As it stands today, traditional/standard protein characterization methods have insufficient limits-of-detection,dynamic range, throughput, cost, accuracy, sensitivity, scale, and/or some combination thereof. Because ofthese shortcomings, there are no currently available methods capable of meeting the needs within theproteomics field: single-cell, proteome-wide characterization/sequencing. New technology must be developed toadvance and revolutionize the field of proteomics, similar to how inventive nanopore-based technologydevelopments have opened and accelerated the fields of genomics and transcriptomics. Nanopore-basedtechnology is a very powerful method for molecular characterization and because of this, it has the potential toalso shape the future of protein sequencing. It is one of only a few potential approaches that represent a viablepath to direct, high-throughput, high-sensitivity, single-molecule, protein sequencing capable of characterizingboth low- and high-abundance proteins, which is an absolute necessity for achieving the accuracy and dynamicrange required for comprehensive, enabling protein analyses. During this program, Electronic BioSciences, Inc.(EBS) aims to develop a completely new nanopore-based technology that will enable de novo proteinsequencing. During this Phase I project, we will develop and build a novel protein sequencing system prototype,fully assess and optimize the associated workflow/methodology for highly controlled and versatile protein/peptidecharacterization, and demonstrate initial sequencing for various proteins and peptides. At the conclusion of thisproject, we will have successfully shown concept feasibility for practical nanopore-based protein sequencing.
Public Health Relevance Statement: Project Narrative
The technology developed during this program will yield the first-ever method for direct, high-throughput,
single-molecule, protein sequencing capable of characterizing both low- and high-abundance proteins. A de
novo, high-accuracy proteomics sequencing technology that can accurately distinguish all 20 natural amino
acids, free from costly labels and error-prone enzymes/motors, will greatly advance proteomics research and
propel the associated diagnostics, prognostics, and therapeutic intervention strategies into the future.
Project Terms: |
