Examination of Endogenous Peptides in Medicago truncatula Using Mass Spectrometry Imaging

Revisiting the Role of Sensors for Shaping Plant Research: Applications and Future Perspectives

Plant health monitoring is essential for understanding the impact of environmental stressors (biotic and abiotic) on crop production, and for tailoring plant developmental and adaptive responses accordingly. Plants are constantly exposed to different stressors like pathogens and soil pollutants (heavy metals and pesticides) which pose a serious threat to their survival and to human health. Plants have the ability to respond to environmental stressors by undergoing rapid transcriptional, translational, and metabolic reprogramming at different cellular compartments in order to balance growth and adaptive responses. However, plants' exceptional responsiveness to environmental cues is highly complex, which is driven by diverse signaling molecules such as calcium Ca2+, reactive oxygen species (ROS), hormones, small peptides and metabolites. Additionally, other factors like pH also influence these responses. The regulation and occurrence of these plant signaling molecules are often undetectable, necessitating nondestructive, live research approaches to understand their molecular complexity and functional traits during growth and stress conditions. With the advent of sensors, in vivo and in vitro understanding of some of these processes associated with plant physiology, signaling, metabolism, and development has provided a novel platform not only for decoding the biochemical complexity of signaling pathways but also for targeted engineering to improve diverse plant traits. The application of sensors in detecting pathogens and soil pollutants like heavy metal and pesticides plays a key role in protecting plant and human health. In this review, we provide an update on sensors used in plant biology for the detection of diverse signaling molecules and their functional attributes. We also discuss different types of sensors (biosensors and nanosensors) used in agriculture for detecting pesticides, pathogens and pollutants.

Origins, Technological Advancement, and Applications of Peptidomics

Peptidomics is the comprehensive characterization of peptides from biological sources instead of heading for a few single peptides in former peptide research. Mass spectrometry allows to detect a multitude of peptides in complex mixtures and thus enables new strategies leading to peptidomics. The term was established in the year 2001, and up to now, this new field has grown to over 3000 publications. Analytical techniques originally developed for fast and comprehensive analysis of peptides in proteomics were specifically adjusted for peptidomics. Although it is thus closely linked to proteomics, there are fundamental differences with conventional bottom-up proteomics. Fundamental technological advancements of peptidomics since have occurred in mass spectrometry and data processing, including quantification, and more slightly in separation technology. Different strategies and diverse sources of peptidomes are mentioned by numerous applications, such as discovery of neuropeptides and other bioactive peptides, including the use of biochemical assays. Furthermore, food and plant peptidomics are introduced similarly. Additionally, applications with a clinical focus are included, comprising biomarker discovery as well as immunopeptidomics. This overview extensively reviews recent methods, strategies, and applications including links to all other chapters of this book.

MALDI MS Imaging of Chickpea Seeds (Cicer arietinum) and Crab's Eye Vine (Abrus precatorius) after Tryptic Digestion Allows Spatially Resolved Identification of Plant Proteins

Matrix-assisted laser desorption/ionization mass spectrometry (MALDI MS) imaging following in situ enzymatic digestion is a versatile analytical method for the untargeted investigation of protein distributions, which has rarely been used for plants so far. The present study describes a workflow for in situ tryptic digestion of plant seed tissue for MALDI MS imaging. Substantial modifications to the sample preparation procedure for mammalian tissues were necessary to cater to the specific properties of plant materials. For the first time, distributions of tryptic peptides were successfully visualized in plant tissue using MS imaging with accurate mass detection. Sixteen proteins were visualized and identified in chickpea seeds showing different distribution patterns, e.g., in the cotyledons, radicle, or testa. All tryptic peptides were detected with a mass resolution higher than 60,000 as well as a mass accuracy better than 1.5 ppm root-mean-square error and were matched to results from complementary liquid chromatography-MS/MS (LC-MS/MS) data. The developed method was also applied to crab's eye vine seeds for targeted MS imaging of the toxic protein abrin, showing the presence of abrin-a in all compartments. Abrin (59 kDa), as well as the majority of proteins visualized in chickpeas, was larger than 50 kDa and would thus not be readily accessible by top-down MS imaging. Since antibodies for plant proteins are often not readily available, in situ digestion MS imaging provides unique information, as it makes the distribution and identification of larger proteins in plant tissues accessible in an untargeted manner. This opens up new possibilities in the field of plant science as well as to assess the nutritional quality and/or safety of crops.

