Showing papers on "Chemostat published in 2022"
TL;DR: In this article , the conversion of the industrial platform organism Escherichia coli into a synthetic methylotroph that assimilates methanol via the energy efficient ribulose monophosphate cycle was reported.
Abstract: Methanol is a liquid with high energy storage capacity that holds promise as an alternative substrate to replace sugars in the biotechnology industry. It can be produced from CO2 or methane and its use does not compete with food and animal feed production. However, there are currently only limited biotechnological options for the valorization of methanol, which hinders its widespread adoption. Here, we report the conversion of the industrial platform organism Escherichia coli into a synthetic methylotroph that assimilates methanol via the energy efficient ribulose monophosphate cycle. Methylotrophy is achieved after evolution of a methanol-dependent E. coli strain over 250 generations in continuous chemostat culture. We demonstrate growth on methanol and biomass formation exclusively from the one-carbon source by 13C isotopic tracer analysis. In line with computational modeling, the methylotrophic E. coli strain optimizes methanol oxidation by upregulation of an improved methanol dehydrogenase, increasing ribulose monophosphate cycle activity, channeling carbon flux through the Entner-Doudoroff pathway and downregulating tricarboxylic acid cycle enzymes. En route towards sustainable bioproduction processes, our work lays the foundation for the efficient utilization of methanol as the dominant carbon and energy resource.
16 citations
TL;DR: It is shown that constraining protein availability substantially improves accuracy of the description of the metabolic state of the cell under dynamic conditions, which enables more realistic and faithful designs of industrially relevant cell‐based processes and, thus, the usefulness of such models.
Abstract: Genome‐scale, constraint‐based models (GEM) and their derivatives are commonly used to model and gain insights into microbial metabolism. Often, however, their accuracy and predictive power are limited and enable only approximate designs. To improve their usefulness for strain and bioprocess design, we studied here their capacity to accurately predict metabolic changes in response to operational conditions in a bioreactor, as well as intracellular, active reactions. We used flux balance analysis (FBA) and dynamic FBA (dFBA) to predict growth dynamics of the model organism Saccharomyces cerevisiae under different industrially relevant conditions. We compared simulations with the latest developed GEM for this organism (Yeast8) and its enzyme‐constrained version (ecYeast8) herein described with experimental data and found that ecYeast8 outperforms Yeast8 in all the simulations. EcYeast8 was able to predict well‐known traits of yeast metabolism including the onset of the Crabtree effect, the order of substrate consumption during mixed carbon cultivation and production of a target metabolite. We showed how the combination of ecGEM and dFBA links reactor operation and genetic modifications to flux predictions, enabling the prediction of yields and productivities of different strains and (dynamic) production processes. Additionally, we present flux sampling as a tool to analyse flux predictions of ecGEM, of major importance for strain design applications. We showed that constraining protein availability substantially improves accuracy of the description of the metabolic state of the cell under dynamic conditions. This therefore enables more realistic and faithful designs of industrially relevant cell‐based processes and, thus, the usefulness of such models.
12 citations
TL;DR: In this article , a high disturbed chemostat model for industrial wastewater is proposed, and the long-run characteristics of the Chemostat process are classified by using the threshold classification approach.
Abstract: In this research, we expose new results on the dynamics of a high disturbed chemostat model for industrial wastewater. Due to the complexity of heavy and erratic environmental variations, we take into consideration the polynomial perturbation. We scout the asymptotic characterization of our proposed system with a general interference response. It is demonstrated that the long-run characteristics of the chemostat process are classified by using the threshold classification approach. If the critical sill is strictly negative, the bacteria will disappear exponentially, indicating that the chemostat wastewater process is not running (excluded scenario), otherwise, the stationarity and ergodicity properties of our model are verified (practical scenario). The theoretical arsenal of this work offers a comprehensive overview of the industrial wastewater behavior under general hypotheses and introduces novel technical aspects to deal with other perturbed systems in biology. Numerically, we audit the accuracy of our threshold in three particular situations: linear, quadratic and cubic perturbations. We establish that the increasing order of disturbance has a passive influence on the extinction time of bacteria. This finding highlights that complex noise sources fulfill a significant role in the transient dynamics of chemostat systems.
