Single-cell protein dynamics reproduce universal fluctuations in cell populations

Protein variability in single cells has been studied extensively in populations, but little is known about temporal protein fluctuations in a single cell over extended times. We present here traces of protein copy number measured in individual bacteria over multiple generations and investigate their statistical properties, comparing them to previously measured population snapshots. We find that temporal fluctuations in individual traces exhibit the same universal features as those previously observed in populations. Scaled fluctuations around the mean of each trace exhibit the same universal distribution shape as found in populations measured under a wide range of conditions and in two distinct microorganisms. Additionally, the mean and variance of the traces over time obey the same quadratic relation. Analyzing the temporal features of the protein traces in individual cells, reveals that within a cell cycle protein content increases as an exponential function with a rate that varies from cycle to cycle. This leads to a compact description of the protein trace as a 3-variable stochastic process - the exponential rate, the cell-cycle duration and the value at the cycle start - sampled once each cell cycle. This compact description is sufficient to preserve the universal statistical properties of the protein fluctuations, namely, the protein distribution shape and the quadratic relationship between variance and mean. Our results show that the protein distribution shape is insensitive to sub-cycle intracellular microscopic details and reflects global cellular properties that fluctuate between generations

A Balance between Secreted Inhibitors and Edge Sensing Controls Gastruloid Self-Organization

The earliest aspects of human embryogenesis remain mysterious. To model patterning events in the human embryo we used colonies of human embryonic stem cells (hESCs) grown on micropatterned substrate and differentiated with BMP4. These gastruloids recapitulate the embryonic arrangement of the mammalian germ layers and provide an assay to assess the structural and signaling mechanisms patterning the human gastrula. Structurally, high-density hESCs lateralize their TGF-β receptors to their lateral side in the center of the colony, while maintaining apical localization of receptors at the edge. This relocalization insulates cells at the center from apically applied ligands while maintaining response to basally presented ones. Additionally, BMP4 directly induces the expression of its own inhibitor, Noggin, generating a reaction-diffusion mechanism that underlies patterning. We develop a quantitative model that integrates edge sensing and inhibitors, to predict human fate positioning in gastruloids, and potentially the human embryo

Self-organization of human embryonic stem cells on micropatterns

Fate allocation in the gastrulating embryo is spatially organized as cells differentiate into specialized cell types depending on their positions with respect to the body axes. There is a need for in vitro protocols that allow the study of spatial organization associated with this developmental transition. Although embryoid bodies and organoids can exhibit some spatial organization of differentiated cells, methods that generate embryoid bodies or organoids do not yield consistent and fully reproducible results. Here, we describe a micropatterning approach in which human embryonic stem cells are confined to disk-shaped, submillimeter colonies. After 42 h of BMP4 stimulation, cells form self-organized differentiation patterns in concentric radial domains, which express specific markers associated with the embryonic germ layers, reminiscent of gastrulating embryos. Our protocol takes 3 d; it uses commercial microfabricated slides (from CYTOO), human laminin-521 (LN-521) as extracellular matrix coating, and either conditioned or chemically defined medium (mTeSR). Differentiation patterns within individual colonies can be determined by immunofluorescence and analyzed with cellular resolution. Both the size of the micropattern and the type of medium affect the patterning outcome. The protocol is appropriate for personnel with basic stem cell culture training. This protocol describes a robust platform for quantitative analysis of the mechanisms associated with pattern formation at the onset of gastrulation