No two individual cells "look" the same, even if they share the same genes and grow under identical conditions. This unexpected phenomenon, frequently termed as 'cellular noise', emerges in part due to the stochastic nature of molecular-level interactions within individual cells that occur during protein production. As such, a form of non-clonal heterogeneity in the copy number and types of proteins between cells arises.

In this presentation, we will discuss the statistical physics nature of cellular noise and our recent findings of how cellular noise propagates from gene expression to metabolism with a focus on lipid production and growth. To this end, we will first present the interferometric and fluorescent bioimaging methods [1] that we employ to dynamically track cellular metabolism of more than 103 single-cells on a microfluidic chip.

We will then proceed with our recent findings of how cellular noise affects lipid production and accumulation [2] and how we can use cellular noise to better understand metabolic dynamics [3]. We will conclude with our more recent results on the independent impacts of cellular noise on growth and lipid accumulation, as well as the underlying metabolic trade-offs and competition between these two metabolic objectives [4].

[1] Metabolic Engineering 27, 115 (2015).
[2] Scientific Reports 5, 17689 (2015).
[3] PLOS ONE 12, e0168889 (2017).
[4] Nature Communications 10, 848 (2019).