10 citations
TL;DR: The presented approach provides insights into environmental conditions observed by microorganisms in large-scale bioreactors and paves the way for an improved understanding of how inhomogeneous environmental conditions influence cellular physiology, growth and production.
Abstract: The biotechnological production of fine chemicals, proteins and pharmaceuticals is usually hampered by loss of microbial performance during scale-up. This challenge is mainly caused by discrepancies between homogeneous environmental conditions at laboratory scale, where bioprocesses are optimized, and inhomogeneous conditions in large-scale bioreactors, where production takes place. Therefore, to improve strain selection and process development, it is of great interest to characterize these fluctuating conditions at large-scale and to study their effects on microbial cells. In this paper, we demonstrate the potential of computational fluid dynamics (CFD) simulation of large-scale bioreactors combined with dynamic microfluidic single-cell cultivation (dMSCC). Environmental conditions in a 200 L bioreactor were characterized with CFD simulations. Computational lifelines were determined by combining simulated turbulent multiphase flow, mass transport and particle tracing. Glucose availability for Corynebacterium glutamicum cells was determined. The reactor was simulated with average glucose concentrations of 6 g m−3, 10 g m−3 and 16 g m−3. The resulting computational lifelines, discretized into starvation and abundance regimes, were used as feed profiles for the dMSCC to investigate how varying glucose concentration affects cell physiology and growth rate. In this study, each colony in the dMSCC device represents a single cell as it travels through the reactor. Under oscillating conditions reproduced in the dMSCC device, a decrease in growth rate of about 40% was observed compared to continuous supply with the same average glucose availability. The presented approach provides insights into environmental conditions observed by microorganisms in large-scale bioreactors. It also paves the way for an improved understanding of how inhomogeneous environmental conditions influence cellular physiology, growth and production.
9 citations
TL;DR: In this paper , a 2.5-L chemostat was operated for 115 days and three operational phases were tested at decreasing SRT of 40, 23 and 13 h, testing S/N ratios in the range of 0.5 − 1 gS/gN.
8 citations
TL;DR: This work investigates the μ-dependent bioprocess performance of the model-acetogen Clostridium autoethanogenum in CO and syngas grown chemostat cultures and shows that faster growth of the biocatalyst improves the gas fermentation biop rocess.
Abstract: Gas fermentation offers both fossil carbon-free sustainable production of fuels and chemicals and recycling of gaseous and solid waste using gas-fermenting microbes. Bioprocess development, systems-level analysis of biocatalyst metabolism, and engineering of cell factories are advancing the widespread deployment of the commercialised technology. Acetogens are particularly attractive biocatalysts but effects of the key physiological parameter – specific growth rate (μ) – on acetogen metabolism and the gas fermentation bioprocess have not been established yet. Here, we investigate the μ-dependent bioprocess performance of the model-acetogen Clostridium autoethanogenum in CO and syngas (CO+CO2+H2) grown chemostat cultures and assess systems-level metabolic responses using gas analysis, metabolomics, transcriptomics, and metabolic modelling. We were able to obtain steady-states up to μ ~2.8 day-1 (~0.12 h-1) and show that faster growth supports both higher yields and productivities for reduced by-products ethanol and 2,3-butanediol. Transcriptomics data revealed differential expression of 1,337 genes with increasing μ and suggest that C. autoethanogenum uses transcriptional regulation to a large extent for facilitating faster growth. Metabolic modelling showed significantly increased fluxes for faster growing cells that were, however, not accompanied by gene expression changes in key catabolic pathways for CO and H2 metabolism. Cells thus seem to maintain sufficient “baseline” gene expression to rapidly respond to CO and H2 availability without delays to kick-start metabolism. Our work advances understanding of transcriptional regulation in acetogens and shows that faster growth of the biocatalyst improves the gas fermentation bioprocess.
