Interaction of Whitefly Effector G4 with Tomato Proteins Impacts Whitefly Performance.

The phloem-feeding insect Bemisia tabaci is an important pest, responsible for the transmission of several crop-threatening virus species. While feeding, the insect secretes a cocktail of effectors to modulate plant defense responses. Here, we present a set of proteins identified in an artificial diet on which B. tabaci was salivating. We subsequently studied whether these candidate effectors can play a role in plant immune suppression. Effector G4 was the most robust suppressor of an induced- reactive oxygen species (ROS) response in Nicotiana benthamiana. In addition, G4 was able to suppress ROS production in Solanum lycopersicum (tomato) and Capsicum annuum (pepper). G4 localized predominantly in the endoplasmic reticulum in N. benthamiana leaves and colocalized with two identified target proteins in tomato: REF-like stress related protein 1 (RSP1) and meloidogyne-induced giant cell protein DB141 (MIPDB141). Silencing of MIPDB141 in tomato reduced whitefly fecundity up to 40%, demonstrating that the protein is involved in susceptibility to B. tabaci. Together, our data demonstrate that effector G4 impairs tomato immunity to whiteflies by interfering with ROS production and via an interaction with tomato susceptibility protein MIPDB141. [Formula: see text] Copyright © 2024 The Author(s). This is an open access article distributed under the CC BY-NC-ND 4.0 International license.

Four layer multi-omics reveals molecular responses to aneuploidy in Leishmania.

Aneuploidy causes system-wide disruptions in the stochiometric balances of transcripts, proteins, and metabolites, often resulting in detrimental effects for the organism. The protozoan parasite Leishmania has an unusually high tolerance for aneuploidy, but the molecular and functional consequences for the pathogen remain poorly understood. Here, we addressed this question in vitro and present the first integrated analysis of the genome, transcriptome, proteome, and metabolome of highly aneuploid Leishmania donovani strains. Our analyses unambiguously establish that aneuploidy in Leishmania proportionally impacts the average transcript- and protein abundance levels of affected chromosomes, ultimately correlating with the degree of metabolic differences between closely related aneuploid strains. This proportionality was present in both proliferative and non-proliferative in vitro promastigotes. However, as in other Eukaryotes, we observed attenuation of dosage effects for protein complex subunits and in addition, non-cytoplasmic proteins. Differentially expressed transcripts and proteins between aneuploid Leishmania strains also originated from non-aneuploid chromosomes. At protein level, these were enriched for proteins involved in protein metabolism, such as chaperones and chaperonins, peptidases, and heat-shock proteins. In conclusion, our results further support the view that aneuploidy in Leishmania can be adaptive. Additionally, we believe that the high karyotype diversity in vitro and absence of classical transcriptional regulation make Leishmania an attractive model to study processes of protein homeostasis in the context of aneuploidy and beyond.

Chemical Mapping of the Degradation of Geranium Lake in Paint Cross Sections by MALDI-MSI.

Matrix assisted laser desorption ionization-mass spectrometry imaging (MALDI-MSI) has become a powerful method to extract spatially resolved chemical information in complex materials. This study provides the first use of MALDI-MSI to define spatial-temporal changes in oil paints. Due to the highly heterogeneous nature of oil paints, the sample preparation had to be optimized to prevent molecules from delocalizing. Here, we present a new protocol for the layer-specific analysis of oil paint cross sections achieving a lateral resolution of 10 µm and without losing ionization efficiency due to topographic effects. The efficacy of this method was investigated in oil paint samples containing a mixture of two historic organic pigments, geranium lake and lead white, a mixture often employed in the work of painter Vincent Van Gogh. This methodology not only allows for spatial visualization of the molecules responsible for the pink hue of the paint but also helps to elucidate the chemical changes behind the discoloration of paintings with this composition. The results demonstrate that this approach provides valuable molecular compositional information about the degradation pathways of pigments in specific paint layers and their interaction with the binding medium and other paint components and with light over time. Since a spatial correlation between molecular species and the visual pattern of the discoloration pattern can be made, we expect that mass spectrometry imaging will become highly relevant in future degradation studies of many more historical pigments and paints.

