MicroRNAs (miRNAs) are short, highly conserved non-coding RNA molecules that repress gene expression in a sequence-dependent manner. We performed single-cell measurements using quantitative fluorescence microscopy and flow cytometry to monitor a target gene’s protein expression in the presence and absence of regulation by miRNA. We find that while the average level of repression is modest, in agreement with previous population-based measurements, the repression among individual cells varies dramatically. In particular, we show that regulation by miRNAs establishes a threshold level of target messenger RNA (mRNA) below which protein production is highly repressed. Near this threshold, protein expression responds sensitively to target mRNA input, consistent with a mathematical model of molecular titration. These results demonstrate that miRNAs can act both as a switch and as a fine-tuner of gene expression.

An important aim of synthetic biology is to uncover the design principles of natural biological systems through the rational design of gene and protein circuits. Here we highlight how the process of engineering biological systems — from synthetic promoters to the control of cell–cell interactions — has contributed to our understanding of how endogenous systems are put together and function. Synthetic biological devices allow us to intuitively grasp the ranges of behavior generated by simple biological circuits, such as linear cascades and interlocking feedback loops, as well as to exert control over natural processes such as gene expression and population dynamics.

Summary paragraph: During ontogeny, proliferating cells become restricted in their fate through the combined action of cell-type specific transcription factors and ubiquitous epigenetic machinery, which recognize universally available histone residues or nucleotides but are nonetheless deployed in a highly context-dependent manner 1 , 2 . The molecular functions of these regulators are generally well understood, but assigning direct developmental roles is hampered by complex mutant phenotypes that often emerge following gastrulation 3 , 4 . Recently, single-cell RNA sequencing (scRNA-seq) and analytical approaches have explored this highly conserved process across numerous model organisms 5 – 8 , including mouse 9 – 18 . To elaborate on these strategies, we investigated a panel of ten essential regulators using a combined zygotic perturbation, scRNA-seq platform where many mutant embryos can be assayed simultaneously to recover robust transcriptional and morphological information. Deeper analysis of central Polycomb Repressive Complex (PRC) 1 and 2 members indicate substantial cooperativity, but distinguishes a PRC2-dominant role in restricting the germline that emerges from gross molecular changes within the initial conceptus. We believe our experimental framework will eventually allow for a fully quantitative view of how cellular diversity emerges using an identical genetic template and from a single totipotent cell.

The remarkably stable circadian oscillations of single cyanobacteria enable a population of growing cells to maintain synchrony for weeks. The cyanobacterial pacemaker is a post-translational regulation (PTR) circuit that generates circadian oscillations in the phosphorylation state of the clock protein, KaiC. Layered on top of the PTR is transcriptional-translational feedback regulation (TTR), common to all circadian systems, consisting of a negative feedback loop in which KaiC regulates its own production. We demonstrate that the PTR circuit is sufficient to generate oscillations in growing cyanobacteria. However, in the absence of TTR individual oscillators were less stable and synchrony was not maintained in a population of cells. Experimentally-constrained, mathematical modeling reproduced sustained oscillations in the PTR circuit alone and the importance of TTR for oscillator synchrony.

Fluctuations in organelle abundance can profoundly limit the precision of cell biological processes from secretion to metabolism. We modeled the dynamics of organelle biogenesis and predicted that organelle abundance fluctuations depend strongly on the specific mechanisms that increase or decrease the number of a given organelle. Our model exactly predicts the size of experimentally measured Golgi apparatus and vacuole abundance fluctuations, suggesting that cells tolerate the maximum level of variability generated by the Golgi and vacuole biogenesis pathways. We observe large increases in peroxisome abundance fluctuations when cells are transferred from glucose-rich to fatty acid-rich environments. These increased fluctuations are significantly diminished in mutants lacking peroxisome fission factors, leading us to infer that peroxisome biogenesis switches from de novo synthesis to primarily fission. Our work provides a general framework for exploring stochastic organelle biogenesis and using fluctuations to quantitatively unravel the biophysical pathways that control the abundance of subcellular structures.

Probes that form covalent bonds with RNA molecules based on their chemical reactivity would advance our ability to study the transcriptome. We developed a set of electrophilic activity-based RNA probes designed to react with unusually nucleophilic RNAs. We used these probes to identify reactive genome-encoded RNAs, resulting in the discovery of a 42-nt catalytic RNA from an archaebacterium that reacts with a 2,3-disubstituted epoxide at N7 of a specific guanosine. Detailed characterization of the catalytic RNA revealed the structural requirements for reactivity. We developed this catalytic RNA into a general tool to selectively conjugate a small molecule to an RNA of interest. This strategy enabled up to 500-fold enrichment of target RNA from total mammalian RNA or from cell lysate. We demonstrated the utility of this approach by selectively capturing proteins in yeast cell lysate that bind to the ASH1 mRNA.

Among the most important processes in the self-assembly of the eukaryotic cell is the synthesis of its organelles, specialized biochemical compartments that house processes crucial to cellular physiology. A critical property that governs organelle function is its size. Numerous molecular factors that regulate the sizes of a diverse array of organelles, including the Golgi, mitochondria, peroxisomes and lipid droplets among others, have been identified. However, our understanding of the quantitative principles governing organelle size control remains incomplete. Here, we combine organelle size data from the single-celled eukaryote Saccharomyces cerevisiae and mathematical theory to show that cells can robustly control organelle size fluctuations across a range of organelle sizes. In particular, our framework suggests that organelle size increases in random bursts from a limited pool of building blocks. Bursty organelle growth allows the cell to decouple the average magnitude of organelle size fluctuations from mean organelle size, provided the bursts do not deplete the pool of building blocks from which organelles grow. Bursty growth thus provides a potentially general mechanism by which cells can regulate the noise of the sizes of its subcellular structures.

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