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Shen, T.

Publications and source records attributed to Shen, T..

2 recordsLinked to original sources
bioRxiv2018

Metabolomics and proteomics analyses of grain yield reduction in rice under abrupt drought-flood alternation

HighlightAbrupt drought-flood alteration is a frequent meteorological disaster that occurs during summer in southern China and the Yangtze river basin, which often causes a large area reduction of rice yield. We previously reported abrupt drought-flood alteration effects on yield and its components, physiological characteristics, matter accumulation and translocation, rice quality of rice. However, the molecular mechanism of rice yield reduction caused by abrupt drought-flood alternation has not been reported.\n\nIn this study, four treatments were provided, no drought and no floods (control), drought without floods (duration of drought 10 d), no drought with floods (duration of floods 8 d), and abrupt drought-flood alteration (duration of drought 10 d and floods 8 d). The quantitative analysis of spike metabolites was proceeded by LC-MS (liquid chromatograph-mass spectrometry) firstly. Then the Heat-map, PCA, PLS-DA, OPLS-DA and response ranking test of OPLS-DA model methods were used to analysis the function of differential metabolites (DMs) during the rice panicle differentiation stage under abrupt drought-flood alteration. In addition, relative quantitative analysis of spike total proteins under the treatment was conducted iTRAQ (isobaric tags for relative and absolute quantification) and LC-MS. In this study, 5708 proteins were identified and 4803 proteins were quantified. The identification and analysis of DEPs function suggested that abrupt drought-flood alteration treatment can promote carbohydrate metabolic, stress response, oxidation-reduction, defense response, and energy reserve metabolic process, etc, during panicle differentiation stage. In this study relative quantitative proteomics, metabolomics and physiology data (soluble protein content, superoxide dismutase activity, hydrogen peroxidase activity, peroxidase activity, malondialdehyde content, free proline content, soluble sugar content and net photosynthetic rate) analysis were applied to explicit the response mechanism of rice panicle differentiation stage under abrupt drought-flood alteration and provides a theoretical basis for the disaster prevention and mitigation.\n\nAbstractAbrupt drought-flood alternation is a meteorological disaster that frequently occurs during summer in southern China and the Yangtze river basin, often causing a significant loss of rice production. In this study, a quantitative analysis of spike metabolites was conducted via liquid chromatograph-mass spectrometry (LC-MS), and Heat-map, PCA, PLS-DA, OPLS-DA, and a response ranking test of OPLS-DA model methods were used to analyze functions of differential metabolites (DMs) during the rice panicle differentiation stage under abrupt drought-flood alternation. The results showed that 102 DMs were identified from the rice spike between T1 (abrupt drought-flood alternation) and CK0 (control) treatment, 104 DMs were identified between T1 and CK1 (drought) treatment and 116 DMs were identified between T1 and CK2 (flood) treatment. In addition, a relative quantitative analysis of spike total proteins was conducted using isobaric tags for relative and absolute quantification (iTRAQ) and LC-MS. The identification and analysis of DEPs functions indicates that abrupt drought-flood alternation treatment can promote carbohydrate metabolic, stress response, oxidation-reduction, defense response, and energy reserve metabolic process during the panicle differentiation stage. In this study, relative quantitative metabolomics and proteomics analyses were applied to explore the response mechanism of rice panicle differentiation in response to abrupt drought-flood alternation.\n\nAbbreviations

plant biology↗
bioRxiv2018

Characterizing the 3D structure and dynamics of chromosomes and proteins in a common contact matrix framework

Any conformational ensemble of biopolymers, whether they are proteins or chromosomes, can be described using contact matrices derived from experimental or computational studies. One powerful approach to extract meaningful information from these contact matrices is to perform principal component analysis (PCA) on the covariance matrix of the contact data. Indeed, PCA on Hi-C chromosome contact matrices has revealed the spatial segregation of active and inactive chromatin. Separately, PCA on contact matrices from snapshots of protein conformations has characterized correlated fluctuations of protein domains. However, despite the similarities of these data and analyses, there has been little synergy between the PCA approaches and the comparison of resulting biological insights obtained for protein and chromosome structures. We note that, to date, different styles of analyses were applied exclusively to each biomolecule type: explicit contact correlation analysis (E-PCA) for proteins and implicit contact correlation (I-PCA) for chromosomes. In this work, we compare the results of applying both methods to both classes of biopolymers. While I-PCA reveals only average features of 3D chromosome structure, we find that applying E-PCA to an ensemble of chromosome structures from microscopy data reveals the dominant motion (concerted fluctuation) of the chromosome. Applying E-PCA to Hi-C data across the human blood cell lineage isolates the aspects of chromosome structure that most strongly differentiate cell types. Conversely, when we apply I-PCA to simulation snapshots of two protein complexes, the major component reports the consensus features of the structure, while the previously applied E-PCA characterizes correlated deviations from the mean structure.

biophysics↗