期刊
PLOS COMPUTATIONAL BIOLOGY
卷 9, 期 7, 页码 -出版社
PUBLIC LIBRARY SCIENCE
DOI: 10.1371/journal.pcbi.1003145
关键词
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资金
- Fannie and John Hertz Foundation
- Helen Hay Whitney Postdoctoral Fellowship
- DARPA Living Foundries Program
- New York Stem Cell Foundation-Robertson Investigator Award
- NIH EUREKA Award [1R01NS075421]
- NIH Transformative [R01 1R01GM104948]
- NIH Single Cell Grant [1 R01 EY023173]
- NIH [1R01DA029639, 1R01NS067199, 5R01NS063399, P01NS044393, 1R01NS074044]
- NSF CAREER Award [CBET 1053233]
- NSF [EFRI0835878, DMS1042134]
- Paul Allen Distinguished Investigator in Neuroscience Award
- SkTech
- Office of Naval Research
- NIH Centers of Excellence in Genomic Science [1P50HG005550]
- Chicago Biomedical Consortium
- Searle Funds at The Chicago Community Trust
- Directorate For Engineering
- Div Of Chem, Bioeng, Env, & Transp Sys [1053233] Funding Source: National Science Foundation
A molecular device that records time-varying signals would enable new approaches in neuroscience. We have recently proposed such a device, termed a molecular ticker tape, in which an engineered DNA polymerase (DNAP) writes time-varying signals into DNA in the form of nucleotide misincorporation patterns. Here, we define a theoretical framework quantifying the expected capabilities of molecular ticker tapes as a function of experimental parameters. We present a decoding algorithm for estimating time-dependent input signals, and DNAP kinetic parameters, directly from misincorporation rates as determined by sequencing. We explore the requirements for accurate signal decoding, particularly the constraints on (1) the polymerase biochemical parameters, and (2) the amplitude, temporal resolution, and duration of the time-varying input signals. Our results suggest that molecular recording devices with kinetic properties similar to natural polymerases could be used to perform experiments in which neural activity is compared across several experimental conditions, and that devices engineered by combining favorable biochemical properties from multiple known polymerases could potentially measure faster phenomena such as slow synchronization of neuronal oscillations. Sophisticated engineering of DNAPs is likely required to achieve molecular recording of neuronal activity with single-spike temporal resolution over experimentally relevant timescales.
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