Spatial Organization Research Articles

Charting the cellular biogeography in colitis reveals fibroblast trajectories and coordinated spatial remodeling

Gut inflammation involves contributions from immune and non-immune cells, whose interactions are shaped by the spatial organization of the healthy gut and its remodeling during inflammation. The crosstalk between fibroblasts and immune cells is an important axis in this process, but our understanding has been challenged by incomplete cell-type definition and biogeography. To address this challenge, we used multiplexed error-robust fluorescence in situ hybridization (MERFISH) to profile the expression of 940 genes in 1.35 million cells imaged across the onset and recovery from a mouse colitis model. We identified diverse cell populations, charted their spatial organization, and revealed their polarization or recruitment in inflammation. We found a staged progression of inflammation-associated tissue neighborhoods defined, in part, by multiple inflammation-associated fibroblasts, with unique expression profiles, spatial localization, cell-cell interactions, and healthy fibroblast origins. Similar signatures in ulcerative colitis suggest conserved human processes. Broadly, we provide a framework for understanding inflammation-induced remodeling in the gut and other tissues.

Exploring kidney allograft rejection: A proof-of-concept study using spatial transcriptomics

In this proof-of-concept study, spatial transcriptomics combined with public single-cell ribonucleic acid-sequencing data were used to explore the potential of this technology to study kidney allograft rejection. We aimed to map gene expression patterns within diverse pathologic states by examining biopsies classified across nonrejection, T cell–mediated acute rejection, interstitial fibrosis, and tubular atrophy. Our results revealed distinct immune cell signatures, including those of T and B lymphocytes, monocytes, mast cells, and plasma cells, and their spatial organization within the renal interstitium. We also mapped chemokine receptors and ligands to study immune cell migration and recruitment. Finally, our analysis demonstrated differential spatial enrichment of transcription signatures associated with kidney allograft rejection across various biopsy regions. Interstitium regions displayed higher enrichment scores for rejection-associated gene expression patterns than tubular areas, which had negative scores. This implies that these signatures are primarily driven by processes unfolding in the renal interstitium. Overall, this study highlights the value of spatial transcriptomics for revealing cellular heterogeneity and immune signatures in renal transplant biopsies and demonstrates its potential for studying the molecular and cellular mechanisms associated with rejection. However, certain limitations must be borne in mind regarding the development and future applications of this technology.

IJCM_100A: Mountain Heights and Aging Insights: A Comprehensive Geriatric Assessment and Its Correlates in a Mesmerizing Hilly City of Northern India

Background: Global population is experiencing a rapid increase in the proportion of older adults, posing unique challenges to healthcare systems. Objective: To conduct a comprehensive geriatric assessment in Shimla, a hilly city in Northern India Methodology: A total of 408 participants aged 60 years and above were included in the study. Data were collected through structured interviews using a specifically designed questionnaire covering wide range of topics including socio-demographic characteristics, medical history, functional assessment, cognitive function assessment, psychosocial assessment, nutritional assessment, physical examination, fall risk assessment, and polypharmacy assessment. Results: The study involved 408 participants, with an average age of 70 years, comprising 53% males and 47% females. Functional assessment indicated theneed for assistance in various activities of daily living (ADLs) (16-32%) and instrumental activities of daily living (IADLs) (28-42%) Cognitive function assessment using the Mini-Mental State Examination (MMSE) and the Montreal Cognitive Assessment (MoCA) revealed cognitive impairment in 32% and 42%, respectively. The Clock Drawing Test indicated difficulties in time representation and spatial organization in 28%. Psychosocial assessment highlighted the prevalence of symptoms of depression in 36% and f anxiety in 27%. Nutritional assessment revealed that 29% were malnourished, and 34% were at high risk of malnutrition according to the Malnutrition Universal Screening Tool (MUST). Musculoskeletal disorders were found in 42%, while sensory impairments were observed in 28%. The fall risk assessment using the Timed Up and Go (TUG) test and the Berg Balance Scale indicated an increased risk of falls in 36% and 41%, respectively. Polypharmacy assessment highlighted that 82 were taking multiple medications concurrently. Conclusion: The findings emphasize the importance of addressing the specific challenges faced by older adults in such geographical contexts. The results can guide the development of effective healthcare interventions and policies that are tailored to the unique needs of older adults in hilly areas.

