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For more than a century, abnormal nuclei in tumor cells, presenting subnuclear invaginations and folds on the nuclear envelope, have been known to be associated with high malignancy and poor prognosis. However, current nuclear morphology analysis focuses on the features of the entire nucleus, overlooking the malignancy-related subnuclear features in nanometer scale. The main technical challenge is to probe such tiny and randomly distributed features inside cells. We here employ nanopillar arrays to guide subnuclear features into ordered patterns, enabling their quantification as a strong indicator of cell malignancy. Both breast and liver cancer cells were validated as well as the quantification of nuclear abnormality heterogeneity. The alterations of subnuclear patterns were also explored as effective readouts for drug treatment. We envision that this nanopillar-enabled quantification of subnuclear abnormal features in tumor cells opens a new angle in characterizing malignant cells and studying the unique nuclear biology in cancer. Ministry of Education (MOE) Nanyang Technological University National Research Foundation (NRF) This work is supported by the Singapore Ministry of Education (MOE) (W.Z., RG145/18 and RG112/20), the Singapore National Research Foundation (W.Z., NRF2019-NRF-ISF003- 3292), the Institute for Digital Molecular Analytics and Science (IDMxS) supported by MOE funding under the Research Centres of Excellence scheme (W.Z.), the NTU Start-up Grant (W.Z.), the NTU-NNI Neurotechnology Fellowship (W.Z.), and AIRC IG-24614 and Sapienza AR1181642EE61111 (I.S.).

The development of single-cell methods for capturing different data modalities including imaging and sequencing has revolutionized our ability to identify heterogeneous cell states. Different data modalities provide different perspectives on a population of cells, and their integration is critical for studying cellular heterogeneity and its function. While various methods have been proposed to integrate different sequencing data modalities, coupling imaging and sequencing has been an open challenge. We here present an approach for integrating vastly different modalities by learning a probabilistic coupling between the different data modalities using autoencoders to map to a shared latent space. We validate this approach by integrating single-cell RNA-seq and chromatin images to identify distinct subpopulations of human naive CD4+ T-cells that are poised for activation. Collectively, our approach provides a framework to integrate and translate between data modalities that cannot yet be measured within the same cell for diverse applications in biomedical discovery., Nature Communications, 12 (1), ISSN:2041-1723

Over the course of the aging process, fibroblasts lose contractility, leading to reduced connective-tissue stiffness. A promising therapeutic avenue for functional rejuvenation of connective tissue is reprogrammed fibroblast replacement, although major hurdles still remain. Toward this, we recently demonstrated that the laterally confined growth of fibroblasts on micropatterned substrates induces stem-cell-like spheroids. In this study, we embedded these partially reprogrammed spheroids in collagen-I matrices of varying densities, mimicking different three-dimensional (3D) tissue constraints. In response to such matrix constraints, these spheroids regained their fibroblastic properties and sprouted to form 3D connective-tissue networks. Interestingly, we found that these differentiated fibroblasts exhibit reduced DNA damage, enhanced cytoskeletal gene expression, and actomyosin contractility. In addition, the rejuvenated fibroblasts show increased matrix protein (fibronectin and laminin) deposition and collagen remodeling compared to the parental fibroblast tissue network. Furthermore, we show that the partially reprogrammed cells have comparatively open chromatin compaction states and may be more poised to redifferentiate into contractile fibroblasts in 3D-collagen matrix. Collectively, our results highlight efficient fibroblast rejuvenation through laterally confined reprogramming, which has important implications in regenerative medicine., Proceedings of the National Academy of Sciences of the United States of America, 117 (19), ISSN:0027-8424, ISSN:1091-6490

