Steady-state Cultures Research Articles

Microbial reaction rate estimation using proteins and proteomes.

Microbes transform their environments using diverse enzymatic reactions. However, it remains challenging to measure microbial reaction rates in natural environments. Despite advances in global quantification of enzyme abundances, the individual relationships between enzyme abundances and their reaction rates have not been systematically examined. Using matched proteomic and reaction rate data from microbial cultures, we show that enzyme abundance is often insufficient to predict its corresponding reaction rate. However, we discovered that global proteomic measurements can be used to make accurate rate predictions of individual reaction rates (median R 2 = 0.78). Accurate rate predictions required only a small number of proteins and they did not need explicit prior mechanistic knowledge or environmental context. These results indicate that proteomes are encoders of cellular reaction rates, potentially enabling proteomic measurements in situ to estimate the rates of microbially mediated reactions in natural systems.

Platform development for high-throughput optimization of perfusion processes:Part I: Implementation of cell bleeds in microwell plates.

The promise of continuous processing to increase yields and improve product quality of biopharmaceuticals while decreasing the manufacturing footprint is transformative. Developingand optimizing perfusion operations requires screening various parameters, which is expensive and time-consuming when using benchtop bioreactors. Scale-down models (SDMs) are the most feasible option for high-throughput data generation and condition screening. However, new SDMs mimicking perfusion are required, enabling experiments to be run in parallel. In this study, a method using microwell plates (MWP) operating in semi-perfusion mode with an implemented cell bleed step is presented. A CHO cell line was cultivated in a 24-well MWP (Vw = 1.2 mL) and grown at four high cell density (HCD) setpoints. Quasi steady-state condition was obtained by manually performing cell bleeds followed by a total medium exchange after centrifugation. Further, two HCD setpoints were scaled up (VW = 30 mL), comparing a squared six-well deepwell plate (DWP) to shake flasks (SF). This evaluation showed comparable results between systems (DWP vs.SF) and scales (MWP vs.DWP + SF). The results show that the well-plate-based methods are suitable to perform HCD and quasi steady-state cultivations providing a robust solution to industrially relevant challenges such as cell clone and media selection.

The γ-secretase substrate proteome and its role in cell signaling regulation

γ-Secretases mediate the regulated intramembrane proteolysis (RIP) of more than 150 integral membrane proteins. We developed an unbiased γ-secretase substrate identification (G-SECSI) method to study to what extent these proteins are processed in parallel. We demonstrate here parallel processing of at least 85 membrane proteins in human microglia in steady-state cell culture conditions. Pharmacological inhibition of γ-secretase caused substantial changes of human microglial transcriptomes, including the expression of genes related to the disease-associated microglia (DAM) response described in Alzheimer disease (AD). While the overall effects of γ-secretase deficiency on transcriptomic cell states remained limited in control conditions, exposure of mouse microglia to AD-inducing amyloid plaques strongly blocked their capacity to mount this putatively protective DAM cell state. We conclude that γ-secretase serves as a critical signaling hub integrating the effects of multiple extracellular stimuli into the overall transcriptome of the cell.

Controls on the hydrogen isotope composition of tetraether lipids in an autotrophic ammonia-oxidizing marine archaeon