Spatial organization and functions of Chk1 activation by TopBP1 biomolecular condensates

Assembly of TopBP1 biomolecular condensates triggers activation of the ataxia telangiectasia-mutated and Rad3-related (ATR)/Chk1 signaling pathway, which coordinates cell responses to impaired DNA replication. Here, we used optogenetics and reverse genetics to investigate the role of sequence-specific motifs in the formation and functions of TopBP1 condensates. We propose that BACH1/FANCJ is involved in the partitioning of BRCA1 within TopBP1 compartments. We show that Chk1 is activated at the interface of TopBP1 condensates and provide evidence that these structures arise at sites of DNA damage and in primary human fibroblasts. Chk1 phosphorylation depends on the integrity of a conserved arginine motif within TopBP1's ATR activation domain (AAD). Its mutation uncouples Chk1 activation from TopBP1 condensation, revealing that optogenetically induced Chk1 phosphorylation triggers cell cycle checkpoints and slows down replication forks in the absence of DNA damage. Together with previous work, these data suggest that the intrinsically disordered AAD encodes distinct molecular steps in the ATR/Chk1 pathway.

Macrophage-coated tumor cluster aggravates hepatoma invasion and immunotherapy resistance via generating local immune deprivation

Immune checkpoint inhibitors (ICIs) represent a promising treatment for hepatocellular carcinoma (HCC) due to their capacity for abundant lymphocyte infiltration. However, some patients with HCC respond poorly toICI therapy due to the presence of various immunosuppressive factors in the tumor microenvironment. Our research reveals that a macrophage-coated tumor cluster (MCTC) signifies a unique spatial structural organization in HCC correlating with diminished recurrence-free survival and overall survival in a total of 572 HCC cases from 3 internal cohorts and 2 independent external validation cohorts. Mechanistically, tumor-derived macrophage-associated lectin Mac-2 binding protein (M2BP) induces MCTC formation andtraps immunocompetent cells at the edge of MCTCs to induce intratumoral cytotoxic Tcell exclusion and local immune deprivation. Blocking M2BP with a Mac-2 antagonist might provide an effective approach to prevent MCTC formation, enhance Tcell infiltration, and thereby improve the efficacy of ICI therapy in HCC.

Change in RhoGAP and RhoGEF availability drives transitions in cortical patterning and excitability in Drosophila

Actin cortex patterning and dynamics are critical for cell shape changes. These dynamics undergo transitions during development, often accompanying changes in collective cell behavior. Although mechanisms have been established for individual cells' dynamic behaviors, the mechanisms and specific molecules that result in developmental transitions invivo are still poorly understood. Here, we took advantage of two developmental systems in Drosophila melanogaster to identify conditions that altered cortical patterning and dynamics. We identified a Rho guanine nucleotide exchange factor (RhoGEF) and Rho GTPase activating protein (RhoGAP) pair required for actomyosin waves in egg chambers. Specifically, depletion of the RhoGEF, Ect2, or the RhoGAP, RhoGAP15B, disrupted actomyosin wave induction, and both proteins relocalized from the nucleus to the cortex preceding wave formation. Furthermore, we found that overexpression of a different RhoGEF and RhoGAP pair, RhoGEF2 and Cumberland GAP (C-GAP), resulted in actomyosin waves in the early embryo, during which RhoA activation precedes actomyosin assembly by ∼4 s. We found that C-GAP was recruited to actomyosin waves, and disrupting F-actin polymerization altered the spatial organization of both RhoA signaling and the cytoskeleton in waves. In addition, disrupting F-actin dynamics increased wave period and width, consistent with a possible role for F-actin in promoting delayed negative feedback. Overall, we showed a mechanism involved in inducing actomyosin waves that is essential for oocyte development and is general to other cell types, such as epithelial and syncytial cells.

