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Sun H, Yu J, Zhang F, Kang J, Li M, Wang Z, Liu W, Zhang J, Yang Q, Long R. iTRAQ-based comparative proteomic analysis of differences in the protein profiles of stems and leaves from two alfalfa genotypes. BMC PLANT BIOLOGY 2020; 20:447. [PMID: 32993512 PMCID: PMC7525974 DOI: 10.1186/s12870-020-02671-2] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/18/2020] [Accepted: 09/23/2020] [Indexed: 05/08/2023]
Abstract
BACKGROUND To explore the molecular regulatory mechanisms of early stem and leaf development, proteomic analysis was performed on leaves and stems of F genotype alfalfa, with thin stems and small leaves, and M genotype alfalfa, with thick stems and large leaves. RESULTS Based on fold-change thresholds of > 1.20 or < 0.83 (p < 0.05), a large number of proteins were identified as being differentially enriched between the M and F genotypes: 249 downregulated and 139 upregulated in stems and 164 downregulated and 134 upregulated in leaves. The differentially enriched proteins in stems were mainly involved in amino acid biosynthesis, phenylpropanoid biosynthesis, carbon fixation, and phenylalanine metabolism. The differentially enriched proteins in leaves were mainly involved in porphyrin and chlorophyll metabolism, phenylpropanoid biosynthesis, starch and sucrose metabolism, and carbon fixation in photosynthetic organisms. Six differentially enriched proteins were mapped onto the porphyrin and chlorophyll metabolism pathway in leaves of the M genotype, including five upregulated proteins involved in chlorophyll biosynthesis and one downregulated protein involved in chlorophyll degradation. Eleven differentially enriched proteins were mapped onto the phenylpropanoid pathway in stems of the M genotype, including two upregulated proteins and nine downregulated proteins. CONCLUSION Enhanced chlorophyll synthesis and decreased lignin synthesis provided a reasonable explanation for the larger leaves and lower levels of stem lignification in M genotype alfalfa. This proteomic study aimed to classify the functions of differentially enriched proteins and to provide information on the molecular regulatory networks involved in stem and leaf development.
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Affiliation(s)
- Hao Sun
- Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100193, China
- Key Laboratory of Animal Nutrition and Feed Science in South China, Ministry of Agriculture and Rural Affairs/ Guangdong Key Laboratory of Animal Breeding and Nutrition, Institute of Animal Science, Guangdong Academy of Agricultural Sciences, Guangzhou, 510640, Guangdong, China
| | - Jie Yu
- Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100193, China
| | - Fan Zhang
- Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100193, China
| | - Junmei Kang
- Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100193, China
| | - Mingna Li
- Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100193, China
| | - Zhen Wang
- Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100193, China
| | - Wenwen Liu
- Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100193, China
| | - Jiaju Zhang
- Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100193, China
| | - Qingchuan Yang
- Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100193, China.
| | - Ruicai Long
- Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100193, China.
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Mamontova T, Lukasheva E, Mavropolo-Stolyarenko G, Proksch C, Bilova T, Kim A, Babakov V, Grishina T, Hoehenwarter W, Medvedev S, Smolikova G, Frolov A. Proteome Map of Pea ( Pisum sativum L.) Embryos Containing Different Amounts of Residual Chlorophylls. Int J Mol Sci 2018; 19:E4066. [PMID: 30558315 PMCID: PMC6320946 DOI: 10.3390/ijms19124066] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/07/2018] [Revised: 12/11/2018] [Accepted: 12/13/2018] [Indexed: 02/06/2023] Open
Abstract
Due to low culturing costs and high seed protein contents, legumes represent the main global source of food protein. Pea (Pisum sativum L.) is one of the major legume crops, impacting both animal feed and human nutrition. Therefore, the quality of pea seeds needs to be ensured in the context of sustainable crop production and nutritional efficiency. Apparently, changes in seed protein patterns might directly affect both of these aspects. Thus, here, we address the pea seed proteome in detail and provide, to the best of our knowledge, the most comprehensive annotation of the functions and intracellular localization of pea seed proteins. To address possible intercultivar differences, we compared seed proteomes of yellow- and green-seeded pea cultivars in a comprehensive case study. The analysis revealed totally 1938 and 1989 nonredundant proteins, respectively. Only 35 and 44 proteins, respectively, could be additionally identified after protamine sulfate precipitation (PSP), potentially indicating the high efficiency of our experimental workflow. Totally 981 protein groups were assigned to 34 functional classes, which were to a large extent differentially represented in yellow and green seeds. Closer analysis of these differences by processing of the data in KEGG and String databases revealed their possible relation to a higher metabolic status and reduced longevity of green seeds.
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Affiliation(s)
- Tatiana Mamontova
- Department of Bioorganic Chemistry, Leibniz Institute of Plant Biochemistry, 06120 Halle (Saale), Germany.
- Department of Biochemistry, St. Petersburg State University, St. Petersburg 199178, Russia.
| | - Elena Lukasheva
- Department of Biochemistry, St. Petersburg State University, St. Petersburg 199178, Russia.
| | | | - Carsten Proksch
- Proteome Analytics, Leibniz Institute of Plant Biochemistry, Weinberg 3, 06120 Halle (Saale), Germany.
| | - Tatiana Bilova
- Department of Bioorganic Chemistry, Leibniz Institute of Plant Biochemistry, 06120 Halle (Saale), Germany.
