Morphological growth pattern of Phanerochaete chrysosporium cultivated on different Miscanthus x giganteus biomass fractions.

BACKGROUND: Solid-state fermentation is a fungal culture technique used to produce compounds and products of industrial interest. The growth behaviour of filamentous fungi on solid media is challenging to study due to the intermixity of the substrate and the growing organism. Several strategies are available to measure indirectly the fungal biomass during the fermentation such as following the biochemical production of mycelium-specific components or microscopic observation. The microscopic observation of the development of the mycelium, on lignocellulosic substrate, has not been reported. In this study, we set up an experimental protocol based on microscopy and image processing through which we investigated the growth pattern of Phanerochaete chrysosporium on different Miscanthus x giganteus biomass fractions. RESULTS: Object coalescence, the occupied surface area, and radial expansion of the colony were measured in time. The substrate was sterilized by autoclaving, which could be considered a type of pre-treatment. The fastest growth rate was measured on the unfractionated biomass, followed by the soluble fraction of the biomass, then the residual solid fractions. The growth rate on the different fractions of the substrate was additive, suggesting that both the solid and soluble fractions were used by the fungus. Based on the FTIR analysis, there were differences in composition between the solid and soluble fractions of the substrate, but the main components for growth were always present. We propose using this novel method for measuring the very initial fungal growth by following the variation of the number of objects over time. Once growth is established, the growth can be followed by measurement of the occupied surface by the mycelium. CONCLUSION: Our data showed that the growth was affected from the very beginning by the nature of the substrate. The most extensive colonization of the surface was observed with the unfractionated substrate containing both soluble and solid components. The methodology was practical and may be applied to investigate the growth of other fungi, including the influence of environmental parameters on the fungal growth.

Shear stress computation in a millimeter thin flat panel photobioreactor: Numerical design validated by experiments.

Flat panels are the most spread type of photobioreactors for studying light effects on a microalgae culture. Their low thickness, usually between 1 and 3 cm, aims at ensuring light homogeneity across the culture. Yet because optical density has to remain very low, studies are still limited to low cell density cultures. To alleviate this problem, even thinner photobioreactors can be designed. Nevertheless, thin flat panel reactors are very prone to induce high shear stress. This work aimed at designing a new millimeter thin panel photobioreactor to study light effects on Chlorella and Scenedesmus genera. We proposed a numerical workflow that is capable of assessing the shear stress intensity in such a reactor. The numerical predictions were validated at three different levels: 2D preliminary simulations were able to reproduce bubble commonly known behaviors; close to the nozzle, the predictions were successfully confronted to shadowgraphy experimental reference; at the mini bioreactor scale, experimental and numerical mixing were found to be close. After these throughout validations, shear stress intensity in the photobioreactor was calculated over 1000 Lagrangian tracers. The experienced shear stress was agglomerated at the population level. From the computed shear stress, it was possible to choose the minimal reactor thickness that would not hinder cell growth.

A predictive dynamic yeast model based on component, energy, and electron carrier balances.

The present study describes a novel yeast model for the prediction of yeast fermentation. The proposed model considers the possible metabolic pathways of yeast. For each pathway, the time evolution of components, energy (ATP/ADP), and electron carriers (NAD+ /NADH) are expressed with limitation factors for all quantities consumed by each respective pathway. In this manner, the model can predict the partition of these pathways based on the growth conditions and their evolution over time. Several biological pathways and their stoichiometric coefficients are well known from literature. It is important to note that most of the kinetic parameters have no effect as the actual kinetics are controlled by the balance of limiting factors. The few remaining parameters were adjusted and compared with the literature when the data set was available. The model fits our experimental data from yeast fermentation on glucose in a nonaerated batch system. The predictive ability of the model and its capacity to represent the intensity of each pathway over time facilitate an improved understanding of the interactions between the pathways. The key role of energy (ATP) and electron carrier (NAD+ ) to trigger the different metabolic pathways during yeast growth is highlighted, whereas the involvement of mitochondrial respiration not being associated with the TCA cycle is also shown.

Multiscale numerical workflow describing microalgae motion and light pattern incidence towards population growth in a photobioreactor.

