Single cell sorting of young yeast based on label‐free fluorescence lifetime imaging microscopy

Kong, Yawei; Zhao, Yinping; Yu, Yao; Liu, Zhijia; Fei, Yiyan; Ma, Junjun; Mi, Lan

doi:10.1002/jbio.202100344

Cited by 4 publications

(5 citation statements)

References 33 publications

(38 reference statements)

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“…These limitations of flow cytometry were also reported by Kong et al 70 . Therefore, more recent studies, for example, Kong et al 70 . have determined similar age fraction contents as determined in this study.…”

Section: Discussionsupporting

confidence: 86%

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Autofluorescence prediction model for fluorescence unmixing and age determination

Eigenfeld

Kerpes

Whitehead

et al. 2022

Biotechnology Journal

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Background: Flow cytometry is a powerful tool for identifying and quantifying various cell markers, such as viability, vitality, and individual cell age, at single-cell stages. However, cell autofluorescence and marker fluorophore signals overlap at low fluorescence intensities. Thus, these signals must be unmixed before determining the age fraction. Methods and Results:A comparison was made between principal component regression (PCR) and random forest (RF) to predict autofluorescence signals of Saccharomyces pastorianus var. carlsbergensis in a flow cytometer. RF provided better prediction results than the PCR and was therefore determined to be better suited for unmixing signals. In the subsequent application for unmixing the autofluorescence signal from the marker fluorophore signal, the Gaussian mixture analysis based on RF was in better agreement with the microscopy-determined replicative age distribution than the PCR-based method. Conclusion:The proposed approach of single-laser spectral unmixing and subsequent Gaussian mixture analysis showed that the microscopy data was consistent with the unmixed fluorescence spectra. The demonstrated approach enables fast and reliable unmixing of flow cytometric spectral data using a single-laser spectral unmixing method. This analysis method enables age determination of cells in industrial processes. This age determination allows for quantifying the yeast cell's age fractions, providing a detailed view of age-related changes. Additionally, the bud scar labeling technique can be used to determine age-related changes in Pichia pastoris yeast for biotechnological applications or recombinant protein expression.

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Section: Discussionsupporting

confidence: 86%

“…After FACS using WGA‐Alexa 488 as bud scar staining fluorophore, the purity of yeast cells with more than one scar is around 65–70% 69 . These limitations of flow cytometry were also reported by Kong et al 70 . Therefore, more recent studies, for example, Kong et al 70 .…”

Section: Discussionmentioning

confidence: 86%

Autofluorescence prediction model for fluorescence unmixing and age determination

Eigenfeld

Kerpes

Whitehead

et al. 2022

Biotechnology Journal

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“…The sizes of experimental ROIs samples ranged from 52 to 104. The data were fitted using a double exponential model as τmean = a1 τ-free + a2 τ-bound (Kong et al, 2022). Statistical analyses were performed by GraphPad-Prism version 8.0 software (GraphPad, United States).…”

Section: Preparation Of Yeast Cells For Fluorescence Lifetime Imagingmentioning

confidence: 99%

“…Usually, a more oxidized state increases both τ-mean and τ-bound, while reducing a1/ a2 (Schaefer et al, 2017;Meleshina et al, 2018). However, there are few reports about the FILM analysis in living yeast cells, including K. marxianus cells (Kong et al, 2022).…”

Section: Introductionmentioning

confidence: 99%

Fluorescence lifetime imaging of NAD(P)H upon oxidative stress in Kluyveromyces marxianus

Luo

Yang

et al. 2022

Front. Bioeng. Biotechnol.

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K. marxianus is a promising cell factory for producing heterologous proteins. Oxidative stresses were raised during overexpression of heterologous proteins, leading to the shift of the redox state. How to measure the redox state of live K. marxianus cells without perturbing their growth remains a big challenge. Here, a fluorescence lifetime imaging (FLIM)-based method was developed in live K. marxianus cells. During the early exponential growth, K. marxianus cells exhibited an increased mean fluorescence lifetime (τ-mean) of NAD(P)H compared with Saccharomyces cerevisiae cells, which was consistent with the preference for respiration in K. marxianus cells and that for fermentation in S. cerevisiae cells. Upon oxidative stresses induced by high temperature or H2O2, K. marxianus cells exhibited an increased τ-mean in company with decreased intracellular NAD(P)H/NAD(P)+, suggesting a correlation between an increased τ-mean and a more oxidized redox state. The relationship between τ-mean and the expression level of a heterologous protein was investigated. There was no difference between the τ-means of K. marxianus strains which were not producing a heterologous protein. The τ-mean of a strain yielding a high level of a heterologous protein was higher than that of a low-yielding strain. The results suggested the potential application of FLIM in the non-invasive screen of high-yielding cells.

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“…[12] This reduction correlates with the simultaneous decrease in fructose-1,6-bisphosphate. [13] Generally, aging is defined as a decline in physiological function [14] accompanied by metabolic changes [15] with a replication-specific increase in mortality, implying that old cells are more likely to die than young cells. When measured across a population, this property results in a sigmoidal survival curve, [12][13][14] which has been reported for haploid, and diploid yeast strains from all genetic backgrounds investigated to date.…”

mentioning

confidence: 99%

Studying the impact of cell age on the yeast growth behaviour of Saccharomyces pastorianus var. carlsbergensis by magnetic separation

Eigenfeld

Wittmann

Kerpes

et al. 2023

Biotechnology Journal

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Despite the fact that yeast is a widely used microorganism in the food, beverage, and pharmaceutical industries, the impact of viability and age distribution on cultivation performance has yet to be fully understood. For a detailed analysis of fermentation performance and physiological state, we introduced a method of magnetic batch separation to isolate daughter and mother cells from a heterogeneous culture. By binding functionalised iron oxide nanoparticles, it is possible to separate the chitin‐enriched bud scars by way of a linker protein. This reveals that low viability cultures with a high daughter cell content perform similarly to a high viability culture with a low daughter cell content. Magnetic separation results in the daughter cell fraction (>95%) showing a 21% higher growth rate in aerobic conditions than mother cells and a 52% higher rate under anaerobic conditions. These findings emphasise the importance of viability and age during cultivation and are the first step towards improving the efficiency of yeast‐based processes.

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Single cell sorting of young yeast based on label‐free fluorescence lifetime imaging microscopy

Cited by 4 publications

References 33 publications

Autofluorescence prediction model for fluorescence unmixing and age determination

Autofluorescence prediction model for fluorescence unmixing and age determination

Fluorescence lifetime imaging of NAD(P)H upon oxidative stress in Kluyveromyces marxianus

Studying the impact of cell age on the yeast growth behaviour of Saccharomyces pastorianus var. carlsbergensis by magnetic separation

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