CEH-60/PBX regulates vitellogenesis and cuticle permeability through intestinal interaction with UNC-62/MEIS in Caenorhabditis elegans.

The onset of sexual maturity involves dramatic changes in physiology and gene expression in many animals. These include abundant yolk protein production in egg-laying species, an energetically costly process under extensive transcriptional control. Here, we used the model organism Caenorhabditis elegans to provide evidence for the spatiotemporally defined interaction of two evolutionarily conserved transcription factors, CEH-60/PBX and UNC-62/MEIS, acting as a gateway to yolk protein production. Via proteomics, bimolecular fluorescence complementation (BiFC), and biochemical and functional readouts, we show that this interaction occurs in the intestine of animals at the onset of sexual maturity and suffices to support the reproductive program. Our electron micrographs and functional assays provide evidence that intestinal PBX/MEIS cooperation drives another process that depends on lipid mobilization: the formation of an impermeable epicuticle. Without this lipid-rich protective layer, mutant animals are hypersensitive to exogenous oxidative stress and are poor partners for mating. Dedicated communication between the hypodermis and intestine in C. elegans likely supports these physiological outcomes, and we propose a fundamental role for the conserved PBX/MEIS interaction in multicellular signaling networks that rely on lipid homeostasis.

Improvement of biomolecular analysis in thin films using in situ matrix enhanced secondary ion mass spectrometry.

Sensitivity to molecular ions remains a limiting factor for high resolution imaging mass spectrometry of organic and biological materials. Here, we investigate a variant of matrix-enhanced secondary ion mass spectrometry in which the transfer of matrix molecules to the analyte sample is carried out in situ (in situ ME-SIMS). This approach is therefore compatible with both 2D and 3D imaging by SIMS. In this exploratory study, nanoscale matrix layers were sputter-transferred inside our time-of-flight (ToF)-SIMS to a series of thin films of biomolecules (proteins, sugars, lipids) adsorbed on silicon, and the resulting layers were analyzed and depth-profiled. For this purpose, matrix molecules were desorbed from a coated target (obtained by drop-casting or sublimation) using 10 keV Ar3000+ ion beam sputtering, followed by redeposition on a collector carrying the sample to be analyzed. After evaluating the quality of the transfer of six different matrices on bare Si collectors, α-cyano-4-hydroxycinnamic acid (CHCA) was selected for further experiments. The mass spectra and depth profiles obtained from the organic layer prior to and after the sputter-transfer of CHCA were compared, along with those obtained from regular ME-SIMS samples (dried droplets) and, finally, with MALDI data for the same matrix-analyte combinations. Signal amplification factors were calculated by dividing the integrated molecular intensities obtained with or without matrix transfer. While the amplification factors are between 0.5 and 2 for molecules already detected with high intensities in SIMS, such as cholesterol or human angiotensin, other compounds show very large integrated signal amplification, even above two orders of magnitude. This is the case for D-glucose and cardiolipin, for which the molecular ion intensity is low (or very low) under normal SIMS analysis conditions. For such low ionization probability compounds, the beneficial effect of the matrix is unquestionable. Test experiments on mouse brain tissue sections also indicate signal enhancement with the matrix, especially for high mass lipid ions.

The challenges of peptidomics in complementing proteomics in a clinical context.

Naturally occurring peptides, including growth factors, hormones, and neurotransmitters, represent an important class of biomolecules and have crucial roles in human physiology. The study of these peptides in clinical samples is therefore as relevant as ever. Compared to more routine proteomics applications in clinical research, peptidomics research questions are more challenging and have special requirements with regard to sample handling, experimental design, and bioinformatics. In this review, we describe the issues that confront peptidomics in a clinical context. After these hurdles are (partially) overcome, peptidomics will be ready for a successful translation into medical practice.

Starch biosynthesis contributes to the maintenance of photosynthesis and leaf growth under drought stress in maize.