Peptidomics Methods Applied to the Study of Flower Development

Understanding the global and dynamic nature of plant developmental processes requires not only the study of the transcriptome, but also of the proteome, including its largely uncharacterized peptidome fraction. Recent advances in proteomics and high-throughput analyses of translating RNAs (ribosome profiling) have begun to address this issue, evidencing the existence of novel, uncharacterized, and possibly functional peptides. To validate the accumulation in tissues of sORF-encoded polypeptides (SEPs), the basic setup of proteomic analyses (i.e., LC-MS/MS) can be followed. However, the detection of peptides that are small (up to ~100 aa, 6-7 kDa) and novel (i.e., not annotated in reference databases) presents specific challenges that need to be addressed both experimentally and with computational biology resources. Several methods have been developed in recent years to isolate and identify peptides from plant tissues. In this chapter, we outline two different peptide extraction protocols and the subsequent peptide identification by mass spectrometry using the database search or the de novo identification methods.

Key defatting tissue pretreatment protocol for enhanced MALDI MS Imaging of peptide biomarkers visualization in the castor beans and their attribution applications

INTRODUCTION

Castor bean or ricin-induced intoxication or terror events have threatened public security and social safety. Potential resources or materials include beans, raw extraction products, crude toxins, and purified ricin. The traceability of the origins of castor beans is thus essential for forensic and anti-terror investigations. As a new imaging technique with label-free, rapid, and high throughput features, matrix-assisted laser desorption ionization mass spectrometry imaging (MALDI-MSI) has been gradually stressed in plant research. However, sample preparation approaches for plant tissues still face severe challenges, especially for some lipid-rich, water-rich, or fragile tissues. Proper tissue washing procedures would be pivotal, but little information is known until now.

METHODS

For castor beans containing plenty of lipids that were fragile when handled, we developed a comprehensive tissue pretreatment protocol. Eight washing procedures aimed at removing lipids were discussed in detail. We then constructed a robust MALDI-MSI method to enhance the detection sensitivity of RCBs in castor beans.

RESULTS AND DISCUSSION

A modified six-step washing procedure was chosen as the most critical parameter regarding the MSI visualization of peptides. The method was further applied to visualize and quantify the defense peptides, Ricinus communis biomarkers (RCBs) in castor bean tissue sections from nine different geographic sources from China, Pakistan, and Ethiopia. Multivariate statistical models, including deep learning network, revealed a valuable classification clue concerning nationality and altitude.

Recent advances in proteomics and metabolomics in plants

Over the past decade, systems biology and plant-omics have increasingly become the main stream in plant biology research. New developments in mass spectrometry and bioinformatics tools, and methodological schema to integrate multi-omics data have leveraged recent advances in proteomics and metabolomics. These progresses are driving a rapid evolution in the field of plant research, greatly facilitating our understanding of the mechanistic aspects of plant metabolisms and the interactions of plants with their external environment. Here, we review the recent progresses in MS-based proteomics and metabolomics tools and workflows with a special focus on their applications to plant biology research using several case studies related to mechanistic understanding of stress response, gene/protein function characterization, metabolic and signaling pathways exploration, and natural product discovery. We also present a projection concerning future perspectives in MS-based proteomics and metabolomics development including their applications to and challenges for system biology. This review is intended to provide readers with an overview of how advanced MS technology, and integrated application of proteomics and metabolomics can be used to advance plant system biology research.

