Quantitative Understanding of Probabilistic Behavior of Living Cells Operated by Vibrant Intracellular Networks

For quantitative understanding of probabilistic behaviors of living cells, it is essential to construct a correct mathematical description of intracellular networks interacting with complex cell environments, which has been a formidable task. Here, we present a novel model and stochastic kinetics fo...

Full description

Bibliographic Details
Main Authors: Yu Rim Lim, Ji-Hyun Kim, Seong Jun Park, Gil-Suk Yang, Sanggeun Song, Suk-Kyu Chang, Nam Ki Lee, Jaeyoung Sung
Format: Article
Language:English
Published: American Physical Society 2015-08-01
Series:Physical Review X
Online Access:http://doi.org/10.1103/PhysRevX.5.031014
id doaj-fe36dfa856424446a3b25ecf13a46203
record_format Article
spelling doaj-fe36dfa856424446a3b25ecf13a462032020-11-24T22:19:00ZengAmerican Physical SocietyPhysical Review X2160-33082015-08-015303101410.1103/PhysRevX.5.031014Quantitative Understanding of Probabilistic Behavior of Living Cells Operated by Vibrant Intracellular NetworksYu Rim LimJi-Hyun KimSeong Jun ParkGil-Suk YangSanggeun SongSuk-Kyu ChangNam Ki LeeJaeyoung SungFor quantitative understanding of probabilistic behaviors of living cells, it is essential to construct a correct mathematical description of intracellular networks interacting with complex cell environments, which has been a formidable task. Here, we present a novel model and stochastic kinetics for an intracellular network interacting with hidden cell environments, employing a complete description of cell state dynamics and its coupling to the system network. Our analysis reveals that various environmental effects on the product number fluctuation of intracellular reaction networks can be collectively characterized by Laplace transform of the time-correlation function of the product creation rate fluctuation with the Laplace variable being the product decay rate. On the basis of the latter result, we propose an efficient method for quantitative analysis of the chemical fluctuation produced by intracellular networks coupled to hidden cell environments. By applying the present approach to the gene expression network, we obtain simple analytic results for the gene expression variability and the environment-induced correlations between the expression levels of mutually noninteracting genes. The theoretical results compose a unified framework for quantitative understanding of various gene expression statistics observed across a number of different systems with a small number of adjustable parameters with clear physical meanings.http://doi.org/10.1103/PhysRevX.5.031014
collection DOAJ
language English
format Article
sources DOAJ
author Yu Rim Lim
Ji-Hyun Kim
Seong Jun Park
Gil-Suk Yang
Sanggeun Song
Suk-Kyu Chang
Nam Ki Lee
Jaeyoung Sung
spellingShingle Yu Rim Lim
Ji-Hyun Kim
Seong Jun Park
Gil-Suk Yang
Sanggeun Song
Suk-Kyu Chang
Nam Ki Lee
Jaeyoung Sung
Quantitative Understanding of Probabilistic Behavior of Living Cells Operated by Vibrant Intracellular Networks
Physical Review X
author_facet Yu Rim Lim
Ji-Hyun Kim
Seong Jun Park
Gil-Suk Yang
Sanggeun Song
Suk-Kyu Chang
Nam Ki Lee
Jaeyoung Sung
author_sort Yu Rim Lim
title Quantitative Understanding of Probabilistic Behavior of Living Cells Operated by Vibrant Intracellular Networks
title_short Quantitative Understanding of Probabilistic Behavior of Living Cells Operated by Vibrant Intracellular Networks
title_full Quantitative Understanding of Probabilistic Behavior of Living Cells Operated by Vibrant Intracellular Networks
title_fullStr Quantitative Understanding of Probabilistic Behavior of Living Cells Operated by Vibrant Intracellular Networks
title_full_unstemmed Quantitative Understanding of Probabilistic Behavior of Living Cells Operated by Vibrant Intracellular Networks
title_sort quantitative understanding of probabilistic behavior of living cells operated by vibrant intracellular networks
publisher American Physical Society
series Physical Review X
issn 2160-3308
publishDate 2015-08-01
description For quantitative understanding of probabilistic behaviors of living cells, it is essential to construct a correct mathematical description of intracellular networks interacting with complex cell environments, which has been a formidable task. Here, we present a novel model and stochastic kinetics for an intracellular network interacting with hidden cell environments, employing a complete description of cell state dynamics and its coupling to the system network. Our analysis reveals that various environmental effects on the product number fluctuation of intracellular reaction networks can be collectively characterized by Laplace transform of the time-correlation function of the product creation rate fluctuation with the Laplace variable being the product decay rate. On the basis of the latter result, we propose an efficient method for quantitative analysis of the chemical fluctuation produced by intracellular networks coupled to hidden cell environments. By applying the present approach to the gene expression network, we obtain simple analytic results for the gene expression variability and the environment-induced correlations between the expression levels of mutually noninteracting genes. The theoretical results compose a unified framework for quantitative understanding of various gene expression statistics observed across a number of different systems with a small number of adjustable parameters with clear physical meanings.
url http://doi.org/10.1103/PhysRevX.5.031014
work_keys_str_mv AT yurimlim quantitativeunderstandingofprobabilisticbehavioroflivingcellsoperatedbyvibrantintracellularnetworks
AT jihyunkim quantitativeunderstandingofprobabilisticbehavioroflivingcellsoperatedbyvibrantintracellularnetworks
AT seongjunpark quantitativeunderstandingofprobabilisticbehavioroflivingcellsoperatedbyvibrantintracellularnetworks
AT gilsukyang quantitativeunderstandingofprobabilisticbehavioroflivingcellsoperatedbyvibrantintracellularnetworks
AT sanggeunsong quantitativeunderstandingofprobabilisticbehavioroflivingcellsoperatedbyvibrantintracellularnetworks
AT sukkyuchang quantitativeunderstandingofprobabilisticbehavioroflivingcellsoperatedbyvibrantintracellularnetworks
AT namkilee quantitativeunderstandingofprobabilisticbehavioroflivingcellsoperatedbyvibrantintracellularnetworks
AT jaeyoungsung quantitativeunderstandingofprobabilisticbehavioroflivingcellsoperatedbyvibrantintracellularnetworks
_version_ 1716566260613906432