1
|
Gupta VK, Vaishnavi VV, Arrieta-Ortiz ML, P S A, K M J, Jeyasankar S, Raghunathan V, Baliga NS, Agarwal R. 3D Hydrogel Culture System Recapitulates Key Tuberculosis Phenotypes and Demonstrates Pyrazinamide Efficacy. Adv Healthc Mater 2024:e2304299. [PMID: 38655817 DOI: 10.1002/adhm.202304299] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/04/2023] [Revised: 03/29/2024] [Indexed: 04/26/2024]
Abstract
The mortality caused by tuberculosis (TB) infections is a global concern, and there is a need to improve understanding of the disease. Current in vitro infection models to study the disease have limitations such as short investigation durations and divergent transcriptional signatures. This study aims to overcome these limitations by developing a 3D collagen culture system that mimics the biomechanical and extracellular matrix (ECM) of lung microenvironment (collagen fibers, stiffness comparable to in vivo conditions) as the infection primarily manifests in the lungs. The system incorporates Mycobacterium tuberculosis (Mtb) infected human THP-1 or primary monocytes/macrophages. Dual RNA sequencing reveals higher mammalian gene expression similarity with patient samples than 2D macrophage infections. Similarly, bacterial gene expression more accurately recapitulates in vivo gene expression patterns compared to bacteria in 2D infection models. Key phenotypes observed in humans, such as foamy macrophages and mycobacterial cords, are reproduced in the model. This biomaterial system overcomes challenges associated with traditional platforms by modulating immune cells and closely mimicking in vivo infection conditions, including showing efficacy with clinically relevant concentrations of anti-TB drug pyrazinamide, not seen in any other in vitro infection model, making it reliable and readily adoptable for tuberculosis studies and drug screening.
Collapse
Affiliation(s)
- Vishal K Gupta
- Department of Bioengineering, Indian Institute of Science, CV Raman Road, Bengaluru, Karnataka, 560012, India
| | - Vijaya V Vaishnavi
- Department of Bioengineering, Indian Institute of Science, CV Raman Road, Bengaluru, Karnataka, 560012, India
| | | | - Abhirami P S
- Department of Bioengineering, Indian Institute of Science, CV Raman Road, Bengaluru, Karnataka, 560012, India
| | - Jyothsna K M
- Department of Electrical Communication Engineering, Indian Institute of Science, CV Raman Road, Bengaluru, Karnataka, 560012, India
| | - Sharumathi Jeyasankar
- Department of Bioengineering, Indian Institute of Science, CV Raman Road, Bengaluru, Karnataka, 560012, India
| | - Varun Raghunathan
- Department of Electrical Communication Engineering, Indian Institute of Science, CV Raman Road, Bengaluru, Karnataka, 560012, India
| | - Nitin S Baliga
- Institute of Systems Biology, 401 Terry Ave N, Seattle, WA, 98109, USA
| | - Rachit Agarwal
- Department of Bioengineering, Indian Institute of Science, CV Raman Road, Bengaluru, Karnataka, 560012, India
| |
Collapse
|
2
|
Hunt KA, Carr AV, Otwell AE, Valenzuela JJ, Walker KS, Dixon ER, Lui LM, Nielsen TN, Bowman S, von Netzer F, Moon JW, Schadt CW, Rodriguez M, Lowe K, Joyner D, Davis KJ, Wu X, Chakraborty R, Fields MW, Zhou J, Hazen TC, Arkin AP, Wankel SD, Baliga NS, Stahl DA. Contribution of Microorganisms with the Clade II Nitrous Oxide Reductase to Suppression of Surface Emissions of Nitrous Oxide. Environ Sci Technol 2024; 58:7056-7065. [PMID: 38608141 DOI: 10.1021/acs.est.3c07972] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/14/2024]
Abstract
The sources and sinks of nitrous oxide, as control emissions to the atmosphere, are generally poorly constrained for most environmental systems. Initial depth-resolved analysis of nitrous oxide flux from observation wells and the proximal surface within a nitrate contaminated aquifer system revealed high subsurface production but little escape from the surface. To better understand the environmental controls of production and emission at this site, we used a combination of isotopic, geochemical, and molecular analyses to show that chemodenitrification and bacterial denitrification are major sources of nitrous oxide in this subsurface, where low DO, low pH, and high nitrate are correlated with significant nitrous oxide production. Depth-resolved metagenomes showed that consumption of nitrous oxide near the surface was correlated with an enrichment of Clade II nitrous oxide reducers, consistent with a growing appreciation of their importance in controlling release of nitrous oxide to the atmosphere. Our work also provides evidence for the reduction of nitrous oxide at a pH of 4, well below the generally accepted limit of pH 5.
Collapse
Affiliation(s)
- Kristopher A Hunt
- Department of Civil and Environmental Engineering, University of Washington, Seattle, Washington 98195, United States
| | - Alex V Carr
- Department of Molecular Engineering Sciences, University of Washington, Seattle, Washington 98105, United States
- Institute for Systems Biology, Seattle, Washington 98109, United States
| | - Anne E Otwell
- Department of Civil and Environmental Engineering, University of Washington, Seattle, Washington 98195, United States
| | | | - Kathleen S Walker
- Biosciences Division, Oak Ridge National Laboratory, Oak Ridge, Tennessee 37830, United States
- Department of Civil and Environmental Engineering, University of Tennessee, Knoxville, Tennessee 37996, United States
| | - Emma R Dixon
- Biosciences Division, Oak Ridge National Laboratory, Oak Ridge, Tennessee 37830, United States
- Department of Civil and Environmental Engineering, University of Tennessee, Knoxville, Tennessee 37996, United States
| | - Lauren M Lui
- Environmental Genomics and Systems Biology, Lawrence Berkeley National Laboratory, Berkeley, California 94720, United States
| | - Torben N Nielsen
- Environmental Genomics and Systems Biology, Lawrence Berkeley National Laboratory, Berkeley, California 94720, United States
| | - Samuel Bowman
- Department of Marine Chemistry and Geochemistry, Woods Hole Oceanographic Institution, Woods Hole, Massachusetts 02540, United States
| | - Frederick von Netzer
- Department of Civil and Environmental Engineering, University of Washington, Seattle, Washington 98195, United States
| | - Ji-Won Moon
- Biosciences Division, Oak Ridge National Laboratory, Oak Ridge, Tennessee 37830, United States
| | - Christopher W Schadt
- Biosciences Division, Oak Ridge National Laboratory, Oak Ridge, Tennessee 37830, United States
| | - Miguel Rodriguez
- Biosciences Division, Oak Ridge National Laboratory, Oak Ridge, Tennessee 37830, United States
| | - Kenneth Lowe
- Environmental Sciences Division, Oak Ridge National Laboratory, Oak Ridge, Tennessee 37830, United States
| | - Dominique Joyner
- Biosciences Division, Oak Ridge National Laboratory, Oak Ridge, Tennessee 37830, United States
- Department of Civil and Environmental Engineering, University of Tennessee, Knoxville, Tennessee 37996, United States
| | - Katherine J Davis
- Center for Biofilm Engineering, Montana State University, Bozeman, Montana 59717, United States
| | - Xiaoqin Wu
- Climate and Ecosystem Sciences Division, Lawrence Berkeley National Laboratory, Berkeley, California 94720, United States
| | - Romy Chakraborty
- Climate and Ecosystem Sciences Division, Lawrence Berkeley National Laboratory, Berkeley, California 94720, United States
| | - Matthew W Fields
- Center for Biofilm Engineering, Montana State University, Bozeman, Montana 59717, United States
- Department of Microbiology and Cell Biology, Montana State University, Bozeman, Montana 59717, United States
| | - Jizhong Zhou
- Climate and Ecosystem Sciences Division, Lawrence Berkeley National Laboratory, Berkeley, California 94720, United States
- Institute for Environmental Genomics and Department of Botany and Microbiology, University of Oklahoma, Norman, Oklahoma 73019, United States
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China
| | - Terry C Hazen
- Biosciences Division, Oak Ridge National Laboratory, Oak Ridge, Tennessee 37830, United States
- Department of Civil and Environmental Engineering, University of Tennessee, Knoxville, Tennessee 37996, United States
| | - Adam P Arkin
- Environmental Genomics and Systems Biology, Lawrence Berkeley National Laboratory, Berkeley, California 94720, United States
- Department of Bioengineering, University of California Berkeley, Berkeley, California 94720, United States
| | - Scott D Wankel
- Department of Marine Chemistry and Geochemistry, Woods Hole Oceanographic Institution, Woods Hole, Massachusetts 02540, United States
| | - Nitin S Baliga
- Department of Molecular Engineering Sciences, University of Washington, Seattle, Washington 98105, United States
- Institute for Systems Biology, Seattle, Washington 98109, United States
| | - David A Stahl
- Department of Civil and Environmental Engineering, University of Washington, Seattle, Washington 98195, United States
| |
Collapse
|
3
|
Turkarslan S, He Y, Hothi P, Murie C, Nicolas A, Kannan K, Park JH, Pan M, Awawda A, Cole ZD, Shapiro MA, Stuhlmiller TJ, Lee H, Patel AP, Cobbs C, Baliga NS. An atlas of causal and mechanistic drivers of interpatient heterogeneity in glioma. medRxiv 2024:2024.04.05.24305380. [PMID: 38633778 PMCID: PMC11023657 DOI: 10.1101/2024.04.05.24305380] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/19/2024]
Abstract
Grade IV glioma, formerly known as glioblastoma multiforme (GBM) is the most aggressive and lethal type of brain tumor, and its treatment remains challenging in part due to extensive interpatient heterogeneity in disease driving mechanisms and lack of prognostic and predictive biomarkers. Using mechanistic inference of node-edge relationship (MINER), we have analyzed multiomics profiles from 516 patients and constructed an atlas of causal and mechanistic drivers of interpatient heterogeneity in GBM (gbmMINER). The atlas has delineated how 30 driver mutations act in a combinatorial scheme to causally influence a network of regulators (306 transcription factors and 73 miRNAs) of 179 transcriptional "programs", influencing disease progression in patients across 23 disease states. Through extensive testing on independent patient cohorts, we share evidence that a machine learning model trained on activity profiles of programs within gbmMINER significantly augments risk stratification, identifying patients who are super-responders to standard of care and those that would benefit from 2 nd line treatments. In addition to providing mechanistic hypotheses regarding disease prognosis, the activity of programs containing targets of 2 nd line treatments accurately predicted efficacy of 28 drugs in killing glioma stem-like cells from 43 patients. Our findings demonstrate that interpatient heterogeneity manifests from differential activities of transcriptional programs, providing actionable strategies for mechanistically characterizing GBM from a systems perspective and developing better prognostic and predictive biomarkers for personalized medicine.
Collapse
|
4
|
Murie C, Turkarslan S, Patel A, Coffey DG, Becker PS, Baliga NS. Individualized dynamic risk assessment for multiple myeloma. medRxiv 2024:2024.04.01.24305024. [PMID: 38633807 PMCID: PMC11023676 DOI: 10.1101/2024.04.01.24305024] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/19/2024]
Abstract
Background Individualized treatment decisions for patients with multiple myeloma (MM) requires accurate risk stratification that takes into account patient-specific consequences of genetic abnormalities and tumor microenvironment on disease outcome and therapy responsiveness. Methods Previously, SYstems Genetic Network AnaLysis (SYGNAL) of multi-omics tumor profiles from 881 MM patients generated the mmSYGNAL network, which uncovered different causal and mechanistic drivers of genetic programs associated with disease progression across MM subtypes. Here, we have trained a machine learning (ML) algorithm on activities of mmSYGNAL programs within individual patient tumor samples to develop a risk classification scheme for MM that significantly outperformed cytogenetics, International Staging System, and multi-gene biomarker panels in predicting risk of PFS across four independent patient cohorts. Results We demonstrate that, unlike other tests, mmSYGNAL can accurately predict disease progression risk at primary diagnosis, pre- and post-transplant and even after multiple relapses, making it useful for individualized dynamic risk assessment throughout the disease trajectory. Conclusion mmSYGNAL provides improved individualized risk stratification that accounts for a patient's distinct set of genetic abnormalities and can monitor risk longitudinally as each patient's disease characteristics change.
Collapse
|
5
|
Park JH, Hothi P, Lopez Garcia de Lomana A, Pan M, Calder R, Turkarslan S, Wu WJ, Lee H, Patel AP, Cobbs C, Huang S, Baliga NS. Gene regulatory network topology governs resistance and treatment escape in glioma stem-like cells. bioRxiv 2024:2024.02.02.578510. [PMID: 38370784 PMCID: PMC10871280 DOI: 10.1101/2024.02.02.578510] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/20/2024]
Abstract
Poor prognosis and drug resistance in glioblastoma (GBM) can result from cellular heterogeneity and treatment-induced shifts in phenotypic states of tumor cells, including dedifferentiation into glioma stem-like cells (GSCs). This rare tumorigenic cell subpopulation resists temozolomide, undergoes proneural-to-mesenchymal transition (PMT) to evade therapy, and drives recurrence. Through inference of transcriptional regulatory networks (TRNs) of patient-derived GSCs (PD-GSCs) at single-cell resolution, we demonstrate how the topology of transcription factor interaction networks drives distinct trajectories of cell state transitions in PD-GSCs resistant or susceptible to cytotoxic drug treatment. By experimentally testing predictions based on TRN simulations, we show that drug treatment drives surviving PD-GSCs along a trajectory of intermediate states, exposing vulnerability to potentiated killing by siRNA or a second drug targeting treatment-induced transcriptional programs governing non-genetic cell plasticity. Our findings demonstrate an approach to uncover TRN topology and use it to rationally predict combinatorial treatments that disrupts acquired resistance in GBM.
Collapse
Affiliation(s)
| | - Parvinder Hothi
- Ivy Center for Advanced Brain Tumor Treatment, Swedish Neuroscience Institute, Seattle, WA
| | | | - Min Pan
- Institute for Systems Biology, Seattle, WA
| | | | | | - Wei-Ju Wu
- Institute for Systems Biology, Seattle, WA
| | - Hwahyung Lee
- Ivy Center for Advanced Brain Tumor Treatment, Swedish Neuroscience Institute, Seattle, WA
| | - Anoop P Patel
- Department of Neurosurgery, Preston Robert Tisch Brain Tumor Center, Duke University, Durham, NC
- Center for Advanced Genomic Technologies, Duke University, Durham, NC
| | - Charles Cobbs
- Ivy Center for Advanced Brain Tumor Treatment, Swedish Neuroscience Institute, Seattle, WA
| | - Sui Huang
- Institute for Systems Biology, Seattle, WA
| | - Nitin S Baliga
- Institute for Systems Biology, Seattle, WA
- Departments of Microbiology, Biology, and Molecular Engineering Sciences, University of Washington, Seattle, WA
| |
Collapse
|
6
|
Carr A, Baliga NS, Diener C, Gibbons SM. Personalized Clostridioides difficile engraftment risk prediction and probiotic therapy assessment in the human gut. bioRxiv 2024:2023.04.28.538771. [PMID: 37162960 PMCID: PMC10168307 DOI: 10.1101/2023.04.28.538771] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/11/2023]
Abstract
Clostridioides difficile colonizes up to 30-40% of community-dwelling adults without causing disease. C. difficile infections (CDIs) are the leading cause of antibiotic-associated diarrhea in the U.S. and typically develop in individuals following disruption of the gut microbiota due to antibiotic or chemotherapy treatments. Further treatment of CDI with antibiotics is not always effective and can lead to antibiotic resistance and recurrent infections (rCDI). The most effective treatment for rCDI is the reestablishment of an intact microbiota via fecal microbiota transplants (FMTs). However, the success of FMTs has been difficult to generalize because the microbial interactions that prevent engraftment and facilitate the successful clearance of C. difficile are still only partially understood. Here we show how microbial community-scale metabolic models (MCMMs) accurately predicted known instances of C. difficile colonization susceptibility or resistance in vitro and in vivo. MCMMs provide detailed mechanistic insights into the ecological interactions that govern C. difficile engraftment, like cross-feeding or competition involving metabolites like succinate, trehalose, and ornithine, which differ from person to person. Indeed, three distinct C. difficile metabolic niches emerge from our MCMMs, two associated with positive growth rates and one that represents non-growth, which are consistently observed across 15,204 individuals from five independent cohorts. Finally, we show how MCMMs can predict personalized engraftment and C. difficile growth suppression for a probiotic cocktail (VE303) designed to replace FMTs for the treatment rCDI. Overall, this powerful modeling approach predicts personalized C. difficile engraftment risk and can be leveraged to assess probiotic treatment efficacy. MCMMs could be extended to understand the mechanistic underpinnings of personalized engraftment of other opportunistic bacterial pathogens, beneficial probiotic organisms, or more complex microbial consortia.
Collapse
Affiliation(s)
- Alex Carr
- Institute for Systems Biology, Seattle, WA, USA
- Molecular Engineering Program, University of Washington, Seattle, WA, USA
| | - Nitin S. Baliga
- Institute for Systems Biology, Seattle, WA, USA
- Molecular Engineering Program, University of Washington, Seattle, WA, USA
- Departments of Biology and Microbiology, University of Washington, Seattle, WA, USA
- Lawrence Berkeley National Lab, Berkeley, CA, USA
| | - Christian Diener
- Institute for Systems Biology, Seattle, WA, USA
- Diagnostic and Research Institute of Hygiene, Microbiology and Environmental Medicine, Medical University of Graz, Graz, Austria
| | - Sean M. Gibbons
- Institute for Systems Biology, Seattle, WA, USA
- Molecular Engineering Program, University of Washington, Seattle, WA, USA
- Departments of Bioengineering and Genome Sciences, University of Washington, Seattle, WA, USA
- eScience Institute, University of Washington, Seattle, WA, USA
| |
Collapse
|
7
|
Wang Y, Gallagher LA, Andrade PA, Liu A, Humphreys IR, Turkarslan S, Cutler KJ, Arrieta-Ortiz ML, Li Y, Radey MC, McLean JS, Cong Q, Baker D, Baliga NS, Peterson SB, Mougous JD. Genetic manipulation of Patescibacteria provides mechanistic insights into microbial dark matter and the epibiotic lifestyle. Cell 2023; 186:4803-4817.e13. [PMID: 37683634 PMCID: PMC10633639 DOI: 10.1016/j.cell.2023.08.017] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2023] [Revised: 07/06/2023] [Accepted: 08/16/2023] [Indexed: 09/10/2023]
Abstract
Patescibacteria, also known as the candidate phyla radiation (CPR), are a diverse group of bacteria that constitute a disproportionately large fraction of microbial dark matter. Its few cultivated members, belonging mostly to Saccharibacteria, grow as epibionts on host Actinobacteria. Due to a lack of suitable tools, the genetic basis of this lifestyle and other unique features of Patescibacteira remain unexplored. Here, we show that Saccharibacteria exhibit natural competence, and we exploit this property for their genetic manipulation. Imaging of fluorescent protein-labeled Saccharibacteria provides high spatiotemporal resolution of phenomena accompanying epibiotic growth, and a transposon-insertion sequencing (Tn-seq) genome-wide screen reveals the contribution of enigmatic Saccharibacterial genes to growth on their hosts. Finally, we leverage metagenomic data to provide cutting-edge protein structure-based bioinformatic resources that support the strain Southlakia epibionticum and its corresponding host, Actinomyces israelii, as a model system for unlocking the molecular underpinnings of the epibiotic lifestyle.