To understand the growth response to drought, we performed a proteomics study in the leaf growth zone of maize (Zea mays L.) seedlings and functionally characterized the role of starch biosynthesis in the regulation of growth, photosynthesis and antioxidant capacity, using the shrunken-2 mutant (sh2), defective in ADP-glucose pyrophosphorylase. Drought altered the abundance of 284 proteins overrepresented for photosynthesis, amino acid, sugar and starch metabolism, and redox-regulation. Changes in protein levels correlated with enzyme activities (increased ATP synthase, cysteine synthase, starch synthase, RuBisCo, peroxiredoxin, glutaredoxin, thioredoxin and decreased triosephosphate isomerase, ferredoxin, cellulose synthase activities, respectively) and metabolite concentrations (increased ATP, cysteine, glycine, serine, starch, proline and decreased cellulose levels). The sh2 mutant showed a reduced increase of starch levels under drought conditions, leading to soluble sugar starvation at the end of the night and correlating with an inhibition of leaf growth rates. Increased RuBisCo activity and pigment concentrations observed in WT, in response to drought, were lacking in the mutant, which suffered more oxidative damage and recovered more slowly after re-watering. These results demonstrate that starch biosynthesis contributes to maintaining leaf growth under drought stress and facilitates enhanced carbon acquisition upon recovery.

Redox homeostasis in the growth zone of the rice leaf plays a key role in cold tolerance.

We analysed the cellular and molecular changes in the leaf growth zone of tolerant and sensitive rice varieties in response to suboptimal temperatures. Cold reduced the final leaf length by 35% and 51% in tolerant and sensitive varieties, respectively. Tolerant lines exhibited a smaller reduction of the leaf elongation rate and greater compensation by an increased duration of leaf growth. Kinematic analysis showed that cold reduced cell production in the meristem and the expansion rate in the elongation zone, but the latter was compensated for by a doubling of the duration of cell expansion. We performed iTRAQ proteome analysis on proliferating and expanding parts of the leaf growth zone. We identified 559 and 542 proteins, of which 163 and 210 were differentially expressed between zones, and 96 and 68 between treatments, in the tolerant and sensitive lines, respectively. The categories protein biosynthesis and redox homeostasis were significantly overrepresented in the up-regulated proteins. We therefore measured redox metabolites and enzyme activities in the leaf growth zone, demonstrating that tolerance of rice lines to suboptimal temperatures correlates with the ability to up-regulate enzymatic antioxidants in the meristem and non-enzymatic antioxidants in the elongation zone.

PRiSM: A prototype for exhaustive, restriction-free database searching for mass spectrometry-based identification.

RATIONALE: The current methods for identifying peptides in mass spectral product ion data still struggle to do so for the majority of spectra. Based on the experimental setup and other assumptions, such methods restrict the search space to speed up computations, but at the cost of creating blind spots. The proteomics community would greatly benefit from a method that is capable of covering the entire search space without using any restrictions, thus establishing a baseline for identification. METHODS: We conceived the "mass pattern paradigm" (MPP) that enables the creation of such an identification method, and we implemented it into a prototype database search engine "PRiSM" (PRotein-Spectrum Matching). We then assessed its operational characteristics by applying it to publicly available high-precision mass spectra of low and high identification difficulty. We used those characteristics to gain theoretical insights into trade-offs between sensitivity and speed when trying to establish a baseline for identification. RESULTS: Of 100 low difficulty spectra, PRiSM and SEQUEST agree on 84 identifications (of which 75 are statistically significant). Of 15 of 100 spectra not identified in a previous study (using SEQUEST), 13 are considered reliable after visual inspection and represent 3 proteins (out of 9 in total) not detected previously. CONCLUSIONS: Despite leaving noise intact, the simple PRiSM prototype can make statistically reliable identifications, while controlling the false discovery rate by fitting a null distribution. It also identifies some spectra previously unidentifiable in an "extremely open" SEQUEST search, paving the way to establishing a baseline for identification in proteomics.

FACS-Based Proteomics Enables Profiling of Proteins in Rare Cell Populations.

