Identification and Targeted Quantification of Endogenous Neuropeptides in the Nematode Caenorhabditis elegans Using Mass Spectrometry.

The nematode Caenorhabditis elegans lends itself as an excellent model organism for peptidomics studies. Its ease of cultivation and quick generation time make it suitable for high-throughput studies. The nervous system, with its 302 neurons, is probably the best-known and studied endocrine tissue. Moreover, its neuropeptidergic signaling pathways display numerous similarities with those observed in other metazoans. Here, we describe two label-free approaches for neuropeptidomics in C. elegans: one for discovery purposes, and another for targeted quantification and comparisons of neuropeptide levels between different samples. Starting from a detailed peptide extraction procedure, we here outline the liquid chromatography tandem mass spectrometry (LC-MS/MS) setup and describe subsequent data analysis approaches.

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.

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.

How the Oviduct Lipidomic Profile Changes over Time after the Start of an Obesogenic Diet in an Outbred Mouse Model.

We investigated whether a high-fat/high-sugar (HF/HS) diet alters the lipidomic profile of the oviductal epithelium (OE) and studied the patterns of these changes over time. Female outbred Swiss mice were fed either a control (10% fat) or HF/HS (60% fat, 20% fructose) diet. Mice (n = 3 per treatment per time point) were sacrificed and oviducts were collected at 3 days and 1, 4, 8, 12 and 16 weeks on the diet. Lipids in the OE were imaged using matrix-assisted laser desorption ionisation mass spectrometry imaging. Discriminative m/z values and differentially regulated lipids were determined in the HF/HS versus control OEs at each time point. Feeding the obesogenic diet resulted in acute changes in the lipid profile in the OE already after 3 days, and thus even before the development of an obese phenotype. The changes in the lipid profile of the OE progressively increased and became more persistent after long-term HF/HS diet feeding. Functional annotation revealed a differential abundance of phospholipids, sphingomyelins and lysophospholipids in particular. These alterations appear to be not only caused by the direct accumulation of the excess circulating dietary fat but also a reduction in the de novo synthesis of several lipid classes, due to oxidative stress and endoplasmic reticulum dysfunction. The described diet-induced lipidomic changes suggest alterations in the OE functions and the oviductal microenvironment which may impact crucial reproductive events that take place in the oviduct, such as fertilization and early embryo development.

A short dasatinib and quercetin treatment is sufficient to reinstate potent adult neuroregenesis in the aged killifish.

The young African turquoise killifish has a high regenerative capacity, but loses it with advancing age, adopting several aspects of the limited form of mammalian regeneration. We deployed a proteomic strategy to identify pathways that underpin the loss of regenerative power caused by aging. Cellular senescence stood out as a potential brake on successful neurorepair. We applied the senolytic cocktail Dasatinib and Quercetin (D + Q) to test clearance of chronic senescent cells from the aged killifish central nervous system (CNS) as well as rebooting the neurogenic output. Our results show that the entire aged killifish telencephalon holds a very high senescent cell burden, including the parenchyma and the neurogenic niches, which could be diminished by a short-term, late-onset D + Q treatment. Reactive proliferation of non-glial progenitors increased substantially and lead to restorative neurogenesis after traumatic brain injury. Our results provide a cellular mechanism for age-related regeneration resilience and a proof-of-concept of a potential therapy to revive the neurogenic potential in an already aged or diseased CNS.

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.

Immunoinformatics Design and Assessment of a Multiepitope Antigen (OvMCBL02) for Onchocerciasis Diagnosis and Monitoring.

