Physical theory of biological noise buffering by multicomponent phase separation

Maintaining homeostasis is a fundamental characteristic of living systems. In cells, this is contributed to by the assembly of biochemically distinct organelles, many of which are not membrane bound but form by the physical process of liquid–liquid phase separation (LLPS). By analogy with LLPS in binary solutions, cellular LLPS was hypothesized to contribute to homeostasis by facilitating “concentration buffering,” which renders the local protein concentration within the organelle robust to global variations in the average cellular concentration (e.g., due to expression noise). Interestingly, concentration buffering was experimentally measured in vivo in a simple organelle with a single solute, while it was observed not to be obeyed in one with several solutes. Here, we formulate theoretically and solve analytically a physical model of LLPS in a ternary solution of two solutes (ϕ and ψ) that interact both homotypically (ϕ–ϕ attractions) and heterotypically (ϕ–ψ attractions). Our physical theory predicts how the coexisting concentrations in LLPS are related to expression noise and thus, generalizes the concept of concentration buffering to multicomponent systems. This allows us to reconcile the seemingly contradictory experimental observations. Furthermore, we predict that incremental changes of the homotypic and heterotypic interactions among the molecules that undergo LLPS, such as those that are caused by mutations in the genes encoding the proteins, may increase the efficiency of concentration buffering of a given system. Thus, we hypothesize that evolution may optimize concentration buffering as an efficient mechanism to maintain LLPS homeostasis and suggest experimental approaches to test this in different systems.

Genomic Competition for Noise Reduction Shaped Evolutionary Landscape of Mir-4673

The genomic platform that informs evolution of microRNA cascades remains unknown. Here we capitalized on the recent evolutionary trajectory of hominin-specific miRNA-4673 (Dokumcu et al., 2018) encoded in intron 4 of notch-1 to uncover the identity of one such precursor genomic element and the selective forces acting upon it. The miRNA targets genes that regulate Wnt/β-catenin signalling cascade. Primary sequence of the microRNA and its target region in Wnt modulating genes evolved from homologous signatures mapped to homotypic cis-clusters recognised by TCF3/4 and TFAP2A/B/C families. Integration of homologous TFAP2A/B/C cis-clusters (short range inhibitor of β-catenin (Li and Dashwood, 2004)) into the transcriptional landscape of Wnt cascade genes can reduce noise in gene expression (Blake et al., 2003). Probabilistic adoption of miRNA secondary structure by one such cis-signature in notch-1 reflected selection for superhelical curvature symmetry of precursor DNA to localize a nucleosome that overlapped the latter cis-cluster. By replicating the cis-cluster signature, non-random interactions of the miRNA with key Wnt modulator genes expanded the transcriptional noise buffering capacity via a coherent feed-forward loop mechanism (Hornstein and Shomron, 2006). In consequence, an autonomous transcriptional noise dampener (the cis-cluster/nucleosome) evolved into a post-transcriptional one (the miRNA). The findings suggest a latent potential for remodelling of transcriptional landscape by miRNAs that capitalize on non-random distribution of genomic cis-signatures.

Experimental evolution reveals a general role for the methyltransferase Hmt1 in noise buffering

ABSTRACTCell-to-cell heterogeneity within an isogenic population has been observed in prokaryotic and eukaryotic cells. Such heterogeneity often manifests at the level of individual protein abundance and may have evolutionary benefits, especially for organisms in fluctuating environments. Although general features and the origins of cellular noise have been revealed, details of the molecular pathways underlying noise regulation remain elusive. Here, we used experimental evolution of Saccharomyces cerevisiae to select for mutations that increase reporter protein noise. By combining bulk segregant analysis and CRISPR/Cas9-based reconstitution, we identified the methyltransferase Hmt1 as a general regulator of noise buffering. Hmt1 methylation activity is critical for the evolved phenotype, and noise buffering is primarily achieved via two Hmt1 methylation targets. Hmt1 functions as an environmental sensor to adjust noise levels in response to environmental cues. Moreover, Hmt1-mediated noise buffering is conserved in an evolutionarily distant yeast species, suggesting broad significance of noise regulation.Author SummaryCell-to-cell heterogeneity within an isogenic population has been observed in prokaryotic and eukaryotic cells. Such heterogeneity often manifests at the level of individual protein abundance and may have evolutionary benefits, especially for organisms in fluctuating environments. Here, we used experimental evolution of Saccharomyces cerevisiae to select for mutations that increase reporter protein noise and identified the methyltransferase Hmt1 as a general regulator of noise buffering. Hmt1 is a central hub protein that is involved in multiple basic cellular pathways, including chromatin remodeling/transcription, translation, ribosome biogenesis, and post-transcriptional regulation. Our results show that Hmt1 constrains the noise level of multiple cellular pathways under normal conditions, so the physiology of individual cells in a population will not deviate too much from optimal peak fitness. However, when cells encounter environmental stresses, HMT1 is quickly down-regulated and expression noise is enhanced to increase the likelihood of population survival. Moreover, the noise buffering function of Hmt1 is conserved in Schizosaccharomyces pombe that diverged from the common ancestor of Saccharomyces cerevisiae more than 400 million years ago. Since the Hmt1 network is conserved from yeast cells to human, it is quite possible that Hmt1-mediated noise buffering also operates in multicellular organisms.

Deterministic Nature of Cellular Position Noise During C. elegans Embryogenesis

ABSTRACTIndividuals with identical genotypes exhibit great phenotypic variability known as biological noise, which has broad implications. While molecular-level noise has been extensively studied, in-depth analysis of cellular-level noise is challenging. Here, we present a systems-level quantitative and functional analysis of noise in cellular position during embryogenesis, an important phenotype indicating differentiation and morphogenesis. We show that cellular position noise is deterministic, stringently regulated by intrinsic and extrinsic mechanisms. The noise level is determined by cell lineage identity and is coupled to developmental properties including embryonic localization, cell contact, and left-right symmetry. Cells follow a concordant low-high-low pattern of noise dynamics, and fate specification triggers a global down-regulation of noise that provide a noise-buffering strategy. Noise is stringently regulated throughout embryogenesis, especially during cell division and cell adhesion and gap junctions function to restrict noise. Collectively, our study reveals system properties and regulatory mechanisms of cellular noise control during development.

ASYMMETRIC TRANSITION AND TIME-SCALE SEPARATION IN INTERLINKED POSITIVE FEEDBACK LOOPS

In [Brandman et al., 2005] it was proposed that interlinked fast and slow positive feedback loops are a frequent motif in biological signaling, because such a device can allow for a rapid response to an external stimulus (sensitivity) along with a certain noise-buffering capacity (robustness), as soon as the two loops operate on different time scales. Here we explore the properties of the nonlinear system responsible for this behavior. We argue that (a) the noise buffering is not linked to the stochastic nature of the stimulus, but only to the time scale of the stimulus variation compared to the intrinsic time scales of the system, and (b) this buffering of stimulus variations follows from the stabilization of a region of the state space away from the equilibrium branches of the system. Our analysis is based on a slow-fast decomposition of the dynamics. We analyze the strength of this buffering as a function of the time scales involved and the Boolean logic of the coupling between dynamic variables, as well as of the amplitude of the stimulus variations. We underline that such a nonequilibrium regime is universal as soon as the stimulus time scale is smaller than the larger time scale of the system, preventing the prediction of the behavior from the features of the bifurcation diagram or using a linear analysis.