Dual-role transcription factors stabilize intermediate expression levels.

Precise control of gene expression levels is essential for normal cell functions, yet how they are defined and tightly maintained, particularly at intermediate levels, remains elusive. Here, using a series of newly developed sequencing, imaging, and functional assays, we uncover a class of transcription factors with dual roles as activators and repressors, referred to as condensate-forming level-regulating dual-action transcription factors (TFs). They reduce high expression but increase low expression to achieve stable intermediate levels. Dual-action TFs directly exert activating and repressing functions via condensate-forming domains that compartmentalize core transcriptional unit selectively. Clinically relevant mutations in these domains, which are linked to a range of developmental disorders, impair condensate selectivity and dual-action TF activity. These results collectively address a fundamental question in expression regulation and demonstrate the potential of level-regulating dual-action TFs as powerful effectors for engineering controlled expression levels.

Spatial engineering of E. coli with addressable phase-separated RNAs.

Biochemical processes often require spatial regulation and specific microenvironments. The general lack of organelles in bacteria limits the potential of bioengineering complex intracellular reactions. Here, we demonstrate synthetic membraneless organelles in Escherichia coli termed transcriptionally engineered addressable RNA solvent droplets (TEARS). TEARS are assembled from RNA-binding protein recruiting domains fused to poly-CAG repeats that spontaneously drive liquid-liquid phase separation from the bulk cytoplasm. Targeting TEARS with fluorescent proteins revealed multilayered structures with composition and reaction robustness governed by non-equilibrium dynamics. We show that TEARS provide organelle-like bioprocess isolation for sequestering biochemical pathways, controlling metabolic branch points, buffering mRNA translation rates, and scaffolding protein-protein interactions. We anticipate TEARS to be a simple and versatile tool for spatially controlling E. coli biochemistry. Particularly, the modular design of TEARS enables applications without expression fine-tuning, simplifying the design-build-test cycle of bioengineering.

Pathogenic Mechanisms of Somatic Mutation and Genome Mosaicism in Aging.

Age-related accumulation of postzygotic DNA mutations results in tissue genetic heterogeneity known as somatic mosaicism. Although implicated in aging as early as the 1950s, somatic mutations in normal tissue have been difficult to study because of their low allele fractions. With the recent emergence of cost-effective high-throughput sequencing down to the single-cell level, enormous progress has been made in our capability to quantitatively analyze somatic mutations in human tissue in relation to aging and disease. Here we first review how recent technological progress has opened up this field, providing the first broad sets of quantitative information on somatic mutations in vivo necessary to gain insight into their possible causal role in human aging and disease. We then propose three major mechanisms that can lead from accumulated de novo mutations across tissues to cell functional loss and human disease.

MorphoSeq: Full Single-Cell Transcriptome Dynamics Up to Gastrulation in a Chordate.

Single-cell RNA sequencing (scRNA-seq) provides a leap forward in resolving cellular diversity and developmental trajectories but fails to comprehensively delineate the spatial organization and precise cellular makeup of individual embryos. Here, we reconstruct from scRNA-seq and light sheet imaging data a canonical digital embryo that captures the genome-wide gene expression trajectory of every single cell at every cell division in the 18 lineages up to gastrulation in the ascidian Phallusia mammillata. By using high-coverage scRNA-seq, we devise a computational framework that stratifies single cells of individual embryos into cell types without prior knowledge. Unbiased transcriptome data analysis mapped each cell's physical position and lineage history, yielding the complete history of gene expression at the genome-wide level for every single cell in a developing embryo. A comparison of individual embryos reveals both extensive reproducibility between symmetric embryo sides and a large inter-embryonic variability due to small differences in embryogenesis timing.

Single-Cell Chromatin Modification Profiling Reveals Increased Epigenetic Variations with Aging.

Post-translational modifications of histone proteins and exchanges of histone variants of chromatin are central to the regulation of nearly all DNA-templated biological processes. However, the degree and variability of chromatin modifications in specific human immune cells remain largely unknown. Here, we employ a highly multiplexed mass cytometry analysis to profile the global levels of a broad array of chromatin modifications in primary human immune cells at the single-cell level. Our data reveal markedly different cell-type- and hematopoietic-lineage-specific chromatin modification patterns. Differential analysis between younger and older adults shows that aging is associated with increased heterogeneity between individuals and elevated cell-to-cell variability in chromatin modifications. Analysis of a twin cohort unveils heritability of chromatin modifications and demonstrates that aging-related chromatin alterations are predominantly driven by non-heritable influences. Together, we present a powerful platform for chromatin and immunology research. Our discoveries highlight the profound impacts of aging on chromatin modifications.

