Multiscale chromatin dynamics and high entropy in plant iPSC ancestors.

Plant protoplasts provide a starting material to induce pluripotent cell masses in vitro competent for tissue regeneration. Dedifferentiation is associated with large-scale chromatin reorganisation and massive transcriptome reprogramming, characterized by stochastic gene expression. How this cellular variability reflects on chromatin organisation in individual cells and what are the factors influencing chromatin transitions during culturing is largely unknown. High-throughput imaging and a custom, supervised image analysis protocol extracting over 100 chromatin features unravelled a rapid, multiscale dynamics of chromatin patterns which trajectory strongly depends on nutrients availability. Decreased abundance in H1 (linker histones) is hallmark of chromatin transitions. We measured a high heterogeneity of chromatin patterns indicating an intrinsic entropy as hallmark of the initial cultures. We further measured an entropy decline over time, and an antagonistic influence by external and intrinsic factors, such as phytohormones and epigenetic modifiers, respectively. Collectively, our study benchmarks an approach to understand the variability and evolution of chromatin patterns underlying plant cell reprogramming in vitro.

Dual specificity kinase DYRK3 regulates cell migration by influencing the stability of protrusions.

Plasma membrane-associated platforms (PMAPs) form at specific sites of plasma membrane by scaffolds including ERC1 and Liprin-α1. We identify a mechanism regulating PMAPs assembly, with consequences on motility/invasion. Silencing Ser/Thr kinase DYRK3 in invasive breast cancer cells inhibits their motility and invasive capacity. Similar effects on motility were observed by increasing DYRK3 levels, while kinase-dead DYRK3 had limited effects. DYRK3 overexpression inhibits PMAPs formation and has negative effects on stability of lamellipodia and adhesions in migrating cells. Liprin-α1 depletion results in unstable lamellipodia and impaired cell motility. DYRK3 causes increased Liprin-α1 phosphorylation. Increasing levels of Liprin-α1 rescue the inhibitory effects of DYRK3 on cell spreading, suggesting that an equilibrium between Liprin-α1 and DYRK3 levels is required for lamellipodia stability and tumor cell motility. Our results show that DYRK3 is relevant to tumor cell motility, and identify a PMAP target of the kinase, highlighting a new mechanism regulating cell edge dynamics.

Learning single-cell perturbation responses using neural optimal transport.

Understanding and predicting molecular responses in single cells upon chemical, genetic or mechanical perturbations is a core question in biology. Obtaining single-cell measurements typically requires the cells to be destroyed. This makes learning heterogeneous perturbation responses challenging as we only observe unpaired distributions of perturbed or non-perturbed cells. Here we leverage the theory of optimal transport and the recent advent of input convex neural architectures to present CellOT, a framework for learning the response of individual cells to a given perturbation by mapping these unpaired distributions. CellOT outperforms current methods at predicting single-cell drug responses, as profiled by scRNA-seq and a multiplexed protein-imaging technology. Further, we illustrate that CellOT generalizes well on unseen settings by (1) predicting the scRNA-seq responses of holdout patients with lupus exposed to interferon-ß and patients with glioblastoma to panobinostat; (2) inferring lipopolysaccharide responses across different species; and (3) modeling the hematopoietic developmental trajectories of different subpopulations.

DYRK3 enables secretory trafficking by maintaining the liquid-like state of ER exit sites.

The dual-specificity kinase DYRK3 controls the formation and dissolution of multiple biomolecular condensates, regulating processes including stress recovery and mitotic progression. Here, we report that DYRK3 functionally interacts with proteins associated with endoplasmic reticulum (ER) exit sites (ERESs) and that inhibition of DYRK3 perturbs the organization of the ERES-Golgi interface and secretory trafficking. DYRK3-mediated regulation of ERES depends on the N-terminal intrinsically disordered region (IDR) of the peripheral membrane protein SEC16A, which co-phase separates with ERES components to form liquid-like condensates on the surface of the ER. By modulating the liquid-like properties of ERES, we show that their physical state is essential for functional cargo trafficking through the early secretory pathway. Our findings support a mechanism whereby phosphorylation by DYRK3 and its reversal by serine-threonine phosphatases regulate the material properties of ERES to create a favorable physicochemical environment for directional membrane traffic in eukaryotic cells.

