Shotgun Proteomics as a Powerful Tool for the Study of the Proteomes of Plants, Their Pathogens, and Plant-Pathogen Interactions

Deep-HPI-pred: An R-Shiny applet for network-based classification and prediction of Host-Pathogen protein-protein interactions

Host-pathogen interactions (HPIs) are vital in numerous biological activities and are intrinsically linked to the onset and progression of infectious diseases. HPIs are pivotal in the entire lifecycle of diseases: from the onset of pathogen introduction, navigating through the mechanisms that bypass host cellular defenses, to its subsequent proliferation inside the host. At the heart of these stages lies the synergy of proteins from both the host and the pathogen. By understanding these interlinking protein dynamics, we can gain crucial insights into how diseases progress and pave the way for stronger plant defenses and the swift formulation of countermeasures. In the framework of current study, we developed a web-based R/Shiny app, Deep-HPI-pred, that uses network-driven feature learning method to predict the yet unmapped interactions between pathogen and host proteins. Leveraging citrus and CLas bacteria training datasets as case study, we spotlight the effectiveness of Deep-HPI-pred in discerning Protein-protein interaction (PPIs) between them. Deep-HPI-pred use Multilayer Perceptron (MLP) models for HPI prediction, which is based on a comprehensive evaluation of topological features and neural network architectures. When subjected to independent validation datasets, the predicted models consistently surpassed a Matthews correlation coefficient (MCC) of 0.80 in host-pathogen interactions. Remarkably, the use of Eigenvector Centrality as the leading topological feature further enhanced this performance. Further, Deep-HPI-pred also offers relevant gene ontology (GO) term information for each pathogen and host protein within the system. This protein annotation data contributes an additional layer to our understanding of the intricate dynamics within host-pathogen interactions. In the additional benchmarking studies, the Deep-HPI-pred model has proven its robustness by consistently delivering reliable results across different host-pathogen systems, including plant-pathogens (accuracy of 98.4% and 97.9%), human-virus (accuracy of 94.3%), and animal-bacteria (accuracy of 96.6%) interactomes. These results not only demonstrate the model's versatility but also pave the way for gaining comprehensive insights into the molecular underpinnings of complex host-pathogen interactions. Taken together, the Deep-HPI-pred applet offers a unified web service for both identifying and illustrating interaction networks. Deep-HPI-pred applet is freely accessible at its homepage: https://cbi.gxu.edu.cn/shiny-apps/Deep-HPI-pred/ and at github: https://github.com/tahirulqamar/Deep-HPI-pred.

Unveiling the Secrets of Oil Palm Genetics: A Look into Omics Research

Oil palm is a versatile oil crop with numerous applications. Significant progress has been made in applying histological techniques in oil palm research in recent years. Whole genome sequencing of oil palm has been carried out to explain the function and structure of the order genome, facilitating the development of molecular markers and the construction of genetic maps, which are crucial for studying important traits and genetic resources in oil palm. Transcriptomics provides a powerful tool for studying various aspects of plant biology, including abiotic and biotic stresses, fatty acid composition and accumulation, and sexual reproduction, while proteomics and metabolomics provide opportunities to study lipid synthesis and stress responses, regulate fatty acid composition based on different gene and metabolite levels, elucidate the physiological mechanisms in response to abiotic stresses, and explain intriguing biological processes in oil palm. This paper summarizes the current status of oil palm research from a multi-omics perspective and hopes to provide a reference for further in-depth research on oil palm.

Incorporating omics-based tools into endophytic fungal research

Fungal endophytes are valuable sources of bioactive compounds with diverse applications. The exploration of these compounds not only contributes to our understanding of ecological interactions but also holds promise for the development of novel products with agricultural, medicinal, and industrial significance. Continued exploration of fungal endophyte diversity and understanding the ecological roles of bioactive compounds present opportunities for new discoveries and applications. Omics techniques, which include genomics, transcriptomics, proteomics, and metabolomics, contribute to the discovery of novel bioactive compounds produced by fungal endophytes with their potential applications. The omics techniques play a critical role in unraveling the complex interactions between fungal endophytes and their host plants, providing valuable insights into the molecular mechanisms and potential applications of these relationships. This review provides an overview of how omics techniques contribute to the study of fungal endophytes.