The stable hydrogen isotope composition of persistent biomolecules is used as a palaeohydrological proxy. While much previous work has focused on plant leaf wax-derived n-alkanes, the potential of prokaryotic lipid biomarkers as carriers of H isotope signatures remains underexplored, particularly in the Archaea. Here we investigated H isotope distributions in the membrane lipids of the ammonia-oxidizing chemoautotroph Nitrosopumilus maritimus strain SCM1. Hydrogen isotope ratios were measured on the cleaved biphytane chains of tetraether membrane lipids extracted from steady-state continuous cultures cultivated at slow, medium, and fast growth rates. In contrast to recent work on bacterial fatty acids, where the direction and magnitude of isotopic fractionation varies widely (ca. 600‰ range) as a function of central C and energy metabolism, archaeal biphytane data in the present work are relatively invariant. The weighted average 2H/1H fractionation values relative to growth water (2εL/W) ranged from –272 to –260‰, despite a three-fold difference in doubling times (30.8–92.5 hr), yielding an average growth-rate effect <0.2‰ hr−1. These 2εL/W values are more negative than most heterotrophic microbial lipid H isotope measurements in the literature, and are on par with those from other autotrophic archaea, as well as with phytol from photoautotrophic algae. N. maritimus values of 2εL/W also varied systematically with the number of internal rings (cyclopentyl + cyclohexyl), increasing for each additional ring by 6.4 ± 2.7‰. Using an isotope flux-balance model in tandem with a comprehensive analysis of the sources of H in archaeal lipid biosynthesis, we use this observation to estimate the kinetic isotope effects (KIEs) of H incorporation from water; from reducing cofactors such as flavins and NADPH, and for the transhydrogenation reaction(s) that convert the electron-donor derived NADH into these cofactors. Consistent with prior studies on bacteria and plants, our results indicate the KIEs of reducing cofactors in archaea are highly fractionating, while those involving exchange of water protons are less so. When combined with the observation of minimal growth-rate sensitivity, our results suggest biphytanes of autotrophic 3HP/4HB utilizing Nitrososphaerota (a.k.a. Thaumarchaeota) may be offset from their growth waters by a nearly constant 2εL/W value. Together with the ring effect, this implies that all biphytanes originating from a common source should have a predictable ordering of their isotope ratios with respect to biphytane ring number, allowing precise reconstruction of the original δ2H value of the environmental water. Collectively, these patterns indicate archaeal biphytanes have potential as paleo-hydrological proxies, either as a complement or an alternative to leaf wax n-alkanes.

One‐shot 13C15N‐metabolic flux analysis for simultaneous quantification of carbon and nitrogen flux

Metabolic flux is the final output of cellular regulation and has been extensively studied for carbon but much less is known about nitrogen, which is another important building block for living organisms. For the tuberculosis pathogen, this is particularly important in informing the development of effective drugs targeting the pathogen's metabolism. Here we performed 13C15N dual isotopic labeling of Mycobacterium bovis BCG steady state cultures, quantified intracellular carbon and nitrogen fluxes and inferred reaction bidirectionalities. This was achieved by model scope extension and refinement, implemented in a multi‐atom transition model, within the statistical framework of Bayesian model averaging (BMA). Using BMA‐based 13C15N‐metabolic flux analysis, we jointly resolve carbon and nitrogen fluxes quantitatively. We provide the first nitrogen flux distributions for amino acid and nucleotide biosynthesis in mycobacteria and establish glutamate as the central node for nitrogen metabolism. We improved resolution of the notoriously elusive anaplerotic node in central carbon metabolism and revealed possible operation modes. Our study provides a powerful and statistically rigorous platform to simultaneously infer carbon and nitrogen metabolism in any biological system.

Bioinformatics and metabolic flux analysis highlight a new mechanism involved in lactate oxidation in Clostridium tyrobutyricum

Climate change and environmental issues compel us to find alternatives to the production of molecules of interest from petrochemistry. This study aims at understanding the production of butyrate, hydrogen, and CO2 from the oxidation of lactate with acetate in Clostridium tyrobutyricum and thus proposes an alternative carbon source to glucose. This specie is known to produce more butyrate than the other butyrate-producing clostridia species due to a lack of solvent genesis phase. The recent discoveries on flavin-based electron bifurcation and confurcation mechanism as a mode of energy conservation led us to suggest a new metabolic scheme for the formation of butyrate from lactate-acetate co-metabolism. While searching for genes encoding for EtfAB complexes and neighboring genes in the genome of C. tyrobutyricum, we identified a cluster of genes involved in butyrate formation and another cluster involved in lactate oxidation homologous to Acetobacterium woodii. A phylogenetic approach encompassing other butyrate-producing and/or lactate-oxidizing species based on EtfAB complexes confirmed these results. A metabolic scheme on the production of butyrate, hydrogen, and CO2 from the lactate-acetate co-metabolism in C. tyrobutyricum was constructed and then confirmed with data of steady-state continuous culture. This in silico metabolic carbon flux analysis model showed the coherence of the scheme from the carbon recovery, the cofactor ratio, and the ATP yield. This study improves our understanding of the lactate oxidation metabolic pathways and the role of acetate and intracellular redox balance, and paves the way for the production of molecules of interest as butyrate and hydrogen with C. tyrobutyricum.