Collapse
Affiliation(s)
- Yaxi Wang
- Department of Microbiology, University of Washington, Seattle, WA 98109, USA
| | - Larry A Gallagher
- Department of Microbiology, University of Washington, Seattle, WA 98109, USA
| | - Pia A Andrade
- Department of Microbiology, University of Washington, Seattle, WA 98109, USA
| | - Andi Liu
- Department of Microbiology, University of Washington, Seattle, WA 98109, USA
| | - Ian R Humphreys
- Department of Biochemistry, University of Washington, Seattle, WA 98195, USA; Institute for Protein Design, University of Washington, Seattle, WA 98195, USA
| | | | - Kevin J Cutler
- Department of Physics, University of Washington, Seattle, WA 98195, USA
| | | | - Yaqiao Li
- Department of Microbiology, University of Washington, Seattle, WA 98109, USA; Institute for Systems Biology, Seattle, WA 98109, USA
| | - Matthew C Radey
- Department of Microbiology, University of Washington, Seattle, WA 98109, USA
| | - Jeffrey S McLean
- Department of Microbiology, University of Washington, Seattle, WA 98109, USA; Department of Periodontics, University of Washington, Seattle, WA 98195, USA
| | - Qian Cong
- Eugene McDermott Center for Human Growth and Development, University of Texas Southwestern Medical Center, Dallas, TX 75390, USA; Department of Biophysics, University of Texas Southwestern Medical Center, Dallas, TX 75390, USA; Harold C. Simmons Comprehensive Cancer Center, University of Texas Southwestern Medical Center, Dallas, TX 75390, USA
| | - David Baker
- Department of Biochemistry, University of Washington, Seattle, WA 98195, USA; Institute for Protein Design, University of Washington, Seattle, WA 98195, USA; Howard Hughes Medical Institute, University of Washington, Seattle, WA 98109, USA
| | | | - S Brook Peterson
- Department of Microbiology, University of Washington, Seattle, WA 98109, USA
| | - Joseph D Mougous
- Department of Microbiology, University of Washington, Seattle, WA 98109, USA; Howard Hughes Medical Institute, University of Washington, Seattle, WA 98109, USA; Microbial Interactions and Microbiome Center, University of Washington, Seattle, WA 98195, USA.
| |
Collapse
|
8
|
Kusebauch U, Lorenzetti APR, Campbell DS, Pan M, Shteynberg D, Kapil C, Midha MK, López García de Lomana A, Baliga NS, Moritz RL. A comprehensive spectral assay library to quantify the Halobacterium salinarum NRC-1 proteome by DIA/SWATH-MS. Sci Data 2023; 10:697. [PMID: 37833331 PMCID: PMC10575869 DOI: 10.1038/s41597-023-02590-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2023] [Accepted: 09/21/2023] [Indexed: 10/15/2023] Open
Abstract
Data-Independent Acquisition (DIA) is a mass spectrometry-based method to reliably identify and reproducibly quantify large fractions of a target proteome. The peptide-centric data analysis strategy employed in DIA requires a priori generated spectral assay libraries. Such assay libraries allow to extract quantitative data in a targeted approach and have been generated for human, mouse, zebrafish, E. coli and few other organisms. However, a spectral assay library for the extreme halophilic archaeon Halobacterium salinarum NRC-1, a model organism that contributed to several notable discoveries, is not publicly available yet. Here, we report a comprehensive spectral assay library to measure 2,563 of 2,646 annotated H. salinarum NRC-1 proteins. We demonstrate the utility of this library by measuring global protein abundances over time under standard growth conditions. The H. salinarum NRC-1 library includes 21,074 distinct peptides representing 97% of the predicted proteome and provides a new, valuable resource to confidently measure and quantify any protein of this archaeon. Data and spectral assay libraries are available via ProteomeXchange (PXD042770, PXD042774) and SWATHAtlas (SAL00312-SAL00319).
Collapse
Affiliation(s)
- Ulrike Kusebauch
- Institute for Systems Biology, 401 Terry Ave N, Seattle, WA, 98109, USA
| | | | - David S Campbell
- Institute for Systems Biology, 401 Terry Ave N, Seattle, WA, 98109, USA
| | - Min Pan
- Institute for Systems Biology, 401 Terry Ave N, Seattle, WA, 98109, USA
| | - David Shteynberg
- Institute for Systems Biology, 401 Terry Ave N, Seattle, WA, 98109, USA
| | - Charu Kapil
- Institute for Systems Biology, 401 Terry Ave N, Seattle, WA, 98109, USA
| | - Mukul K Midha
- Institute for Systems Biology, 401 Terry Ave N, Seattle, WA, 98109, USA
| | - Adrián López García de Lomana
- Institute for Systems Biology, 401 Terry Ave N, Seattle, WA, 98109, USA
- Center for Systems Biology, University of Iceland, Reykjavik, Iceland
| | - Nitin S Baliga
- Institute for Systems Biology, 401 Terry Ave N, Seattle, WA, 98109, USA
- Departments of Biology and Microbiology, University of Washington, Seattle, WA, USA
- Molecular and Cellular Biology Program, University of Washington, Seattle, WA, USA
- Lawrence Berkeley National Lab, Berkeley, CA, USA
| | - Robert L Moritz
- Institute for Systems Biology, 401 Terry Ave N, Seattle, WA, 98109, USA.
| |
Collapse
|
9
|
Lim JJ, Diener C, Wilson J, Valenzuela JJ, Baliga NS, Gibbons SM. Growth phase estimation for abundant bacterial populations sampled longitudinally from human stool metagenomes. Nat Commun 2023; 14:5682. [PMID: 37709733 PMCID: PMC10502120 DOI: 10.1038/s41467-023-41424-1] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/27/2022] [Accepted: 09/04/2023] [Indexed: 09/16/2023] Open
Abstract
Longitudinal sampling of the stool has yielded important insights into the ecological dynamics of the human gut microbiome. However, human stool samples are available approximately once per day, while commensal population doubling times are likely on the order of minutes-to-hours. Despite this mismatch in timescales, much of the prior work on human gut microbiome time series modeling has assumed that day-to-day fluctuations in taxon abundances are related to population growth or death rates, which is likely not the case. Here, we propose an alternative model of the human gut as a stationary system, where population dynamics occur internally and the bacterial population sizes measured in a bolus of stool represent a steady-state endpoint of these dynamics. We formalize this idea as stochastic logistic growth. We show how this model provides a path toward estimating the growth phases of gut bacterial populations in situ. We validate our model predictions using an in vitro Escherichia coli growth experiment. Finally, we show how this method can be applied to densely-sampled human stool metagenomic time series data. We discuss how these growth phase estimates may be used to better inform metabolic modeling in flow-through ecosystems, like animal guts or industrial bioreactors.
Collapse
Affiliation(s)
- Joe J Lim
- Department of Environmental & Occupational Health Sciences, University of Washington, Seattle, WA, 98105, USA
| | | | - James Wilson
- Institute for Systems Biology, Seattle, WA, 98109, USA
| | | | - Nitin S Baliga
- Institute for Systems Biology, Seattle, WA, 98109, USA
- Departments of Biology and Microbiology, University of Washington, Seattle, WA, 98105, USA
- Lawrence Berkeley National Laboratory, CA, 94720, Berkeley, USA
- Molecular and Cellular Biology Program, University of Washington, WA, 98105, Seattle, USA
- Molecular Engineering Graduate Program, University of Washington, WA, 98105, Seattle, USA
| | - Sean M Gibbons
- Institute for Systems Biology, Seattle, WA, 98109, USA.
- Molecular Engineering Graduate Program, University of Washington, WA, 98105, Seattle, USA.
- Department of Bioengineering, University of Washington, Seattle, WA, 98105, USA.
- Department of Genome Sciences, University of Washington, Seattle, WA, 98105, USA.
- eScience Institute, University of Washington, Seattle, WA, 98105, USA.
| |
Collapse
|
10
|
Peterson EJR, Brooks AN, Reiss DJ, Kaur A, Do J, Pan M, Wu WJ, Morrison R, Srinivas V, Carter W, Arrieta-Ortiz ML, Ruiz RA, Bhatt A, Baliga NS. MtrA modulates Mycobacterium tuberculosis cell division in host microenvironments to mediate intrinsic resistance and drug tolerance. Cell Rep 2023; 42:112875. [PMID: 37542718 PMCID: PMC10480492 DOI: 10.1016/j.celrep.2023.112875] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/16/2021] [Revised: 04/21/2023] [Accepted: 07/11/2023] [Indexed: 08/07/2023] Open
Abstract
The success of Mycobacterium tuberculosis (Mtb) is largely attributed to its ability to physiologically adapt and withstand diverse localized stresses within host microenvironments. Here, we present a data-driven model (EGRIN 2.0) that captures the dynamic interplay of environmental cues and genome-encoded regulatory programs in Mtb. Analysis of EGRIN 2.0 shows how modulation of the MtrAB two-component signaling system tunes Mtb growth in response to related host microenvironmental cues. Disruption of MtrAB by tunable CRISPR interference confirms that the signaling system regulates multiple peptidoglycan hydrolases, among other targets, that are important for cell division. Further, MtrA decreases the effectiveness of antibiotics by mechanisms of both intrinsic resistance and drug tolerance. Together, the model-enabled dissection of complex MtrA regulation highlights its importance as a drug target and illustrates how EGRIN 2.0 facilitates discovery and mechanistic characterization of Mtb adaptation to specific host microenvironments within the host.
Collapse
Affiliation(s)
| | | | - David J Reiss
- Institute for Systems Biology, Seattle, WA 98109, USA
| | - Amardeep Kaur
- Institute for Systems Biology, Seattle, WA 98109, USA
| | - Julie Do
- Institute for Systems Biology, Seattle, WA 98109, USA
| | - Min Pan
- Institute for Systems Biology, Seattle, WA 98109, USA
| | - Wei-Ju Wu
- Institute for Systems Biology, Seattle, WA 98109, USA
| | - Robert Morrison
- Laboratory of Malaria, Immunology and Vaccinology, National Institute of Allergy and Infectious Diseases, NIH, Bethesda, MD 20892, USA
| | | | - Warren Carter
- Institute for Systems Biology, Seattle, WA 98109, USA
| | | | - Rene A Ruiz
- Institute for Systems Biology, Seattle, WA 98109, USA
| | - Apoorva Bhatt
- School of Biosciences and Institute of Microbiology and Infection, University of Birmingham, Birmingham B15 2TT, UK
| | - Nitin S Baliga
- Institute for Systems Biology, Seattle, WA 98109, USA; Departments of Biology and Microbiology, University of Washington, Seattle, WA 98195, USA; Molecular and Cellular Biology Program, University of Washington, Seattle, WA 98195, USA; Lawrence Berkeley National Lab, Berkeley, CA 94720, USA.
| |
Collapse
|
11
|
Wang Y, Ledvina HE, Tower CA, Kambarev S, Liu E, Charity JC, Kreuk LSM, Tang Q, Chen Q, Gallagher LA, Radey MC, Rerolle GF, Li Y, Penewit KM, Turkarslan S, Skerrett SJ, Salipante SJ, Baliga NS, Woodward JJ, Dove SL, Peterson SB, Celli J, Mougous JD. Discovery of a glutathione utilization pathway in Francisella that shows functional divergence between environmental and pathogenic species. Cell Host Microbe 2023; 31:1359-1370.e7. [PMID: 37453420 PMCID: PMC10763578 DOI: 10.1016/j.chom.2023.06.010] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/25/2023] [Revised: 05/19/2023] [Accepted: 06/20/2023] [Indexed: 07/18/2023]
Abstract
Glutathione (GSH) is an abundant metabolite within eukaryotic cells that can act as a signal, a nutrient source, or serve in a redox capacity for intracellular bacterial pathogens. For Francisella, GSH is thought to be a critical in vivo source of cysteine; however, the cellular pathways permitting GSH utilization by Francisella differ between strains and have remained poorly understood. Using genetic screening, we discovered a unique pathway for GSH utilization in Francisella. Whereas prior work suggested GSH catabolism initiates in the periplasm, the pathway we define consists of a major facilitator superfamily (MFS) member that transports intact GSH and a previously unrecognized bacterial cytoplasmic enzyme that catalyzes the first step of GSH degradation. Interestingly, we find that the transporter gene for this pathway is pseudogenized in pathogenic Francisella, explaining phenotypic discrepancies in GSH utilization among Francisella spp. and revealing a critical role for GSH in the environmental niche of these bacteria.
Collapse
Affiliation(s)
- Yaxi Wang
- Department of Microbiology, University of Washington, Seattle, WA 98109, USA
| | - Hannah E Ledvina
- Department of Microbiology, University of Washington, Seattle, WA 98109, USA
| | - Catherine A Tower
- Department of Microbiology, University of Washington, Seattle, WA 98109, USA
| | - Stanimir Kambarev
- Paul G. Allen School for Global Health, Washington State University, Pullman, WA 99164, USA
| | - Elizabeth Liu
- Department of Microbiology, University of Washington, Seattle, WA 98109, USA
| | - James C Charity
- Division of Infectious Diseases, Boston Children's Hospital, Harvard Medical School, Boston, MA 02115, USA
| | | | - Qing Tang
- Department of Microbiology, University of Washington, Seattle, WA 98109, USA
| | - Qiwen Chen
- Department of Microbiology, University of Washington, Seattle, WA 98109, USA
| | - Larry A Gallagher
- Department of Microbiology, University of Washington, Seattle, WA 98109, USA
| | - Matthew C Radey
- Department of Microbiology, University of Washington, Seattle, WA 98109, USA
| | - Guilhem F Rerolle
- Department of Medicine, University of Washington, Seattle, WA 98195, USA
| | - Yaqiao Li
- Department of Microbiology, University of Washington, Seattle, WA 98109, USA; Institute for Systems Biology, Seattle, WA 98109, USA
| | - Kelsi M Penewit
- Department of Laboratory Medicine and Pathology, University of Washington, Seattle, WA 98195, USA
| | | | - Shawn J Skerrett
- Department of Medicine, University of Washington, Seattle, WA 98195, USA
| | - Stephen J Salipante
- Department of Laboratory Medicine and Pathology, University of Washington, Seattle, WA 98195, USA
| | | | - Joshua J Woodward
- Department of Microbiology, University of Washington, Seattle, WA 98109, USA
| | - Simon L Dove
- Division of Infectious Diseases, Boston Children's Hospital, Harvard Medical School, Boston, MA 02115, USA
| | - S Brook Peterson
- Department of Microbiology, University of Washington, Seattle, WA 98109, USA
| | - Jean Celli
- Paul G. Allen School for Global Health, Washington State University, Pullman, WA 99164, USA
| | - Joseph D Mougous
- Department of Microbiology, University of Washington, Seattle, WA 98109, USA; Microbial Interactions and Microbiome Center, University of Washington, Seattle, WA 98195, USA; Howard Hughes Medical Institute, University of Washington, Seattle, WA 98109, USA.
| |
Collapse
|
12
|
Wang Y, Gallagher LA, Andrade PA, Liu A, Humphreys IR, Turkarslan S, Cutler KJ, Arrieta-Ortiz ML, Li Y, Radey MC, McLean JS, Cong Q, Baker D, Baliga NS, Peterson SB, Mougous JD. Genetic manipulation of candidate phyla radiation bacteria provides functional insights into microbial dark matter. bioRxiv 2023:2023.05.02.539146. [PMID: 37205512 PMCID: PMC10187176 DOI: 10.1101/2023.05.02.539146] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/21/2023]
Abstract
The study of bacteria has yielded fundamental insights into cellular biology and physiology, biotechnological advances and many therapeutics. Yet due to a lack of suitable tools, the significant portion of bacterial diversity held within the candidate phyla radiation (CPR) remains inaccessible to such pursuits. Here we show that CPR bacteria belonging to the phylum Saccharibacteria exhibit natural competence. We exploit this property to develop methods for their genetic manipulation, including the insertion of heterologous sequences and the construction of targeted gene deletions. Imaging of fluorescent protein-labeled Saccharibacteria provides high spatiotemporal resolution of phenomena accompanying epibiotic growth and a transposon insertion sequencing genome-wide screen reveals the contribution of enigmatic Saccharibacterial genes to growth on their Actinobacteria hosts. Finally, we leverage metagenomic data to provide cutting-edge protein structure-based bioinformatic resources that support the strain Southlakia epibionticum and its corresponding host, Actinomyces israelii , as a model system for unlocking the molecular underpinnings of the epibiotic lifestyle.