A Post-Transcriptional Feedback Mechanism for Noise Suppression and Fate Stabilization.

Diverse biological systems utilize fluctuations ("noise") in gene expression to drive lineage-commitment decisions. However, once a commitment is made, noise becomes detrimental to reliable function, and the mechanisms enabling post-commitment noise suppression are unclear. Here, we find that architectural constraints on noise suppression are overcome to stabilize fate commitment. Using single-molecule and time-lapse imaging, we find that-after a noise-driven event-human immunodeficiency virus (HIV) strongly attenuates expression noise through a non-transcriptional negative-feedback circuit. Feedback is established through a serial cascade of post-transcriptional splicing, whereby proteins generated from spliced mRNAs auto-deplete their own precursor unspliced mRNAs. Strikingly, this auto-depletion circuitry minimizes noise to stabilize HIV's commitment decision, and a noise-suppression molecule promotes stabilization. This feedback mechanism for noise suppression suggests a functional role for delayed splicing in other systems and may represent a generalizable architecture of diverse homeostatic signaling circuits.

Aneuploidy Causes Non-genetic Individuality.

Phenotypic variability is a hallmark of diseases involving chromosome gains and losses, such as Down syndrome and cancer. Allelic variances have been thought to be the sole cause of this heterogeneity. Here, we systematically examine the consequences of gaining and losing single or multiple chromosomes to show that the aneuploid state causes non-genetic phenotypic variability. Yeast cell populations harboring the same defined aneuploidy exhibit heterogeneity in cell-cycle progression and response to environmental perturbations. Variability increases with degree of aneuploidy and is partly due to gene copy number imbalances, suggesting that subtle changes in gene expression impact the robustness of biological networks and cause alternate behaviors when they occur across many genes. As inbred trisomic mice also exhibit variable phenotypes, we further propose that non-genetic individuality is a universal characteristic of the aneuploid state that may contribute to variability in presentation and treatment responses of diseases caused by aneuploidy.

Functional analysis of a random-sequence chromosome reveals a high level and the molecular nature of transcriptional noise in yeast cells.

We measure transcriptional noise in yeast by analyzing chromatin structure and transcription of an 18-kb region of DNA whose sequence was randomly generated. Nucleosomes fully occupy random-sequence DNA, but nucleosome-depleted regions (NDRs) are much less frequent, and there are fewer well-positioned nucleosomes and shorter nucleosome arrays. Steady-state levels of random-sequence RNAs are comparable to yeast mRNAs, although transcription and decay rates are higher. Transcriptional initiation from random-sequence DNA occurs at numerous sites, indicating very low intrinsic specificity of the RNA Pol II machinery. In contrast, poly(A) profiles of random-sequence RNAs are roughly comparable to those of yeast mRNAs, suggesting limited evolutionary restraints on poly(A) site choice. Random-sequence RNAs show higher cell-to-cell variability than yeast mRNAs, suggesting that functional elements limit variability. These observations indicate that transcriptional noise occurs at high levels in yeast, and they provide insight into how chromatin and transcription patterns arise from the evolved yeast genome.

A scalable and robust variance components method reveals insights into the architecture of gene-environment interactions underlying complex traits.

