Ying Zhu

The paper develops nanoMAPS, a droplet-based magnetic affinity purification system for surfaceome profiling of 100-500 cells, improving recovery and reducing non-specific absorption.

This study identifies cell-type-specific carbon metabolism changes in poplar under combined abiotic stresses using multi-omics approaches.

This paper develops a high-throughput single-cell proteomic method for PBMCs, achieving 660 cells per day with 750 protein identifications per cell and identifying low-frequency cell types.

This study applies single-cell proteomics to Arabidopsis leaf mesophyll cells to identify drought stress-related proteins and changes in protein networks.

The paper introduces nanoSPINS, a platform for high-throughput single-cell multiomics that integrates transcriptomic and proteomic profiling from the same cells, demonstrating improved throughput and statistical power.

This paper introduces multi-tiered Dicers for microdissection, achieving better protein preservation and higher peptide/protein yield compared to LCM at 10-20 micron resolution.

The paper uses single-islet proteomics to analyze pseudo-temporal immune responses and beta-cell dysfunction in stage 1 T1D, identifying key pathways involved in islet dysfunction.

The paper introduces toma-scpMS, a method that improves quantification in multiplexed single cell proteomics by separating carrier and single cell proteomes during mass spectrometry.

This paper develops a spatial proteomics workflow to identify and map proteoforms in human kidney tissue, revealing spatially distinct proteomic profiles between glomeruli and tubules.

The paper introduces nanoSPLITS, a platform for simultaneous transcriptome and proteome profiling of single cells, and demonstrates its application in cell cycle regulation and cell type identification.

This study benchmarks label-free and TMT-MS2 methods for spatial proteome mapping, showing label-free provides deeper coverage and higher dynamic range, while TMT-MS2 offers faster throughput.

The paper develops a spatial proteomics method to map the human pancreatic islet microenvironment and identifies spatial gradients in RNA processing proteins.

This paper introduces TIFF, a method enhancing single-cell proteomics sensitivity and accuracy by filtering background ions and using 3D MS1 feature matching, achieving deep proteome analysis in single cells.

This paper introduces a nested nanowell chip to improve single-cell proteomics throughput and robustness, demonstrating the ability to quantify ~1500 proteins from ~100 cells with low abundance variation.

This paper introduces an ultrasensitive single-cell proteomics workflow that identifies over 1000 protein groups per mammalian cell using advanced mass spectrometry techniques.

This study identifies de novo CBX1 variants in three individuals with neurodevelopmental features and shows they cause dominant-negative effects by disrupting HP1β chromatin binding.