Collapse
Affiliation(s)
- Yaxi Wang
- Department of Microbiology, University of Washington, Seattle, WA 98109, USA
| | - Larry A. Gallagher
- Department of Microbiology, University of Washington, Seattle, WA 98109, USA
| | - Pia A. Andrade
- Department of Microbiology, University of Washington, Seattle, WA 98109, USA
| | - Andi Liu
- Department of Microbiology, University of Washington, Seattle, WA 98109, USA
| | - Ian R. Humphreys
- Department of Biochemistry, University of Washington, Seattle, WA 98109, USA
- Institute for Protein Design, Seattle, WA 98109, USA
| | | | - Kevin J. Cutler
- Department of Physics, University of Washington, Seattle, WA 98195, USA
| | | | - Yaqiao Li
- Department of Microbiology, University of Washington, Seattle, WA 98109, USA
- Institute for Systems Biology, Seattle, WA 98109, USA
| | - Matthew C. Radey
- Department of Microbiology, University of Washington, Seattle, WA 98109, USA
| | - Jeffrey S. McLean
- Department of Microbiology, University of Washington, Seattle, WA 98109, USA
- Department of Periodontics, University of Washington, Seattle, WA 98195, USA
| | - Qian Cong
- Eugene McDermott Center for Human Growth and Development, University of Texas Southwestern Medical Center, Dallas, TX, USA
- Department of Biophysics, University of Texas Southwestern Medical Center, Dallas, TX, USA
- Harold C. Simmons Comprehensive Cancer Center, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - David Baker
- Department of Biochemistry, University of Washington, Seattle, WA 98109, USA
- Institute for Protein Design, Seattle, WA 98109, USA
- Howard Hughes Medical Institute, University of Washington, Seattle, WA 98195, USA
| | | | - S. Brook Peterson
- Department of Microbiology, University of Washington, Seattle, WA 98109, USA
| | - Joseph D. Mougous
- Department of Microbiology, University of Washington, Seattle, WA 98109, USA
- Howard Hughes Medical Institute, University of Washington, Seattle, WA 98195, USA
- Microbial Interactions and Microbiome Center, University of Washington, Seattle, WA 98109, USA
| |
Collapse
|
13
|
Park JH, Feroze AH, Emerson SN, Mihalas AB, Keene CD, Cimino PJ, de Lomana ALG, Kannan K, Wu WJ, Turkarslan S, Baliga NS, Patel AP. A single-cell based precision medicine approach using glioblastoma patient-specific models. NPJ Precis Oncol 2022; 6:55. [PMID: 35941215 PMCID: PMC9360428 DOI: 10.1038/s41698-022-00294-4] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2021] [Accepted: 06/22/2022] [Indexed: 02/08/2023] Open
Abstract
Glioblastoma (GBM) is a heterogeneous tumor made up of cell states that evolve over time. Here, we modeled tumor evolutionary trajectories during standard-of-care treatment using multi-omic single-cell analysis of a primary tumor sample, corresponding mouse xenografts subjected to standard of care therapy, and recurrent tumor at autopsy. We mined the multi-omic data with single-cell SYstems Genetics Network AnaLysis (scSYGNAL) to identify a network of 52 regulators that mediate treatment-induced shifts in xenograft tumor-cell states that were also reflected in recurrence. By integrating scSYGNAL-derived regulatory network information with transcription factor accessibility deviations derived from single-cell ATAC-seq data, we developed consensus networks that modulate cell state transitions across subpopulations of primary and recurrent tumor cells. Finally, by matching targeted therapies to active regulatory networks underlying tumor evolutionary trajectories, we provide a framework for applying single-cell-based precision medicine approaches to an individual patient in a concurrent, adjuvant, or recurrent setting.
Collapse
Affiliation(s)
| | - Abdullah H Feroze
- Department of Neurological Surgery, University of Washington, Seattle, WA, USA
| | - Samuel N Emerson
- Department of Neurological Surgery, University of Washington, Seattle, WA, USA
| | - Anca B Mihalas
- Department of Neurological Surgery, University of Washington, Seattle, WA, USA
- Human Biology Division, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
| | - C Dirk Keene
- Department of Pathology, University of Washington, Seattle, WA, USA
| | - Patrick J Cimino
- Department of Pathology, University of Washington, Seattle, WA, USA
| | | | | | - Wei-Ju Wu
- Institute for Systems Biology, Seattle, WA, USA
| | | | - Nitin S Baliga
- Institute for Systems Biology, Seattle, WA, USA.
- Departments of Microbiology, Biology, and Molecular Engineering Sciences, University of Washington, Seattle, WA, USA.
| | - Anoop P Patel
- Department of Neurological Surgery, University of Washington, Seattle, WA, USA.
- Human Biology Division, Fred Hutchinson Cancer Research Center, Seattle, WA, USA.
- Brotman-Baty Institute for Precision Medicine, University of Washington, Seattle, WA, USA.
- Department of Neurosurgery, Preston Robert Tisch Brain Tumor Center, Duke University, Durham, NC, USA.
| |
Collapse
|
14
|
Akhade AS, Mosquera GV, Arrieta-Ortiz ML, Kaur A, Peterson EJ, Baliga NS, Hughes KT, Subramanian N. A non-canonical role of caspase-1 in regulating bacterial physiology and antimicrobial resistance. The Journal of Immunology 2022. [DOI: 10.4049/jimmunol.208.supp.51.05] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/03/2023]
Abstract
Abstract
Caspase-1 is a key effector molecule involved in inflammasome activation and has a well-established role in restricting the growth of intracellular pathogens like Salmonella by triggering a form of cell death called pyroptosis. Here we reveal a non-canonical, cell death independent role for caspase-1 in controlling the transcriptional state and drug resistance of intracellular Salmonella. Using Pathogen-sequencing, a method for sensitive transcriptional profiling of miniscule numbers of intracellular bacteria from infected macrophages, we show that that caspase-1 regulates key processes involved in survival and antimicrobial susceptibility of intracellular Salmonella. Host caspase-1 increased susceptibility of Salmonella to endogenous cationic antimicrobial peptides, as well as to a cationic polypeptide antibiotic used as a last-line drug in Gram-negative bacterial infections. These effects of caspase-1 were independent of its enzymatic activity but dependent on its ability to repress activation of a two-component signal transduction system in intracellular bacteria. These effects were also independent of caspase-11. Our data suggest a “backup” role for caspase-1 in dampening antimicrobial resistance of intracellular Salmonella which evade initial innate immune detection and restriction by caspase-1. These findings also reveal the role of a key innate immune effector in altering pathogen physiology, broadening our view of host-pathogen crosstalk with possible implications for targeting caspase-1 in host-directed therapy to combat antimicrobial resistance.
Supported by grant from NIH (R01 AI155685-A1 ) and AAI Careers in Immunology Fellowship (2018-2019)
Collapse
|
15
|
Xavier JB, Monk JM, Poudel S, Norsigian CJ, Sastry AV, Liao C, Bento J, Suchard MA, Arrieta-Ortiz ML, Peterson EJ, Baliga NS, Stoeger T, Ruffin F, Richardson RA, Gao CA, Horvath TD, Haag AM, Wu Q, Savidge T, Yeaman MR. Mathematical models to study the biology of pathogens and the infectious diseases they cause. iScience 2022; 25:104079. [PMID: 35359802 PMCID: PMC8961237 DOI: 10.1016/j.isci.2022.104079] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2022] Open
Abstract
Mathematical models have many applications in infectious diseases: epidemiologists use them to forecast outbreaks and design containment strategies; systems biologists use them to study complex processes sustaining pathogens, from the metabolic networks empowering microbial cells to ecological networks in the microbiome that protects its host. Here, we (1) review important models relevant to infectious diseases, (2) draw parallels among models ranging widely in scale. We end by discussing a minimal set of information for a model to promote its use by others and to enable predictions that help us better fight pathogens and the diseases they cause.
Collapse
Affiliation(s)
- Joao B. Xavier
- Program for Computational and Systems Biology, Memorial Sloan-Kettering Cancer Center, New York, NY, USA
| | | | - Saugat Poudel
- Department of Bioengineering, UC San Diego, San Diego, CA, USA
| | | | - Anand V. Sastry
- Department of Bioengineering, UC San Diego, San Diego, CA, USA
| | - Chen Liao
- Program for Computational and Systems Biology, Memorial Sloan-Kettering Cancer Center, New York, NY, USA
| | - Jose Bento
- Computer Science Department, Boston College, Chestnut Hill, MA, USA
| | - Marc A. Suchard
- Department of Computational Medicine, David Geffen School of Medicine at UCLA, University of California, Los Angeles, CA, USA
| | | | | | | | - Thomas Stoeger
- Department of Chemical and Biological Engineering; Northwestern University, Evanston, IL 60208, USA
- Successful Clinical Response in Pneumonia Therapy (SCRIPT) Systems Biology Center, Northwestern University, Chicago, IL, USA
| | - Felicia Ruffin
- Division of Infectious Diseases, Department of Medicine, Duke University School of Medicine, Durham, NC, USA
| | - Reese A.K. Richardson
- Department of Chemical and Biological Engineering; Northwestern University, Evanston, IL 60208, USA
- Successful Clinical Response in Pneumonia Therapy (SCRIPT) Systems Biology Center, Northwestern University, Chicago, IL, USA
| | - Catherine A. Gao
- Successful Clinical Response in Pneumonia Therapy (SCRIPT) Systems Biology Center, Northwestern University, Chicago, IL, USA
- Division of Pulmonary and Critical Care, Northwestern University Feinberg School of Medicine, Chicago, IL 60611, USA
| | - Thomas D. Horvath
- Department of Pathology and Immunology, Baylor College of Medicine, Houston, TX 77030, USA
- Department of Pathology, Texas Children’s Microbiome Center, Texas Children’s Hospital, Houston, TX 77030, USA
| | - Anthony M. Haag
- Department of Pathology and Immunology, Baylor College of Medicine, Houston, TX 77030, USA
- Department of Pathology, Texas Children’s Microbiome Center, Texas Children’s Hospital, Houston, TX 77030, USA
| | - Qinglong Wu
- Department of Pathology and Immunology, Baylor College of Medicine, Houston, TX 77030, USA
- Department of Pathology, Texas Children’s Microbiome Center, Texas Children’s Hospital, Houston, TX 77030, USA
| | - Tor Savidge
- Department of Pathology and Immunology, Baylor College of Medicine, Houston, TX 77030, USA
- Department of Pathology, Texas Children’s Microbiome Center, Texas Children’s Hospital, Houston, TX 77030, USA
| | - Michael R. Yeaman
- David Geffen School of Medicine at UCLA & Lundquist Institute for Infection & Immunity at Harbor UCLA Medical Center, Los Angeles, CA, USA
| |
Collapse
|
16
|
Srinivas V, Ruiz RA, Pan M, Immanuel SRC, Peterson EJ, Baliga NS. Transcriptome signature of cell viability predicts drug response and drug interaction in Mycobacterium tuberculosis. Cell Rep Methods 2021; 1:None. [PMID: 34977849 PMCID: PMC8688151 DOI: 10.1016/j.crmeth.2021.100123] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/05/2021] [Revised: 08/23/2021] [Accepted: 11/08/2021] [Indexed: 12/23/2022]
Abstract
There is an urgent need for new drug regimens to rapidly cure tuberculosis. Here, we report the development of drug response assayer (DRonA) and "MLSynergy," algorithms to perform rapid drug response assays and predict response of Mycobacterium tuberculosis (Mtb) to drug combinations. Using a transcriptome signature for cell viability, DRonA detects Mtb killing by diverse mechanisms in broth culture, macrophage infection, and patient sputum, providing an efficient and more sensitive alternative to time- and resource-intensive bacteriologic assays. Further, MLSynergy builds on DRonA to predict synergistic and antagonistic multidrug combinations using transcriptomes of Mtb treated with single drugs. Together, DRonA and MLSynergy represent a generalizable framework for rapid monitoring of drug effects in host-relevant contexts and accelerate the discovery of efficacious high-order drug combinations.
Collapse
Affiliation(s)
| | | | - Min Pan
- Institute for Systems Biology, Seattle, WA, USA
| | | | | | - Nitin S. Baliga
- Institute for Systems Biology, Seattle, WA, USA
- Departments of Biology and Microbiology, University of Washington, Seattle, WA, USA
- Molecular and Cellular Biology Program, University of Washington, Seattle, WA, USA
- Lawrence Berkeley National Lab, Berkeley, CA, USA
| |
Collapse
|
17
|
Immanuel SRC, Arrieta-Ortiz ML, Ruiz RA, Pan M, Lopez Garcia de Lomana A, Peterson EJR, Baliga NS. Quantitative prediction of conditional vulnerabilities in regulatory and metabolic networks using PRIME. NPJ Syst Biol Appl 2021; 7:43. [PMID: 34873198 PMCID: PMC8648758 DOI: 10.1038/s41540-021-00205-6] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2021] [Accepted: 11/02/2021] [Indexed: 12/04/2022] Open
Abstract
The ability of Mycobacterium tuberculosis (Mtb) to adopt heterogeneous physiological states underlies its success in evading the immune system and tolerating antibiotic killing. Drug tolerant phenotypes are a major reason why the tuberculosis (TB) mortality rate is so high, with over 1.8 million deaths annually. To develop new TB therapeutics that better treat the infection (faster and more completely), a systems-level approach is needed to reveal the complexity of network-based adaptations of Mtb. Here, we report a new predictive model called PRIME (Phenotype of Regulatory influences Integrated with Metabolism and Environment) to uncover environment-specific vulnerabilities within the regulatory and metabolic networks of Mtb. Through extensive performance evaluations using genome-wide fitness screens, we demonstrate that PRIME makes mechanistically accurate predictions of context-specific vulnerabilities within the integrated regulatory and metabolic networks of Mtb, accurately rank-ordering targets for potentiating treatment with frontline drugs.
Collapse
Affiliation(s)
| | | | - Rene A Ruiz
- Institute for Systems Biology, Seattle, WA, USA
| | - Min Pan
- Institute for Systems Biology, Seattle, WA, USA
| | - Adrian Lopez Garcia de Lomana
- Institute for Systems Biology, Seattle, WA, USA
- Center for Systems Biology, University of Iceland, Reykjavik, Iceland
| | | | - Nitin S Baliga
- Institute for Systems Biology, Seattle, WA, USA.
- Departments of Biology and Microbiology, University of Washington, Seattle, WA, USA.
- Molecular and Cellular Biology Program, University of Washington, Seattle, WA, USA.
- Lawrence Berkeley National Lab, Berkeley, CA, USA.
| |
Collapse
|
18
|
Girinathan BP, DiBenedetto N, Worley JN, Peltier J, Arrieta-Ortiz ML, Immanuel SRC, Lavin R, Delaney ML, Cummins CK, Hoffman M, Luo Y, Gonzalez-Escalona N, Allard M, Onderdonk AB, Gerber GK, Sonenshein AL, Baliga NS, Dupuy B, Bry L. In vivo commensal control of Clostridioides difficile virulence. Cell Host Microbe 2021; 29:1693-1708.e7. [PMID: 34637781 DOI: 10.1016/j.chom.2021.09.007] [Citation(s) in RCA: 54] [Impact Index Per Article: 18.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2021] [Revised: 07/26/2021] [Accepted: 09/16/2021] [Indexed: 12/23/2022]
Abstract
Leveraging systems biology approaches, we illustrate how metabolically distinct species of Clostridia protect against or worsen Clostridioides difficile infection in mice by modulating the pathogen's colonization, growth, and virulence to impact host survival. Gnotobiotic mice colonized with the amino acid fermenter Paraclostridium bifermentans survive infection with reduced disease severity, while mice colonized with the butyrate-producer, Clostridium sardiniense, succumb more rapidly. Systematic in vivo analyses revealed how each commensal alters the gut-nutrient environment to modulate the pathogen's metabolism, gene regulatory networks, and toxin production. Oral administration of P. bifermentans rescues conventional, clindamycin-treated mice from lethal C. difficile infection in a manner similar to that of monocolonized animals, thereby supporting the therapeutic potential of this commensal species. Our findings lay the foundation for mechanistically informed therapies to counter C. difficile disease using systems biology approaches to define host-commensal-pathogen interactions in vivo.
Collapse
Affiliation(s)
- Brintha P Girinathan
- Massachusetts Host-Microbiome Center, Brigham & Women's Hospital, Harvard Medical School, Boston, MA 02115, USA
| | - Nicholas DiBenedetto
- Massachusetts Host-Microbiome Center, Brigham & Women's Hospital, Harvard Medical School, Boston, MA 02115, USA
| | - Jay N Worley
- Massachusetts Host-Microbiome Center, Brigham & Women's Hospital, Harvard Medical School, Boston, MA 02115, USA; National Center of Biotechnology Information, National Library of Medicine, Bethesda, MD 20894, USA
| | - Johann Peltier
- Laboratoire Pathogenèse des Bactéries Anaérobies, Institut Pasteur, UMR CNRS 2001, Université de Paris, 25-28 Rue du Dr. Roux, Institut Pasteur, 75015 Paris Cedex, France; Institute for Integrative Biology of the Cell (I2BC), CEA, CNRS, Université Paris-Saclay, 91198, Gif-sur-yvette Cedex, France
| | | | | | - Richard Lavin
- Massachusetts Host-Microbiome Center, Brigham & Women's Hospital, Harvard Medical School, Boston, MA 02115, USA
| | - Mary L Delaney
- Massachusetts Host-Microbiome Center, Brigham & Women's Hospital, Harvard Medical School, Boston, MA 02115, USA; Clinical Microbiology Laboratory, Department of Pathology, Brigham & Women's Hospital, Boston, MA 02115, USA
| | - Christopher K Cummins
- Massachusetts Host-Microbiome Center, Brigham & Women's Hospital, Harvard Medical School, Boston, MA 02115, USA
| | - Maria Hoffman
- Center for Food Safety and Applied Nutrition, United States Food and Drug Administration, Department of Microbiology, College Park, MD 20740, USA
| | - Yan Luo
- Center for Food Safety and Applied Nutrition, United States Food and Drug Administration, Department of Microbiology, College Park, MD 20740, USA
| | - Narjol Gonzalez-Escalona
- Center for Food Safety and Applied Nutrition, United States Food and Drug Administration, Department of Microbiology, College Park, MD 20740, USA
| | - Marc Allard
- Center for Food Safety and Applied Nutrition, United States Food and Drug Administration, Department of Microbiology, College Park, MD 20740, USA
| | - Andrew B Onderdonk
- Massachusetts Host-Microbiome Center, Brigham & Women's Hospital, Harvard Medical School, Boston, MA 02115, USA; Clinical Microbiology Laboratory, Department of Pathology, Brigham & Women's Hospital, Boston, MA 02115, USA
| | - Georg K Gerber
- Massachusetts Host-Microbiome Center, Brigham & Women's Hospital, Harvard Medical School, Boston, MA 02115, USA; Harvard-MIT Health Sciences & Technology, Cambridge, MA 02139, USA
| | - Abraham L Sonenshein
- Department of Molecular Biology and Microbiology, Tufts University School of Medicine, Boston, MA 02111, USA
| | | | - Bruno Dupuy
- Laboratoire Pathogenèse des Bactéries Anaérobies, Institut Pasteur, UMR CNRS 2001, Université de Paris, 25-28 Rue du Dr. Roux, Institut Pasteur, 75015 Paris Cedex, France
| | - Lynn Bry
- Massachusetts Host-Microbiome Center, Brigham & Women's Hospital, Harvard Medical School, Boston, MA 02115, USA; Clinical Microbiology Laboratory, Department of Pathology, Brigham & Women's Hospital, Boston, MA 02115, USA.
| |
Collapse
|
19
|
Arrieta-Ortiz ML, Immanuel SRC, Turkarslan S, Wu WJ, Girinathan BP, Worley JN, DiBenedetto N, Soutourina O, Peltier J, Dupuy B, Bry L, Baliga NS. Predictive regulatory and metabolic network models for systems analysis of Clostridioides difficile. Cell Host Microbe 2021; 29:1709-1723.e5. [PMID: 34637780 PMCID: PMC8595754 DOI: 10.1016/j.chom.2021.09.008] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2021] [Revised: 07/29/2021] [Accepted: 09/16/2021] [Indexed: 12/15/2022]
Abstract
We present predictive models for comprehensive systems analysis of Clostridioides difficile, the etiology of pseudomembranous colitis. By leveraging 151 published transcriptomes, we generated an EGRIN model that organizes 90% of C. difficile genes into a transcriptional regulatory network of 297 co-regulated modules, implicating genes in sporulation, carbohydrate transport, and metabolism. By advancing a metabolic model through addition and curation of metabolic reactions including nutrient uptake, we discovered 14 amino acids, diverse carbohydrates, and 10 metabolic genes as essential for C. difficile growth in the intestinal environment. Finally, we developed a PRIME model to uncover how EGRIN-inferred combinatorial gene regulation by transcription factors, such as CcpA and CodY, modulates essential metabolic processes to enable C. difficile growth relative to commensal colonization. The C. difficile interactive web portal provides access to these model resources to support collaborative systems-level studies of context-specific virulence mechanisms in C. difficile.