LA-ICP-MS and MALDI-MS image registration for correlating nanomaterial biodistributions and their biochemical effects

Laser ablation inductively-coupled plasma mass spectrometry (LA-ICP-MS) imaging and matrix assisted laser desorption ionization mass spectrometry imaging (MALDI-MSI) are complementary methods that measure distributions of elements and biomolecules in tissue sections. Quantitative correlations of the information provided by these two imaging modalities requires that the datasets be registered in the same coordinate system, allowing for pixel-by-pixel comparisons. We describe here a computational workflow written in Python that accomplishes this registration, even for adjacent tissue sections, with accuracies within ±50 μm. The value of this registration process is demonstrated by correlating images of tissue sections from mice injected with gold nanomaterial drug delivery systems. Quantitative correlations of the nanomaterial delivery vehicle, as detected by LA-ICP-MS imaging, with biochemical changes, as detected by MALDI-MSI, provide deeper insight into how nanomaterial delivery systems influence lipid biochemistry in tissues. Moreover, the registration process allows the more precise images associated with LA-ICP-MS imaging to be leveraged to achieve improved segmentation in MALDI-MS images, resulting in the identification of lipids that are most associated with different sub-organ regions in tissues.

Unravel the Local Complexity of Biological Environments by MALDI Mass Spectrometry Imaging

Classic metabolomic methods have proven to be very useful to study functional biology and variation in the chemical composition of different tissues. However, they do not provide any information in terms of spatial localization within fine structures. Matrix-assisted laser desorption ionization mass spectrometry imaging (MALDI MSI) does and reaches at best a spatial resolution of 0.25 μm depending on the laser setup, making it a very powerful tool to analyze the local complexity of biological samples at the cellular level. Here, we intend to give an overview of the diversity of the molecules and localizations analyzed using this method as well as to update on the latest adaptations made to circumvent the complexity of samples. MALDI MSI has been widely used in medical sciences and is now developing in research areas as diverse as entomology, microbiology, plant biology, and plant–microbe interactions, the rhizobia symbiosis being the most exhaustively described so far. Those are the fields of interest on which we will focus to demonstrate MALDI MSI strengths in characterizing the spatial distributions of metabolites, lipids, and peptides in relation to biological questions.

In Situ Localization of Plant Lipid Metabolites by Matrix-Assisted Laser Desorption/Ionization Mass Spectrometry Imaging (MALDI-MSI)

Matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI) has emerged as a major analytical platform for the determination and localization of lipid metabolites directly from tissue sections. Unlike analysis of lipid extracts, where lipid localizations are lost due to homogenization and/ or solvent extraction, MALDI-MSI analysis is capable of revealing spatial localization of metabolites while simultaneously collecting high chemical resolution mass spectra. Important considerations for obtaining high quality MALDI-MS images include tissue preservation, section preparation, MS data collection and data processing. Errors in any of these steps can lead to poor quality metabolite images and increases the chance for metabolite misidentification and/ or incorrect localization. Here, we present detailed methods and recommendations for specimen preparation, MALDI-MS instrument parameters, software analysis platforms for data processing, and practical considerations for each of these steps to ensure acquisition of high-quality chemical and spatial resolution data for reconstructing MALDI-MS images of plant tissues.

Sensors for the quantification, localization and analysis of the dynamics of plant hormones

Plant hormones play important roles in plant growth and development and physiology, and in acclimation to environmental changes. The hormone signaling networks are highly complex and interconnected. It is thus important to not only know where the hormones are produced, how they are transported and how and where they are perceived, but also to monitor their distribution quantitatively, ideally in a non-invasive manner. Here we summarize the diverse set of tools available for quantifying and visualizing hormone distribution and dynamics. We provide an overview over the tools that are currently available, including transcriptional reporters, degradation sensors, and luciferase and fluorescent sensors, and compare the tools and their suitability for different purposes.

Profiling Analysis Reveals the Crucial Role of the Endogenous Peptides in Bladder Cancer Progression

Background

Peptide drugs provide promising regimes in bladder cancer. In order to identify potential bioactive peptides involved in bladder cancer, we performed the present study.

Methods

Liquid chromatography/mass spectrometry assay was used to compare the endogenous peptides between bladder cancer and normal control. The potential biological functions of these dysregulated peptides are assessed by GO analysis and KEGG pathway analysis of their precursors. The SMART and UniProt databases are used to identify the sequences of the dysregulated peptides located in the functional domains. The Open Targets Platform database was used to investigate the precursors related to metabolic diseases.

