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Incomplete understanding of the metastatic process hinders personalized therapy. Here we report the most comprehensive whole-genome study of colorectal metastases vs. matched primary tumors. 65% of somatic mutations originate from a common progenitor, with 15% being tumor- and 19% metastasis-specific, implicating a higher mutation rate in metastases. Tumor- and metastasis-specific mutations harbor elevated levels of BRCAness. We confirm multistage progression with new components ARHGEF7/ARHGEF33 . Recurrently mutated non-coding elements include ncRNAs RP11-594N15.3, AC010091, SNHG14 , 3’ UTRs of FOXP2, DACH2, TRPM3, XKR4, ANO5, CBL, CBLB , the latter four potentially dual protagonists in metastasis and efferocytosis-/ PD-L1 mediated immunosuppression. Actionable metastasis-specific lesions include FAT1, FGF1, BRCA2, KDR , and AKT2 -, AKT3 -, and PDGFRA -3’ UTRs. Metastasis specific mutations are enriched in PI3K-Akt signaling, cell adhesion, ECM and hepatic stellate activation genes, suggesting genetic programs for site-specific colonization. Our results put forward hypotheses on tumor and metastasis evolution, and evidence for metastasis-specific events relevant for personalized therapy. The evolution and genetic nature of metastatic lesions is not completely characterized. Here the authors perform a comprehensive whole-genome study of colorectal metastases in comparison to matched primary tumors and define a multistage progression model and metastasis-specific changes that, in part, are therapeutically actionable.

The creation of orthogonal ‘AND’ logic gates by combining DNA-binding proteins into complex, layered circuits opens the way to the design of programmable integrated circuits in synthetic biology. New levels of complexity for synthetic gene circuits Synthetic genetic circuits tend to interfere with one another, a complication that restricts the number of circuits that can be used to program a cell. Chris Voigt and colleagues have mined a collection of DNA-binding proteins that depend on specific 'chaperone' proteins to activate the transcription of their target genes, and combined them into complex, layered circuits of orthogonal 'AND' logic gates. Using this system, the authors constructed one of the largest genetic programs built so far, consisting of seven integrated sensors/circuits and eleven regulatory proteins. This work opens the way for the design of programmable integrated circuits in synthetic biology. Genetic programs function to integrate environmental sensors, implement signal processing algorithms and control expression dynamics 1 . These programs consist of integrated genetic circuits that individually implement operations ranging from digital logic to dynamic circuits 2 , 3 , 4 , 5 , 6 , and they have been used in various cellular engineering applications, including the implementation of process control in metabolic networks and the coordination of spatial differentiation in artificial tissues. A key limitation is that the circuits are based on biochemical interactions occurring in the confined volume of the cell, so the size of programs has been limited to a few circuits 1 , 7 . Here we apply part mining and directed evolution to build a set of transcriptional AND gates in Escherichia coli . Each AND gate integrates two promoter inputs and controls one promoter output. This allows the gates to be layered by having the output promoter of an upstream circuit serve as the input promoter for a downstream circuit. Each gate consists of a transcription factor that requires a second chaperone protein to activate the output promoter. Multiple activator–chaperone pairs are identified from type III secretion pathways in different strains of bacteria. Directed evolution is applied to increase the dynamic range and orthogonality of the circuits. These gates are connected in different permutations to form programs, the largest of which is a 4-input AND gate that consists of 3 circuits that integrate 4 inducible systems, thus requiring 11 regulatory proteins. Measuring the performance of individual gates is sufficient to capture the behaviour of the complete program. Errors in the output due to delays (faults), a common problem for layered circuits, are not observed. This work demonstrates the successful layering of orthogonal logic gates, a design strategy that could enable the construction of large, integrated circuits in single cells.

Single-cell analysis of the adult human brain is facilitated by improved methods for RNA-seq and hypersensitive-site mapping. Detailed characterization of the cell types in the human brain requires scalable experimental approaches to examine multiple aspects of the molecular state of individual cells, as well as computational integration of the data to produce unified cell-state annotations. Here we report improved high-throughput methods for single-nucleus droplet-based sequencing (snDrop-seq) and single-cell transposome hypersensitive site sequencing (scTHS-seq). We used each method to acquire nuclear transcriptomic and DNA accessibility maps for >60,000 single cells from human adult visual cortex, frontal cortex, and cerebellum. Integration of these data revealed regulatory elements and transcription factors that underlie cell-type distinctions, providing a basis for the study of complex processes in the brain, such as genetic programs that coordinate adult remyelination. We also mapped disease-associated risk variants to specific cellular populations, which provided insights into normal and pathogenic cellular processes in the human brain. This integrative multi-omics approach permits more detailed single-cell interrogation of complex organs and tissues.

