Online Biomass Monitoring Enables Characterization of the Growth Pattern of Aspergillus fumigatus in Liquid Shake Conditions

Abstract

Numerous filamentous fungal species are extensively studied due to their role as model organisms, workhorses in biotechnology, or as pathogens for plants, animals, and humans. Growth studies are mainly carried out on solid media. However, studies concerning gene expression, biochemistry, or metabolism are carried out usually in liquid shake conditions, which do not correspond to the growth pattern on solid media. The reason for this practice is the problem of on-line growth monitoring of filamentous fungal species, which usually form pellets in liquid shake cultures. Here, we compared the time-consuming and tedious process of dry-weight determination of the mold Aspergillus fumigatus with online monitoring of biomass in liquid shake culture by the parallelizable CGQ (“cell growth quantifier”), which implements dynamic biomass determination by backscattered light measurement. The results revealed a strong correlation of CGQ-mediated growth monitoring and classical biomass measurement of A. fumigatus grown over a time course. Moreover, CGQ-mediated growth monitoring displayed the difference in growth of A. fumigatus in response to the limitation of iron or nitrogen as well as the growth defects of previously reported mutant strains (ΔhapX, ΔsrbA). Furthermore, the frequently used wild-type strain Af293 showed largely decreased and delayed growth in liquid shake cultures compared to other strains (AfS77, A1160p+, AfS35). Taken together, the CGQ allows for robust, automated biomass monitoring of A. fumigatus during liquid shake conditions, which largely facilitates the characterization of the growth pattern of filamentous fungal species.

Squalene production under oxygen limitation by Schizochytrium sp. S31 in different cultivation systems

“…2 , after approximately 4 g/L). The same has been demonstrated for S. cerevisiae and A. fumigatus (Bauer et al 2022 ; Bruder et al 2016 ). The last datapoint for each data set was excluded from the graph because the backscatter signal decreased slowly after the stationary phase was reached.…”

“…This behaviour leads to inaccurate growth determination via optical density measurements. Growth monitoring by backscatter light is a relatively new technique, which provides more accurate and non-invasive data for filamentous/cluster-forming organisms than OD600 measurements (Bauer et al 2022 ). To the best of our knowledge, CGQ measurements have not been described for thraustochytrids yet.…”

“…For continuous cultivation, 48 h of batch operation and the time until the steady state was reached theoretically were added. The runtime of the continuous cultivation (25 d) was chosen to equal the space-time yield reached by the fed-batch cultivation been demonstrated for S. cerevisiae and A. fumigatus (Bauer et al 2022;Bruder et al 2016). The last datapoint for each data set was excluded from the graph because the backscatter signal decreased slowly after the stationary phase was reached.…”