A scalable multi-scale framework for parallel simulation and visualization of microbial evolution

Vadim Mozhayskiy, Bob Miller, Kwan-Liu Ma, Ilias Tagkopoulos

Research output: Chapter in Book/Report/Conference proceedingConference contribution

4 Citations (Scopus)

Abstract

Bacteria are some of the most ubiquitous, simple and fastest evolving life forms in the planet, yet even in their case, evolution is painstakingly difficult to trace in a laboratory setting. However, evolution of microorganisms in controlled and/or accelerated settings is crucial to advance our understanding on how various behavioral patterns emerge, or to engineer new strains with desired proprieties (e.g. resilient strains for recombinant protein or bio-fuels production). We present a microbial evolution simulator, a tool to study and analyze hypotheses regarding microbial evolution dynamics. The simulator employs multi-scale models and data structures that capture a whole ecology of interactions between the environment, populations, organisms, and their respective gene regulatory and biochemical networks. For each time point, the evolutionary "fossil record" is recorded in each run. This dataset (stored in HDF5 format for scalability) includes all environmental and cellular parameters, cellular (division, death) and evolutionary events (mutations, Horizontal Gene Transfer). This leads to the creation of a coherent dataset that could not have been obtained experimentally. To efficiently analyze it, we have developed a novel visualization tool that projects information in multiple levels (population, phylogeny, networks, and phenotypes). Additionally, we present some of the unique insights in microbial evolution that were possible through simulations in TeraGrid, and we describe further steps to address scalability issues for populations beyond 32,000 cells.

Original languageEnglish (US)
Title of host publicationProceedings of the TeraGrid 2011 Conference
Subtitle of host publicationExtreme Digital Discovery, TG'11
DOIs
StatePublished - Sep 7 2011
EventTeraGrid 2011 Conference: Extreme Digital Discovery, TG'11 - Salt Lake City, UT, United States
Duration: Jul 18 2011Jul 21 2011

Other

OtherTeraGrid 2011 Conference: Extreme Digital Discovery, TG'11
CountryUnited States
CitySalt Lake City, UT
Period7/18/117/21/11

Fingerprint

Scalability
Visualization
Simulators
Gene transfer
Recombinant proteins
Planets
Ecology
Model structures
Microorganisms
Data structures
Bacteria
Genes
Engineers
Phylogeny

Keywords

  • biological networks
  • high performance computing
  • microbial evolution
  • multi-scale modeling
  • simulation
  • visualization

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Hardware and Architecture

Cite this

Mozhayskiy, V., Miller, B., Ma, K-L., & Tagkopoulos, I. (2011). A scalable multi-scale framework for parallel simulation and visualization of microbial evolution. In Proceedings of the TeraGrid 2011 Conference: Extreme Digital Discovery, TG'11 https://doi.org/10.1145/2016741.2016749

A scalable multi-scale framework for parallel simulation and visualization of microbial evolution. / Mozhayskiy, Vadim; Miller, Bob; Ma, Kwan-Liu; Tagkopoulos, Ilias.

Proceedings of the TeraGrid 2011 Conference: Extreme Digital Discovery, TG'11. 2011.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Mozhayskiy, V, Miller, B, Ma, K-L & Tagkopoulos, I 2011, A scalable multi-scale framework for parallel simulation and visualization of microbial evolution. in Proceedings of the TeraGrid 2011 Conference: Extreme Digital Discovery, TG'11. TeraGrid 2011 Conference: Extreme Digital Discovery, TG'11, Salt Lake City, UT, United States, 7/18/11. https://doi.org/10.1145/2016741.2016749
Mozhayskiy V, Miller B, Ma K-L, Tagkopoulos I. A scalable multi-scale framework for parallel simulation and visualization of microbial evolution. In Proceedings of the TeraGrid 2011 Conference: Extreme Digital Discovery, TG'11. 2011 https://doi.org/10.1145/2016741.2016749
Mozhayskiy, Vadim ; Miller, Bob ; Ma, Kwan-Liu ; Tagkopoulos, Ilias. / A scalable multi-scale framework for parallel simulation and visualization of microbial evolution. Proceedings of the TeraGrid 2011 Conference: Extreme Digital Discovery, TG'11. 2011.
@inproceedings{b6f13ff7590c434f835ed80964fc53f9,
title = "A scalable multi-scale framework for parallel simulation and visualization of microbial evolution",
abstract = "Bacteria are some of the most ubiquitous, simple and fastest evolving life forms in the planet, yet even in their case, evolution is painstakingly difficult to trace in a laboratory setting. However, evolution of microorganisms in controlled and/or accelerated settings is crucial to advance our understanding on how various behavioral patterns emerge, or to engineer new strains with desired proprieties (e.g. resilient strains for recombinant protein or bio-fuels production). We present a microbial evolution simulator, a tool to study and analyze hypotheses regarding microbial evolution dynamics. The simulator employs multi-scale models and data structures that capture a whole ecology of interactions between the environment, populations, organisms, and their respective gene regulatory and biochemical networks. For each time point, the evolutionary {"}fossil record{"} is recorded in each run. This dataset (stored in HDF5 format for scalability) includes all environmental and cellular parameters, cellular (division, death) and evolutionary events (mutations, Horizontal Gene Transfer). This leads to the creation of a coherent dataset that could not have been obtained experimentally. To efficiently analyze it, we have developed a novel visualization tool that projects information in multiple levels (population, phylogeny, networks, and phenotypes). Additionally, we present some of the unique insights in microbial evolution that were possible through simulations in TeraGrid, and we describe further steps to address scalability issues for populations beyond 32,000 cells.",
keywords = "biological networks, high performance computing, microbial evolution, multi-scale modeling, simulation, visualization",
author = "Vadim Mozhayskiy and Bob Miller and Kwan-Liu Ma and Ilias Tagkopoulos",
year = "2011",
month = "9",
day = "7",
doi = "10.1145/2016741.2016749",
language = "English (US)",
isbn = "9781450308885",
booktitle = "Proceedings of the TeraGrid 2011 Conference",