In this article, a numerical workflow describing the microalgal growth inside of a photobioreactor is proposed. CFD is used to compute reactor internal hydrodynamics taking into account marine impeller rotation and sparged bubbles motion. Lagrangian approach is used to track microalgae motion inside of the culture vessel. The illumination across the reactor is obtained using the classical Beer-Lambert's law. The combination of light field and cell motion allows to reconstruct the light history of each microalgae. These histories are then supplied to Han's model which predicts individual growth rate and experienced photodamages. Once computed, several thousands of trajectories are agglomerated at the population level yielding the photobioreactor performances. After having ensured properties convergence, this procedure is applied to a large range of optical density (0 to 4.0), i.e. cell concentration, and incident light intensities (0 to 2000 µmolPhoton/m2/s). From this exploration, it is possible to determine the photobioreactor response surfaces in terms of growth rate and photodamages. These are latter used to propose an optimal lighting strategy for biomass production - reducing photobioreactor operation time by 16% compared to classical two-step procedure - and assist light induced stress with the aim of triggering secondary metabolites production.

Effect of increasing oxygen partial pressure on Saccharomyces cerevisiae growth and antioxidant and enzyme productions.

This study investigated the impact of oxygen partial pressure on yeast growth. Saccharomyces cerevisiae cells were exposed to various hyperbaric air conditions from 1 bar to 9 bar absolute pressure (A). Batch cultures were grown under continuous airflow in a 750 mL (500 mL culture) bioreactor and monitored through growth rate and specific yields of ethanol and glycerol. In addition, the concentrations of antioxidant metabolites glutathione (reduced state, GSH and oxidized state, GSSG) and the activity of antioxidative enzymes superoxide dismutases (SOD) and catalases (CAT) were monitored. The results demonstrated that the different oxygen partial pressures significantly impacted the key growth parameters monitored. Compared with atmospheric pressure, under 2 to 5 bar (A), yeast cells showed higher growth rates (µ = 0.32 ± 0.01 h-1) and higher catalase (CAT) concentrations (214 ± 5 mU/g). GSH/GSSG ratio (6.36 ± 0.37) maintained until 6 bar (A) and total SOD (240 ± 5 mU/g) level significantly increased compared with 2 bar (A) until 7 bar (A). Under 6 to 9 bar (A), cell growth was inhibited, and a pressure of 9 bar (A) led to excessive GSSG accumulation (GSH/GSSG = 0.31 ± 0.06). The inhibition of t-SOD (160 ± 3 mU/g) and CAT (62.73 ± 0.2 mU/g) was observed under 9 bar (A). A reference experiment (8 bar (A) N2 + 1 bar (A) air) confirmed that the observed behaviors were entirely due to O2. In addition to their utility in biotechnological process design, these results showed that growth impairment was solely due to oxidative stress induced by excessive oxygen pressure. KEY POINTS: • Yeast cells were grown in batch mode under 1 to 9 bar (A) air pressures and up to 5 bar (A) promoted then hindered growth. • The GSH/GSSG ratio was stable up to 5 bar (A) then GSSG accumulated to excess. • Complementary investigations of the activity of SOD and CAT validated growth limitations due to oxidative stress.

A 3-variable PDE model for predicting fungal growth derived from microscopic mechanisms.

In this work, we present a new PDE model of the growth of Postia placenta, a species of brown rot fungus. The formulation was derived mainly from the biological mechanisms embedded in our discrete model, validated against experimental data. In order to mimic the growth mechanisms, we propose a new reaction-diffusion formulation, based on three variables: the concentration of tips, the branch density and the total hyphal density. The evolution of tips obeys a reaction-diffusion model, with constant diffusivity, while the evolution of the two other variables results from time integrals. The numerical solution is in excellent agreement with the averaged radial tip/hyphal densities of the mycelial network obtained by the discrete model. Thanks to the efficient exponential Euler method with Krylov subspace approximation, the solution needs only 3.5 s of CPU time to simulate 104-day of mycelium growth, in comparison with 8 hours for the discrete model. The great reduction of the RAM memory and computing time gives the possibility to upscale the simulation. The novelty of the PDE system is that the spatial colonization is formulated as a diffusion mechanism, which is self-standing, contrary to models based on an advection term. The continuous model can also reproduce the radial densities when the growth parameters in the discrete model are varied to adapt to different growth conditions. The correlation constructed between the two models provides us a tool for mutual insights between local biological mechanisms to the global biomass distribution, especially when analyzing experimental data.

Process for symbiotic culture of Saccharomyces cerevisiae and Chlorella vulgaris for in situ CO2 mitigation.