Collapse
Affiliation(s)
| | | | | | - Wei-Ju Wu
- Institute for Systems Biology, Seattle, WA 98109, USA
| | - Brintha P Girinathan
- Massachusetts Host-Microbiome Center, Brigham & Women's Hospital, Harvard Medical School, Boston, MA 02115, USA
| | - Jay N Worley
- Massachusetts Host-Microbiome Center, Brigham & Women's Hospital, Harvard Medical School, Boston, MA 02115, USA
| | - Nicholas DiBenedetto
- Massachusetts Host-Microbiome Center, Brigham & Women's Hospital, Harvard Medical School, Boston, MA 02115, USA
| | - Olga Soutourina
- Université Paris-Saclay, CEA, CNRS, Institute for Integrative Biology of the Cell (I2BC), Gif-sur-yvette 91198, France
| | - Johann Peltier
- Université Paris-Saclay, CEA, CNRS, Institute for Integrative Biology of the Cell (I2BC), Gif-sur-yvette 91198, France
| | - Bruno Dupuy
- Laboratoire Pathogenèse des Bactéries anaérobies, Institut Pasteur, Université de Paris, UMR CNRS 2001, Paris 75015, France
| | - Lynn Bry
- Massachusetts Host-Microbiome Center, Brigham & Women's Hospital, Harvard Medical School, Boston, MA 02115, USA
| | | |
Collapse
|
20
|
Nivedita N, Aitchison JD, Baliga NS. Autophagy as a Mechanism for Adaptive Prediction-Mediated Emergence of Drug Resistance. Front Microbiol 2021; 12:712631. [PMID: 34566920 PMCID: PMC8461305 DOI: 10.3389/fmicb.2021.712631] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/20/2021] [Accepted: 08/23/2021] [Indexed: 11/13/2022] Open
Abstract
Drug resistance is a major problem in treatment of microbial infections and cancers. There is growing evidence that a transient drug tolerant state may precede and potentiate the emergence of drug resistance. Therefore, understanding the mechanisms leading to tolerance is critical for combating drug resistance and for the development of effective therapeutic strategy. Through laboratory evolution of yeast, we recently demonstrated that adaptive prediction (AP), a strategy employed by organisms to anticipate and prepare for a future stressful environment, can emerge within 100 generations by linking the response triggered by a neutral cue (caffeine) to a mechanism of protection against a lethal agent (5-fluoroorotic acid, 5-FOA). Here, we demonstrate that mutations selected across multiple laboratory-evolved lines had linked the neutral cue response to core genes of autophagy. Across these evolved lines, conditional activation of autophagy through AP conferred tolerance, and potentiated subsequent selection of mutations in genes specific to overcoming the toxicity of 5-FOA. These results offer a new perspective on how extensive genome-wide genetic interactions of autophagy could have facilitated the emergence of AP over short evolutionary timescales to potentiate selection of 5-FOA resistance-conferring mutations.
Collapse
|
21
|
Voolstra CR, Valenzuela JJ, Turkarslan S, Cárdenas A, Hume BCC, Perna G, Buitrago-López C, Rowe K, Orellana MV, Baliga NS, Paranjape S, Banc-Prandi G, Bellworthy J, Fine M, Frias-Torres S, Barshis DJ. Contrasting heat stress response patterns of coral holobionts across the Red Sea suggest distinct mechanisms of thermal tolerance. Mol Ecol 2021; 30:4466-4480. [PMID: 34342082 DOI: 10.1111/mec.16064] [Citation(s) in RCA: 32] [Impact Index Per Article: 10.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/25/2021] [Revised: 06/04/2021] [Accepted: 06/30/2021] [Indexed: 12/18/2022]
Abstract
Corals from the northern Red Sea, in particular the Gulf of Aqaba (GoA), have exceptionally high bleaching thresholds approaching >5℃ above their maximum monthly mean (MMM) temperatures. These elevated thresholds are thought to be due to historical selection, as corals passed through the warmer Southern Red Sea during recolonization from the Arabian Sea. To test this hypothesis, we determined thermal tolerance thresholds of GoA versus central Red Sea (CRS) Stylophora pistillata corals using multi-temperature acute thermal stress assays to determine thermal thresholds. Relative thermal thresholds of GoA and CRS corals were indeed similar and exceptionally high (~7℃ above MMM). However, absolute thermal thresholds of CRS corals were on average 3℃ above those of GoA corals. To explore the molecular underpinnings, we determined gene expression and microbiome response of the coral holobiont. Transcriptomic responses differed markedly, with a strong response to the thermal stress in GoA corals and their symbiotic algae versus a remarkably muted response in CRS colonies. Concomitant to this, coral and algal genes showed temperature-induced expression in GoA corals, while exhibiting fixed high expression (front-loading) in CRS corals. Bacterial community composition of GoA corals changed dramatically under heat stress, whereas CRS corals displayed stable assemblages. We interpret the response of GoA corals as that of a resilient population approaching a tipping point in contrast to a pattern of consistently elevated thermal resistance in CRS corals that cannot further attune. Such response differences suggest distinct thermal tolerance mechanisms that may affect the response of coral populations to ocean warming.
Collapse
Affiliation(s)
| | | | | | - Anny Cárdenas
- Department of Biology, University of Konstanz, Konstanz, Germany
| | | | - Gabriela Perna
- Department of Biology, University of Konstanz, Konstanz, Germany
| | | | - Katherine Rowe
- School of Science, The University of Waikato, Hamilton, New Zealand
| | - Monica V Orellana
- Institute for Systems Biology, Seattle, USA.,Polar Science Center, University of Washington, Seattle, USA
| | - Nitin S Baliga
- Institute for Systems Biology, Seattle, USA.,Departments of Biology and Microbiology, University of Washington, Seattle, USA.,Molecular and Cellular Biology Program, University of Washington, Seattle, USA.,Lawrence Berkeley National Laboratory, Berkeley, USA
| | | | - Guilhem Banc-Prandi
- The Interuniversity Institute for Marine Sciences (IUI), Eilat, Israel.,The Goodman Faculty of Life Sciences, Bar Ilan University, Ramat-Gan, Israel
| | - Jessica Bellworthy
- The Interuniversity Institute for Marine Sciences (IUI), Eilat, Israel.,The Goodman Faculty of Life Sciences, Bar Ilan University, Ramat-Gan, Israel
| | - Maoz Fine
- The Interuniversity Institute for Marine Sciences (IUI), Eilat, Israel.,The Goodman Faculty of Life Sciences, Bar Ilan University, Ramat-Gan, Israel
| | | | - Daniel J Barshis
- Department of Biological Sciences, Old Dominion University, Norfolk, USA
| |
Collapse
|
22
|
Turkarslan S, Stopnisek N, Thompson AW, Arens CE, Valenzuela JJ, Wilson J, Hunt KA, Hardwicke J, de Lomana ALG, Lim S, Seah YM, Fu Y, Wu L, Zhou J, Hillesland KL, Stahl DA, Baliga NS. Synergistic epistasis enhances the co-operativity of mutualistic interspecies interactions. ISME J 2021; 15:2233-2247. [PMID: 33612833 PMCID: PMC8319347 DOI: 10.1038/s41396-021-00919-9] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/26/2020] [Revised: 12/18/2020] [Accepted: 01/29/2021] [Indexed: 01/31/2023]
Abstract
Early evolution of mutualism is characterized by big and predictable adaptive changes, including the specialization of interacting partners, such as through deleterious mutations in genes not required for metabolic cross-feeding. We sought to investigate whether these early mutations improve cooperativity by manifesting in synergistic epistasis between genomes of the mutually interacting species. Specifically, we have characterized evolutionary trajectories of syntrophic interactions of Desulfovibrio vulgaris (Dv) with Methanococcus maripaludis (Mm) by longitudinally monitoring mutations accumulated over 1000 generations of nine independently evolved communities with analysis of the genotypic structure of one community down to the single-cell level. We discovered extensive parallelism across communities despite considerable variance in their evolutionary trajectories and the perseverance within many evolution lines of a rare lineage of Dv that retained sulfate-respiration (SR+) capability, which is not required for metabolic cross-feeding. An in-depth investigation revealed that synergistic epistasis across pairings of Dv and Mm genotypes had enhanced cooperativity within SR- and SR+ assemblages, enabling their coexistence within the same community. Thus, our findings demonstrate that cooperativity of a mutualism can improve through synergistic epistasis between genomes of the interacting species, enabling the coexistence of mutualistic assemblages of generalists and their specialized variants.
Collapse
Affiliation(s)
- Serdar Turkarslan
- grid.64212.330000 0004 0463 2320Institute for Systems Biology, Seattle, WA 98109 USA
| | - Nejc Stopnisek
- grid.34477.330000000122986657Civil and Environmental Engineering, University of Washington, Seattle, WA 98195 USA
| | - Anne W. Thompson
- grid.262075.40000 0001 1087 1481Department of Biology, Portland State University, Portland, OR 97201 USA
| | - Christina E. Arens
- grid.64212.330000 0004 0463 2320Institute for Systems Biology, Seattle, WA 98109 USA
| | - Jacob J. Valenzuela
- grid.64212.330000 0004 0463 2320Institute for Systems Biology, Seattle, WA 98109 USA
| | - James Wilson
- grid.64212.330000 0004 0463 2320Institute for Systems Biology, Seattle, WA 98109 USA
| | - Kristopher A. Hunt
- grid.34477.330000000122986657Civil and Environmental Engineering, University of Washington, Seattle, WA 98195 USA
| | - Jessica Hardwicke
- grid.34477.330000000122986657Civil and Environmental Engineering, University of Washington, Seattle, WA 98195 USA
| | | | - Sujung Lim
- grid.20861.3d0000000107068890Division of Geological and Planetary Sciences, California Institute of Technology, Pasadena, CA 91125 USA
| | - Yee Mey Seah
- grid.462982.30000 0000 8883 2602Biological Sciences, University of Washington Bothell, Bothell, WA 98011 USA
| | - Ying Fu
- grid.266900.b0000 0004 0447 0018Institute for Environmental Genomics and Department of Microbiology & Plant Biology, University of Oklahoma, Norman, OK 73072 USA
| | - Liyou Wu
- grid.266900.b0000 0004 0447 0018Institute for Environmental Genomics and Department of Microbiology & Plant Biology, University of Oklahoma, Norman, OK 73072 USA
| | - Jizhong Zhou
- grid.266900.b0000 0004 0447 0018Institute for Environmental Genomics and Department of Microbiology & Plant Biology, University of Oklahoma, Norman, OK 73072 USA
| | - Kristina L. Hillesland
- grid.462982.30000 0000 8883 2602Biological Sciences, University of Washington Bothell, Bothell, WA 98011 USA
| | - David A. Stahl
- grid.34477.330000000122986657Civil and Environmental Engineering, University of Washington, Seattle, WA 98195 USA
| | - Nitin S. Baliga
- grid.64212.330000 0004 0463 2320Institute for Systems Biology, Seattle, WA 98109 USA
| |
Collapse
|
23
|
Park JH, de Lomana ALG, Marzese DM, Juarez T, Feroze A, Hothi P, Cobbs C, Patel AP, Kesari S, Huang S, Baliga NS. A Systems Approach to Brain Tumor Treatment. Cancers (Basel) 2021; 13:3152. [PMID: 34202449 PMCID: PMC8269017 DOI: 10.3390/cancers13133152] [Citation(s) in RCA: 19] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2021] [Revised: 06/11/2021] [Accepted: 06/17/2021] [Indexed: 12/12/2022] Open
Abstract
Brain tumors are among the most lethal tumors. Glioblastoma, the most frequent primary brain tumor in adults, has a median survival time of approximately 15 months after diagnosis or a five-year survival rate of 10%; the recurrence rate is nearly 90%. Unfortunately, this prognosis has not improved for several decades. The lack of progress in the treatment of brain tumors has been attributed to their high rate of primary therapy resistance. Challenges such as pronounced inter-patient variability, intratumoral heterogeneity, and drug delivery across the blood-brain barrier hinder progress. A comprehensive, multiscale understanding of the disease, from the molecular to the whole tumor level, is needed to address the intratumor heterogeneity resulting from the coexistence of a diversity of neoplastic and non-neoplastic cell types in the tumor tissue. By contrast, inter-patient variability must be addressed by subtyping brain tumors to stratify patients and identify the best-matched drug(s) and therapies for a particular patient or cohort of patients. Accomplishing these diverse tasks will require a new framework, one involving a systems perspective in assessing the immense complexity of brain tumors. This would in turn entail a shift in how clinical medicine interfaces with the rapidly advancing high-throughput (HTP) technologies that have enabled the omics-scale profiling of molecular features of brain tumors from the single-cell to the tissue level. However, several gaps must be closed before such a framework can fulfill the promise of precision and personalized medicine for brain tumors. Ultimately, the goal is to integrate seamlessly multiscale systems analyses of patient tumors and clinical medicine. Accomplishing this goal would facilitate the rational design of therapeutic strategies matched to the characteristics of patients and their tumors. Here, we discuss some of the technologies, methodologies, and computational tools that will facilitate the realization of this vision to practice.
Collapse
Affiliation(s)
- James H. Park
- Institute for Systems Biology, Seattle, WA 98109, USA; (J.H.P.); (S.H.)
| | | | - Diego M. Marzese
- Balearic Islands Health Research Institute (IdISBa), 07010 Palma, Spain;
| | - Tiffany Juarez
- St. John’s Cancer Institute, Santa Monica, CA 90401, USA; (T.J.); (S.K.)
| | - Abdullah Feroze
- Department of Neurological Surgery, University of Washington, Seattle, WA 98195, USA; (A.F.); (A.P.P.)
| | - Parvinder Hothi
- Swedish Neuroscience Institute, Seattle, WA 98122, USA; (P.H.); (C.C.)
- Ben and Catherine Ivy Center for Advanced Brain Tumor Treatment, Seattle, WA 98122, USA
| | - Charles Cobbs
- Swedish Neuroscience Institute, Seattle, WA 98122, USA; (P.H.); (C.C.)
- Ben and Catherine Ivy Center for Advanced Brain Tumor Treatment, Seattle, WA 98122, USA
| | - Anoop P. Patel
- Department of Neurological Surgery, University of Washington, Seattle, WA 98195, USA; (A.F.); (A.P.P.)
- Human Biology Division, Fred Hutchinson Cancer Research Center, Seattle, WA 98109, USA
- Brotman-Baty Institute for Precision Medicine, University of Washington, Seattle, WA 98195, USA
| | - Santosh Kesari
- St. John’s Cancer Institute, Santa Monica, CA 90401, USA; (T.J.); (S.K.)
| | - Sui Huang
- Institute for Systems Biology, Seattle, WA 98109, USA; (J.H.P.); (S.H.)
| | - Nitin S. Baliga
- Institute for Systems Biology, Seattle, WA 98109, USA; (J.H.P.); (S.H.)
- Departments of Microbiology, Biology, and Molecular Engineering Sciences, University of Washington, Seattle, WA 98105, USA
| |
Collapse
|
24
|
Peterson EJR, Abidi AA, Arrieta-Ortiz ML, Aguilar B, Yurkovich JT, Kaur A, Pan M, Srinivas V, Shmulevich I, Baliga NS. Intricate Genetic Programs Controlling Dormancy in Mycobacterium tuberculosis. Cell Rep 2021; 35:109287. [PMID: 34133939 PMCID: PMC8274401 DOI: 10.1016/j.celrep.2021.109287] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/23/2022] Open
|
25
|
Peterson EJR, Abidi AA, Arrieta-Ortiz ML, Aguilar B, Yurkovich JT, Kaur A, Pan M, Srinivas V, Shmulevich I, Baliga NS. Intricate Genetic Programs Controlling Dormancy in Mycobacterium tuberculosis. Cell Rep 2021; 31:107577. [PMID: 32348771 PMCID: PMC7605849 DOI: 10.1016/j.celrep.2020.107577] [Citation(s) in RCA: 18] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/14/2019] [Revised: 12/18/2019] [Accepted: 04/06/2020] [Indexed: 11/24/2022] Open
Abstract
Mycobacterium tuberculosis (MTB) displays the remarkable ability to transition in and out of dormancy, a hallmark of the pathogen’s capacity to evade the immune system and exploit susceptible individuals. Uncovering the gene regulatory programs that underlie the phenotypic shifts in MTB during disease latency and reactivation has posed a challenge. We develop an experimental system to precisely control dissolved oxygen levels in MTB cultures in order to capture the transcriptional events that unfold as MTB transitions into and out of hypoxia-induced dormancy. Using a comprehensive genome-wide transcription factor binding map and insights from network topology analysis, we identify regulatory circuits that deterministically drive sequential transitions across six transcriptionally and functionally distinct states encompassing more than three-fifths of the MTB genome. The architecture of the genetic programs explains the transcriptional dynamics underlying synchronous entry of cells into a dormant state that is primed to infect the host upon encountering favorable conditions. Mycobacterium tuberculosis (MTB) persists within the host by counteracting disparate stressors including hypoxia. Peterson et al. report a transcriptional program that coordinates sequential state transitions to drive MTB in and out of hypoxia-induced dormancy. Among varied properties, this program encodes advanced preparedness to infect the host in favorable conditions.