Results

A total of 9 up-regulated peptides and 110 down-regulated peptides in bladder cancer compared with normal control were identified (fold change > 1.2, P < 0.05). The MW of these dysregulated peptides ranged from 500 Da to 2500 Da and the MW of all identified peptides was below 3500 Da. The GO and KEGG pathway analysis indicated that these dysregulated peptides could play an important role in bladder cancer. Our further analysis revealed that ⁴⁵HFNPRFNAHGDAN ⁵⁷ derived from LGALS1 and those peptides derived from P4HB and SERPINA1 might be the promising diagnostic biomarkers and therapeutic targets of bladder cancer.

Conclusion

In the present study, we have identified the profile of the peptides significantly dysregulated in bladder cancer. Moreover, using bioinformatic analysis, we found the peptides derived from LGALS1, P4HB and SERPINA1 could be the promising diagnostic biomarkers and therapeutic targets of bladder cancer.

MALDI Mass Spectrometry Imaging of Peptides in Medicago truncatula Root Nodules

Mass spectrometry imaging is routinely used to visualize the distributions of biomolecules in tissue sections. In plants, mass spectrometry imaging of metabolites is more often conducted, but the imaging of larger molecules is less frequently performed despite the importance of proteins and endogenous peptides to the plant. Here, we describe a matrix-assisted laser desorption/ionization mass spectrometry imaging method for the imaging of peptides in Medicago truncatula root nodules. Sample preparation steps including embedding in gelatin, sectioning, and matrix application are described. The method described is employed to determine the spatial distribution of hundreds of peptide peaks.

Imaging Mass Spectrometry of Endogenous Polypeptides and Secondary Metabolites from Galls Induced by Root-Knot Nematodes in Tomato Roots

Nematodes are devastating pests that infect most cultivated plant species and cause considerable agricultural losses worldwide. The understanding of metabolic adjustments induced during plant-nematode interaction is crucial to generate resistant plants or to select more efficient molecules to fight against this pest. Matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI) has been used herein for in situ detection and mapping endogenous polypeptides and secondary metabolites from nematode-induced gall tissue. One of the major critical features of this technique is sample preparation; mainly, the generation of intact sections of plant cells with their rigid cell walls and vacuolated cytoplasm. Our experimental settings allowed us to obtain sections without contamination of exogenous ions or diffusion of molecules and to map the differential presence of low and high molecular weight ions in uninfected roots compared with nematode-induced galls. We predict the presence of lipids in both uninfected roots and galls, which was validated by MALDI time-of-flight tandem mass spectrometry and high-resolution mass spectrometry analysis of lipid extracts. Based on the isotopic ion distribution profile, both esters and glycerophospholipids were predicted compounds and may be playing an important role in gall development. Our results indicate that the MALDI-MSI technology is a promising tool to identify secondary metabolites as well as peptides and proteins in complex plant tissues like galls to decipher molecular processes responsible for infection and maintenance of these feeding sites during nematode parasitism.

Digestion-Free Analysis of Peptides from 30-year-old Formalin-Fixed, Paraffin-Embedded Tissue by Mass Spectrometry Imaging

Formalin-fixed neuroendocrine tissues from American cockroaches ( Periplaneta americana) embedded in paraffin more than 30 years ago were recently analyzed by matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI), to reveal the histological localization of more than 20 peptide ions. These represented protonated, and other cationic species of, at least, 14 known neuropeptides. The characterization of peptides in such historical samples was made possible by a novel sample preparation protocol rendering the endogenous peptides readily amenable to MSI analysis. The protocol comprises brief deparaffinization steps involving xylene and ethanol, and is further devoid of conventional aqueous washing, buffer incubations, or antigen retrieval steps. Endogenous secretory peptides that are typically highly soluble are therefore retained in-tissue with this protocol. The method is fully "top-down", that is, without laborious in situ enzymatic digestion that typically disturbs the detection of low-abundance endogenous peptides by MSI. Peptide identifications were supported by accurate mass, on-tissue tandem MS analyses, and by earlier MALDI-MSI results reported for freshly prepared P. americana samples. In contrast to earlier literature accounts stating that MALDI-MSI detection of endogenous peptides is possible only in fresh or freshly frozen tissues, or exceptionally, in formalin-fixed, paraffin-embedded (FFPE) material of less than 1 year old, we demonstrate that MALDI-MSI works for endogenous peptides in FFPE tissue of up to 30 years old. Our findings put forward a useful method for digestion-free, high-throughput analysis of endogenous peptides from FFPE samples and offer the potential for reinvestigating archived and historically interesting FFPE material, such as those stored in hospital biobanks.