Understanding disease pathology often does not require an overall proteomic analysis of clinical samples but rather the analysis of different, often rare, subpopulations of cells in a heterogeneous mixture of cell types. For the isolation of pre-specified cellular subtypes, fluorescence activated cell sorting (FACS) is commonly used for its ability to isolate the required cell populations with high purity, even of scarce cell types. The proteomic analysis of a limited number of FACS-sorted cells, however, is very challenging as both sample preparation inefficiencies and limits in terms of instrument sensitivity are present. In this study, we used CD14+CD15+ immune cells sorted out of peripheral blood mononuclear cells isolated from whole blood to improve and evaluate FACS-based proteomics. To optimize both the protein extraction protocol and the mass spectrometry (MS) data acquisition method, PBMCs as well as commercialized HeLa digest were used. To reflect the limited number of sorted cells in some clinical samples, different numbers of sorted cells (1000, 5000, 10,000, or 50,000) were used. This allowed comparing protein profiles across samples with limited protein material and provided further insights in the benefits and limitations of using a very limited numbers of cells.

QCQuan: A Web Tool for the Automated Assessment of Protein Expression and Data Quality of Labeled Mass Spectrometry Experiments.

In the context of omics disciplines and especially proteomics and biomarker discovery, the analysis of a clinical sample using label-based tandem mass spectrometry (MS) can be affected by sample preparation effects or by the measurement process itself, resulting in an incorrect outcome. Detection and correction of these mistakes using state-of-the-art methods based on mixed models can use large amounts of (computing) time. MS-based proteomics laboratories are high-throughput and need to avoid a bottleneck in their quantitative pipeline by quickly discriminating between high- and low-quality data. To this end we developed an easy-to-use web-tool called QCQuan (available at qcquan.net ) which is built around the CONSTANd normalization algorithm. It automatically provides the user with exploratory and quality control information as well as a differential expression analysis based on conservative, simple statistics. In this document we describe in detail the scientifically relevant steps that constitute the workflow and assess its qualitative and quantitative performance on three reference data sets. We find that QCQuan provides clear and accurate indications about the scientific value of both a high- and a low-quality data set. Moreover, it performed quantitatively better on a third data set than a comparable workflow assembled using established, reliable software.

MIND: A Double-Linear Model To Accurately Determine Monoisotopic Precursor Mass in High-Resolution Top-Down Proteomics.

Top-down proteomics approaches are becoming ever more popular, due to the advantages offered by knowledge of the intact protein mass in correctly identifying the various proteoforms that potentially arise due to point mutation, alternative splicing, post-translational modifications, etc. Usually, the average mass is used in this context; however, it is known that this can fluctuate significantly due to both natural and technical causes. Ideally, one would prefer to use the monoisotopic precursor mass, but this falls below the detection limit for all but the smallest proteins. Methods that predict the monoisotopic mass based on the average mass are potentially affected by imprecisions associated with the average mass. To address this issue, we have developed a framework based on simple, linear models that allows prediction of the monoisotopic mass based on the exact mass of the most-abundant (aggregated) isotope peak, which is a robust measure of mass, insensitive to the aforementioned natural and technical causes. This linear model was tested experimentally, as well as in silico, and typically predicts monoisotopic masses with an accuracy of only a few parts per million. A confidence measure is associated with the predicted monoisotopic mass to handle the off-by-one-Da prediction error. Furthermore, we introduce a correction function to extract the "true" (i.e., theoretically) most-abundant isotope peak from a spectrum, even if the observed isotope distribution is distorted by noise or poor ion statistics. The method is available online as an R shiny app: https://valkenborg-lab.shinyapps.io/mind/.

Comprehensive Peptide Analysis of Mouse Brain Striatum Identifies Novel sORF-Encoded Polypeptides.

Bio-active peptides are involved in the regulation of most physiological processes in the body. Classical bio-active peptides (CBAPs) are cleaved from a larger precursor protein and stored in secretion vesicles from which they are released in the extracellular space. Recently, another non-classical type of bio-active peptides (NCBAPs) has gained interest. These typically are not secreted but instead appear to be translated from short open reading frames (sORF) and released directly into the cytoplasm. In contrast to CBAPs, these peptides are involved in the regulation of intra-cellular processes such as transcriptional control, calcium handling and DNA repair. However, bio-chemical evidence for the translation of sORFs remains elusive. Comprehensive analysis of sORF-encoded polypeptides (SEPs) is hampered by a number of methodological and biological challenges: the low molecular mass (many 4-10 kDa), the low abundance, transient expression and complications in data analysis. We developed a strategy to address a number of these issues. Our strategy is to exclude false positive identifications. In total sample, we identified 926 peptides originated from 37 known (neuro)peptide precursors in mouse striatum. In addition, four SEPs were identified including NoBody, a SEP that was previously discovered in humans and three novel SEPS from 5' untranslated transcript regions (UTRs).