Although the main task of a neuroprogenitor is to produce more cells, it may not always produce the same cells. Some progenitors produce different daughter neurons as an embryo develops. Concurrently, these daughter neurons are also transitioning through states toward maturation. Telley et al. used single-cell RNA sequencing to survey the transcriptional identity of cells early in mouse brain development. As a neuroprogenitor transitioned to new states, it produced daughter neurons that reflect those new states. The neuron's own postmitotic differentiation program is apparently overlaid onto these parentally supplied programs, driving emergence of specialized neuronal cell types in the neocortex. Science , this issue p. eaav2522 During corticogenesis in the brain, temporally dynamic molecular birthmarks in progenitors act as seeds for later neuronal diversity. During corticogenesis, distinct subtypes of neurons are sequentially born from ventricular zone progenitors. How these cells are molecularly temporally patterned is poorly understood. We used single-cell RNA sequencing at high temporal resolution to trace the lineage of the molecular identities of successive generations of apical progenitors (APs) and their daughter neurons in mouse embryos. We identified a core set of evolutionarily conserved, temporally patterned genes that drive APs from internally driven to more exteroceptive states. We found that the Polycomb repressor complex 2 (PRC2) epigenetically regulates AP temporal progression. Embryonic age–dependent AP molecular states are transmitted to their progeny as successive ground states, onto which essentially conserved early postmitotic differentiation programs are applied, and are complemented by later-occurring environment-dependent signals. Thus, epigenetically regulated temporal molecular birthmarks present in progenitors act in their postmitotic progeny to seed adult neuronal diversity.

Measurement of the location of molecules in tissues is essential for understanding tissue formation and function. Previously, we developed Slide-seq, a technology that enables transcriptome-wide detection of RNAs with a spatial resolution of 10 μm. Here we report Slide-seqV2, which combines improvements in library generation, bead synthesis and array indexing to reach an RNA capture efficiency ~50% that of single-cell RNA-seq data (~10-fold greater than Slide-seq), approaching the detection efficiency of droplet-based single-cell RNA-seq techniques. First, we leverage the detection efficiency of Slide-seqV2 to identify dendritically localized mRNAs in neurons of the mouse hippocampus. Second, we integrate the spatial information of Slide-seqV2 data with single-cell trajectory analysis tools to characterize the spatiotemporal development of the mouse neocortex, identifying underlying genetic programs that were poorly sampled with Slide-seq. The combination of near-cellular resolution and high transcript detection efficiency makes Slide-seqV2 useful across many experimental contexts. An improved method for spatial transcriptomics with detection efficiency approaching that of droplet-based single-cell RNA-seq techniques.

Molecular characterization of the individual cell types in human kidney as well as model organisms are critical in defining organ function and understanding translational aspects of biomedical research. Previous studies have uncovered gene expression profiles of several kidney glomerular cell types, however, important cells, including mesangial (MCs) and glomerular parietal epithelial cells (PECs), are missing or incompletely described, and a systematic comparison between mouse and human kidney is lacking. To this end, we use Smart-seq2 to profile 4332 individual glomerulus-associated cells isolated from human living donor renal biopsies and mouse kidney. The analysis reveals genetic programs for all four glomerular cell types (podocytes, glomerular endothelial cells, MCs and PECs) as well as rare glomerulus-associated macula densa cells. Importantly, we detect heterogeneity in glomerulus-associated Pdgfrb -expressing cells, including bona fide intraglomerular MCs with the functionally active phagocytic molecular machinery, as well as a unique mural cell type located in the central stalk region of the glomerulus tuft. Furthermore, we observe remarkable species differences in the individual gene expression profiles of defined glomerular cell types that highlight translational challenges in the field and provide a guide to design translational studies. The molecular identity of renal glomerular cells is poorly characterized and rodent glomerulopathy models translate poorly to humans. Here, the authors show molecular signatures of glomerulus-associated cells using single cell RNA sequencing and highlight differences between mouse and human cells.

