| 1. |
- Chen, Ruibing, et al.
(författare)
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Engineering cofactor supply and recycling to drive phenolic acid biosynthesis in yeast
- 2022
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Ingår i: Nature Chemical Biology. - : Springer Science and Business Media LLC. - 1552-4450 .- 1552-4469. ; 18:5, s. 520-529
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Tidskriftsartikel (refereegranskat)abstract
- Advances in synthetic biology enable microbial hosts to synthesize valuable natural products in an efficient, cost-competitive and safe manner. However, current engineering endeavors focus mainly on enzyme engineering and pathway optimization, leaving the role of cofactors in microbial production of natural products and cofactor engineering largely ignored. Here we systematically engineered the supply and recycling of three cofactors (FADH2, S-adenosyl-l-methion and NADPH) in the yeast Saccharomyces cerevisiae, for high-level production of the phenolic acids caffeic acid and ferulic acid, the precursors of many pharmaceutical molecules. Tailored engineering strategies were developed for rewiring biosynthesis, compartmentalization and recycling of the cofactors, which enabled the highest production of caffeic acid (5.5 ± 0.2 g l−1) and ferulic acid (3.8 ± 0.3 g l−1) in microbial cell factories. These results demonstrate that cofactors play an essential role in driving natural product biosynthesis and the engineering strategies described here can be easily adopted for regulating the metabolism of other cofactors. [Figure not available: see fulltext.].
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| 2. |
- Wu, Jingnan, 1994, et al.
(författare)
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On the Conformation of Dimeric Acceptors and Their Polymer Solar Cells with Efficiency over 18 %
- 2023
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Ingår i: Angewandte Chemie International Edition. - : John Wiley & Sons. - 1433-7851 .- 1521-3773. ; 62:45
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Tidskriftsartikel (refereegranskat)abstract
- The determination of molecular conformations of oligomeric acceptors (OAs) and their impact on molecular packing are crucial for understanding the photovoltaic performance of their resulting polymer solar cells (PSCs) but have not been well studied yet. Herein, we synthesized two dimeric acceptor materials, DIBP3F-Se and DIBP3F-S, which bridged two segments of Y6-derivatives by selenophene and thiophene, respectively. Theoretical simulation and experimental 1D and 2D NMR spectroscopic studies prove that both dimers exhibit O-shaped conformations other than S- or U-shaped counter-ones. Notably, this O-shaped conformation is likely governed by a distinctive "conformational lock" mechanism, arising from the intensified intramolecular & pi;-& pi; interactions among their two terminal groups within the dimers. PSCs based on DIBP3F-Se deliver a maximum efficiency of 18.09 %, outperforming DIBP3F-S-based cells (16.11 %) and ranking among the highest efficiencies for OA-based PSCs. This work demonstrates a facile method to obtain OA conformations and highlights the potential of dimeric acceptors for high-performance PSCs.
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| 3. |
- Chen, Yu, 1990, et al.
(författare)
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Yeast optimizes metal utilization based on metabolic network and enzyme kinetics
- 2021
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Ingår i: Proceedings of the National Academy of Sciences of the United States of America. - : Proceedings of the National Academy of Sciences. - 0027-8424 .- 1091-6490. ; 118:12
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Tidskriftsartikel (refereegranskat)abstract
- Metal ions are vital to metabolism, as they can act as cofactors on enzymes and thus modulate individual enzymatic reactions. Although many enzymes have been reported to interact with metal ions, the quantitative relationships between metal ions and metabolism are lacking. Here, we reconstructed a genome-scale metabolic model of the yeast Saccharomyces cerevisiae to account for proteome constraints and enzyme cofactors such as metal ions, named CofactorYeast. The model is able to estimate abundances of metal ions binding on enzymes in cells under various conditions, which are comparable to measured metal ion contents in biomass. In addition, the model predicts distinct metabolic flux distributions in response to reduced levels of various metal ions in the medium. Specifically, the model reproduces changes upon iron deficiency in metabolic and gene expression levels, which could be interpreted by optimization principles (i.e., yeast optimizes iron utilization based on metabolic network and enzyme kinetics rather than preferentially targeting iron to specific enzymes or pathways). At last, we show the potential of using the model for understanding cell factories that harbor heterologous iron-containing enzymes to synthesize high-value compounds such as p-coumaric acid. Overall, the model demonstrates the dependence of enzymes on metal ions and links metal ions to metabolism on a genome scale.
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| 4. |
- Liu, Quanli, 1988, et al.
(författare)
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Rewiring carbon metabolism in yeast for high level production of aromatic chemicals
- 2019
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Ingår i: Nature Communications. - : Springer Science and Business Media LLC. - 2041-1723 .- 2041-1723. ; 10:1
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Tidskriftsartikel (refereegranskat)abstract
- The production of bioactive plant compounds using microbial hosts is considered a safe, cost-competitive and scalable approach to their production. However, microbial production of some compounds like aromatic amino acid (AAA)-derived chemicals, remains an outstanding metabolic engineering challenge. Here we present the construction of a Saccharomyces cerevisiae platform strain able to produce high levels of p-coumaric acid, an AAA-derived precursor for many commercially valuable chemicals. This is achieved through engineering the AAA biosynthesis pathway, introducing a phosphoketalose-based pathway to divert glycolytic flux towards erythrose 4-phosphate formation, and optimizing carbon distribution between glycolysis and the AAA biosynthesis pathway by replacing the promoters of several important genes at key nodes between these two pathways. This results in a maximum p-coumaric acid titer of 12.5 g L−1 and a maximum yield on glucose of 154.9 mg g−1.
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| 5. |
- Qin, Ning, 1990, et al.
(författare)
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Flux regulation through glycolysis and respiration is balanced by inositol pyrophosphates in yeast
- 2023
-
Ingår i: Cell. - : Elsevier BV. - 0092-8674 .- 1097-4172. ; 186:4, s. 748-763.e15
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Tidskriftsartikel (refereegranskat)abstract
- Although many prokaryotes have glycolysis alternatives, it's considered as the only energy-generating glucose catabolic pathway in eukaryotes. Here, we managed to create a hybrid-glycolysis yeast. Subsequently, we identified an inositol pyrophosphatase encoded by OCA5 that could regulate glycolysis and respiration by adjusting 5-diphosphoinositol 1,2,3,4,6-pentakisphosphate (5-InsP7) levels. 5-InsP7 levels could regulate the expression of genes involved in glycolysis and respiration, representing a global mechanism that could sense ATP levels and regulate central carbon metabolism. The hybrid-glycolysis yeast did not produce ethanol during growth under excess glucose and could produce 2.68 g/L free fatty acids, which is the highest reported production in shake flask of Saccharomyces cerevisiae. This study demonstrated the significance of hybrid-glycolysis yeast and determined Oca5 as an inositol pyrophosphatase controlling the balance between glycolysis and respiration, which may shed light on the role of inositol pyrophosphates in regulating eukaryotic metabolism.
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| 6. |
- Bu, Junling, et al.
(författare)
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Catalytic promiscuity of O-methyltransferases from Corydalis yanhusuo leading to the structural diversity of benzylisoquinoline alkaloids
- 2022
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Ingår i: Horticulture Research. - : Oxford University Press (OUP). - 2662-6810 .- 2052-7276. ; 9
-
Tidskriftsartikel (refereegranskat)abstract
- O-methyltransferases play essential roles in producing structural diversity and improving the biological properties of benzylisoquinoline alkaloids (BIAs) in plants. In this study, Corydalis yanhusuo, a plant used in traditional Chinese medicine due to the analgesic effects of its BIA-active compounds, was employed to analyze the catalytic characteristics of O-methyltransferases in the formation of BIA diversity. Seven genes encoding O-methyltransferases were cloned, and functionally characterized using seven potential BIA substrates. Specifically, an O-methyltransferase (CyOMT2) with highly efficient catalytic activity of both 4′- and 6-O-methylations of 1-BIAs was found. CyOMT6 was found to perform two sequential methylations at both 9- and 2-positions of the essential intermediate of tetrahydroprotoberberines, (S)-scoulerine. Two O-methyltransferases (CyOMT5 and CyOMT7) with wide substrate promiscuity were found, with the 2-position of tetrahydroprotoberberines as the preferential catalytic site for CyOMT5 (named scoulerine 2-O-methyltransferase) and the 6-position of 1-BIAs as the preferential site for CyOMT7. In addition, results of integrated phylogenetic molecular docking analysis and site-directed mutation suggested that residues at sites 172, 306, 313, and 314 in CyOMT5 are important for enzyme promiscuity related to O-methylations at the 6- and 7-positions of isoquinoline. Cys at site 253 in CyOMT2 was proved to promote the methylation activity of the 6-position and to expand substrate scopes. This work provides insight into O-methyltransferases in producing BIA diversity in C. yanhusuo and genetic elements for producing BIAs by metabolic engineering and synthetic biology.
