Evidence map›Paper›PMID 28459860›Full record

ArticlePLoS computational biology2017

Nucleotide-time alignment for molecular recorders.

Thaddeus R Cybulski, Edward S Boyden, George M Church, Keith E J Tyo, Konrad P Kording

Open access · goldAbstract read
In one paragraph

Article in PLoS computational biology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact, top 95% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed, 0 citations in OpenAlex.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors at 3 institutions in 1 country.

Thaddeus R CybulskiDepartment of Physical Medicine and Rehabilitation, Rehabilitation Institute of Chicago, Northwestern University, Chicago, Illinois, United States of America.ORCID 0000-0003-0613-7617
Edward S BoydenMedia Lab, Massachusetts Institute of Technology, Cambridge, Massachusetts, United States of America.
George M ChurchBiophysics Program, Harvard University, Boston, Massachusetts, United States of America.
Keith E J TyoDepartment of Chemical and Biological Engineering, Northwestern University, Evanston, Illinois, United States of America.ORCID 0000-0002-2342-0687
Konrad P KordingDepartment of Physical Medicine and Rehabilitation, Rehabilitation Institute of Chicago, Northwestern University, Chicago, Illinois, United States of America.
Northwestern University · USHarvard University · USMcGovern Institute for Brain Research · US

Funding

MEDICAL SCIENTIST TRAINING PROGRAMT32GM008152 · NIGMS · NORTHWESTERN UNIVERSITY AT CHICAGO · PI ARDEHALI, HOSSEIN · 1987 to 2021
$24.0M
Recording neural activities onto DNAR01MH103910 · NIMH · UNIVERSITY OF PENNSYLVANIA · PI BOYDEN, EDWARD S., CHURCH, GEORGE M · 2013 to 2017
$9.5M
Millisecond-Timescale Whole-Brain Neural Activity Mapping in Health and DiseaseDP1NS087724 · NINDS · MASSACHUSETTS INSTITUTE OF TECHNOLOGY · PI BOYDEN, EDWARD S. · 2013 to 2017
$3.9M
NIGMS NIH HHS T32 GM008152NIMH NIH HHS R01 MH103910NINDS NIH HHS DP1 NS087724
6 · The paper itself

Abstract

Using a DNA polymerase to record intracellular calcium levels has been proposed as a novel neural recording technique, promising massive-scale, single-cell resolution monitoring of large portions of the brain. This technique relies on local storage of neural activity in strands of DNA, followed by offline analysis of that DNA. In simple implementations of this scheme, the time when each nucleotide was written cannot be determined directly by post-hoc DNA sequencing; the timing data must be estimated instead. Here, we use a Dynamic Time Warping-based algorithm to perform this estimation, exploiting correlations between neural activity and observed experimental variables to translate DNA-based signals to an estimate of neural activity over time. This algorithm improves the parallelizability of traditional Dynamic Time Warping, allowing several-fold increases in computation speed. The algorithm also provides a solution to several critical problems with the molecular recording paradigm: determining recording start times and coping with DNA polymerase pausing. The algorithm can generally locate DNA-based records to within <10% of a recording window, allowing for the estimation of unobserved incorporation times and latent neural tunings. We apply our technique to an in silico motor control neuroscience experiment, using the algorithm to estimate both timings of DNA-based data and the directional tuning of motor cortical cells during a center-out reaching task. We also use this algorithm to explore the impact of polymerase characteristics on system performance, determining the precision of a molecular recorder as a function of its kinetic and error-generating properties. We find useful ranges of properties for DNA polymerase-based recorders, providing guidance for future protein engineering attempts. This work demonstrates a useful general extension to dynamic alignment algorithms, as well as direct applications of that extension toward the development of molecular recorders, providing a necessary stepping stone for future biological work.

Indexed as

AlgorithmsDNANucleotidesCalciumComputational BiologyComputer SimulationDNA-Directed DNA PolymeraseModels, BiologicalNeuronsNeurosciencesSingle-Cell AnalysisTime FactorsCalciumDNADNA-Directed DNA PolymeraseNucleotides

Identifiers

PMID28459860
PMCPMC5432193
OpenAlexW2610995603

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.