Industrial biotechnology relies heavily on fermentation processes that release considerable amounts of CO2. Apart from the fact that this CO2 represents a considerable part of the organic substrate, it has a negative impact on the environment. Microalgae cultures have been suggested as potential means of capturing the CO2 with further applications in high-value compounds production or directly for feed applications. We developed a sustainable process based on a mixed co-dominant culture of Saccharomyces cerevisiae and Chlorella vulgaris where the CO2 production and utilization controlled the microbial ecology of the culture. By mixing yeast and microalga in the same culture, the CO2 is produced in dissolved form and is available to the microalga avoiding degassing and dissolution phenomena. With this process, the CO2 production and utilization rates were balanced and a mutual symbiosis between the yeast and the microalga was set up in the culture. In this study, the reutilization of CO2 and growth of C. vulgaris was demonstrated. The two organism populations were balanced at approximately 20 × 106 cells ml-1 and almost all the CO2 produced by yeast was reutilized by microalga within 168 h of culture. The C. vulgaris inoculum preparation played a key role in establishing co-dominance of the two organisms. Other key factors in establishing symbiosis were the inoculum ratio of the two organisms and the growth medium design. A new method allowed the independent enumeration of each organism in a mixed culture. This study could provide a basis for the development of green processes of low environmental impact.

Han's model parameters for microalgae grown under intermittent illumination: Determined using particle swarm optimization.

This work provides a model and the associated set of parameters allowing for microalgae population growth computation under intermittent lightning. Han's model is coupled with a simple microalgae growth model to yield a relationship between illumination and population growth. The model parameters were obtained by fitting a dataset available in literature using Particle Swarm Optimization method. In their work, authors grew microalgae in excess of nutrients under flashing conditions. Light/dark cycles used for these experimentations are quite close to those found in photobioreactor, i.e. ranging from several seconds to one minute. In this work, in addition to producing the set of parameters, Particle Swarm Optimization robustness was assessed. To do so, two different swarm initialization techniques were used, i.e. uniform and random distribution throughout the search-space. Both yielded the same results. In addition, swarm distribution analysis reveals that the swarm converges to a unique minimum. Thus, the produced set of parameters can be trustfully used to link light intensity to population growth rate. Furthermore, the set is capable to describe photodamages effects on population growth. Hence, accounting for light overexposure effect on algal growth.

Building blocks needed for mechanistic modeling of bioprocesses: A critical review based on protein production by CHO cells.

This paper reviews the key building blocks needed to develop a mechanistic model for use as an operational production tool. The Chinese Hamster Ovary (CHO) cell, one of the most widely used hosts for antibody production in the pharmaceutical industry, is considered as a case study. CHO cell metabolism is characterized by two main phases, exponential growth followed by a stationary phase with strong protein production. This process presents an appropriate degree of complexity to outline the modeling strategy. The paper is organized into four main steps: (1) CHO systems and data collection; (2) metabolic analysis; (3) formulation of the mathematical model; and finally, (4) numerical solution, calibration, and validation. The overall approach can build a predictive model of target variables. According to the literature, one of the main current modeling challenges lies in understanding and predicting the spontaneous metabolic shift. Possible candidates for the trigger of the metabolic shift include the concentration of lactate and carbon dioxide. In our opinion, ammonium, which is also an inhibiting product, should be further investigated. Finally, the expected progress in the emerging field of hybrid modeling, which combines the best of mechanistic modeling and machine learning, is presented as a fascinating breakthrough. Note that the modeling strategy discussed here is a general framework that can be applied to any bioprocess.

The effect of light intensity on microalgae biofilm structures and physiology under continuous illumination.

The interest by biofilm-based microalgae technologies has increased lately due to productivity improvement, energy consumption reduction and easy harvesting. However, the effect of light, one key factor for system's operation, received less attention than for planktonic cultures. This work assessed the impact of Photon Flux Density (PFD) on Chlorella vulgaris biofilm dynamics (structure, physiology, activity). Microalgae biofilms were cultivated in a flow-cell system with PFD from 100 to 500 [Formula: see text]. In the first stage of biofilm development, uniform cell distribution was observed on the substratum exposed to 100 [Formula: see text] while cell clusters were formed under 500 [Formula: see text]. Though similar specific growth rate in exponential phase (ca. 0.3 [Formula: see text]) was obtained under all light intensities, biofilm cells at 500 [Formula: see text] seem to be ultimately photoinhibited (lower final cell density). Data confirm that Chlorella vulgaris showed a remarkable capability to cope with high light. This was marked for sessile cells at 300 [Formula: see text], which reduce very rapidly (in 2 days) their chlorophyll-a content, most probably to reduce photodamage, while maintaining a high final cell density. Besides cellular physiological adjustments, our data demonstrate that cellular spatial organization is light-dependent.

Water vapor transport properties of bio-based multilayer materials determined by original and complementary methods.

