Urine Proteomic Signatures of Mild Hypothermia Treatment in Cerebral Ischemia-Reperfusion Injury in Rats.

Mild hypothermia (MH) is an effective measure to alleviate cerebral ischemia-reperfusion (I/R) injury. However, the underlying biological mechanisms remain unclear. This study set out to investigate dynamic changes in urinary proteome due to MH in rats with cerebral I/R injury and explore the neuroprotective mechanisms of MH. A Pulsinelli's four-vessel occlusion (4-VO) rat model was used to mimic global cerebral I/R injury. Liquid chromatography-tandem mass spectrometry (LC-MS/MS) was employed to profile the urinary proteome of rats with/without MH (32 °C) treatment after I/R injury. Representative differentially expressed proteins (DEPs) associated with MH were validated by western blotting in hippocampus. A total of 597 urinary proteins were identified, among which 119 demonstrated significant changes associated with MH. Gene Ontology (GO) annotation of the DEPs revealed that MH significantly enriched in endopeptidase activity, inflammatory response, aging, response to oxidative stress and reactive oxygen species, blood coagulation, and cell adhesion. Notably, changes in 12 DEPs were significantly reversed by MH treatment. Among them, 8 differential urinary proteins were previously reported to be closely associated with brain disease, including NP, FZD1, B2M, EPCR, ATRN, MB, CA1and VPS4A. Two representative proteins (FZD1, B2M) were further validated by western blotting in the hippocampus and the results were shown to be consistent with urinary proteomic analysis. Overall, this study strengthens the idea that urinary proteome can sensitively reflect pathophysiological changes in the brain, and appears to be the first study to explore the neuroprotective effects of MH by urinary proteomic analysis. FZD1 and B2M may be involved in the most fundamental molecular biological mechanisms of MH neuroprotection.

A reanalysis and integration of transcriptomics and proteomics datasets unveil novel drug targets for Mekong schistosomiasis.

Schistosomiasis, caused by Schistosoma trematodes, is a significant global health concern, particularly affecting millions in Africa and Southeast Asia. Despite efforts to combat it, the rise of praziquantel (PZQ) resistance underscores the need for new treatment options. Protein kinases (PKs) are vital in cellular signaling and offer potential as drug targets. This study focused on focal adhesion kinase (FAK) as a candidate for anti-schistosomal therapy. Transcriptomic and proteomic analyses of adult S. mekongi worms identified FAK as a promising target due to its upregulation and essential role in cellular processes. Molecular docking simulations assessed the binding energy of FAK inhibitors to Schistosoma FAK versus human FAK. FAK inhibitor 14 and PF-03814735 exhibited strong binding to Schistosoma FAK with minimal binding for human FAK. In vitro assays confirmed significant anti-parasitic activity against S. mekongi, S. mansoni, and S. japonicum, comparable to PZQ, with low toxicity in human cells, indicating potential safety. These findings highlight FAK as a promising target for novel anti-schistosomal therapies. However, further research, including in vivo studies, is necessary to validate efficacy and safety before clinical use. This study offers a hopeful strategy to combat schistosomiasis and reduce its global impact.

Data-independent acquisition combined with liquid chromatography mass spectrometry technique to detect prognostic protein markers in type I gastric neuroendocrine neoplasm.

RATIONALE: This study used proteomics-based data-independent acquisition (DIA) technology with the aim of screening for differential expression proteins in type I gastric neuroendocrine neoplasm (g-NEN). METHODS: Differential expression proteins in type I g-NEN and peritumoral tissues were screened using DIA with liquid chromatography/tandem mass spectrometry (DIA-LC/MS/MS). The identified proteins were then functionally analysed using bioinformatics methods. We selected the three most highly expressed proteins, combined with patients' clinical data, for prognostic analysis. RESULTS: Compared with peritumoral tissues, 224 proteins were up-regulated, and 70 were down-regulated. The most significantly enriched biological processes and pathways were vacuolar proton-transporting V-type ATPase complex assembly and metabolism-related pathways. PCSK1, FBXO2, ACSL1, IRS2, and PTPRZ1 expression was markedly up-regulated in type I g-NENs. High IRS2 expression significantly correlated with a shorter time to recurrence. CONCLUSIONS: Our study provides a comprehensive proteomic signature based on DIA-LC/MS/MS and highlights high IRS2 expression as a potential prognostic marker for type I gNENs.

