Mass spectrometry-based proteomics for the detection of plant pathogens

Combinatorial Interactions of Biotic and Abiotic Stresses in Plants and Their Molecular Mechanisms: Systems Biology Approach

Plants are continually facing biotic and abiotic stresses, and hence, they need to respond and adapt to survive. Plant response during multiple and combined biotic and abiotic stresses is highly complex and varied than the individual stress. These stresses resulted alteration of plant behavior through regulating the levels of microRNA, heat shock proteins, epigenetic variations. These variations can cause many adverse effects on the growth and development of the plant. Further, in natural conditions, several abiotic stresses causing factors make the plant more susceptible to pathogens infections and vice-versa. A very intricate and multifaceted interactions of various biomolecules are involved in metabolic pathways that can direct towards a cross-tolerance and improvement of plant's defence system. Systems biology approach plays a significant role in the investigation of these molecular interactions. The valuable information obtained by systems biology will help to develop stress-resistant plant varieties against multiple stresses. Thus, this review aims to decipher various multilevel interactions at the molecular level under combinatorial biotic and abiotic stresses and the role of systems biology to understand these molecular interactions.

Analysis of root proteome unravels differential molecular responses during compatible and incompatible interaction between chickpea (Cicer arietinum L.) and Fusarium oxysporum f. sp. ciceri Race1 (Foc1)

BACKGROUND

Vascular wilt caused by Fusarium oxysporum f. sp. ciceri Race 1 (Foc1) is a serious disease of chickpea (Cicer arietinum L.) accounting for approximately 10-15% annual crop loss. The fungus invades the plant via roots, colonizes the xylem vessels and prevents the upward translocation of water and nutrients, finally resulting in wilting of the entire plant. Although comparative transcriptomic profiling have highlighted some important signaling molecules, but proteomic studies involving chickpea-Foc1 are limited. The present study focuses on comparative root proteomics of susceptible (JG62) and resistant (WR315) chickpea genotypes infected with Foc1, to understand the mechanistic basis of susceptibility and/or resistance.

RESULTS

The differential and unique proteins of both genotypes were identified at 48 h, 72 h, and 96 h post Foc1 inoculation. 2D PAGE analyses followed by MALDI-TOF MS and MS/MS identified 100 differentially (>1.5 fold<, p<0.05) or uniquely expressed proteins. These proteins were further categorized into 10 functional classes and grouped into GO (gene ontology) categories. Network analyses of identified proteins revealed intra and inter relationship of these proteins with their neighbors as well as their association with different defense signaling pathways. qRT-PCR analyses were performed to correlate the mRNA and protein levels of some proteins of representative classes.

CONCLUSIONS

The differential and unique proteins identified indicate their involvement in early defense signaling of the host. Comparative analyses of expression profiles of obtained proteins suggest that albeit some common components participate in early defense signaling in both susceptible and resistant genotypes, but their roles and regulation differ in case of compatible and/or incompatible interactions. Thus, functional characterization of identified PR proteins (PR1, BGL2, TLP), Trypsin protease inhibitor, ABA responsive protein, cysteine protease, protein disulphide isomerase, ripening related protein and albumins are expected to serve as important molecular components for biotechnological application and development of sustainable resistance against Foc1.

Screening metagenomic data for viruses using the e-probe diagnostic nucleic acid assay

Next generation sequencing (NGS) is not used commonly in diagnostics, in part due to the large amount of time and computational power needed to identify the taxonomic origin of each sequence in a NGS data set. By using the unassembled NGS data sets as the target for searches, pathogen-specific sequences, termed e-probes, could be used as queries to enable detection of specific viruses or organisms in plant sample metagenomes. This method, designated e-probe diagnostic nucleic acid assay, first tested with mock sequence databases, was tested with NGS data sets generated from plants infected with a DNA (Bean golden yellow mosaic virus, BGYMV) or an RNA (Plum pox virus, PPV) virus. In addition, the ability to detect and differentiate among strains of a single virus species, PPV, was examined by using probe sets that were specific to strains. The use of probe sets for multiple viruses determined that one sample was dually infected with BGYMV and Bean golden mosaic virus.