Multi‐Frequency Ultrasound Directed Self‐Assembly

AbstractUltrasound‐directed self‐assembly (DSA) utilizes the acoustic radiation force associated with a standing ultrasound wave field to organize particles dispersed in a fluid medium into specific patterns. State‐of‐the‐art ultrasound DSA methods use single‐frequency ultrasound wave fields, which only allow organizing particles into simple, periodic patterns, or require a large number of ultrasound transducers to assemble complex patterns. In contrast, this work introduces multi‐frequency ultrasound wave fields to organize particles into complex patterns. A method is theoretically derived to determine the operating parameters (frequency, amplitude, phase) of any arrangement of ultrasound transducers, required to assemble spherical particles dispersed in a fluid medium into specific patterns, and experimentally validated for a system with two frequencies. The results show that multi‐frequency compared to single‐frequency ultrasound DSA enables the assembly of complex patterns of particles with substantially fewer ultrasound transducers. Additionally, the method does not incur a penalty in terms of accuracy, and it does not require custom hardware for each different pattern, thus offering reconfigurability, which contrasts, e.g., acoustic holography. Multi‐frequency ultrasound DSA can spur progress in a myriad of engineering applications, including the manufacturing of multi‐functional polymer matrix composite materials that derive their structural, electric, acoustic, or thermal properties from the spatial organization of particles in the matrix.

First person – Anne Rosfelter

ABSTRACT First Person is a series of interviews with the first authors of a selection of papers published in Journal of Cell Science, helping researchers promote themselves alongside their papers. Anne Rosfelter is first author on ‘ Reduction of cortical pulling at mitotic entry facilitates aster centration’, published in JCS. Anne conducted the research described in this article while a PhD student in Alex McDougall's lab at Laboratoire Biologie du Développement (LBDV), Villefranche-sur-Mer, France. She is now a post-doctoral researcher in the lab of Yu-Chiun Wang at the RIKEN Center for Biosystems Dynamics Research (BDR), Kobe, Japan, investigating the spatial organization of cells and tissue through studying the cytoskeleton.

"Earthly paradise" in Alexander Dovzhenko films

"Earthly paradise" in Alexander Dovzhenko films

The effect of trisomic chromosomes on spatial genome organization and global transcription in embryonic stem cells.

Aneuploidy frequently occurs in cancer and developmental diseases such as Down syndrome, with its functional consequences implicated in dosage effects on gene expression and global perturbation of stress response and cell proliferation pathways. However, how aneuploidy affects spatial genome organization remains less understood. In this study, we addressed this question by utilizing the previously established isogenic wild-type (WT) and trisomic mouse embryonic stem cells (mESCs). We employed a combination of Hi-C, RNA-seq, chromosome painting and nascent RNA imaging technologies to compare the spatial genome structures and gene transcription among these cells. We found that trisomy has little effect on spatial genome organization at the level of A/B compartment or topologically associating domain (TAD). Inter-chromosomal interactions are associated with chromosome regions with high gene density, active histone modifications and high transcription levels, which are confirmed by imaging. Imaging also revealed contracted chromosome volume and weakened transcriptional activity for trisomic chromosomes, suggesting potential implications for the transcriptional output of these chromosomes. Our data resources and findings may contribute to a better understanding of the consequences of aneuploidy from the angle of spatial genome organization.

Targeting Siglec-Sialylated MUC1 Immune Axis in Cancer.

Siglecs play a key role in mediating cell-cell interactions via the recognition of different sialylated glycoconjugates, including tumor-associated MUC1, which can lead to the activation or inhibition of the immune response. The activation occurs through the signaling of Siglecs with the cytoplasmic immunoreceptor tyrosine-based activation motif (ITAM)-containing proteins, while the inhibition signal is a result of the interaction of intracellular immunoreceptor tyrosine-based inhibition motif (ITIM)-bearing receptors. The interaction of tumor-associated MUC1 sialylated glycans with Siglecs via ITIM motifs decreases antitumor immunity. Consequently, these interactions are expected to play a key role in tumor evasion. Efforts to modulate the response of immune cells by blocking the immune-suppressive effects of inhibitory Siglecs, driving immune-activating Siglecs, and/or altering the synthesis and expression of the sialic acid glycocalyx are new therapeutic strategies deserving further investigation. We will highlight the role of Siglec's family receptors in immune evasion through interactions with glycan ligands in their natural context, presented on the protein such as MUC1, factors affecting their fine binding specificities, such as the role of multivalency either at the ligand or receptor side, their spatial organization, and finally the current and future therapeutic interventions targeting the Siglec-sialylated MUC1 immune axis in cancer.