Organizational dynamics: culture, design, and performance

Abstract We examine the two-way interplay between organizational cultures and organizational design, where culture is modeled as the prevailing social identities among workplace groups that can affect project choices. In a setting where cultural dynamics depend on the expected relative payoffs of holding different identities, we investigate how tribalism and charismatic leadership shape organizational dynamics and steady-state cultures. We show how a strong culture can be a virtue when it permits greater delegated authority, but a vice when the culture is poorly aligned with organizational objectives. We apply our analysis to concrete debates about the interaction of design, performance, and culture (JEL L23, M14).

Combination of Genome-Scale Models and Bioreactor Dynamics to Optimize the Production of Commodity Chemicals.

The current production of a number of commodity chemicals relies on the exploitation of fossil fuels and hence has an irreversible impact on the environment. Biotechnological processes offer an attractive alternative by enabling the manufacturing of chemicals by genetically modified microorganisms. However, this alternative approach poses some important technical challenges that must be tackled to make it competitive. On the one hand, the design of biotechnological processes is based on trial-and-error approaches, which are not only costly in terms of time and money, but also result in suboptimal designs. On the other hand, the manufacturing of chemicals by biological processes is almost exclusively carried out by batch or fed-batch cultures. Given that batch cultures are expensive and not easy to scale, technical means must be developed to make continuous cultures feasible and efficient. In order to address these challenges, we have developed a mathematical model able to integrate in a single model both the genome-scale metabolic model for the organism synthesizing the chemical of interest and the dynamics of the bioreactor in which the organism is cultured. Such a model is based on the use of Flexible Nets, a modeling formalism for dynamical systems. The integration of a microscopic (organism) and a macroscopic (bioreactor) model in a single net provides an overall view of the whole system and opens the door to global optimizations. As a case study, the production of citramalate with respect to the substrate consumed by E. coli is modeled, simulated and optimized in order to find the maximum productivity in a steady-state continuous culture. The predicted computational results were consistent with the wet lab experiments.

Monitoring of amino acids and antibody N-glycosylation in high cell density perfusion culture based on Raman spectroscopy

Raman spectrum based predictive models provide a process analytical technology (PAT) tool for monitoring and control of culture parameters in bioprocesses. Steady-state perfusion cultures generate a relatively stable metabolite profile, which is not conducive to modeling due to the absence of variations of culture parameters. Here we present an approach where different steady-states obtained by variation of the cell specific perfusion rate (CSPR) between 10 and 40 pL/(cell * day) with cell densities up to 100 × 106 cells/mL during the process development provided a dynamic culture environment, favorable for the model calibration. The cell density had no effect on the culture performance at similar CSPR, however a variation in the CSPR had a strong influence on the metabolism, mAb productivity and N-glycosylation. Predictive models were developed for multiple culture parameters, including cell density, lactate, ammonium and amino acids; and then validated with new runs performed at multiple or single steady-states, showing high prediction accuracy. The relationship of amino acids and antibody N-glycosylation was modeled to predict the glycosylation pattern of the product in real time. The present efficient process development approach with integration of Raman spectroscopy provides a valuable PAT tool for later implementation in steady-state perfusion production processes.

Production of extracellular α-amylase by single-stage steady-state continuous cultures of Candida wangnamkhiaoensis in an airlift bioreactor.

The kinetics of growth and α-amylase production of a novel Candida wangnamkhiaoensis yeast strain were studied in single-stage steady-state continuous cultures. This was performed in a split-cylinder internal-loop airlift bioreactor, using a variety of carbon sources as fermentation substrates. Results showed that the steady-state yields of cell mass from carbohydrates were practically constant for the range of dilution rates assayed, equaling 0.535 ± 0.030, 0.456 ± 0.033, and 0.491 ± 0.035 g biomass/g carbohydrate, when glucose, maltose, and starch, respectively were used as carbon sources. No α-amylase activity was detected when glucose was used as the carbon source in the influent medium, indicating that α-amylase synthesis of C. wangnamkhiaoensis is catabolically repressed by glucose. Contrastingly, maltose and starch induce synthesis of α-amylase in C. wangnamkhiaoensis, with starch being the best α-amylase inducer. The highest α-amylase volumetric and specific activities (58400 ± 800 U/L and 16900 ± 200 U/g biomass, respectively), and productivities (14000 ± 200 U/L·h and 4050 ± 60 U/g biomass·h, respectively) were achieved at a dilution rate of 0.24 h-1 using starch as the carbon source. In conclusion, single-stage steady-state continuous culture in an airlift bioreactor represents a powerful tool, both for studying the regulatory mechanisms of α-amylase synthesis by C. wangnamkhiaoensis and for α-amylase production. Furthermore, results showed that C. wangnamkhiaoensis represents a potential yeast species for the biotechnological production of α-amylase, which can be used for the saccharification of starch. This offers an attractive renewable resource for the production of biofuels (particularly bioethanol), representing an alternative to fossil fuels with reduced cost of substrates.