A Gene Family Coding for Salivary Proteins (SHOT) of the Polyphagous Spider Mite Tetranychus urticae Exhibits Fast Host-Dependent Transcriptional Plasticity.

The salivary protein repertoire released by the herbivorous pest Tetranychus urticae is assumed to hold keys to its success on diverse crops. We report on a spider mite-specific protein family that is expanded in T. urticae. The encoding genes have an expression pattern restricted to the anterior podocephalic glands, while peptide fragments were found in the T. urticae secretome, supporting the salivary nature of these proteins. As peptide fragments were identified in a host-dependent manner, we designated this family as the SHOT (secreted host-responsive protein of Tetranychidae) family. The proteins were divided in three groups based on sequence similarity. Unlike TuSHOT3 genes, TuSHOT1 and TuSHOT2 genes were highly expressed when feeding on a subset of family Fabaceae, while expression was depleted on other hosts. TuSHOT1 and TuSHOT2 expression was induced within 24 h after certain host transfers, pointing toward transcriptional plasticity rather than selection as the cause. Transfer from an 'inducer' to a 'noninducer' plant was associated with slow yet strong downregulation of TuSHOT1 and TuSHOT2, occurring over generations rather than hours. This asymmetric on and off regulation points toward host-specific effects of SHOT proteins, which is further supported by the diversity of SHOT genes identified in Tetranychidae with a distinct host repertoire.

CONSTANd : A Normalization Method for Isobaric Labeled Spectra by Constrained Optimization.

In quantitative proteomics applications, the use of isobaric labels is a very popular concept as they allow for multiplexing, such that peptides from multiple biological samples are quantified simultaneously in one mass spectrometry experiment. Although this multiplexing allows that peptide intensities are affected by the same amount of instrument variability, systematic effects during sample preparation can also introduce a bias in the quantitation measurements. Therefore, normalization methods are required to remove this systematic error. At present, a few dedicated normalization methods for isobaric labeled data are at hand. Most of these normalization methods include a framework for statistical data analysis and rely on ANOVA or linear mixed models. However, for swift quality control of the samples or data visualization a simple normalization technique is sufficient. To this aim, we present a new and easy-to-use data-driven normalization method, named CONSTANd. The CONSTANd method employs constrained optimization and prior information about the labeling strategy to normalize the peptide intensities. Further, it allows maintaining the connection to any biological effect while reducing the systematic and technical errors. As a result, peptides can not only be compared directly within a multiplexed experiment, but are also comparable between other isobaric labeled datasets from multiple experimental designs that are normalized by the CONSTANd method, without the need to include a reference sample in every experimental setup. The latter property is especially useful when more than six, eight or ten (TMT/iTRAQ) biological samples are required to detect differential peptides with sufficient statistical power and to optimally make use of the multiplexing capacity of isobaric labels.

The Salivary Protein Repertoire of the Polyphagous Spider Mite Tetranychus urticae: A Quest for Effectors.

The two-spotted spider mite Tetranychus urticae is an extremely polyphagous crop pest. Alongside an unparalleled detoxification potential for plant secondary metabolites, it has recently been shown that spider mites can attenuate or even suppress plant defenses. Salivary constituents, notably effectors, have been proposed to play an important role in manipulating plant defenses and might determine the outcome of plant-mite interactions. Here, the proteomic composition of saliva from T. urticae lines adapted to various host plants-bean, maize, soy, and tomato-was analyzed using a custom-developed feeding assay coupled with nano-LC tandem mass spectrometry. About 90 putative T. urticae salivary proteins were identified. Many are of unknown function, and in numerous cases belonging to multimembered gene families. RNAseq expression analysis revealed that many genes coding for these salivary proteins were highly expressed in the proterosoma, the mite body region that includes the salivary glands. A subset of genes encoding putative salivary proteins was selected for whole-mount in situ hybridization, and were found to be expressed in the anterior and dorsal podocephalic glands. Strikingly, host plant dependent expression was evident for putative salivary proteins, and was further studied in detail by micro-array based genome-wide expression profiling. This meta-analysis revealed for the first time the salivary protein repertoire of a phytophagous chelicerate. The availability of this salivary proteome will assist in unraveling the molecular interface between phytophagous mites and their host plants, and may ultimately facilitate the development of mite-resistant crops. Furthermore, the technique used in this study is a time- and resource-efficient method to examine the salivary protein composition of other small arthropods for which saliva or salivary glands cannot be isolated easily.

