Limited Mechanistic Link Between the Monod Equation and Methanogen Growth: a Perspective from Metabolic Modeling

Jin, Qusheng; Wu, Qiong; Shapiro, Benjamin M.; McKernan, Shannon E.

doi:10.1128/spectrum.02259-21

Cited by 5 publications

(4 citation statements)

References 77 publications

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“…While these data are consistent with prior observations from studies with Methanothermobacter spp., they diverge from predictions made by metabolic models of Methanosarcina spp. during methanol growth (13). Clearly, more physiological studies like ours are required to bridge the gap between research with enzymes in isolation and systems-level analyses of methanogens.…”

Section: Discussionmentioning

confidence: 99%

“…No direct evidence linking MCR abundance to growth and methanogenesis is currently available, and there are differing views literature. A recent study used a kinetic and stoichiometric hybrid approach to model the growth of Methanosarcina barkeri on methanol (13). Here, they showed MCR has a high control coefficient (of ∼0.9) during growth on high methanol concentrations (> 15 mM) i.e., that small changes in MCR levels have a dramatic impact on growth rate under typical batch-culture conditions.…”

Section: Introductionmentioning

confidence: 99%

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Physiological and transcriptomic response to methyl-coenzyme M reductase limitation inMethanosarcina acetivorans

Chadwick,

Dury,

Nayak

2023

Preprint

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Methyl-coenzyme M reductase (MCR) catalyzes the final step of methanogenesis, the microbial metabolism responsible for nearly all biological methane emissions to the atmosphere. Decades of biochemical and structural studies have generated detailed insights into MCR functionin vitro, yet very little is known about the interplay between MCR and methanogen physiology. For instance, while it is routinely stated that MCR catalyzes the rate-limiting step of methanogenesis, this statement has not been categorically tested. Here, to gain a more direct understanding of MCR’s control on the growth ofMethanosarcina acetivorans,we generate a strain with an induciblemcroperon on the chromosome, allowing for careful control of MCR expression. We show that MCR is not growth rate limiting in substrate-replete batch cultures. However, through careful titration of MCR expression, growth-limiting state(s) can be obtained. Transcriptomic analysis ofM. acetivoransexperiencing MCR-limitation reveals a global response with hundreds of differentially expressed genes across diverse functional categories. Notably, MCR limitation leads to a strong induction of methylsulfide methyltransferases, likely due to insufficient recycling of metabolic intermediates. In addition, themcroperon does not seem to be transcriptionally regulated, i.e., it is constitutively expressed, suggesting that the overabundance of MCR might be beneficial when cells experience nutrient limitation or stressful conditions. Altogether, we show that there is wide range of cellular MCR concentrations that can sustain optimal growth, suggesting that other factors like anabolic reactions might be rate-limiting for methanogenic growth.ImportanceMethane is a potent greenhouse gas that has contributed toca.25% of global warming in the post-industrial era. Atmospheric methane is primarily of biogenic origin, mostly produced by microorganisms called methanogens. In methanogens, methyl-coenzyme M reductase (MCR) catalyzes methane formation. Even though MCR comprisesca.10% of the cellular proteome, it is hypothesized to be growth-limiting during methanogenesis. Here, we show thatMethanosarcina acetivoransgrown under standard laboratory conditions produces more MCR than its cellular demand for optimal growth. The tools outlined in this study can be used to refine metabolic models of methanogenesis and assay lesions in MCR in a higher throughput manner than isolation and biochemical characterization of pure protein.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Physiological and transcriptomic response to methyl-coenzyme M reductase limitation inMethanosarcina acetivorans

Chadwick,

Dury,

Nayak

2023

Preprint

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“…In 1942, Monod, the founder of cellular growth kinetics, proposed a hyperbolic relationship between the concentration of substrate and cell growth kinetics (i.e., the Monod model, see Equation (1)) [ 18 ]. The Monod kinetic model describes the growth kinetics of cells through thousands of enzymes, which is the most widely used unstructured kinetic model [ 19 ]. For example, Pau et al described the uptake rates of the substrates, glucose and xylose, and the inhibitors using a Monod-type kinetic model in the lignocellulosic fermentation [ 20 ].…”