Cells sense mechanical signals from their microenvironment and transduce them to the nucleus to regulate gene expression programs. To elucidate the physical mechanisms involved in this regulation, we developed an active 3D chemomechanical model to describe the three-way feedback between the adhesions, the cytoskeleton, and the nucleus. The model shows local tensile stresses generated at the interface of the cell and the extracellular matrix regulate the properties of the nucleus, including nuclear morphology, levels of lamin A,C, and histone deacetylation, as these tensile stresses 1) are transmitted to the nucleus through cytoskeletal physical links and 2) trigger an actomyosin-dependent shuttling of epigenetic factors. We then show how cell geometric constraints affect the local tensile stresses and subsequently the three-way feedback and induce cytoskeleton-mediated alterations in the properties of the nucleus such as nuclear lamina softening, chromatin stiffening, nuclear lamina invaginations, increase in nuclear height, and shrinkage of nuclear volume. We predict a phase diagram that describes how the disruption of cytoskeletal components impacts the feedback and subsequently induce contractility-dependent alterations in the properties of the nucleus. Our simulations show that these changes in contractility levels can be also used as predictors of nucleocytoplasmic shuttling of transcription factors and the level of chromatin condensation. The predictions are experimentally validated by studying the properties of nuclei of fibroblasts on micropatterned substrates with different shapes and areas.

We analyse the stem cell nucleus shape fluctuation spectrum obtained from optical confocal microscopy on an hour time scale with 10 s resolution. In particular, we investigate the angular and time dependencies of these fluctuations, define appropriate correlation functions that reveal the fundamentally out of equilibrium nature of the observed fluctuations as well as their global anisotropy. Langevin equations respecting the symmetry of the system allow us to model the damped oscillatory behaviour of the time correlations.

Given the severity of the SARS-CoV-2 pandemic, a major challenge is to rapidly repurpose existing approved drugs for clinical interventions. While a number of data-driven and experimental approaches have been suggested in the context of drug repurposing, a platform that systematically integrates available transcriptomic, proteomic and structural data is missing. More importantly, given that SARS-CoV-2 pathogenicity is highly age-dependent, it is critical to integrate aging signatures into drug discovery platforms. We here take advantage of large-scale transcriptional drug screens combined with RNA-seq data of the lung epithelium with SARS-CoV-2 infection as well as the aging lung. To identify robust druggable protein targets, we propose a principled causal framework that makes use of multiple data modalities. Our analysis highlights the importance of serine/threonine and tyrosine kinases as potential targets that intersect the SARS-CoV-2 and aging pathways. By integrating transcriptomic, proteomic and structural data that is available for many diseases, our drug discovery platform is broadly applicable. Rigorous in vitro experiments as well as clinical trials are needed to validate the identified candidate drugs., Nature Communications, 12 (1), ISSN:2041-1723

The supplementary information file includes notes clarifying the materials and methods mentioned in the main manuscript such as "Boundary Detection", "Derivation of the contour amplitude", "Fourier analysis", "correlation equations", and "Asymmetry of cross-correlation functions and irreversibility".

Fibroblasts are a heterogeneous group of cells comprising subpopulations that have been found to be activated in the stromal microenvironment that regulates tumor initiation and growth. The underlying mechanisms of such selective activation of fibroblasts are not understood. We propose that the intrinsic geometric heterogeneity of fibroblasts modulates the nuclear mechanotransduction of signals from the microenvironment, resulting in their selective activation. To test this, we developed an engineered 3D fibroblast tumor coculture system and used high resolution images to quantify multiple cell geometry sensitive nuclear morphological and chromatin organizational features. These features were then mapped to activation levels as measured by the nuclear abundance of transcription cofactor, megakaryoblastic leukemia, and protein levels of its target, αSMA. Importantly, our results indicate the presence of activation-“primed” cell geometries that present higher activation levels, which are further enhanced in the presence of stimuli from cancer cells. Further, we show that by enriching the population of activation-primed cell geometric states by either increasing matrix rigidity or micropatterning primed cell shapes, fibroblast activation levels can be increased. Collectively, our results reveal important cellular geometric states that select for fibroblast activation within the heterogenous tumor microenvironment., Molecular Biology of the Cell, 31 (8), ISSN:1939-4586, ISSN:1059-1524