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| 7. |
- Cao, Xuan, et al.
(författare)
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Engineering yeast for high-level production of diterpenoid sclareol
- 2023
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Ingår i: Metabolic Engineering. - : Elsevier BV. - 1096-7176 .- 1096-7184. ; 75, s. 19-28
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Tidskriftsartikel (refereegranskat)abstract
- The diterpenoid sclareol is an industrially important precursor for alternative sustainable supply of ambergris. However, its current production from plant extraction is neither economical nor environmental-friendly, since it requires laborious and cost-intensive purification procedures and plants cultivation is susceptible to environmental factors. Engineering cell factories for bio-manufacturing can enable sustainable production of natural products. However, stringent metabolic regulation poses challenges to rewire cellular metabolism for overproduction of compounds of interest. Here we used a modular approach to globally rewire the cellular metabolism for improving sclareol production to 11.4 g/L in budding yeast Saccharomyces cerevisiae, the highest reported diterpenoid titer in microbes. Metabolic flux analysis showed that modular balanced metabolism drove the metabolic flux toward the biosynthesis of targeted molecules, and transcriptomic analysis revealed that the expression of central metabolism genes was shaped for a new balanced metabolism, which laid a foundation in extensive metabolic engineering of other microbial species for sustainable bio-production.
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| 8. |
- Cronin, M. F., et al.
(författare)
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Developing an Observing Air-Sea Interactions Strategy (OASIS) for the global ocean
- 2022
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Ingår i: Ices Journal of Marine Science. - : Oxford University Press (OUP). - 1054-3139 .- 1095-9289. ; 80:2, s. 367-73
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Tidskriftsartikel (refereegranskat)abstract
- The Observing Air-Sea Interactions Strategy (OASIS) is a new United Nations Decade of Ocean Science for Sustainable Development programme working to develop a practical, integrated approach for observing air-sea interactions globally for improved Earth system (including ecosystem) forecasts, CO2 uptake assessments called for by the Paris Agreement, and invaluable surface ocean information for decision makers. Our "Theory of Change" relies upon leveraged multi-disciplinary activities, partnerships, and capacity strengthening. Recommendations from >40 OceanObs'19 community papers and a series of workshops have been consolidated into three interlinked Grand Ideas for creating #1: a globally distributed network of mobile air-sea observing platforms built around an expanded array of long-term time-series stations; #2: a satellite network, with high spatial and temporal resolution, optimized for measuring air-sea fluxes; and #3: improved representation of air-sea coupling in a hierarchy of Earth system models. OASIS activities are organized across five Theme Teams: (1) Observing Network Design & Model Improvement; (2) Partnership & Capacity Strengthening; (3) UN Decade OASIS Actions; (4) Best Practices & Interoperability Experiments; and (5) Findable-Accessible-Interoperable-Reusable (FAIR) models, data, and OASIS products. Stakeholders, including researchers, are actively recruited to participate in Theme Teams to help promote a predicted, safe, clean, healthy, resilient, and productive ocean.
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| 9. |
- Davies, Stuart J., et al.
(författare)
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ForestGEO: Understanding forest diversity and dynamics through a global observatory network
- 2021
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Ingår i: Biological Conservation. - : Elsevier BV. - 0006-3207. ; 253
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Tidskriftsartikel (refereegranskat)abstract
- ForestGEO is a network of scientists and long-term forest dynamics plots (FDPs) spanning the Earth's major forest types. ForestGEO's mission is to advance understanding of the diversity and dynamics of forests and to strengthen global capacity for forest science research. ForestGEO is unique among forest plot networks in its large-scale plot dimensions, censusing of all stems ≥1 cm in diameter, inclusion of tropical, temperate and boreal forests, and investigation of additional biotic (e.g., arthropods) and abiotic (e.g., soils) drivers, which together provide a holistic view of forest functioning. The 71 FDPs in 27 countries include approximately 7.33 million living trees and about 12,000 species, representing 20% of the world's known tree diversity. With >1300 published papers, ForestGEO researchers have made significant contributions in two fundamental areas: species coexistence and diversity, and ecosystem functioning. Specifically, defining the major biotic and abiotic controls on the distribution and coexistence of species and functional types and on variation in species' demography has led to improved understanding of how the multiple dimensions of forest diversity are structured across space and time and how this diversity relates to the processes controlling the role of forests in the Earth system. Nevertheless, knowledge gaps remain that impede our ability to predict how forest diversity and function will respond to climate change and other stressors. Meeting these global research challenges requires major advances in standardizing taxonomy of tropical species, resolving the main drivers of forest dynamics, and integrating plot-based ground and remote sensing observations to scale up estimates of forest diversity and function, coupled with improved predictive models. However, they cannot be met without greater financial commitment to sustain the long-term research of ForestGEO and other forest plot networks, greatly expanded scientific capacity across the world's forested nations, and increased collaboration and integration among research networks and disciplines addressing forest science.
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| 10. |
- Lu, Hongzhong, 1987, et al.
(författare)
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Yeast metabolic innovations emerged via expanded metabolic network and gene positive selection
- 2021
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Ingår i: Molecular Systems Biology. - : EMBO. - 1744-4292. ; 17:10
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Tidskriftsartikel (refereegranskat)abstract
- Yeasts are known to have versatile metabolic traits, while how these metabolic traits have evolved has not been elucidated systematically. We performed integrative evolution analysis to investigate how genomic evolution determines trait generation by reconstructing genome-scale metabolic models (GEMs) for 332 yeasts. These GEMs could comprehensively characterize trait diversity and predict enzyme functionality, thereby signifying that sequence-level evolution has shaped reaction networks towards new metabolic functions. Strikingly, using GEMs, we can mechanistically map different evolutionary events, e.g. horizontal gene transfer and gene duplication, onto relevant subpathways to explain metabolic plasticity. This demonstrates that gene family expansion and enzyme promiscuity are prominent mechanisms for metabolic trait gains, while GEM simulations reveal that additional factors, such as gene loss from distant pathways, contribute to trait losses. Furthermore, our analysis could pinpoint to specific genes and pathways that have been under positive selection and relevant for the formulation of complex metabolic traits, i.e. thermotolerance and the Crabtree effect. Our findings illustrate how multidimensional evolution in both metabolic network structure and individual enzymes drives phenotypic variations.
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| 11. |
- Qin, Ning, et al.
(författare)
-
Increased CO 2 fixation enables high carbon-yield production of 3-hydroxypropionic acid in yeast
- 2024
-
Ingår i: Nature Communications. - 2041-1723 .- 2041-1723. ; 15:1
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Tidskriftsartikel (refereegranskat)abstract
- CO2 fixation plays a key role to make biobased production cost competitive. Here, we use 3-hydroxypropionic acid (3-HP) to showcase how CO2 fixation enables approaching theoretical-yield production. Using genome-scale metabolic models to calculate the production envelope, we demonstrate that the provision of bicarbonate, formed from CO2, restricts previous attempts for high yield production of 3-HP. We thus develop multiple strategies for bicarbonate uptake, including the identification of Sul1 as a potential bicarbonate transporter, domain swapping of malonyl-CoA reductase, identification of Esbp6 as a potential 3-HP exporter, and deletion of Uga1 to prevent 3-HP degradation. The combined rational engineering increases 3-HP production from 0.14 g/L to 11.25 g/L in shake flask using 20 g/L glucose, approaching the maximum theoretical yield with concurrent biomass formation. The engineered yeast forms the basis for commercialization of bio-acrylic acid, while our CO2 fixation strategies pave the way for CO2 being used as the sole carbon source.