Section: Development Of Modelingmentioning

confidence: 99%

From Spatial-Temporal Multiscale Modeling to Application: Bridging the Valley of Death in Industrial Biotechnology

et al. 2023

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The Valley of Death confronts industrial biotechnology with a significant challenge to the commercialization of products. Fortunately, with the integration of computation, automation and artificial intelligence (AI) technology, the industrial biotechnology accelerates to cross the Valley of Death. The Fourth Industrial Revolution (Industry 4.0) has spurred advanced development of intelligent biomanufacturing, which has evolved the industrial structures in line with the worldwide trend. To achieve this, intelligent biomanufacturing can be structured into three main parts that comprise digitalization, modeling and intellectualization, with modeling forming a crucial link between the other two components. This paper provides an overview of mechanistic models, data-driven models and their applications in bioprocess development. We provide a detailed elaboration of the hybrid model and its applications in bioprocess engineering, including strain design, process control and optimization, as well as bioreactor scale-up. Finally, the challenges and opportunities of biomanufacturing towards Industry 4.0 are also discussed.

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“…No direct evidence linking MCR abundance to growth and methanogenesis is currently available, and there are differing views in literature. A recent study used a kinetic and stoichiometric hybrid approach to model the growth of Methanosarcina barkeri on methanol ( 13 ). They showed that MCR has a high control coefficient (of ~0.9) during growth on high methanol concentrations (> 15 mM), i.e., small changes in MCR levels will have a dramatic impact on growth rate under typical batch-culture conditions.…”

Section: Introductionmentioning

confidence: 99%

Physiological and transcriptomic response to methyl-coenzyme M reductase limitation in Methanosarcina acetivorans

Chadwick,

Dury,

Nayak

2024

Appl Environ Microbiol

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Methyl-coenzyme M reductase (MCR) catalyzes the final step of methanogenesis, the microbial metabolism responsible for nearly all biological methane emissions to the atmosphere. Decades of biochemical and structural research studies have generated detailed insights into MCR function in vitro , yet very little is known about the interplay between MCR and methanogen physiology. For instance, while it is routinely stated that MCR catalyzes the rate-limiting step of methanogenesis, this has not been categorically tested. In this study, to gain a more direct understanding of MCR’s control on the growth of Methanosarcina acetivorans, we generate a strain with an inducible mcr operon on the chromosome, allowing for careful control of MCR expression. We show that MCR is not growth rate-limiting in substrate-replete batch cultures. However, through careful titration of MCR expression, growth-limiting state(s) can be obtained. Transcriptomic analysis of M. acetivorans experiencing MCR limitation reveals a global response with hundreds of differentially expressed genes across diverse functional categories. Notably, MCR limitation leads to strong induction of methylsulfide methyltransferases, likely due to insufficient recycling of metabolic intermediates. In addition, the mcr operon is not transcriptionally regulated, i.e., it is constitutively expressed, suggesting that the overabundance of MCR might be beneficial when cells experience nutrient limitation or stressful conditions. Altogether, we show that there is a wide range of cellular MCR concentrations that can sustain optimal growth, suggesting that other factors such as anabolic reactions might be rate-limiting for methanogenic growth. IMPORTANCE Methane is a potent greenhouse gas that has contributed to ca. 25% of global warming in the post-industrial era. Atmospheric methane is primarily of biogenic origin, mostly produced by microorganisms called methanogens. Methyl-coenzyme M reductase (MCR) catalyzes methane formatio in methanogens. Even though MCR comprises ca. 10% of the cellular proteome, it is hypothesized to be growth-limiting during methanogenesis. In this study, we show that Methanosarcina acetivorans cells grown in substrate–replicate batch cultures produce more MCR than its cellular demand for optimal growth. The tools outlined in this study can be used to refine metabolic models of methanogenesis and assay lesions in MCR in a higher-throughput manner than isolation and biochemical characterization of pure protein.

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Limited Mechanistic Link Between the Monod Equation and Methanogen Growth: a Perspective from Metabolic Modeling

Cited by 5 publications

References 77 publications

Physiological and transcriptomic response to methyl-coenzyme M reductase limitation inMethanosarcina acetivorans

Physiological and transcriptomic response to methyl-coenzyme M reductase limitation inMethanosarcina acetivorans

From Spatial-Temporal Multiscale Modeling to Application: Bridging the Valley of Death in Industrial Biotechnology

Physiological and transcriptomic response to methyl-coenzyme M reductase limitation in Methanosarcina acetivorans

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