8 citations
TL;DR: In this paper , a chemostat-like model was proposed for thin biofilms forming on highly perfusable (non-diffusible) anodes in small-scale, continuous flow MFCs due to the unique properties of the electroactive biofilm.
7 citations
01 Jan 2022
TL;DR: In this article, the problem of controlling the dilution rate in a chemostat to regulate the ratio between the concentrations of two microbial populations growing in continuous culture has been addressed and two alternative feedback control strategies, one based on a gain-scheduled state feedback controller, the other on a switching control strategy, are presented.
Abstract: We address the problem of controlling the dilution rate in a chemostat to regulate the ratio between the concentrations of two microbial populations growing in continuous culture. After analyzing the open-loop dynamics of this multicellular system, we present two alternative feedback control strategies, one based on a gain-scheduled state feedback controller, the other on a switching control strategy. We show that both strategies are effective in solving the problem and illustrate the results by a set of representative in-silico experiments.
7 citations
TL;DR: In this article , 1.6-L chemostat cultures inoculated with activated sludge samples were sustained for ca. 100 days with low concentration (<2 ppmv) and feed rate (<1.44 µmoles h-1) of N2O, and the resulting microbial consortia were analyzed via quantitative PCR (qPCR) and metagenomic/metatranscriptomic analyses.
Abstract: Microorganisms possessing N2O reductases (NosZ) are the only known environmental sink of N2O. While oxygen inhibition of NosZ activity is widely known, environments where N2O reduction occurs are often not devoid of O2. However, little is known regarding N2O reduction in microoxic systems. Here, 1.6-L chemostat cultures inoculated with activated sludge samples were sustained for ca. 100 days with low concentration (<2 ppmv) and feed rate (<1.44 µmoles h-1) of N2O, and the resulting microbial consortia were analyzed via quantitative PCR (qPCR) and metagenomic/metatranscriptomic analyses. Unintended but quantified intrusion of O2 sustained dissolved oxygen concentration above 4 µM; however, complete N2O reduction of influent N2O persisted throughout incubation. Metagenomic investigations indicated that the microbiomes were dominated by an uncultured taxon affiliated to Burkholderiales, and, along with the qPCR results, suggested coexistence of clade I and II N2O reducers. Contrastingly, metatranscriptomic nosZ pools were dominated by the Dechloromonas-like nosZ subclade, suggesting the importance of the microorganisms possessing this nosZ subclade in reduction of trace N2O. Further, co-expression of nosZ and ccoNO/cydAB genes found in the metagenome-assembled genomes representing these putative N2O-reducers implies a survival strategy to maximize utilization of scarcely available electron acceptors in microoxic environmental niches.
7 citations
TL;DR: In this article , the authors considered a Lotka-Volterra food chain chemostat model that incorporates both distributed delay and stochastic perturbations, and obtained sufficient conditions for the existence of stationary distribution by constructing suitable Lyapunov functions.
6 citations
TL;DR: A Lotka–Volterra food chain che mostat model that incorporates both distributed delay and stochastic perturbations is considered, and stationary distribution indicates the two species in the chemostat can coexist in the long term.
TL;DR: In this article , the authors analyzed the transcriptomic responses of three Saccharomyces cerevisiae strains, a commercial wine strain, ADY5, a laboratory strain, CEN.PK113-7D and a commercial bioethanol strain, Ethanol Red, grown at non-optimal temperatures under anaerobic chemostat conditions.
TL;DR: In this paper , a model-based analysis of the competition between microalgae and bacteria mediated by nitrogen and organic carbon in a continuous bioreactor with recycle is presented, aimed to evaluate if the ability of micro algae to uncouple nitrogen and carbon uptake can allow to prevent the contamination of bacteria with negligible carbon accumulation or to sustain the coexistence of micro alga and bacteria.