Lineage tracing involves the identification of all ancestors and descendants of a given cell, and is an important tool for studying biological processes such as development and disease progression. However, in many settings, controlled time-course experiments are not feasible, for example when working with tissue samples from patients. Here we present ImageAEOT, a computational pipeline based on autoencoders and optimal transport for predicting the lineages of cells using time-labeled datasets from different stages of a cellular process. Given a single-cell image from one of the stages, ImageAEOT generates an artificial lineage of this cell based on the population characteristics of the other stages. These lineages can be used to connect subpopulations of cells through the different stages and identify image-based features and biomarkers underlying the biological process. To validate our method, we apply ImageAEOT to a benchmark task based on nuclear and chromatin images during the activation of fibroblasts by tumor cells in engineered 3D tissues. We further validate ImageAEOT on chromatin images of various breast cancer cell lines and human tissue samples, thereby linking alterations in chromatin condensation patterns to different stages of tumor progression. Our results demonstrate the promise of computational methods based on autoencoding and optimal transport principles for lineage tracing in settings where existing experimental strategies cannot be used., PLoS Computational Biology, 16 (4), ISSN:1553-734X, ISSN:1553-7358

For systematic identification of transcription signatures of human cell aging, we carried out Weighted Gene Co-expression Network Analysis (WGCNA) with the RNA-sequencing data generated with young to old human dermal fibroblasts. By relating the modules to the donor's traits, we uncovered the natural aging- and premature aging disease-associated modules. The STRING functional association networks built with the core module memberships provided a systematic overview of genome-wide transcriptional changes upon aging. We validated the selected candidates via quantitative reverse transcription PCR (RT-qPCR) assay with young and aged human fibroblasts, and uncovered several genes involved in ECM, cell, and nuclear mechanics as a potential aging biomarker. Collectively, our study not only provides a snapshot of functional changes during human fibroblast aging but also presents potential aging markers that are relevant to cell mechanics., Scientific Reports, 10 (1), ISSN:2045-2322

Fibroblasts exhibit heterogeneous cell geometries in tissues and integrate both mechanical and biochemical signals in their local microenvironment to regulate genomic programs via chromatin remodelling. While in connective tissues fibroblasts experience tensile and compressive forces (CFs), the role of compressive forces in regulating cell behavior and, in particular, the impact of cell geometry in modulating transcriptional response to such extrinsic mechanical forces is unclear. Here we show that CF on geometrically well-defined mouse fibroblast cells reduces actomyosin contractility and shuttles histone deacetylase 3 (HDAC3) into the nucleus. HDAC3 then triggers an increase in the heterochromatin content by initiating removal of acetylation marks on the histone tails. This suggests that, in response to CF, fibroblasts condense their chromatin and enter into a transcriptionally less active and quiescent states as also revealed by transcriptome analysis. On removal of CF, the alteration in chromatin condensation was reversed. We also present a quantitative model linking CF-dependent changes in actomyosin contractility leading to chromatin condensation. Further, transcriptome analysis also revealed that the transcriptional response of cells to CF was geometry dependent. Collectively, our results suggest that CFs induce chromatin condensation and geometry-dependent differential transcriptional response in fibroblasts that allows maintenance of tissue homeostasis.

In vivo, cells are frequently exposed to multiple mechanical stimuli arising from the extracellular microenvironment, with a deep impact on many biological functions. On the other hand, current methods for mechanobiology do not allow one to easily replicate in vitro the complex spatio-temporal profile of such mechanical signals. Here we introduce a new platform for studying the mechanical coupling between single cells and a dynamic extracellular environment, based on active substrates for cell culture made of Fe-coated polymeric micropillars. Under the action of quasi-static external magnetic fields, each group of pillars produces synchronous mechanical stimuli at different points of the cell membrane, thanks to the highly controllable pillars' deflection. This method allows one to apply complex stress fields, resulting in the parallel application of localized forces with tunable intensity and temporal profile. The platform has been validated by studying the cellular response to periodic stimuli in NIH3T3 fibroblasts. We find that low-frequency mechanical stimulation affects the actin cytoskeleton, nuclear morphology, and H2B core-histone dynamics and induces MKL transcription-cofactor translocation from nucleus to cytoplasm. The unique capability of the proposed platform to apply stimuli with a tunable temporal profile and high parallelism on a cell culture holds great potential for the investigation of mechanotransduction mechanisms in cells and tissues.

