TY - ABST

T1 - Dynamics in population heterogeneity during batch and continuous fermentation of Saccharomyces cerevisiae

A1 - Heins,Anna-Lena

A1 - Lencastre Fernandes,Rita

A1 - Lundin,L.

A1 - Carlquist,M.

A1 - Sörensen,S.

A1 - Gernaey,Krist

A1 - Eliasson Lantz,Anna

AU - Heins,Anna-Lena

AU - Lencastre Fernandes,Rita

AU - Lundin,L.

AU - Carlquist,M.

AU - Sörensen,S.

AU - Gernaey,Krist

AU - Eliasson Lantz,Anna

PB - Elsevier BV

PY - 2012

Y1 - 2012

N2 - Traditionally, microbial populations in optimization studies of fermentation processes have been considered homogeneous. However, research has shown that a typical microbial population in fermentation is heterogeneous. There are indications that this heterogeneity may be both beneficial (facilitates quick adaptation to new conditions) and harmful (reduces yields and productivities)[1,2]. Typically, gradients of e.g. dissolved oxygen, substrates, and pH are observed in industrial scale fermentation processes. Consequently, microbial cells circulating throughout a bioreactor experience rapid environmental changes, which might pose stress on the cells, affect their metabolism and consequently influence the level of heterogeneity of the population. To gain a deeper understanding of population heterogeneity and the triggering phenomena, a Saccharomyces cerevisiae growth reporter strain based on the expression of green fluorescent protein (GFP) was constructed which enable to perform single cell analysis, and thereby provides a tool to map population heterogeneity. A factorial design experiment followed by multivariate data analysis demonstrated a highly dynamic behavior with regard to subpopulation distribution during different growth stages. To further simulate which effect gradients have on population heterogeneity, glucose and ethanol perturbations during continuous cultivation were performed. Physiological changes were analyzed on single cell level by using flow cytometry followed by cell sorting of different subpopulations. Furthermore the expression of the reporter gene was examined by qPCR. It could be demonstrated that pulses had a clear influence on population distribution. In conclusion, we now have a tool to study the effect environmental gradients have on population heterogeneity.

AB - Traditionally, microbial populations in optimization studies of fermentation processes have been considered homogeneous. However, research has shown that a typical microbial population in fermentation is heterogeneous. There are indications that this heterogeneity may be both beneficial (facilitates quick adaptation to new conditions) and harmful (reduces yields and productivities)[1,2]. Typically, gradients of e.g. dissolved oxygen, substrates, and pH are observed in industrial scale fermentation processes. Consequently, microbial cells circulating throughout a bioreactor experience rapid environmental changes, which might pose stress on the cells, affect their metabolism and consequently influence the level of heterogeneity of the population. To gain a deeper understanding of population heterogeneity and the triggering phenomena, a Saccharomyces cerevisiae growth reporter strain based on the expression of green fluorescent protein (GFP) was constructed which enable to perform single cell analysis, and thereby provides a tool to map population heterogeneity. A factorial design experiment followed by multivariate data analysis demonstrated a highly dynamic behavior with regard to subpopulation distribution during different growth stages. To further simulate which effect gradients have on population heterogeneity, glucose and ethanol perturbations during continuous cultivation were performed. Physiological changes were analyzed on single cell level by using flow cytometry followed by cell sorting of different subpopulations. Furthermore the expression of the reporter gene was examined by qPCR. It could be demonstrated that pulses had a clear influence on population distribution. In conclusion, we now have a tool to study the effect environmental gradients have on population heterogeneity.

U2 - 10.1016/j.nbt.2012.08.561

DO - 10.1016/j.nbt.2012.08.561

JO - New Biotechnology

JF - New Biotechnology

SN - 1871-6784

VL - 29S

SP - S199-S200

ER -