Single-tissue proteomics in Caenorhabditis elegans reveals proteins resident in intestinal lysosome-related organelles.

The nematode intestine is the primary site for nutrient uptake and storage as well as the synthesis of biomolecules; lysosome-related organelles known as gut granules are important for many of these functions. Aspects of intestine biology are not well understood, including the export of the nutrients it imports and the molecules it synthesizes, as well as the complete functions and protein content of the gut granules. Here, we report a mass spectrometry (MS)-based proteomic analysis of the intestine of the Caenorhabditis elegans and of its gut granules. Overall, we identified approximately 5,000 proteins each in the intestine and the gonad and showed that most of these proteins can be detected in samples extracted from a single worm, suggesting the feasibility of individual-level genetic analysis using proteomes. Comparing proteomes and published transcriptomes of the intestine and the gonad, we identified proteins that appear to be synthesized in the intestine and then transferred to the gonad. To identify gut granule proteins, we compared the proteome of individual intestines deficient in gut granules to the wild type. The identified gut granule proteome includes proteins known to be exclusively localized to the granules and additional putative gut granule proteins. We selected two of these putative gut granule proteins for validation via immunohistochemistry, and our successful confirmation of both suggests that our strategy was effective in identifying the gut granule proteome. Our results demonstrate the practicability of single-tissue MS-based proteomic analysis in small organisms and in its future utility.

Digital Microfluidics for Microproteomic Analysis of Minute Mammalian Tissue Samples Enabled by a Photocleavable Surfactant.

Proteome profiles of precious tissue samples have great clinical potential for accelerating disease biomarker discovery and promoting novel strategies for early diagnosis and treatment. However, tiny clinical tissue samples are often difficult to handle and analyze with conventional proteomic methods. Automated digital microfluidic (DMF) workflows facilitate the manipulation of size-limited tissue samples. Here, we report the assessment of a DMF microproteomics workflow enabled by a photocleavable surfactant for proteomic analysis of minute tissue samples. The surfactant 4-hexylphenylazosulfonate (Azo) was found to facilitate fast droplet movement on DMF and enhance the proteomics analysis. Comparisons of Azo and n-Dodecyl ß-d-maltoside (DDM) using small samples of HeLa digest standards and MCF-7 cell digests revealed distinct differences at the peptide level despite similar results at the protein level. The DMF microproteomics workflow was applied for the sample preparation of ∼3 µg biopsies from murine brain tissue. A total of 1969 proteins were identified in three samples, including established neural biomarkers and proteins related to synaptic signaling. Going forward, we propose that the Azo-enabled DMF workflow has the potential to advance the practical clinical application of DMF for the analysis of size-limited tissue samples.

MALDImID: Spatialomics R package and Shiny app for more specific identification of MALDI imaging proteolytic peaks using LC-MS/MS-based proteomic biomarker discovery data.

Matrix-assisted laser desorption/ionization (MALDI) imaging of proteolytic peptides from formalin-fixed paraffin embedded (FFPE) tissue sections could be integrated in the portfolio of molecular pathologists for protein localization and tissue classification. However, protein identification can be very tedious using MALDI-time-of-flight (TOF) and post-source decay (PSD)-based fragmentation. Hereby, we implemented an R package and Shiny app to exploit liquid chromatography-tandem mass spectrometry (LC-MS/MS)-based proteomic biomarker discovery data for more specific identification of peaks observed in bottom-up MALDI imaging data. The package is made available under the GPL 3 license. The Shiny app can directly be used at the following address: https://biosciences.shinyapps.io/Maldimid.

Identification of Important Factors Causing Developmental Arrest in Cloned Pig Embryos by Embryo Biopsy Combined with Microproteomics.

The technique of pig cloning holds great promise for the livestock industry, life science, and biomedicine. However, the prenatal death rate of cloned pig embryos is extremely high, resulting in a very low cloning efficiency. This limits the development and application of pig cloning. In this study, we utilized embryo biopsy combined with microproteomics to identify potential factors causing the developmental arrest in cloned pig embryos. We verified the roles of two potential regulators, PDCD6 and PLK1, in cloned pig embryo development. We found that siRNA-mediated knockdown of PDCD6 reduced mRNA and protein expression levels of the pro-apoptotic gene, CASP3, in cloned pig embryos. PDCD6 knockdown also increased the cleavage rate and blastocyst rate of cloned porcine embryos. Overexpression of PLK1 via mRNA microinjection also improved the cleavage rate of cloned pig embryos. This study provided a new strategy to identify key factors responsible for the developmental defects in cloned pig embryos. It also helped establish new methods to improve pig cloning efficiency, specifically by correcting the expression pattern of PDCD6 and PLK1 in cloned pig embryos.

