SoyProLow: A protein database enriched in low abundant soybean proteins

Progress in soybean functional genomics over the past decade

Soybean is one of the most important oilseed and fodder crops. Benefiting from the efforts of soybean breeders and the development of breeding technology, large number of germplasm has been generated over the last 100 years. Nevertheless, soybean breeding needs to be accelerated to meet the needs of a growing world population, to promote sustainable agriculture and to address future environmental changes. The acceleration is highly reliant on the discoveries in gene functional studies. The release of the reference soybean genome in 2010 has significantly facilitated the advance in soybean functional genomics. Here, we review the research progress in soybean omics (genomics, transcriptomics, epigenomics and proteomics), germplasm development (germplasm resources and databases), gene discovery (genes that are responsible for important soybean traits including yield, flowering and maturity, seed quality, stress resistance, nodulation and domestication) and transformation technology during the past decade. At the end, we also briefly discuss current challenges and future directions.

GmGPA3 is involved in post-Golgi trafficking of storage proteins and cell growth in soybean cotyledons

As the major nutritional component in soybean seeds storage proteins are initially synthesized on the endoplasmic reticulum as precursors and subsequently delivered to protein storage vacuoles (PSVs) via the Golgi-mediated pathway where they are converted into mature subunits and accumulated. However, the molecular machinery required for storage protein trafficking in soybean remains largely unknown. In this study, we cloned the sole soybean homolog of OsGPA3 that encodes a plant-unique kelch-repeat regulator of post-Golgi vesicular traffic for rice storage protein sorting. A complementation test showed that GmGPA3 could rescue the rice gpa3 mutant. Biochemical assays verified that GmGPA3 physically interacts with GmRab5 and its guanine exchange factor (GEF) GmVPS9. Expression of GmGPA3 had no obvious effect on the GEF activity of GmVPS9 toward GmRab5a. Notably, knock-down of GmGPA3 disrupted the trafficking of mmRFP-CT10 (an artificial cargo destined for PSVs) in developing soybean cotyledons. We identified two putative GmGPA3 interacting partners (GmGMG3 and GmGMG11) by screening a yeast cDNA library. Overexpression of GmGPA3 or GmGMG3 caused shrunken cotyledon cells. Our overall results suggested that GmGPA3 plays an important role in cell growth and development, in addition to its conserved role in mediating storage protein trafficking in soybean cotyledons.

Detection of Plant Low-Abundance Proteins by Means of Combinatorial Peptide Ligand Library Methods

The detection and identification of low-abundance proteins from plant tissues is still a major challenge. Among the reasons are the low protein content, the presence of few very high-abundance proteins, and the presence of massive amounts of other biochemical compounds. In the last decade numerous technologies have been devised to resolve the situation, in particular with methods based on solid-phase combinatorial peptide ligand libraries. This methodology, allowing for an enhancement of low-abundance proteins, has been extensively applied with the advantage of deciphering the proteome composition of various plant organs. This general methodology is here described extensively along with a number of possible variations. Specific guidelines are suggested to cover peculiar situations or to comply with other associated analytical methods.

Low-abundance plant protein enrichment with peptide libraries to enlarge proteome coverage and related applications

In plant tissues proteins are present in low amounts but in a very large number. To this peculiar situation many complex foreign components render protein extraction and purification very difficult. In the last several years interesting technologies have been described to improve the technical situation to the point that some methodologies allow reaching very low-abundance proteins and minor allergens. Among enrichment methods the one documented in this report is based on combinatorial peptide ligand libraries (CPLLs) that emerged in the last decade by contributing to largely improve the knowledge in plant proteomics. It is the aim of this review to describe how this technology allows detecting low-abundance proteins from various plant tissues and to report the dynamics of the proteome components in response to environmental changes and biotic attacks. Typical documented examples with the description of their scientific interest are reported. The described technical approach and selected applications are considered as one of the most advanced approaches for plant proteomics investigations with possibilities not only to enlarge the knowledge of plant proteomes but also to discover novel allergens as well as plant biomarkers subsequent to stressful situations.

Integration of gel-based and gel-free proteomic data for functional analysis of proteins through Soybean Proteome Database

The Soybean Proteome Database (SPD) stores data on soybean proteins obtained with gel-based and gel-free proteomic techniques. The database was constructed to provide information on proteins for functional analyses. The majority of the data is focused on soybean (Glycine max 'Enrei'). The growth and yield of soybean are strongly affected by environmental stresses such as flooding. The database was originally constructed using data on soybean proteins separated by two-dimensional polyacrylamide gel electrophoresis, which is a gel-based proteomic technique. Since 2015, the database has been expanded to incorporate data obtained by label-free mass spectrometry-based quantitative proteomics, which is a gel-free proteomic technique. Here, the portions of the database consisting of gel-free proteomic data are described. The gel-free proteomic database contains 39,212 proteins identified in 63 sample sets, such as temporal and organ-specific samples of soybean plants grown under flooding stress or non-stressed conditions. In addition, data on organellar proteins identified in mitochondria, nuclei, and endoplasmic reticulum are stored. Furthermore, the database integrates multiple omics data such as genomics, transcriptomics, metabolomics, and proteomics. The SPD database is accessible at http://proteome.dc.affrc.go.jp/Soybean/.

BIOLOGICAL SIGNIFICANCE

The Soybean Proteome Database stores data obtained from both gel-based and gel-free proteomic techniques. The gel-free proteomic database comprises 39,212 proteins identified in 63 sample sets, such as different organs of soybean plants grown under flooding stress or non-stressed conditions in a time-dependent manner. In addition, organellar proteins identified in mitochondria, nuclei, and endoplasmic reticulum are stored in the gel-free proteomics database. A total of 44,704 proteins, including 5490 proteins identified using a gel-based proteomic technique, are stored in the SPD. It accounts for approximately 80% of all predicted proteins from genome sequences, though there are over lapped proteins. Based on the demonstrated application of data stored in the database for functional analyses, it is suggested that these data will be useful for analyses of biological mechanisms in soybean. Furthermore, coupled with recent advances in information and communication technology, the usefulness of this database would increase in the analyses of biological mechanisms.

Improvement of Soybean Products Through the Response Mechanism Analysis Using Proteomic Technique

Soybean is rich in protein/vegetable oil and contains several phytochemicals such as isoflavones and phenolic compounds. Because of the predominated nutritional values, soybean is considered as traditional health benefit food. Soybean is a widely cultivated crop; however, its growth and yield are markedly affected by adverse environmental conditions. Proteomic techniques make it feasible to map protein profiles both during soybean growth and under unfavorable conditions. The stress-responsive mechanisms during soybean growth have been uncovered with the help of proteomic studies. In this review, the history of soybean as food and the morphology/physiology of soybean are described. The utilization of proteomics during soybean germination and development is summarized. In addition, the stress-responsive mechanisms explored using proteomic techniques are reviewed in soybean.