Quantitative Proteomics of the Intracellular Bacterial Pathogen Salmonella enterica Serovar Typhimurium.

Mass spectrometry-based proteomics provides a wealth of information about changes in protein production and abundance under diverse conditions, as well as mechanisms of regulation, signaling cascades, interaction partners, and communication patterns across biological systems. For profiling of intracellular pathogens, proteomic profiling can be performed in the absence of a host to singularly define the pathogenic proteome or during an infection-like setting to identify dual perspectives of infection. In this chapter, we present techniques to extract proteins from the human bacterial intracellular pathogen, Salmonella enterica serovar Typhimurium, in the presence of macrophages, an important innate immune cell in host defense. We outline sample preparation, including protein extraction, digestion, and purification, as well as mass spectrometry measurements and bioinformatics analysis. The data generated from our dual perspective profiling approach provides new insight into pathogen and host protein modulation under infection-like conditions.

iTRAQ-based proteomic analysis reveals the effect of ribosomal proteins on essential-oil accumulation in Houttuynia cordata Thunb.

Houttuynia cordata Thunb., also known as Yuxingcao in Chinese, occupies a pivotal role in Asian traditional medicine and cuisine. The aerial parts and underground stems of H. cordata exhibit remarkable chemical diversity, particularly in essential oil. Nevertheless, the mechanisms regulating essential oil biosynthesis in H. cordata remain unclear. In this study, we present a quantitative overview of the proteomes across four tissues (flower, stem, leaf, and underground stem) of H. cordata, achieved through the application of the isobaric tag for relative and absolute quantitation (iTRAQ). Our research findings indicate that certain crucial ribosomal proteins and their interactions may significantly impact the production of essential oils in H. cordata. These results offer novel insights into the roles of ribosomal proteins and their associations in essential oil biosynthesis across various organisms of H. cordata.

Nanoliter-Scale Sample Preparation for Single-Cell Proteomic Analysis Using Glass-Oil-Air-Droplet Chip.

Single-cell proteomic analyses are of fundamental importance in order to capture biological heterogeneity within complex cell systems' heterogeneous populations. Mass spectrometry (MS)-based proteomics is a promising alternative for quantitative single-cell proteomics. Various techniques are continually evolving to address the challenges of limited sample material, detection sensitivity, and throughput constraints. In this chapter, we describe a nanoliter-scale glass-oil-air-droplet (gOAD) chip engineered for heat tolerance, which combines droplet-based microfluidics and shotgun proteomic analysis techniques to enable multistep sample pretreatment.

Comprehensive Micro-SPE-Based Bottom-Up Proteomic Workflow for Sensitive Analysis of Limited Samples.

Clinical and biological samples are often scarce and precious (e.g., rare cell isolates, microneedle tissue biopsies, small-volume liquid biopsies, and even single cells or organelles). Typical large-scale proteomic methods, where significantly higher protein amounts are analyzed, are not directly transferable to the analysis of limited samples due to their incompatibility with pg-, ng-, and low-µg-level protein sample amounts. Here, we report the on-microsolid-phase extraction tip (OmSET)-based sample preparation workflow for sensitive analysis of limited biological samples to address this challenge. The developed platform was successfully tested for the analysis of 100-10,000 typical mammalian cells and is scalable to allow for lower and larger protein amounts and more samples to be analyzed (i.e., higher throughput of analysis).

A Sample Preparation Procedure for Isobaric Labeling-Based Single-Cell Proteomics.

