and arginine biosynthesis) were significantly altered and abundantly enriched in the incompatible soybean variety PI437654, and likely played pivotal roles in defending against HG1.2.3.5.7 infection. Three key metabolites (N-acetyltranexamic acid, nicotine and D,L-tryptophan) found to be significantly up-regulated in the incompatible soybean variety PI437654 infected by HG1.2.3.5.7 were classified into two types and used for combined analyses with the transcriptomic expression profiling. Associated genes were predicted, along with the likely corresponding biological processes, cellular components, molecular functions and pathways.

CONCLUSIONS

Our results not only identified potential novel metabolites and associated genes involved in the incompatible response of PI437654 to soybean cyst nematode HG1.2.3.5.7, but also provided new insights into the interactions between soybeans and soybean cyst nematodes.

CE-MS for metabolomics: Developments and applications in the period 2018-2020

Capillary electrophoresis-mass spectrometry (CE-MS) is now a mature analytical technique in metabolomics, notably for the efficient profiling of polar and charged metabolites. Over the past few years, (further) progress has been made in the design of improved interfacing techniques for coupling CE to MS; also, in the development of CE-MS approaches for profiling metabolites in volume-restricted samples, and in strategies that further enhance the metabolic coverage. In this article, which is a follow-up of a previous review article covering the years 2016-2018 (Electrophoresis 2019, 40, 165-179), the main (technological) developments in CE-MS methods and strategies for metabolomics are discussed covering the literature from July 2018 to June 2020. Representative examples highlight the utility of CE-MS in the fields of biomedical, clinical, microbial, plant and food metabolomics. A complete overview of recent CE-MS-based metabolomics studies is given in a table, which provides information on sample type and pretreatment, capillary coatings, and MS detection mode. Finally, some general conclusions and perspectives are given.

Metabolic Profiling of Resistant and Susceptible Tobaccos Response Incited by Ralstonia pseudosolanacearum Causing Bacterial Wilt

The causal agent of bacterial wilt, Ralstonia pseudosolanacearum, can cause significant economic losses during tobacco production. Metabolic analyses are a useful tool for the comprehensive identification of plant defense response metabolites. In this study, a gas chromatography-mass spectrometry (GC-MS) approach was used to identify metabolites differences in tobacco xylem sap in response to R. pseudosolanacearum CQPS-1 in two tobacco cultivars: Yunyan87 (susceptible to R. pseudosolanacearum) and K326 (quantitatively resistant). Metabolite profiling 7 days post inoculation with R. pseudosolanacearum identified 88 known compounds, 42 of them enriched and 6 depleted in the susceptible cultivar Yunyan87, while almost no changes occurred in quantitatively resistant cultivar K326. Putrescine was the most enriched compound (12-fold) in infected susceptible tobacco xylem, followed by methyl-alpha-d-glucopyranoside (9-fold) and arabinitol (6-fold). Other sugars, amino acids, and organic acids were also enriched upon infection. Collectively, these metabolites can promote R. pseudosolanacearum growth, as shown by the increased growth of bacterial cultures supplemented with xylem sap from infected tobacco plants. Comparison with previous metabolic data showed that beta-alanine, phenylalanine, and leucine were enriched during bacterial wilt in both tobacco and tomato xylem.