Understanding the contribution of gene-environment interactions (GxE) to complex trait variation can provide insights into disease mechanisms, explain sources of heritability, and improve genetic risk prediction. While large biobanks with genetic and deep phenotypic data hold promise for obtaining novel insights into GxE, our understanding of GxE architecture in complex traits remains limited. We introduce a method to estimate the proportion of trait variance explained by GxE (GxE heritability) and additive genetic effects (additive heritability) across the genome and within specific genomic annotations. We show that our method is accurate in simulations and computationally efficient for biobank-scale datasets. We applied our method to common array SNPs (MAF ≥1%), fifty quantitative traits, and four environmental variables (smoking, sex, age, and statin usage) in unrelated white British individuals in the UK Biobank. We found 68 trait-E pairs with significant genome-wide GxE heritability (p<0.05/200) with a ratio of GxE to additive heritability of ≈6.8% on average. Analyzing ≈8 million imputed SNPs (MAF ≥0.1%), we documented an approximate 28% increase in genome-wide GxE heritability compared to array SNPs. We partitioned GxE heritability across minor allele frequency (MAF) and local linkage disequilibrium (LD) values, revealing that, like additive allelic effects, GxE allelic effects tend to increase with decreasing MAF and LD. Analyzing GxE heritability near genes highly expressed in specific tissues, we find significant brain-specific enrichment for body mass index (BMI) and basal metabolic rate in the context of smoking and adipose-specific enrichment for waist-hip ratio (WHR) in the context of sex.

Quantum Barkhausen noise induced by domain wall cotunneling.

Most macroscopic magnetic phenomena (including magnetic hysteresis) are typically understood classically. Here, we examine the dynamics of a uniaxial rare-earth ferromagnet deep within the quantum regime, so that domain wall motion, and the associated hysteresis, is initiated by quantum nucleation, which then grows into large-scale domain wall motion, which is observable as an unusual form of Barkhausen noise. We observe noncritical behavior in the resulting avalanche dynamics that only can be explained by going beyond traditional renormalization group methods or classical domain wall models. We find that this "quantum Barkhausen noise" exhibits two distinct mechanisms for domain wall movement, each of which is quantum-mechanical, but with very different dependences on an external magnetic field applied transverse to the spin (Ising) axis. These observations can be understood in terms of the correlated motion of pairs of domain walls, nucleated by cotunneling of plaquettes (sections of domain wall), with plaquette pairs correlated by dipolar interactions; this correlation is suppressed by the transverse field. Similar macroscopic correlations may be expected to appear in the hysteresis of other systems with long-range interactions.

Spatially resolved random telegraph fluctuations of a single trap at the Si/SiO2 interface.

We use electrostatic force microscopy to spatially resolve random telegraph noise at the Si/SiO2 interface. Our measurements demonstrate that two-state fluctuations are localized at interfacial traps, with bias-dependent rates and amplitudes. These two-level systems lead to correlated carrier number and mobility fluctuations with a range of characteristic timescales; taken together as an ensemble, they give rise to a [Formula: see text] power spectral trend. Such individual defect fluctuations at the Si/SiO2 interface impair the performance and reliability of nanoscale semiconductor devices and will be a significant source of noise in semiconductor-based quantum sensors and computers. The fluctuations measured here are associated with a four-fold competition of rates, including slow two-state switching on the order of seconds and, in one state, fast switching on the order of nanoseconds which is associated with energy loss.

Shot noise-mitigated secondary electron imaging with ion count-aided microscopy.

Modern science is dependent on imaging on the nanoscale, often achieved through processes that detect secondary electrons created by a highly focused incident charged particle beam. Multiple types of measurement noise limit the ultimate trade-off between the image quality and the incident particle dose, which can preclude useful imaging of dose-sensitive samples. Existing methods to improve image quality do not fundamentally mitigate the noise sources. Furthermore, barriers to assigning a physically meaningful scale make the images qualitative. Here, we introduce ion count-aided microscopy (ICAM), which is a quantitative imaging technique that uses statistically principled estimation of the secondary electron yield. With a readily implemented change in data collection, ICAM substantially reduces source shot noise. In helium ion microscopy, we demonstrate 3[Formula: see text] dose reduction and a good match between these empirical results and theoretical performance predictions. ICAM facilitates imaging of fragile samples and may make imaging with heavier particles more attractive.

Cochlear zinc signaling dysregulation is associated with noise-induced hearing loss, and zinc chelation enhances cochlear recovery.