Collapse
Affiliation(s)
| | - Abrar A Abidi
- Institute for Systems Biology, Seattle, WA 98109, USA
| | | | - Boris Aguilar
- Institute for Systems Biology, Seattle, WA 98109, USA
| | | | - Amardeep Kaur
- Institute for Systems Biology, Seattle, WA 98109, USA
| | - Min Pan
- Institute for Systems Biology, Seattle, WA 98109, USA
| | | | | | - Nitin S Baliga
- Institute for Systems Biology, Seattle, WA 98109, USA; Molecular and Cellular Biology Program, Departments of Microbiology and Biology, University of Washington, Seattle, WA; Lawrence Berkeley National Laboratories, Berkeley, CA.
| |
Collapse
|
26
|
Azer K, Kaddi CD, Barrett JS, Bai JPF, McQuade ST, Merrill NJ, Piccoli B, Neves-Zaph S, Marchetti L, Lombardo R, Parolo S, Immanuel SRC, Baliga NS. History and Future Perspectives on the Discipline of Quantitative Systems Pharmacology Modeling and Its Applications. Front Physiol 2021; 12:637999. [PMID: 33841175 PMCID: PMC8027332 DOI: 10.3389/fphys.2021.637999] [Citation(s) in RCA: 17] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2020] [Accepted: 01/25/2021] [Indexed: 12/24/2022] Open
Abstract
Mathematical biology and pharmacology models have a long and rich history in the fields of medicine and physiology, impacting our understanding of disease mechanisms and the development of novel therapeutics. With an increased focus on the pharmacology application of system models and the advances in data science spanning mechanistic and empirical approaches, there is a significant opportunity and promise to leverage these advancements to enhance the development and application of the systems pharmacology field. In this paper, we will review milestones in the evolution of mathematical biology and pharmacology models, highlight some of the gaps and challenges in developing and applying systems pharmacology models, and provide a vision for an integrated strategy that leverages advances in adjacent fields to overcome these challenges.
Collapse
Affiliation(s)
- Karim Azer
- Quantitative Sciences, Bill and Melinda Gates Medical Research Institute, Cambridge, MA, United States
| | - Chanchala D. Kaddi
- Quantitative Sciences, Bill and Melinda Gates Medical Research Institute, Cambridge, MA, United States
| | | | - Jane P. F. Bai
- Office of Clinical Pharmacology, Center for Drug Evaluation and Research, U.S. Food and Drug Administration, Silver Spring, MD, United States
| | - Sean T. McQuade
- Center for Computational and Integrative Biology, Rutgers University, Camden, NJ, United States
| | - Nathaniel J. Merrill
- Center for Computational and Integrative Biology, Rutgers University, Camden, NJ, United States
| | - Benedetto Piccoli
- Department of Mathematical Sciences and Center for Computational and Integrative Biology, Rutgers University, Camden, NJ, United States
| | - Susana Neves-Zaph
- Translational Disease Modeling, Data and Data Science, Sanofi, Bridgewater, NJ, United States
| | - Luca Marchetti
- Fondazione the Microsoft Research – University of Trento Centre for Computational and Systems Biology (COSBI), Rovereto, Italy
| | - Rosario Lombardo
- Fondazione the Microsoft Research – University of Trento Centre for Computational and Systems Biology (COSBI), Rovereto, Italy
| | - Silvia Parolo
- Fondazione the Microsoft Research – University of Trento Centre for Computational and Systems Biology (COSBI), Rovereto, Italy
| | | | | |
Collapse
|
27
|
Lui LM, Majumder ELW, Smith HJ, Carlson HK, von Netzer F, Fields MW, Stahl DA, Zhou J, Hazen TC, Baliga NS, Adams PD, Arkin AP. Mechanism Across Scales: A Holistic Modeling Framework Integrating Laboratory and Field Studies for Microbial Ecology. Front Microbiol 2021; 12:642422. [PMID: 33841364 PMCID: PMC8024649 DOI: 10.3389/fmicb.2021.642422] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2020] [Accepted: 02/22/2021] [Indexed: 11/13/2022] Open
Abstract
Over the last century, leaps in technology for imaging, sampling, detection, high-throughput sequencing, and -omics analyses have revolutionized microbial ecology to enable rapid acquisition of extensive datasets for microbial communities across the ever-increasing temporal and spatial scales. The present challenge is capitalizing on our enhanced abilities of observation and integrating diverse data types from different scales, resolutions, and disciplines to reach a causal and mechanistic understanding of how microbial communities transform and respond to perturbations in the environment. This type of causal and mechanistic understanding will make predictions of microbial community behavior more robust and actionable in addressing microbially mediated global problems. To discern drivers of microbial community assembly and function, we recognize the need for a conceptual, quantitative framework that connects measurements of genomic potential, the environment, and ecological and physical forces to rates of microbial growth at specific locations. We describe the Framework for Integrated, Conceptual, and Systematic Microbial Ecology (FICSME), an experimental design framework for conducting process-focused microbial ecology studies that incorporates biological, chemical, and physical drivers of a microbial system into a conceptual model. Through iterative cycles that advance our understanding of the coupling across scales and processes, we can reliably predict how perturbations to microbial systems impact ecosystem-scale processes or vice versa. We describe an approach and potential applications for using the FICSME to elucidate the mechanisms of globally important ecological and physical processes, toward attaining the goal of predicting the structure and function of microbial communities in chemically complex natural environments.
Collapse
Affiliation(s)
- Lauren M. Lui
- Division of Environmental Genomics and Systems Biology, Lawrence Berkeley National Laboratory, Berkeley, CA, United States
| | - Erica L.-W. Majumder
- Department of Bacteriology, University of Wisconsin–Madison, Madison, WI, United States
| | - Heidi J. Smith
- Center for Biofilm Engineering, Department of Microbiology and Immunology, Montana State University, Bozeman, MT, United States
| | - Hans K. Carlson
- Division of Environmental Genomics and Systems Biology, Lawrence Berkeley National Laboratory, Berkeley, CA, United States
| | - Frederick von Netzer
- Department of Civil and Environmental Engineering, University of Washington, Seattle, WA, United States
| | - Matthew W. Fields
- Center for Biofilm Engineering, Department of Microbiology and Immunology, Montana State University, Bozeman, MT, United States
| | - David A. Stahl
- Department of Civil and Environmental Engineering, University of Washington, Seattle, WA, United States
| | - Jizhong Zhou
- Institute for Environmental Genomics, Department of Microbiology & Plant Biology, School of Civil Engineering and Environmental Sciences, University of Oklahoma, Norman, OK, United States
| | - Terry C. Hazen
- Department of Civil and Environmental Engineering, University of Tennessee, Knoxville, Knoxville, TN, United States
| | | | - Paul D. Adams
- Division of Environmental Genomics and Systems Biology, Lawrence Berkeley National Laboratory, Berkeley, CA, United States
- Department of Bioengineering, University of California, Berkeley, Berkeley, CA, United States
| | - Adam P. Arkin
- Division of Environmental Genomics and Systems Biology, Lawrence Berkeley National Laboratory, Berkeley, CA, United States
- Department of Bioengineering, University of California, Berkeley, Berkeley, CA, United States
| |
Collapse
|
28
|
Day JA, Diener C, Otwell AE, Tams KE, Bebout B, Detweiler AM, Lee MD, Scott MT, Ta W, Ha M, Carreon SA, Tong K, Ali AA, Gibbons SM, Baliga NS. Lettuce (Lactuca sativa) productivity influenced by microbial inocula under nitrogen-limited conditions in aquaponics. PLoS One 2021; 16:e0247534. [PMID: 33621265 PMCID: PMC7901782 DOI: 10.1371/journal.pone.0247534] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2020] [Accepted: 02/08/2021] [Indexed: 01/04/2023] Open
Abstract
The demand for food will outpace productivity of conventional agriculture due to projected growth of the human population, concomitant with shrinkage of arable land, increasing scarcity of freshwater, and a rapidly changing climate. While aquaponics has potential to sustainably supplement food production with minimal environmental impact, there is a need to better characterize the complex interplay between the various components (fish, plant, microbiome) of these systems to optimize scale up and productivity. Here, we investigated how the commonly-implemented practice of continued microbial community transfer from pre-existing systems might promote or impede productivity of aquaponics. Specifically, we monitored plant growth phenotypes, water chemistry, and microbiome composition of rhizospheres, biofilters, and fish feces over 61-days of lettuce (Lactuca sativa var. crispa) growth in nitrogen-limited aquaponic systems inoculated with bacteria that were either commercially sourced or originating from a pre-existing aquaponic system. Lettuce above- and below-ground growth were significantly reduced across replicates treated with a pre-existing aquaponic system inoculum when compared to replicates treated with a commercial inoculum. Reduced productivity was associated with enrichment in specific bacterial genera in plant roots, including Pseudomonas, following inoculum transfer from pre-existing systems. Increased productivity was associated with enrichment of nitrogen-fixing Rahnella in roots of plants treated with the commercial inoculum. Thus, we show that inoculation from a pre-existing system, rather than from a commercial inoculum, is associated with lower yields. Further work will be necessary to test the putative mechanisms involved.
Collapse
Affiliation(s)
- Jessica A. Day
- Institute for Systems Biology, Seattle, Washington, United States of America
| | - Christian Diener
- Institute for Systems Biology, Seattle, Washington, United States of America
| | - Anne E. Otwell
- Institute for Systems Biology, Seattle, Washington, United States of America
| | - Kourtney E. Tams
- St. Edward’s University, Environmental Science and Policy, Behavioral and Social Sciences, Austin, Texas, United States of America
| | - Brad Bebout
- National Aeronautics and Space Administration, Exobiology Branch, NASA Ames Research Center, Mountain View, California, United States of America
| | - Angela M. Detweiler
- National Aeronautics and Space Administration, Exobiology Branch, NASA Ames Research Center, Mountain View, California, United States of America
- Bay Area Environmental Research Institute, Moffett Field, California, United States of America
| | - Michael D. Lee
- National Aeronautics and Space Administration, Exobiology Branch, NASA Ames Research Center, Mountain View, California, United States of America
- Blue Marble Space Institute of Science, Seattle, Washington, United States of America
| | - Madeline T. Scott
- Seattle Youth Employment Program, Seattle, Washington, United States of America
| | - Wilson Ta
- Seattle Youth Employment Program, Seattle, Washington, United States of America
| | - Monica Ha
- Seattle Youth Employment Program, Seattle, Washington, United States of America
| | - Shienna A. Carreon
- Seattle Youth Employment Program, Seattle, Washington, United States of America
| | - Kenny Tong
- Seattle Youth Employment Program, Seattle, Washington, United States of America
| | - Abdirizak A. Ali
- Seattle Youth Employment Program, Seattle, Washington, United States of America
| | - Sean M. Gibbons
- Institute for Systems Biology, Seattle, Washington, United States of America
- eScience Institute, University of Washington, Seattle, Washington, United States of America
- Department of Bioengineering, University of Washington, Seattle, Washington, United States of America
| | - Nitin S. Baliga
- Institute for Systems Biology, Seattle, Washington, United States of America
- Department of Microbiology, University of Washington, Seattle, Washington, United States of America
- Department of Biology, University of Washington, Seattle, Washington, United States of America
- Molecular Engineering and Sciences, University of Washington, Seattle, Washington, United States of America
- Lawrence Berkeley National Laboratories, Berkeley, California, United States of America
| |
Collapse
|
29
|
Midha MK, Kusebauch U, Shteynberg D, Kapil C, Bader SL, Reddy PJ, Campbell DS, Baliga NS, Moritz RL. A comprehensive spectral assay library to quantify the Escherichia coli proteome by DIA/SWATH-MS. Sci Data 2020; 7:389. [PMID: 33184295 PMCID: PMC7665006 DOI: 10.1038/s41597-020-00724-7] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/16/2020] [Accepted: 10/05/2020] [Indexed: 02/06/2023] Open
Abstract
Data-Independent Acquisition (DIA) is a method to improve consistent identification and precise quantitation of peptides and proteins by mass spectrometry (MS). The targeted data analysis strategy in DIA relies on spectral assay libraries that are generally derived from a priori measurements of peptides for each species. Although Escherichia coli (E. coli) is among the best studied model organisms, so far there is no spectral assay library for the bacterium publicly available. Here, we generated a spectral assay library for 4,014 of the 4,389 annotated E. coli proteins using one- and two-dimensional fractionated samples, and ion mobility separation enabling deep proteome coverage. We demonstrate the utility of this high-quality library with robustness in quantitation of the E. coli proteome and with rapid-chromatography to enhance throughput by targeted DIA-MS. The spectral assay library supports the detection and quantification of 91.5% of all E. coli proteins at high-confidence with 56,182 proteotypic peptides, making it a valuable resource for the scientific community. Data and spectral libraries are available via ProteomeXchange (PXD020761, PXD020785) and SWATHAtlas (SAL00222-28).
Collapse
Affiliation(s)
- Mukul K Midha
- Institute for Systems Biology, 401 Terry Ave N, Seattle, WA, 98109, USA
| | - Ulrike Kusebauch
- Institute for Systems Biology, 401 Terry Ave N, Seattle, WA, 98109, USA
| | - David Shteynberg
- Institute for Systems Biology, 401 Terry Ave N, Seattle, WA, 98109, USA
| | - Charu Kapil
- Institute for Systems Biology, 401 Terry Ave N, Seattle, WA, 98109, USA
| | - Samuel L Bader
- Institute for Systems Biology, 401 Terry Ave N, Seattle, WA, 98109, USA
| | | | - David S Campbell
- Institute for Systems Biology, 401 Terry Ave N, Seattle, WA, 98109, USA
| | - Nitin S Baliga
- Institute for Systems Biology, 401 Terry Ave N, Seattle, WA, 98109, USA
- Departments of Biology and Microbiology, University of Washington, Seattle, WA, USA
- Molecular and Cellular Biology Program, University of Washington, Seattle, WA, USA
- Lawrence Berkeley National Lab, Berkeley, CA, USA
| | - Robert L Moritz
- Institute for Systems Biology, 401 Terry Ave N, Seattle, WA, 98109, USA.
| |
Collapse
|
30
|
Mast FD, Navare AT, van der Sloot AM, Coulombe-Huntington J, Rout MP, Baliga NS, Kaushansky A, Chait BT, Aderem A, Rice CM, Sali A, Tyers M, Aitchison JD. Crippling life support for SARS-CoV-2 and other viruses through synthetic lethality. J Cell Biol 2020; 219:152015. [PMID: 32785687 PMCID: PMC7659715 DOI: 10.1083/jcb.202006159] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/25/2020] [Revised: 07/28/2020] [Accepted: 07/28/2020] [Indexed: 02/07/2023] Open
Abstract
With the rapid global spread of SARS-CoV-2, we have become acutely aware of the inadequacies of our ability to respond to viral epidemics. Although disrupting the viral life cycle is critical for limiting viral spread and disease, it has proven challenging to develop targeted and selective therapeutics. Synthetic lethality offers a promising but largely unexploited strategy against infectious viral disease; as viruses infect cells, they abnormally alter the cell state, unwittingly exposing new vulnerabilities in the infected cell. Therefore, we propose that effective therapies can be developed to selectively target the virally reconfigured host cell networks that accompany altered cellular states to cripple the host cell that has been converted into a virus factory, thus disrupting the viral life cycle.
Collapse
Affiliation(s)
- Fred D Mast
- Center for Global Infectious Disease Research, Seattle Children's Research Institute, Seattle, WA
| | - Arti T Navare
- Center for Global Infectious Disease Research, Seattle Children's Research Institute, Seattle, WA
| | - Almer M van der Sloot
- Institute for Research in Immunology and Cancer, Université de Montréal, Montreal, Canada
| | | | - Michael P Rout
- Laboratory of Cellular and Structural Biology, The Rockefeller University, New York, NY
| | | | - Alexis Kaushansky
- Center for Global Infectious Disease Research, Seattle Children's Research Institute, Seattle, WA.,Department of Pediatrics, University of Washington, Seattle, WA
| | - Brian T Chait
- Laboratory of Mass Spectrometry and Gaseous Ion Chemistry, The Rockefeller University, New York, NY
| | - Alan Aderem
- Center for Global Infectious Disease Research, Seattle Children's Research Institute, Seattle, WA.,Department of Pediatrics, University of Washington, Seattle, WA
| | - Charles M Rice
- Laboratory of Virology and Infectious Disease, The Rockefeller University, New York, NY
| | - Andrej Sali
- Department of Bioengineering and Therapeutic Sciences, Department of Pharmaceutical Chemistry, and California Institute for Quantitative Biosciences, University of California, San Francisco, San Francisco, CA
| | - Mike Tyers
- Institute for Research in Immunology and Cancer, Université de Montréal, Montreal, Canada
| | - John D Aitchison
- Center for Global Infectious Disease Research, Seattle Children's Research Institute, Seattle, WA.,Department of Pediatrics, University of Washington, Seattle, WA.,Department of Biochemistry, University of Washington, Seattle, WA
| |
Collapse
|
31
|
Baliga NS, Björkegren JLM, Boeke JD, Boutros M, Crawford NPS, Dudley AM, Farber CR, Jones A, Levey AI, Lusis AJ, Mak HC, Nadeau JH, Noyes MB, Petretto E, Seyfried NT, Steinmetz LM, Vonesch SC. The State of Systems Genetics in 2017. Cell Syst 2019; 4:7-15. [PMID: 28125793 DOI: 10.1016/j.cels.2017.01.005] [Citation(s) in RCA: 20] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2022]
Abstract
Cell Systems invited 16 experts to share their views on the field of systems genetics. In questions repeated in the headings, we asked them to define systems genetics, highlight its relevance to researchers outside the field, discuss what makes a strong systems genetics paper, and paint a picture of where the field is heading in the coming years. Their responses, ordered by the journal but otherwise unedited, make it clear that deciphering genotype to phenotype relationships is a central challenge of systems genetics and will require understanding how networks and higher-order properties of biological systems underlie complex traits. In addition, our experts illuminate the applications and relevance of systems genetics to human disease, the gut microbiome, development of tools that connect the global research community, sustainability, drug discovery, patient-specific disease and network models, and personalized treatments. Finally, a table of suggested reading provides a sample of influential work in the field.
