Literature DB >> 24038690

Single-cell measurements of enzyme levels as a predictive tool for cellular fates during organic acid production.

Stefan Zdraljevic1, Drew Wagner, Kevin Cheng, Laura Ruohonen, Jussi Jäntti, Merja Penttilä, Orna Resnekov, C Gustavo Pesce.   

Abstract

Organic acids derived from engineered microbes can replace fossil-derived chemicals in many applications. Fungal hosts are preferred for organic acid production because they tolerate lignocellulosic hydrolysates and low pH, allowing economic production and recovery of the free acid. However, cell death caused by cytosolic acidification constrains productivity. Cytosolic acidification affects cells asynchronously, suggesting that there is an underlying cell-to-cell heterogeneity in acid productivity and/or in resistance to toxicity. We used fluorescence microscopy to investigate the relationship between enzyme concentration, cytosolic pH, and viability at the single-cell level in Saccharomyces cerevisiae engineered to synthesize xylonic acid. We found that cultures producing xylonic acid accumulate cells with cytosolic pH below 5 (referred to here as "acidified"). Using live-cell time courses, we found that the probability of acidification was related to the initial levels of xylose dehydrogenase and sharply increased from 0.2 to 0.8 with just a 60% increase in enzyme abundance (Hill coefficient, >6). This "switch-like" relationship likely results from an enzyme level threshold above which the produced acid overwhelms the cell's pH buffering capacity. Consistent with this hypothesis, we showed that expression of xylose dehydrogenase from a chromosomal locus yields ∼20 times fewer acidified cells and ∼2-fold more xylonic acid relative to expression of the enzyme from a plasmid with variable copy number. These results suggest that strategies that further reduce cell-to-cell heterogeneity in enzyme levels could result in additional gains in xylonic acid productivity. Our results demonstrate a generalizable approach that takes advantage of the cell-to-cell variation of a clonal population to uncover causal relationships in the toxicity of engineered pathways.

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Year:  2013        PMID: 24038690      PMCID: PMC3837828          DOI: 10.1128/AEM.01749-13

Source DB:  PubMed          Journal:  Appl Environ Microbiol        ISSN: 0099-2240            Impact factor:   4.792


  38 in total

1.  Correlating cell cycle with metabolism in single cells: combination of image and metabolic cytometry.

Authors:  S N Krylov; Z Zhang; N W Chan; E Arriaga; M M Palcic; N J Dovichi
Journal:  Cytometry       Date:  1999-09-01

Review 2.  Network motifs: theory and experimental approaches.

Authors:  Uri Alon
Journal:  Nat Rev Genet       Date:  2007-06       Impact factor: 53.242

Review 3.  The Molecular Basis of pH Sensing, Signaling, and Homeostasis in Fungi.

Authors:  Elaine Bignell
Journal:  Adv Appl Microbiol       Date:  2012       Impact factor: 5.086

4.  Design of a dynamic sensor-regulator system for production of chemicals and fuels derived from fatty acids.

Authors:  Fuzhong Zhang; James M Carothers; Jay D Keasling
Journal:  Nat Biotechnol       Date:  2012-03-25       Impact factor: 54.908

5.  In silico feedback for in vivo regulation of a gene expression circuit.

Authors:  Andreas Milias-Argeitis; Sean Summers; Jacob Stewart-Ornstein; Ignacio Zuleta; David Pincus; Hana El-Samad; Mustafa Khammash; John Lygeros
Journal:  Nat Biotechnol       Date:  2011-11-06       Impact factor: 54.908

6.  Using Cell-ID 1.4 with R for microscope-based cytometry.

Authors:  Alan Bush; Ariel Chernomoretz; Richard Yu; Andrew Gordon; Alejandro Colman-Lerner
Journal:  Curr Protoc Mol Biol       Date:  2012-10

Review 7.  16 years research on lactic acid production with yeast - ready for the market?

Authors:  Michael Sauer; Danilo Porro; Diethard Mattanovich; Paola Branduardi
Journal:  Biotechnol Genet Eng Rev       Date:  2010

8.  A model for improving microbial biofuel production using a synthetic feedback loop.

Authors:  Mary J Dunlop; Jay D Keasling; Aindrila Mukhopadhyay
Journal:  Syst Synth Biol       Date:  2010-02-25

9.  Single-cell quantification of molecules and rates using open-source microscope-based cytometry.

Authors:  Andrew Gordon; Alejandro Colman-Lerner; Tina E Chin; Kirsten R Benjamin; Richard C Yu; Roger Brent
Journal:  Nat Methods       Date:  2007-01-21       Impact factor: 28.547

10.  Variability in gene expression underlies incomplete penetrance.

Authors:  Arjun Raj; Scott A Rifkin; Erik Andersen; Alexander van Oudenaarden
Journal:  Nature       Date:  2010-02-18       Impact factor: 49.962

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  3 in total

1.  The Cytosolic pH of Individual Saccharomyces cerevisiae Cells Is a Key Factor in Acetic Acid Tolerance.

Authors:  Miguel Fernández-Niño; Maribel Marquina; Steve Swinnen; Boris Rodríguez-Porrata; Elke Nevoigt; Joaquín Ariño
Journal:  Appl Environ Microbiol       Date:  2015-09-04       Impact factor: 4.792

2.  Effects of glucose, ethanol and acetic acid on regulation of ADH2 gene from Lachancea fermentati.

Authors:  Norhayati Yaacob; Mohd Shukuri Mohamad Ali; Abu Bakar Salleh; Nor Aini Abdul Rahman
Journal:  PeerJ       Date:  2016-03-10       Impact factor: 2.984

3.  Transcriptome of Saccharomyces cerevisiae during production of D-xylonate.

Authors:  Dominik Mojzita; Merja Oja; Eija Rintala; Marilyn Wiebe; Merja Penttilä; Laura Ruohonen
Journal:  BMC Genomics       Date:  2014-09-05       Impact factor: 3.969

  3 in total

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