Digital Microfluidics Supported Microproteomics for Quantitative Proteome Analysis of Single Caenorhabditis elegans Nematodes.

Miniaturization of sample preparation, including omissible manual sample handling steps, is key for reproducible nanoproteomics, as material is often restricted to only hundreds of cells or single model organisms. Here, we demonstrate a highly sensitive digital microfluidics (DMF)-based sample preparation workflow making use of single-pot solid-phase enhanced sample preparation (SP3) in combination with high-field asymmetric-waveform ion mobility spectrometry (FAIMS), and fast and sensitive ion trap detection on an Orbitrap tribrid MS system. Compared to a manual in-tube SP3-supported sample preparation, the numbers of identified peptides and proteins were markedly increased, while lower standard deviations between replicates were observed. We repeatedly identified up to 5000 proteins from single nematodes. Moreover, label-free quantification of protein changes in single Caenorhabditis elegans treated with a heat stimulus yielded 45 differentially abundant proteins when compared to the untreated control, highlighting the potential of this technology for low-input proteomics studies. LC-MS data have been deposited to the ProteomeXchange Consortium with the data set identifier PXD033143.

Applications of spatially resolved omics in the field of endocrine tumors.

Endocrine tumors derive from endocrine cells with high heterogeneity in function, structure and embryology, and are characteristic of a marked diversity and tissue heterogeneity. There are still challenges in analyzing the molecular alternations within the heterogeneous microenvironment for endocrine tumors. Recently, several proteomic, lipidomic and metabolomic platforms have been applied to the analysis of endocrine tumors to explore the cellular and molecular mechanisms of tumor genesis, progression and metastasis. In this review, we provide a comprehensive overview of spatially resolved proteomics, lipidomics and metabolomics guided by mass spectrometry imaging and spatially resolved microproteomics directed by microextraction and tandem mass spectrometry. In this regard, we will discuss different mass spectrometry imaging techniques, including secondary ion mass spectrometry, matrix-assisted laser desorption/ionization and desorption electrospray ionization. Additionally, we will highlight microextraction approaches such as laser capture microdissection and liquid microjunction extraction. With these methods, proteins can be extracted precisely from specific regions of the endocrine tumor. Finally, we compare applications of proteomic, lipidomic and metabolomic platforms in the field of endocrine tumors and outline their potentials in elucidating cellular and molecular processes involved in endocrine tumors.

Microproteomic sample preparation.

Multiple applications of proteomics in life and health science, pathology and pharmacology, require handling size-limited cell and tissue samples. During proteomic sample preparation, analyte loss in these samples arises when standard procedures are used. Thus, specific considerations have to be taken into account for processing, that are summarised under the term microproteomics (µPs). Microproteomic workflows include: sampling (e.g., flow cytometry, laser capture microdissection), sample preparation (possible disruption of cells or tissue pieces via lysis, protein extraction, digestion in bottom-up approaches, and sample clean-up) and analysis (chromatographic or electrophoretic separation, mass spectrometric measurements and statistical/bioinformatic evaluation). All these steps must be optimised to reach wide protein dynamic ranges and high numbers of identifications. Under optimal conditions, sampling is adapted to the studied sample types and nature, sample preparation isolates and enriches the whole protein content, clean-up removes salts and other interferences such as detergents or chaotropes, and analysis identifies as many analytes as the instrumental throughput and sensitivity allow. In the suggested review, we present and discuss the current state in µP applications for processing of small number of cells (cell µPs) and microscopic tissue regions (tissue µPs).

Path to Clonal Theranostics in Luminal Breast Cancers.