Exposure to loud noise triggers sensory organ damage and degeneration that, in turn, leads to hearing loss. Despite the troublesome impact of noise-induced hearing loss (NIHL) in individuals and societies, treatment strategies that protect and restore hearing are few and insufficient. As such, identification and mechanistic understanding of the signaling pathways involved in NIHL are required. Biological zinc is mostly bound to proteins, where it plays major structural or catalytic roles; however, there is also a pool of unbound, mobile (labile) zinc. Labile zinc is mostly found in vesicles in secretory tissues, where it is released and plays a critical signaling role. In the brain, labile zinc fine-tunes neurotransmission and sensory processing. However, injury-induced dysregulation of labile zinc signaling contributes to neurodegeneration. Here, we tested whether zinc dysregulation occurs and contributes to NIHL in mice. We found that ZnT3, the vesicular zinc transporter responsible for loading zinc into vesicles, is expressed in cochlear hair cells and the spiral limbus, with labile zinc also present in the same areas. Soon after noise trauma, ZnT3 and zinc levels are significantly increased, and their subcellular localization is vastly altered. Disruption of zinc signaling, either via ZnT3 deletion or pharmacological zinc chelation, mitigated NIHL, as evidenced by enhanced auditory brainstem responses, distortion product otoacoustic emissions, and number of hair cell synapses. These data reveal that noise-induced zinc dysregulation is associated with cochlear dysfunction and recovery after NIHL, and point to zinc chelation as a potential treatment for mitigating NIHL.

Screening p-hackers: Dissemination noise as bait.

We show that adding noise before publishing data effectively screens [Formula: see text]-hacked findings: spurious explanations produced by fitting many statistical models (data mining). Noise creates "baits" that affect two types of researchers differently. Uninformed [Formula: see text]-hackers, who are fully ignorant of the true mechanism and engage in data mining, often fall for baits. Informed researchers, who start with an ex ante hypothesis, are minimally affected. We show that as the number of observations grows large, dissemination noise asymptotically achieves optimal screening. In a tractable special case where the informed researchers' theory can identify the true causal mechanism with very few data, we characterize the optimal level of dissemination noise and highlight the relevant trade-offs. Dissemination noise is a tool that statistical agencies currently use to protect privacy. We argue this existing practice can be repurposed to screen [Formula: see text]-hackers and thus improve research credibility.

Dark continuous noise from mutant G90D-rhodopsin predominantly underlies congenital stationary night blindness.

Congenital stationary night blindness (CSNB) is an inherited retinal disease that causes a profound loss of rod sensitivity without severe retinal degeneration. One well-studied rhodopsin point mutant, G90D-Rho, is thought to cause CSNB because of its constitutive activity in darkness causing rod desensitization. However, the nature of this constitutive activity and its precise molecular source have not been resolved for almost 30 y. In this study, we made a knock-in (KI) mouse line with a very low expression of G90D-Rho (equal in amount to ~0.1% of normal rhodopsin, WT-Rho, in WT rods), with the remaining WT-Rho replaced by REY-Rho, a mutant with a very low efficiency of activating transducin due to a charge reversal of the highly conserved ERY motif to REY. We observed two kinds of constitutive noise: one being spontaneous isomerization (R*) of G90D-Rho at a molecular rate (R* s-1) 175-fold higher than WT-Rho and the other being G90D-Rho-generated dark continuous noise comprising low-amplitude unitary events occurring at a very high molecular rate equivalent in effect to ~40,000-fold of R* s-1 from WT-Rho. Neither noise type originated from G90D-Opsin because exogenous 11-cis-retinal had no effect. Extrapolating the above observations at low (0.1%) expression of G90D-Rho to normal disease exhibited by a KI mouse model with RhoG90D/WTand RhoG90D/G90D genotypes predicts the disease condition very well quantitatively. Overall, the continuous noise from G90D-Rho therefore predominates, constituting the major equivalent background light causing rod desensitization in CSNB.

Mitotic checkpoint gene expression is tuned by codon usage bias.

The mitotic checkpoint (also called spindle assembly checkpoint, SAC) is a signaling pathway that safeguards proper chromosome segregation. Correct functioning of the SAC depends on adequate protein concentrations and appropriate stoichiometries between SAC proteins. Yet very little is known about the regulation of SAC gene expression. Here, we show in the fission yeast Schizosaccharomyces pombe that a combination of short mRNA half-lives and long protein half-lives supports stable SAC protein levels. For the SAC genes mad2+ and mad3+ , their short mRNA half-lives are caused, in part, by a high frequency of nonoptimal codons. In contrast, mad1+ mRNA has a short half-life despite a higher frequency of optimal codons, and despite the lack of known RNA-destabilizing motifs. Hence, different SAC genes employ different strategies of expression. We further show that Mad1 homodimers form co-translationally, which may necessitate a certain codon usage pattern. Taken together, we propose that the codon usage of SAC genes is fine-tuned to ensure proper SAC function. Our work shines light on gene expression features that promote spindle assembly checkpoint function and suggests that synonymous mutations may weaken the checkpoint.