Common Post-translational Modifications (PTMs) of Proteins: Analysis by Up-to-Date Analytical Techniques with an Emphasis on Barley

Post-translational modifications (PTMs) of biomacromolecules can be useful for understanding the processes by which a relatively small number of individual genes in a particular genome can generate enormous biological complexity in different organisms. The proteomes of barley and the brewing process were investigated by different techniques. However, their diverse and complex PTMs remain understudied. As standard analytical approaches have limitations, innovative analytical approaches need to be developed and applied in PTM studies. To make further progress in this field, it is necessary to specify the sites of modification, as well as to characterize individual isoforms with increased selectivity and sensitivity. This review summarizes advances in the PTM analysis of barley proteins, particularly those involving mass spectrometric detection. Our focus is on monitoring phosphorylation, glycation, and glycosylation, which critically influence functional behavior in metabolism and regulation in organisms.

Comprehensive Organ-Specific Profiling of Douglas Fir (Pseudotsuga menziesii) Proteome

The Douglas fir (Pseudotsuga menziesii) is a conifer native to North America that has become increasingly popular in plantations in France due to its many advantages as timber: rapid growth, quality wood, and good adaptation to climate change. Tree genetic improvement programs require knowledge of a species' genetic structure and history and the development of genetic markers. The very slow progress in this field, for Douglas fir as well as the entire genus Pinus, can be explained using the very large size of their genomes, as well as by the presence of numerous highly repeated sequences. Proteomics, therefore, provides a powerful way to access genomic information of otherwise challenging species. Here, we present the first Douglas fir proteomes acquired using nLC-MS/MS from 12 different plant organs or tissues. We identified 3975 different proteins and quantified 3462 of them, then examined the distribution of specific proteins across plant organs/tissues and their implications in various molecular processes. As the first large proteomic study of a resinous tree species with organ-specific profiling, this short note provides an important foundation for future genomic annotations of conifers and other trees.

The Pitaya Flower Tissue's Gene Differential Expression Analysis between Self-Incompatible and Self-Compatible Varieties for the Identification of Genes Involved in Self-Incompatibility Regulation

Self-incompatible pitaya varieties have low fruit-setting rates under natural conditions, leading to higher production costs and hindering industrial prosperity. Through transcriptome sequencing, we obtained the 36,900 longest transcripts (including 9167 new transcripts) from 60 samples of flowers. Samples were collected pre- and post-pollination (at 0 h, 0.5 h, 2 h, 4 h, and 12 h) from two varieties of pitaya (self-compatible Jindu No. 1 and self-incompatible Cu Sha). Using the RNA-Seq data and comparison of reference genomes, we annotated 28,817 genes in various databases, and 1740 genes were optimized in their structure for annotation. There were significant differences in the expression of differentially expressed genes (DEGs) in the pitaya stigmas under different pollination types, especially at the late post-pollination stage, where the expression of protease genes increasedal significantly under cross-pollination. We identified DEGs involved in the ribosomal, ubiquitination-mediated, and phyto-signaling pathways that may be involved in pitaya SI regulation. Based on the available transcriptome data and bioinformatics analysis, we tentatively identified HuS-RNase2 as a candidate gynogenetic S gene in the pitaya GSI system.

A bibliometric analysis of the global impact of metaproteomics research

Background

Metaproteomics is a subfield in meta-omics that is used to characterize the proteome of a microbial community. Despite its importance and the plethora of publications in different research area, scientists struggle to fully comprehend its functional impact on the study of microbiomes. In this study, bibliometric analyses are used to evaluate the current state of metaproteomic research globally as well as evaluate the specific contribution of Africa to this burgeoning research area. In this study, we use bibliometric analyses to evaluate the current state of metaproteomic research globally, identify research frontiers and hotspots, and further predict future trends in metaproteomics. The specific contribution of Africa to this research area was evaluated.

Methods

Relevant documents from 2004 to 2022 were extracted from the Scopus database. The documents were subjected to bibliometric analyses and visualization using VOS viewer and Biblioshiny package in R. Factors such as the trends in publication, country and institutional cooperation networks, leading scientific journals, author's productivity, and keywords analyses were conducted. The African publications were ranked using Field-Weighted Citation Impact (FWCI) scores.

Results

A total of 1,138 documents were included and the number of publications increased drastically from 2004 to 2022 with more publications (170) reported in 2021. In terms of publishers, Frontiers in Microbiology had the highest number of total publications (62). The United States of America (USA), Germany, China, and Canada, together with other European countries were the most productive. Institution-wise, the Helmholtz Zentrum für Umweltforschung, Germany had more publications while Max Plank Institute had the highest total collaborative link strength. Jehmlich N. was the most productive author whereas Hettich RL had the highest h-index of 63. Regarding Africa, only 2.2% of the overall publications were from the continent with more publication outputs from South Africa. More than half of the publications from the continent had an FWCI score ≥ 1.

Conclusion

The scientific outputs of metaproteomics are rapidly evolving with developed countries leading the way. Although Africa showed prospects for future progress, this could only be accelerated by providing funding, increased collaborations, and mentorship programs.