Mass spectrometry-based proteomics has traditionally been limited by the amount of input material for analysis. Single-cell proteomics has emerged as a challenging discipline due to the ultra-high sensitivity required. Isobaric labeling-based multiplex strategies with a carrier proteome offer an approach to overcome the sensitivity limitations. Following this as the basic strategy, we show here the general workflow for preparing cells for single-cell mass spectrometry-based proteomics. This protocol can also be applied to manually isolated cells when large cells, such as cardiomyocytes, are difficult to isolate properly with conventional fluorescence-activated cell sorting (FACS) sorter methods.

Label-Free Sample Preparation for Single-Cell Proteomics.

In recent years, single-cell proteomics (SCP) has become a valuable addition to other single-cell omics technologies for studying cellular heterogeneity. The amount of protein in a single cell is very limited, and in contrast to sequencing techniques, there are currently no means for protein amplification. Therefore, most single-cell proteomics approaches aim to maximize sample preparation efficiency while minimizing peptide loss. By reducing processing volumes to sub-microliters and avoiding manual transfer steps that could lead to peptide loss, peptide recovery, and the robustness of SCP workflows have been significantly improved. In this chapter, we describe a protocol for label-free SCP sample preparation using the cellenONE® platform and the proteoCHIP LF 48 substrate prior to analysis with high-performance liquid chromatography-mass spectrometry.

Fully Integrated Online Strategy for Highly Sensitive Proteome Profiling.

Low-input proteomics, which treats tens to hundreds of mammalian cells, is the gap between standard proteomics and single-cell proteomics. Low-input proteomics is widely applicable and needs special sample preparation methods to achieve deep proteome profiling. This chapter describes protocols for the preparation and application of an easy-to-use and scalable device for processing low-input samples. Protein preconcentration, impurity removal, reduction, alkylation, digestion, and desalting are fully integrated into this workflow, and the device can be directly connected to online nanoLC-MS to avoid sample transfer.

Robust Surfactant-Assisted One-Pot Sample Preparation for Label-Free Single-Cell and Nanoscale Proteomics.

With advanced mass spectrometry (MS)-based proteomics, genome-scale proteome coverage can be achieved from bulk cells. However, such bulk measurement obscures cell-to-cell heterogeneity, precluding proteome profiling of single cells and small numbers of cells of interest. To address this issue, in the recent 5 years, there has been a surge of small sample preparation methods developed for robust and effective collection and processing of single cells and small numbers of cells for in-depth MS-based proteome profiling. Based on their broad accessibility, they can be categorized into two types: methods based on specific devices and those based on standard PCR tubes or multi-well plates. In this chapter, we describe the detailed protocol of our recently developed, easily adoptable, Surfactant-assisted One-Pot (SOP) sample preparation coupled with MS method termed SOP-MS for label-free single-cell and nanoscale proteomics. SOP-MS capitalizes on the combination of an MS-compatible surfactant, n-dodecyl-ß-D-maltoside (DDM), and standard low-bind PCR tube or multi-well plate for "all-in-one" one-pot sample preparation without sample transfer. With its robust and convenient features, SOP-MS can be readily implemented in any MS laboratory for single-cell and nanoscale proteomics. With further improvements in MS detection sensitivity and sample throughput, we believe that SOP-MS could open an avenue for single-cell proteomics with broad applicability in biological and biomedical research.

Efficient and Sensitive Sample Preparation, Separations, and Data Acquisition for Label-Free Single-Cell Proteomics.

We describe a sensitive and efficient workflow for label-free single-cell proteomics that spans sample preparation, liquid chromatography separations, and mass spectrometry data acquisition. The Tecan Uno Single Cell Dispenser provides rapid cell isolation and nanoliter-volume reagent dispensing within 384-well PCR plates. A newly developed sample processing workflow achieves cell lysis, protein denaturation, and digestion in 1 h with a single reagent dispensing step. Low-flow liquid chromatography coupled with wide-window data-dependent acquisition results in the quantification of nearly 3000 proteins per cell using an Orbitrap Exploris 480 mass spectrometer. This approach greatly broadens accessibility to sensitive single-cell proteome profiling for nonspecialist laboratories.