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| 12. |
- Reithmaier, Gloria M.S., et al.
(författare)
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Carbonate chemistry and carbon sequestration driven by inorganic carbon outwelling from mangroves and saltmarshes
- 2023
-
Ingår i: Nature Communications. - 2041-1723. ; 14:1
-
Tidskriftsartikel (refereegranskat)abstract
- Mangroves and saltmarshes are biogeochemical hotspots storing carbon in sediments and in the ocean following lateral carbon export (outwelling). Coastal seawater pH is modified by both uptake of anthropogenic carbon dioxide and natural biogeochemical processes, e.g., wetland inputs. Here, we investigate how mangroves and saltmarshes influence coastal carbonate chemistry and quantify the contribution of alkalinity and dissolved inorganic carbon (DIC) outwelling to blue carbon budgets. Observations from 45 mangroves and 16 saltmarshes worldwide revealed that >70% of intertidal wetlands export more DIC than alkalinity, potentially decreasing thepH of coastal waters. Porewater-derived DIC outwelling (81 ± 47 mmol m−2 d−1 in mangroves and 57 ± 104 mmol m−2 d−1 in saltmarshes) was the major term in blue carbon budgets. However, substantial amounts of fixed carbon remain unaccounted for. Concurrently, alkalinity outwelling was similar or higher than sediment carbon burial and is therefore a significant but often overlooked carbon sequestration mechanism.
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| 13. |
- Buchanan, E. M., et al.
(författare)
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The Psychological Science Accelerator's COVID-19 rapid-response dataset
- 2023
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Ingår i: Scientific Data. - : Springer Science and Business Media LLC. - 2052-4463. ; 10:1
-
Tidskriftsartikel (refereegranskat)abstract
- In response to the COVID-19 pandemic, the Psychological Science Accelerator coordinated three large-scale psychological studies to examine the effects of loss-gain framing, cognitive reappraisals, and autonomy framing manipulations on behavioral intentions and affective measures. The data collected (April to October 2020) included specific measures for each experimental study, a general questionnaire examining health prevention behaviors and COVID-19 experience, geographical and cultural context characterization, and demographic information for each participant. Each participant started the study with the same general questions and then was randomized to complete either one longer experiment or two shorter experiments. Data were provided by 73,223 participants with varying completion rates. Participants completed the survey from 111 geopolitical regions in 44 unique languages/dialects. The anonymized dataset described here is provided in both raw and processed formats to facilitate re-use and further analyses. The dataset offers secondary analytic opportunities to explore coping, framing, and self-determination across a diverse, global sample obtained at the onset of the COVID-19 pandemic, which can be merged with other time-sampled or geographic data.
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| 14. |
- Chen, Ping, et al.
(författare)
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A 12.4-day periodicity in a close binary system after a supernova
- 2024
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Ingår i: Nature. - 0028-0836 .- 1476-4687. ; 625:7994, s. 253-258
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Tidskriftsartikel (refereegranskat)abstract
- Neutron stars and stellar-mass black holes are the remnants of massive star explosions1. Most massive stars reside in close binary systems2, and the interplay between the companion star and the newly formed compact object has been theoretically explored3, but signatures for binarity or evidence for the formation of a compact object during a supernova explosion are still lacking. Here we report a stripped-envelope supernova, SN 2022jli, which shows 12.4-day periodic undulations during the declining light curve. Narrow Hα emission is detected in late-time spectra with concordant periodic velocity shifts, probably arising from hydrogen gas stripped from a companion and accreted onto the compact remnant. A new Fermi-LAT γ-ray source is temporally and positionally consistent with SN 2022jli. The observed properties of SN 2022jli, including periodic undulations in the optical light curve, coherent Hα emission shifting and evidence for association with a γ-ray source, point to the explosion of a massive star in a binary system leaving behind a bound compact remnant. Mass accretion from the companion star onto the compact object powers the light curve of the supernova and generates the γ-ray emission.
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| 15. |
- Chen, Yu, 1990, et al.
(författare)
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Energy metabolism controls phenotypes by protein efficiency and allocation
- 2019
-
Ingår i: Proceedings of the National Academy of Sciences of the United States of America. - : Proceedings of the National Academy of Sciences. - 0027-8424 .- 1091-6490. ; 116:35, s. 17592-17597
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Tidskriftsartikel (refereegranskat)abstract
- Cells require energy for growth and maintenance and have evolved to have multiple pathways to produce energy in response to varying conditions. A basic question in this context is how cells organize energy metabolism, which is, however, challenging to elucidate due to its complexity, i.e., the energy-producing pathways overlap with each other and even intertwine with biomass formation pathways. Here, we propose a modeling concept that decomposes energy metabolism into biomass formation and ATP-producing pathways. The latter can be further decomposed into a high-yield and a low-yield pathway. This enables independent estimation of protein efficiency for each pathway. With this concept, we modeled energy metabolism for Escherichia coli and Saccharomyces cerevisiae and found that the high-yield pathway shows lower protein efficiency than the low-yield pathway. Taken together with a fixed protein constraint, we predict overflow metabolism in E. coli and the Crabtree effect in S. cerevisiae, meaning that energy metabolism is sufficient to explain the metabolic switches. The static protein constraint is supported by the findings that protein mass of energy metabolism is conserved across conditions based on absolute proteomics data. This also suggests that enzymes may have decreased saturation or activity at low glucose uptake rates. Finally, our analyses point out three ways to improve growth, i.e., increasing protein allocation to energy metabolism, decreasing ATP demand, or increasing activity for key enzymes.
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| 16. |
- Chen, Yu, 1990, et al.
(författare)
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Flux control through protein phosphorylation in yeast
- 2016
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Ingår i: FEMS Yeast Research. - : Oxford University Press (OUP). - 1567-1356 .- 1567-1364. ; 16:8
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Tidskriftsartikel (refereegranskat)abstract
- Protein phosphorylation is one of the most important mechanisms regulating metabolism as it can directly modify metabolic enzymes by the addition of phosphate groups. Attributed to such a rapid and reversible mechanism, cells can adjust metabolism rapidly in response to temporal changes. The yeast Saccharomyces cerevisiae, a widely used cell factory and model organism, is reported to show frequent phosphorylation events in metabolism. Studying protein phosphorylation in S. cerevisiae allows for gaining new insight into the function of regulatory networks, which may enable improved metabolic engineering as well as identify mechanisms underlying human metabolic diseases. Here we collect functional phosphorylation events of 41 enzymes involved in yeast metabolism and demonstrate functional mechanisms and the application of this information in metabolic engineering. From a systems biology perspective, we describe the development of phosphoproteomics in yeast as well as approaches to analysing the phosphoproteomics data. Finally, we focus on integrated analyses with other omics data sets and genome-scale metabolic models. Despite the advances, future studies improving both experimental technologies and computational approaches are imperative to expand the current knowledge of protein phosphorylation in S. cerevisiae.
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| 17. |
- Chen, Yu, 1990, et al.
(författare)
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Genome-Scale Metabolic Modeling from Yeast to Human Cell Models of Complex Diseases: Latest Advances and Challenges
- 2019
-
Ingår i: Methods in Molecular Biology. - New York, NY : Springer New York. - 1940-6029 .- 1064-3745. ; 2049, s. 329-345
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Bokkapitel (övrigt vetenskapligt/konstnärligt)abstract
- Genome-scale metabolic models (GEMs) are mathematical models that enable systematic analysis of metabolism. This modeling concept has been applied to study the metabolism of many organisms including the eukaryal model organism, the yeast Saccharomyces cerevisiae, that also serves as an important cell factory for production of fuels and chemicals. With the application of yeast GEMs, our knowledge of metabolism is increasing. Therefore, GEMs have also been used for modeling human cells to study metabolic diseases. Here we introduce the concept of GEMs and provide a protocol for reconstructing GEMs. Besides, we show the historic development of yeast GEMs and their applications. Also, we review human GEMs as well as their uses in the studies of complex diseases.