01 Jan 2022
TL;DR: In this article , the problem of controlling the dilution rate in a chemostat to regulate the ratio between the concentrations of two microbial populations growing in continuous culture has been addressed and two alternative feedback control strategies, one based on a gain-scheduled state feedback controller, the other on a switching control strategy, are presented.
Abstract: We address the problem of controlling the dilution rate in a chemostat to regulate the ratio between the concentrations of two microbial populations growing in continuous culture. After analyzing the open-loop dynamics of this multicellular system, we present two alternative feedback control strategies, one based on a gain-scheduled state feedback controller, the other on a switching control strategy. We show that both strategies are effective in solving the problem and illustrate the results by a set of representative in-silico experiments.
TL;DR: The entire approach, including both strain and bioprocess engineering, represents a relevant novelty involving physiological control in Pichia cell factory and is of crucial interest in biop rocess optimization, boosting RPP, allowing bioproducts to be economically competitive in the market, and helping develop the bio economy.
Abstract: The combination of strain and bioprocess engineering strategies should be considered to obtain the highest levels of recombinant protein production (RPP) while assuring product quality and process reproducibility of heterologous products. In this work, two complementary approaches were investigated to improve bioprocess efficiency based on the yeast P. pastoris. Firstly, the performance of two Candida rugosa lipase 1 producer clones with different gene dosage under the regulation of the constitutive P GAP were compared in chemostat cultures with different oxygen-limiting conditions. Secondly, hypoxic conditions in carbon-limited fed-batch cultures were applied by means of a physiological control based on the respiratory quotient (RQ). Stirring rate was selected to maintain RQ between 1.4 and 1.6, since it was found to be the most favorable in chemostat. As the major outcome, between 2-fold and 4-fold higher specific production rate (q P ) values were observed when comparing multicopy clone (MCC) and single-copy clone (SCC), both in chemostat and fed-batch. Additionally, when applying oxygen limitation, between 1.5-fold and 3-fold higher q P values were obtained compared with normoxic conditions. Thus, notable increases of up to 9-fold in the production rates were reached. Furthermore, transcriptional analysis of certain key genes related to RPP and central carbon metabolism were performed. Results seem to indicate the presence of a limitation in post-transcriptional protein processing steps and a possible transcription attenuation of the target gene in the strains with high gene dosage. The entire approach, including both strain and bioprocess engineering, represents a relevant novelty involving physiological control in Pichia cell factory and is of crucial interest in bioprocess optimization, boosting RPP, allowing bioproducts to be economically competitive in the market, and helping develop the bioeconomy.
TL;DR: In this article , the authors performed gene expression analysis of Saccharomyces cerevisiae grown in intermittently fed chemostat cultures to study the effect of limitation-starvation transitions.
Abstract: In fed‐batch operated industrial bioreactors, glucose‐limited feeding is commonly applied for optimal control of cell growth and product formation. Still, microbial cells such as yeasts and bacteria are frequently exposed to glucose starvation conditions in poorly mixed zones or far away from the feedstock inlet point. Despite its commonness, studies mimicking related stimuli are still underrepresented in scale‐up/scale‐down considerations. This may surprise as the transition from glucose limitation to starvation has the potential to provoke regulatory responses with negative consequences for production performance. In order to shed more light, we performed gene‐expression analysis of Saccharomyces cerevisiae grown in intermittently fed chemostat cultures to study the effect of limitation‐starvation transitions. The resulting glucose concentration gradient was representative for the commercial scale and compelled cells to tolerate about 76 s with sub‐optimal substrate supply. Special attention was paid to the adaptation status of the population by discriminating between first time and repeated entry into the starvation regime. Unprepared cells reacted with a transiently reduced growth rate governed by the general stress response. Yeasts adapted to the dynamic environment by increasing internal growth capacities at the cost of rising maintenance demands by 2.7%. Evidence was found that multiple protein kinase A (PKA) and Snf1‐mediated regulatory circuits were initiated and ramped down still keeping the cells in an adapted trade‐off between growth optimization and down‐regulation of stress response. From this finding, primary engineering guidelines are deduced to optimize both the production host's genetic background and the design of scale‐down experiments.