Profiling Mouse Brain Single-Cell-Type Proteomes Via Adeno-Associated Virus-Mediated Proximity Labeling and Mass Spectrometry.

Single-cell-type proteomics is an emerging field of research that combines cell-type specificity with the comprehensive proteome coverage offered by bulk proteomics. However, the extraction of single-cell-type proteomes remains a challenge, particularly for hard-to-isolate cells like neurons. In this chapter, we present an innovative technique for profiling single-cell-type proteomes using adeno-associated virus (AAV)-mediated proximity labeling (PL) and tandem-mass-tag (TMT) mass spectrometry. This technique eliminates the need for cell isolation and offers a streamlined workflow, including AAV delivery to express TurboID (an engineered biotin ligase) controlled by cell-type-specific promoters, biotinylated protein purification, on-bead digestion, TMT labeling, and liquid chromatography-mass spectrometry (LC-MS). We examined this method by analyzing distinct brain cell types in mice. Initially, recombinant AAVs were used to concurrently express TurboID and mCherry proteins driven by neuron- or astrocyte-specific promoters, which was validated through co-immunostaining with cellular markers. With biotin purification and TMT analysis, we successfully identified around 10,000 unique proteins from a few micrograms of protein samples with high reproducibility. Our statistical analyses revealed that these proteomes encompass cell-type-specific cellular pathways. By utilizing this technique, researchers can explore the proteomic landscape of specific cell types, paving the way for new insights into cellular processes, deciphering disease mechanisms, and identifying therapeutic targets in neuroscience and beyond.

Spatial Proteomics of Single Hepatocytes with Multiplexed Data-Independent Acquisition (mDIA).

Spatially resolved mass spectrometry-based proteomics at single-cell resolution promises to provide insights into biological heterogeneity. We describe a protocol based on multiplexed data-independent acquisition (mDIA) with dimethyl labeling to enhance proteome depth, accuracy, and throughput while minimizing costs. It enables high-quality proteome analysis of single isolated hepatocytes and utilizes liver zonation for single-cell proteomics benchmarking. This adaptable, modular protocol will promote the use of single-cell proteomics in spatial biology.

EquiCP: Targeted Single-Cell Proteomics by Mass Spectrometry with Isobaric Labeled Multiplexing.

Nontargeted single-cell proteomics analysis by mass spectrometry with sample multiplexing utilizing isobaric labeling is often performed using a carrier proteome. The presented protocol describes a targeted approach that replaces the carrier proteome with a set of synthetic peptides from selected proteins, which improves the identification and quantification of these proteins in single human cells.

Standardized Workflow for Mass-Spectrometry-Based Single-Cell Proteomics Data Processing and Analysis Using the scp Package.

Mass-spectrometry (MS)-based single-cell proteomics (SCP) explores cellular heterogeneity by focusing on the functional effectors of the cells-proteins. However, extracting meaningful biological information from MS data is far from trivial, especially with single cells. Currently, data analysis workflows are substantially different from one research team to another. Moreover, it is difficult to evaluate pipelines as ground truths are missing. Our team has developed the R/Bioconductor package called scp to provide a standardized framework for SCP data analysis. It relies on the widely used QFeatures and SingleCellExperiment data structures. In addition, we used a design containing cell lines mixed in known proportions to generate controlled variability for data analysis benchmarking. In this chapter, we provide a flexible data analysis protocol for SCP data using the scp package together with comprehensive explanations at each step of the processing. Our main steps are quality control on the feature and cell level, aggregation of the raw data into peptides and proteins, normalization, and batch correction. We validate our workflow using our ground truth data set. We illustrate how to use this modular, standardized framework and highlight some crucial steps.

Single-Cell Proteomics Analysis with Tecan Uno and SCREEN Workflow.

With advances in sample preparation, small-volume liquid dispensing technologies, high-resolution MS/MS instrumentation, and data acquisition methodologies, it has become increasingly possible to confidently investigate the heterogeneous proteome found within individual cells. In this chapter, we present an automated high-throughput sample preparation workflow based on the Tecan Uno instrument for quantitative single-cell mass spectrometry-based proteomics. Cells are analyzed by the Single-Cell Proteome Analysis platform (SCREEN), which was introduced earlier and provides deeper proteome coverage across single cells.

