Application of genome-scale models of metabolism and expression to the simulation and design of recombinant organisms DOI Creative Commons
Omid Oftadeh, Vassily Hatzimanikatis

bioRxiv (Cold Spring Harbor Laboratory), Journal Year: 2023, Volume and Issue: unknown

Published: Sept. 15, 2023

Abstract The production of recombinant proteins in a host using synthetic constructs such as plasmids comes at the cost detrimental effects reduced growth, energetic inefficiencies, and other stress responses, collectively known metabolic stress. Increasing number copies foreign gene increases load but expression protein. Thus, there is trade-off between biomass product yield response to changes heterologous copy number. This work proposes computational method, rETFL (recombinant Expression Thermodynamic Flux), for analyzing predicting responses organisms introduction constructs. an extension ETFL formulations designed reconstruct models metabolism (ME-models). We have illustrated capabilities method four studies (i) capture growth reduction plasmid-containing E. coli protein production; (ii) explore plasmid varied; (iii) predict emergence overflow agreement with experimental data; (iv) investigate individual pathways enzymes affected by presence plasmid. anticipate that will serve comprehensive platform integrating available omics data making context-specific predictions can help optimize systems biopharmaceutical therapy.

Language: Английский

De novo evolution of antibiotic resistance to Oct-TriA1 DOI Creative Commons
Farhan Rahman Chowdhury, Laura Domínguez Mercado,

Katya Kharitonov

et al.

Microbiological Research, Journal Year: 2025, Volume and Issue: 293, P. 128056 - 128056

Published: Jan. 14, 2025

Language: Английский

Citations

0
Actionable Forecasting as a Determinant of Biological Adaptation DOI Creative Commons
José M. G. Vilar, Leonor Saiz

Advanced Science, Journal Year: 2025, Volume and Issue: unknown

Published: Feb. 27, 2025

Abstract Organisms continuously adapt to changing environments survive. Here, contrary the prevailing view that predictive strategies are essential for perfect adaptation, it is shown biological systems can precisely track their optimal state by adapting a non‐anticipatory actionable target integrates current optimum with its rate of change. Predictive mechanisms, such as circadian rhythms, beneficial accurately inferring when environmental sensing slow or unreliable. A new mathematical framework developed, showing dynamics‐informed neural networks embodying these principles efficiently capture adaptation even in noisy environments. These results provide fundamental insights into interplay between forecasting, control, and inference systems, redefining guiding design advanced adaptive biomolecular circuits.

Language: Английский

Citations

0
The Dawn of High-Throughput and Genome-Scale Kinetic Modeling: Recent Advances and Future Directions DOI Creative Commons

Ilias Toumpe,

Subham Choudhury, Vassily Hatzimanikatis

et al.

ACS Synthetic Biology, Journal Year: 2025, Volume and Issue: unknown

Published: April 22, 2025

Researchers have invested much effort into developing kinetic models due to their ability capture dynamic behaviors, transient states, and regulatory mechanisms of metabolism, providing a detailed realistic representation cellular processes. Historically, the requirements for parametrization significant computational resources created barriers development adoption high-throughput studies. However, recent advancements, including integration machine learning with mechanistic metabolic models, novel parameter databases, use tailor-made strategies, are reshaping field modeling. In this Review, we discuss these developments offer future directions, highlighting potential advances drive progress in systems synthetic biology, engineering, medical research at an unprecedented scale pace.

Language: Английский

Citations

0
Geometrically balanced model of cell growth DOI
Alexei Vázquez, Tomáš Gedeon

Journal of Theoretical Biology, Journal Year: 2025, Volume and Issue: unknown, P. 112085 - 112085

Published: March 1, 2025

Language: Английский

Citations

0
Differential anaerobic oxidation of benzoate in Geotalea daltonii FRC-32 DOI Creative Commons
Christina M. Kiessling,

Sujay F. Greenlund,

James E. Bullows

et al.

Microbiology Spectrum, Journal Year: 2025, Volume and Issue: unknown

Published: March 5, 2025

The efficient carbon source utilization in dynamic environments, including anoxic subsurface contaminated by aromatic compounds, is a challenge for anaerobic bacteria such as Geotalea daltonii strain FRC-32. aim of this study was to elucidate the metabolic pathways employed G. FRC-32 during benzoate oxidation presence acetate, key intermediate organic matter degradation, predict transport and strategies. Simultaneous monoauxic growth were observed cultures grown on 1 mM + 5 2 acetate spiked with benzoate. Sequential diauxic only Benzoate accumulation whole cell lysates indicated that intracellular occurred acetate. Expression analyses putative transporter BenK protein-ligand binding affinity prediction suggested BenK's specificity transporting Relative expression levels gene benK, encoding BenK, genes bamNOPQ, involved benzoyl-CoA pathway, significantly higher both than sole source, indicating facilitated regulation bamNOPQ. Our results demonstrated can perform differential either simultaneous or sequential oxidation, which plasticity response varying availability.IMPORTANCEThe contamination environments crude oil derivatives compounds global concern due persistence toxicity these pollutants. Anaerobic play crucial role degradation hydrocarbons under conditions; however, potential mechanisms are not well understood. This contributed elucidating how efficiently utilizes Findings associated understanding FRC-32's pathways, provided significant insights into modulate energetically favorable strategies environmental conditions.