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| 18. |
- Chen, Yu, 1990, et al.
(författare)
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Genome-scale modeling for Bacillus coagulans to understand the metabolic characteristics
- 2020
-
Ingår i: Biotechnology and Bioengineering. - : Wiley. - 0006-3592 .- 1097-0290. ; 117:11, s. 3545-3558
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Tidskriftsartikel (refereegranskat)abstract
- Lactic acid is widely used in many industries, especially in the production of poly-lactic acid. Bacillus coagulans is a promising lactic acid producer in industrial fermentation due to its thermophilic property. In this study, we developed the first genome-scale metabolic model (GEM) of B. coagulans iBag597, together with an enzyme-constrained model ec-iBag597. We measured strain-specific biomass composition and integrated the data into a biomass equation. Then, we validated iBag597 against experimental data generated in this study, including amino acid requirements and carbon source utilization, showing that simulations were generally consistent with the experimental results. Subsequently, we carried out chemostats to investigate the effects of specific growth rate and culture pH on metabolism of B. coagulans. Meanwhile, we used iBag597 to estimate the intracellular metabolic fluxes for those conditions. The results showed that B. coagulans was capable of generating ATP via multiple pathways, and switched among them in response to various conditions. With ec-iBag597, we estimated the protein cost and protein efficiency for each ATP-producing pathway to investigate the switches. Our models pave the way for systems biology of B. coagulans, and our findings suggest that maintaining a proper growth rate and selecting an optimal pH are beneficial for lactate fermentation.
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| 19. |
- Chen, Yu, 1990, et al.
(författare)
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Genome-scale modeling of yeast metabolism: retrospectives and perspectives
- 2022
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Ingår i: FEMS Yeast Research. - : Oxford University Press (OUP). - 1567-1356 .- 1567-1364. ; 22:1
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Forskningsöversikt (refereegranskat)abstract
- Yeasts have been widely used for production of bread, beer and wine, as well as for production of bioethanol, but they have also been designed as cell factories to produce various chemicals, advanced biofuels and recombinant proteins. To systematically understand and rationally engineer yeast metabolism, genome-scale metabolic models (GEMs) have been reconstructed for the model yeast Saccharomyces cerevisiae and nonconventional yeasts. Here, we review the historical development of yeast GEMs together with their recent applications, including metabolic flux prediction, cell factory design, culture condition optimization and multi-yeast comparative analysis. Furthermore, we present an emerging effort, namely the integration of proteome constraints into yeast GEMs, resulting in models with improved performance. At last, we discuss challenges and perspectives on the development of yeast GEMs and the integration of proteome constraints.
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| 20. |
- Chen, Yu, 1990, et al.
(författare)
-
In vitro turnover numbers do not reflect in vivo activities of yeast enzymes
- 2021
-
Ingår i: Proceedings of the National Academy of Sciences of the United States of America. - : Proceedings of the National Academy of Sciences. - 0027-8424 .- 1091-6490. ; 118:32
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Tidskriftsartikel (refereegranskat)abstract
- Turnover numbers (kcat values) quantitatively represent the activity of enzymes, which are mostly measured in vitro. While a few studies have reported in vivo catalytic rates (kapp values) in bacteria, a large-scale estimation of kapp in eukaryotes is lacking. Here, we estimated kapp of the yeast Saccharomyces cerevisiae under diverse conditions. By comparing the maximum kapp across conditions with in vitro kcat we found a weak correlation in log scale of R2 = 0.28, which is lower than for Escherichia coli (R2 = 0.62). The weak correlation is caused by the fact that many in vitro kcat values were measured for enzymes obtained through heterologous expression. Removal of these enzymes improved the correlation to R2 = 0.41 but still not as good as for E. coli, suggesting considerable deviations between in vitro and in vivo enzyme activities in yeast. By parameterizing an enzyme-constrained metabolic model with our kapp dataset we observed better performance than the default model with in vitro kcat in predicting proteomics data, demonstrating the strength of using the dataset generated here.
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| 21. |
- Chen, Yu, 1990, et al.
(författare)
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Mathematical modeling of proteome constraints within metabolism
- 2021
-
Ingår i: Current Opinion in Systems Biology. - : Elsevier BV. - 2452-3100. ; 25, s. 50-56
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Forskningsöversikt (refereegranskat)abstract
- Genome-scale metabolic models (GEMs) are widely used to predict phenotypes with the aid of constraint-based modeling. In order to improve the predictive power of these models, there have been many efforts on imposing biological constraints, among which proteome constraints are of particular interest. Here we describe the concept of proteome constraints and review proteome-constrained GEMs, as well as their advantages and applications. In addition, we discuss a key issue in the field, i.e., low coverage of enzyme-specific turnover rates, and subsequently provide a few solutions to solve it. We end with a discussion on the trade-off between model complexity and capability.
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| 22. |
- Chen, Yu, 1990, et al.
(författare)
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Proteome Constraints in Genome-Scale Models
- 2021
-
Ingår i: Metabolic Engineering: Concepts and Applications: Volume 13a and 13b. - : Wiley. ; 13, s. 137-152
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Bokkapitel (övrigt vetenskapligt/konstnärligt)abstract
- Genome-scale metabolic models (GEMs) describe the stoichiometry of all reactions in the cellular metabolic network, and at the same time associate the reactions to the enzymes that catalyze them. This chapter discusses proteome constraints followed by examples on how one particular type of cellular constraint, namely a proteome constraint, is a powerful approach to improve the predictive strength of GEMs. Cells operate under myriad constraints that govern their phenotypes and functioning. A fundamental constraint in the context of metabolism is the conservation of mass and energy. The chapter addresses the recently developed approach GECKO to illustrate how proteome constraints can be integrated into a GEM in a coarse-grained manner. Coarse-grained approaches as GECKO provide a straightforward platform to integrate proteome constraints. Contrasting with the coarse-grained integration, fine-tuned approaches tend to explicitly integrate biological processes into a GEM, example protein synthesis process.
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| 23. |
- Chen, Yu, 1990, et al.
(författare)
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Proteome constraints reveal targets for improving microbial fitness in nutrient-rich environments
- 2021
-
Ingår i: Molecular Systems Biology. - : EMBO. - 1744-4292. ; 17:4
-
Tidskriftsartikel (refereegranskat)abstract
- Cells adapt to different conditions via gene expression that tunes metabolism for maximal fitness. Constraints on cellular proteome may limit such expression strategies and introduce trade-offs. Resource allocation under proteome constraints has explained regulatory strategies in bacteria. It is unclear, however, to what extent these constraints can predict evolutionary changes, especially for microorganisms that evolved under nutrient-rich conditions, i.e., multiple available nitrogen sources, such as Lactococcus lactis. Here, we present a proteome-constrained genome-scale metabolic model of L. lactis (pcLactis) to interpret growth on multiple nutrients. Through integration of proteomics and flux data, in glucose-limited chemostats, the model predicted glucose and arginine uptake as dominant constraints at low growth rates. Indeed, glucose and arginine catabolism were found upregulated in evolved mutants. At high growth rates, pcLactis correctly predicted the observed shutdown of arginine catabolism because limited proteome availability favored lactate for ATP production. Thus, our model-based analysis is able to identify and explain the proteome constraints that limit growth rate in nutrient-rich environments and thus form targets of fitness improvement.
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| 24. |
- Chen, Yu, 1990, et al.