Bioinformatics Pipeline for Processing Single-Cell Data.

Single-cell proteomics can offer valuable insights into dynamic cellular interactions, but identifying proteins at this level is challenging due to their low abundance. In this chapter, we present a state-of-the-art bioinformatics pipeline for single-cell proteomics that combines the search engine Sage (via SearchGUI), identification rescoring with MS2Rescore, quantification through FlashLFQ, and differential expression analysis using MSqRob2. MS2Rescore leverages LC-MS/MS behavior predictors, such as MS2PIP and DeepLC, to recalibrate scores with Percolator or mokapot. Combining these tools into a unified pipeline, this approach improves the detection of low-abundance peptides, resulting in increased identifications while maintaining stringent FDR thresholds.

Plasma-based proteomic profiling identifies the distinct regulation of proteins in hyperplasia and endometrial cancer.

BACKGROUND: Among gynaecological malignancies, endometrial cancer (EC) is the most prevalent type of uterine cancer affecting women. This study explored the proteomic profiles of plasma samples obtained from EC patients, those with hyperplasia (Hy), and a control group (CO). A combination of techniques, such as 2D-DIGE, mass spectrometry, and bioinformatics, including pathway analysis, was used to identify proteins with modified expression levels, biomarkers and their associated metabolic pathways in these groups. METHODS: Thirty-four patients, categorized into three groups-10 with EC, 12 with Hy, and 12 CO-between the ages of 46 and 75 years old were included in the study. Untargeted proteomic analysis was carried out using two-dimensional difference in gel electrophoresis (2D-DIGE) coupled with matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF-MS). RESULTS: In all three groups, 114 proteins that were significantly (p ≤ 0.05 and fold change ≥ 1.5) altered were successfully identified using peptide mass fingerprints (PMFs). Compared with those in the control group (CO), the EC samples had 85 differentially expressed proteins (39 upregulated and 46 downregulated), and in the Hy group, 81 proteins were dysregulated (40 upregulated and 41 downregulated) compared to those in the CO group, while 33 proteins exhibited differential regulation (12 upregulated and 21 downregulated) in the EC plasma samples compared to those in the Hy group. Vitamin D binding protein and complement C3 distinguished Hy and EC from CO with the greatest changes in expression. Among the differentially expressed proteins identified, enzymes with catalytic activity represented the largest group (42.9%). In terms of biological processes, most of the proteins were involved in cellular processes (28.8%), followed by metabolic processes (16.7%). STRING analysis for protein interactions revealed that the significantly differentially abundant proteins in the three groups are involved in three main biological processes: signalling of complement and coagulation cascades, regulation of insulin-like growth factor (IGF) transport and uptake by insulin-like growth factor binding proteins (IGFBPs), and plasma lipoprotein assembly, remodelling, and clearance. CONCLUSION: The identified plasma protein markers have the potential to serve as biomarkers for differentiating between EC and Hy, as well as for early diagnosis and monitoring of cancer progression.

Development of an efficient, effective, and economical technology for proteome analysis.

We present an efficient, effective, and economical approach, named E3technology, for proteomics sample preparation. By immobilizing silica microparticles into the polytetrafluoroethylene matrix, we develop a robust membrane medium, which could serve as a reliable platform to generate proteomics-friendly samples in a rapid and low-cost fashion. We benchmark its performance using different formats and demonstrate them with a variety of sample types of varied complexity, quantity, and volume. Our data suggest that E3technology provides proteome-wide identification and quantitation performance equivalent or superior to many existing methods. We further propose an enhanced single-vessel approach, named E4technology, which performs on-filter in-cell digestion with minimal sample loss and high sensitivity, enabling low-input and low-cell proteomics. Lastly, we utilized the above technologies to investigate RNA-binding proteins and profile the intact bacterial cell proteome.