Onchocerciasis is a Neglected Tropical Disease that has a significant socioeconomic impact, especially in Sub-Saharan Africa. Numerous reports indicate that the Expanded Special Project for the Elimination of Neglected Tropical Diseases needs novel diagnostic tools before achieving its goal of successful elimination of onchocerciasis in Africa. The current diagnostic tests are either invasive, insensitive, or not applicable in the field and about 25% of persons infected cannot mount immune responses against the single antigen used in the only approved Ov-16 serological test. In the quest to identify novel biomarkers that can be used to certify that a patient is free from the disease, evaluate the progress of elimination programmes, and conduct post elimination surveillances, mass spectrometric analysis of Onchocerca volvulus crude extract revealed that 1392 proteins are expressed in the adult and microfilariae stages of the parasite. Computational analysis predicted six of the proteins as O. volvulus potential diagnostic targets. Linear B-epitopes were predicted from the six proteins and used to construct a multiepitope antigen (OvMCBL02). Serological analysis revealed that the OvMCBL02 test significantly differentiated between serum samples of onchocerciasis patients from the Kombone Health Area in the South West Region of Cameroon (n = 63) and control serum samples from Rwanda (n = 29) and Europe (n = 26) as well as between serum samples from the onchocerciasis hyperendemic region of Kombone Health Area (n = 63) and the hypoendemic region of Bandjoun Health District (n = 54). Interestingly, the test did not cross-react with serum samples from patients suffering from related nematode infections, thereby suggesting that further characterization of the OvMCBL02 multiepitope antigen will render it an additional member of the diagnostic toolbox for the elimination of onchocerciasis.

Identification of Potential Urinary Metabolite Biomarkers of Pseudomonas aeruginosa Ventilator-Associated Pneumonia.

Introduction: Ventilator-associated pneumonia (VAP) caused by Pseudomonas aeruginosa is a major cause of morbidity and mortality in hospital intensive care units (ICU). Rapid identification of P. aeruginosa-derived markers in easily accessible patients' samples can enable an early detection of P. aeruginosa VAP (VAP-PA), thereby stewarding antibiotic use and improving clinical outcomes. Methods: Metabolites were analysed using liquid chromatography-mass spectrometry (LC-MS) in prospectively collected urine samples from mechanically ventilated patients admitted to the Antwerp University Hospital ICU. Patients were followed from the start of mechanical ventilation (n = 100 patients) till the time of clinical diagnosis of VAP (n = 13). Patients (n = 8) in whom diagnosis of VAP was further confirmed by culturing respiratory samples and urine samples were studied for semi-quantitative metabolomics. Results: We first show that multivariate analyses highly discriminated VAP-PA from VAP-non-PA as well as from the pre-infection groups (R 2 = .97 and .98, respectively). A further univariate analysis identified 58 metabolites that were significantly elevated or uniquely present in VAP-PA compared to the VAP-non-PA and pre-infection groups (P < .05). These comprised both a known metabolite of histidine as well as a novel nicotine metabolite. Most interestingly, we identified 3 metabolites that were not only highly upregulated for, but were also highly specific to, VAP-PA, as these metabolites were completely absent in all pre-infection timepoints and in VAP-non-PA group. Conclusions: Considerable differences exist between urine metabolites in VAP-PA compared to VAP due to other bacterial aetiologies as well to non-VAP (pre-infection) timepoints. The unique urinary metabolic biomarkers we describe here, if further validated, could serve as highly specific diagnostic biomarkers of VAP-PA.

Identification of Non-Canonical Translation Products in C. elegans Using Tandem Mass Spectrometry.

Transcriptome and ribosome sequencing have revealed the existence of many non-canonical transcripts, mainly containing splice variants, ncRNA, sORFs and altORFs. However, identification and characterization of products that may be translated out of these remains a challenge. Addressing this, we here report on 552 non-canonical proteins and splice variants in the model organism C. elegans using tandem mass spectrometry. Aided by sequencing-based prediction, we generated a custom proteome database tailored to search for non-canonical translation products of C. elegans. Using this database, we mined available mass spectrometric resources of C. elegans, from which 51 novel, non-canonical proteins could be identified. Furthermore, we utilized diverse proteomic and peptidomic strategies to detect 40 novel non-canonical proteins in C. elegans by LC-TIMS-MS/MS, of which 6 were common with our meta-analysis of existing resources. Together, this permits us to provide a resource with detailed annotation of 467 splice variants and 85 novel proteins mapped onto UTRs, non-coding regions and alternative open reading frames of the C. elegans genome.

Ion Mobility Coupled to a Time-of-Flight Mass Analyzer Combined With Fragment Intensity Predictions Improves Identification of Classical Bioactive Peptides and Small Open Reading Frame-Encoded Peptides.

Bioactive peptides exhibit key roles in a wide variety of complex processes, such as regulation of body weight, learning, aging, and innate immune response. Next to the classical bioactive peptides, emerging from larger precursor proteins by specific proteolytic processing, a new class of peptides originating from small open reading frames (sORFs) have been recognized as important biological regulators. But their intrinsic properties, specific expression pattern and location on presumed non-coding regions have hindered the full characterization of the repertoire of bioactive peptides, despite their predominant role in various pathways. Although the development of peptidomics has offered the opportunity to study these peptides in vivo, it remains challenging to identify the full peptidome as the lack of cleavage enzyme specification and large search space complicates conventional database search approaches. In this study, we introduce a proteogenomics methodology using a new type of mass spectrometry instrument and the implementation of machine learning tools toward improved identification of potential bioactive peptides in the mouse brain. The application of trapped ion mobility spectrometry (tims) coupled to a time-of-flight mass analyzer (TOF) offers improved sensitivity, an enhanced peptide coverage, reduction in chemical noise and the reduced occurrence of chimeric spectra. Subsequent machine learning tools MS2PIP, predicting fragment ion intensities and DeepLC, predicting retention times, improve the database searching based on a large and comprehensive custom database containing both sORFs and alternative ORFs. Finally, the identification of peptides is further enhanced by applying the post-processing semi-supervised learning tool Percolator. Applying this workflow, the first peptidomics workflow combined with spectral intensity and retention time predictions, we identified a total of 167 predicted sORF-encoded peptides, of which 48 originating from presumed non-coding locations, next to 401 peptides from known neuropeptide precursors, linked to 66 annotated bioactive neuropeptides from within 22 different families. Additional PEAKS analysis expanded the pool of SEPs on presumed non-coding locations to 84, while an additional 204 peptides completed the list of peptides from neuropeptide precursors. Altogether, this study provides insights into a new robust pipeline that fuses technological advancements from different fields ensuring an improved coverage of the neuropeptidome in the mouse brain.

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.

Prognostic and Predictive Biomarkers in Non-Small Cell Lung Cancer Patients on Immunotherapy-The Role of Liquid Biopsy in Unraveling the Puzzle.

In the last decade, immunotherapy has been one of the most important advances in the non-small cell lung cancer (NSCLC) treatment landscape. Nevertheless, only a subset of NSCLC patients benefits from it. Currently, the only Food and Drug Administration (FDA) approved diagnostic test for first-line immunotherapy in metastatic NSCLC patients uses tissue biopsies to determine the programmed death ligand 1 (PD-L1) status. However, obtaining tumor tissue is not always feasible and puts the patient at risk. Liquid biopsy, which refers to the tumor-derived material present in body fluids, offers an alternative approach. This less invasive technique gives real-time information on the tumor characteristics. This review addresses different promising liquid biopsy based biomarkers in NSCLC patients that enable the selection of patients who benefit from immunotherapy and the monitoring of patients during this therapy. The challenges and the opportunities of blood-based biomarkers such as cell-free DNA (cfDNA), circulating tumor cells (CTCs), exosomes, epigenetic signatures, microRNAs (miRNAs) and the T cell repertoire will be addressed. This review also focuses on the less-studied feces-based and breath-based biomarkers.

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.

Urinary Protein Biomarker Panel for the Diagnosis of Antibody-Mediated Rejection in Kidney Transplant Recipients.