Integrating tumor heterogeneity in the drug discovery process is a key challenge to tackle breast cancer resistance. Identifying protein targets for functionally distinct tumor clones is particularly important to tailor therapy to the heterogeneous tumor subpopulations and achieve clonal theranostics. For this purpose, we performed an unsupervised, label-free, spatially resolved shotgun proteomics guided by MALDI mass spectrometry imaging (MSI) on 124 selected tumor clonal areas from early luminal breast cancers, tumor stroma, and breast cancer metastases. 2868 proteins were identified. The main protein classes found in the clonal proteome dataset were enzymes, cytoskeletal proteins, membrane-traffic, translational or scaffold proteins, or transporters. As a comparison, gene-specific transcriptional regulators, chromatin related proteins or transmembrane signal receptor were more abundant in the TCGA dataset. Moreover, 26 mutated proteins have been identified. Similarly, expanding the search to alternative proteins databases retrieved 126 alternative proteins in the clonal proteome dataset. Most of these alternative proteins were coded mainly from non-coding RNA. To fully understand the molecular information brought by our approach and its relevance to drug target discovery, the clonal proteomic dataset was further compared to the TCGA breast cancer database and two transcriptomic panels, BC360 (nanoString®) and CDx (Foundation One®). We retrieved 139 pathways in the clonal proteome dataset. Only 55% of these pathways were also present in the TCGA dataset, 68% in BC360 and 50% in CDx. Seven of these pathways have been suggested as candidate for drug targeting, 22 have been associated with breast cancer in experimental or clinical reports, the remaining 19 pathways have been understudied in breast cancer. Among the anticancer drugs, 35 drugs matched uniquely with the clonal proteome dataset, with only 7 of them already approved in breast cancer. The number of target and drug interactions with non-anticancer drugs (such as agents targeting the cardiovascular system, metabolism, the musculoskeletal or the nervous systems) was higher in the clonal proteome dataset (540 interactions) compared to TCGA (83 interactions), BC360 (419 interactions), or CDx (172 interactions). Many of the protein targets identified and drugs screened were clinically relevant to breast cancer and are in clinical trials. Thus, we described the non-redundant knowledge brought by this clone-tailored approach compared to TCGA or transcriptomic panels, the targetable proteins identified in the clonal proteome dataset, and the potential of this approach for drug discovery and repurposing through drug interactions with antineoplastic agents and non-anticancer drugs.

Histo-molecular differentiation of renal cancer subtypes by mass spectrometry imaging and rapid proteome profiling of formalin-fixed paraffin-embedded tumor tissue sections.

Pathology differentiation of renal cancer types is challenging due to tissue similarities or overlapping histological features of various tumor (sub) types. As assessment is often manually conducted outcomes can be prone to human error and therefore require high-level expertise and experience. Mass spectrometry can provide detailed histo-molecular information on tissue and is becoming increasingly popular in clinical settings. Spatially resolving technologies such as mass spectrometry imaging and quantitative microproteomics profiling in combination with machine learning approaches provide promising tools for automated tumor classification of clinical tissue sections. In this proof of concept study we used MALDI-MS imaging (MSI) and rapid LC-MS/MS-based microproteomics technologies (15 min/sample) to analyze formalin-fixed paraffin embedded (FFPE) tissue sections and classify renal oncocytoma (RO, n = 11), clear cell renal cell carcinoma (ccRCC, n = 12) and chromophobe renal cell carcinoma (ChRCC, n = 5). Both methods were able to distinguish ccRCC, RO and ChRCC in cross-validation experiments. MSI correctly classified 87% of the patients whereas the rapid LC-MS/MS-based microproteomics approach correctly classified 100% of the patients. This strategy involving MSI and rapid proteome profiling by LC-MS/MS reveals molecular features of tumor sections and enables cancer subtype classification. Mass spectrometry provides a promising complementary approach to current pathological technologies for precise digitized diagnosis of diseases.

MS Imaging-Guided Microproteomics for Spatial Omics on a Single Instrument.