(författare)
-
Reconstruction, simulation and analysis of enzyme-constrained metabolic models using GECKO Toolbox 3.0
- 2024
-
Ingår i: Nature Protocols. - 1754-2189 .- 1750-2799. ; 19:3, s. 629-667
-
Tidskriftsartikel (refereegranskat)abstract
- Genome-scale metabolic models (GEMs) are computational representations that enable mathematical exploration of metabolic behaviors within cellular and environmental constraints. Despite their wide usage in biotechnology, biomedicine and fundamental studies, there are many phenotypes that GEMs are unable to correctly predict. GECKO is a method to improve the predictive power of a GEM by incorporating enzymatic constraints using kinetic and omics data. GECKO has enabled reconstruction of enzyme-constrained metabolic models (ecModels) for diverse organisms, which show better predictive performance than conventional GEMs. In this protocol, we describe how to use the latest version GECKO 3.0; the procedure has five stages: (1) expansion from a starting metabolic model to an ecModel structure, (2) integration of enzyme turnover numbers into the ecModel structure, (3) model tuning, (4) integration of proteomics data into the ecModel and (5) simulation and analysis of ecModels. GECKO 3.0 incorporates deep learning-predicted enzyme kinetics, paving the way for improved metabolic models for virtually any organism and cell line in the absence of experimental data. The time of running the whole protocol is organism dependent, e.g., ~5 h for yeast.
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| 25. |
- Chen, Yu, 1990, et al.
(författare)
-
Single-cell omics analysis with genome-scale metabolic modeling
- 2024
-
Ingår i: Current Opinion in Biotechnology. - 0958-1669 .- 1879-0429. ; 86
-
Forskningsöversikt (refereegranskat)abstract
- Single-cell technologies have been widely used in biological studies and generated a plethora of single-cell data to be interpreted. Due to the inclusion of the priori metabolic network knowledge as well as gene–protein–reaction associations, genome-scale metabolic models (GEMs) have been a powerful tool to integrate and thereby interpret various omics data mostly from bulk samples. Here, we first review two common ways to leverage bulk omics data with GEMs and then discuss advances on integrative analysis of single-cell omics data with GEMs. We end by presenting our views on current challenges and perspectives in this field.
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| 26. |
- Chen, Yu, 1990, et al.
(författare)
-
Systematic inference of functional phosphorylation events in yeast metabolism
- 2017
-
Ingår i: Bioinformatics. - : Oxford University Press (OUP). - 1367-4803 .- 1367-4811. ; 33:13, s. 1995-2001
-
Tidskriftsartikel (refereegranskat)abstract
- Motivation: Protein phosphorylation is a post-translational modification that affects proteins by changing their structure and conformation in a rapid and reversible way, and it is an important mechanism for metabolic regulation in cells. Phosphoproteomics enables high-throughput identification of phosphorylation events on metabolic enzymes, but identifying functional phosphorylation events still requires more detailed biochemical characterization. Therefore, development of computational methods for investigating unknown functions of a large number of phosphorylation events identified by phosphoproteomics has received increased attention. Results: We developed a mathematical framework that describes the relationship between phosphorylation level of a metabolic enzyme and the corresponding flux through the enzyme. Using this framework, it is possible to quantitatively estimate contribution of phosphorylation events to flux changes. We showed that phosphorylation regulation analysis, combined with a systematic workflow and correlation analysis, can be used for inference of functional phosphorylation events in steady and dynamic conditions, respectively. Using this analysis, we assigned functionality to phosphorylation events of 17 metabolic enzymes in the yeast Saccharomyces cerevisiae, among which 10 are novel. Phosphorylation regulation analysis cannot only be extended for inference of other functional post-translational modifications but also be a promising scaffold formulti-omics data integration in systems biology.
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| 27. |
- Chen, Yu, 1990, et al.
(författare)
-
Yeast has evolved to minimize protein resource cost for synthesizing amino acids
- 2022
-
Ingår i: Proceedings of the National Academy of Sciences of the United States of America. - : Proceedings of the National Academy of Sciences. - 0027-8424 .- 1091-6490. ; 119:4
-
Tidskriftsartikel (refereegranskat)abstract
- Proteins, as essential biomolecules, account for a large fraction of cell mass, and thus the synthesis of the complete set of proteins (i.e., the proteome) represents a substantial part of the cellular resource budget. Therefore, cells might be under selective pressures to optimize the resource costs for protein synthesis, particularly the biosynthesis of the 20 proteinogenic amino acids. Previous studies showed that less energetically costly amino acids are more abundant in the proteomes of bacteria that survive under energy-limited conditions, but the energy cost of synthesizing amino acids was reported to be weakly associated with the amino acid usage in Saccharomyces cerevisiae. Here we present a modeling framework to estimate the protein cost of synthesizing each amino acid (i.e., the protein mass required for supporting one unit of amino acid biosynthetic flux) and the glucose cost (i.e., the glucose consumed per amino acid synthesized). We show that the logarithms of the relative abundances of amino acids in S. cerevisiae's proteome correlate well with the protein costs of synthesizing amino acids (Pearson's r = 20.89), which is better than that with the glucose costs (Pearson's r = 20.5). Therefore, we demonstrate that S. cerevisiae tends to minimize protein resource, rather than glucose or energy, for synthesizing amino acids.
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| 28. |
- Fürst, Kristoffer, 1990, et al.
(författare)
-
Hierarchical LSTM-Based Classification of Household Heating Types Using Measurement Data
- 2024
-
Ingår i: IEEE Transactions on Smart Grid. - 1949-3053 .- 1949-3061. ; 15:2, s. 2261-2270
-
Tidskriftsartikel (refereegranskat)abstract
- A lack of knowledge of the heating systems used by electricity consumers impedes distribution system operators in developing a sound grid upgrade plan and estimating potential demand flexibility from these consumers. The large-scale rollout of smart meters for electricity consumers provides an excellent opportunity to identify end users’ heating types. This paper proposed a hierarchically structured deep-learning framework for identifying heating types of individual electricity consumers. The main contributions of the paper are: (a) We propose an effective framework based on long short-term memory (LSTM) that offers an effective automatic feature learning from sequential electricity consumption data and weather conditions. (b) We apply the proposed deep-learning architecture for household heating type classification which is among the first few successful reports on this application. We evaluate the performance using hourly measurement data collected over four years from one and two-family dwellings with either district heating, exhaust air heat pumps or direct electric heating as the heating type. Good performance was shown from the test results using the proposed framework, with an average test accuracy of 94.2%. Comparisons with four existing machine learning algorithms using handcrafted features and a single-layer LSTM-based deep-learning algorithm have shown marked improvement of the proposed method.
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| 29. |
- Fürst, Kristoffer, 1990, et al.
(författare)
-
Improved Peak Load Estimation from Single and Multiple Consumer Categories
- 2020
-
Ingår i: IET Conference Publications. - : Institution of Engineering and Technology (IET). - 2515-0855. ; 2020:CP767, s. 178-181
-
Konferensbidrag (refereegranskat)abstract
- Velander’s formula and coincidence factors have traditionally been used to estimate peak load for new connections in the distribution grid. By re-evaluating their underlying assumptions, this paper proposes two improved models for aggregated peak load estimation (PLE). For single-category load aggregation, the proposed coincidence factor model, by incorporating an average correlation coefficient, improves the model fitting by 76%–96% as compared to the standard Rusck model. For multiple-category load aggregation, the proposed joint Gaussian regression model reduces the PLE bias from 3%–34% to 0.2%–3% compared to the traditional approach. (see the full paper in 4 pages)
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| 30. |
- Fürst, Kristoffer, 1990, et al.
(författare)
-
Support vector machine for classification of households' heating type using load curves
- 2023
-
Ingår i: IET Conference Proceedings. - 2732-4494. ; 2023:6, s. 3884-3888
-
Konferensbidrag (refereegranskat)abstract
- The distribution system operator lacks the knowledge of the heating system used by their customers to make sound grid planning decisions. Energy declaration from buildings and the large-scale rollout of smart meters provides an excellent opportunity to classify the heating system used. This paper proposes a machine-learning-based approach using a support vector machine (SVM) with daily load curves (mean and standard deviation of consumption) extracted from smart meter measurements. Three heating types are analysed: district heating, exhaust air heat pump, and direct electric heating. The performance was compared among the classifiers using daily load curves extracted over one year, for each month, each week, and each day of the year. The highest average accuracy of 92.6% was obtained for the SVM classifier using daily load curves extracted for each week of a year as features. Furthermore, the classifier showed a higher performance than using an ensemble of SVM or random forest classifiers (90.6%/90.5%) proposed in the literature. Lastly, an error analysis of the misclassification was carried out, including building characteristics and geographical analysis.
