Dataset Information

A molecular study of Italian ryegrass grown on Martian regolith simulant

ABSTRACT: The International Space Exploration Coordination Group has set a roadmap whose long-range strategy envisions the first human settlements on Mars by 2040. In this scenario, finding ways to exploit the local resources for the provision of food, construction materials, propellants, pharmaceuticals is an urgent need. Plants are important resources for deep space manned missions because they produce phytochemicals of pharmaceutical relevance, are sources of food and perform photosynthesis, thus providing oxygen which is crucial in bioregenerative life support systems (BLSS). Growth analysis and plant biomass yield have been previously evaluated on Martian regolith simulants, but molecular studies, such as gene expression analysis and protein profiling are still missing. The present work aims at filling this gap by providing molecular data on a representative member of the Poaceae, Lolium multiflorum Lam., grown on normal soil and Martian regolith simulant (MMS-1). The molecular data were complemented with optical microscopy of root/leaf tissues and soil physico-chemical analyses.

INSTRUMENT(S): TripleTOF 6600

ORGANISM(S): Lolium Multiflorum

TISSUE(S): Plant Cell, Root, Leaf

SUBMITTER: Céline LECLERCQ

LAB HEAD: Celine LECLERCQ

PROVIDER: PXD035041 | Pride | 2022-11-07

REPOSITORIES: Pride

ACCESS DATA

Similar Datasets

Project description:Detailed information: Rice (*Oryza sativa* L. cv. Nipponbare) is a drought-susceptible species which is well suited for studies of abiotic stress response because of the comprehensive bioinformatics resource available. By withholding water from the entire root system of young rice plants, or half the root system only, it was possible to infer the relative impact of signals arriving from roots growing in wet and dry soil on the shoot proteome. The global proteome of shoots had 685 proteins in common to all three drought treatments but there were major shifts in abundance of individual proteins within 16 functional categories. The dominant changes were analyzed more deeply. First, we investigated transport and cell component organization, where some proteins were up-regulated by drought but many more down-regulated. Proteins involved in protein metabolism were up-regulated in general by drought when they were responsible for protein degradation but those involved in protein synthesis were down-regulated when water was withheld. Stress-related proteins behaved very consistently by increasing in droughted plants but notably some proteins were most abundant when roots of the same plant were growing in both wet and dry soil. This suggests that drought signals are complex interactions and not simply the additive effect of water supply to the roots. Changes in carbohydrate-processing proteins were consistent with the passive accumulation of soluble sugars in shoots under drought, with hydrolysis of sucrose and starch synthesis both enhanced. Data analysis information: The result raw files were converted to mzXML format and processed through the global proteome machine (GPM) software (version 2.1.1) of the X!Tandem algorithm (freely available at http://www.thegpm.org). The 16 gel fractions were processed serially for each experiment and the output files were generated as non-redundant, merged files with protein identifications with log (e) values less than -1, for each individual gel fraction. A protein database compiled from NCBI *O*. *sativa* with 26938 protein sequences (August 2011) was used in GPM to search the tandem mass spectra; the database also included common trypsin and human peptide contaminants. False discovery rates (FDR) were evaluated by searching against a reversed sequence database. Search parameters included MS and MS/MS tolerances of +2 Da and +0.2 Da, carbamidomethylation of cysteine as fixed modifications, oxidation of methionine as variable modifications and tolerance of two missed tryptic cleavages and K/R-P cleavages.

Project description:Switchgrass plants were grown in a Sandwich tube system to induce gradual drought stress by withholding watering. After 29 days, leaf photosynthetic rate decreased significantly, compared to the control plants which were watered regularly. The drought-treated plants recovered to the same leaf water content after three days of re-watering. Root tip (1cm basal fragment, designated as RT1 hereafter) and the elongation/maturation zone (the next upper 1 cm tissue, designated as RT2 hereafter) tissues were collected at the 29th day of drought stress treatment, (named SDT for severe drought treated), one (D1W) and three days (D3W) of re-watering. The tandem mass tags mass spectrometry-based quantitative proteomics analysis was performed to identify the proteomes, and drought-induced differentially expressed proteins (DEPs). From RT1 tissues, 6,156, 7,687 and 7,699 proteins were quantified, and 296, 535 and 384 DEPs were identified in the SDT, D1W and D3W samples, respectively. From RT2 tissues, 7,382, 7,255 and 6,883 proteins were quantified, and 393, 587 and 321 proteins DEPs were identified in the SDT, D1W and D3W samples. Between RT1 and RT2 tissues, very few DEPs overlapped at SDT, but the number of such proteins increased during the recovery phase. A large number of hydrophilic proteins and stress-responsive proteins were induced during SDT and remained at a higher level during the recovery stages. A large number of DEPs in RT1 tissues maintained the same expression pattern throughout drought treatment and the recovery phases. The DEPs in RT1 tissues were classified in cell proliferation, mitotic cell division, and chromatin modification, and those in RT2 were placed in cell wall remodeling and cell expansion processes. This study provided information pertaining to root zone-specific proteome changes during drought and recover phases, which will allow us to choose the proteins (genes) as better defined targets for developing drought tolerant plants.

Dataset Information

A molecular study of Italian ryegrass grown on Martian regolith simulant

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure