Quantifying the benefit of a proteome reserve in fluctuating environments

Mori, Matteo; Schink, Severin Josef; Erickson, David W.; Gerland, Ulrich; Hwa, Terence

doi:10.1038/s41467-017-01242-8

Cited by 140 publications

(193 citation statements)

References 53 publications

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“…which are no focus of this work) potentially show short-term trade-offs(Mori et al, 2017; Reimers et al, 318 2017), these might lead to a discrepancy between modeled and real evolutionary scenario. In particular, 319 the difference between periodic and fluctuating conditions of the natural ancestral habitat on one hand, 320 and the stable experimental growth conditions in audited growth chambers and the statically modeled 321 evolutionary scenario on the other hand might have a strong effect.…”

mentioning

confidence: 93%

Modeling Cellular Resource Allocation Reveals Low Phenotypic Plasticity of C₄ Plants and Infers Environments of C₄ Photosynthesis Evolution

Sundermann

Lercher

Heckmann

2018

Preprint

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Summary-The regulation of resource allocation in biological systems observed today is the cumulative result of natural selection in ancestral and recent environments. To what extent are observed resource allocation patterns in different photosynthetic types optimally adapted to current conditions, and to what extend do they reflect ancestral environments? Here, we explore these questions for C3, C4, and C3-C4 intermediate plants of the model genus Flaveria.-We developed a detailed mathematical model of carbon fixation, which accounts for various environmental parameters and for energy and nitrogen partitioning across photosynthetic components. This allows us to assess environment-dependent plant physiology and performance as a function of resource allocation patterns.-To achieve maximal CO2 fixation rates under growth conditions differing from those experienced during their evolution, C4 species need to re-allocate significantly more nitrogen between photosynthetic components than their C3 relatives. As this is linked to a limited phenotypic plasticity, observed resource distributions in C4 plants still reflect optimality in ancestral environments, allowing their quantitative inference.-Our work allows us to quantify environmental effects on resource allocation and performance of photosynthetic organisms. This understanding paves the way for interpreting present photosynthetic physiology in the light of evolutionary history.

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mentioning

confidence: 93%

Modeling Cellular Resource Allocation Reveals Low Phenotypic Plasticity of C₄ Plants and Infers Environments of C₄ Photosynthesis Evolution

Sundermann

Lercher

Heckmann

2018

Preprint

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“…In particular, they often go from poor conditions with slow growth to richer conditions with more rapid growth, changes known as nutritional upshifts (Poulsen et al, 1995). Despite the considerable experimental and theoretical research going back to Maaløe and Koch on nutritional upshifts (Brunschede et al, 1977;Dennis, 1974;Ehrenberg et al, 2013;Erickson et al, 2017;Giordano et al, 2016;Koch and Deppe, 1971;Maaløe and Kjeldgaard, 1966;Mori et al, 2017b;Pavlov and Ehrenberg, 2013;Sloan and Urban, 1976), no simple upshift growth law was yet described.…”

Section: Introductionmentioning

confidence: 99%

A bacterial growth law out of steady-state

Kohanim

Levi

Jona

et al. 2018

Preprint

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SummaryBacterial growth depends on numerous reactions, and yet follows surprisingly simple laws that inspired biologists for decades. Growth laws until now primarily dealt with steady-state exponential growth in constant conditions. However, bacteria in nature often face fluctuating environments, with nutritional upshifts and downshifts. We therefore ask whether there are growth laws that apply to changing environments. We derive a law for strong upshifts using an optimal resource-allocation model that was previously calibrated at steady-state growth: the post-shift growth rate equals the geometrical mean of the pre-shift growth rate and the growth rate on saturating carbon. We test this using chemostat and robotic batch culture experiments, as well as previous data from several species, and find good agreement with the model predictions. The increase in growth rate after an upshift indicates that ribosomes have spare capacity. We demonstrate theoretically that spare ribosomal capacity has the cost of slow steady-state growth, but is beneficial in fluctuating environments because it prevents large overshoots in intracellular metabolites after an upshift and allows rapid response to change. We also provide predictions for downshifts for future experimental tests. Spare capacity appears in diverse biological systems, and the present study quantifies the optimal degree of spare capacity, which rises the slower the growth rate, and suggests that it can be precisely regulated.

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“…Yet we observed differences at the genomic level that are consistent with recently proposed models, which predict that competitive advantage of bacteria under changing environmental condition is achieved by reserve capacity of ribosomes and transporters. Accordingly, sub-saturation allows bacteria to rapidly adapt in fluctuating environments by producing new ribosomes and high affinity transporters for optimal growth (54,55). We also observed that the disturbed period was significantly enriched in secretion system, which are used to deliver a variety of different proteins, including bacterial toxins and degradative enzymes such as proteases and lipases (56).…”

Section: Discussionmentioning

confidence: 85%

Time-series genome-centric analysis unveils bacterial response to operational disturbance in activated sludge

Pérez

Guerrero

Orellana

et al. 2019

Preprint

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Understanding ecosystem response to disturbances and identifying the most critical traits for the maintenance of ecosystem functioning are important goals for microbial community ecology. In this study, we used 16S rRNA amplicon sequencing and metagenomics to investigate the assembly of bacterial populations in a full-scale municipal activated sludge wastewater treatment plant over a period of three years, including a period of nine month of disturbance, characterized by short-term plant shutdowns. Following the reconstruction of 173 metagenome-assembled genomes, we assessed the functional potential, the number of rRNA gene operons and the in situ growth rate of microorganisms present throughout the time series. Operational disturbances caused a significant decrease in bacteria with a single copy of the ribosomal RNA (rrn) operon. Despite only moderate differences in resource availability, Understanding the drivers of community structure is important for developing predictive models and for guiding engineering and management practice of microbial community ecosystems (1-4). Activated sludge is the most widely used process for biological wastewater treatment worldwide (5). It involves highly diverse biomass aggregated into flocs, which can be separated from treated wastewater by gravity settling. The heterogeneous structure of activated sludge flocs is a result of physical, chemical, and biological processes. These include (a) physicochemical interactions between microorganisms, exopolymeric substances (EPS), inorganic particles and di-and trivalent cations, (b) biological interactions among diverse microorganisms within the community, and (c) physiological processes for nutrient uptake and resource allocation between biological activities in bacterial cells (6). The selection of microbial populations in these ecosystems is driven primarily by environmental and operational pressures (7).A great deal of knowledge has been achieved during the last two decades from research exploring how bacterial community composition is affected by process configuration, solid retention time (SRT), temperature, redox conditions, wastewater composition, pH, and other factors (8)(9)(10)(11)(12)(13)(14)(15)(16). Recent progress in high-throughput sequencing technology has facilitated a detailed characterization of the composition of microbial communities in a large number of wastewater treatment systems worldwide (12,(17)(18)(19). However, the ability to produce a precise ecological description of activated sludge based on the abundance of the species present is still elusive.Typically, wastewater treatment plants (WWTP) are able to perform reliably under fluctuating conditions. Given that the stability of microbial communities is affected by disturbance events, it is important to understand how ecosystems respond to disturbance and which traits are the most critical for the maintenance of functioning. To date few studies have addressed the response of microbial communities to disturbance in full-scale wastewater treatment systems (20...

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Quantifying the benefit of a proteome reserve in fluctuating environments

Cited by 140 publications

References 53 publications

Modeling Cellular Resource Allocation Reveals Low Phenotypic Plasticity of C₄ Plants and Infers Environments of C₄ Photosynthesis Evolution

Modeling Cellular Resource Allocation Reveals Low Phenotypic Plasticity of C₄ Plants and Infers Environments of C₄ Photosynthesis Evolution

A bacterial growth law out of steady-state

Time-series genome-centric analysis unveils bacterial response to operational disturbance in activated sludge

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Quantifying the benefit of a proteome reserve in fluctuating environments

Cited by 140 publications

References 53 publications

Modeling Cellular Resource Allocation Reveals Low Phenotypic Plasticity of C4 Plants and Infers Environments of C4 Photosynthesis Evolution

Modeling Cellular Resource Allocation Reveals Low Phenotypic Plasticity of C4 Plants and Infers Environments of C4 Photosynthesis Evolution

A bacterial growth law out of steady-state

Time-series genome-centric analysis unveils bacterial response to operational disturbance in activated sludge

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Product

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Modeling Cellular Resource Allocation Reveals Low Phenotypic Plasticity of C₄ Plants and Infers Environments of C₄ Photosynthesis Evolution

Modeling Cellular Resource Allocation Reveals Low Phenotypic Plasticity of C₄ Plants and Infers Environments of C₄ Photosynthesis Evolution