Single-Molecule Proteomics using Protein Identification by Short-epitope Mapping

Presented By:
Dr. Parag Mallick

Speaker Biography:
Dr. Parag Mallick is recognized as an influential figure in the global proteomics community based on his innovative research and entrepreneurial success. His original training is in both computer science and biochemistry from Washington University. He obtained his Ph.D. from UCLA in Chemistry & Biochemistry, where he worked with Dr. David Eisenberg. He then completed his post-doctoral training with proteomics pioneer Ruedi Aebersold at the Institute for Systems Biology where he worked on defining the biophysical origins of proteotypic peptides. He also did early work in proteogenomics and proteomics-based biomarker discovery. As an Associate Professor at Stanford, his lab uses a mix of quantitative proteomics, machine learning, and nanotechnology to perform systems biology studies of cancer initiation and progression that drive precision medicine approaches for cancer diagnosis and treatment. Additionally, as the initiator and PI of the ProteoWizard Project, his group is at the forefront of open science, developing open-source multi-omics data analysis methods. Beyond his academic pursuits, he is the founder and chief scientist of Nautilus Biotechnology (Nasdaq: NAUT), a company developing a large-scale, single-molecule platform for comprehensively quantifying the proteome. Nautilus’ objective is to enable important discoveries in biological research and healthcare by making it possible for every lab and researcher to benefit from this emerging frontier of biological science.

Webinar:
Single-Molecule Proteomics using Protein Identification by Short-epitope Mapping

Webinar Abstract:
The field of proteomics is poised for a single-molecule revolution – enabling more comprehensive analysis of the proteins in a sample with increased sensitivity, reproducibility, and accessibility. Here we demonstrate Protein Identification by Short-epitope Mapping (PrISM). PrISM is a single-molecule analysis method where intact proteins are immobilized, iteratively probed with multi-affinity probes, and machine learning is applied to convert binding patterns to protein identification and quantification. PrISM uses non-traditional affinity reagents with high affinity and low specificity that bind to short epitopes in multiple proteins. Simulations using these multi-affinity probes show that the accumulated information from multiple rounds of detection of short (2-4 amino acid) epitopes enables identification of more than 95% of the human proteome with just 300 probes. Model proteins were conjugated to DNA nanoparticles and deposited on a high-density patterned flow cell at optically resolvable locations. We acquired PrISM data using 30 multi-affinity probes targeting trimer or tetramer sequences. We demonstrate identification of individual protein molecules through iterative probing with our multi-affinity probes. By combining single-molecule analysis, intact (non-digested) proteins, and iterative probing, PrISM provides a new tool for the quantitation of proteins enabling new exploration of the proteome.

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