Osmoprotectants play a major role in the Portulaca oleracea resistance to high levels of salinity stress-insights from a metabolomics and proteomics integrated approach

Introduction

Purslane (Portulaca oleracea L.) is a non-conventional food plant used extensively in folk medicine and classified as a multipurpose plant species, serving as a source of features of direct importance to the agricultural and agri-industrial sectors. This species is considered a suitable model to study the mechanisms behind resistance to several abiotic stresses including salinity. The recently achieved technological developments in high-throughput biology opened a new window of opportunity to gain additional insights on purslane resistance to salinity stress-a complex, multigenic, and still not well-understood trait. Only a few reports on single-omics analysis (SOA) of purslane are available, and only one multi-omics integration (MOI) analysis exists so far integrating distinct omics platforms (transcriptomics and metabolomics) to characterize the response of purslane plants to salinity stress.

Methods

The present study is a second step in building a robust database on the morpho-physiological and molecular responses purslane to salinity stress and its subsequent use in attempting to decode the genetics behind its resistance to this abiotic stress. Here, the characterization of the morpho-physiological responses of adult purslane plants to salinity stress and a metabolomics and proteomics integrative approach to study the changes at the molecular level in their leaves and roots is presented.

Results and discussion

Adult plants of the B1 purslane accession lost approximately 50% of the fresh and dry weight (from shoots and roots) whensubmitted to very high salinity stress (2.0 g of NaCl/100 g of the substrate). The resistance to very high levels of salinity stress increases as the purslane plant matures, and most of the absorbed sodium remains in the roots, with only a part (~12%) reaching the shoots. Crystal-like structures, constituted mainly by Na⁺, Cl^-, and K⁺, were found in the leaf veins and intercellular space near the stoma, indicating that this species has a mechanism of salt exclusion operating on the leaves, which has its role in salt tolerance. The MOI approach showed that 41 metabolites were statistically significant on the leaves and 65 metabolites on the roots of adult purslane plants. The combination of the mummichog algorithm and metabolomics database comparison revealed that the glycine, serine, and threonine, amino sugar and nucleotide sugar, and glycolysis/gluconeogenesis pathways were the most significantly enriched pathways when considering the total number of occurrences in the leaves (with 14, 13, and 13, respectively) and roots (all with eight) of adult plants; and that purslane plants employ the adaptive mechanism of osmoprotection to mitigate the negative effect of very high levels of salinity stress; and that this mechanism is prevalent in the leaves. The multi-omics database built by our group underwent a screen for salt-responsive genes, which are now under further characterization for their potential to promote resistance to salinity stress when heterologously overexpressed in salt-sensitive plants.

Bottom-Up Proteomics: Advancements in Sample Preparation

Liquid chromatography–tandem mass spectrometry (LC–MS/MS)-based proteomics is a powerful technique for profiling proteomes of cells, tissues, and body fluids. Typical bottom-up proteomic workflows consist of the following three major steps: sample preparation, LC–MS/MS analysis, and data analysis. LC–MS/MS and data analysis techniques have been intensively developed, whereas sample preparation, a laborious process, remains a difficult task and the main challenge in different applications. Sample preparation is a crucial stage that affects the overall efficiency of a proteomic study; however, it is prone to errors and has low reproducibility and throughput. In-solution digestion and filter-aided sample preparation are the typical and widely used methods. In the past decade, novel methods to improve and facilitate the entire sample preparation process or integrate sample preparation and fractionation have been reported to reduce time, increase throughput, and improve reproducibility. In this review, we have outlined the current methods used for sample preparation in proteomics, including on-membrane digestion, bead-based digestion, immobilized enzymatic digestion, and suspension trapping. Additionally, we have summarized and discussed current devices and methods for integrating different steps of sample preparation and peptide fractionation.

Understanding the Proteomes of Plant Development and Stress Responses in Brassica Crops

Brassica crops have great economic value due to their rich nutritional content and are therefore grown worldwide as oilseeds, vegetables, and condiments. Deciphering the molecular mechanisms associated with the advantageous phenotype is the major objective of various Brassica improvement programs. As large technological advancements have been achieved in the past decade, the methods to understand molecular mechanisms underlying the traits of interest have also taken a sharp upturn in plant breeding practices. Proteomics has emerged as one of the preferred choices nowadays along with genomics and other molecular approaches, as proteins are the ultimate effector molecules responsible for phenotypic changes in living systems, and allow plants to resist variable environmental stresses. In the last two decades, rapid progress has been made in the field of proteomics research in Brassica crops, but a comprehensive review that collates the different studies is lacking. This review provides an inclusive summary of different proteomic studies undertaken in Brassica crops for cytoplasmic male sterility, oil content, and proteomics of floral organs and seeds, under different biotic and abiotic stresses including post-translational modifications of proteins. This comprehensive review will help in understanding the role of different proteins in controlling plant phenotypes, and provides information for initiating future studies on Brassica breeding and improvement programs.

