A simple dual online ultra-high pressure liquid chromatography system (sDO-UHPLC) for high throughput proteome analysis

Proteogenomic characterization of molecular and cellular targets for treatment-resistant subtypes in locally advanced cervical cancers

We report proteogenomic analysis of locally advanced cervical cancer (LACC). Exome-seq data revealed predominant alterations of keratinization-TP53 regulation and O-glycosylation-TP53 regulation axes in squamous and adeno-LACC, respectively, compared to in early-stage cervical cancer. Integrated clustering of mRNA, protein, and phosphorylation data identified six subtypes (Sub1-6) of LACC among which Sub3, 5, and 6 showed the treatment-resistant nature with poor local recurrence-free survival. Elevated immune and extracellular matrix (ECM) activation mediated by activated stroma (PDGFD and CXCL1high fibroblasts) characterized the immune-hot Sub3 enriched with MUC5AChigh epithelial cells (ECs). Increased epithelial-mesenchymal-transition (EMT) and ECM remodeling characterized the immune-cold squamous Sub5 enriched with PGK1 and CXCL10high ECs. We further demonstrated that CIC mutations could trigger EMT activation by upregulating ETV4, and the elevation of the immune checkpoint PVR and neutrophil-like myeloid-derived suppressive cells (FCN1 and FCGR3Bhigh macrophages) could cause suppression of T-cell activation in Sub5. Increased O-linked glycosylation of mucin characterized adeno-LACC Sub6 enriched with MUC5AChigh ECs. These results provide a battery of somatic mutations, cellular pathways, and cellular players that can be used to predict treatment-resistant LACC subtypes and can serve as potential therapeutic targets for these LACC subtypes.

Hypoxia increases methylated histones to prevent histone clipping and heterochromatin redistribution during Raf-induced senescence

Hypoxia enhances histone methylation by inhibiting oxygen- and α-ketoglutarate-dependent demethylases, resulting in increased methylated histones. This study reveals how hypoxia-induced methylation affects histone clipping and the reorganization of heterochromatin into senescence-associated heterochromatin foci (SAHF) during oncogene-induced senescence (OIS) in IMR90 human fibroblasts. Notably, using top-down proteomics, we discovered specific cleavage sites targeted by Cathepsin L (CTSL) in H3, H2B and H4 during Raf activation, identifying novel sites in H2B and H4. Hypoxia counteracts CTSL-mediated histone clipping by promoting methylation without affecting CTSL's activity. This increase in methylation under hypoxia protects against clipping, reshaping the epigenetic landscape and influencing chromatin accessibility, as shown by ATAC-seq analysis. These insights underscore the pivotal role of hypoxia-induced histone methylation in protecting chromatin from significant epigenetic shifts during cellular aging.

Wideband PRM: Highly Accurate and Sensitive Method for High-Throughput Targeted Proteomics

Targeted mass spectrometry (MS) approaches, which are powerful methods for uniquely and confidently quantifying a specific panel of proteins in complex biological samples, play a crucial role in validating and clinically translating protein biomarkers discovered through global proteomic profiling. Common targeted MS methods, such as multiple reaction monitoring (MRM) and parallel-reaction monitoring (PRM), employ specific mass spectrometric technologies to quantify protein levels by comparing the transitions of surrogate endogenous (ENDO) peptides with those of stable isotope-labeled (SIL) peptide counterparts. These methods utilizing amino acid analyzed (AAA) SIL peptides warrant sensitive and precise measurements required for targeted MS assays. Compared with MRM, PRM provides higher experimental throughput by simultaneously acquiring all transitions of the target peptides and thereby compensates for different ion suppressions among transitions of a target peptide. However, PRM still suffers different ion suppressions between ENDO and SIL peptides due to spray instability, as the ENDO and SIL peptides were monitored at different liquid chromatography (LC) retention times. Here we introduce a new targeted MS method, termed wideband PRM (WBPRM), that is designed for high-throughput targeted MS analysis. WBPRM employs a wide isolation window for simultaneous fragmentation of both ENDO and SIL peptides along with multiplexed single ion monitoring (SIM) scans for enhanced MS sensitivity of the target peptides. Compared with PRM, WBPRM was demonstrated to provide increased sensitivity, precision, and reproducibility of quantitative measurements of target peptides with increased throughput, allowing more target peptide measurements in a shortened experiment time. WBPRM is a straightforward adaptation to a manufacturer-provided MS method, making it an easily implementable technique, particularly in complex biological samples where the demand for higher precision, sensitivity, and efficiency is paramount.