- Department of Plant Physiology and Biochemistry, St. Petersburg State University, St. Petersburg 199034, Russia.
| | - Ahyoung Kim
- Department of Bioorganic Chemistry, Leibniz Institute of Plant Biochemistry, 06120 Halle (Saale), Germany.
| | - Vladimir Babakov
- Research Institute of Hygiene, Occupational Pathology, and Human Ecology, Federal Medicobiological Agency, 188663 Kapitolovo, Russia.
| | - Tatiana Grishina
- Department of Biochemistry, St. Petersburg State University, St. Petersburg 199178, Russia.
| | - Wolfgang Hoehenwarter
- Proteome Analytics, Leibniz Institute of Plant Biochemistry, Weinberg 3, 06120 Halle (Saale), Germany.
| | - Sergei Medvedev
- Department of Plant Physiology and Biochemistry, St. Petersburg State University, St. Petersburg 199034, Russia.
| | - Galina Smolikova
- Department of Plant Physiology and Biochemistry, St. Petersburg State University, St. Petersburg 199034, Russia.
| | - Andrej Frolov
- Department of Bioorganic Chemistry, Leibniz Institute of Plant Biochemistry, 06120 Halle (Saale), Germany.
- Department of Biochemistry, St. Petersburg State University, St. Petersburg 199178, Russia.
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Big Data in Plant Science: Resources and Data Mining Tools for Plant Genomics and Proteomics. Methods Mol Biol 2016; 1415:533-47. [PMID: 27115651 DOI: 10.1007/978-1-4939-3572-7_27] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/11/2023]
Abstract
In modern plant biology, progress is increasingly defined by the scientists' ability to gather and analyze data sets of high volume and complexity, otherwise known as "big data". Arguably, the largest increase in the volume of plant data sets over the last decade is a consequence of the application of the next-generation sequencing and mass-spectrometry technologies to the study of experimental model and crop plants. The increase in quantity and complexity of biological data brings challenges, mostly associated with data acquisition, processing, and sharing within the scientific community. Nonetheless, big data in plant science create unique opportunities in advancing our understanding of complex biological processes at a level of accuracy without precedence, and establish a base for the plant systems biology. In this chapter, we summarize the major drivers of big data in plant science and big data initiatives in life sciences with a focus on the scope and impact of iPlant, a representative cyberinfrastructure platform for plant science.
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Matysiak J, Hajduk J, Pietrzak Ł, Schmelzer CEH, Kokot ZJ. Shotgun proteome analysis of honeybee venom using targeted enrichment strategies. Toxicon 2014; 90:255-64. [PMID: 25173076 DOI: 10.1016/j.toxicon.2014.08.069] [Citation(s) in RCA: 25] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2014] [Revised: 08/19/2014] [Accepted: 08/20/2014] [Indexed: 01/30/2023]
Abstract
The aim of this study was to explore the honeybee venom proteome applying a shotgun proteomics approach using different enrichment strategies (combinatorial peptide ligand libraries and solid phase extraction). The studies were conducted using nano-LC/MALDI-TOF/TOF-MS system. The MS analysis of peptide profiles (in the range of 900-4500 Da) and virtual gel-image of proteins from Lab-on-Chip assay (in the range of 10-250 kDa) confirm that use of targeted enrichment strategies increase detection of honeybee venom components. The gel-free shotgun strategy and sophisticated instrumentation led to a significant increase of the sensitivity and higher number of identified peptides in honeybee venom samples, comparing with the current literature. Moreover, 11 of 12 known honeybee venom allergens were acknowledged and 4 new, so far uncharacterized proteins were identified. In addition, similarity searches were performed in order to investigate biological relations and homology between newly identified proteins sequences from Apis mellifera and other Hymenoptera.
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Affiliation(s)
- Jan Matysiak
- Department of Inorganic & Analytical Chemistry, Poznan University of Medical Sciences, 6 Grunwaldzka Street, 60-780 Poznań, Poland.
| | - Joanna Hajduk
- Department of Inorganic & Analytical Chemistry, Poznan University of Medical Sciences, 6 Grunwaldzka Street, 60-780 Poznań, Poland
| | - Łukasz Pietrzak
- Department of Inorganic & Analytical Chemistry, Poznan University of Medical Sciences, 6 Grunwaldzka Street, 60-780 Poznań, Poland
| | - Christian E H Schmelzer
- Institute of Pharmacy, Faculty of Natural Sciences I, Martin Luther University Halle-Wittenberg, Halle (Saale), Germany
| | - Zenon J Kokot
- Department of Inorganic & Analytical Chemistry, Poznan University of Medical Sciences, 6 Grunwaldzka Street, 60-780 Poznań, Poland
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Righetti PG, Candiano G, Citterio A, Boschetti E. Combinatorial Peptide Ligand Libraries as a “Trojan Horse” in Deep Discovery Proteomics. Anal Chem 2014; 87:293-305. [DOI: 10.1021/ac502171b] [Citation(s) in RCA: 27] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Affiliation(s)
- Pier Giorgio Righetti
- Politecnico di Milano, Department of Chemistry, Materials and Chemical Engineering “Giulio
Natta”, Via Mancinelli
7, Milano 20131, Italy
| | - Giovanni Candiano
- Laboratory on Pathophysiology of Uremia
and Department of Nephrology, Istituto Giannina Gaslini, Genova, Italy
| | - Attilio Citterio
- Politecnico di Milano, Department of Chemistry, Materials and Chemical Engineering “Giulio
Natta”, Via Mancinelli
7, Milano 20131, Italy
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