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| 31. |
- Kim, Hyowon, et al.
(författare)
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RIS-Enabled and Access-Point-Free Simultaneous Radio Localization and Mapping
- 2024
-
Ingår i: IEEE Transactions on Wireless Communications. - 1558-2248 .- 1536-1276. ; 23:4, s. 3344-3360
-
Tidskriftsartikel (refereegranskat)abstract
- In the upcoming sixth generation (6G) of wireless communication systems, reconfigurable intelligent surfaces (RISs) are regarded as one of the promising technological enablers, which can provide programmable signal propagation. Therefore, simultaneous radio localization and mapping (SLAM) with RISs appears as an emerging research direction within the 6G ecosystem. In this paper, we propose a novel framework of RIS-enabled radio SLAM for wireless operation without the intervention of access points (APs). We first design the RIS phase profiles leveraging prior information for the user equipment (UE), such that they uniformly illuminate the angular sector where the UE is probabilistically located. Second, we modify the marginal Poisson multi-Bernoulli SLAM filter and estimate the UE state and landmarks, which enables efficient mapping of the radio propagation environment. Third, we derive the theoretical Cramér-Rao lower bounds on the estimators for the channel parameters and the UE state. We finally evaluate the performance of the proposed method under scenarios with a limited number of transmissions, taking into account the channel coherence time. Our results demonstrate that the RIS enables solving the radio SLAM problem with zero APs, and that the consideration of the Doppler shift contributes to improving the UE speed estimates.
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| 32. |
- Leite, Melina de Souza, et al.
(författare)
-
Major axes of variation in tree demography across global forests
- 2024
-
Ingår i: Ecography. - 0906-7590 .- 1600-0587.
-
Tidskriftsartikel (refereegranskat)abstract
- The future trajectory of global forests is closely intertwined with tree demography, and a major fundamental goal in ecology is to understand the key mechanisms governing spatio-temporal patterns in tree population dynamics. While previous research has made substantial progress in identifying the mechanisms individually, their relative importance among forests remains unclear mainly due to practical limitations. One approach to overcome these limitations is to group mechanisms according to their shared effects on the variability of tree vital rates and quantify patterns therein. We developed a conceptual and statistical framework (variance partitioning of Bayesian multilevel models) that attributes the variability in tree growth, mortality, and recruitment to variation in species, space, and time, and their interactions – categories we refer to as organising principles (OPs). We applied the framework to data from 21 forest plots covering more than 2.9 million trees of approximately 6500 species. We found that differences among species, the species OP, proved a major source of variability in tree vital rates, explaining 28–33% of demographic variance alone, and 14–17% in interaction with space, totalling 40–43%. Our results support the hypothesis that the range of vital rates is similar across global forests. However, the average variability among species declined with species richness, indicating that diverse forests featured smaller interspecific differences in vital rates. Moreover, decomposing the variance in vital rates into the proposed OPs showed the importance of unexplained variability, which includes individual variation, in tree demography. A focus on how demographic variance is organized in forests can facilitate the construction of more targeted models with clearer expectations of which covariates might drive a vital rate. This study therefore highlights the most promising avenues for future research, both in terms of understanding the relative contributions of groups of mechanisms to forest demography and diversity, and for improving projections of forest ecosystems.
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| 33. |
- Li, Feiran, 1993, et al.
(författare)
-
Deep learning-based k(cat) prediction enables improved enzyme-constrained model reconstruction
- 2022
-
Ingår i: Nature Catalysis. - : Springer Science and Business Media LLC. - 2520-1158. ; 5:8, s. 662-672
-
Tidskriftsartikel (refereegranskat)abstract
- Enzyme turnover numbers (k(cat)) are key to understanding cellular metabolism, proteome allocation and physiological diversity, but experimentally measured k(cat) data are sparse and noisy. Here we provide a deep learning approach (DLKcat) for high-throughput k(cat) prediction for metabolic enzymes from any organism merely from substrate structures and protein sequences. DLKcat can capture k(cat) changes for mutated enzymes and identify amino acid residues with a strong impact on k(cat) values. We applied this approach to predict genome-scale k(cat) values for more than 300 yeast species. Additionally, we designed a Bayesian pipeline to parameterize enzyme-constrained genome-scale metabolic models from predicted k(cat) values. The resulting models outperformed the corresponding original enzyme-constrained genome-scale metabolic models from previous pipelines in predicting phenotypes and proteomes, and enabled us to explain phenotypic differences. DLKcat and the enzyme-constrained genome-scale metabolic model construction pipeline are valuable tools to uncover global trends of enzyme kinetics and physiological diversity, and to further elucidate cellular metabolism on a large scale.
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| 34. |
- Li, Feiran, 1993, et al.
(författare)
-
Genome-scale metabolic models applied for human health and biopharmaceutical engineering
- 2023
-
Ingår i: Quantitative Biology. - 2095-4689 .- 2095-4697. ; 11:4, s. 363-375
-
Forskningsöversikt (refereegranskat)abstract
- Over the last 15 years, genome-scale metabolic models (GEMs) have been reconstructed for human and model animals, such as mouse and rat, to systematically understand metabolism, simulate multicellular or multi-tissue interplay, understand human diseases, and guide cell factory design for biopharmaceutical protein production. Here, we describe how metabolic networks can be represented using stoichiometric matrices and well-defined constraints for flux simulation. Then, we review the history of GEM development for quantitative understanding of Homo sapiens and other relevant animals, together with their applications. We describe how model develops from H. sapiens to other animals and from generic purpose to precise context-specific simulation. The progress of GEMs for animals greatly expand our systematic understanding of metabolism in human and related animals. We discuss the difficulties and present perspectives on the GEM development and the quest to integrate more biological processes and omics data for future research and translation. We truly hope that this review can inspire new models developed for other mammalian organisms and generate new algorithms for integrating big data to conduct more in-depth analysis to further make progress on human health and biopharmaceutical engineering.
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| 35. |
- Li, Feiran, 1993, et al.
(författare)
-
GotEnzymes: an extensive database of enzyme parameter predictions
- 2023
-
Ingår i: Nucleic Acids Research. - : Oxford University Press (OUP). - 0305-1048 .- 1362-4962. ; 51:D1, s. D583-D586
-
Tidskriftsartikel (refereegranskat)abstract
- Enzyme parameters are essential for quantitatively understanding, modelling, and engineering cells. However, experimental measurements cover only a small fraction of known enzyme-compound pairs in model organisms, much less in other organisms. Artificial intelligence (Al) techniques have accelerated the pace of exploring enzyme properties by predicting these in a high-throughput manner. Here, we present GotEnzymes, an extensive database with enzyme parameter predictions by Al approaches, which is publicly available at https://metabolicatlas.org/gotenzymes for interactive web exploration and programmatic access. The first release of this data resource contains predicted turnover numbers of over 25.7 million enzyme-compound pairs across 8099 organisms. We believe that GotEnzymes, with the readily-predicted enzyme parameters, would bring a speed boost to biological research covering both experimental and computational fields that involve working with candidate enzymes.
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| 36. |
- Li, Feiran, 1993, et al.
(författare)
-
Improving recombinant protein production by yeast through genome-scale modeling using proteome constraints
- 2022
-
Ingår i: Nature Communications. - : Springer Science and Business Media LLC. - 2041-1723 .- 2041-1723. ; 13:1
-
Tidskriftsartikel (refereegranskat)abstract
- Eukaryotic cells are used as cell factories to produce and secrete multitudes of recombinant pharmaceutical proteins, including several of the current top-selling drugs. Due to the essential role and complexity of the secretory pathway, improvement for recombinant protein production through metabolic engineering has traditionally been relatively ad-hoc; and a more systematic approach is required to generate novel design principles. Here, we present the proteome-constrained genome-scale protein secretory model of yeast Saccharomyces cerevisiae (pcSecYeast), which enables us to simulate and explain phenotypes caused by limited secretory capacity. We further apply the pcSecYeast model to predict overexpression targets for the production of several recombinant proteins. We experimentally validate many of the predicted targets for alpha-amylase production to demonstrate pcSecYeast application as a computational tool in guiding yeast engineering and improving recombinant protein production. Due to the complexity of the protein secretory pathway, strategy suitable for the production of a certain recombination protein cannot be generalized. Here, the authors construct a proteome-constrained genome-scale protein secretory model for yeast and show its application in the production of different misfolded or recombinant proteins.