Language: Английский

Citations

0
New insights in metabolism modelling to decipher plant–microbe interactions DOI Creative Commons

Clara Blonde,

Amélie Caddeo,

William Nasser

et al.

New Phytologist, Journal Year: 2025, Volume and Issue: unknown

Published: March 21, 2025

Summary Plant disease outbreaks, exacerbated by climate change, threaten food security and environmental sustainability world‐wide. Plants interact with a wide range of microorganisms. The quest for resilient agriculture requires deep insight into the molecular ecological interplays between plants their associated microbial communities. Omics methods, profiling entire sets, have shed light on these complex interactions. Nonetheless, deciphering relationships among thousands components remains formidable challenge, studies that integrate cohesive biological networks involving microbes are still limited. Systems biology has potential to predict effects biotic abiotic perturbations networks. It is therefore promising framework addressing full complexity plant–microbiome

Language: Английский

Citations

0
Recent advances in model-assisted metabolic engineering DOI
Steinn Guðmundsson, Juan Nogales

Current Opinion in Systems Biology, Journal Year: 2021, Volume and Issue: 28, P. 100392 - 100392

Published: Oct. 13, 2021

Language: Английский

Citations

23
Biodiversity is enhanced by sequential resource utilization and environmental fluctuations via emergent temporal niches DOI Creative Commons
Blox Bloxham, Hyunseok Lee, Jeff Gore

et al.

bioRxiv (Cold Spring Harbor Laboratory), Journal Year: 2023, Volume and Issue: unknown

Published: Feb. 21, 2023

Abstract How natural communities maintain their remarkable biodiversity and which species survive in complex are central questions ecology. Resource competition models successfully explain many phenomena but typically predict only as resources can coexist. Here, we demonstrate that sequential resource utilization, or diauxie, with periodic growth cycles support more than resources. We explore how modify own environments by sequentially depleting to form sequences of temporal niches, intermediately depleted environments. Biodiversity is enhanced when community-driven environmental fluctuations modulate the depletion order produce different niches on each cycle. Community-driven under constant conditions rare, exploring them illuminates niche structure emerges from utilization. With fluctuations, find most have stably coexisting survivors accurately predicted same following a distinct optimal strategy. Our results thus present new niche-based approach understanding highly diverse fluctuating communities.

Language: Английский

Citations

8
The Architecture of Metabolic Networks Constrains the Evolution of Microbial Resource Hierarchies DOI Creative Commons

Sotaro Takano,

Jean C. C. Vila, Ryo Miyazaki

et al.

Molecular Biology and Evolution, Journal Year: 2023, Volume and Issue: 40(9)

Published: Aug. 23, 2023

Microbial strategies for resource use are an essential determinant of their fitness in complex habitats. When facing environments with multiple nutrients, microbes often them sequentially according to a preference hierarchy, resulting well-known patterns diauxic growth. In theory, the evolutionary diversification metabolic hierarchies could represent mechanism supporting coexistence and biodiversity by enabling temporal segregation niches. Despite this ecologically critical role, extent which substrate can evolve diversify remains largely unexplored. Here, we used genome-scale modeling systematically explore evolution across vast space network genotypes. We find that only limited number readily evolve, corresponding most commonly observed genome-derived models. further show how novel is constrained architecture central metabolism, determines both propensity change ranks between pairs substrates effect specific reactions on hierarchy evolution. Our analysis sheds light genetic mechanistic determinants microbial hierarchies, opening new research avenues understand evolution, evolvability, ecology.

Language: Английский

Citations

6
The Expanding Computational Toolbox for Engineering Microbial Phenotypes at the Genome Scale DOI Creative Commons
Daniel C. Zielinski, Arjun Patel, Bernhard Ø. Palsson

et al.

Microorganisms, Journal Year: 2020, Volume and Issue: 8(12), P. 2050 - 2050

Published: Dec. 21, 2020

Microbial strains are being engineered for an increasingly diverse array of applications, from chemical production to human health. While traditional engineering disciplines driven by predictive design tools, these tools have been difficult build biological due the complexity systems and many unknowns their quantitative behavior. However, recent advances, gap between in biology other fields is closing. In this work, we discuss promising areas development computational microbial strains. We define five frontiers active research: (1) Constraint-based modeling metabolic network reconstruction, (2) Kinetics thermodynamic modeling, (3) Protein structure analysis, (4) Genome sequence (5) Regulatory analysis. Experimental machine learning drivers enabled methods improve leaps bounds both scope accuracy. Modern strain projects will require be comprehensively applied entire cell efficiently integrated within a single workflow. expect that frontiers, ongoing revolution big data science, drive forward more advanced powerful strategies.

Language: Английский

Citations

13