TL;DR: In this paper , a simple mechanistic model of Pseudo-nitzschia and domoic acid dynamics was proposed to quantify and estimate the feedbacks between DA production and environmental conditions, which validated against batch and chemostat experiments.
TL;DR: In this article , a food chain chemostat model with double delays was studied and the conditions for the Hopf bifurcation of the system at the positive equilibrium were analyzed.
Abstract: In this paper, we study a food chain chemostat model with Michaelis-Menten function response and double delays. Applying the stability theory of functional differential equations, we discuss the conditions for the stability of three equilibria, respectively. Furthermore, we analyze the sufficient conditions for the Hopf bifurcation of the system at the positive equilibrium. Finally, we present some numerical examples to verify the correctness of the theoretical analysis and give some valuable conclusions and further discussions at the end of the paper.
TL;DR: This S. cerevisiae-E.
Abstract: Hydroxytyrosol is a valuable plant-derived phenolic compound with excellent pharmacological activities for application in the food and health care industries. Microbial biosynthesis provides a promising approach for sustainable production of hydroxytyrosol via metabolic engineering. However, its efficient production is limited by the machinery and resources available in the commonly used individual microbial platform, for example, Escherichia coli, Saccharomyces cerevisiae. In this study, a S. cerevisiae-E. coli coculture system was designed for de novo biosynthesis of hydroxytyrosol by taking advantage of their inherent metabolic properties, whereby S. cerevisiae was engineered for de novo production of tyrosol based on an endogenous Ehrlich pathway, and E. coli was dedicated to converting tyrosol to hydroxytyrosol by use of native hydroxyphenylacetate 3-monooxygenase (EcHpaBC). To enhance hydroxytyrosol production, intra- and intermodule engineering was employed in this microbial consortium: (I) in the upstream S. cerevisiae strain, multipath regulations combining with a glucose-sensitive GAL regulation system were engineered to enhance the precursor supply, resulting in significant increase of tyrosol production (from 17.60 mg/L to 461.07 mg/L); (II) Echpabc was overexpressed in the downstream E. coli strain, improving the conversion rate of tyrosol to hydroxytyrosol from 0.03% to 86.02%; (III) and last, intermodule engineering with this coculture system was performed by optimization of the initial inoculation ratio of each population and fermentation conditions, achieving 435.32 mg/L of hydroxytyrosol. This S. cerevisiae-E. coli coculture strategy provides a new opportunity for de novo production of hydroxytyrosol from inexpensive feedstock.
TL;DR: In this paper , metabolic models for the haptophyte microalgae Tisochrysis lutea with different possible organic carbon excretion mechanisms were proposed, based on the DRUM (Dynamic Reduction of Unbalanced Metabolism) methodology.
Abstract: We propose metabolic models for the haptophyte microalgae Tisochrysis lutea with different possible organic carbon excretion mechanisms. These models—based on the DRUM (Dynamic Reduction of Unbalanced Metabolism) methodology—are calibrated with an experiment of nitrogen starvation under day/night cycles, and then validated with nitrogen-limited chemostat culture under continuous light. We show that models including exopolysaccharide excretion offer a better prediction capability. It also gives an alternative mechanistic interpretation to the Droop model for nitrogen limitation, which can be understood as an accumulation of carbon storage during nitrogen stress, rather than the common belief of a nitrogen pool driving growth. Excretion of organic carbon limits its accumulation, which leads to a maximal C/N ratio (corresponding to the minimum Droop N/C quota). Although others phenomena—including metabolic regulations and dissipation of energy—are possibly at stake, excretion appears as a key component in our metabolic model, that we propose to include in the Droop model.