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| 37. |
- Liu, Shuai, et al.
(författare)
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Development of Pdn/g-C3N4 adsorbent for Hg0 removal – DFT study of influences of the support and Pd cluster size
- 2019
-
Ingår i: Fuel. - : Elsevier BV. - 0016-2361. ; 254
-
Tidskriftsartikel (refereegranskat)abstract
- Elemental mercury in the flue gas is highly hazardous to the ecosystem. However, its removal from gas phase is of challenges as it is highly volatile, chemically very stable and insoluble in water. It is therefore imperative to develop novel adsorbents that are efficient in the removal of elemental mercury from gas mixtures. In this study, density functional theory (DFT) was adopted to assist the development of novel adsorbents for mercury removal based on the in-depth understanding of the adsorption of Hg0 on g-C3N4, single Pd atoms and Pdn(n=2–4) clusters as well as the influences of the support and the size of Pd clusters on Hg0 adsorption. It is found that Hg0 atoms are physically adsorbed on the pristine g-C3N4 and are chemisorbed on the pure Pdn clusters and the Pdn/g-C3N4. The strongest adsorption happens on the Pd2 cluster and the Pd3/g-C3N4, while single Pd atoms doped on the g-C3N4 do not adsorb Hg0 atoms effectively. For a Pd4 cluster, there are at least four adsorption sites for the adsorption of Hg0, while these sites become more active in the presence of the support and the number of active sites for Hg0 adsorption on a Pd4 cluster doped on the g-C3N4 becomes seven due to the enhanced charge transfer from Hg atoms to the Pd cluster and the g-C3N4 surface. The most charge transfers are found to take place in the case of Pd2, Pd2/g-C3N4 and Pd3/g-C3N4, indicating the most intensive interactions between Hg0 and these configurations. Moreover, the shortened Pd-Hg bonds in the Pd3/g-C3N4 and the Pd4/g-C3N4 also shows the enhanced mercury adsorption, while opposite phenomena were observed in the other two structures, i.e., the Pd/g-C3N4 and the Pd2/g-C3N4.
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| 38. |
- Lu, Hongzhong, 1987, et al.
(författare)
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Kinetic Models of Metabolism
- 2021
-
Ingår i: Metabolic Engineering: Concepts and Applications: Volume 13a and 13b. - : Wiley. ; 13, s. 153-170
-
Bokkapitel (övrigt vetenskapligt/konstnärligt)abstract
- This chapter introduces the kinetic models of metabolism followed by examples on the construction of kinetic models as well as applications. With the Michaelis-Menten formulation, the influence of enzyme properties, enzyme abundance, and metabolite concentration on the dynamic behavior of a reaction can be explained mechanistically. Kinetic models mechanistically represent the processes that take place within a cell, and these models are made up of a series of ordinary differential equations. A kinetic model requires the definition of rate equations and their respective parameters for each of the reactions, which are currently unknown for many of the reactions contained in genome-scale models. Reaction kinetics can be described with mathematical expressions where the reaction rates are functions of kinetic parameters and the concentration of metabolites. Approximative rate expression is also adopted in the kinetic model reconstruction. Estimation of parameters in rate expressions is essential for having good predictive performance of a kinetic model.
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| 39. |
- Needham, Jessica F., et al.
(författare)
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Demographic composition, not demographic diversity, predicts biomass and turnover across temperate and tropical forests
- 2022
-
Ingår i: Global Change Biology. - : Wiley. - 1354-1013 .- 1365-2486. ; 28, s. 2895-2909
-
Tidskriftsartikel (refereegranskat)abstract
- The growth and survival of individual trees determine the physical structure of a forest with important consequences for forest function. However, given the diversity of tree species and forest biomes, quantifying the multitude of demographic strategies within and across forests and the way that they translate into forest structure and function remains a significant challenge. Here, we quantify the demographic rates of 1961 tree species from temperate and tropical forests and evaluate how demographic diversity (DD) and demographic composition (DC) differ across forests, and how these differences in demography relate to species richness, aboveground biomass (AGB), and carbon residence time. We find wide variation in DD and DC across forest plots, patterns that are not explained by species richness or climate variables alone. There is no evidence that DD has an effect on either AGB or carbon residence time. Rather, the DC of forests, specifically the relative abundance of large statured species, predicted both biomass and carbon residence time. Our results demonstrate the distinct DCs of globally distributed forests, reflecting biogeography, recent history, and current plot conditions. Linking the DC of forests to resilience or vulnerability to climate change, will improve the precision and accuracy of predictions of future forest composition, structure, and function.
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| 40. |
- Qin, Jiufu, 1985, et al.
(författare)
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Engineering yeast metabolism for the discovery and production of polyamines and polyamine analogues
- 2021
-
Ingår i: Nature Catalysis. - : Springer Science and Business Media LLC. - 2520-1158. ; 4:6, s. 498-509
-
Tidskriftsartikel (refereegranskat)abstract
- Structurally complex and diverse polyamines and polyamine analogues are potential therapeutics and agrochemicals that can address grand societal challenges, for example, healthy ageing and sustainable food production. However, their structural complexity and low abundance in nature hampers either bulk chemical synthesis or extraction from natural resources. Here we reprogrammed the metabolism of baker’s yeast Saccharomyces cerevisiae and recruited nature’s diverse reservoir of biochemical tools to enable a complete biosynthesis of multiple polyamines and polyamine analogues. Specifically, we adopted a systematic engineering strategy to enable gram-per-litre-scale titres of spermidine, a central metabolite in polyamine metabolism. To demonstrate the potential of our polyamine platform, various polyamine synthases and ATP-dependent amide-bond-forming systems were introduced for the biosynthesis of natural and unnatural polyamine analogues. The yeast platform serves as a resource to accelerate the discovery and production of polyamines and polyamine analogues, and thereby unlocks this chemical space for further pharmacological and insecticidal studies. [Figure not available: see fulltext.]
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| 41. |
- Wang, Ying, et al.
(författare)
-
Epoxy composite with high thermal conductivity by constructing 3D-oriented carbon fiber and BN network structure
- 2021
-
Ingår i: RSC Advances. - : Royal Society of Chemistry (RSC). - 2046-2069. ; 11:41, s. 25422-25430
-
Tidskriftsartikel (refereegranskat)abstract
- As electronic devices tend to be integrated and high-powered, thermal conductivity is regarded as the crucial parameter of electronic components, which has become the main factor that limits the operating speed and service lifetime of electronic devices. However, constructing continuous thermal conductive paths for low content particle fillers and reducing interface thermal resistance between fillers and matrix are still two challenging issues for the preparation of thermally conductive composites. In this study, 3D-oriented carbon fiber (CF) thermal network structures filled with boron nitride flakes (BN) as thermal conductive bridges were successfully constructed. The epoxy composite was fabricated by thermal conductive material with a 3D oriented structure by the vacuum liquid impregnation method. This special 3D-oriented structure modified by BN (BN/CF) could efficiently broaden the heat conduction pathway and connected adjacent fibers, which leads to the reduction of thermal resistance. The thermal conductivity of the boron nitride/carbon fiber/epoxy resin composite (BN/CF/EP) with 5 vol% 10 mm CF and 40 vol% BN reaches up to 3.1 W m(-1) K-1, and its conductivity is only 2.5 x 10(-4) S cm(-1). This facile and high-efficient method could provide some useful advice for the thermal management material in the microelectronic field and aerospace industry.
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| 42. |
- Wang, Ying, et al.