Significance We develop a network analysis approach for identifying clusters of interactions between chromosomes, which we validate experimentally. Our method integrates 1D features of the genome, such as epigenetic marks, with 3D interactions, allowing us to study spatially colocalized regions between chromosomes that are functionally relevant. We observe that clusters of interchromosomal regions fall into active and inactive categories. We find that active clusters share transcription factors and are enriched for transcriptional machinery, suggesting that chromosome intermingling regions play a key role in genome regulation. Our method provides a unique quantitative framework that can be broadly applied to study the principles of genome organization and regulation during processes such as cell differentiation and reprogramming., The 3D structure of the genome plays a key role in regulatory control of the cell. Experimental methods such as high-throughput chromosome conformation capture (Hi-C) have been developed to probe the 3D structure of the genome. However, it remains a challenge to deduce from these data chromosome regions that are colocalized and coregulated. Here, we present an integrative approach that leverages 1D functional genomic features (e.g., epigenetic marks) with 3D interactions from Hi-C data to identify functional interchromosomal interactions. We construct a weighted network with 250-kb genomic regions as nodes and Hi-C interactions as edges, where the edge weights are given by the correlation between 1D genomic features. Individual interacting clusters are determined using weighted correlation clustering on the network. We show that intermingling regions generally fall into either active or inactive clusters based on the enrichment for RNA polymerase II (RNAPII) and H3K9me3, respectively. We show that active clusters are hotspots for transcription factor binding sites. We also validate our predictions experimentally by 3D fluorescence in situ hybridization (FISH) experiments and show that active RNAPII is enriched in predicted active clusters. Our method provides a general quantitative framework that couples 1D genomic features with 3D interactions from Hi-C to probe the guiding principles that link the spatial organization of the genome with regulatory control.

Phosphoinositide lipids (PPIs) are enriched in the nucleus and are accumulated at DNA damage sites. Here, we investigate roles of nuclear PPIs in DNA damage response by sequestering specific PPIs with the expression of nuclear-targeted PH domains, which inhibits recruitment of Ataxia telangiectasia and Rad3-related protein (ATR) and reduces activation of Chk1. PPI-binding domains rapidly (, Phosphoinositides are enriched in the nucleus and accumulate upon DNA damage but their role in responding to DNA damage is poorly defined. Here, the authors show that phosphoinositides rapidly accumulate at DNA damage sites and are required for ATR recruitment and subsequent Chk1 activation.

It is well established that cells sense chemical signals from their local microenvironment and transduce them to the nucleus to regulate gene expression programmes. Although a number of experiments have shown that mechanical cues can also modulate gene expression, the underlying mechanisms are far from clear. Nevertheless, we are now beginning to understand how mechanical cues are transduced to the nucleus and how they influence nuclear mechanics, genome organization and transcription. In particular, recent progress in super-resolution imaging, in genome-wide application of RNA sequencing, chromatin immunoprecipitation and chromosome conformation capture and in theoretical modelling of 3D genome organization enables the exploration of the relationship between cell mechanics, 3D chromatin configurations and transcription, thereby shedding new light on how mechanical forces regulate gene expression.

Coronaviruses employ various nuclear signalling mechanisms for their propagation. Here we link replication of coronaviruses, including SARS-CoV-2, the coronavirus disease 2019 (COVID-19)-causing virus, with cytoskeleton-dependent signalling and 3D genome organization. This link could provide novel insights into the high coronavirus pathogenicity in certain cellular states, particularly those associated with ageing. Shivashankar and Uhler propose a link between cell mechano-genomics and coronavirus replication with implications for understanding the pathogenicity of SARS-CoV-2.

