Connecting the dots across time: reconstruction of single-cell signalling trajectories using time-stamped data

Sayak Mukherjee; David Stewart; William Stewart; Lewis L Lanier; Jayajit Das

doi:10.1098/rsos.170811

Back

Connecting the dots across time: reconstruction of single-cell signalling trajectories using time-stamped data

Journal article

Open access

Peer reviewed

Connecting the dots across time: reconstruction of single-cell signalling trajectories using time-stamped data

Sayak Mukherjee, David Stewart, William Stewart, Lewis L Lanier and Jayajit Das

Royal Society Open Science, Vol.4(8), pp.170811-170811

2017

DOI: 10.1098/rsos.170811

PMCID: PMC5579131

PMID: 28879015

Files and links (1)

url

https://doi.org/10.1098/rsos.170811View

Published (Version of record) Open Access

Abstract

Single-cell responses are shaped by the geometry of signalling kinetic trajectories carved in a multidimensional space spanned by signalling protein abundances. It is, however, challenging to assay a large number (more than 3) of signalling species in live-cell imaging, which makes it difficult to probe single-cell signalling kinetic trajectories in large dimensions. Flow and mass cytometry techniques can measure a large number (4 to more than 40) of signalling species but are unable to track single cells. Thus, cytometry experiments provide detailed time-stamped snapshots of single-cell signalling kinetics. Is it possible to use the time-stamped cytometry data to reconstruct single-cell signalling trajectories? Borrowing concepts of conserved and slow variables from non-equilibrium statistical physics we develop an approach to reconstruct signalling trajectories using snapshot data by creating new variables that remain invariant or vary slowly during the signalling kinetics. We apply this approach to reconstruct trajectories using snapshot data obtained from in silico simulations, live-cell imaging measurements, and, synthetic flow cytometry datasets. The application of invariants and slow variables to reconstruct trajectories provides a radically different way to track objects using snapshot data. The approach is likely to have implications for solving matching problems in a wide range of disciplines.

Biochemistry and Biophysics

1003

1001

trajectory reconstruction

flow cytometry

mass cytometry

pair-matching

1009

single-cell signalling kinetics

invariants

Details

Title: Subtitle: Connecting the dots across time: reconstruction of single-cell signalling trajectories using time-stamped data
Creators: Sayak Mukherjee - ,
David Stewart - ,
William Stewart - ,
Lewis L Lanier - ,
Jayajit Das - ,
Resource Type: Journal article
Publication Details: Royal Society Open Science, Vol.4(8), pp.170811-170811
DOI: 10.1098/rsos.170811
PMID: 28879015
PMCID: PMC5579131
NLM abbreviation: R Soc Open Sci
ISSN: 2054-5703
eISSN: 2054-5703
Publisher: The Royal Society Publishing
Grant note: R56AI108880-01 / ;
Alternative title: Reconstruction of signaling trajectories
Language: English
Date published: 2017
Academic Unit: Mathematics
Record Identifier: 9983985716402771

Metrics

13 Record Views

4 Times Cited - Web of Science