Development of proteomic technology of shotgun and label free combined with multiple reaction monitoring to simultaneously detect southern rice black-streaked dwarf virus and rice ragged stunt virus

The co-infection of rice caused by southern rice black-streaked dwarf virus (SRBSDV) and rice ragged stunt virus (RRSV) was widely found at many regions, such as Yunnan Province, China, and North and Central Vietnam. These rice viral diseases lead to seriously yield loss of rice. In this study, the proteomics technology of shotgun and label free combined with multiple reaction monitoring (MRM) was developed to detect rice sample of a single or/and co-infection. The shotgun assay indicated that some proteins coded by SRBSDV and RRSV were detected via the mode of in-gel digestion, except for P5-2, P7-2 and P9-2 of SRBSDV and P4b, P5, P6, P8a and P8b of RRSV. The technology of label free combined with MRM indicated that P2, P5-1, P4, P8, P7-1, P6, P9-1 and P10 of SRBSDV and P1, P3 and P9 of RRSV were higher abundance in rice plant, and P5-2, P7-2 and P9-2 of SRBSDV and P4b and P5 of RRSV were lower abundance in viruliferous-rice plant. So SRBSDV P9-1 and RRSV P3 was selected as marker molecule to be used in detection technology, and the label free combined with MRM technology was established to detect two kinds of rice virus.

Identifying secreted proteins of Marssonina brunnea by degenerate PCR

Marssonina brunnea is an important fungal pathogen of the Populus genus. To further our understanding of the pathogenesis of M. brunnea, we initiated a proteome-level study of the fungal secretome. Using de novo peptide sequencing by MS/MS, we obtained peptide sequences for 32 protein spots. Four proteins were identified by sequence homology to conserved proteins in public databases using MS-driven BLAST. To identify additional protein spots, we combined a degenerate PCR method, based on the Consensus-DEgenerate Hybrid Oligonucleotide Primer (CODEHOP) method, and a rapid amplification of cDNA ends method to clone the full-length cDNA fragments encoding the proteins identified in the gel. Using this method, we cloned the full-length cDNA fragments encoding 11 M. brunnea-specific proteins. This method provides an efficient approach to identification of species-specific proteins of non-sequenced organisms. Furthermore, we analyzed the expression patterns of these genes during infection. We found that most of the identified secreted proteins could be induced in artificial medium after hyphae entered poplar apoplast spaces. We propose that for the host-specialized M. brunnea, the elongation of hyphae has evolved closely with the secretion of apoplastic proteins.

Identification of plant viruses using one-dimensional gel electrophoresis and peptide mass fingerprints

A generic assay to detect and partially characterize unknown viruses from plants was developed. Proteins extracted from virus-infected and uninfected plants were separated in one dimension by SDS polyacrylamide gel electrophoresis. Differentially expressed protein bands were eluted after trypsin digestion and resulting peptide fragments separated according to their mass by matrix-assisted laser-desorption ionization time-of-flight (MALDI-TOF) mass spectrometry. Resulting peptide mass fingerprints (PMF) were compared with those in protein databases. The assay was used to identify three known viruses: the potyviruses Zucchini yellow mosaic virus and Turnip mosaic virus, and an alfamovirus Alfalfa mosaic virus. It was also used to identify a virus that manifested symptoms in wild Cakile maritima plants, tentatively identified as Pelargonium zonate spot virus (PZSV) (genus Anulavirus) by its PMF, and then confirmed by nucleotide sequencing. The detection of PZSV constitutes a first record of this virus in Australia and in this host. It is proposed that this rapid and simple assay is a useful approach for analysis of plant samples known to harbor viruses that could not be identified using antisera or nucleic acid-based assays.

Tools for exploring the proteomosphere

Homology-driven proteomics aims at exploring the proteomes of organisms with unsequenced genomes that, despite rapid genomic sequencing progress, still represent the overwhelming majority of species in the biosphere. Methodologies have been developed to enable automated LC-MS/MS identifications of unknown proteins, which rely on the sequence similarity between the fragmented peptides and reference database sequences from phylogenetically related species. However, because full sequences of matched proteins are not available and matching specificity is reduced, estimating protein abundances should become the obligatory element of homology-driven proteomics pipelines to circumvent the interpretation bias towards proteins from evolutionary conserved families.

Tandem mass spectrometry for the detection of plant pathogenic fungi and the effects of database composition on protein inferences

LC-MS/MS has demonstrated potential for detecting plant pathogens. Unlike PCR or ELISA, LC-MS/MS does not require pathogen-specific reagents for the detection of pathogen-specific proteins and peptides. However, the MS/MS approach we and others have explored does require a protein sequence reference database and database-search software to interpret tandem mass spectra. To evaluate the limitations of database composition on pathogen identification, we analyzed proteins from cultured Ustilago maydis, Phytophthora sojae, Fusarium graminearum, and Rhizoctonia solani by LC-MS/MS. When the search database did not contain sequences for a target pathogen, or contained sequences to related pathogens, target pathogen spectra were reliably matched to protein sequences from nontarget organisms, giving an illusion that proteins from nontarget organisms were identified. Our analysis demonstrates that when database-search software is used as part of the identification process, a paradox exists whereby additional sequences needed to detect a wide variety of possible organisms may lead to more cross-species protein matches and misidentification of pathogens.