Optimizing microbioreactor cultivation strategies for Trichoderma reesei: from batch to fed-batch operations.

BACKGROUND: Filamentous fungi have long been recognized for their exceptional enzyme production capabilities. Among these, Trichoderma reesei has emerged as a key producer of various industrially relevant enzymes and is particularly known for the production of cellulases. Despite the availability of advanced gene editing techniques for T. reesei, the cultivation and characterization of resulting strain libraries remain challenging, necessitating well-defined and controlled conditions with higher throughput. Small-scale cultivation devices are popular for screening bacterial strain libraries. However, their current use for filamentous fungi is limited due to their complex morphology. RESULTS: This study addresses this research gap through the development of a batch cultivation protocol using a microbioreactor for cellulase-producing T. reesei strains (wild type, RutC30 and RutC30 TR3158) with offline cellulase activity analysis. Additionally, the feasibility of a microscale fed-batch cultivation workflow is explored, crucial for mimicking industrial cellulase production conditions. A batch cultivation protocol was developed and validated using the BioLector microbioreactor, a Round Well Plate, adapted medium and a shaking frequency of 1000 rpm. A strong correlation between scattered light intensity and cell dry weight underscores the reliability of this method in reflecting fungal biomass formation, even in the context of complex fungal morphology. Building on the batch results, a fed-batch strategy was established for T. reesei RutC30. Starting with a glucose concentration of 2.5 g l - 1 in the batch phase, we introduced a dual-purpose lactose feed to induce cellulase production and prevent carbon catabolite repression. Investigating lactose feeding rates from 0.3 to 0.75 g (l h) - 1 , the lowest rate of 0.3 g (l h) - 1 revealed a threefold increase in cellobiohydrolase and a fivefold increase in ß -glucosidase activity compared to batch processes using the same type and amount of carbon sources. CONCLUSION: We successfully established a robust microbioreactor batch cultivation protocol for T. reesei wild type, RutC30 and RutC30 TR3158, overcoming challenges associated with complex fungal morphologies. The study highlights the effectiveness of microbioreactor workflows in optimizing cellulase production with T. reesei, providing a valuable tool for simultaneous assessment of critical bioprocess parameters and facilitating efficient strain screening. The findings underscore the potential of microscale fed-batch strategies for enhancing enzyme production capabilities, revealing insights for future industrial applications in biotechnology.

Assessing the capabilities of 2D fluorescence monitoring in microtiter plates with data-driven modeling for secondary substrate limitation experiments of Hansenula polymorpha.

BACKGROUND: Non-invasive online fluorescence monitoring in high-throughput microbioreactors is a well-established method to accelerate early-stage bioprocess development. Recently, single-wavelength fluorescence monitoring in microtiter plates was extended to measurements of highly resolved 2D fluorescence spectra, by introducing charge-coupled device (CCD) detectors. Although introductory experiments demonstrated a high potential of the new monitoring technology, an assessment of the capabilities and limits for practical applications is yet to be provided. RESULTS: In this study, three experimental sets introducing secondary substrate limitations of magnesium, potassium, and phosphate to cultivations of a GFP-expressing H. polymorpha strain were conducted. This increased the complexity of the spectral dynamics, which were determined by 2D fluorescence measurements. The metabolic responses upon growth limiting conditions were assessed by monitoring of the oxygen transfer rate and extensive offline sampling. Using only the spectral data, subsequently, partial least-square (PLS) regression models for the key parameters of glycerol, cell dry weight, and pH value were generated. For model calibration, spectral data of only two cultivation conditions were combined with sparse offline sampling data. Applying the models to spectral data of six cultures not used for calibration, resulted in an average relative root-mean-square error (RMSE) of prediction between 6.8 and 6.0%. Thus, while demanding only sparse offline data, the models allowed the estimation of biomass accumulation and glycerol consumption, even in the presence of more or less pronounced secondary substrate limitation. CONCLUSION: For the secondary substrate limitation experiments of this study, the generation of data-driven models allowed a considerable reduction in sampling efforts while also providing process information for unsampled cultures. Therefore, the practical experiments of this study strongly affirm the previously claimed advantages of 2D fluorescence spectroscopy in microtiter plates.

Alternative type of Ames test allows for dynamic mutagenicity detection by online monitoring of respiration activity.

The Ames test is the most commonly used mutagenicity test worldwide. It is based on a microbial system that uses histidine auxotrophic Salmonella typhimurium strains. Due to either spontaneous mutations or mutations induced by a mutagenic compound, the cells can regain their ability to grow without histidine supplementation. The degree of mutagenicity of a sample correlates with the number of cells that are able to grow in media that lack histidine. All test variants published up to now are endpoint determinations providing no information about cell growth and respiration activity during the cultivation time. This study aimed to develop an alternative type of Ames test by characterizing the respiration activity of Salmonella typhimurium over time for dynamic mutagenicity detection. It focuses on elucidating the mechanisms underlying this novel test system, and serves as a general proof of principle. Respiration activity (oxygen transfer and uptake rate) and biomass growth of Salmonella typhimurium TA 100 and TA 98 were mechanistically modeled to understand and predict the behavior of the bacteria during the Ames test. The results simulated by the model were experimentally validated by the online monitoring of respiration activity over cultivation time using a Respiration Activity MOnitoring System (RAMOS). The simulated prediction was observed to fit well to the experimental data. When a mutagenic compound was added, its mutagenicity could be detected online due to the elevated cell number and respiration of histidine prototrophic cells. Laborious manual evaluation of mutagenicity after cultivation is not necessary. Mutagenicity evaluation with the presented alternative Ames RAMOS test fitted well to results from an Ames fluctuation test. In the future, a miniaturized RAMOS device for microtiter plates should allow for a high-throughput Ames RAMOS test.