To enhance PLA gas barrier properties, multilayer designs with highly polar barrier layers, such as nanocelluloses, have shown promising results. However, the properties of these polar layers change with humidity. As a result, we investigated water transport phenomena in PLA films coated with nanometric layers of chitosan and nanocelluloses, utilizing a combination of techniques including dynamic vapor sorption (DVS) and long-term water vapor adsorption-diffusion experiments (back-face measurements) to understand the influence of each layer on the behavior of multilayer films. Surprisingly, nanometric coatings impacted PLA water vapor transport. Chitosan/nanocelluloses layers, representing less than 1 wt.% of the multilayer film, increased the water vapor uptake of the film by 14.6%. The nanometric chitosan coating appeared to have localized effects on PLA structure. Moreover, nanocelluloses coatings displayed varying impacts on sample properties depending on their interactions (hydrogen, ionic bonds) with chitosan. The negatively charged CNF TEMPO coating formed a dense network that demonstrated higher resistance to water sorption and diffusion compared to CNF and CNC coatings. This work also highlights the limitations of conventional water vapor permeability measurements, especially when dealing with materials containing ultrathin nanocelluloses layers. It shows the necessity of considering the synergistic effects between layers to accurately evaluate the transport properties.

A Novel Strategy to Enhance Antioxidant Content in Saccharomyces Cerevisiae Based on Oxygen Pressure.

Antioxidant foods represent a potent lever to improve diets while creating value. Yet, their cultivation is often tied to a specific area and climate, limiting availability and increasing market cost. Therefore, microorganism-based antioxidant production emerges as a promising technology to solve these problems. In this view, a novel process was investigated for antioxidant accumulation in yeast culture. S. cerevisiae cells were exposed to various hyperbaric air conditions from 1 to 9 bar (A). Yeast cultures exhibited an increased reactive oxygen species content, which induced oxidative defense expression. After a few hours, reactive oxygen species levels decreased while antioxidant contents remained high, leading to a net increase in antioxidant power. At 6 bar (A), yeast achieved the highest net antioxidant power (phenolics content +48.3 ± 18.6 %, reducing power +120 ± 11.4 %) with an acceptable growth rate (0.27 h-1). Regarding time evolution, a 2 h exposure seems to be the optimum: cells have the lowest reactive oxygen species level while their antioxidant power is increased. From a biotechnological perspective, this finding highlights air pressure as an antioxidant-manipulating stress strategy. Moreover, the proposed process led to a patent that could potentially reduce energy and chemical consumption in such antioxidant accumulation processes.

Principal factors affecting the yield of dilute acid pretreatment of lignocellulosic biomass: A critical review.

This review provides a critical analysis of the state of the art of dilute acid pretreatment applied to lignocellulosic biomass. Data from 63 publications were extracted and analysed. The majority of the papers used residence times of<30 min, temperature ranges from 100 °C to 200 °C, and acid levels between 0 % and 2 %. Yields are quantified directly after pretreatment (xylose content) or after enzymatic hydrolysis (glucose content). Statistical analyses allowed the time-temperature equivalence to be quantified for three types of biomass: they were formulated by non-linear expressions. In further works, investigating less explored areas, for example moderate temperature levels with longer residence times, is recommended. Pretreatment material (time-temperature kinetics, reactor type) and analytical methods should be standardized and better described. It becomes mandatory to promote the development of an open, findable, accessible, interoperable, and reusable data approach for pretreatments research.

The impact of light/dark regimes on structure and physiology of Chlorella vulgaris biofilms.

Introduction: Biofilm-based microalgae production technologies offer enormous potential for improving sustainability and productivity. However, the light pattern induced by these technologies is a key concern for optimization. Methods: In this work, the effects of light/dark cycles on architecture, growth, and physiology of Chlorella vulgaris biofilms were assessed in a millifluidic flow-cell with different time cycles (15 s to 3 min) keeping the average light constant at 100 µmol·m-2·s-1. Results and discussion: Results showed that photoinhibition can be mitigated by applying a light fraction of 1/3 and a cycle time of 15 s. By contrast, when the cycle time is extended to 90 s and 3 min, photoinhibition is high and photoefficiency dramatically decreases. To cope with light stress, cells acclimate and organize themselves differently in space. A high peak light (500 µmol·m-2·s-1) triggers a stress, reducing cell division and inducing clusters in the biofilm. This work provides guidelines for optimizing rotating microalgae production systems in biofilms and assesses the minimum rotating frequency required to maintain the net growth rate close to that of continuous light of the same average intensity, mitigating photo-inhibition. The overall gain in productivity is then provided by the total surface of the biofilm turning in the illuminated surface area.

Improvement of Sinapine Extraction from Mustard Seed Meal by Application of Emerging Technologies.

