Review of methods to probe single cell metabolism and bioenergetics

Vasdekis, Andreas E.; Stephanopoulos, Gregory

doi:10.1016/j.ymben.2014.09.007

Cited by 81 publications

(64 citation statements)

References 366 publications

(417 reference statements)

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“…DGA1 is the final step of the triglyceride synthesis pathway thereby enabling MTYL053 with enhanced lipid production5. To evaluate the phenotypic diversity in culture, image cytometry13 was employed (Supplementary Information) to define the size and number/size of lipid droplets (LDs) in individual cells. As shown in Fig.…”

Section: Resultsmentioning

confidence: 99%

Origins of Cell-to-Cell Bioprocessing Diversity and Implications of the Extracellular Environment Revealed at the Single-Cell Level

Vasdekis

Silverman

Stephanopoulos

2015

Sci Rep

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Bioprocess limitations imposed by microbial cell-to-cell phenotypic diversity remain poorly understood. To address this, we investigated the origins of such culture diversity during lipid production and assessed the impact of the fermentation microenvironment. We measured the single-cell lipid production dynamics in a time-invariant microfluidic environment and discovered that production is not monotonic, but rather sporadic with time. To characterize this, we introduce bioprocessing noise and identify its epigenetic origins. We linked such intracellular production fluctuations with cell-to-cell productivity diversity in culture. This unmasked the phenotypic diversity amplification by the culture microenvironment, a critical parameter in strain engineering as well as metabolic disease treatment.

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Section: Resultsmentioning

confidence: 99%

Origins of Cell-to-Cell Bioprocessing Diversity and Implications of the Extracellular Environment Revealed at the Single-Cell Level

Vasdekis

Silverman

Stephanopoulos

2015

Sci Rep

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“…This form of phenotypic diversity was discovered decades ago [33], and can only be unmasked at the single-cell level [34]. Following substantial interest in the stochasticity of gene expression [35–40], infection [41], and cell growth [42–44], such stochastic fluctuations have been recently applied to the discovery of many unknown aspects of gene regulation [22, 23].…”

Section: Discussionmentioning

confidence: 99%

Exploiting Bioprocessing Fluctuations to Elicit the Mechanistics of De Novo Lipogenesis in Yarrowia lipolytica

Vasdekis¹,

Silverman²,

Stephanopoulos³

2017

PLoS ONE

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Despite substantial achievements in elucidating the metabolic pathways of lipogenesis, a mechanistic representation of lipid accumulation and degradation has not been fully attained to-date. Recent evidence suggests that lipid accumulation can occur through increases of either the cytosolic copy-number of lipid droplets (LDs), or the LDs size. However, the prevailing phenotype, or how such mechanisms pertain to lipid degradation remain poorly understood. To address this shortcoming, we employed the–recently discovered–innate bioprocessing fluctuations in Yarrowia lipolytica, and performed single-cell fluctuation analysis using optical microscopy and microfluidics that generate a quasi-time invariant microenvironment. We report that lipid accumulation at early stationary phase in rich medium is substantially more likely to occur through variations in the LDs copy-number, rather than the LDs size. Critically, these mechanistics are also preserved during lipid degradation, as well as upon exposure to a protein translation inhibitor. The latter condition additionally induced a lipid accumulation phase, accompanied by the downregulation of lipid catabolism. Our results enable an in-depth mechanistic understanding of lipid biogenesis, and expand longitudinal single-cell fluctuation analyses from gene regulation to metabolism.

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“…38, 225–230 In the next sections, recent experiments regarding on chip single cell analysis for genome, transcriptome, and proteome analysis are reviewed, particularly highlighting approaches for high throughput, multiplex analysis.…”

Section: Sample Preparationmentioning

confidence: 99%