1
|
Ostacolo K, López García de Lomana A, Larat C, Hjaltalin V, Holm KY, Hlynsdóttir SS, Soucheray M, Sooman L, Rolfsson O, Krogan NJ, Steingrimsson E, Swaney DL, Ogmundsdottir MH. ATG7(2) Interacts With Metabolic Proteins and Regulates Central Energy Metabolism. Traffic 2024; 25:e12933. [PMID: 38600522 DOI: 10.1111/tra.12933] [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: 05/10/2023] [Revised: 03/01/2024] [Accepted: 03/10/2024] [Indexed: 04/12/2024]
Abstract
Macroautophagy/autophagy is an essential catabolic process that targets a wide variety of cellular components including proteins, organelles, and pathogens. ATG7, a protein involved in the autophagy process, plays a crucial role in maintaining cellular homeostasis and can contribute to the development of diseases such as cancer. ATG7 initiates autophagy by facilitating the lipidation of the ATG8 proteins in the growing autophagosome membrane. The noncanonical isoform ATG7(2) is unable to perform ATG8 lipidation; however, its cellular regulation and function are unknown. Here, we uncovered a distinct regulation and function of ATG7(2) in contrast with ATG7(1), the canonical isoform. First, affinity-purification mass spectrometry analysis revealed that ATG7(2) establishes direct protein-protein interactions (PPIs) with metabolic proteins, whereas ATG7(1) primarily interacts with autophagy machinery proteins. Furthermore, we identified that ATG7(2) mediates a decrease in metabolic activity, highlighting a novel splice-dependent function of this important autophagy protein. Then, we found a divergent expression pattern of ATG7(1) and ATG7(2) across human tissues. Conclusively, our work uncovers the divergent patterns of expression, protein interactions, and function of ATG7(2) in contrast to ATG7(1). These findings suggest a molecular switch between main catabolic processes through isoform-dependent expression of a key autophagy gene.
Collapse
Affiliation(s)
- Kevin Ostacolo
- Department of Anatomy, Biomedical Center, Faculty of Medicine, University of Iceland, Reykjavik, Iceland
| | - Adrián López García de Lomana
- Department of Biochemistry and Molecular Biology, Biomedical Center, Faculty of Medicine, University of Iceland, Reykjavik, Iceland
| | - Clémence Larat
- Department of Anatomy, Biomedical Center, Faculty of Medicine, University of Iceland, Reykjavik, Iceland
| | - Valgerdur Hjaltalin
- Department of Anatomy, Biomedical Center, Faculty of Medicine, University of Iceland, Reykjavik, Iceland
| | - Kristrun Yr Holm
- Department of Anatomy, Biomedical Center, Faculty of Medicine, University of Iceland, Reykjavik, Iceland
| | - Sigríður S Hlynsdóttir
- Department of Anatomy, Biomedical Center, Faculty of Medicine, University of Iceland, Reykjavik, Iceland
| | - Margaret Soucheray
- Gladstone Institutes, San Francisco, California, USA
- Department of Cellular and Molecular Pharmacology, University of California, San Francisco, California, USA
- Quantitative Biosciences Institute (QBI), University of California, San Francisco, California, USA
| | - Linda Sooman
- Department of Anatomy, Biomedical Center, Faculty of Medicine, University of Iceland, Reykjavik, Iceland
| | - Ottar Rolfsson
- Department of Biochemistry and Molecular Biology, Biomedical Center, Faculty of Medicine, University of Iceland, Reykjavik, Iceland
| | - Nevan J Krogan
- Gladstone Institutes, San Francisco, California, USA
- Department of Cellular and Molecular Pharmacology, University of California, San Francisco, California, USA
- Quantitative Biosciences Institute (QBI), University of California, San Francisco, California, USA
| | - Eirikur Steingrimsson
- Department of Biochemistry and Molecular Biology, Biomedical Center, Faculty of Medicine, University of Iceland, Reykjavik, Iceland
| | - Danielle L Swaney
- Gladstone Institutes, San Francisco, California, USA
- Department of Cellular and Molecular Pharmacology, University of California, San Francisco, California, USA
- Quantitative Biosciences Institute (QBI), University of California, San Francisco, California, USA
| | - Margret H Ogmundsdottir
- Department of Anatomy, Biomedical Center, Faculty of Medicine, University of Iceland, Reykjavik, Iceland
| |
Collapse
|
2
|
