Award Abstract # 2042948
A systems biology framework to uncover rules governing robustness of a microbial community

NSF Org: DBI
Division of Biological Infrastructure
Recipient: INSTITUTE FOR SYSTEMS BIOLOGY
Initial Amendment Date: July 16, 2021
Latest Amendment Date: August 28, 2024
Award Number: 2042948
Award Instrument: Continuing Grant
Program Manager: Jennifer Weller
jweller@nsf.gov
 (703)292-2224
DBI
 Division of Biological Infrastructure
BIO
 Directorate for Biological Sciences
Start Date: August 1, 2021
End Date: July 31, 2025 (Estimated)
Total Intended Award Amount: $1,552,327.00
Total Awarded Amount to Date: $1,552,327.00
Funds Obligated to Date: FY 2021 = $363,361.00
FY 2022 = $365,952.00

FY 2023 = $407,220.00

FY 2024 = $415,794.00
History of Investigator:
  • Nitin Baliga (Principal Investigator)
    nbaliga@systemsbiology.org
  • Serdar Turkarslan (Co-Principal Investigator)
Recipient Sponsored Research Office: Institute for Systems Biology
401 TERRY AVE N
SEATTLE
WA  US  98109-5263
(206)732-1200
Sponsor Congressional District: 07
Primary Place of Performance: Institute for Systems Biology
401 Terry Avenue North
Seattle
WA  US  98109-5263
Primary Place of Performance
Congressional District:
07
Unique Entity Identifier (UEI): SMK9PCMKXED6
Parent UEI: SMK9PCMKXED6
NSF Program(s): Innovation: Bioinformatics
Primary Program Source: 01002122DB NSF RESEARCH & RELATED ACTIVIT
01002223DB NSF RESEARCH & RELATED ACTIVIT

01002324DB NSF RESEARCH & RELATED ACTIVIT

01002425DB NSF RESEARCH & RELATED ACTIVIT
Program Reference Code(s):
Program Element Code(s): 164Y00
Award Agency Code: 4900
Fund Agency Code: 4900
Assistance Listing Number(s): 47.074

ABSTRACT

This project is uncovering how a microbial community adapts to changes in its environment to enable powerful biotechnology solutions, such as the production of high value commodity chemicals in a sustainable manner. Adapting to fluctuations in resource availability is an energetically expensive process for a microbial community, requiring the modulation of hundreds to thousands of genes. This project is characterizing the molecular and cellular networks of a microbial community that drive this adaptive process. Activities in this project are using a systems biology approach to study a microbial community as a whole. Specifically, using modern sequencing technologies this project is investigating how controlled environmental fluctuations induce changes in the expression of all genes of a synthetic microbial community of two organisms that play a central role across diverse environments, including lake sediment, soil, and the human gut, contributing to a biogeochemically important process of cycling >1 gigaton of carbon annually.

By developing innovative computational modeling technologies these data are being analyzed to uncover how regulatory networks drive the dynamic community-wide gene expression changes, to coordinate flux changes through metabolic pathways, and ultimately manifest in overall improved fitness of the community. In so doing, this project is generating a predictive and mechanistic understanding of the adaptive processes of a microbial community. Hypotheses based on the predictive and mechanistic understanding of the adaptive process are being tested using targeted genetic and environmental manipulation of the cellular and molecular networks of the community. The research capabilities, predictive models, and knowledge being generated in this project are widely applicable to research and biotechnology programs in the public and private sectors, including projects across the MCB and IOS Divisions of NSF. To ascertain wide outreach, this project is leveraging a long-term NSF-funded effort to engage women, minorities, and disadvantaged students and teachers, to bring current science concepts and practices generated by this project into high school classrooms. Curricula developed in this project are being disseminated across all 50 states in the US and across >100 countries worldwide.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

PUBLICATIONS PRODUCED AS A RESULT OF THIS RESEARCH

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Arrieta-Ortiz, Mario L. and Immanuel, Selva Rupa and Turkarslan, Serdar and Wu, Wei-Ju and Girinathan, Brintha P. and Worley, Jay N. and DiBenedetto, Nicholas and Soutourina, Olga and Peltier, Johann and Dupuy, Bruno and Bry, Lynn and Baliga, Nitin S. "Predictive regulatory and metabolic network models for systems analysis of Clostridioides difficile" Cell Host & Microbe , v.29 , 2021 https://doi.org/10.1016/j.chom.2021.09.008 Citation Details
Arrieta-Ortiz, Mario L. and Pan, Min and Kaur, Amardeep and Pepper-Tunick, Evan and Srinivas, Vivek and Dash, Ananya and Immanuel, Selva Rupa and Brooks, Aaron N. and Shepherd, Tyson R. and Baliga, Nitin S. "Disrupting the ArcA Regulatory Network Amplifies the Fitness Cost of Tetracycline Resistance in Escherichia coli" mSystems , v.8 , 2023 https://doi.org/10.1128/msystems.00904-22 Citation Details
Girinathan, Brintha P. and DiBenedetto, Nicholas and Worley, Jay N. and Peltier, Johann and Arrieta-Ortiz, Mario L. and Immanuel, Selva Rupa and Lavin, Richard and Delaney, Mary L. and Cummins, Christopher K. and Hoffman, Maria and Luo, Yan and Gonzalez-E "In vivo commensal control of Clostridioides difficile virulence" Cell Host & Microbe , v.29 , 2021 https://doi.org/10.1016/j.chom.2021.09.007 Citation Details
Immanuel, Selva Rupa and Arrieta-Ortiz, Mario L. and Ruiz, Rene A. and Pan, Min and Lopez Garcia de Lomana, Adrian and Peterson, Eliza J. and Baliga, Nitin S. "Quantitative prediction of conditional vulnerabilities in regulatory and metabolic networks using PRIME" npj Systems Biology and Applications , v.7 , 2021 https://doi.org/10.1038/s41540-021-00205-6 Citation Details
Pavao, Aidan and Graham, Madeline and Arrieta-Ortiz, Mario L. and Immanuel, Selva Rupa and Baliga, Nitin S. and Bry, Lynn "Reconsidering the in vivo functions of Clostridial Stickland amino acid fermentations" Anaerobe , v.76 , 2022 https://doi.org/10.1016/j.anaerobe.2022.102600 Citation Details
Srinivas, Vivek and Ruiz, Rene A. and Pan, Min and Immanuel, Selva Rupa and Peterson, Eliza J.R. and Baliga, Nitin S. "Transcriptome signature of cell viability predicts drug response and drug interaction in Mycobacterium tuberculosis" Cell Reports Methods , v.1 , 2021 https://doi.org/10.1016/j.crmeth.2021.100123 Citation Details

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