Engineering mammalian cells to carry out sophisticated and customizable genetic programs requires a toolkit of multiple orthogonal and well-characterized transcription factors (TFs). To address this need, we develop the COmposable Mammalian Elements of Transcription (COMET)—an ensemble of TFs and promoters that enable the design and tuning of gene expression to an extent not, to the best of our knowledge, previously possible. COMET currently comprises 44 activating and 12 inhibitory zinc-finger TFs and 83 cognate promoters, combined in a framework that readily accommodates new parts. This system can tune gene expression over three orders of magnitude, provides chemically inducible control of TF activity, and enables single-layer Boolean logic. We also develop a mathematical model that provides mechanistic insights into COMET performance characteristics. Altogether, COMET enables the design and construction of customizable genetic programs in mammalian cells. Engineering mammalian cellular functions requires a toolkit of orthogonal and well-characterized genetic components. Here the authors develop COMET: an ensemble of transcription factors, promoters, and accompanying models for the design and construction of genetic programs.

The interplay of transcription factors and cis-regulatory elements (CREs) orchestrates the dynamic and diverse genetic programs that assemble the human central nervous system (CNS) during development and maintain its function throughout life. Genetic variation within CREs plays a central role in phenotypic variation in complex traits including the risk of developing disease. We took advantage of the retina, a well-characterized region of the CNS known to be affected by pathogenic variants in CREs, to establish a roadmap for characterizing regulatory variation in the human CNS. This comprehensive analysis of tissue-specific regulatory elements, transcription factor binding, and gene expression programs in three regions of the human visual system (retina, macula, and retinal pigment epithelium/choroid) reveals features of regulatory element evolution that shape tissue-specific gene expression programs and defines regulatory elements with the potential to contribute to Mendelian and complex disorders of human vision.

Neural control of the function of visceral organs is essential for homeostasis and health. Intestinal peristalsis is critical for digestive physiology and host defence, and is often dysregulated in gastrointestinal disorders 1 . Luminal factors, such as diet and microbiota, regulate neurogenic programs of gut motility 2 – 5 , but the underlying molecular mechanisms remain unclear. Here we show that the transcription factor aryl hydrocarbon receptor (AHR) functions as a biosensor in intestinal neural circuits, linking their functional output to the microbial environment of the gut lumen. Using nuclear RNA sequencing of mouse enteric neurons that represent distinct intestinal segments and microbiota states, we demonstrate that the intrinsic neural networks of the colon exhibit unique transcriptional profiles that are controlled by the combined effects of host genetic programs and microbial colonization. Microbiota-induced expression of AHR in neurons of the distal gastrointestinal tract enables these neurons to respond to the luminal environment and to induce expression of neuron-specific effector mechanisms. Neuron-specific deletion of Ahr , or constitutive overexpression of its negative feedback regulator CYP1A1, results in reduced peristaltic activity of the colon, similar to that observed in microbiota-depleted mice. Finally, expression of Ahr in the enteric neurons of mice treated with antibiotics partially restores intestinal motility. Together, our experiments identify AHR signalling in enteric neurons as a regulatory node that integrates the luminal environment with the physiological output of intestinal neural circuits to maintain gut homeostasis and health. In a mouse model, aryl hydrocarbon receptor signalling in enteric neurons is revealed as a mechanism that helps to maintain gut homeostasis by integrating the luminal environment with the physiology of intestinal neural circuits.

Unavoidable circuit–host interactions confound the modularity of engineered synthetic gene circuits.Unintuitive emergent dynamics can be better understood by incorporating the influence of feedback context factors into the system.Mechanistic understanding of the intricate relationships between circuits and hosts enhances our ability to predict and control them.Complementary control strategies can be incorporated into circuit design to mitigate unwanted effects.Early identification of context-dependent modes of failure can accelerate circuit development. Cells provide dynamic platforms for executing exogenous genetic programs in synthetic biology, resulting in highly context-dependent circuit performance. Recent years have seen an increasing interest in understanding the intricacies of circuit–host relationships, their influence on the synthetic bioengineering workflow, and in devising strategies to alleviate undesired effects. We provide an overview of how emerging circuit–host interactions, such as growth feedback and resource competition, impact both deterministic and stochastic circuit behaviors. We also emphasize control strategies for mitigating these unwanted effects. This review summarizes the latest advances and the current state of host-aware and resource-aware design of synthetic gene circuits. Cells provide dynamic platforms for executing exogenous genetic programs in synthetic biology, resulting in highly context-dependent circuit performance. Recent years have seen an increasing interest in understanding the intricacies of circuit–host relationships, their influence on the synthetic bioengineering workflow, and in devising strategies to alleviate undesired effects. We provide an overview of how emerging circuit–host interactions, such as growth feedback and resource competition, impact on both deterministic and stochastic circuit behaviors. We also emphasize control strategies for mitigating these unwanted effects. This review summarizes the latest advances and the current state of host-aware and resource-aware design of synthetic gene circuits.