Kotronoulas A, de Lomana ALG, Einarsdóttir HK, Kjartansson H, Stone R, Rolfsson Ó. Fish Skin Grafts Affect Adenosine and Methionine Metabolism during Burn Wound Healing. Antioxidants (Basel) 2023; 12:2076. [PMID: 38136196 PMCID: PMC10741162 DOI: 10.3390/antiox12122076] [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] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2023] [Revised: 11/23/2023] [Accepted: 11/29/2023] [Indexed: 12/24/2023] Open
Abstract
Burn wound healing is a complex process orchestrated through successive biochemical events that span from weeks to months depending on the depth of the wound. Here, we report an untargeted metabolomics discovery approach to capture metabolic changes during the healing of deep partial-thickness (DPT) and full-thickness (FT) burn wounds in a porcine burn wound model. The metabolic changes during healing could be described with six and seven distinct metabolic trajectories for DPT and FT wounds, respectively. Arginine and histidine metabolism were the most affected metabolic pathways during healing, irrespective of burn depth. Metabolic proxies for oxidative stress were different in the wound types, reaching maximum levels at day 14 in DPT burns but at day 7 in FT burns. We examined how acellular fish skin graft (AFSG) influences the wound metabolome compared to other standard-or-care burn wound treatments. We identified changes in metabolites within the methionine salvage pathway, specifically in DPT burn wounds that is novel to the understanding of the wound healing process. Furthermore, we found that AFSGs boost glutamate and adenosine in wounds that is of relevance given the importance of purinergic signaling in regulating oxidative stress and wound healing. Collectively, these results serve to define biomarkers of burn wound healing. These results conclusively contribute to the understanding of the multifactorial mechanism of the action of AFSG that has traditionally been attributed to its structural properties and omega-3 fatty acid content.
Collapse
Affiliation(s)
- Aristotelis Kotronoulas
- Center for Systems Biology, Medical Department, University of Iceland, Sturlugata 8, 102 Reykjavik, Iceland
| | | | | | | | - Randolph Stone
- US Army Institute of Surgical Research, JBSA Fort Sam Houston, TX 78234, USA
| | - Óttar Rolfsson
- Center for Systems Biology, Medical Department, University of Iceland, Sturlugata 8, 102 Reykjavik, Iceland
| |
Collapse
|
3
|
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
|
4
|
Kotronoulas A, de Lomana ALG, Karvelsson ST, Heijink M, Stone Ii R, Giera M, Rolfsson O. Lipid mediator profiles of burn wound healing: Acellular cod fish skin grafts promote the formation of EPA and DHA derived lipid mediators following seven days of treatment. Prostaglandins Leukot Essent Fatty Acids 2021; 175:102358. [PMID: 34753002 DOI: 10.1016/j.plefa.2021.102358] [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] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/12/2021] [Revised: 09/16/2021] [Accepted: 10/20/2021] [Indexed: 12/09/2022]
Abstract
The use of acellular fish skin grafts (FSG) for the treatment of burn wounds is becoming more common due to its beneficial wound healing properties. In our previous study we demonstarted that FSG is a scaffold biomaterial that is rich in eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA) conjugated to phosphatidylcholines. Here we investigated whether EPA and DHA derived lipid mediators are influenced during the healing of burn wounds treated with FSG. Deep partial and full thickness burn wounds (DPT and FT, respectively) were created on Yorkshire pigs (n = 4). DPT were treated with either FSG or fetal bovine dermis while FT were treated either with FSG or cadaver skin initially and followed by a split thickness skin graft. Punch biopsies were collected on days 7, 14, 21, 28 and 60 and analyzed in respect of changes to approximately 45 derivatives of EPA, DHA, arachidonic acid (AA), and linoleic acid (LA) employing UPLC-MS/MS methodology. Nine EPA and DHA lipid mediators, principally mono-hydroxylated derivatives such as 18-HEPE and 17-HDHA, were significantly higher on day 7 in the DPT when treated with FSG. A similar but non-significant trend was observed for the FT. The results suggest that the use of FSG in burn wound treatment can alter the formation of EPA and DHA mono hydroxylated lipid mediators in comparison to other grafts of mammalian origin. The differences observed during the first seven days after treatment indicates that FSG affects the early stages of wound healing.
