Tamiris Roque

Fadhel Ben Chaabane

Frédéric Augier

Catherine Béal

A W Nienow

Application of the sale-down methodology to study the effect of mixing on Trichoderma reesei physiology and enzyme production

Highlights

 Trichoderma reesei is sensitive to anaerobiosis  Oxygen gradients in T. reesei cultures lead to a complex metabolic response  Long exposure of T.reesei to anaerobiosis decrease the cellulases production

Introduction

Techno-economic evaluations of processes for ethanol production from lignocellulosic biomass show that reducing the cost of the cellulases used to hydrolyze the cellulose into glucose is a prerequisite to bring the ethanol cost to values close to the ethanol produced from starch. A very attractive option is to perform the production of enzymes on site in order to substitute expensive and pure carbon sources by lignocellulosic waste generated by the agri-food or forestry activity.

Industrial cellulases are mainly produced by an aerobic filamentous fungus, Trichoderma reesei, because of its high secretion capacity. Scaling-up this process is very challenging because of the complex links that exist between the process conditions, the morphology of this fungus and its productivity. Actually, the filamentous morphology induces an increase of the medium viscosity that strongly reduces the oxygen mass transfer rate. To ensure a sufficient rate, the power input has to be increased, which increase the fluid dynamic stresses on the mycelial structures. Carrying out fermentations with these microorganisms is complicated as the fungal morphology impacts process parameters, whereas process conditions affect in return the morphology and possibly the process productivity. Moreover, with increasing scale, the media experiences ever increasing spatial and temporal variations, especially in dissolved oxygen and sugar concentration compared to the bench scale. Scale-down techniques are a way of establishing at the bench scale the large scale behavior and their implications for the economics of the process. The goal of this work is to better understand and evaluate the impact of the upscaling on the physiology of T. reesei.

Methods

The effect of physical-chemical heterogeneities induced by the scale-up on the behavior of the microorganism are investigated using 2 scale-down approaches : a two-compartment system (2STR) and a single compartment system (1STR). The enzyme production follows a two-steps process: growth and production. The growth step is operated in batch mode in excess of sugar to reach biomass concentrations of 15g/L. Cultures medium, preculture and operating conditions in growth step are similar to those reported in [1]. The production step is carried out in fed-batch mode. For the 2STR experiment, a 3.5L aerobic bioreactor (2.5L of culture medium) kept at 40% of dissolved oxygen saturation (pO 2 ) is connected to a 2.0L anaerobic bioreactor (0.5L of culture media) where the pO 2 is kept at 0% by injecting nitrogen. Two peristaltic pumps keep the broth circulating between the two bioreactors throughout the experiment. Two different cycling residence times in the anaerobic zone are tested by changing the volume of the bioreactors. For the 1STR experiment, cycling oscillations in the pO 2 (0-40%) are produced in a single 3.5L bioreactor by injecting a mix of air and nitrogen. For both scale down approaches, the temperature is 27°C and pH is 4.0 for all the experiments. The gas flow rate in the 3.5L bioreactors is constant and equal to 0.25 l/mn. A determination of the secreted proteins concentration is achieved on the medium filtrate by using the DCTM Protein Assay kit (Biorad, Hercules, United States of America) and is based on a range of bovine serum albumin (BSA, 0-1.5 gL-1) [2].

Results and discussion

As reported in figure 1

Conclusions

In this study, the effect of oxygen oscillations on enzyme production has been investigated during cultures of T. reesei. The possible low sensitivity of the fungus with respect to oxygen heterogeneities in production phase, opens perspectives in terms of technological choice on an industrial scale. However, its complex biological response to oxygen oscillations seems to be correlated with the distribution of the residence time in anaerobic zones inside large bioreactors.

Figure 1 .

 1 figure 1.III showed very different results for the same characteristic times (3,4min) in the anaerobic zone. This indicates a) the sensitivity of T. reesei to anaerobiosis and b) the fact that the metabolic response is complex and not immediate because it depends on the distribution of the residence times of the microorganisms in the aerated or non-aerated zones.