Cell Length Growth in the Fission Yeast Cell Cycle: Is It (Bi)linear or (Bi)exponential?

Fission yeast is commonly used as a model organism in eukaryotic cell growth studies. To describe the cells’ length growth patterns during the mitotic cycle, different models have been proposed previously as linear, exponential, bilinear and biexponential ones. The task of discriminating among these patterns is still challenging. Here, we have analyzed 298 individual cells altogether, namely from three different steady-state cultures (wild-type, wee1-50 mutant and pom1Δ mutant). We have concluded that in 190 cases (63.8%) the bilinear model was more adequate than either the linear or the exponential ones. These 190 cells were further examined by separately analyzing the linear segments of the best fitted bilinear models. Linear and exponential functions have been fitted to these growth segments to determine whether the previously fitted bilinear functions were really correct. The majority of these growth segments were found to be linear; nonetheless, a significant number of exponential ones were also detected. However, exponential ones occurred mainly in cases of rather short segments (&lt;40 min), where there were not enough data for an accurate model fitting. By contrast, in long enough growth segments (≥40 min), linear patterns highly dominated over exponential ones, verifying that overall growth is probably bilinear.

Global transcriptome profiling reveals genes responding to overproduction of a small secretory, a high cysteine- and a high glycosylation-bearing protein in Yarrowia lipolytica

Investigation of the yeast cell’s response to recombinant secretory protein (rs-Prot) overproduction is relevant for both basic and applied research. Imbalance, overloading or stress within this process impacts the whole cell. In the present study, by using steady-state cultures and transcriptomics, we investigated the cellular response of Yarrowia lipolytica challenged with high-level expression of genes encoding proteins with significantly different biochemical characteristics: a small protein retained within the cell i) or secreted ii), a medium size secretory protein with a high number of disulfide bonds iii), or glycosylation sites iv). Extensive analysis of omics data, supported by careful manual curation, led to some anticipated observations on oxidative and unfolded protein stress (CTT1, PXMP2/4, HAC1), glycosylation (ALGs, KTRs, MNTs, MNNs), folding and translocation (SSAs, SSEs) but also generated new exciting knowledge on non-conventional protein secretion (NCE102), transcriptional regulators (FLO11, MHY1, D01353 g, RSFA, E23925g or MAF1), vacuolar proteolysis targets in Y. lipolytica (ATGs, VPSs, HSE1, PRB1, PRC1, PEP4) or growth arrest (CLN1) upon rs-Prots overproduction.

Quantifying absolute gene expression profiles reveals distinct regulation of central carbon metabolism genes in yeast.

In addition to controlled expression of genes by specific regulatory circuits, the abundance of proteins and transcripts can also be influenced by physiological states of the cell such as growth rate and metabolism. Here we examine the control of gene expression by growth rate and metabolism, by analyzing a multi-omics dataset consisting of absolute-quantitative abundances of the transcriptome, proteome, and amino acids in 22 steady-state yeast cultures. We find that transcription and translation are coordinately controlled by the cell growth rate via RNA polymerase II and ribosome abundance, but they are independently controlled by nitrogen metabolism via amino acid and nucleotide availabilities. Genes in central carbon metabolism, however, are distinctly regulated and do not respond to the cell growth rate or nitrogen metabolism as all other genes. Understanding these effects allows the confounding factors of growth rate and metabolism to be accounted for in gene expression profiling studies.

High-throughput optofluidic screening for improved microbial cell factories via real-time micron-scale productivity monitoring.