TL;DR: In this article , the authors considered the problem of species separation in a photobioreactor, where the objective is to select the desired species in minimal time and to synthesize an optimal feedback control.
Abstract: In this paper, we investigate the problem of species separation in minimal time. Droop model is considered to describe the evolution of two distinct populations of microorganisms that are in competition for the same resource in a photobioreactor. We focus on an optimal control problem (OCP) subject to a five-dimensional controlled system in which the control represents the dilution rate of the chemostat. The objective is to select the desired species in minimal-time and to synthesize an optimal feedback control. This is a very challenging issue, since we are are dealing with a ten-dimensional optimality system. We provide properties of optimal controls allowing the strain of interest to dominate the population. Our analysis is based on the Pontryagin Maximum Principle (PMP), along with a thorough study of singular arcs that is crucial in the synthesis of optimal controls. These theoretical results are also extensively illustrated and validated using a direct method in optimal control (via the Bocop software for numerically solving optimal control problems). The approach is illustrated with numerical examples with microalgae, reflecting the complexity of the optimal control structure and the richness of the dynamical behavior.
TL;DR: This paper investigated the response of a batch-cultured subantarctic diatom to projected change simulating conditions for 2100 (increased temperature/CO2/irradiance/iron; decreased macronutrients), showed a twofold higher chlorophyll-derived growth rate driven mainly by temperature and iron.
Abstract: The influence of global change on Southern Ocean productivity will have major ramifications for future management of polar life. A prior laboratory study investigated the response of a batch‐cultured subantarctic diatom to projected change simulating conditions for 2100 (increased temperature/CO2/irradiance/iron; decreased macronutrients), showed a twofold higher chlorophyll‐derived growth rate driven mainly by temperature and iron. We translated this design to the field to understand the phytoplankton community response, within a subantarctic foodweb, to 2100 conditions. A 7‐d shipboard study utilizing 250‐liter mesocosms was conducted in March 2016. The outcome mirrors lab‐culture experiments, yielding twofold higher chlorophyll in the 2100 treatment relative to the control. This trend was also evident for intrinsic metrics including nutrient depletion. Unlike the lab‐culture study, photosynthetic competence revealed a transient effect in the 2100 mesocosm, peaking on day 3 then declining. Metaproteomics revealed significant differences in protein profiles between treatments by day 7. The control proteome was enriched for photosynthetic processes (c.f. 2100) and exhibited iron‐limitation signatures; the 2100 proteome exposed a shift in cellular energy production. Our findings of enhanced phytoplankton growth are comparable to model simulations, but underlying mechanisms (temperature, iron, and/or light) differ between experiments and models. Batch‐culture approaches hinder cross‐comparison of mesocosm findings to model simulations (the latter are akin to “continuous‐culture chemostats”). However, chemostat techniques are problematic to use with mesocosms, as mesozooplankton will evade seawater flow‐through, thereby accumulating. Thus, laboratory, field, and modeling approaches reveal challenges to be addressed to better understand how global change will alter Southern Ocean productivity.
TL;DR: Nitrogenase-dependent H2 production by photosynthetic bacteria, such as Rhodobacter capsulatus, has been extensively investigated and random mutations in the genome of the engineered H2-sensing strain were induced to induce random mutations leading to H2 overproduction.