Cellular state landscape and herpes simplex virus type 1 infection progression are connected.

Prediction, prevention and treatment of virus infections require understanding of cell-to-cell variability that leads to heterogenous disease outcomes, but the source of this heterogeneity has yet to be clarified. To study the multimodal response of single human cells to herpes simplex virus type 1 (HSV-1) infection, we mapped high-dimensional viral and cellular state spaces throughout the infection using multiplexed imaging and quantitative single-cell measurements of viral and cellular mRNAs and proteins. Here we show that the high-dimensional cellular state scape can predict heterogenous infections, and cells move through the cellular state landscape according to infection progression. Spatial information reveals that infection changes the cellular state of both infected cells and of their neighbors. The multiplexed imaging of HSV-1-induced cellular modifications links infection progression to changes in signaling responses, transcriptional activity, and processing bodies. Our data show that multiplexed quantification of responses at the single-cell level, across thousands of cells helps predict infections and identify new targets for antivirals.

Iterative Indirect Immunofluorescence Imaging (4i) on Adherent Cells and Tissue Sections.

Highly multiplexed protein measurements from multiple spatial scales using fluorescence microscopy recently emerged as a powerful way to investigate tumor microenvironments in biomedicine and the multivariate nature of complex systems' interactions. A range of methods for this exist, which either rely on directly labeling the primary antibody with oligonucleotides/rare metals or employing methods to remove fluorescence for cyclic acquisition. Here, we describe a protocol that uses off-the-shelf primary and secondary antibodies without further need for modification and only commonly available chemical reagents. The method harnesses the observation that antibodies can crosslink to bound epitopes during light exposure, thus preventing elution. By utilizing a simple oxygen radical scavenging buffer during imaging and by blocking free sulfhydryl groups before antibody incubation, the presented method can employ comparably mild conditions to remove bound antibodies from epitopes, which preserves sample integrity. Thus, with the stated minor modifications, it allows for a standard immunofluorescence imaging protocol in cyclic fashion, currently permitting staining of up to ~80 unique epitopes.

OME-Zarr: a cloud-optimized bioimaging file format with international community support.

A growing community is constructing a next-generation file format (NGFF) for bioimaging to overcome problems of scalability and heterogeneity. Organized by the Open Microscopy Environment (OME), individuals and institutes across diverse modalities facing these problems have designed a format specification process (OME-NGFF) to address these needs. This paper brings together a wide range of those community members to describe the cloud-optimized format itself-OME-Zarr-along with tools and data resources available today to increase FAIR access and remove barriers in the scientific process. The current momentum offers an opportunity to unify a key component of the bioimaging domain-the file format that underlies so many personal, institutional, and global data management and analysis tasks.

Multimodal spatiotemporal phenotyping of human retinal organoid development.

Organoids generated from human pluripotent stem cells provide experimental systems to study development and disease, but quantitative measurements across different spatial scales and molecular modalities are lacking. In this study, we generated multiplexed protein maps over a retinal organoid time course and primary adult human retinal tissue. We developed a toolkit to visualize progenitor and neuron location, the spatial arrangements of extracellular and subcellular components and global patterning in each organoid and primary tissue. In addition, we generated a single-cell transcriptome and chromatin accessibility timecourse dataset and inferred a gene regulatory network underlying organoid development. We integrated genomic data with spatially segmented nuclei into a multimodal atlas to explore organoid patterning and retinal ganglion cell (RGC) spatial neighborhoods, highlighting pathways involved in RGC cell death and showing that mosaic genetic perturbations in retinal organoids provide insight into cell fate regulation.

Learning consistent subcellular landmarks to quantify changes in multiplexed protein maps.