In this Current Opinion, we highlight the importance of the material properties of tissues and how alterations therein, which influence epithelial-to-mesenchymal transitions, represent an important layer of regulation in a number of diseases and potentially also play a critical role in host-pathogen interactions. In light of the current SARS-CoV-2 pandemic, we here highlight the possible role of lung tissue stiffening with ageing and how this might facilitate increased SARS-CoV-2 replication through matrix-stiffness dependent epithelial-to-mesenchymal transitions of the lung epithelium. This emphasizes the need for integrating material properties of tissues in drug discovery programs.

Although we can increasingly image and measure biological processes at single-cell resolution, most assays can only take snapshots from a population of cells in time. Here we describe ImageAEOT, which combines an AutoEncoder, to map single-cell Images from different cell populations to a common latent space, with the framework of Optimal Transport to infer cellular trajectories. As a proof-of-concept, we apply ImageAEOT to nuclear and chromatin images during the activation of fibroblasts by tumor cells in engineered 3D tissues. We further validate ImageAEOT on chromatin images of various breast cancer cell lines and human tissue samples, thereby linking alterations in chromatin condensation patterns to different stages of tumor progression. Importantly, ImageAEOT can infer the trajectory of a particular cell from one snapshot in time and identify the changing features to provide early biomarkers for developmental and disease progression.

Landmark experiments in vitro showed that somatic cells can be reprogrammed to stem-cells by the constitutive expression of particular transcription factors. However, in vivo cells naturally exhibit de-differentiation and trans-differentiation programs, thereby suggesting that the signals from the local mechanical microenvironment may be sufficient to induce stem-cell state transitions. In this review, we discuss recent evidence for the biophysical regulation of genome architecture and nuclear programs. We start by discussing the coupling between cellular architecture, genome organization and gene expression. We then review the role of biophysical factors in regulating genome architecture and cell-state transitions. Finally, we discuss the molecular basis of cell-state transitions during nuclear reprogramming. Collectively, we highlight the importance of the mechanical regulation of genome organization on cell-fate decisions.

Cells in tissues undergo transdifferentiation programs when stimulated by specific mechanical and biochemical signals. While seminal studies have demonstrated that exogenous biochemical factors can reprogram somatic cells into pluripotent stem cells, the critical roles played by mechanical signals in such reprogramming process have not been well documented. In this paper, we show that laterally confined growth of fibroblasts on micropatterned substrates induces nuclear reprogramming with high efficiency in the absence of any exogenous reprogramming factors. We provide compelling evidence on the induction of stem cell-like properties using alkaline phosphatase assays and expression of pluripotent markers. Early onset of reprogramming was accompanied with enhanced nuclear dynamics and changes in chromosome intermingling degrees, potentially facilitating rewiring of the genome. Time-lapse analysis of promoter occupancy by immunoprecipitation of H3K9Ac chromatin fragments revealed that epithelial, proliferative, and reprogramming gene promoters were progressively acetylated, while mesenchymal promoters were deacetylated by 10 days. Consistently, RNA sequencing analysis showed a systematic progression from mesenchymal to stem cell transcriptome, highlighting pathways involving mechanisms underlying nuclear reprogramming. We then demonstrated that these mechanically reprogrammed cells could be maintained as stem cells and can be redifferentiated into multiple lineages with high efficiency. Importantly, we also demonstrate the induction of cancer stemness properties in MCF7 cells grown in such laterally confined conditions. Collectively, our results highlight an important generic property of somatic cells that, when grown in laterally confined conditions, acquire stemness. Such mechanical reprogramming of somatic cells demonstrated here has important implications in tissue regeneration and disease models.