Abstract: Nitrogenase-dependent H2 production by photosynthetic bacteria, such as Rhodobacter capsulatus, has been extensively investigated. An important limitation to increase H2 production using genetic manipulation is the scarcity of high-throughput screening methods to detect possible overproducing mutants. Previously, we engineered R. capsulatus strains that emitted fluorescence in response to H2 and used them to identify mutations in the nitrogenase Fe protein leading to H2 overproduction. Here, we used ultraviolet light to induce random mutations in the genome of the engineered H2-sensing strain, and fluorescent-activated cell sorting to detect and isolate the H2-overproducing cells from libraries containing 5 × 105 mutants. Three rounds of mutagenesis and strain selection gradually increased H2 production up to 3-fold. The whole genomes of five H2 overproducing strains were sequenced and compared to that of the parental sensor strain to determine the basis for H2 overproduction. No mutations were present in well-characterized functions related to nitrogen fixation, except for the transcriptional activator nifA2. However, several mutations mapped to energy-generating systems and to carbon metabolism-related functions, which could feed reducing power or ATP to nitrogenase. Time-course experiments of nitrogenase depression in batch cultures exposed mismatches between nitrogenase protein levels and their H2 and ethylene production activities that suggested energy limitation. Consistently, cultivating in a chemostat produced up to 19-fold more H2 than the corresponding batch cultures, revealing the potential of selected H2 overproducing strains.
TL;DR: In this paper , a diffusive predator-prey chemostat system was investigated in terms of the diffusion rate and the results showed that there exist two critical diffusion rates which classify the dynamical behavior of this system into the following three scenarios: (i) for a large diffusion rate, all species will be washed out; (ii) for an intermediate diffusion rates, the predator goes extinct and the prey survives; (iii) for the small diffusion rate all species coexist.
Abstract: This paper deals with a diffusive predator-prey chemostat system which describes the growth of planktonic rotifers, Brachionus calyciflorus, feeding on unicellular green algae, Chlorella vulgaris. The dynamical behavior of this system is established in terms of the diffusion rate. The results show that there exist two critical diffusion rates which classify the dynamical behavior of this system into the following three scenarios: (i) for a large diffusion rate, all species will be washed out; (ii) for an intermediate diffusion rate, the predator goes extinct and the prey survives; (iii) for a small diffusion rate, all species coexist. Finally, our numerical results show that the solution of this system may undergo a steady-state bifurcation or Hopf bifurcation for a suitably small diffusion rate, which supplements our theoretical results.
TL;DR: In this paper , the authors proposed a maximum entropy inference method for E. coli, which can be explained by the chemostat dynamics, which typically drives nutrient-limited cultures toward observable metabolic states maximally restricted in the dimensions of those fluxes.
TL;DR: Comparative proteomic analysis of Y. lipolytica grown in nitrogen-limited chemostat cultures at different dilution rates identified various cellular functions and biological mechanisms involved in oleaginousness and selected genes affected lipid accumulation.
Abstract: Given the strong potential of Yarrowia lipolytica to produce lipids for use as renewable fuels and oleochemicals, it is important to gain in-depth understanding of the molecular mechanism underlying its lipid accumulation. As cellular growth rate affects biomass lipid content, we performed a comparative proteomic analysis of Y. lipolytica grown in nitrogen-limited chemostat cultures at different dilution rates. After confirming the correlation between growth rate and lipid accumulation, we were able to identify various cellular functions and biological mechanisms involved in oleaginousness. Inspection of significantly up- and downregulated proteins revealed nonintuitive processes associated with lipid accumulation in this yeast. This included proteins related to endoplasmic reticulum (ER) stress, ER–plasma membrane tether proteins, and arginase. Genetic engineering of selected targets validated that some genes indeed affected lipid accumulation. They were able to increase lipid content and were complementary to other genetic engineering strategies to optimize lipid yield.
TL;DR: A method for manipulating phage-bacteria dynamics using an in vitro chemostat bioreactor model of the distal human gut to simulate individual-specific features of human distal gut microbiota that can be used to transmit phages between ecosystems and measure their impacts on the microbiota.