High-Throughput Proteomics Enabled by a Fully Automated Dual-Trap and Dual-Column LC-MS

This Technical Note describes a dual-column liquid chromatography system coupled to mass spectrometry (LC-MS) for high-throughput bottom-up proteomic analysis. This system made full use of two 2-position 10-port valves and a binary pump with an integrated loading pump of a commercial LC instrument to provide successive operation of two parallel subsystems. Each subsystem consisted of a set of trap columns and an analytical column. A T-junction union was used to split the mobile phase from the loading pump into two parts. This allowed one set of columns to be washed and equilibrated, followed by the injection of the next sample, while the previous sample was eluting and being analyzed on the other set of columns, thereby greatly increasing the analysis throughput. This approach showed high reproducibility for the analysis of HeLa tryptic digests with average relative standard deviation (RSD) values of 1.75%, 6.90%, and 5.19% for the identification number of proteins, peptides, and peptide-spectrum matches (PSMs), respectively, across 10 consecutive runs. The capacity for peptide and protein identification, as well as proteome depth, of the dual-column LC system was comparable to a conventional single-column system. Due to its simple equipment requirements and set up process, this method should be highly accessible for other laboratories.

Targeted proteomics data interpretation with DeepMRM

Targeted proteomics is widely utilized in clinical proteomics; however, researchers often devote substantial time to manual data interpretation, which hinders the transferability, reproducibility, and scalability of this approach. We introduce DeepMRM, a software package based on deep learning algorithms for object detection developed to minimize manual intervention in targeted proteomics data analysis. DeepMRM was evaluated on internal and public datasets, demonstrating superior accuracy compared with the community standard tool Skyline. To promote widespread adoption, we have incorporated a stand-alone graphical user interface for DeepMRM and integrated its algorithm into the Skyline software package as an external tool.

Multidimensional Separations in Top-Down Proteomics

Top-down proteomics (TDP) identifies, quantifies, and characterizes proteins at the intact proteoform level in complex biological samples to understand proteoform function and cellular mechanisms. However, analyzing complex biological samples using TDP is still challenging due to high sample complexity and wide dynamic range. High-resolution separation methods are often applied prior to mass spectrometry (MS) analysis to decrease sample complexity and increase proteomics throughput. These separation methods, however, may not be efficient enough to characterize low abundance intact proteins in complex samples. As such, multidimensional separation techniques (combination of two or more separation methods with high orthogonality) have been developed and applied that demonstrate improved separation resolution and more comprehensive identification in TDP. A suite of multidimensional separation methods that couple various types of liquid chromatography (LC), capillary electrophoresis (CE), and/or gel electrophoresis-based separation approaches have been developed and applied in TDP to analyze complex biological samples. Here, we reviewed multidimensional separation strategies employed for TDP, summarized current applications, and discussed the gaps that may be addressed in the future.

Chromatographic separation of peptides and proteins for characterization of proteomes

Characterization of proteomes aims to comprehensively characterize proteins in cells or tissues via two main strategies: (1) bottom-up strategy based on the separation and identification of enzymatic peptides; (2) top-down strategy based on the separation and identification of intact proteins. However, it is challenged by the high complexity of proteomes. Consequently, the improvements in peptide and protein separation technologies for simplifying the sample should be critical. In this feature article, separation columns for peptide and protein separation were introduced, and peptide separation technologies for bottom-up proteomic analysis as well as protein separation technologies for top-down proteomic analysis were summarized. The achievement, recent development, limitation and future trends are discussed. Besides, the outlook on challenges and future directions of chromatographic separation in the field of proteomics was also presented.

Novel Online Three-Dimensional Separation Expands the Detectable Functional Landscape of Cellular Phosphoproteome

Protein phosphorylation is a prevalent post-translational modification that regulates essentially every aspect of cellular processes. Currently, liquid chromatography-tandem mass spectrometry (LC-MS/MS) with an extensive offline sample fractionation and a phosphopeptide enrichment method is a best practice for deep phosphoproteome profiling, but balancing throughput and profiling depth remains a practical challenge. We present an online three-dimensional separation method for ultradeep phosphoproteome profiling that combines an online two-dimensional liquid chromatography separation and an additional gas-phase separation. This method identified over 100,000 phosphopeptides (>60,000 phosphosites) in HeLa cells during 1.5 days of data acquisition, and the largest HeLa cell phosphoproteome significantly expanded the detectable functional landscape of cellular phosphoproteome.

Label-Free Profiling of up to 200 Single-Cell Proteomes per Day Using a Dual-Column Nanoflow Liquid Chromatography Platform

Single-cell proteomics (SCP) has great potential to advance biomedical research and personalized medicine. The sensitivity of such measurements increases with low-flow separations (<100 nL/min) due to improved ionization efficiency, but the time required for sample loading, column washing, and regeneration in these systems can lead to low measurement throughput and inefficient utilization of the mass spectrometer. Herein, we developed a two-column liquid chromatography (LC) system that dramatically increases the throughput of label-free SCP using two parallel subsystems to multiplex sample loading, online desalting, analysis, and column regeneration. The integration of MS1-based feature matching increased proteome coverage when short LC gradients were used. The high-throughput LC system was reproducible between the columns, with a 4% difference in median peptide abundance and a median CV of 18% across 100 replicate analyses of a single-cell-sized peptide standard. An average of 621, 774, 952, and 1622 protein groups were identified with total analysis times of 7, 10, 15, and 30 min, corresponding to a measurement throughput of 206, 144, 96, and 48 samples per day, respectively. When applied to single HeLa cells, we identified nearly 1000 protein groups per cell using 30 min cycles and 660 protein groups per cell for 15 min cycles. We explored the possibility of measuring cancer therapeutic targets with a pilot study comparing the K562 and Jurkat leukemia cell lines. This work demonstrates the feasibility of high-throughput label-free single-cell proteomics.