Collapse
Affiliation(s)
| | - Johan L M Björkegren
- Department of Genetics and Genomic Sciences, Icahn Institute for Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York, NY 10029-6574, USA; Department of Medical Biochemistry and Biophysics, Vascular Biology Unit, Karolinska Institutet, Stockholm, Sweden; Department of Physiology, Institute of Biomedicine and Translation Medicine, University of Tartu, Estonia
| | - Jef D Boeke
- Institute for Systems Genetics, NYU Langone Medical Center, New York, NY, USA
| | - Michael Boutros
- German Cancer Research Center (DKFZ) and Heidelberg University, Germany
| | | | - Aimée M Dudley
- Pacific Northwest Research Institute, Seattle, Washington, USA
| | - Charles R Farber
- Departments of Public Health Sciences and Biochemistry and Molecular Genetics, Center for Public Health Genomics, University of Virginia, Charlottesville VA, 22908, USA
| | - Allan Jones
- European Molecular Biology Laboratory (EMBL), Genome Biology Unit, 69117 Heidelberg, Germany
| | - Allan I Levey
- Department of Neurology, Emory University School of Medicine, Atlanta, GA, USA
| | - Aldons J Lusis
- Department of Medicine; Department of Microbiology, Immunology and Molecular Genetics; Department of Human Genetics, University of California Los Angeles, California, USA
| | - H Craig Mak
- Cell Systems, Cell Press, Cambridge, MA, USA.
| | - Joseph H Nadeau
- Pacific Northwest Research Institute, Seattle, Washington, USA
| | - Marcus B Noyes
- Institute for Systems Genetics, NYU Langone Medical Center, New York, NY, USA
| | - Enrico Petretto
- Cardiovascular & Metabolic Disorders Program and Centre for Computational Biology, Duke-National University of Singapore (NUS) Medical School, Singapore
| | - Nicholas T Seyfried
- Department of Biochemistry and Neurology, Emory University School of Medicine, Atlanta, GA, USA
| | - Lars M Steinmetz
- European Molecular Biology Laboratory (EMBL), Genome Biology Unit, 69117 Heidelberg, Germany; Stanford Genome Technology Center, Stanford University, Palo Alto, CA 94304, USA; Department of Genetics, Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Sibylle C Vonesch
- European Molecular Biology Laboratory (EMBL), Genome Biology Unit, 69117 Heidelberg, Germany
| |
Collapse
|
32
|
Zengler K, Hofmockel K, Baliga NS, Behie SW, Bernstein HC, Brown JB, Dinneny JR, Floge SA, Forry SP, Hess M, Jackson SA, Jansson C, Lindemann SR, Pett-Ridge J, Maranas C, Venturelli OS, Wallenstein MD, Shank EA, Northen TR. EcoFABs: advancing microbiome science through standardized fabricated ecosystems. Nat Methods 2019; 16:567-571. [PMID: 31227812 PMCID: PMC6733021 DOI: 10.1038/s41592-019-0465-0] [Citation(s) in RCA: 56] [Impact Index Per Article: 11.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022]
Abstract
Microbiomes play critical roles in ecosystems and human health, yet in most cases scientists lack standardized and reproducible model microbial communities. The development of fabricated microbial ecosystems, which we term EcoFABs, will provide such model systems for microbiome studies.
Collapse
Affiliation(s)
- Karsten Zengler
- Department of Pediatrics, University of California, San Diego, CA, USA
- Center for Microbiome Innovation, University of California, San Diego, CA, USA
| | - Kirsten Hofmockel
- Environmental Molecular Sciences Laboratory, Pacific Northwest National Laboratory, Richland, WA, USA
- Department of Ecology, Evolution and Organismal Biology, Iowa State University, Ames, IA, USA
| | - Nitin S Baliga
- Institute for Systems Biology, Seattle, WA, USA
- Departments of Microbiology and Biology, University of Washington, Seattle, WA, USA
- Molecular and Cellular Biology Program, University of Washington, Seattle, WA, USA
| | - Scott W Behie
- Department of Plant and Microbial Biology, University of California, Berkeley, Berkeley, CA, USA
| | - Hans C Bernstein
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA, USA
- The Norwegian College of Fishery Science and Arctic Centre for Sustainable Energy, UiT-The Arctic University of Norway, Tromsø, Norway
| | - James B Brown
- Environmental Genomics and Systems Biology Division, Lawrence Berkeley National Laboratory, Berkeley, CA, USA
- Centre for Computational Biology, School of Biosciences, University of Birmingham, Birmingham, UK
- Statistics Department, University of California, Berkeley, Berkeley, CA, USA
- Preminon, LLC, Antioch, CA, USA
| | - José R Dinneny
- Department of Biology, Stanford University, Stanford, CA, USA
| | - Sheri A Floge
- Department of Microbiology, The Ohio State University, Columbus, OH, USA
- Department of Biology, Wake Forest University, Winston-Salem, NC, USA
| | - Samuel P Forry
- Biosystems and Biomaterials Division, National Institute of Standards and Technology, Gaithersburg, MD, USA
| | - Matthias Hess
- Department of Animal Science, University of California, Davis, Davis, CA, USA
| | - Scott A Jackson
- Biosystems and Biomaterials Division, National Institute of Standards and Technology, Gaithersburg, MD, USA
| | - Christer Jansson
- Environmental Molecular Sciences Laboratory, Pacific Northwest National Laboratory, Richland, WA, USA
| | - Stephen R Lindemann
- Whistler Center for Carbohydrate Research, Department of Food Science, Purdue University, West Lafayette, IN, USA
- Department of Nutrition Science, Purdue University, West Lafayette, IN, USA
| | - Jennifer Pett-Ridge
- Physical and Life Sciences Directorate, Lawrence Livermore National Laboratory, Livermore, CA, USA
| | - Costas Maranas
- Department of Chemical Engineering, The Pennsylvania State University, University Park, PA, USA
| | | | - Matthew D Wallenstein
- Department of Soil and Crop Sciences, Colorado State University, Fort Collins, CO, USA
| | - Elizabeth A Shank
- Department of Biology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Department of Microbiology and Immunology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Trent R Northen
- Environmental Genomics and Systems Biology Division, Lawrence Berkeley National Laboratory, Berkeley, CA, USA.
- DOE Joint Genome Institute, Walnut Creek, CA, USA.
| |
Collapse
|
33
|
Peterson EJ, Bailo R, Rothchild AC, Arrieta-Ortiz ML, Kaur A, Pan M, Mai D, Abidi AA, Cooper C, Aderem A, Bhatt A, Baliga NS. Path-seq identifies an essential mycolate remodeling program for mycobacterial host adaptation. Mol Syst Biol 2019; 15:e8584. [PMID: 30833303 PMCID: PMC6398593 DOI: 10.15252/msb.20188584] [Citation(s) in RCA: 40] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/23/2022] Open
Abstract
The success of Mycobacterium tuberculosis (MTB) stems from its ability to remain hidden from the immune system within macrophages. Here, we report a new technology (Path‐seq) to sequence miniscule amounts of MTB transcripts within up to million‐fold excess host RNA. Using Path‐seq and regulatory network analyses, we have discovered a novel transcriptional program for in vivo mycobacterial cell wall remodeling when the pathogen infects alveolar macrophages in mice. We have discovered that MadR transcriptionally modulates two mycolic acid desaturases desA1/desA2 to initially promote cell wall remodeling upon in vitro macrophage infection and, subsequently, reduces mycolate biosynthesis upon entering dormancy. We demonstrate that disrupting MadR program is lethal to diverse mycobacteria making this evolutionarily conserved regulator a prime antitubercular target for both early and late stages of infection.
Collapse
Affiliation(s)
| | - Rebeca Bailo
- School of Biosciences and Institute of Microbiology and Infection, University of Birmingham, Birmingham, UK
| | - Alissa C Rothchild
- Center for Global Infectious Disease Research, Seattle Children's Research Institute, Seattle, WA, USA
| | | | | | - Min Pan
- Institute for Systems Biology, Seattle, WA, USA
| | - Dat Mai
- Center for Global Infectious Disease Research, Seattle Children's Research Institute, Seattle, WA, USA
| | | | - Charlotte Cooper
- School of Biosciences and Institute of Microbiology and Infection, University of Birmingham, Birmingham, UK
| | - Alan Aderem
- Center for Global Infectious Disease Research, Seattle Children's Research Institute, Seattle, WA, USA
| | - Apoorva Bhatt
- School of Biosciences and Institute of Microbiology and Infection, University of Birmingham, Birmingham, UK
| | - Nitin S Baliga
- Institute for Systems Biology, Seattle, WA, USA .,Molecular and Cellular Biology Program, Departments of Microbiology and Biology, University of Washington, Seattle, WA, USA.,Lawrence Berkeley National Laboratories, Berkeley, CA, USA
| |
Collapse
|
34
|
Otwell AE, López García de Lomana A, Gibbons SM, Orellana MV, Baliga NS. Systems biology approaches towards predictive microbial ecology. Environ Microbiol 2018; 20:4197-4209. [DOI: 10.1111/1462-2920.14378] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2018] [Accepted: 08/14/2018] [Indexed: 01/17/2023]
Affiliation(s)
| | | | - Sean M. Gibbons
- Institute for Systems Biology Seattle WA USA
- eScience Institute, University of Washington Seattle WA USA
- Molecular and Cellular Biology Program University of Washington Seattle WA USA
| | - Mónica V. Orellana
- Institute for Systems Biology Seattle WA USA
- Polar Science Center Applied Physics Lab, University of Washington Seattle WA
| | - Nitin S. Baliga
- Institute for Systems Biology Seattle WA USA
- Molecular and Cellular Biology Program University of Washington Seattle WA USA
- Departments of Biology and Microbiology University of Washington Seattle WA USA
- Lawrence Berkeley National Lab Berkeley CA USA
| |
Collapse
|
35
|
Valenzuela JJ, López García de Lomana A, Lee A, Armbrust EV, Orellana MV, Baliga NS. Ocean acidification conditions increase resilience of marine diatoms. Nat Commun 2018; 9:2328. [PMID: 29899534 PMCID: PMC5997998 DOI: 10.1038/s41467-018-04742-3] [Citation(s) in RCA: 30] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2016] [Accepted: 05/21/2018] [Indexed: 11/25/2022] Open
Abstract
The fate of diatoms in future acidified oceans could have dramatic implications on marine ecosystems, because they account for ~40% of marine primary production. Here, we quantify resilience of Thalassiosira pseudonana in mid-20th century (300 ppm CO2) and future (1000 ppm CO2) conditions that cause ocean acidification, using a stress test that probes its ability to recover from incrementally higher amount of low-dose ultraviolet A (UVA) and B (UVB) radiation and re-initiate growth in day-night cycles, limited by nitrogen. While all cultures eventually collapse, those growing at 300 ppm CO2 succumb sooner. The underlying mechanism for collapse appears to be a system failure resulting from "loss of relational resilience," that is, inability to adopt physiological states matched to N-availability and phase of the diurnal cycle. Importantly, under elevated CO2 conditions diatoms sustain relational resilience over a longer timeframe, demonstrating increased resilience to future acidified ocean conditions. This stress test framework can be extended to evaluate and predict how various climate change associated stressors may impact microbial community resilience.
Collapse
Affiliation(s)
| | | | - Allison Lee
- Institute for Systems Biology, Seattle, WA, 98109, USA
| | - E V Armbrust
- School of Oceanography, University of Washington, Seattle, WA, 98105, USA
| | - Mónica V Orellana
- Institute for Systems Biology, Seattle, WA, 98109, USA.
- Applied Physics Laboratory, Polar Science Center, University of Washington, Seattle, WA, 98105, USA.
| | - Nitin S Baliga
- Institute for Systems Biology, Seattle, WA, 98109, USA.
- Departments of Biology and Microbiology, University of Washington, Seattle, WA, 98195, USA.
- Molecular and Cellular Biology Program, University of Washington, Seattle, WA, 98195, USA.
- Lawrence Berkeley National Lab, Berkeley, CA, 94720, USA.
| |
Collapse
|
36
|
Flores-Valdez MA, Pedroza-Roldán C, Aceves-Sánchez MDJ, Peterson EJR, Baliga NS, Hernández-Pando R, Troudt J, Creissen E, Izzo L, Bielefeldt-Ohmann H, Bickett T, Izzo AA. The BCGΔBCG1419c Vaccine Candidate Reduces Lung Pathology, IL-6, TNF-α, and IL-10 During Chronic TB Infection. Front Microbiol 2018; 9:1281. [PMID: 29946316 PMCID: PMC6005825 DOI: 10.3389/fmicb.2018.01281] [Citation(s) in RCA: 22] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2017] [Accepted: 05/25/2018] [Indexed: 12/14/2022] Open
Abstract
Mycobacterium tuberculosis (M. tuberculosis), the causative agent of human tuberculosis (TB), is estimated to be harbored by up to 2 billion people in a latent TB infection (LTBI) state. The only TB vaccine approved for use in humans, BCG, does not confer protection against establishment of or reactivation from LTBI, so new vaccine candidates are needed to specifically address this need. Following the hypothesis that mycobacterial biofilms resemble aspects of LTBI, we modified BCG by deleting the BCG1419c gene to create the BCGΔBCG1419c vaccine strain. In this study, we compared cytokine profiles, bacterial burden, and lung lesions after immunization with BCG or BCGΔBCG1419c before and after 6 months of aerosol infection with M. tuberculosis H37Rv in the resistant C57BL/6 mouse model. Our results show that in infected mice, BCGΔBCG1419c significantly reduced lung lesions and IL-6 in comparison to the unmodified BCG strain, and was the only vaccine that decreased production of TNF-α and IL-10 compared to non-vaccinated mice, while vaccination with BCG or BCGΔBCG1419c significantly reduced IFN-γ production. Moreover, transcriptome profiling of BCGΔBCG1419c suggests that compared to BCG, it has decreased expression of genes involved in mycolic acids (MAs) metabolism, and antigenic chaperones, which might be involved in reduced pathology compared to BCG-vaccinated mice.
Collapse
Affiliation(s)
- Mario A Flores-Valdez
- Biotecnología Médica y Farmacéutica, Centro de Investigación y Asistencia en Tecnología y Diseño del Estado de Jalisco, Guadalajara, Mexico
| | - César Pedroza-Roldán
- Departamento de Medicina Veterinaria, Centro Universitario de Ciencias Biológicas y Agropecuarias, Universidad de Guadalajara, Zapopan, Mexico
| | - Michel de Jesús Aceves-Sánchez
- Biotecnología Médica y Farmacéutica, Centro de Investigación y Asistencia en Tecnología y Diseño del Estado de Jalisco, Guadalajara, Mexico
| | | | - Nitin S Baliga
- Institute for Systems Biology, Seattle, WA, United States
| | - Rogelio Hernández-Pando
- Sección de Patología Experimental, Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán, Mexico City, Mexico
| | - JoLynn Troudt
- Department of Microbiology, Immunology and Pathology, Colorado State University, Fort Collins, CO, United States
| | - Elizabeth Creissen
- Department of Microbiology, Immunology and Pathology, Colorado State University, Fort Collins, CO, United States
| | - Linda Izzo
- Department of Microbiology, Immunology and Pathology, Colorado State University, Fort Collins, CO, United States
| | - Helle Bielefeldt-Ohmann
- Australian Infectious Diseases Research Centre, The University of Queensland, Saint Lucia, QLD, Australia.,School of Veterinary Science, The University of Queensland, Brisbane, QLD, Australia
| | - Thomas Bickett
- Department of Microbiology, Immunology and Pathology, Colorado State University, Fort Collins, CO, United States
| | - Angelo A Izzo
- Department of Microbiology, Immunology and Pathology, Colorado State University, Fort Collins, CO, United States
| |
Collapse
|
37
|
Ament SA, Pearl JR, Cantle JP, Bragg RM, Skene PJ, Coffey SR, Bergey DE, Wheeler VC, MacDonald ME, Baliga NS, Rosinski J, Hood LE, Carroll JB, Price ND. Transcriptional regulatory networks underlying gene expression changes in Huntington's disease. Mol Syst Biol 2018; 14:e7435. [PMID: 29581148 PMCID: PMC5868199 DOI: 10.15252/msb.20167435] [Citation(s) in RCA: 35] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2016] [Revised: 01/23/2018] [Accepted: 02/26/2018] [Indexed: 12/19/2022] Open
Abstract
Transcriptional changes occur presymptomatically and throughout Huntington's disease (HD), motivating the study of transcriptional regulatory networks (TRNs) in HD We reconstructed a genome-scale model for the target genes of 718 transcription factors (TFs) in the mouse striatum by integrating a model of genomic binding sites with transcriptome profiling of striatal tissue from HD mouse models. We identified 48 differentially expressed TF-target gene modules associated with age- and CAG repeat length-dependent gene expression changes in Htt CAG knock-in mouse striatum and replicated many of these associations in independent transcriptomic and proteomic datasets. Thirteen of 48 of these predicted TF-target gene modules were also differentially expressed in striatal tissue from human disease. We experimentally validated a specific model prediction that SMAD3 regulates HD-related gene expression changes using chromatin immunoprecipitation and deep sequencing (ChIP-seq) of mouse striatum. We found CAG repeat length-dependent changes in the genomic occupancy of SMAD3 and confirmed our model's prediction that many SMAD3 target genes are downregulated early in HD.
Collapse
Affiliation(s)
- Seth A Ament
- Institute for Systems Biology, Seattle, WA, USA
- Institute for Genome Sciences and Department of Psychiatry, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Jocelynn R Pearl
- Institute for Systems Biology, Seattle, WA, USA
- Molecular & Cellular Biology Graduate Program, University of Washington, Seattle, WA, USA
- Altius Institute for Biomedical Sciences, Seattle, WA, USA
| | - Jeffrey P Cantle
- Behavioral Neuroscience Program, Department of Psychology, Western Washington University, Bellingham, WA, USA
| | - Robert M Bragg
- Behavioral Neuroscience Program, Department of Psychology, Western Washington University, Bellingham, WA, USA
| | - Peter J Skene
- Basic Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
| | - Sydney R Coffey
- Behavioral Neuroscience Program, Department of Psychology, Western Washington University, Bellingham, WA, USA
| | | | - Vanessa C Wheeler
- Molecular Neurogenetics Unit, Center for Human Genetic Research, Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Marcy E MacDonald
- Molecular Neurogenetics Unit, Center for Human Genetic Research, Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | | | - Jim Rosinski
- CHDI Management, CHDI Foundation, Princeton, NJ, USA
| | | | - Jeffrey B Carroll
- Behavioral Neuroscience Program, Department of Psychology, Western Washington University, Bellingham, WA, USA
| | | |
Collapse
|
38
|
López García de Lomana A, Kaur A, Turkarslan S, Beer KD, Mast FD, Smith JJ, Aitchison JD, Baliga NS. Adaptive Prediction Emerges Over Short Evolutionary Time Scales. Genome Biol Evol 2017; 9:1616-1623. [PMID: 28854640 PMCID: PMC5570091 DOI: 10.1093/gbe/evx116] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 07/11/2017] [Indexed: 12/11/2022] Open
Abstract
Adaptive prediction is a capability of diverse organisms, including microbes, to sense a cue and prepare in advance to deal with a future environmental challenge. Here, we investigated the timeframe over which adaptive prediction emerges when an organism encounters an environment with novel structure. We subjected yeast to laboratory evolution in a novel environment with repetitive, coupled exposures to a neutral chemical cue (caffeine), followed by a sublethal dose of a toxin (5-FOA), with an interspersed requirement for uracil prototrophy to counter-select mutants that gained constitutive 5-FOA resistance. We demonstrate the remarkable ability of yeast to internalize a novel environmental pattern within 50-150 generations by adaptively predicting 5-FOA stress upon sensing caffeine. We also demonstrate how novel environmental structure can be internalized by coupling two unrelated response networks, such as the response to caffeine and signaling-mediated conditional peroxisomal localization of proteins.
