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This paper reports a laser capture microdissection-tandem mass tag-quantitative proteomics analysis of Al-sensitive cells in root tips. Cherry tomato (Solanum lycopersicum var. cerasiforme 'LA2710') seedlings were treated under 15 μM Al3+ activity for 13 d. Root-tip longitudinal fresh frozen tissue sections of 10 μm thickness were prepared. The Al-sensitive root zone and cells were determined using histochemical analysis of root-tips and micro-sections. A procedure for collecting the Al-sensitive cells using laser capture microdissection-protein extraction-tandem mass tag-proteomics analysis was developed. Proteomics analysis of 18 μg protein/sample with three biological replicates per treatment condition identified 3879 quantifiable proteins each associated with two or more unique peptides. Quantified proteins constituted a broad range of Kyoto Encyclopedia of Genes and Genomes pathways when searched in the annotated tomato genome. Differentially expressed proteins between the Al-treated and non-Al treated control conditions were identified, including 128 Al-up-regulated and 32 Al-down-regulated proteins. Analysis of functional pathways and protein-protein interaction networks showed that the Al-down-regulated proteins are involved in transcription and translation, and the Al-up-regulated proteins are associated with antioxidant and detoxification and protein quality control processes. The proteomics data are available via ProteomeXchange with identifier PXD010459 under project title 'LCM-quantitative proteomics analysis of Al-sensitive tomato root cells'. SIGNIFICANCE: This paper presents an efficient laser capture microdissection-tandem mass tag-quantitative proteomics analysis platform for the analysis of Al sensitive root cells. The analytical procedure has a broad application for proteomics analysis of spatially separated cells from complex tissues. This study has provided a comprehensive proteomics dataset expressed in the epidermal and outer-cortical cells at root-tip transition zone of Al-treated tomato seedlings. The proteomes from the Al-sensitive root cells are valuable resources for understanding and improving Al tolerance in plants.
Pubmed ID: 31669359
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Randomized controlled trial being conducted at two clinical centers in the United States to learn more about the effects of weight loss on urinary incontinence. About 330 overweight women aged 30 or older will participate and will be followed for 18 months. Efficacy of weight reduction as a treatment for urinary incontinence will be examined at 6 months following the intensive weight control program, and the sustained impact of the intervention will be examined at 18 months. To increase the maintenance of weight reduction and facilitate evaluation of the enduring impact of weight loss on urinary incontinence, they propose to study a motivation-based weight maintenance program. At the end of the intensive weight control program, women randomized to the weight loss program will be randomized to either a 12-month skill-based maintenance intervention or to a motivation-based maintenance intervention. The maintenance interventions maximize the potential for sustained weight loss and will allow them to determine if long-term weight reduction will produce continued improvement in urinary incontinence.
View all literature mentionsA software which acquires and processes data sets, primarily through the Xcalibur system.
View all literature mentionsPercolator post-processes the results of a shotgun proteomics database search program, re-ranking peptide-spectrum matches so that the top of the list is enriched for correct matches. Shotgun proteomics uses liquid chromatography-tandem mass spectrometry to identify proteins in complex biological samples. We describe an algorithm, called Percolator, for improving the rate of peptide identifications from a collection of tandem mass spectra. Percolator uses semi-supervised machine learning to discriminate between correct and decoy spectrum identifications, correctly assigning peptides to 17% more spectra from a tryptic dataset and up to 77% more spectra from non-tryptic digests, relative to a fully supervised approach. The yeast-01 data is available in tab delimetered format. The SEQUEST parameter file and target database for the yeast and worm data are also available.
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