The industrial synthetic biology sector has made huge investments to achieve relevant miniaturized screening systems for scalable fermentation. Here we present the first example of a high-throughput (>103 genotypes per week) perfusion-based screening system to improve small-molecule secretion from microbial strains. Using the Berkeley Lights Beacon® system, the productivity of each strain could be directly monitored in real time during continuous culture, yielding phenotypes that correlated strongly (r2 > 0.8, p < 0.0005) with behavior in industrially relevant bioreactor processes. This method allows a much closer approximation of a typical fed-batch fermentation than conventional batch-like droplet or microplate culture models, in addition to rich time-dependent data on growth and productivity. We demonstrate these advantages by application to the improvement of high-productivity strains using whole-genome random mutagenesis, yielding mutants with substantially improved (by up to 85%) peak specific productivities in bioreactors. Each screen of ∼5 × 103 mutants could be completed in under 8 days (including 5 days involving user intervention), saving ∼50-75% of the time required for conventional microplate-based screening methods.

Strongly oversized fission yeast cells lack any size control and tend to grow linearly rather than bilinearly.

During the mitotic cycle, the rod-shaped fission yeast cells grow only at their tips. The newly born cells grow first unipolarly at their old end, but later in the cycle, the 'new end take-off' event occurs, resulting in bipolar growth. Photographs were taken of several steady-state and induction synchronous cultures of different cell cycle mutants of fission yeast, generally larger than wild type. Length measurements of many individual cells were performed from birth to division. For all the measured growth patterns, three different functions (linear, bilinear and exponential) were fitted, and the most adequate one was chosen by using specific statistical criteria, considering the altering parameter numbers. Although the growth patterns were heterogeneous in all the cultures studied, we could find some tendencies. In cultures with sufficiently wide size distribution, cells large enough at birth tend to grow linearly, whereas the other cells generally tend to grow bilinearly. We have found that among bilinearly growing cells, the larger they are at birth, the rate change point during their bilinear pattern occurs earlier in the cycle. This shifting near to the beginning of the cycle might finally cause a linear pattern, if the cells are even larger. In all of the steady-state cultures studied, a size control mechanism operates to maintain homeostasis. By contrast, strongly oversized cells of induction synchronous cultures lack any sizer, and their cycle rather behaves like an adder. We could determine the critical cell size for both the G1 and G2 size controls, where these mechanisms become cryptic. TAKE AWAY: Most individual fission yeast cells in steady-state cultures grow bilinearly. In strongly oversized fission yeast cells, linear growth dominates over bilinear. Above birth length thresholds, both the G1 and G2 size controls become cryptic.

Prediction of maximum algal productivity in membrane bioreactors with a light-dependent growth model

Algal productivity in steady-state cultivation systems depends on important factors such as biomass concentration, solids retention time (SRT), and light intensity. Current modeling of algal growth often ignores light distribution in algal cultivation systems and does not consider all these factors simultaneously. We developed a new algal growth model using a first principles approach to incorporate the effect of light intensity on algal growth while simultaneously considering biomass concentration and SRT. We first measured light attenuation (decay) with depth in an indoor algal membrane bioreactor (A-MBR) cultivating Chlorella sp. We then simulated the light decay using a multi-layer approach and correlated the decay with biomass concentration and SRT in model development. The model was calibrated by delineating specific light absorptivity and half-saturation constant to match the algal biomass concentration in the A-MBR operated at a target SRT. We finally applied the model to predict the maximum algal productivity in both indoor and outdoor A-MBRs. The predicted maximum algal productivities in indoor and outdoor A-MBRs were 6.7 g·m−2·d−1 (incident light intensity 5732 lx, SRT approximately 8 d) and 28 g·m−2·d−1 (sunlight intensity 28,660 lx, SRT approximately 4 d), respectively. The model can be extended to include other factors (e.g., water temperature and carbon dioxide bubbling) and such a modeling framework can be applied to full-scale, continuous flow outdoor systems to improve algal productivity.

Exponential trajectories, cell size fluctuations, and the adder property in bacteria follow from simple chemical dynamics and division control.