Collapse
Affiliation(s)
| | | | | | - Karlyn D. Beer
- Institute for Systems Biology, Seattle, Washington
- Present address: Centers for Disease Control and Prevention, Atlanta, Georgia
| | - Fred D. Mast
- Institute for Systems Biology, Seattle, Washington
- Center for Infectious Disease Research, Seattle, Washington
| | - Jennifer J. Smith
- Institute for Systems Biology, Seattle, Washington
- Center for Infectious Disease Research, Seattle, Washington
| | - John D. Aitchison
- Institute for Systems Biology, Seattle, Washington
- Center for Infectious Disease Research, Seattle, Washington
- Molecular and Cellular Biology Program, University of Washington
- Department of Cell Biology, University of Alberta, Edmonton, Alberta, Canada
| | - Nitin S. Baliga
- Institute for Systems Biology, Seattle, Washington
- Molecular and Cellular Biology Program, University of Washington
- Departments of Biology and Microbiology, University of Washington
- Lawrence Berkeley National Lab, Berkeley, California
| |
Collapse
|
39
|
Thompson AW, Turkarslan S, Arens CE, López García de Lomana A, Raman AV, Stahl DA, Baliga NS. Robustness of a model microbial community emerges from population structure among single cells of a clonal population. Environ Microbiol 2017; 19:3059-3069. [PMID: 28419704 DOI: 10.1111/1462-2920.13764] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2016] [Revised: 03/15/2017] [Accepted: 04/10/2017] [Indexed: 01/12/2023]
Abstract
Microbial populations can withstand, overcome and persist in the face of environmental fluctuation. Previously, we demonstrated how conditional gene regulation in a fluctuating environment drives dilution of condition-specific transcripts, causing a population of Desulfovibrio vulgaris Hildenborough (DvH) to collapse after repeatedly transitioning from sulfate respiration to syntrophic conditions with the methanogen Methanococcus maripaludis. Failure of the DvH to successfully transition contributed to the collapse of this model community. We investigated the mechanistic basis for loss of robustness by examining whether conditional gene regulation altered heterogeneity in gene expression across individual DvH cells. We discovered that robustness of a microbial population across environmental transitions was attributable to the retention of cells in two states that exhibited different condition-specific gene expression patterns. In our experiments, a population with disrupted conditional regulation successfully alternated between cell states. Meanwhile, a population with intact conditional regulation successfully switched between cell states initially, but collapsed after repeated transitions, possibly due to the high energy requirements of regulation. These results demonstrate that the survival of this entire model microbial community is dependent on the regulatory system's influence on the distribution of distinct cell states among individual cells within a clonal population.
Collapse
Affiliation(s)
| | | | | | | | | | - David A Stahl
- Civil and Environmental Engineering, University of Washington, Seattle, WA, USA
| | | |
Collapse
|
40
|
Wang Z, Danziger SA, Heavner BD, Ma S, Smith JJ, Li S, Herricks T, Simeonidis E, Baliga NS, Aitchison JD, Price ND. Combining inferred regulatory and reconstructed metabolic networks enhances phenotype prediction in yeast. PLoS Comput Biol 2017; 13:e1005489. [PMID: 28520713 PMCID: PMC5453602 DOI: 10.1371/journal.pcbi.1005489] [Citation(s) in RCA: 31] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2016] [Revised: 06/01/2017] [Accepted: 03/30/2017] [Indexed: 01/24/2023] Open
Abstract
Gene regulatory and metabolic network models have been used successfully in many organisms, but inherent differences between them make networks difficult to integrate. Probabilistic Regulation Of Metabolism (PROM) provides a partial solution, but it does not incorporate network inference and underperforms in eukaryotes. We present an Integrated Deduced And Metabolism (IDREAM) method that combines statistically inferred Environment and Gene Regulatory Influence Network (EGRIN) models with the PROM framework to create enhanced metabolic-regulatory network models. We used IDREAM to predict phenotypes and genetic interactions between transcription factors and genes encoding metabolic activities in the eukaryote, Saccharomyces cerevisiae. IDREAM models contain many fewer interactions than PROM and yet produce significantly more accurate growth predictions. IDREAM consistently outperformed PROM using any of three popular yeast metabolic models and across three experimental growth conditions. Importantly, IDREAM's enhanced accuracy makes it possible to identify subtle synthetic growth defects. With experimental validation, these novel genetic interactions involving the pyruvate dehydrogenase complex suggested a new role for fatty acid-responsive factor Oaf1 in regulating acetyl-CoA production in glucose grown cells.
Collapse
Affiliation(s)
- Zhuo Wang
- Key laboratory for the Genetics of Developmental and Neuropsychiatric Disorders (Ministry of Education), Bio-X Institutes, Shanghai Jiao Tong University, Shanghai, China
- School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai, China
- Institute for Systems Biology, Seattle, Washington, United States of America
| | - Samuel A. Danziger
- Institute for Systems Biology, Seattle, Washington, United States of America
- Center for Infectious Disease Research, Seattle, Washington, United States of America
| | - Benjamin D. Heavner
- Institute for Systems Biology, Seattle, Washington, United States of America
- Department of Biostatistics, University of Washington, Seattle, Washington, United States of America
| | - Shuyi Ma
- Institute for Systems Biology, Seattle, Washington, United States of America
- Center for Infectious Disease Research, Seattle, Washington, United States of America
- Department of Chemical and Biomolecular Engineering, University of Illinois, Urbana-Champaign, Illinois, United States of America
| | - Jennifer J. Smith
- Institute for Systems Biology, Seattle, Washington, United States of America
| | - Song Li
- Institute for Systems Biology, Seattle, Washington, United States of America
| | - Thurston Herricks
- Institute for Systems Biology, Seattle, Washington, United States of America
| | | | - Nitin S. Baliga
- Institute for Systems Biology, Seattle, Washington, United States of America
- Departments of Biology and Microbiology & Molecular and Cellular Biology Program, University of Washington, Seattle, Washington, United States of America
- Lawrence Berkeley National Lab, Berkeley, California, United States of America
| | - John D. Aitchison
- Institute for Systems Biology, Seattle, Washington, United States of America
- Center for Infectious Disease Research, Seattle, Washington, United States of America
| | - Nathan D. Price
- Institute for Systems Biology, Seattle, Washington, United States of America
| |
Collapse
|
41
|
Turkarslan S, Raman AV, Thompson AW, Arens CE, Gillespie MA, von Netzer F, Hillesland KL, Stolyar S, López García de Lomana A, Reiss DJ, Gorman-Lewis D, Zane GM, Ranish JA, Wall JD, Stahl DA, Baliga NS. Mechanism for microbial population collapse in a fluctuating resource environment. Mol Syst Biol 2017; 13:919. [PMID: 28320772 PMCID: PMC5371734 DOI: 10.15252/msb.20167058] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/23/2022] Open
Abstract
Managing trade-offs through gene regulation is believed to confer resilience to a microbial community in a fluctuating resource environment. To investigate this hypothesis, we imposed a fluctuating environment that required the sulfate-reducer Desulfovibrio vulgaris to undergo repeated ecologically relevant shifts between retaining metabolic independence (active capacity for sulfate respiration) and becoming metabolically specialized to a mutualistic association with the hydrogen-consuming Methanococcus maripaludis Strikingly, the microbial community became progressively less proficient at restoring the environmentally relevant physiological state after each perturbation and most cultures collapsed within 3-7 shifts. Counterintuitively, the collapse phenomenon was prevented by a single regulatory mutation. We have characterized the mechanism for collapse by conducting RNA-seq analysis, proteomics, microcalorimetry, and single-cell transcriptome analysis. We demonstrate that the collapse was caused by conditional gene regulation, which drove precipitous decline in intracellular abundance of essential transcripts and proteins, imposing greater energetic burden of regulation to restore function in a fluctuating environment.
Collapse
Affiliation(s)
| | | | | | | | | | | | | | | | | | | | - Drew Gorman-Lewis
- Earth and Space Sciences, University of Washington, Seattle, WA, USA
| | - Grant M Zane
- Department of Biochemistry, University of Missouri, Columbia, MO, USA
| | | | - Judy D Wall
- Department of Biochemistry, University of Missouri, Columbia, MO, USA
| | - David A Stahl
- Civil and Environmental Engineering, University of Washington, Seattle, WA, USA
| | | |
Collapse
|
42
|
Keller MP, Paul PK, Rabaglia ME, Stapleton DS, Schueler KL, Broman AT, Ye SI, Leng N, Brandon CJ, Neto EC, Plaisier CL, Simonett SP, Kebede MA, Sheynkman GM, Klein MA, Baliga NS, Smith LM, Broman KW, Yandell BS, Kendziorski C, Attie AD. The Transcription Factor Nfatc2 Regulates β-Cell Proliferation and Genes Associated with Type 2 Diabetes in Mouse and Human Islets. PLoS Genet 2016; 12:e1006466. [PMID: 27935966 PMCID: PMC5147809 DOI: 10.1371/journal.pgen.1006466] [Citation(s) in RCA: 35] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2016] [Accepted: 11/04/2016] [Indexed: 12/22/2022] Open
Abstract
Human genome-wide association studies (GWAS) have shown that genetic variation at >130 gene loci is associated with type 2 diabetes (T2D). We asked if the expression of the candidate T2D-associated genes within these loci is regulated by a common locus in pancreatic islets. Using an obese F2 mouse intercross segregating for T2D, we show that the expression of ~40% of the T2D-associated genes is linked to a broad region on mouse chromosome (Chr) 2. As all but 9 of these genes are not physically located on Chr 2, linkage to Chr 2 suggests a genomic factor(s) located on Chr 2 regulates their expression in trans. The transcription factor Nfatc2 is physically located on Chr 2 and its expression demonstrates cis linkage; i.e., its expression maps to itself. When conditioned on the expression of Nfatc2, linkage for the T2D-associated genes was greatly diminished, supporting Nfatc2 as a driver of their expression. Plasma insulin also showed linkage to the same broad region on Chr 2. Overexpression of a constitutively active (ca) form of Nfatc2 induced β-cell proliferation in mouse and human islets, and transcriptionally regulated more than half of the T2D-associated genes. Overexpression of either ca-Nfatc2 or ca-Nfatc1 in mouse islets enhanced insulin secretion, whereas only ca-Nfatc2 was able to promote β-cell proliferation, suggesting distinct molecular pathways mediating insulin secretion vs. β-cell proliferation are regulated by NFAT. Our results suggest that many of the T2D-associated genes are downstream transcriptional targets of NFAT, and may act coordinately in a pathway through which NFAT regulates β-cell proliferation in both mouse and human islets. Genome-wide association studies (GWAS) and linkage studies provide a powerful way to establish a causal connection between a gene locus and a physiological or pathophysiological phenotype. We wondered if candidate genes associated with type 2 diabetes in human populations, in addition to being causal for the disease, could also be intermediate traits in a pathway leading to disease. In addition, we wished to know if there were any regulatory loci that could coordinately drive the expression of these genes in pancreatic islets and thus complete a pathway; i.e. Driver → GWAS candidate expression → type 2 diabetes. Using data from a mouse intercross between a diabetes-susceptible and a diabetes-resistant mouse strain, we found that the expression of ~40% of >130 candidate GWAS genes genetically mapped to a hot spot on mouse chromosome 2. Using a variety of statistical methods, we identified the transcription factor Nfatc2 as the candidate driver. Follow-up experiments showed that overexpression of Nfatc2 does indeed affect the expression of the GWAS genes and regulates β-cell proliferation and insulin secretion. The work shows that in addition to being causal, GWAS candidate genes can be intermediate traits in a pathway leading to disease. Model organisms can be used to explore these novel causal pathways.
Collapse
Affiliation(s)
- Mark P. Keller
- Department of Biochemistry, University of Wisconsin, Madison, Wisconsin, United States of America
| | - Pradyut K. Paul
- Department of Biochemistry, University of Wisconsin, Madison, Wisconsin, United States of America
| | - Mary E. Rabaglia
- Department of Biochemistry, University of Wisconsin, Madison, Wisconsin, United States of America
| | - Donnie S. Stapleton
- Department of Biochemistry, University of Wisconsin, Madison, Wisconsin, United States of America
| | - Kathryn L. Schueler
- Department of Biochemistry, University of Wisconsin, Madison, Wisconsin, United States of America
| | - Aimee Teo Broman
- Department of Biostatistics & Medical Informatics, University of Wisconsin, Madison, Wisconsin, United States of America
| | - Shuyun Isabella Ye
- Department of Statistics, University of Wisconsin, Madison, Wisconsin, United States of America
| | - Ning Leng
- Department of Biostatistics & Medical Informatics, University of Wisconsin, Madison, Wisconsin, United States of America
| | - Christopher J. Brandon
- Department of Biochemistry, University of Wisconsin, Madison, Wisconsin, United States of America
| | | | | | - Shane P. Simonett
- Department of Biochemistry, University of Wisconsin, Madison, Wisconsin, United States of America
| | - Melkam A. Kebede
- Department of Biochemistry, University of Wisconsin, Madison, Wisconsin, United States of America
| | - Gloria M. Sheynkman
- Department of Chemistry, University of Wisconsin, Madison, Wisconsin, United States of America
| | - Mark A. Klein
- Department of Biochemistry, University of Wisconsin, Madison, Wisconsin, United States of America
| | | | - Lloyd M. Smith
- Department of Chemistry, University of Wisconsin, Madison, Wisconsin, United States of America
| | - Karl W. Broman
- Department of Biostatistics & Medical Informatics, University of Wisconsin, Madison, Wisconsin, United States of America
| | - Brian S. Yandell
- Department of Statistics, University of Wisconsin, Madison, Wisconsin, United States of America
| | - Christina Kendziorski
- Department of Biostatistics & Medical Informatics, University of Wisconsin, Madison, Wisconsin, United States of America
| | - Alan D. Attie
- Department of Biochemistry, University of Wisconsin, Madison, Wisconsin, United States of America
- * E-mail:
| |
Collapse
|
43
|
Patra B, Kon Y, Yadav G, Sevold AW, Frumkin JP, Vallabhajosyula RR, Hintze A, Østman B, Schossau J, Bhan A, Marzolf B, Tamashiro JK, Kaur A, Baliga NS, Grayhack EJ, Adami C, Galas DJ, Raval A, Phizicky EM, Ray A. A genome wide dosage suppressor network reveals genomic robustness. Nucleic Acids Res 2016; 45:255-270. [PMID: 27899637 PMCID: PMC5224485 DOI: 10.1093/nar/gkw1148] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2016] [Revised: 10/17/2016] [Accepted: 11/07/2016] [Indexed: 01/17/2023] Open
Abstract
Genomic robustness is the extent to which an organism has evolved to withstand the effects of deleterious mutations. We explored the extent of genomic robustness in budding yeast by genome wide dosage suppressor analysis of 53 conditional lethal mutations in cell division cycle and RNA synthesis related genes, revealing 660 suppressor interactions of which 642 are novel. This collection has several distinctive features, including high co-occurrence of mutant-suppressor pairs within protein modules, highly correlated functions between the pairs and higher diversity of functions among the co-suppressors than previously observed. Dosage suppression of essential genes encoding RNA polymerase subunits and chromosome cohesion complex suggests a surprising degree of functional plasticity of macromolecular complexes, and the existence of numerous degenerate pathways for circumventing the effects of potentially lethal mutations. These results imply that organisms and cancer are likely able to exploit the genomic robustness properties, due the persistence of cryptic gene and pathway functions, to generate variation and adapt to selective pressures.
Collapse
Affiliation(s)
- Biranchi Patra
- Keck Graduate Institute, 535 Watson Drive, Claremont, CA 91711, USA
| | - Yoshiko Kon
- Department of Biochemistry, University of Rochester School of Medicine, Rochester, NY 14627, USA
| | - Gitanjali Yadav
- Keck Graduate Institute, 535 Watson Drive, Claremont, CA 91711, USA.,National Institute of Plant Genome Research (NIPGR), Aruna Asaf Ali Marg, New Delhi 110067, India
| | - Anthony W Sevold
- Keck Graduate Institute, 535 Watson Drive, Claremont, CA 91711, USA
| | - Jesse P Frumkin
- Keck Graduate Institute, 535 Watson Drive, Claremont, CA 91711, USA
| | | | - Arend Hintze
- Keck Graduate Institute, 535 Watson Drive, Claremont, CA 91711, USA
| | - Bjørn Østman
- Keck Graduate Institute, 535 Watson Drive, Claremont, CA 91711, USA
| | - Jory Schossau
- Keck Graduate Institute, 535 Watson Drive, Claremont, CA 91711, USA
| | - Ashish Bhan
- Keck Graduate Institute, 535 Watson Drive, Claremont, CA 91711, USA
| | - Bruz Marzolf
- Institute for Systems Biology, 1441 N 34th St, Seattle, WA 98103, USA
| | | | - Amardeep Kaur
- Institute for Systems Biology, 1441 N 34th St, Seattle, WA 98103, USA
| | - Nitin S Baliga
- Institute for Systems Biology, 1441 N 34th St, Seattle, WA 98103, USA
| | - Elizabeth J Grayhack
- Department of Biochemistry, University of Rochester School of Medicine, Rochester, NY 14627, USA
| | - Christoph Adami
- Keck Graduate Institute, 535 Watson Drive, Claremont, CA 91711, USA
| | - David J Galas
- Institute for Systems Biology, 1441 N 34th St, Seattle, WA 98103, USA
| | - Alpan Raval
- Keck Graduate Institute, 535 Watson Drive, Claremont, CA 91711, USA.,Institute of Mathematical Sciences, Claremont Graduate University, Claremont, CA 91711, USA
| | - Eric M Phizicky
- Department of Biochemistry, University of Rochester School of Medicine, Rochester, NY 14627, USA
| | - Animesh Ray
- Keck Graduate Institute, 535 Watson Drive, Claremont, CA 91711, USA .,Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA 91125, USA
| |
Collapse
|
44
|
Plaisier CL, O'Brien S, Bernard B, Reynolds S, Simon Z, Toledo CM, Ding Y, Reiss DJ, Paddison PJ, Baliga NS. Causal Mechanistic Regulatory Network for Glioblastoma Deciphered Using Systems Genetics Network Analysis. Cell Syst 2016; 3:172-186. [PMID: 27426982 DOI: 10.1016/j.cels.2016.06.006] [Citation(s) in RCA: 66] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2016] [Revised: 04/20/2016] [Accepted: 06/09/2016] [Indexed: 12/30/2022]
Abstract
We developed the transcription factor (TF)-target gene database and the Systems Genetics Network Analysis (SYGNAL) pipeline to decipher transcriptional regulatory networks from multi-omic and clinical patient data, and we applied these tools to 422 patients with glioblastoma multiforme (GBM). The resulting gbmSYGNAL network predicted 112 somatically mutated genes or pathways that act through 74 TFs and 37 microRNAs (miRNAs) (67 not previously associated with GBM) to dysregulate 237 distinct co-regulated gene modules associated with patient survival or oncogenic processes. The regulatory predictions were associated to cancer phenotypes using CRISPR-Cas9 and small RNA perturbation studies and also demonstrated GBM specificity. Two pairwise combinations (ETV6-NFKB1 and romidepsin-miR-486-3p) predicted by the gbmSYGNAL network had synergistic anti-proliferative effects. Finally, the network revealed that mutations in NF1 and PIK3CA modulate IRF1-mediated regulation of MHC class I antigen processing and presentation genes to increase tumor lymphocyte infiltration and worsen prognosis. Importantly, SYGNAL is widely applicable for integrating genomic and transcriptomic measurements from other human cohorts.