}

TY - GEN

T1 - A scalable multi-scale framework for parallel simulation and visualization of microbial evolution

AU - Mozhayskiy, Vadim

AU - Miller, Bob

AU - Ma, Kwan-Liu

AU - Tagkopoulos, Ilias

PY - 2011/9/7

Y1 - 2011/9/7

N2 - Bacteria are some of the most ubiquitous, simple and fastest evolving life forms in the planet, yet even in their case, evolution is painstakingly difficult to trace in a laboratory setting. However, evolution of microorganisms in controlled and/or accelerated settings is crucial to advance our understanding on how various behavioral patterns emerge, or to engineer new strains with desired proprieties (e.g. resilient strains for recombinant protein or bio-fuels production). We present a microbial evolution simulator, a tool to study and analyze hypotheses regarding microbial evolution dynamics. The simulator employs multi-scale models and data structures that capture a whole ecology of interactions between the environment, populations, organisms, and their respective gene regulatory and biochemical networks. For each time point, the evolutionary "fossil record" is recorded in each run. This dataset (stored in HDF5 format for scalability) includes all environmental and cellular parameters, cellular (division, death) and evolutionary events (mutations, Horizontal Gene Transfer). This leads to the creation of a coherent dataset that could not have been obtained experimentally. To efficiently analyze it, we have developed a novel visualization tool that projects information in multiple levels (population, phylogeny, networks, and phenotypes). Additionally, we present some of the unique insights in microbial evolution that were possible through simulations in TeraGrid, and we describe further steps to address scalability issues for populations beyond 32,000 cells.

AB - Bacteria are some of the most ubiquitous, simple and fastest evolving life forms in the planet, yet even in their case, evolution is painstakingly difficult to trace in a laboratory setting. However, evolution of microorganisms in controlled and/or accelerated settings is crucial to advance our understanding on how various behavioral patterns emerge, or to engineer new strains with desired proprieties (e.g. resilient strains for recombinant protein or bio-fuels production). We present a microbial evolution simulator, a tool to study and analyze hypotheses regarding microbial evolution dynamics. The simulator employs multi-scale models and data structures that capture a whole ecology of interactions between the environment, populations, organisms, and their respective gene regulatory and biochemical networks. For each time point, the evolutionary "fossil record" is recorded in each run. This dataset (stored in HDF5 format for scalability) includes all environmental and cellular parameters, cellular (division, death) and evolutionary events (mutations, Horizontal Gene Transfer). This leads to the creation of a coherent dataset that could not have been obtained experimentally. To efficiently analyze it, we have developed a novel visualization tool that projects information in multiple levels (population, phylogeny, networks, and phenotypes). Additionally, we present some of the unique insights in microbial evolution that were possible through simulations in TeraGrid, and we describe further steps to address scalability issues for populations beyond 32,000 cells.

KW - biological networks

KW - high performance computing

KW - microbial evolution

KW - multi-scale modeling

KW - simulation

KW - visualization

UR - http://www.scopus.com/inward/record.url?scp=80052330079&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=80052330079&partnerID=8YFLogxK

U2 - 10.1145/2016741.2016749

DO - 10.1145/2016741.2016749

M3 - Conference contribution

AN - SCOPUS:80052330079

SN - 9781450308885

BT - Proceedings of the TeraGrid 2011 Conference

ER -