Thi-Lan-Phuong Nguyen

Claire-Saulou Bérion

Catherine Béal

Influences of environmental factors on Lactobacillus reuteri growth and 3-hydroxypropionic acid production in the context of coupling with extraction

Highlights

 Glycerol bioconversion into 3-hydoxypropionic by Lactobacilllus reuteri.  Plackett -Burman method

Introduction

In the framework of bioeconomy, 3-hydroxypropionic acid (3-HP) is gaining more and more interest due to its desirable industrial applications. As a bifunctionality molecule, 3-HP can be converted through chemical reactions into a variety of added-value chemicals, such as 1,3propanediol (1,3-PDO), acrylic acid, malonic acid, or biodegradable polyesters [Matsakas et al., 2018], all of them give versatile applications in both industry and in everyday life. Among non-GMO microorganisms able to naturally produce 3-HP, L. reuteri is noticeable thanks to its ability to produce 3-HP from glycerol, which is a by-product in biodiesel manufacturing industries. This Gram-positive probiotic bacteria is an interesting candidate due to its G.R.A.S. status and ability to synthesize vitamin B12, an essential co-factor for the first enzyme of the bioconversion pathway. Having the ability to convert glycerol into equimolar concentration of 3-HP and 1,3-propanediol, but the cells do not use glycerol as a carbon source, thus avoiding the synthesis of by-products that can hinder extraction performance. However, the effects of nutritional and environmental factors during the growth phase, on the cell ability to perform bioconversion have not been elucidated yet. In this context, the aim of this work is to better understand the effect of these factors on the growth and the bioconversion, in order to identify the conditions to optimize the 3-HP production by L. reuteri.

Methods

The 3-stages process of 3-HP production by L. reuteri.

L. reuteri DSM 17938 that was purchased from BioGaia AB (Stockholm, Sweden) was cultivated in batch mode, in a controlled 5L bioreactor until reach to stationary phase. Cells then were harvested by centrifugation at 7500 rpm before being introduced into a 2L bioreactor working in fed-batch mode with glycerol addition at 0.5 g.h -1 . The cell concentration as quantified by flow cytometry (FCM), cell physiological states (determined by FCM coupled with carboxyfluorescein diacetate and propidium iodide staining [Rault et al. 2007 [Plackett and Burman, 1946]. All statically analysis for data were performed by the software Statgraphic plus version 5.0, at 95% confidence intervals for coefficient estimates.

Results and discussion

Effects of environmental factors on the cell growth.

The results showed that increasing glucose concentration into MRS medium gives a higher final cell concentration, together with a higher number of viable cells. Meanwhile, lower temperature of cultivation results in less growth and less acid lactic production, compared to the condition at 37 o C.

Effects of environmental factors on cell ability to perform bioconversion.

By increasing glucose concentration, the molar ratio between 3-HP/1,3-PDO goes down. This can be explained that the more NADH produced during the glycolysis step are preferentially reoxidized to NAD + by the reduction of 3-HPA to 1,3-propanediol. Temperature decreases at 33 o C gives no considerable effect since the P value is higher than 0.05. Surprisingly, the addition of vitamin B12 gives a negative impact to 3-HP production. A supplementary of such element in bioconversion stage under the presence of the substrate glycerol may give a better influence. Regarding to the duration of glycerol consumption, some interesting factors were observed, including the addition of betain and KCl, 1,2-PDO, and phytone peptone. It seems match to the previous studies that supplementary of betain at 2mM to medium consequence in the increase the cell tolerance under osmotic stress to L. plantarum [Ket et al. 1994]. Meanwhile, the presence of 1,2-propanediol is a preparation step for cell in the expression of the genes encoding the enzymes and structural proteins involving the Pdu pathway [Dishisha 2015a].

Conditions leading to the highest 3-HP production

The experimental design allowed to identify the best conditions that lead to the highest production of 3-HP at 19.6 g (corresponding to 15 g.L -1 ), compared to the production of 13 g (12 g.L -1 ) in the reference condition.

Conclusions

Addition of glucose increases cell proliferation but also decreases the molar ratio 3-HP/1,3-PDO. Conversely, lower temperature reduce the growth but gives no impact to bioconversion. Addition of vitamin B12 in the growth phase is not effective to 3-HP production while the presence of betain plus KCl, 1,2-PDO and phytone peptone extend the time of glycerol consumption. The selective factors giving positive impacts to the bioconversion will be considered in a second experimental design to optimize the conditions during the bioconversion step for 3-HP production by L. reuteri.

A

  Plackett-Burman experimental matrix was designed to test the effects of 11 growth factors on the growth phase and bioconversion ability of L. reuteri for 3-HP production [Plackett and Burman, 1946]. The tested factors include addition of glucose, yeast extract, phytone peptone, 1,2-propanediol (1,2-PDO), cysteine, betain plus KCl, tween 80, vitamin B12, lower pH at 5.5, lower temperature at 33 o C. The results allow defining model of the following general form: Y i = k i + Ʃa i •Y (+)i (Y i : Response variable; k i : Constant corresponding to the value of Y i when all 11 variables are at their low level; a i : Linear coefficient of each variable to express the effect of the high level; Y (+)i : Value of the plus level of the variable)