Highly multiplexed imaging holds enormous promise for understanding how spatial context shapes the activity of the genome and its products at multiple length scales. Here, we introduce a deep learning framework called CAMPA (Conditional Autoencoder for Multiplexed Pixel Analysis), which uses a conditional variational autoencoder to learn representations of molecular pixel profiles that are consistent across heterogeneous cell populations and experimental perturbations. Clustering these pixel-level representations identifies consistent subcellular landmarks, which can be quantitatively compared in terms of their size, shape, molecular composition and relative spatial organization. Using high-resolution multiplexed immunofluorescence, this reveals how subcellular organization changes upon perturbation of RNA synthesis, RNA processing or cell size, and uncovers links between the molecular composition of membraneless organelles and cell-to-cell variability in bulk RNA synthesis rates. By capturing interpretable cellular phenotypes, we anticipate that CAMPA will greatly accelerate the systematic mapping of multiscale atlases of biological organization to identify the rules by which context shapes physiology and disease.

OME-Zarr: a cloud-optimized bioimaging file format with international community support.

A growing community is constructing a next-generation file format (NGFF) for bioimaging to overcome problems of scalability and heterogeneity. Organized by the Open Microscopy Environment (OME), individuals and institutes across diverse modalities facing these problems have designed a format specification process (OME-NGFF) to address these needs. This paper brings together a wide range of those community members to describe the cloud-optimized format itself -- OME-Zarr -- along with tools and data resources available today to increase FAIR access and remove barriers in the scientific process. The current momentum offers an opportunity to unify a key component of the bioimaging domain -- the file format that underlies so many personal, institutional, and global data management and analysis tasks.

Multimodal perception links cellular state to decision-making in single cells.

Individual cells make decisions that are adapted to their internal state and surroundings, but how cells can reliably do this remains unclear. To study the information processing capacity of human cells, we conducted multiplexed quantification of signaling responses and markers of the cellular state. Signaling nodes in a network displayed adaptive information processing, which led to heterogeneous growth factor responses and enabled nodes to capture partially nonredundant information about the cellular state. Collectively, as a multimodal percept this gives individual cells a large information processing capacity to accurately place growth factor concentration within the context of their cellular state and make cellular state-dependent decisions. Heterogeneity and complexity in signaling networks may have coevolved to enable specific and context-aware cellular decision-making in a multicellular setting.

Mechanisms of cellular mRNA transcript homeostasis.

For most genes, mRNA transcript abundance scales with cell size to ensure a constant concentration. Scaling of mRNA synthesis rates with cell size plays an important role, with regulation of the activity and abundance of RNA polymerase II (Pol II) now emerging as a key point of control. However, there is also considerable evidence for feedback mechanisms that kinetically couple the rates of mRNA synthesis, nuclear export, and degradation to allow cells to compensate for changes in one by adjusting the others. Researchers are beginning to integrate results from these different fields to reveal the mechanisms underlying transcript homeostasis. This will be crucial for moving beyond our current understanding of relative gene expression towards an appreciation of how absolute transcript levels are linked to other aspects of the cellular phenotype.

Feedback from nuclear RNA on transcription promotes robust RNA concentration homeostasis in human cells.

RNA concentration homeostasis involves coordinating RNA abundance and synthesis rates with cell size. Here, we study this in human cells by combining genome-wide perturbations with quantitative single-cell measurements. Despite relative ease in perturbing RNA synthesis, we find that RNA concentrations generally remain highly constant. Perturbations that would be expected to increase nuclear mRNA levels, including those targeting nuclear mRNA degradation or export, result in downregulation of RNA synthesis. This is associated with reduced abundance of transcription-associated proteins and protein states that are normally coordinated with RNA production in single cells, including RNA polymerase II (RNA Pol II) itself. Acute perturbations, elevation of nuclear mRNA levels, and mathematical modeling indicate that mammalian cells achieve robust mRNA concentration homeostasis by the mRNA-based negative feedback on transcriptional activity in the nucleus. This ultimately acts to coordinate RNA Pol II abundance with nuclear mRNA degradation and export rates and may underpin the scaling of mRNA abundance with cell size.