(författare)
-
Epoxy Composites with High Thermal Conductivity by Constructing Three-Dimensional Carbon Fiber/Carbon/Nickel Networks Using an Electroplating Method
- 2021
-
Ingår i: ACS Omega. - : American Chemical Society (ACS). - 2470-1343. ; 6:29, s. 19238-19251
-
Tidskriftsartikel (refereegranskat)abstract
- Heat dissipation problem is the primary factor restricting the service life of an electronic component. The thermal conductivity of materials has become a bottleneck that hinders the development of the electronic information industry (such as light-emitting diodes, SG mobile phones). Therefore, the research on improving the thermal conductivity of materials has a very important theoretical value and a practical application value. Whether the thermally conductive filler in polymer composites can form a highly thermal conductive pathway is a key issue at this stage. The carbon fiber/carbon felt (CF/C felt) prepared in the study has a three-dimensional continuous network structure. The nickel-coated carbon fiber/carbon felt (CF/C/Ni felt) was fabricated by an electroplating deposition method. Three-dimensional CF/C/Ni/epoxy composites were manufactured by vacuum-assisted liquid-phase impregnation. By forming connection points between the adjacent carbon fibers, the thermal conduction path inside the felt can be improved so as to improve the thermal conductivity of the CF/C/Ni/epoxy composite. The thermal conductivity of the CF/ C/Ni/epoxy composite (in-plane KO is up to 2.13 W/(m K) with 14.0 wt % CF/C and 3.70 wt % Ni particles (60 min electroplating deposition). This paper provides a theoretical basis for the development of high thermal conductivity and high-performance composite materials urgently needed in industrial production and high-tech fields.
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| 43. |
- Xia, Jianye, 1980, et al.
(författare)
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Proteome allocations change linearly with the specific growth rate of Saccharomyces cerevisiae under glucose limitation
- 2022
-
Ingår i: Nature Communications. - : Springer Science and Business Media LLC. - 2041-1723 .- 2041-1723. ; 13:1
-
Tidskriftsartikel (refereegranskat)abstract
- Saccharomyces cerevisiae is a widely used cell factory; therefore, it is important to understand how it organizes key functional parts when cultured under different conditions. Here, we perform a multiomics analysis of S. cerevisiae by culturing the strain with a wide range of specific growth rates using glucose as the sole limiting nutrient. Under these different conditions, we measure the absolute transcriptome, the absolute proteome, the phosphoproteome, and the metabolome. Most functional protein groups show a linear dependence on the specific growth rate. Proteins engaged in translation show a perfect linear increase with the specific growth rate, while glycolysis and chaperone proteins show a linear decrease under respiratory conditions. Glycolytic enzymes and chaperones, however, show decreased phosphorylation with increasing specific growth rates; at the same time, an overall increased flux through these pathways is observed. Further analysis show that even though mRNA levels do not correlate with protein levels for all individual genes, the transcriptome level of functional groups correlates very well with its corresponding proteome. Finally, using enzyme-constrained genome-scale modeling, we find that enzyme usage plays an important role in controlling flux in amino acid biosynthesis. Understanding how yeast organizes its functional proteome is a fundamental task in systems biology. Here, the authors conduct a multiomics analysis on yeast cells cultured with different growth rates, identifying a linear dependence of the functional proteome on the growth rate.
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| 44. |
- Yang, Liting, et al.
(författare)
-
NiMn layered double hydroxide nanosheets/NiCo2O4 nanowires with surface rich high valence state metal oxide as an efficient electrocatalyst for oxygen evolution reaction
- 2018
-
Ingår i: Journal of Power Sources. - : Elsevier BV. - 0378-7753. ; 392, s. 23-32
-
Tidskriftsartikel (refereegranskat)abstract
- High valence transition metal oxide is significant for anode catalyst of proton membrane water electrolysis technique. Herein, we demonstrate NiMn layered double hydroxide nanosheets/NiCo 2 O 4 nanowires hierarchical nanocomposite catalyst with surface rich high valence metal oxide as an efficient catalyst for oxygen evolution reaction. A low overpotential of 310 mV is needed to drive a 10 mA cm −2 with a Tafel slope of 99 mV dec −1 , and a remarkable stability during 8 h is demonstrated in a chronoamperometry test. Theoretical calculation displays the change in the rate-determining step on the nanocomposite electrode in comparison to NiCo 2 O 4 nanowires alone. It is found high valence Ni and Mn oxide in the catalyst system can efficiently facilitate the charge transport across the electrode/electrolyte interface. The enhanced electrical conductivity, more accessible active sites and synergistic effects between NiMn layered double hydroxide nanosheets and NiCo 2 O 4 nanowires can account for the excellent oxygen evolution reaction. The catalytic performance is comparable to most of the best non-noble catalysts and IrO 2 noble catalyst, indicating the promising applications in water-splitting technology. It is an important step in the development of hierarchical nanocomposites by surface valence state tuning as an alternative to noble metals for oxygen evolution reaction.
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| 45. |
- Zhang, J., et al.
(författare)
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Combining mechanistic and machine learning models for predictive engineering and optimization of tryptophan metabolism
- 2020
-
Ingår i: Nature Communications. - : Springer Science and Business Media LLC. - 2041-1723 .- 2041-1723. ; 11:1
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Tidskriftsartikel (refereegranskat)abstract
- Through advanced mechanistic modeling and the generation of large high-quality datasets, machine learning is becoming an integral part of understanding and engineering living systems. Here we show that mechanistic and machine learning models can be combined to enable accurate genotype-to-phenotype predictions. We use a genome-scale model to pinpoint engineering targets, efficient library construction of metabolic pathway designs, and high-throughput biosensor-enabled screening for training diverse machine learning algorithms. From a single data-generation cycle, this enables successful forward engineering of complex aromatic amino acid metabolism in yeast, with the best machine learning-guided design recommendations improving tryptophan titer and productivity by up to 74 and 43%, respectively, compared to the best designs used for algorithm training. Thus, this study highlights the power of combining mechanistic and machine learning models to effectively direct metabolic engineering efforts.
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| 46. |
- Zhang, Yiming, 1986, et al.
(författare)
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Engineering yeast mitochondrial metabolism for 3-hydroxypropionate production
- 2023
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Ingår i: Biotechnology for Biofuels and Bioproducts. - 2731-3654. ; 16:1
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Tidskriftsartikel (refereegranskat)abstract
- Background: With unique physiochemical environments in subcellular organelles, there has been growing interest in harnessing yeast organelles for bioproduct synthesis. Among these organelles, the yeast mitochondrion has been found to be an attractive compartment for production of terpenoids and branched-chain alcohols, which could be credited to the abundant supply of acetyl-CoA, ATP and cofactors. In this study we explored the mitochondrial potential for production of 3-hydroxypropionate (3-HP) and performed the cofactor engineering and flux control at the acetyl-CoA node to maximize 3-HP synthesis. Results: Metabolic modeling suggested that the mitochondrion serves as a more suitable compartment for 3-HP synthesis via the malonyl-CoA pathway than the cytosol, due to the opportunity to obtain a higher maximum yield and a lower oxygen consumption. With the malonyl-CoA reductase (MCR) targeted into the mitochondria, the 3-HP production increased to 0.27 g/L compared with 0.09 g/L with MCR expressed in the cytosol. With enhanced expression of dissected MCR enzymes, the titer reached to 4.42 g/L, comparable to the highest titer achieved in the cytosol so far. Then, the mitochondrial NADPH supply was optimized by overexpressing POS5 and IDP1, which resulted in an increase in the 3-HP titer to 5.11 g/L. Furthermore, with induced expression of an ACC1 mutant in the mitochondria, the final 3-HP production reached 6.16 g/L in shake flask fermentations. The constructed strain was then evaluated in fed-batch fermentations, and produced 71.09 g/L 3-HP with a productivity of 0.71 g/L/h and a yield on glucose of 0.23 g/g. Conclusions: In this study, the yeast mitochondrion is reported as an attractive compartment for 3-HP production. The final 3-HP titer of 71.09 g/L with a productivity of 0.71 g/L/h was achieved in fed-batch fermentations, representing the highest titer reported for Saccharomyces cerevisiae so far, that demonstrated the potential of recruiting the yeast mitochondria for further development of cell factories.
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