Abnormalities in nuclear and chromatin organization are hallmarks of many diseases including cancer. This review provides our understanding of how the cellular microenvironment regulates nuclear morphology and with it the spatial organization of chromosomes and genes, resulting in cell-type specific genomic programs. We also discuss the molecular basis for maintaining nuclear and genomic integrity and how alterations in nuclear mechanotransduction pathways result in various diseases. Finally, we highlight the importance of digital pathology based on nuclear morphometric features combined with single-cell genomics for early cancer diagnostics., NSF (Grant DMS-1651995), ONR (Grant N00014-17-1-2147)

Genome regulatory programs such as telomere functioning require extracellular signals to be transmitted from the microenvironment to the nucleus and chromatin. Although the cytoskeleton has been shown to directly transmit stresses, we show that the intrinsically dynamic nature of the actin cytoskeleton is important in relaying extracellular signals to telomeres. Interestingly, this mechanical pathway not only transmits physical stimuli but also chemical stimuli. The cytoskeletal network continuously reorganizes and applies dynamic forces on the nucleus and feeds into the regulation of telomere dynamics. We further found that distal telomeres are mechanically coupled in a length- and timescale-dependent manner and identified nesprin 2G as well as lamin A/C as being essential to regulate their translational dynamics. Finally, we demonstrated that such mechanotransduction events impinge on the binding dynamics of critical telomere binding proteins. Our results highlight an overarching physical pathway that regulates positional and molecular stability of telomeres.

Physical boundary conditions of the cell define its cytoskeletal organization and thus regulate the force balance on the nucleus. The boundary can be very precisely engineered by plating cells on micropatterned substrate of various geometries. Such modulations of cell shape and size impinge on nuclear morphology and dynamics. Understanding the regulation of nuclear dynamics is crucial for both physiological processes such as migration, wound healing, stem cell differentiation, and gene expression program and for disease conditions like cancer progression and laminopathies. In this chapter, we discuss the different types of nuclear dynamics, translation, rotation, and fluctuations of the nuclear envelope, forces contributing to such dynamics, and their implications in cell physiology.

The formin family proteins are important regulators of actin polymerization that are involved in many cellular processes. However, little is known about their specific cellular localizations. Here, we show that Diaphanous-related formin-3 (mDia2) localizes to the cytoplasmic side of the nuclear envelope. This localization of mDia2 to the nuclear rim required the presence of a nuclear localization signal (NLS) sequence at the mDia2 N-terminal. Consistent with this result, super-resolution images demonstrated that at the nuclear rim, mDia2 co-localized with the nuclear pore complexes and a nuclear transport receptor, importin β. Furthermore, an interaction between mDia2 and importin β was detected by immunoprecipitation, and silencing of importin β was shown to attenuate accumulation of mDia2 to the nuclear rim. We have shown previously that Ca2+ entry leads to the assembly of perinuclear actin rim in an inverted formin 2 (INF2) dependent manner. mDia2, however, was not involved in this process since abolishing its localization at the nuclear rim by silencing of importin β had no effect on actin assembly at the nuclear rim triggered by Ca2+ stimulation., Summary: Formin mDia2 accumulates to the cytoplasmic side of the nuclear envelope and co-localizes with the nuclear pore complexes in an importin β-dependent manner.

Cells sense physical cues at the level of focal adhesions and transduce them to the nucleus by biochemical and mechanical pathways. While the molecular intermediates in the mechanical links have been well studied, their dynamic coupling is poorly understood. In this study, fibroblast cells were adhered to micropillar arrays to probe correlations in the physical coupling between focal adhesions and nucleus. For this, we used novel imaging setup to simultaneously visualize micropillar deflections and EGFP labeled chromatin structure at high spatial and temporal resolution. We observed that micropillar deflections, depending on their relative positions, were positively or negatively correlated to nuclear and heterochromatin movements. Our results measuring the time scales between micropillar deflections and nucleus centroid displacement are suggestive of a strong elastic coupling that mediates differential force transmission to the nucleus.