MS imaging and mass spectrometric synaptosome profiling identify PEP-19/pcp4 as a synaptic molecule involved in spatial learning in mice.

The Morris water maze (MWM) spatial learning task has been demonstrated to involve a cognitive switch of action control to serve the transition from an early towards a late learning phase. However, the molecular mechanisms governing this switch are largely unknown. We employed MALDI MS imaging (MSI) to screen for changes in expression of small proteins in brain structures implicated in the different learning phases. We compared mice trained for 3days and 30days in the MWM, reflecting an early and a late learning phase in relation to the acquisition of a spatial learning task. An ion with m/z of 6724, identified as PEP-19/pcp4 by top-down tandem MS, was detected at higher intensity in the dorsal striatum of the late learning phase group compared with the early learning phase group. In addition, mass spectrometric analysis of synaptosomes confirmed the presence of PEP-19/pcp4 at the synapse. PEP-19/pcp4 has previously been identified as a critical determinant of synaptic plasticity in locomotor learning. Our findings extend PEP-19/pcp4 function to spatial learning in the forebrain and put MSI forward as a valid and unbiased research strategy for the discovery and identification of the molecular machinery involved in learning, memory and synaptic plasticity. This article is part of a Special Issue entitled: MALDI Imaging, edited by Dr. Corinna Henkel and Prof. Peter Hoffmann.

The use of elemental mass spectrometry in phosphoproteomic applications.

Reversible phosphorylation is one of the most important post-translational modifications in mammalian cells. Because this molecular switch is an important mechanism that diversifies and regulates proteins in cellular processes, knowledge about the extent and quantity of phosphorylation is very important to understand the complex cellular interplay. Although phosphoproteomics strategies are applied worldwide, they mainly include only molecular mass spectrometry (like MALDI or ESI)-based experiments. Although identification and relative quantification of phosphopeptides is straightforward with these techniques, absolute quantification is more complex and usually requires for specific isotopically phosphopeptide standards. However, the use of elemental mass spectrometry, and in particular inductively coupled plasma mass spectrometry (ICP-MS), in phosphoproteomics-based experiments, allow one to absolutely quantify phosphopeptides. Here, these phosphoproteomic applications with ICP-MS as elemental detector are reviewed. Pioneering work and recent developments in the field are both described. Additionally, the advantage of the parallel use of molecular and elemental mass spectrometry is stressed.

Fast and Reliable Quantitative Peptidomics with labelpepmatch.

The use of stable isotope tags in quantitative peptidomics offers many advantages, but the laborious identification of matching sets of labeled peptide peaks is still a major bottleneck. Here we present labelpepmatch, an R-package for fast and straightforward analysis of LC-MS spectra of labeled peptides. This open-source tool offers fast and accurate identification of peak pairs alongside an appropriate framework for statistical inference on quantitative peptidomics data, based on techniques from other -omics disciplines. A relevant case study on the desert locust Schistocerca gregaria proves our pipeline to be a reliable tool for quick but thorough explorative analyses.

Designing biomedical proteomics experiments: state-of-the-art and future perspectives.

With the current expanded technical capabilities to perform mass spectrometry-based biomedical proteomics experiments, an improved focus on the design of experiments is crucial. As it is clear that ignoring the importance of a good design leads to an unprecedented rate of false discoveries which would poison our results, more and more tools are developed to help researchers designing proteomic experiments. In this review, we apply statistical thinking to go through the entire proteomics workflow for biomarker discovery and validation and relate the considerations that should be made at the level of hypothesis building, technology selection, experimental design and the optimization of the experimental parameters.