INTRODUCTION: Antibody-mediated rejection (ABMR) impacts kidney allograft outcome. The diagnosis is made based on findings from invasive kidney transplant biopsy specimens. The aim of this study was to identify a noninvasive urinary protein biomarker for ABMR after kidney transplantation. METHODS: We performed a multicenter case-control study to identify a urinary biomarker for ABMR (training cohort, n = 249) and an independent, prospective multicenter cohort study for validation (n = 391). We used concomitant biopsies to classify the samples according to the Banff classification. After untargeted protein identification and quantification, we used a support vector machine to train the model in the training cohort. The primary endpoint was the diagnostic accuracy of the urinary biomarker for ABMR in the validation cohort. RESULTS: We identified a set of 10 urinary proteins that accurately discriminated patients with (n = 60) and without (n = 189) ABMR in the training cohort with an area under the curve (AUC) of 0.98 (95% confidence interval [CI], 0.96-1.00). The diagnostic accuracy was maintained in the validation cohort (AUC, 0.88; 95% CI, 0.8-0.93) for discriminating the presence (n = 43) from the absence (n = 348) of ABMR. The negative predictive value of the 10-protein marker set for exclusion of ABMR was 0.99, and the positive predictive value was 0.33. The diagnostic accuracy was independent of the reason for performing the biopsy, time after transplantation, and better than the accuracy of gross proteinuria (AUC, 0.76). CONCLUSIONS: We identified and validated a urinary protein biomarker set that can be used to exclude ABMR.

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.

Implementation of MALDI Mass Spectrometry Imaging in Cancer Proteomics Research: Applications and Challenges.

Studying the proteome-the entire set of proteins in cells, tissues, organs and body fluids-is of great relevance in cancer research, as differential forms of proteins are expressed in response to specific intrinsic and extrinsic signals. Discovering protein signatures/pathways responsible for cancer transformation may lead to a better understanding of tumor biology and to a more effective diagnosis, prognosis, recurrence and response to therapy. Moreover, proteins can act as a biomarker or potential drug targets. Hence, it is of major importance to implement proteomic, particularly mass spectrometric, approaches in cancer research, to provide new crucial insights into tumor biology. Recently, mass spectrometry imaging (MSI) approaches were implemented in cancer research, to provide individual molecular characteristics of each individual tumor while retaining molecular spatial distribution, essential in the context of personalized disease management and medicine.

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.

Mass Spectrometry Imaging Reveals Neutrophil Defensins as Additional Biomarkers for Anti-PD-(L)1 Immunotherapy Response in NSCLC Patients.

(1) Background: Therapeutic blocking of the interaction between programmed death-1 (PD-1) with its ligand PD-L1, an immune checkpoint, is a promising approach to restore the antitumor immune response. Improved clinical outcomes have been shown in different human cancers, including non-small cell lung cancer (NSCLC). Unfortunately, still a high number of NSCLC patients are treated with immunotherapy without obtaining any clinical benefit, due to the limitations of PD-L1 protein expression as the currently sole predictive biomarker for clinical use; (2) Methods: In this study, we applied mass spectrometry imaging (MSI) to discover new protein biomarkers, and to assess the possible correlation between candidate biomarkers and a positive immunotherapy response by matrix-assisted laser desorption/ionization (MALDI) MSI in 25 formalin-fixed paraffin-embedded (FFPE) pretreatment tumor biopsies (Biobank@UZA); (3) Results: Using MALDI MSI, we revealed that the addition of neutrophil defensin 1, 2 and 3 as pretreatment biomarkers may more accurately predict the outcome of immunotherapy treatment in NSCLC. These results were verified and confirmed with immunohistochemical analyses. In addition, we provide in-vitro evidence of the immune stimulatory effect of neutrophil defensins towards cancer cells; and (4) Conclusions: With proteomic approaches, we have discovered neutrophil defensins as additional prospective biomarkers for an anti-PD-(L)1 immunotherapy response. Thereby, we also demonstrated that the neutrophil defensins contribute in the activation of the immune response towards cancer cells, which could provide a new lead towards an anticancer therapy.

Next-generation protein analysis in the pathology department.

Traditionally, immunohistochemistry (IHC) is used by pathologists to localise specific proteins or peptides in tissue slides. In the era of personalised medicine, however, molecular tissue analysis becomes indispensable for correct diagnosis, prognosis and therapeutic decision, not only on the DNA or mRNA level but also on the protein level. Combining molecular information with imaging presents many advantages. Therefore, matrix-assisted laser desorption/ionisation imaging mass spectrometry (MALDI IMS) is a promising technique to be added to the armamentarium of the pathologist. Here, we focus on the workflow, advantages and drawbacks of both MALDI IMS and IHC. We also briefly discuss a few other protein imaging modalities and give examples of applications.

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.