Label-Free Quantitative Proteome Profiling of Cerebrospinal Fluid from a Rat Stroke Model with Stem Cell Therapy

Human adipose-derived mesenchymal stem cells (hAMSCs) are capable of immunomodulation and regeneration after neural injury. For these reasons, hAMSCs have been investigated as a promising stem cell candidate for stroke treatment. However, noninvasive experiments studying the effects of grafted stem cells in the host brain have not yet been reported. Cerebrospinal fluid (CSF), which can be collected without sacrificing the subject, is involved in physiological control of the brain and reflects the pathophysiology of various neurological disorders of the central nervous system (CNS). Following stem cell transplantation in a stroke model, quantitative analysis of CSF proteome changes can potentially reveal the therapeutic effect of stem cells on the host CNS. We examined hAMSC-secreted proteins obtained from serum-free culture medium by liquid chromatography-tandem mass spectrometry (LC-MS/MS), which identified several extracellular matrix proteins, supporting the well-known active paracrine function of hAMSCs. Subsequently, we performed label-free quantitative proteomic analysis on CSF samples from rat stroke models intravenously injected with hAMSC (experimental) or phosphate buffered saline (control). In total, 524 proteins were identified; among them, 125 and 91 proteins were increased and decreased with hAMSC treatment, respectively. Furthermore, gene set enrichment analysis revealed three proteins, 14-3-3 theta, MAG, and neurocan, that showed significant increases in the hAMSC-treated model; these proteins are core members of neurotrophin signaling, nerve growth factor (NGF) signaling, and glycosaminoglycan metabolism, respectively. Subsequent histological and neurologic function experiments validated proliferative neurogenesis in the hAMSC-treated stroke model. We conclude that (i) intravenous injection of hAMSCs can induce neurologic recovery in a rat stroke model and (ii) CSF may reflect the therapeutic effect of hAMSCs. Additionally, proteins as 14-3-3 theta, MAG, and neurocan could be considered as potential CSF biomarkers of neuroregeneration. These CSF proteome profiling results would be utilized as valuable resource in further stroke studies.

MS1-Level Proteome Quantification Platform Allowing Maximally Increased Multiplexity for SILAC and In Vitro Chemical Labeling

Quantitative proteomic platforms based on precursor intensity in mass spectrometry (MS1-level) uniquely support in vivo metabolic labeling with superior quantification accuracy but suffer from limited multiplexity (≤3-plex) and frequent missing quantities. Here we present a new MS1-level quantification platform that allows maximal multiplexing with high quantification accuracy and precision for the given labeling scheme. The platform currently comprises 6-plex in vivo SILAC or in vitro diethylation labeling with a dedicated algorithm and is also expandable to higher multiplexity (e.g., nine-plex for SILAC). For complex samples with broad dynamic ranges such as total cell lysates, our platform performs highly accurately and free of missing quantities. Furthermore, we successfully applied our method to measure protein synthesis rate under heat shock response in human cells by 6-plex pulsed SILAC experiments, demonstrating the unique biological merits of our in vivo platform to disclose translational regulations for cellular response to stress.

Comprehensive proteome and phosphoproteome profiling shows negligible influence of RNAlater on protein abundance and phosphorylation

Certain tumors such as pancreatic ductal adenocarcinoma (PDAC) are known to contain a variety of hydrolytic enzymes including RNases and proteases that may lead to degradation of RNA and proteins during sample processing. For such tumor tissues with RNA instability, RNAlater containing a high concentration of quaternary ammonium sulfates that denature RNA-hydrolyzing enzymes is often used to protect RNAs from hydrolysis. Although a few studies have been carried out to determine the effect of RNAlater on DNA and RNA, whether RNAlater influences the proteome and phosphoproteome is largely unknown. In this study we carried out a systematic and comprehensive analysis of the effect of RNAlater on the proteome and phosphoproteome using high-resolution mass spectrometry. PDAC tissues from three patients were individually pulverized and the tissue powders of each patient were divided into two portions, one of which was incubated in RNAlater at 4 °C for 24 h (RNAlater tissue) while the other was kept at - 80 °C (frozen tissue). Comprehensive quantitative profiling experiments on the RNAlater tissues and the frozen tissues resulted in the identification of 99,136 distinct peptides of 8803 protein groups and 17,345 phosphopeptides of 16,436 phosphosites. The data exhibited no significant quantitative changes in both proteins and phosphorylation between the RNAlater tissues and the frozen tissue. In addition, the phosphoproteome data showed heterogeneously activated pathways among the three patients that were not altered by RNAlater. These results indicate that the tissue preservation method using RNAlater can be effectively used on PDAC tissues for proteogenomic studies where preservation of intact DNA, RNA and proteins is prerequisite. Data from this study are available via ProteomeXchange with the identifier PXD010710.