Experiments on steady-state bacterial cultures have uncovered several quantitative regularities at the system level. These include, first, the exponential growth of cell size with time and the balanced growth of intracellular chemicals between cell birth and division, which are puzzling given the nonlinear and decentralized chemical dynamics in the cell. We model a cell as a set of chemical populations undergoing nonlinear mass action kinetics in a container whose volume is a linear function of the chemical populations. This turns out to be a special class of dynamical systems that generically has attractors in which all populations grow exponentially with time at the same rate. This explains exponential balanced growth of bacterial cells without invoking any regulatory mechanisms and suggests that this could be a robust property of protocells as well. Second, we consider the hypothesis that cells commit themselves to division when a certain internal chemical population reaches a threshold of N molecules. We show that this hypothesis leads to a simple explanation of some of the variability observed across cells in a bacterial culture. In particular, it reproduces the adder property of cell size fluctuations observed recently in E. coli; the observed correlations among interdivision time, birth volume, and added volume in a generation; and the observed scale of the fluctuations (CV ≈ 10-30%) when N is between 10 and 100. Third, upon including a suitable regulatory mechanism that optimizes the growth rate of the cell, the model reproduces the observed bacterial growth laws including the dependence of the growth rate and ribosomal protein fraction on the medium. Thus, the models provide a framework for unifying diverse aspects of bacterial growth physiology under one roof. They also suggest new questions for experimental and theoretical enquiry.

Nitrogen limitation reveals large reserves in metabolic and translational capacities of yeast

Cells maintain reserves in their metabolic and translational capacities as a strategy to quickly respond to changing environments. Here we quantify these reserves by stepwise reducing nitrogen availability in yeast steady-state chemostat cultures, imposing severe restrictions on total cellular protein and transcript content. Combining multi-omics analysis with metabolic modeling, we find that seven metabolic superpathways maintain >50% metabolic capacity in reserve, with glucose metabolism maintaining >80% reserve capacity. Cells maintain >50% reserve in translational capacity for 2490 out of 3361 expressed genes (74%), with a disproportionately large reserve dedicated to translating metabolic proteins. Finally, ribosome reserves contain up to 30% sub-stoichiometric ribosomal proteins, with activation of reserve translational capacity associated with selective upregulation of 17 ribosomal proteins. Together, our dataset provides a quantitative link between yeast physiology and cellular economics, which could be leveraged in future cell engineering through targeted proteome streamlining.

The Impact of Global Transcriptional Regulation on Bacterial Gene Order.

SummaryBacterial gene expression depends on the allocation of limited transcriptional resources provided a particular growth rate and growth condition. Early studies in a few genes suggested this global regulation to generate a unifying hyperbolic expression pattern. Here, we developed a large-scale method that generalizes these experiments to quantify the response to growth of over 700 genes that a priori do not exhibit any specific control. We distinguish a core subset following a promoter-specific hyperbolic response. Within this group, we sort genes with regard to their responsiveness to the global regulatory program to show that those with a particularly sensitive linear response are located near the origin of replication. We then find evidence that this genomic architecture is biologically significant by examining position conservation of E. coli genes in 100 bacteria. The response to the transcriptional resources of the cell results in an additional feature contributing to bacterial genome organization.

Gradual adaptation of facultative anaerobic pathogens to microaerobic and anaerobic conditions.

Many notable human pathogens are facultative anaerobes. These pathogens exhibit redundant metabolic pathways and a whole array of regulatory systems to adapt to changing oxygen levels. However, our knowledge of facultative anaerobic pathogens is mostly based on fully aerobic or anaerobic cultures, which does not reflect real infection conditions, while the microaerobic range remains understudied. Here, we examine the behavior of pathogenic and nonpathogenic strains of two facultative anaerobes, Escherichia coli and Pseudomonas aeruginosa, during the aerobic-anaerobic transition. To do so, we introduce a new technique named AnaeroTrans, in which we allow self-consumption of oxygen by steady-state cultures and monitor the system by measuring the gas-phase oxygen concentration. We explore the different behavior of the studied species toward oxygen and examine how this behavior is associated with the targeted infection sites. As a model, we characterize the adaptation profile of the ribonucleotide reductase network, a complex oxygen-dependent enzymatic system responsible for the generation of the deoxyribonucleotides. We also explore the actions of the most important anaerobic regulators and how these regulators influence bacterial fitness. Our results allow us to classify the different elements that compose the aerobic-anaerobic transition into reproducible stages, thus showing the different adaptation mechanisms of the studied species.