Mass spectrometry imaging (MSI) allows investigating the spatial distribution of chemical compounds directly in biological tissues. As the analytical depth of MSI is limited, MSI needs to be coupled to more sensitive local extraction-based omics approaches to achieve a comprehensive molecular characterization. For this, it is important to retain the spatial information provided by MSI for follow-up omics studies. It has been shown that regiospecific MSI data can be used to guide a laser microdissection system for ultra-sensitive liquid chromatography-mass spectrometry (LC-MS) analyses. So far, this combination has required separate and specialized mass spectrometry (MS) instrumentation. Recent advances in dual-source instrumentation, harboring both matrix assisted laser/desorption ionization (MALDI) and electrospray ionization (ESI) sources, promise state-of-the-art MSI and liquid-based proteomic capabilities on the same MS instrument. This study demonstrates that such an instrument can offer both fast lipid-based MSI at high mass and high lateral resolution and sensitive LC-MS on local protein extracts from the exact same tissue section.

Microproteomics and Immunohistochemistry Reveal Differences in Aldo-Keto Reductase Family 1 Member C3 in Tissue Specimens of Ulcerative Colitis and Crohn's Disease.

PURPOSE: Differential diagnosis of ulcerative colitis (UC) and Crohn's disease (CD) is of utmost importance for the decision making of respective therapeutic treatment strategies but in about 10-15% of cases, a clinical and histopathological assessment does not lead to a definite diagnosis. The aim of the study is to characterize proteomic differences between UC and CD. EXPERIMENTAL DESIGN: Microproteomics is performed on formalin-fixed paraffin-embedded colonic tissue specimens from 9 UC and 9 CD patients. Protein validation is performed using immunohistochemistry (IHC) (nUC =51, nCD =62, nCTRL =10) followed by digital analysis. RESULTS: Microproteomic analyses reveal eight proteins with higher abundance in CD compared to UC including proteins related to neutrophil activity and damage-associated molecular patterns. Moreover, one protein, Aldo-keto reductase family 1 member C3 (AKR1C3), is present in eight out of nine CD and absent in all UC samples. Digital IHC analysis reveal a higher percentage and an increased expression intensity of AKR1C3-positive epithelial cells in CD compared to UC and in controls compared to inflammatory bowel disease (IBD). CONCLUSION AND CLINICAL RELEVANCE: Overall, the results suggest that microproteomics is an adequate tool to highlight protein patterns in IBD. IHC and digital pathology might support future differential diagnosis of UC and CD.

Precise co-registration of mass spectrometry imaging, histology, and laser microdissection-based omics.

Mass spectrometry imaging (MSI) is an analytical technique for the unlabeled and multiplex imaging of molecules in biological tissue sections. It therefore enables the spatial and molecular annotations of tissues complementary to histology. It has already been shown that MSI can guide subsequent material isolation technologies such as laser microdissection (LMD) to enable a more in-depth molecular characterization of MSI-highlighted tissue regions. However, with MSI now reaching spatial resolutions at the single-cell scale, there is a need for a precise co-registration between MSI and the LMD. As proof-of-principle, MSI of lipids was performed on a breast cancer tissue followed by a segmentation of the data to detect molecularly distinct segments within its tumor areas. After image processing of the segmentation results, the coordinates of the MSI-detected segments were passed to the LMD system by three co-registration steps. The errors of each co-registration step were quantified and the total error was found to be less than 13 µm. With this link established, MSI data can now accurately guide LMD to excise MSI-defined regions of interest for subsequent extract-based analyses. In our example, the excised tissue material was then subjected to ultrasensitive microproteomics in order to determine predominant molecular mechanisms in each of the MSI-highlighted intratumor segments. This work shows how the strengths of MSI, histology, and extract-based omics can be combined to enable a more comprehensive molecular characterization of in situ biological processes.

Mapping Spatiotemporal Microproteomics Landscape in Experimental Model of Traumatic Brain Injury Unveils a link to Parkinson's Disease.

Traumatic brain injury (TBI) represents a major health concerns with no clinically-approved FDA drug available for therapeutic intervention. Several genomics and neuroproteomics studies have been employed to decipher the underlying pathological mechanisms involved that can serve as potential neurotherapeutic targets and unveil a possible underlying relation of TBI to other secondary neurological disorders. In this work, we present a novel high throughput systems biology approach using a spatially resolved microproteomics platform conducted on different brain regions in an experimental rat model of moderate of controlled cortical injury (CCI) at a temporal pattern postinjury (1 day, 3 days, 7 days, and 10 days). Mapping the spatiotemporal landscape of signature markers in TBI revealed an overexpression of major protein families known to be implicated in Parkinson's disease (PD) such as GPR158, HGMB1, synaptotagmin and glutamate decarboxylase in the ipsilateral substantia nigra. In silico bioinformatics docking experiments indicated the potential correlation between TBI and PD through alpha-synuclein. In an in vitro model, stimulation with palmitoylcarnitine triggered an inflammatory response in macrophages and a regeneration processes in astrocytes which also further confirmed the in vivo TBI proteomics data. Taken together, this is the first study to assess the microproteomics landscape in TBI, mainly in the substantia nigra, thus revealing a potential predisposition for PD or Parkinsonism post-TBI.