Abstract: Bacteriophages are relatively ubiquitous in the environment and are highly abundant in the human microbiome. Phages can be commonly transmitted between close contacts, but the impact that such transmissions may have on their bacteria counterparts in our microbiomes is unknown. ABSTRACT The study of bacteriophage communities reproducing in the gastrointestinal tract is limited by the quality of model systems supporting experimental manipulation in vitro. Traditionally, studies aiming to experimentally address phage-bacteria dynamics have utilized gnotobiotic mice inoculated with defined bacterial communities. While mouse models simulate complex interactions between microbes and their host, they also forestall the study of phage-bacteria dynamics in isolation of host factors. Here, we established a method for manipulating phage-bacteria dynamics using an in vitro chemostat bioreactor model of the distal human gut. We create defined communities representing a subset of bacteria in the feces of two human individuals, cultivated these communities in chemostat bioreactors, developed methods to purify the autochthonous viromes associated with each cultured community, and trialed a system for transmitting live or heat-killed viruses between chemostat bioreactors to decipher outcomes of virus-mediated perturbation. We found that allochthonous viromes were detectable via metagenomic sequencing against the autochthonous virome background and that shifts in bacterial community diversity and composition were detectable in relation to time posttreatment. These microbiome composition changes spanned multiple phyla, including Bacteroidetes, Firmicutes, and Actinobacteria. We also found that compositional changes occurred when using live viruses regardless of whether intrasubject or intersubject viruses were used as the perturbation agents. Our results supported the use of chemostat bioreactors as a platform for studying complex bacteria-phage dynamics in vitro. IMPORTANCE Bacteriophages are relatively ubiquitous in the environment and are highly abundant in the human microbiome. Phages can be commonly transmitted between close contacts, but the impact that such transmissions may have on their bacteria counterparts in our microbiomes is unknown. We developed a chemostat cultivation system to simulate individual-specific features of human distal gut microbiota that can be used to transmit phages between ecosystems and measure their impacts on the microbiota. We used this system to transfer phage communities between chemostats that represented different human subjects. We found that there were significant effects on overall microbiota diversity and changes in the relative abundances of Bacteroidetes, Firmicutes, and Actinobacteria, when intersubject perturbations were performed, compared to intrasubject perturbations. These changes were observed when perturbations were performed using live phages, but not when heat-killed phages were used, and they support the use of chemostat systems for studying complex human bacteria-phage dynamics.
TL;DR: In this article , the authors identify dependence on respiration for NADH reoxidation as a key contributor to unexpectedly high oxygen requirements of O. parapolymorpha, which is an attractive trait for yeast used in industrial ethanol production.
Abstract: While thermotolerance is an attractive trait for yeasts used in industrial ethanol production, oxygen requirements of known thermotolerant species are incompatible with process requirements. Analysis of oxygen-sufficient and oxygen-limited chemostat cultures of the facultatively fermentative, thermotolerant species Ogataea parapolymorpha showed its minimum oxygen requirements to be an order of magnitude larger than those reported for the thermotolerant yeast Kluyveromyces marxianus. High oxygen requirements of O. parapolymorpha coincided with a near absence of glycerol, a key NADH/NAD+ redox-cofactor-balancing product in many other yeasts, in oxygen-limited cultures. Genome analysis indicated absence of orthologs of the Saccharomyces cerevisiae glycerol-3-phosphate-phosphatase genes GPP1 and GPP2. Co-feeding of acetoin, whose conversion to 2,3-butanediol enables reoxidation of cytosolic NADH, supported a 2.5-fold increase of the biomass concentration in oxygen-limited cultures. An O. parapolymorpha strain in which key genes involved in mitochondrial reoxidation of NADH were inactivated did produce glycerol, but transcriptome analysis did not reveal a clear candidate for a responsible phosphatase. Expression of S. cerevisiae GPD2, which encodes NAD+-dependent glycerol-3-phosphate dehydrogenase, and GPP1 supported increased glycerol production by oxygen-limited chemostat cultures of O. parapolymorpha. These results identify dependence on respiration for NADH reoxidation as a key contributor to unexpectedly high oxygen requirements of O. parapolymorpha.
TL;DR: In this article , a genome-scale metabolic reconstruction of P. laurentii based on homology is presented, and the final model includes 796 genes, 2465 reactions and 2127 metabolites, and its biomass equation is based on direct measurements of all major biomass components.