Collapse
Affiliation(s)
| | | | | | - Marieke Heijink
- Center for Proteomics and Metabolomics, Leiden University Medical Center (LUMC), the Netherlands
| | - Randolph Stone Ii
- US Army Institute of Surgical Research, JBSA Fort Sam Houston, TX, USA
| | - Martin Giera
- Center for Proteomics and Metabolomics, Leiden University Medical Center (LUMC), the Netherlands
| | - Ottar Rolfsson
- Center for Systems Biology, University of Iceland, Reykjavik, Iceland.
| |
Collapse
|
5
|
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
|
6
|
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
|
7
|
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
|
8
|
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
|
9
|
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
|
10
|
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
|
11
|
López García de Lomana A, Schäuble S, Valenzuela J, Imam S, Carter W, Bilgin DD, Yohn CB, Turkarslan S, Reiss DJ, Orellana MV, Price ND, Baliga NS. Transcriptional program for nitrogen starvation-induced lipid accumulation in Chlamydomonas reinhardtii. Biotechnol Biofuels 2015; 8:207. [PMID: 26633994 PMCID: PMC4667458 DOI: 10.1186/s13068-015-0391-z] [Citation(s) in RCA: 30] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/29/2015] [Accepted: 11/17/2015] [Indexed: 05/08/2023]
Abstract
BACKGROUND Algae accumulate lipids to endure different kinds of environmental stresses including macronutrient starvation. Although this response has been extensively studied, an in depth understanding of the transcriptional regulatory network (TRN) that controls the transition into lipid accumulation remains elusive. In this study, we used a systems biology approach to elucidate the transcriptional program that coordinates the nitrogen starvation-induced metabolic readjustments that drive lipid accumulation in Chlamydomonas reinhardtii. RESULTS We demonstrate that nitrogen starvation triggered differential regulation of 2147 transcripts, which were co-regulated in 215 distinct modules and temporally ordered as 31 transcriptional waves. An early-stage response was triggered within 12 min that initiated growth arrest through activation of key signaling pathways, while simultaneously preparing the intracellular environment for later stages by modulating transport processes and ubiquitin-mediated protein degradation. Subsequently, central metabolism and carbon fixation were remodeled to trigger the accumulation of triacylglycerols. Further analysis revealed that these waves of genome-wide transcriptional events were coordinated by a regulatory program orchestrated by at least 17 transcriptional regulators, many of which had not been previously implicated in this process. We demonstrate that the TRN coordinates transcriptional downregulation of 57 metabolic enzymes across a period of nearly 4 h to drive an increase in lipid content per unit biomass. Notably, this TRN appears to also drive lipid accumulation during sulfur starvation, while phosphorus starvation induces a different regulatory program. The TRN model described here is available as a community-wide web-resource at http://networks.systemsbiology.net/chlamy-portal. CONCLUSIONS In this work, we have uncovered a comprehensive mechanistic model of the TRN controlling the transition from N starvation to lipid accumulation. The program coordinates sequentially ordered transcriptional waves that simultaneously arrest growth and lead to lipid accumulation. This study has generated predictive tools that will aid in devising strategies for the rational manipulation of regulatory and metabolic networks for better biofuel and biomass production.