Non-specific adhesive forces between filaments and membraneless organelles.

Many membraneless organelles are liquid-like domains that form inside the active, viscoelastic environment of living cells through phase separation. To investigate the potential coupling of phase separation with the cytoskeleton, we quantify the structural correlations of membraneless organelles (stress granules) and cytoskeletal filaments (microtubules) in a human-derived epithelial cell line. We find that microtubule networks are substantially denser in the vicinity of stress granules. When microtubules are depolymerized, the sub-units localize near the surface of the stress granules. We interpret these data using a thermodynamic model of partitioning of particles to the surface and bulk of the droplets. In this framework, our data are consistent with a weak (≲k B T) affinity of the microtubule sub-units for stress granule interfaces. As microtubules polymerize, their interfacial affinity increases, providing sufficient adhesion to deform droplets and/or the network. Our work suggests that proteins and other objects in the cell have a non-specific affinity for droplet interfaces that increases with the contact area and becomes most apparent when they have no preference for the interior of a droplet over the rest of the cytoplasm. We validate this basic physical phenomenon in vitro through the interaction of a simple protein-RNA condensate with microtubules.

Erratum: Publisher Correction: Non-specific adhesive forces between filaments and membraneless organelles.

[This corrects the article DOI: 10.1038/s41567-022-01537-8.].

Characterization of the neurogenic niche in the aging dentate gyrus using iterative immunofluorescence imaging.

Advancing age causes reduced hippocampal neurogenesis, associated with age-related cognitive decline. The spatial relationship of age-induced alterations in neural stem cells (NSCs) and surrounding cells within the hippocampal niche remains poorly understood due to limitations of antibody-based cellular phenotyping. We established iterative indirect immunofluorescence imaging (4i) in tissue sections, allowing for simultaneous detection of 18 proteins to characterize NSCs and surrounding cells in 2-, 6-, and 12-month-old mice. We show that reorganization of the dentate gyrus (DG) niche already occurs in middle-aged mice, paralleling the decline in neurogenesis. 4i-based tissue analysis of the DG identifies changes in cell-type contributions to the blood-brain barrier and microenvironments surrounding NSCs to play a pivotal role to preserve neurogenic permissiveness. The data provided represent a resource to characterize the principles causing alterations of stem cell-associated plasticity within the aging DG and provide a blueprint to analyze somatic stem cell niches across lifespan in complex tissues.

High content genome-wide siRNA screen to investigate the coordination of cell size and RNA production.

Coordination of RNA abundance and production rate with cell size has been observed in diverse organisms and cell populations. However, how cells achieve such 'scaling' of transcription with size is unknown. Here we describe a genome-wide siRNA screen to identify regulators of global RNA production rates in HeLa cells. We quantify the single-cell RNA production rate using metabolic pulse-labelling of RNA and subsequent high-content imaging. Our quantitative, single-cell measurements of DNA, nascent RNA, proliferating cell nuclear antigen (PCNA), and total protein, as well as cell morphology and population-context, capture a detailed cellular phenotype. This allows us to account for changes in cell size and cell-cycle distribution (G1/S/G2) in perturbation conditions, which indirectly affect global RNA production. We also take advantage of the subcellular information to distinguish between nascent RNA localised in the nucleolus and nucleoplasm, to approximate ribosomal and non-ribosomal RNA contributions to perturbation phenotypes. Perturbations uncovered through this screen provide a resource for exploring the mechanisms of regulation of global RNA metabolism and its coordination with cellular states.

The Tumor Profiler Study: integrated, multi-omic, functional tumor profiling for clinical decision support.

The application and integration of molecular profiling technologies create novel opportunities for personalized medicine. Here, we introduce the Tumor Profiler Study, an observational trial combining a prospective diagnostic approach to assess the relevance of in-depth tumor profiling to support clinical decision-making with an exploratory approach to improve the biological understanding of the disease.