High-Throughput, Comprehensive Single-Cell Proteomic Analysis of Xenopus laevis Embryos at the 50-Cell Stage Using a Microplate-Based MICROFASP System

Ultrasensitive Proteomics of Trace Cardiac Tissues with Anchor-Nanoparticles

Pathological cardiac hypertrophy is a complex process that often leads to heart failure. Label-free proteomics has emerged as an important platform to reveal protein variations and to elucidate the mechanisms of cardiac hypertrophy. Endomyocardial biopsy is a minimally invasive technique for sampling cardiac tissue, but it yields only limited amounts of an ethically permissible specimen. After regular pathological examination, the remaining trace samples pose significant challenges for effective protein extraction and mass spectrometry analysis. Herein, we developed trace cardiac tissue proteomics based on the anchor-nanoparticles (TCPA) method. We identified an average of 6666 protein groups using ∼50 μg of myocardial interventricular septum samples by TCPA. We then applied TCPA to acquire proteomics from patients' cardiac samples both diagnosed as hypertrophic hearts and myocarditis controls and identified significant alterations in pathways such as regulation of actin cytoskeleton, oxidative phosphorylation, and cGMP-PKG signaling pathway. Moreover, we found multiple lipid metabolic pathways to be dysregulated in transthyretin cardiac amyloidosis compared to other types of cardiac hypertrophy. TCPA offers a new technique for studying pathological cardiac hypertrophy and can serve as a platform toolbox for proteomic research in other cardiac diseases.

Uncovering biology by single-cell proteomics

Recent technological advances have opened the door to single-cell proteomics that can answer key biological questions regarding how protein expression, post-translational modifications, and protein interactions dictate cell state in health and disease.

Separation methods in single-cell proteomics: RPLC or CE?

Cellular heterogeneity is commonly investigated using single-cell genomics and transcriptomics to investigate biological questions such as disease mechanism, therapeutic screening, and genomic and transcriptomic diversity between cellular populations and subpopulations at the cellular level. Single-cell mass spectrometry (MS)-based proteomics enables the high-throughput examination of protein expression at the single-cell level with wide applicability, and with spatial and temporal resolution, applicable to the study of cellular development, disease, effect of treatment, etc. The study of single-cell proteomics has lagged behind genomics and transcriptomics largely because proteins from single-cell samples cannot be amplified as DNA and RNA can using well established techniques such as PCR. Therefore, analytical methods must be robust, reproducible, and sensitive enough to detect the very small amount of protein within a single cell. To this end, nearly every step of the proteomics process has been extensively altered and improved to facilitate the proteomics analysis of single cells including cell counting and sorting, lysis, protein digestion, sample cleanup, separation, MS data acquisition, and data analysis. Here, we have reviewed recent advances in single-cell protein separation using nano reversed phase liquid chromatography (nRPLC) and capillary electrophoresis (CE) to inform application driven selection of separation techniques in the laboratory setting.

Seamlessly Integrated Miniaturized Filter-Aided Sample Preparation Method to Fractionation Techniques for Fast, Loss-Less, and In-Depth Proteomics Analysis of 1 μg of Cell Lysates at Low Cost

We report an integrated platform that enabled a seamlessly coupling miniaturized filter-aided sample preparation (MICROFASP) method to high-pH reversed phase (RP) or strong cation exchange (SCX) microreactors for low-loss sample preparation and fractionation of 1 μg of cell lysates prior to LC-ESI-MS/MS analysis. Due to the reduced size of the microreactor, only 5 μL of buffer volume is required to generate each fraction, which speeds both elution and lyophilization. The fraction was directly eluted into an autosampler insert vial for LC-MS analysis to reduce sample transfer steps and minimize sample loss as well as contamination. The flow-through sample generated during the loading step was also collected and analyzed. The integrated platform generated 48,890 unique peptides and 4723 protein groups from 1 μg of a K562 cell lysate using MICROFASP and C18 microreactor-based high-pH RP fractionation methods, which are comparable with the state-of-the-art result using in-StageTip sample preparation and nanoflow RPLC-based fractionation methods but with a significant reduction in cost and time. Both pH gradient elution and salt gradient elution approaches provide high reproducibility for the SCX microreactor-based fractionation method. This integrated platform has significant potential in deep proteomics analysis of mass-limited samples with reduced time and equipment requirements.

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.