Application of a Sensitive and Reproducible Label-Free Proteomic Approach to Explore the Proteome of Individual Meiotic-Phase Barley Anthers.

Meiosis is a highly dynamic and precisely regulated process of cell division, leading to the production of haploid gametes from one diploid parental cell. In the crop plant barley (Hordeum vulgare), male meiosis occurs in anthers, in specialized cells called meiocytes. Barley meiotic tissue is scarce and not easily accessible, making meiosis study a challenging task. We describe here a new micro-proteomics workflow that allows sensitive and reproducible genome-wide label-free proteomic analysis of individual staged barley anthers. This micro-proteomic approach detects more than 4,000 proteins from such small amounts of material as two individual anthers, covering a dynamic range of protein relative abundance levels across five orders of magnitude. We applied our micro-proteomics workflow to investigate the proteome of the developing barley anther containing pollen mother cells in the early stages of meiosis and we successfully identified 57 known and putative meiosis-related proteins. Meiotic proteins identified in our study were found to be key players of many steps and processes in early prophase such as: chromosome condensation, synapsis, DNA double-strand breaks or crossover formation. Considering the small amount of starting material, this work demonstrates an important technological advance in plant proteomics and can be applied for proteomic examination of many size-limited plant specimens. Moreover, it is the first insight into the proteome of individual barley anther at early meiosis. The proteomic data have been deposited to the ProteomeXchange with the accession number PXD010887.

A novel Microproteomic Approach Using Laser Capture Microdissection to Study Cellular Protrusions.

Cell⁻cell communication is vital to multicellular organisms, and distinct types of cellular protrusions play critical roles during development, cell signaling, and the spreading of pathogens and cancer. The differences in the structure and protein composition of these different types of protrusions and their specific functions have not been elucidated due to the lack of a method for their specific isolation and analysis. In this paper, we described, for the first time, a method to specifically isolate distinct protrusion subtypes, based on their morphological structures or fluorescent markers, using laser capture microdissection (LCM). Combined with a unique fixation and protein extraction protocol, we pushed the limits of microproteomics and demonstrate that proteins from LCM-isolated protrusions can successfully and reproducibly be identified by mass spectrometry using ultra-high field Orbitrap technologies. Our method confirmed that different types of protrusions have distinct proteomes and it promises to advance the characterization and the understanding of these unique structures to shed light on their possible role in health and disease.

Identification of MALDI Imaging Proteolytic Peptides Using LC-MS/MS-Based Biomarker Discovery Data: A Proof of Concept.

PURPOSE: Identification of proteolytic peptides from matrix-assisted laser desorption/ionization (MALDI) imaging remains a challenge. The low fragmentation yields obtained using in situ post source decay impairs identification. Liquid chromatography-tandem mass spectrometry (LC-MS/MS) is an alternative to in situ MS/MS, but leads to multiple identification candidates for a given mass. The authors propose to use LC-MS/MS-based biomarker discovery results to reliably identify proteolytic peptides from MALDI imaging. EXPERIMENTAL DESIGN: The authors defined m/z values of interest for high grade squamous intraepithelial lesion (HSIL) by MALDI imaging. In parallel the authors used data from a biomarker discovery study to correlate m/z from MALDI imaging with masses of peptides identified by LC-MS/MS in HSIL. The authors neglected candidates that were not significantly more abundant in HSIL according to the biomarker discovery investigation. RESULTS: The authors assigned identifications to three m/z of interest. The number of possible identifiers for MALDI imaging m/z peaks using LC-MS/MS-based biomarker discovery studies was reduced by about tenfold compared using a single LC-MS/MS experiment. One peptide identification candidate was validated by immunohistochemistry. CONCLUSION AND CLINICAL RELEVANCE: This concept combines LC-MS/MS-based quantitative proteomics with MALDI imaging and allows reliable peptide identification. Public datasets from LC-MS/MS biomarker discovery experiments will be useful to identify MALDI imaging m/z peaks.

