Research output: Contribution to journal › Review article › peer-review
State-of the-Art Constraint-Based Modeling of Microbial Metabolism: From Basics to Context-Specific Models with a Focus on Methanotrophs. / Куляшов, Михаил Андреевич; Колмыков, Семён Константинович; Хлебодарова, Тамара Михайловна et al.
In: Microorganisms, Vol. 11, No. 12, 2987, 14.12.2023.Research output: Contribution to journal › Review article › peer-review
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TY - JOUR
T1 - State-of the-Art Constraint-Based Modeling of Microbial Metabolism: From Basics to Context-Specific Models with a Focus on Methanotrophs
AU - Куляшов, Михаил Андреевич
AU - Колмыков, Семён Константинович
AU - Хлебодарова, Тамара Михайловна
AU - Акбердин, Илья Ринатович
N1 - The study was financially supported by the Russian Science Foundation (project № 23-24-00606, https://rscf.ru/en/project/23-24-00606/).
PY - 2023/12/14
Y1 - 2023/12/14
N2 - Methanotrophy is the ability of an organism to capture and utilize the greenhouse gas, methane, as a source of energy-rich carbon. Over the years, significant progress has been made in understanding of mechanisms for methane utilization, mostly in bacterial systems, including the key metabolic pathways, regulation and the impact of various factors (iron, copper, calcium, lanthanum, and tungsten) on cell growth and methane bioconversion. The implementation of -omics approaches provided vast amount of heterogeneous data that require the adaptation or development of computational tools for a system-wide interrogative analysis of methanotrophy. The genome-scale mathematical modeling of its metabolism has been envisioned as one of the most productive strategies for the integration of muti-scale data to better understand methane metabolism and enable its biotechnological implementation. Herein, we provide an overview of various computational strategies implemented for methanotrophic systems. We highlight functional capabilities as well as limitations of the most popular web resources for the reconstruction, modification and optimization of the genome-scale metabolic models for methane-utilizing bacteria.
AB - Methanotrophy is the ability of an organism to capture and utilize the greenhouse gas, methane, as a source of energy-rich carbon. Over the years, significant progress has been made in understanding of mechanisms for methane utilization, mostly in bacterial systems, including the key metabolic pathways, regulation and the impact of various factors (iron, copper, calcium, lanthanum, and tungsten) on cell growth and methane bioconversion. The implementation of -omics approaches provided vast amount of heterogeneous data that require the adaptation or development of computational tools for a system-wide interrogative analysis of methanotrophy. The genome-scale mathematical modeling of its metabolism has been envisioned as one of the most productive strategies for the integration of muti-scale data to better understand methane metabolism and enable its biotechnological implementation. Herein, we provide an overview of various computational strategies implemented for methanotrophic systems. We highlight functional capabilities as well as limitations of the most popular web resources for the reconstruction, modification and optimization of the genome-scale metabolic models for methane-utilizing bacteria.
KW - constraint-based modeling
KW - context-specific modeling
KW - genome-scale metabolic modeling
KW - methanotrophy
KW - pipeline
KW - tool
KW - transcriptomics
UR - https://www.scopus.com/record/display.uri?eid=2-s2.0-85180675040&origin=inward&txGid=271955e8894959b28240ab3d93f21c39
UR - https://www.mendeley.com/catalogue/a8f5de38-c475-35e5-a64a-e12f17dbada2/
U2 - 10.3390/microorganisms11122987
DO - 10.3390/microorganisms11122987
M3 - Review article
C2 - 38138131
VL - 11
JO - Microorganisms
JF - Microorganisms
SN - 2076-2607
IS - 12
M1 - 2987
ER -
ID: 59344701