Basic and Translational Neuroscience of Childhood-Onset Dystonia: A Control-Theory Perspective.

Dystonia is a collection of symptoms with involuntary muscle activation causing hypertonia, hyperkinetic movements, and overflow. In children, dystonia can have numerous etiologies with varying neuroanatomic distribution. The semiology of dystonia can be explained by gain-of-function failure of a feedback controller that is responsible for stabilizing posture and movement. Because postural control is maintained by a widely distributed network, many different anatomic regions may be responsible for symptoms of dystonia, although all features of dystonia can be explained by uncontrolled activation or hypersensitivity of motor cortical regions that can cause increased reflex gain, inserted postures, or sensitivity to irrelevant sensory variables. Effective treatment of dystonia in children requires an understanding of the relationship between etiology, anatomy, and the specific mechanism of failure of postural stabilization.

Cognition as a Window into Neuronal Population Space.

Understanding how cognitive processes affect the responses of sensory neurons may clarify the relationship between neuronal population activity and behavior. However, tools for analyzing neuronal activity have not kept up with technological advances in recording from large neuronal populations. Here, we describe prevalent hypotheses of how cognitive processes affect sensory neurons, driven largely by a model based on the activity of single neurons or pools of neurons as the units of computation. We then use simple simulations to expand this model to a new conceptual framework that focuses on subspaces of population activity as the relevant units of computation, uses comparisons between brain areas or to behavior to guide analyses of these subspaces, and suggests that population activity is optimized to decode the large variety of stimuli and tasks that animals encounter in natural behavior. This framework provides new ways of understanding the ever-growing quantity of recorded population activity data.

On the origins of developmental robustness: modeling buffering mechanisms against cell-level noise.

During development, cells are subject to stochastic fluctuations in their positions (i.e. cell-level noise) that can potentially lead to morphological noise (i.e. stochastic differences between morphologies that are expected to be equal, e.g. the right and left sides of bilateral organisms). In this study, we explore new and existing hypotheses on buffering mechanisms against cell-level noise. Many of these hypotheses focus on how the boundaries between territories of gene expression remain regular and well defined, despite cell-level noise and division. We study these hypotheses and how irregular territory boundaries lead to morphological noise. To determine the consistency of the different hypotheses, we use a general computational model of development: EmbryoMaker. EmbryoMaker can implement arbitrary gene networks regulating basic cell behaviors (contraction, adhesion, etc.), signaling and tissue biomechanics. We found that buffering mechanisms based on the orientation of cell divisions cannot lead to regular boundaries but that other buffering mechanisms can (homotypic adhesion, planar contraction, non-dividing boundaries, constant signaling and majority rule hypotheses). We also explore the effects of the shape and size of the territories on morphological noise.

Collective signalling drives rapid jumping between cell states.

Development can proceed in 'fits and starts', with rapid transitions between cell states involving concerted transcriptome-wide changes in gene expression. However, it is not clear how these transitions are regulated in complex cell populations, in which cells receive multiple inputs. We address this issue using Dictyostelium cells undergoing development in their physiological niche. A continuous single cell transcriptomics time series identifies a sharp 'jump' in global gene expression marking functionally different cell states. By simultaneously imaging the physiological dynamics of transcription and signalling, we show the jump coincides with the onset of collective oscillations of cAMP. Optogenetic control of cAMP pulses shows that different jump genes respond to distinct dynamic features of signalling. Late jump gene expression changes are almost completely dependent on cAMP, whereas transcript changes at the onset of the jump require additional input. The coupling of collective signalling with gene expression is a potentially powerful strategy to drive robust cell state transitions in heterogeneous signalling environments. Based on the context of the jump, we also conclude that sharp gene expression transitions may not be sufficient for commitment.