Xiaojing Sui, PhD

Postdoctoral Fellow @ Northwestern University

About

Accomplished and highly collaborative multidisciplinary scientist with 15 years of experience applying mass spectrometry–based quantitative proteomics and large-scale data analysis to understand protein homeostasis in aging and neurodegenerative diseases. Recognized as a Rising Star in Proteomics and Metabolomics 2024. Expert in developing proteomic workflows, including affinity purification, proximity labeling, and protein structural and compositional analysis, built from the ground up using molecular biology and genetics in model organisms. Highly skilled in bioinformatics and multi-omics integration using Python and HPC platforms. Proven track record of cross-disciplinary collaboration and leading complex, multi-institutional research programs.Creator of interactive bioinformatics platforms for the scientific community, including:1. Protein Whisper: An interactive structural proteomics platform integrating AlphaFold-based 3D visualization, peptide-level conformational dynamics profiling, and protein solubility/abundance dynamics across aging and diverse cellular perturbations. (https://proteinwhisperapp-g949efa9imn35reycubkov.streamlit.app/)2. Proteostasis Network: An interactive web tool for searching and exploring PN genes. (https://proteostasisnetwork.streamlit.app/)

Country

United States

City

Evanston

Industry

Higher Education

Skill

aging, Computational Biology, Neurodegenerative Disease, Python (Programming Language), Structural Biology, Fluorescence Microscopy, Proteomics, Mass Spectrometry, 2D-DIGE, Western Blotting, ELISA, Cell Culture, Atomic force microscopy, SDS-PAGE, Transfection, Biomarker Discovery, Immunohistochemistry, Immunofluorescence, HPLC, HPLC-MS

Experience

Postdoctoral Fellow

Northwestern University

2019-10 - Present · 7 yrs

Evanston, Illinois

• Developed a multiplexed limited-proteolysis coupled with LC-MS/MS (TMT-LiP-MS) workflow to monitor conformational changes of thousands of proteins simultaneously during aging. • Built computational pipelines integrating age-dependent proteome-wide structural changes with AlphaFold2, PDB, UniProt and InterPro databases, enabling residue-level conformational dynamics analysis. • Automated large-scale 3D structural comparison and visualization of proteome-wide conformational shifts using PyMOL, ChimeraX and Python, enabling rapid structural interrogation across thousands of proteins. • Applied machine learning approaches to identify β-sheet and intrinsically disordered regions as key features of conformationally metastable proteins during aging. • Established a proximity labeling-based affinity purification strategy for isolating native, active proteasome complex for biochemical and cryo-EM analyses. • Mentored junior scientists in LC-MS/MS workflows, large-scale data analysis and CRISPR-Cas9 genome editing; presented research findings at prestigious conferences. • Secured multiple competitive awards, including three postdoctoral fellowships and one research grant.