Nilesh Patel

Morphological characterization and viability assessment of Trichoderma reesei by image analysis.

The production of cellulase from the filamentous fungus Trichoderma reesei is a critical step in the industrial process leading to cellulose ethanol. As a result of the lack of quantitative analysis tools, the intimate relationship that exists between the morphological and physiological states of the microorganism, the shear field in the bioreactor, and the process performance is not yet fully understood. A semiautomatic image analysis protocol was developed to characterize the mycelium morphology and to estimate its percentage viability during the fermentation process based on four morphological types (unbranched, branched, entangled, and clumped microorganisms). Pictures taken under bright field microscopy combined with images of fluorescein diacetate stained fungi were used to assess the morphological parameters and the percentage viability of microorganisms simultaneously. The method was tested during the course of fed‐batch fermentation in a reciprocating plate bioreactor. The use of the image analysis protocol was found to be successful in quantifying the variations in the morphology and the viability of T. reesei throughout the fermentation.

Blood glucose monitor: an alternative off-line method to measure glucose concentration during fermentations with Trichoderma reesei

Two home, blood-glucose monitoring meters, OneTouch Ultra and Ascensia Contour, were used to determine the glucose concentration during fermentations of Trichoderma reesei in both flasks and bioreactors. The results, when compared to those given by the 3,5-dinitrosalicylic acid reducing sugar assay, HPLC and YSI 2700 SELECT Biochemistry analyzer, showed that the glucose meters are a quick, reliable and economical alternative method for frequent glucose concentration measurement during fermentation. For T. reesei fermentations, the OneTouch meter was the more suitable

Application of image analysis in the fungal fermentation of Trichoderma reesei RUT-C30.

Trichoderma reesei was grown in a stirred‐tank bioreactor (STB) and a reciprocating plate bioreactor (RPB) at four different agitation speeds. A semiautomatic image analysis protocol that was developed to characterize the mycelium morphology during the fermentation process based on four morphological types (unbranched, branched, entangled, and clumped microorganisms) was applied to study the effect of agitation on the morphology of T. reesei. It was shown via statistical validation that broth samples used for image analysis represented the whole population of the fungi in the bioreactor. High shear was found to be damaging to T. reesei grown in the STB. The gentler shear produced in the RPB was not detrimental to the microorganism even at higher agitation speed. Better productivity was obtained for T. reesei grown in the STB and the highest productivity, 0.121 IU/mL h, was obtained at 400 rpm. The morphological parameter, the hyphal growth unit, was found to be correlated to the productivity. Understanding the effect of agitation on the morphology and productivity of T. reesei could lead to the design of better bioreactors and the selection of operating conditions of bioreactors to optimize the production of cellulase.

An image analysis technique to estimate the cell density and biomass concentration of Trichoderma reesei.

Aim:  The objective is to develop an automated image analysis protocol to quantify the cell volume fraction of filamentous fungi (Trichoderma reesei) and estimate the biomass concentration.

Evaluation of oxygen mass transfer in Aspergillus niger fermentation using data reconciliation.

Fermentation experiments using Aspergillus niger result in a very viscous broth due to the growth of filamentous microorganism. For viscous fermentation processes, it is difficult to estimate with confidence the volumetric oxygen mass transfer coefficient ( KL a), which can be used for scale‐up or design of bioreactors. In the present study, four methods based on dynamic and stationary approaches were used to measure KL a throughout the fermentation. Data reconciliation was used to obtain a more reliable and consistent KL a. The KL a value obtained by a data reconciliation technique was found to be more reliable since it takes into consideration both the reliability of all measured variables and the accuracy of all mass balance equations.

Design of a novel Couette flow bioreactor to study the growth of fungal microorganism.

Cultivations using Trichoderma reesei Rut C-30 were performed in a 5-l Couette flow bioreactor (CFB) which was designed and built to perform experiments in batch and continuous modes. Process parameters such as dissolved oxygen, pH and temperature were measured and controlled without disturbing the shear profile inside the bioreactor. Effect of shear on the growth, protein production and morphology was studied by performing runs at 100, 200, 300 and 400 rpm. At higher shear rates, lower protein production rate and activity, and higher rate of fragmentation were observed. Also, the cell thickness decreased with increasing speed, going from 8.3 microm for the experiment at 100 rpm to 4.3 microm at 400 rpm. The effect of substrate, lactose (an inducer) or glucose, was investigated by switching the feed medium during the two runs performed at 300 and 400 rpm. The novel design of the CFB used in the present study includes a large volume that allows growing larger size microorganisms (e.g. fungi) and permits larger sampling volumes without affecting the cultivation. It also has the ability to carry out experiments for long periods of time, both in batch and continuous modes.

Data Reconciliation Using Neural Networks for the Determination of KLa

The oxygen mass transfer coefficient (KLa) is of paramount importance in conducting aerobic fermentation. KLa also serves to compare the efficiency of bioreactors and their mixing devices as well as being an important scale-up factor. In submerged fermentations, four methods are available to estimate the overall oxygen mass transfer coefficient (KLa): the dynamic method, the stationary method based on a previous determination of the oxygen uptake rate (QO2X), the gaseous oxygen balance and the carbon dioxide balance. Each method provides a distinct estimation of the value of KLa. Data reconciliation can be used to obtain the most probable value of KLa by minimizing an objective function that includes measurement terms and oxygen conservation models, each being weighted according to their level of confidence. Another alternative, for a more rapid determination of KLa, is using a neural network which has been previously trained to predict KLa from the series of oxygen conservation models. Results obtained with this new approach show that KLa can be predicted rapidly and gives values that are equivalent to those obtained with the conventional data reconciliation algorithm.

Evaluation of the Oxygen Mass Transfer Using Data Reconciliation

Abstract Fermentation experiments done with Aspergillus niger results in a very viscous broth due to the growth of this filamentous microorganism. For this type of viscous fermentation process, it is difficult to estimate with confidence the oxygen mass transfer coefficient (KLa). In the present study, four methods based on dynamic and stationary approaches were available to measure KLa during the fermentation process. Data reconciliation was used to obtain a more reliable and consistent value of KLa. The KLa value obtained by data reconciliation technique was found to be more reliable