Collapse
Affiliation(s)
| | - Sofie O'Brien
- Institute for Systems Biology, 401 Terry Avenue North, Seattle, WA 98109-5234, USA
| | - Brady Bernard
- Institute for Systems Biology, 401 Terry Avenue North, Seattle, WA 98109-5234, USA
| | - Sheila Reynolds
- Institute for Systems Biology, 401 Terry Avenue North, Seattle, WA 98109-5234, USA
| | - Zac Simon
- Institute for Systems Biology, 401 Terry Avenue North, Seattle, WA 98109-5234, USA
| | - Chad M Toledo
- Human Biology Division, Fred Hutchinson Cancer Research Center, Seattle, WA 98109, USA; Molecular and Cellular Biology Program, University of Washington, Seattle, WA 98195, USA
| | - Yu Ding
- Human Biology Division, Fred Hutchinson Cancer Research Center, Seattle, WA 98109, USA
| | - David J Reiss
- Institute for Systems Biology, 401 Terry Avenue North, Seattle, WA 98109-5234, USA
| | - Patrick J Paddison
- Human Biology Division, Fred Hutchinson Cancer Research Center, Seattle, WA 98109, USA; Molecular and Cellular Biology Program, University of Washington, Seattle, WA 98195, USA
| | - Nitin S Baliga
- Institute for Systems Biology, 401 Terry Avenue North, Seattle, WA 98109-5234, USA.
| |
Collapse
|
45
|
Ashworth J, Turkarslan S, Harris M, Orellana MV, Baliga NS. Pan-transcriptomic analysis identifies coordinated and orthologous functional modules in the diatoms Thalassiosira pseudonana and Phaeodactylum tricornutum. Mar Genomics 2016; 26:21-8. [DOI: 10.1016/j.margen.2015.10.011] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/17/2015] [Revised: 10/28/2015] [Accepted: 10/29/2015] [Indexed: 01/01/2023]
|
46
|
Gomes-Filho JV, Zaramela LS, Italiani VCDS, Baliga NS, Vêncio RZN, Koide T. Sense overlapping transcripts in IS1341-type transposase genes are functional non-coding RNAs in archaea. RNA Biol 2016; 12:490-500. [PMID: 25806405 PMCID: PMC4615843 DOI: 10.1080/15476286.2015.1019998] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/08/2023] Open
Abstract
The existence of sense overlapping transcripts that share regulatory and coding information in the same genomic sequence shows an additional level of prokaryotic gene expression complexity. Here we report the discovery of ncRNAs associated with IS1341-type transposase (tnpB) genes, at the 3'-end of such elements, with examples in archaea and bacteria. Focusing on the model haloarchaeon Halobacterium salinarum NRC-1, we show the existence of sense overlapping transcripts (sotRNAs) for all its IS1341-type transposases. Publicly available transcriptome compendium show condition-dependent differential regulation between sotRNAs and their cognate genes. These sotRNAs allowed us to find a UUCA tetraloop motif that is present in other archaea (ncRNA family HgcC) and in a H. salinarum intergenic ncRNA derived from a palindrome associated transposable elements (PATE). Overexpression of one sotRNA and the PATE-derived RNA harboring the tetraloop motif improved H. salinarum growth, indicating that these ncRNAs are functional.
Collapse
Affiliation(s)
- José Vicente Gomes-Filho
- a Department of Biochemistry and Immunology ; Ribeirão Preto Medical School ; University of São Paulo ; Ribeirão Preto , Brazil
| | | | | | | | | | | |
Collapse
|
47
|
Toledo CM, Ding Y, Hoellerbauer P, Davis RJ, Basom R, Girard EJ, Lee E, Corrin P, Hart T, Bolouri H, Davison J, Zhang Q, Hardcastle J, Aronow BJ, Plaisier CL, Baliga NS, Moffat J, Lin Q, Li XN, Nam DH, Lee J, Pollard SM, Zhu J, Delrow JJ, Clurman BE, Olson JM, Paddison PJ. Genome-wide CRISPR-Cas9 Screens Reveal Loss of Redundancy between PKMYT1 and WEE1 in Glioblastoma Stem-like Cells. Cell Rep 2015; 13:2425-2439. [PMID: 26673326 PMCID: PMC4691575 DOI: 10.1016/j.celrep.2015.11.021] [Citation(s) in RCA: 122] [Impact Index Per Article: 13.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2015] [Revised: 10/12/2015] [Accepted: 11/03/2015] [Indexed: 12/31/2022] Open
Abstract
To identify therapeutic targets for glioblastoma (GBM), we performed genome-wide CRISPR-Cas9 knockout (KO) screens in patient-derived GBM stem-like cells (GSCs) and human neural stem/progenitors (NSCs), non-neoplastic stem cell controls, for genes required for their in vitro growth. Surprisingly, the vast majority GSC-lethal hits were found outside of molecular networks commonly altered in GBM and GSCs (e.g., oncogenic drivers). In vitro and in vivo validation of GSC-specific targets revealed several strong hits, including the wee1-like kinase, PKMYT1/Myt1. Mechanistic studies demonstrated that PKMYT1 acts redundantly with WEE1 to inhibit cyclin B-CDK1 activity via CDK1-Y15 phosphorylation and to promote timely completion of mitosis in NSCs. However, in GSCs, this redundancy is lost, most likely as a result of oncogenic signaling, causing GBM-specific lethality.
Collapse
Affiliation(s)
- Chad M Toledo
- Human Biology Division, Fred Hutchinson Cancer Research Center, Seattle, WA 98109, USA; Molecular and Cellular Biology Program, University of Washington, Seattle, WA 98195, USA
| | - Yu Ding
- Human Biology Division, Fred Hutchinson Cancer Research Center, Seattle, WA 98109, USA
| | - Pia Hoellerbauer
- Human Biology Division, Fred Hutchinson Cancer Research Center, Seattle, WA 98109, USA; Molecular and Cellular Biology Program, University of Washington, Seattle, WA 98195, USA
| | - Ryan J Davis
- Human Biology Division, Fred Hutchinson Cancer Research Center, Seattle, WA 98109, USA; Molecular and Cellular Biology Program, University of Washington, Seattle, WA 98195, USA; Clinical Research Division, Fred Hutchinson Cancer Research Center, Seattle, WA 98109, USA
| | - Ryan Basom
- Genomics and Bioinformatics Shared Resources, Fred Hutchinson Cancer Research Center, Seattle, WA 98109, USA
| | - Emily J Girard
- Clinical Research Division, Fred Hutchinson Cancer Research Center, Seattle, WA 98109, USA
| | - Eunjee Lee
- Department of Genetics and Genomic Sciences, Icahn Institute of Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Philip Corrin
- Human Biology Division, Fred Hutchinson Cancer Research Center, Seattle, WA 98109, USA
| | - Traver Hart
- Department of Molecular Genetics, University of Toronto and Donnelly Centre, Toronto, ON M5S3E1, Canada; Canadian Institute for Advanced Research, Toronto, ON M5G1Z8, Canada
| | - Hamid Bolouri
- Human Biology Division, Fred Hutchinson Cancer Research Center, Seattle, WA 98109, USA
| | - Jerry Davison
- Genomics and Bioinformatics Shared Resources, Fred Hutchinson Cancer Research Center, Seattle, WA 98109, USA
| | - Qing Zhang
- Genomics and Bioinformatics Shared Resources, Fred Hutchinson Cancer Research Center, Seattle, WA 98109, USA
| | - Justin Hardcastle
- Human Biology Division, Fred Hutchinson Cancer Research Center, Seattle, WA 98109, USA
| | - Bruce J Aronow
- Division of Biomedical Informatics, Cincinnati Children's Hospital Medical Center, Cincinnati, OH 45229, USA
| | | | | | - Jason Moffat
- Department of Molecular Genetics, University of Toronto and Donnelly Centre, Toronto, ON M5S3E1, Canada; Canadian Institute for Advanced Research, Toronto, ON M5G1Z8, Canada
| | - Qi Lin
- Brain Tumor Program, Texas Children's Cancer Center, Department of Pediatrics, Baylor College of Medicine, Houston, TX 77030, USA
| | - Xiao-Nan Li
- Brain Tumor Program, Texas Children's Cancer Center, Department of Pediatrics, Baylor College of Medicine, Houston, TX 77030, USA
| | - Do-Hyun Nam
- Institute for Refractory Cancer Research, Samsung Medical Center, Seoul 135-710, Korea
| | - Jeongwu Lee
- Department of Stem Cell Biology and Regenerative Medicine, Lerner Research Institute, Cleveland Clinic, Cleveland, OH 44192, USA
| | - Steven M Pollard
- Edinburgh CRUK Cancer Research Centre and MRC Centre for Regenerative Medicine, The University of Edinburgh, Edinburgh EH16 4UU, UK
| | - Jun Zhu
- Department of Genetics and Genomic Sciences, Icahn Institute of Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Jeffery J Delrow
- Genomics and Bioinformatics Shared Resources, Fred Hutchinson Cancer Research Center, Seattle, WA 98109, USA
| | - Bruce E Clurman
- Human Biology Division, Fred Hutchinson Cancer Research Center, Seattle, WA 98109, USA; Clinical Research Division, Fred Hutchinson Cancer Research Center, Seattle, WA 98109, USA
| | - James M Olson
- Clinical Research Division, Fred Hutchinson Cancer Research Center, Seattle, WA 98109, USA.
| | - Patrick J Paddison
- Human Biology Division, Fred Hutchinson Cancer Research Center, Seattle, WA 98109, USA; Molecular and Cellular Biology Program, University of Washington, Seattle, WA 98195, USA.
| |
Collapse
|
48
|
Imam S, Schäuble S, Valenzuela J, de Lomana ALG, Carter W, Price ND, Baliga NS. A refined genome-scale reconstruction of Chlamydomonas metabolism provides a platform for systems-level analyses. Plant J 2015; 84:1239-56. [PMID: 26485611 PMCID: PMC4715634 DOI: 10.1111/tpj.13059] [Citation(s) in RCA: 41] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/10/2015] [Revised: 09/30/2015] [Accepted: 10/09/2015] [Indexed: 05/11/2023]
Abstract
Microalgae have reemerged as organisms of prime biotechnological interest due to their ability to synthesize a suite of valuable chemicals. To harness the capabilities of these organisms, we need a comprehensive systems-level understanding of their metabolism, which can be fundamentally achieved through large-scale mechanistic models of metabolism. In this study, we present a revised and significantly improved genome-scale metabolic model for the widely-studied microalga, Chlamydomonas reinhardtii. The model, iCre1355, represents a major advance over previous models, both in content and predictive power. iCre1355 encompasses a broad range of metabolic functions encoded across the nuclear, chloroplast and mitochondrial genomes accounting for 1355 genes (1460 transcripts), 2394 and 1133 metabolites. We found improved performance over the previous metabolic model based on comparisons of predictive accuracy across 306 phenotypes (from 81 mutants), lipid yield analysis and growth rates derived from chemostat-grown cells (under three conditions). Measurement of macronutrient uptake revealed carbon and phosphate to be good predictors of growth rate, while nitrogen consumption appeared to be in excess. We analyzed high-resolution time series transcriptomics data using iCre1355 to uncover dynamic pathway-level changes that occur in response to nitrogen starvation and changes in light intensity. This approach enabled accurate prediction of growth rates, the cessation of growth and accumulation of triacylglycerols during nitrogen starvation, and the temporal response of different growth-associated pathways to increased light intensity. Thus, iCre1355 represents an experimentally validated genome-scale reconstruction of C. reinhardtii metabolism that should serve as a useful resource for studying the metabolic processes of this and related microalgae.
Collapse
Affiliation(s)
- Saheed Imam
- Institute for Systems Biology, Seattle, WA, USA
| | - Sascha Schäuble
- Institute for Systems Biology, Seattle, WA, USA
- Jena University Language & Information Engineering (JULIE) Lab, Friedrich-Schiller-University Jena, Jena, Germany
- Research Group Theoretical Systems Biology, Friedrich-Schiller-University Jena, 07743 Jena, Germany
| | | | | | | | - Nathan D. Price
- Institute for Systems Biology, Seattle, WA, USA
- Departments of Bioengineering and Computer Science & Engineering, University of Washington, Seattle, WA, USA
- Molecular and Cellular Biology Program, University of Washington, Seattle, WA, USA
| | - Nitin S. Baliga
- Institute for Systems Biology, Seattle, WA, USA
- Departments of Biology and Microbiology, University of Washington, Seattle, WA, USA
- Molecular and Cellular Biology Program, University of Washington, Seattle, WA, USA
- Lawrence Berkeley National Lab, Berkeley, CA
- Correspondence: Nitin S. Baliga, Institute for Systems Biology, 401 Terry Ave N., Seattle, WA 98109, Telephone: 206.732.1266, Fax: 206.732.1299,
| |
Collapse
|
49
|
Reiss DJ, Plaisier CL, Wu WJ, Baliga NS. cMonkey2: Automated, systematic, integrated detection of co-regulated gene modules for any organism. Nucleic Acids Res 2015; 43:e87. [PMID: 25873626 PMCID: PMC4513845 DOI: 10.1093/nar/gkv300] [Citation(s) in RCA: 28] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/17/2014] [Revised: 03/05/2015] [Accepted: 03/26/2015] [Indexed: 12/25/2022] Open
Abstract
The cMonkey integrated biclustering algorithm identifies conditionally co-regulated modules of genes (biclusters). cMonkey integrates various orthogonal pieces of information which support evidence of gene co-regulation, and optimizes biclusters to be supported simultaneously by one or more of these prior constraints. The algorithm served as the cornerstone for constructing the first global, predictive Environmental Gene Regulatory Influence Network (EGRIN) model for a free-living cell, and has now been applied to many more organisms. However, due to its computational inefficiencies, long run-time and complexity of various input data types, cMonkey was not readily usable by the wider community. To address these primary concerns, we have significantly updated the cMonkey algorithm and refactored its implementation, improving its usability and extendibility. These improvements provide a fully functioning and user-friendly platform for building co-regulated gene modules and the tools necessary for their exploration and interpretation. We show, via three separate analyses of data for E. coli, M. tuberculosis and H. sapiens, that the updated algorithm and inclusion of novel scoring functions for new data types (e.g. ChIP-seq and transcription factor over-expression [TFOE]) improve discovery of biologically informative co-regulated modules. The complete cMonkey2 software package, including source code, is available at https://github.com/baliga-lab/cmonkey2.
Collapse
Affiliation(s)
- David J Reiss
- Institute for Systems Biology, 401 Terry Ave N, Seattle, WA 98109, USA
| | | | - Wei-Ju Wu
- Institute for Systems Biology, 401 Terry Ave N, Seattle, WA 98109, USA
| | - Nitin S Baliga
- Institute for Systems Biology, 401 Terry Ave N, Seattle, WA 98109, USA Department of Microbiology, University of Washington, Seattle, WA 98103, USA
| |
Collapse
|
50
|
Rustad TR, Minch KJ, Ma S, Winkler JK, Hobbs S, Hickey M, Brabant W, Turkarslan S, Price ND, Baliga NS, Sherman DR. Mapping and manipulating the Mycobacterium tuberculosis transcriptome using a transcription factor overexpression-derived regulatory network. Genome Biol 2015; 15:502. [PMID: 25380655 DOI: 10.1186/preaccept-1701638048134699] [Citation(s) in RCA: 66] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/10/2014] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Mycobacterium tuberculosis senses and responds to the shifting and hostile landscape of the host. To characterize the underlying intertwined gene regulatory network governed by approximately 200 transcription factors of M. tuberculosis, we have assayed the global transcriptional consequences of overexpressing each transcription factor from an inducible promoter. RESULTS We cloned and overexpressed 206 transcription factors in M. tuberculosis to identify the regulatory signature of each. We identified 9,335 regulatory consequences of overexpressing each of 183 transcription factors, providing evidence of regulation for 70% of the M. tuberculosis genome. These transcriptional signatures agree well with previously described M. tuberculosis regulons. The number of genes differentially regulated by transcription factor overexpression varied from hundreds of genes to none, with the majority of expression changes repressing basal transcription. Exploring the global transcriptional maps of transcription factor overexpressing (TFOE) strains, we predicted and validated the phenotype of a regulator that reduces susceptibility to a first line anti-tubercular drug, isoniazid. We also combined the TFOE data with an existing model of M. tuberculosis metabolism to predict the growth rates of individual TFOE strains with high fidelity. CONCLUSION This work has led to a systems-level framework describing the transcriptome of a devastating bacterial pathogen, characterized the transcriptional influence of nearly all individual transcription factors in M. tuberculosis, and demonstrated the utility of this resource. These results will stimulate additional systems-level and hypothesis-driven efforts to understand M. tuberculosis adaptations that promote disease.
Collapse
|