Real-Time Monitoring of the Yeast Intracellular State During Bioprocesses With a Toolbox of Biosensors

Abstract

Industrial fermentation processes strive for high robustness to ensure optimal and consistent performance. Medium components, fermentation products, and physical perturbations may cause stress and lower performance. Cellular stress elicits a range of responses, whose extracellular manifestations have been extensively studied; whereas intracellular aspects remain poorly known due to lack of tools for real-time monitoring. Genetically encoded biosensors have emerged as promising tools and have been used to improve microbial productivity and tolerance toward industrially relevant stresses. Here, fluorescent biosensors able to sense the yeast intracellular environment (pH, ATP levels, oxidative stress, glycolytic flux, and ribosome production) were implemented into a versatile and easy-to-use toolbox. Marker-free and efficient genome integration at a conserved site on chromosome X of Saccharomyces cerevisiae strains and a commercial Saccharomyces boulardii strain was developed. Moreover, multiple biosensors were used to simultaneously monitor different intracellular parameters in a single cell. Even when combined together, the biosensors did not significantly affect key physiological parameters, such as specific growth rate and product yields. Activation and response of each biosensor and their interconnection were assessed using an advanced micro-cultivation system. Finally, the toolbox was used to screen cell behavior in a synthetic lignocellulosic hydrolysate that mimicked harsh industrial substrates, revealing differences in the oxidative stress response between laboratory (CEN.PK113-7D) and industrial (Ethanol Red) S. cerevisiae strains. In summary, the toolbox will allow both the exploration of yeast diversity and physiological responses in natural and complex industrial conditions, as well as the possibility to monitor production processes.

Identification of acetic acid sensitive strains through biosensor-based screening of a Saccharomyces cerevisiae CRISPRi library

“…6 b). A higher sfpHluorin ratio indicates a higher cytosolic pH [ 24 , 39 ]. The comparison between the maximum reporter expression of the acetic acid biosensor observed for each strain and the respective sfpHluorin ratio calculated at the time of maximum biosensor output, displayed a strong positive correlation (R 2 = 0.78, Fig.…”

“…We set to monitor the intracellular pH using sfpHluorin and found a strong (R 2 = 0.78) correlation between the reporter of the acetic acid biosensor (indicating the intracellular acetic acid retention) and the sfpHluorin signal. Unexpectedly, the sfpHluorin ratio of UV-GFP/GFP fluorescence measured at the time when the acetic acid biosensor signal peaked, grew as the acetic acid biosensor signal increased, indicating a higher cytosolic pH [ 24 , 39 ] in cells with a higher biosensor signal. We speculate that the strains isolated that presumably retained more acetic acid may still have been able to extrude protons and thereby maintain a higher intracellular pH.…”

“…Biosensors are efficient tools for screening strain libraries or monitoring strain performance [ 19 ], including production of specific compounds [ 20 – 23 ], intracellular pH [ 24 , 25 ], various stress responses [ 24 , 26 ] or concentration of compounds such as metals [ 27 ], sugars [ 28 ] or intracellular metabolites, such as ATP [ 29 ], fructose-bisphosphate [ 30 ] or malonyl-CoA [ 31 ]. The use of biosensors can considerably accelerate strain evaluation and can also allow real-time monitoring of cellular states [ 19 ].…”

Assessment of fluorescent protein candidates for multi-color flow cytometry analysis of Saccharomyces cerevisiae

“…Combinations of up to four FPs have already been achieved in S. cerevisiae , including the use of FPs such as mTagBFP, mCherry, TagRFP-T, CFP or YFP; however, these were all optimized for live-cell imaging studies [ 20 , 33 , 34 ]. While compiling the present study, a parallel study was also published with a combination of up to three FPs, mTurquoise2, mCherry and YmPET whose genes were co-expressed in S. cerevisiae and the fluorescence recorded using a biolector [15] . All these approaches have in common the need for several excitation lasers, including a violet (405 nm) or yellow (561 nm) laser which are not commonly available in commercial flow cytometers.…”

“…However, a major challenge of multicolor flow cytometry is the selection of the appropriate combination of FPs. Due to the limited space in the visible spectrum, the emission fluorescence of FPs overlap can make it difficult to distinguish between the emission signals [15] . Operational adjustments such as the selection of appropriate emission filters are also necessary to optimize the simultaneous detection of multiple fluorescence signals [16] .…”