Collapse
Affiliation(s)
| | - Sascha Schäuble
- />Institute for Systems Biology, 401 Terry Ave N, Seattle, 98109 WA USA
- />Jena University Language and Information Engineering (JULIE) Lab, Friedrich-Schiller-University Jena, Jena, Germany
- />Research Group Theoretical Systems Biology, Friedrich-Schiller-University Jena, Jena, Germany
| | - Jacob Valenzuela
- />Institute for Systems Biology, 401 Terry Ave N, Seattle, 98109 WA USA
| | - Saheed Imam
- />Institute for Systems Biology, 401 Terry Ave N, Seattle, 98109 WA USA
| | - Warren Carter
- />Institute for Systems Biology, 401 Terry Ave N, Seattle, 98109 WA USA
| | | | | | - Serdar Turkarslan
- />Institute for Systems Biology, 401 Terry Ave N, Seattle, 98109 WA USA
| | - David J. Reiss
- />Institute for Systems Biology, 401 Terry Ave N, Seattle, 98109 WA USA
| | - Mónica V. Orellana
- />Institute for Systems Biology, 401 Terry Ave N, Seattle, 98109 WA USA
- />Polar Science Center, University of Washington, Seattle, WA USA
| | - Nathan D. Price
- />Institute for Systems Biology, 401 Terry Ave N, Seattle, 98109 WA USA
- />Departments of Bioengineering and Computer Science and 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, 401 Terry Ave N, Seattle, 98109 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
|
12
|
Sunnåker M, Zamora-Sillero E, López García de Lomana A, Rudroff F, Sauer U, Stelling J, Wagner A. Topological augmentation to infer hidden processes in biological systems. ACTA ACUST UNITED AC 2013; 30:221-7. [PMID: 24297519 PMCID: PMC3892687 DOI: 10.1093/bioinformatics/btt638] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.1] [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] [Indexed: 11/12/2022]
Abstract
Motivation: A common problem in understanding a biochemical system is to infer its correct structure or topology. This topology consists of all relevant state variables—usually molecules and their interactions. Here we present a method called topological augmentation to infer this structure in a statistically rigorous and systematic way from prior knowledge and experimental data. Results: Topological augmentation starts from a simple model that is unable to explain the experimental data and augments its topology by adding new terms that capture the experimental behavior. This process is guided by representing the uncertainty in the model topology through stochastic differential equations whose trajectories contain information about missing model parts. We first apply this semiautomatic procedure to a pharmacokinetic model. This example illustrates that a global sampling of the parameter space is critical for inferring a correct model structure. We also use our method to improve our understanding of glutamine transport in yeast. This analysis shows that transport dynamics is determined by glutamine permeases with two different kinds of kinetics. Topological augmentation can not only be applied to biochemical systems, but also to any system that can be described by ordinary differential equations. Availability and implementation: Matlab code and examples are available at: http://www.csb.ethz.ch/tools/index. Contact:mikael.sunnaker@bsse.ethz.ch; andreas.wagner@ieu.uzh.ch Supplementary information:Supplementary data are available at Bioinformatics online.
Collapse
Affiliation(s)
- Mikael Sunnåker
- Department of Biosystems Science and Engineering/Swiss Institute of Bioinformatics, ETH Zurich, 4058 Basel, Switzerland, Competence Center for Systems Physiology and Metabolic Diseases, ETH Zurich, 8093 Zurich, Switzerland, Institute of Evolutionary Biology and Environmental Studies/Swiss Institute of Bioinformatics, University of Zurich, 8057 Zurich, Switzerland, Institute for Molecular Systems Biology, 8093 Zurich, Switzerland and The Santa Fe Institute, Santa Fe, 87501 New Mexico, USA
| | | | | | | | | | | | | |
Collapse
|