Sinapine is a phenolic compound found in mustard (Brassica juncea) seed meal. It has numerous beneficial properties such as antitumor, neuroprotective, antioxidant, and hepatoprotective effects, making its extraction relevant. In this study, the extraction of sinapine was investigated using three methods: (i) from a mustard seed meal defatted by a supercritical CO2 (SC-CO2) pretreatment, (ii) by the implementation of high-voltage electrical discharges (HVEDs), (iii) and by the use of ultrasound. The use of SC-CO2 pretreatment resulted in a dual effect on the valorization of mustard seed meal, acting as a green solvent for oil recovery and increasing the yield of extracted sinapine by 24.4% compared to the control. The combination of ultrasound and SC-CO2 pretreatment further increased the yield of sinapine by 32%. The optimal conditions for ultrasound-assisted extraction, determined through a response surface methodology, are a temperature of 75 °C, 70% ethanol, and 100% ultrasound amplitude, resulting in a sinapine yield of 6.90 ± 0.03 mg/g dry matter. In contrast, the application of HVEDs in the extraction process was not optimized, as it led to the degradation of sinapine even at low-energy inputs.

Elevated CO2 and/or ozone modify lignification in the wood of poplars (Populus tremula x alba).

Trees will have to cope with increasing levels of CO(2) and ozone in the atmosphere. The purpose of this work was to assess whether the lignification process could be altered in the wood of poplars under elevated CO(2) and/or ozone. Young poplars were exposed either to charcoal-filtered air (control), to elevated CO(2) (800 µl l(-1)), to ozone (200 nl l(-1)) or to a combination of elevated CO(2) and ozone in controlled chambers. Lignification was analysed at different levels: biosynthesis pathway activities (enzyme and transcript), lignin content, and capacity to incorporate new assimilates by using (13)C labelling. Elevated CO(2) and ozone had opposite effects on many parameters (growth, biomass, cambial activity, wood cell wall thickness) except on lignin content which was increased by elevated CO(2) and/or ozone. However, this increased lignification was due to different response mechanisms. Under elevated CO(2), carbon supply to the stem and effective lignin synthesis were enhanced, leading to increased lignin content, although there was a reduction in the level of some enzyme and transcript involved in the lignin pathway. Ozone treatment induced a reduction in carbon supply and effective lignin synthesis as well as transcripts from all steps of the lignin pathway and some corresponding enzyme activities. However, lignin content was increased under ozone probably due to variations in other major components of the cell wall. Both mechanisms seemed to coexist under combined treatment and resulted in a high increase in lignin content.

A macroscopic Washburn approach of liquid imbibition in wood derived from X-ray tomography observations.

Imbibition of water and silicone oil in poplar and spruce is investigated at the anatomical level by X-ray tomography observations and at the macroscopic level by imbibition kinetics. Imbibition mechanisms depend on both liquid and species. In poplar, oil penetrates vessels with a small contact angle, consistent with the value measured on solid wood (ca. [Formula: see text]). Surprisingly, no direct penetration of water was observed in vessels. The large contact angle for water blocks the capillary rise at the scars between vessel cells. In spruce, oil and water penetrate primarily in latewood, where bordered pits remain open. Subsequently, water slowly invades the rest of the growth ring, while transversal migration is quasi-absent for oil. These 3D observations were quantified to feed a simple imbibition model that satisfactorily simulates macroscopic imbibition kinetics. A 1D approach is sufficient for oil imbibition while a 2D approach is required for water, revealing dual scale effects.

A predictive model of organic acids separation by chromatography with strong anionic resins in sulfate form.

Organic acids commonly have quite symmetrical chromatography profiles at low pH (< 1.5) with strong anionic resins, but a significant tailing can be observed with succinic and citric acids. Classical adsorption models, like the Langmuir model, fail to predict this behavior, which can have a major influence on mean retention times and profile shapes, therefore on chromatography performances. A new retention model was developed to better predict organic acid separation with strong anionic resin. This model combines a refined Langmuir adsorption model and an ion-exchange model. Organic acid adsorption is assumed to be due to hydrogen bonding with sulfate and hydrogen sulfate counter-anions on the resin. The adsorption capacity depends mostly on molecular size: up to sixteen formic acid molecules could be adsorbed per counter-anions, meanwhile only two succinic acid or one citric acid molecules could be adsorbed. This adsorption model was then embedded in a generic and accurate modeling approach (continuous column with mass balance equations solved by the conservation element/solution element (CE/SE) method). All parameters of this column model were identified by fitting the simulation to experimental results (equilibrium curves and pulse tests). Then, the column model was validated with original experimental results from a binary mixture pulse test (formic and succinic acids). Results show that simulations are much more predictive for multi-component pulse tests, both in terms of profile shape and retention time, which cannot be captured without considering ion-exchange.