Model-driven insights into the effects of temperature on metabolism

Wendering, Philipp; Nikoloski, Zoran

doi:10.1016/j.biotechadv.2023.108203

Cited by 6 publications

(5 citation statements)

References 186 publications

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“…This provides a possible route for examining secondary metabolism in microbes by constraining GEMs with gene-expression data. Many tools have been developed for this purpose (e.g., [ 54 , 116 , 117 , 118 , 119 , 120 , 121 , 122 ]), and their uses and differences have been reviewed [ 123 , 124 , 125 ]. The deluge of heterogenous system-level data makes the use of these types of modeling essential for elucidating the metabolic state of a system under different conditions, particularly when the change in the environment is not biochemical but physical (e.g., temperature change).…”

Section: Discussionmentioning

confidence: 99%

Uses of Multi-Objective Flux Analysis for Optimization of Microbial Production of Secondary Metabolites

Griesemer,

Navid

2023

Microorganisms

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Secondary metabolites are not essential for the growth of microorganisms, but they play a critical role in how microbes interact with their surroundings. In addition to this important ecological role, secondary metabolites also have a variety of agricultural, medicinal, and industrial uses, and thus the examination of secondary metabolism of plants and microbes is a growing scientific field. While the chemical production of certain secondary metabolites is possible, industrial-scale microbial production is a green and economically attractive alternative. This is even more true, given the advances in bioengineering that allow us to alter the workings of microbes in order to increase their production of compounds of interest. This type of engineering requires detailed knowledge of the “chassis” organism’s metabolism. Since the resources and the catalytic capacity of enzymes in microbes is finite, it is important to examine the tradeoffs between various bioprocesses in an engineered system and alter its working in a manner that minimally perturbs the robustness of the system while allowing for the maximum production of a product of interest. The in silico multi-objective analysis of metabolism using genome-scale models is an ideal method for such examinations.

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Section: Discussionmentioning

confidence: 99%

Uses of Multi-Objective Flux Analysis for Optimization of Microbial Production of Secondary Metabolites

Griesemer,

Navid

2023

Microorganisms

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“…For both species, we excluded the conditions that did not have measured uptake rates, growth rates, or protein content. In addition, we excluded the temperature stress conditions from Lahtvee et al [ 19 ], as temperature can severely impact the function of enzymes [ 51 ], and temperature stress responses entail changes beyond metabolic flux redistribution [ 17 ]. To prevent overconstraining the models, we allowed 5% flexibility on the growth rate.…”

Section: Methodsmentioning

confidence: 99%

PARROT: Prediction of enzyme abundances using protein-constrained metabolic models

Ferreira,

Silveira,

Nikoloski

2023

PLoS Comput Biol

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Protein allocation determines the activity of cellular pathways and affects growth across all organisms. Therefore, different experimental and machine learning approaches have been developed to quantify and predict protein abundance and how they are allocated to different cellular functions, respectively. Yet, despite advances in protein quantification, it remains challenging to predict condition-specific allocation of enzymes in metabolic networks. Here, using protein-constrained metabolic models, we propose a family of constrained-based approaches, termed PARROT, to predict how much of each enzyme is used based on the principle of minimizing the difference between a reference and an alternative growth condition. To this end, PARROT variants model the minimization of enzyme reallocation using four different (combinations of) distance functions. We demonstrate that the PARROT variant that minimizes the Manhattan distance between the enzyme allocation of a reference and an alternative condition outperforms existing approaches based on the parsimonious distribution of fluxes or enzymes for both Escherichia coli and Saccharomyces cerevisiae. Further, we show that the combined minimization of flux and enzyme allocation adjustment leads to inconsistent predictions. Together, our findings indicate that minimization of protein allocation rather than flux redistribution is a governing principle determining steady-state pathway activity for microorganism grown in alternative growth conditions.

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“…The majority of temperature-specific metabolic models are created through the integration of transcriptomics data of organisms growing at two different temperatures in vitro . The integration of ‘-omics’ data to create temperature-specific models is predominantly achieved using FVA to align flux and expression ratios [ 156 ]. Metabolic factors contributing to thermotolerance have been investigated using temperature-specific reconstructions of the fungus Kluyveromyces marxianus [ 128 ] and the Antarctic bacterium Pseudoalteromonas haloplanktis [ 157 ].…”

Section: Introductionmentioning

confidence: 99%

Applications of genome-scale metabolic models to investigate microbial metabolic adaptations in response to genetic or environmental perturbations

Carter,

Constantinidou,

Alam

2023

Briefings in Bioinformatics

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Environmental perturbations are encountered by microorganisms regularly and will require metabolic adaptations to ensure an organism can survive in the newly presenting conditions. In order to study the mechanisms of metabolic adaptation in such conditions, various experimental and computational approaches have been used. Genome-scale metabolic models (GEMs) are one of the most powerful approaches to study metabolism, providing a platform to study the systems level adaptations of an organism to different environments which could otherwise be infeasible experimentally. In this review, we are describing the application of GEMs in understanding how microbes reprogram their metabolic system as a result of environmental variation. In particular, we provide the details of metabolic model reconstruction approaches, various algorithms and tools for model simulation, consequences of genetic perturbations, integration of ‘-omics’ datasets for creating context-specific models and their application in studying metabolic adaptation due to the change in environmental conditions.

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Model-driven insights into the effects of temperature on metabolism

Cited by 6 publications

References 186 publications

Uses of Multi-Objective Flux Analysis for Optimization of Microbial Production of Secondary Metabolites

Uses of Multi-Objective Flux Analysis for Optimization of Microbial Production of Secondary Metabolites

PARROT: Prediction of enzyme abundances using protein-constrained metabolic models

Applications of genome-scale metabolic models to investigate microbial metabolic adaptations in response to genetic or environmental perturbations

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