Recent advances in matrix-assisted laser desorption/ionisation mass spectrometry imaging (MALDI-MSI) for in situ analysis of endogenous molecules in plants

INTRODUCTION

Mass spectrometry imaging (MSI) as a label-free and powerful imaging technique enables in situ evaluation of a tissue metabolome and/or proteome, becoming increasingly popular in the detection of plant endogenous molecules.

OBJECTIVE

The characterisation of structure and spatial information of endogenous molecules in plants are both very important aspects to better understand the physiological mechanism of plant organism.

METHODS

Matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI) is a commonly-used tissue imaging technique, which requires matrix to assist in situ detection of a variety of molecules on the surface of a tissue section. In previous studies, MALDI-MSI was mostly used for the detection of molecules from animal tissue sections, compared to plant samples due to cell structural limitations, such as plant cuticles, epicuticular waxes, and cell walls. Despite the enormous progress that has been made in tissue imaging, there is still a challenge for MALDI-MSI suitable for the imaging of endogenous compounds in plants.

RESULTS

This review summarises the recent advances in MALDI-MSI, focusing on the application of in situ detection of endogenous molecules in different plant organs, i.e. root, stem, leaf, flower, fruit, and seed.

CONCLUSION

Further improvements on instrumentation sensitivity, matrix selection, image processing and sample preparation will expand the application of MALDI-MSI in plant research.

Spatial analysis of lipid metabolites and expressed genes reveals tissue-specific heterogeneity of lipid metabolism in high- and low-oil Brassica napus L. seeds

Despite the importance of oilseeds to worldwide human nutrition, and more recently to the production of bio-based diesel fuels, the detailed mechanisms regulating seed oil biosynthesis remain only partly understood, especially from a tissue-specific perspective. Here, we investigated the spatial distributions of lipid metabolites and transcripts involved in oil biosynthesis from seeds of two low-erucic acid genotypes of Brassica napus with high and low seed-oil content. Integrated results from matrix-assisted laser desorption/ionization-mass spectrometry imaging (MALDI-MSI) of lipids in situ, lipidome profiling of extracts from seed tissues, and tissue-specific transcriptome analysis revealed complex spatial distribution patterns of lipids and transcripts. In general, it appeared that many triacylglycerol and phosphatidylcholine species distributed heterogeneously throughout the embryos. Tissue-specific transcriptome analysis identified key genes involved in de novo fatty acid biosynthesis in plastid, triacylglycerols assembly and lipid droplet packaging in the endoplasmic reticulum (ER) that may contribute to the high or low oil phenotype and heterogeneity of lipid distribution. Our results imply that transcriptional regulation represents an important means of impacting lipid compartmentalization in oil seeds. While much information remains to be learned about the intricacies of seed oil accumulation and distribution, these studies highlight the advances that come from evaluating lipid metabolism within a spatial context and with multiple omics level datasets.

Comparative peptidomic profile between human hypertrophic scar tissue and matched normal skin for identification of endogenous peptides involved in scar pathology

Endogenous peptides recently attract increasing attention for their participation in various biological processes. Their roles in the pathogenesis of human hypertrophic scar remains poorly understood. In this study, we used liquid chromatography-tandem mass spectrometry to construct a comparative peptidomic profiling between human hypertrophic scar tissue and matched normal skin. A total of 179 peptides were significantly differentially expressed in human hypertrophic scar tissue, with 95 upregulated and 84 downregulated peptides between hypertrophic scar tissue and matched normal skin. Further bioinformatics analysis (Gene ontology and Kyoto Encyclopedia of Genes and Genomes pathway analysis) indicated that precursor proteins of these differentially expressed peptides correlate with cellular process, biological regulation, cell part, binding and structural molecule activity ribosome, and PPAR signaling pathway occurring during pathological changes of hypertrophic scar. Based on prediction database, we found that 78 differentially expressed peptides shared homology with antimicrobial peptides and five matched known immunomodulatory peptides. In conclusion, our results show significantly altered expression profiles of peptides in human hypertrophic scar tissue. These peptides may participate in the etiology of hypertrophic scar and provide beneficial scheme for scar evaluation and treatments.

