Currently, most mass spectrometric (MS) analyses for proteomics are performed in sequential mode, wherein various species in a sample are selected and interrogated one after another. As a consequence of the finite time needed to examine each species in turn, sequential mode MS suffers from inescapable limitations in sensitivity, speed and ability to analyze all ions, especially when the composition of the ion beam is complex and rapidly changing. These limitations have kept vast tracts of biology and biomedicine, including, for example, deep single cell proteome analysis, out of reach of the current MS technology. In the present proposal, we posit that sensitivity, speed and dynamic range can be vastly improved by performing MS in parallel (by analogy to Next Generation DNA Sequencing), thus overcoming the technical barriers inherent to current commercial mass spectrometers that operate largely in sequential mode. Here, we propose to develop new MS instrumentation to execute MS in a massively parallel manner, with two major objectives in mind: Objective 1. Increase the sensitivity, speed and depth of proteome analyses by up to and ultimately beyond 1000-fold. The current sequential MS approaches can be likened to sampling the Niagara Falls with a bucket, where the majority of the sample is wasted. Our proposed parallel MS technology is designed to eliminate this immense waste. Objective 2. Filter noise in real time to eliminate unwanted ion background prior to MS analysis, thereby maximizing the MS utilization of the sample ions of interest and the resulting signal-to- noise ratios, as well as providing increased dynamic range to measure very low abundance components in the presence of highly abundant components. Successful attainment of these objectives will allow deep, comprehensive, high throughput analyses of proteomes in cases where sample availability is limiting, where the components of interest elude detection due to their low abundance, or when single cell analysis is needed to address the biological or biomedical question at hand. Success in this endeavor will propel forward many areas of basic and applied biomedical research that require proteomic analyses in a manner analogous to the immense progress that has been made through development of Next Generation DNA Sequencing.

Public Health Relevance

The proposal will develop a new technology, designed for ready utilization by the biomedical researcher, which will allow deep, comprehensive, high throughput analyses of the protein components of living organisms (i.e., their proteomes). The technology, which we term Next Generation Mass Spectrometry, promises to be transformative for vast tracts of biology and biomedicine that are currently largely out of reach, including as examples: cellular and organismal biology through deep, high throughput single cell proteomic analysis; immunology through time/state-resolved single cell proteomic analysis; cancer biology through deep proteomic analysis of small collections of cancer cells; infectious disease through analysis of the modulation of host proteomes by pathogens during infection; normal and abnormal development through comparative analyses of the proteomes of sequential developmental states; structural biology through deep analysis of the products of protein crosslinking; cellular signaling through the comprehensive analysis of time/state-resolved posttranslational modifications; chromosomal biology through the analysis of proteins on single specified loci; brain biology through thorough proteomic analyses of specific synapse connections as well as of specific cell types; as well as personalized medicine in general.

Agency
National Institute of Health (NIH)
Institute
National Institute of General Medical Sciences (NIGMS)
Type
Research Project (R01)
Project #
1R01GM136654-01
Application #
9790251
Study Section
Special Emphasis Panel (ZRG1)
Program Officer
Smith, Ward
Project Start
2019-09-01
Project End
2024-08-31
Budget Start
2019-09-01
Budget End
2020-08-31
Support Year
1
Fiscal Year
2019
Total Cost
Indirect Cost
Name
Rockefeller University
Department
Internal Medicine/Medicine
Type
Graduate Schools
DUNS #
071037113
City
New York
State
NY
Country
United States
Zip Code
10065