Microproteomic Profiling of High-Grade Squamous Intraepithelial Lesion of the Cervix: Insight into Biological Mechanisms of Dysplasia and New Potential Diagnostic Markers.

PURPOSE: High-grade squamous intraepithelial lesion (HSIL) is a known precursor for squamous cell carcinoma of uterine cervix. Although it is known that SILs are associated to infection by human papillomavirus, downstream biological mechanisms are still poorly described. In this study, we compared the microproteomic profile of HSIL to normal tissues: ectocervix (ectoC) and endocervix (endoC). EXPERIMENTAL DESIGN: Tissue regions of endoC, ectoC, and HSlL were collected by laser microdissection (3500 cells each) from five patients. Samples were processed and analyzed using our recently developed laser microdissection-based microproteomic method. Tissues were compared in order to retrieve HSIL's proteomic profile. Potentially interesting proteins for pathology were stained by immunohistochemistry. RESULTS: We identified 3072 proteins among the fifteen samples and 2386 were quantified in at least four out of the five biological replicates of at least one tissue type. We found 236 proteins more abundant in HSIL. Gene ontology enrichments revealed mechanisms of DNA replication and RNA splicing. Despite the squamous nature of HSIL, a common signature between HSIL and endoC could be found. Finally, potential new markers could support diagnosis of dysplasia in SILs. CONCLUSION AND CLINICAL RELEVANCE: This microproteomic investigation of HSIL gives insights into the biology of cervical precancerous lesions.

Laser Microdissection-Based Microproteomics of Formalin-Fixed and Paraffin-Embedded (FFPE) Tissues.

Laser microdissection-based proteomics on formalin-fixed and paraffin-embedded tissues is usually performed from relatively large tissue areas or pools of multiple tissue pieces. However, several molecular pathology studies require working on very limited amounts of tissue. This is for example the case when very early cancer lesions have to be handled. Hereby, we present a method for the processing of very small pieces of formalin-fixed and paraffin-embedded tissues for proteomic purposes. This approach is designed in order to avoid sample loss during technical processing and to optimize the digestion of tissue areas containing as little as 2700 cells.

MALDI Imaging-Guided Microproteomic Analyses of Heterogeneous Breast Tumors-A Pilot Study.

Matrix-assisted laser desorption/ionization (MALDI) imaging is an ideal tool to study intratumor heterogeneity (ITH) and its implication in prognostic stratification of patients. However, there are some drawbacks concerning protein identification. On the other hand, laser microdissection (LMD)-based microproteomics allows retrieving thousands of protein identifications from small tissue pieces. As a proof of concept, the authors combine these two complementary approaches to analyze heterogeneous regions in breast tumors. Invasive ductal breast cancer FFPE tissue sections from five patients are analyzed by MALDI imaging and the dataset is processed by segmentation. Heterogeneous regions within tumors are processed by LMD-based microproteomics, in duplicates. Liquid chromatography-tandem mass spectrometry data are classified by hierarchical clustering. Heterogeneous tissue regions are discriminated on the basis of their actual molecular heterogeneity. The dataset is correlated with MALDI imaging to identify m/z values discriminating heterogeneous regions. The molecular characterization of cell clones in tumors related to bad patient outcome could have great impact for pathology. A combined application of LMD-based microproteomics and MALDI imaging for ITH studies is presented.

MALDI Imaging Combined with Laser Microdissection-Based Microproteomics for Protein Identification: Application to Intratumor Heterogeneity Studies.

Matrix-assisted laser desorption ionization (MALDI) imaging is widely used for in situ proteomic mapping and finds multiple applications in pathology. However, low fragmentation yields in MALDI avoid an optimal identification of peptides from tissues. On the other hand, LMD-based microproteomic analyses allow for the identification of hundreds to thousands of proteins from small tissue regions. Herein, we present the combination of MALDI imaging and LMD-based microproteomic approaches for parallel identification. We illustrate the workflow with an application to intratumor heterogeneity studies.