Origins, Technological Development, and Applications of Peptidomics

Peptidomics is the comprehensive characterization of peptides from biological sources mainly by HPLC and mass spectrometry. Mass spectrometry allows the detection of a multitude of single peptides in complex mixtures. The term first appeared in full papers in the year 2001, after over 100 years of peptide research with a main focus on one or a few specific peptides. Within the last 15 years, this new field has grown to over 1200 publications. Mass spectrometry techniques, in combination with other analytical methods, were developed for the fast and comprehensive analysis of peptides in proteomics and specifically adjusted to implement peptidomics technologies. Although peptidomics is closely linked to proteomics, there are fundamental differences with conventional bottom-up proteomics. The development of peptidomics is described, including the most important implementations for its technological basis. Different strategies are covered which are applied to several important applications, such as neuropeptidomics and discovery of bioactive peptides or biomarkers. This overview includes links to all other chapters in the book as well as recent developments of separation, mass spectrometric, and data processing technologies. Additionally, some new applications in food and plant peptidomics as well as immunopeptidomics are introduced.

MSiReader v1.0: Evolving Open-Source Mass Spectrometry Imaging Software for Targeted and Untargeted Analyses

A major update to the mass spectrometry imaging (MSI) software MSiReader is presented, offering a multitude of newly added features critical to MSI analyses. MSiReader is a free, open-source, and vendor-neutral software written in the MATLAB platform and is capable of analyzing most common MSI data formats. A standalone version of the software, which does not require a MATLAB license, is also distributed. The newly incorporated data analysis features expand the utility of MSiReader beyond simple visualization of molecular distributions. The MSiQuantification tool allows researchers to calculate absolute concentrations from quantification MSI experiments exclusively through MSiReader software, significantly reducing data analysis time. An image overlay feature allows the incorporation of complementary imaging modalities to be displayed with the MSI data. A polarity filter has also been incorporated into the data loading step, allowing the facile analysis of polarity switching experiments without the need for data parsing prior to loading the data file into MSiReader. A quality assurance feature to generate a mass measurement accuracy (MMA) heatmap for an analyte of interest has also been added to allow for the investigation of MMA across the imaging experiment. Most importantly, as new features have been added performance has not degraded, in fact it has been dramatically improved. These new tools and the improvements to the performance in MSiReader v1.0 enable the MSI community to evaluate their data in greater depth and in less time. Graphical Abstract ᅟ.

A Proteomic View on the Role of Legume Symbiotic Interactions

Legume plants are key elements in sustainable agriculture and represent a significant source of plant-based protein for humans and animal feed worldwide. One specific feature of the family is the ability to establish nitrogen-fixing symbiosis with Rhizobium bacteria. Additionally, like most vascular flowering plants, legumes are able to form a mutualistic endosymbiosis with arbuscular mycorrhizal (AM) fungi. These beneficial associations can enhance the plant resistance to biotic and abiotic stresses. Understanding how symbiotic interactions influence and increase plant stress tolerance are relevant questions toward maintaining crop yield and food safety in the scope of climate change. Proteomics offers numerous tools for the identification of proteins involved in such responses, allowing the study of sub-cellular localization and turnover regulation, as well as the discovery of post-translational modifications (PTMs). The current work reviews the progress made during the last decades in the field of proteomics applied to the study of the legume-Rhizobium and -AM symbioses, and highlights their influence on the plant responses to pathogens and abiotic stresses. We further discuss future perspectives and new experimental approaches that are likely to have a significant impact on the field including peptidomics, mass spectrometric imaging, and quantitative proteomics.