The nucleus is sculpted toward various morphologies during cellular differentiation and development. Alterations in nuclear shape often result in changes to chromatin organization and genome function. This is thought to be reflective of its role as a cellular mechanotransducer. Recent evidence has highlighted the importance of cytoskeletal organization in defining how nuclear morphology regulates chromatin dynamics. However, the mechanisms underlying cytoskeletal control of chromatin remodeling are not well understood. We demonstrate here the differential influence of perinuclear actin- and microtubule-driven assemblies on nuclear architecture using pharmacological inhibitors and targeted RNA interference knockdown of cytoskeleton components in Drosophila cells. We find evidence that the loss of perinuclear actin assembly results in basolateral enhancement of microtubule organization and this is reflected functionally by enhanced nuclear dynamics. Cytoskeleton reorganization leads to nuclear lamina deformation that influences heterochromatin localization and core histone protein mobility. We also show that modulations in actin-microtubule assembly result in differential gene expression patterns. Taken together, we suggest that perinuclear actin and basolateral microtubule organization exerts mechanical control on nuclear morphology and chromatin dynamics.

Cells in physical microenvironments regulate their functioning and geometry in response to mechanical stimuli. Recent studies have demonstrated the influence of the integrated actin cytoskeleton on nuclear integrity and chromatin organization. However, the mechanisms underlying the mechanotransduction of their physical coupling to nuclear protein dynamics are not well understood. In this study, we take advantage of micropatterned geometric substrates in NIH3T3 mouse fibroblasts to probe the functional influence of actin organization on nuclear lamina and chromatin assembly. Fluorescence correlation spectroscopy studies demonstrate that stabilization of perinuclear actin strengthens the transient interactions of lamin A with the chromatin. Correspondingly, fluorescence recovery after photobleaching studies reveal enhanced mobility of these nuclear lamina proteins when actin organization is perturbed. Combining these fluorescence dynamics assays, we also demonstrate an actin-driven differential modulation of core histone H2B and heterochromatin HP1α protein dynamics with chromatin. These altered dynamics are reflected structurally by concomitant changes in the architecture of the heterochromatin foci as seen by immunofluorescence assays. Taken together, our study provides a demonstration of the differential mechanical control of perinuclear actin on the dynamics of the nuclear lamina, euchromatin and heterochromatin regimes of the nucleus, and suggests an actin-mediated route to spatially and structurally tune chromatin organization and dynamics.

Current cancer diagnosis employs various nuclear morphometric measures. While these have allowed accurate late-stage prognosis, early diagnosis is still a major challenge. Recent evidence highlights the importance of alterations in mechanical properties of single cells and their nuclei as critical drivers for the onset of cancer. We here present a method to detect subtle changes in nuclear morphometrics at single-cell resolution by combining fluorescence imaging and deep learning. This assay includes a convolutional neural net pipeline and allows us to discriminate between normal and human breast cancer cell lines (fibrocystic and metastatic states) as well as normal and cancer cells in tissue slices with high accuracy. Further, we establish the sensitivity of our pipeline by detecting subtle alterations in normal cells when subjected to small mechano-chemical perturbations that mimic tumor microenvironments. In addition, our assay provides interpretable features that could aid pathological inspections. This pipeline opens new avenues for early disease diagnostics and drug discovery.

A combination of experiments and ellipsoid packing models elucidate the critical role of cell geometry in the 3D organization of chromosomes and gene expression. The results show that transcription-dependent chromosome positions, their orientations, and their relative intermingling depend on cell mechanical constraints., Extracellular matrix signals from the microenvironment regulate gene expression patterns and cell behavior. Using a combination of experiments and geometric models, we demonstrate correlations between cell geometry, three-dimensional (3D) organization of chromosome territories, and gene expression. Fluorescence in situ hybridization experiments showed that micropatterned fibroblasts cultured on anisotropic versus isotropic substrates resulted in repositioning of specific chromosomes, which contained genes that were differentially regulated by cell geometries. Experiments combined with ellipsoid packing models revealed that the mechanosensitivity of chromosomes was correlated with their orientation in the nucleus. Transcription inhibition experiments suggested that the intermingling degree was more sensitive to global changes in transcription than to chromosome radial positioning and its orientations. These results suggested that cell geometry modulated 3D chromosome arrangement, and their neighborhoods correlated with gene expression patterns in a predictable manner. This is central to understanding geometric control of genetic programs involved in cellular homeostasis and the associated diseases.