Endophytic Diaporthe as Promising Leads for the Development of Biopesticides and Biofertilizers for a Sustainable Agriculture

Plant pathogens are responsible for causing economic and production losses in several crops worldwide, thus reducing the quality and quantity of agricultural supplies. To reduce the usage of chemically synthesized pesticides, strategies and approaches using microorganisms are being used in plant disease management. Most of the studies concerning plant-growth promotion and biological agents to control plant diseases are mainly focused on bacteria. In addition, a great portion of registered and commercialized biopesticides are bacterial-based products. Despite fungal endophytes having been identified as promising candidates for their use in biological control, it is of the utmost importance to develop and improve the existing knowledge on this research field. The genus Diaporthe, encompasses plant pathogens, saprobes and endophytes that have been screened for secondary metabolite, mainly due to their production of polyketides and a variety of unique bioactive metabolites with agronomic importance. Some of these metabolites exhibit antifungal and antibacterial activity for controlling plant pathogens, and phytotoxic activity for the development of potential mycoherbicides. Moreover, species of Diaporthe are reported as promising agents in the development of biofertilizers. For this reason, in this review we summarize the potential of Diaporthe species to produce natural products with application in agriculture and describe the benefits of these fungi to promote their host plant's growth.

Comparative Proteomic Analysis of Potato Roots from Resistant and Susceptible Cultivars to Spongospora subterranea Zoospore Root Attachment In Vitro

Potato (Solanum tuberosum L.) exhibits broad variations in cultivar resistance to tuber and root infections by the soilborne, obligate biotrophic pathogen Spongospora subterranea. Host resistance has been recognised as an important approach in potato disease management, whereas zoospore root attachment has been identified as an effective indicator for the host resistance to Spongospora root infection. However, the mechanism of host resistance to zoospore root attachment is currently not well understood. To identify the potential basis for host resistance to S. subterranea at the molecular level, twelve potato cultivars differing in host resistance to zoospore root attachment were used for comparative proteomic analysis. In total, 3723 proteins were quantified from root samples across the twelve cultivars using a data-independent acquisition mass spectrometry approach. Statistical analysis identified 454 proteins that were significantly more abundant in the resistant cultivars; 626 proteins were more abundant in the susceptible cultivars. In resistant cultivars, functional annotation of the proteomic data indicated that Gene Ontology terms related to the oxidative stress and metabolic processes were significantly over-represented. KEGG pathway analysis identified that the phenylpropanoid biosynthesis pathway was associated with the resistant cultivars, suggesting the potential role of lignin biosynthesis in the host resistance to S. subterranea. Several enzymes involved in pectin biosynthesis and remodelling, such as pectinesterase and pectin acetylesterase, were more abundant in the resistant cultivars. Further investigation of the potential role of root cell wall pectin revealed that the pectinase treatment of roots resulted in a significant reduction in zoospore root attachment in both resistant and susceptible cultivars. This study provides a comprehensive proteome-level overview of resistance to S. subterranea zoospore root attachment across twelve potato cultivars and has identified a potential role for cell wall pectin in regulating zoospore root attachment.

Large-Scale Protein and Phosphoprotein Profiling to Explore Potato Resistance Mechanisms to Spongospora subterranea Infection

Potato is one of the most important food crops for human consumption. The soilborne pathogen Spongospora subterranea infects potato roots and tubers, resulting in considerable economic losses from diminished tuber yields and quality. A comprehensive understanding of how potato plants respond to S. subterranea infection is essential for the development of pathogen-resistant crops. Here, we employed label-free proteomics and phosphoproteomics to quantify systemically expressed protein-level responses to S. subterranea root infection in potato foliage of the susceptible and resistant potato cultivars. A total of 2,669 proteins and 1,498 phosphoproteins were quantified in the leaf samples of the different treatment groups. Following statistical analysis of the proteomic data, we identified oxidoreductase activity, electron transfer, and photosynthesis as significant processes that differentially changed upon root infection specifically in the resistant cultivar and not in the susceptible cultivar. The phosphoproteomics results indicated increased activity of signal transduction and defense response functions in the resistant cultivar. In contrast, the majority of increased phosphoproteins in the susceptible cultivar were related to transporter activity and sub-cellular localization. This study provides new insight into the molecular mechanisms and systemic signals involved in potato resistance to S. subterranea infection and has identified new roles for protein phosphorylation in the regulation of potato immune response.