Differential proteomics profile of microcapillary networks in response to sound pattern-driven local cell density enhancement

Spatial cell organization and biofabrication of microcapillary networks in vitro has a great potential in tissue engineering and regenerative medicine. This study explores the impact of local cell density enhancement achieved through an innovative sound-based patterning on microcapillary networks formation and their proteomic profile. Human umbilical vein endothelial cells (HUVEC) and human pericytes from placenta (hPC-PL) were mixed in a fibrin suspension. The mild effect of sound-induced hydrodynamic forces condensed cells into architected geometries showing good fidelity to the numerical simulation of the physical process. Local cell density increased significantly within the patterned areas and the capillary-like structures formed following the cell density gradient. Over five days, these patterns were well-maintained, resulting in concentric circles and honeycomb-like structures.Proteomic analysis of the pre-condensed cells cultured for 5 days, revealed over 900 differentially expressed proteins when cells were preassembled through mild-hydrodynamic forces. Gene ontology (GO) enrichment analysis identified cellular components, molecular functions, and biological processes that were up- and down-regulated, providing insights regarding molecular processes influenced by the local density enhancement. Furthermore, we employed Ingenuity Pathway Analysis (IPA) to identify altered pathways and predict upstream regulators. Notably, VEGF-A emerged as one of the most prominent upstream regulators.Accordingly, this study initiates the unraveling of the changes in microcapillary networks at both molecular and proteins level induced by cell condensation obtained through sound patterning. The findings provide valuable insights for further investigation into sound patterning as a biofabrication technique for creating more complex microcapillary networks and advancing in vitro models.

Ergativity in the reconstruction of Ukraine. Towards the analysis and assessment of spatial processes in the state

The destruction of Ukraine's spatial potential by the war has changed the processes of life in the country and has made it necessary to find models for reconstruction and spatial revitalisation (return to life) of destroyed territories and cities. The article expresses the idea of ergatonicity in substantiating the decisions of Ukraine's reconstruction, which considers the state and its space as a "system-process", which is characterised by behaviour, the ability to self-organise and self-development in the face of changing situations. The authors examine the processes related to: functional and urban changes in the territories of the state; connections and multidimensional dynamics of the territory; placement of new elements and investments in the existing spatial structure; spatial-temporal and structural-parametric processes in the space of the state. The factors that influence processes in space are structured in a five-vector representation: "person L - functions F - conditions U - geometry G - time T", which made it possible to analyse the interactions between dimensions, establish patterns and features of processes in the system, and assess their consistency and efficiency. The territories are distinguished by: social processes; conditions, features and technological processes; and the emotional component of the perception of events. Taking into account the classification of the importance and location of processes in the space of the state, an ergatic map (map of processes) in Ukraine is constructed and four clusters are identified according to the selected criteria. A substantiated methodological toolkit for taking into account the requirements of ergatonicity in the spatial organisation of territorial systems of different hierarchies makes it possible to eliminate uncertainties, intensify positive trends in evolution and effective development of space at different levels.

Vortex Pattern Stabilization in Thin Films Resulting from Shear Thickening of Active Suspensions.

The need for structuring on micrometer scales is abundant, for example, in view of phononic applications. We here outline a novel approach based on the phenomenon of active turbulence on the mesoscale. As we demonstrate, a shear-thickening carrier fluid of active microswimmers intrinsically stabilizes regular vortex patterns of otherwise turbulent active suspensions. The fluid self-organizes into a periodically structured nonequilibrium state. Introducing additional passive particles of intermediate size leads to regular spatial organization of these objects. Our approach opens a new path toward functionalization through patterning of thin films and membranes.

New Methods in Digital Wood Anatomy: The Use of Pixel-Contrast Densitometry with Example of Angiosperm Shrubs in Southern Siberia.

This methodological study describes the adaptation of a new method in digital wood anatomy, pixel-contrast densitometry, for angiosperm species. The new method was tested on eight species of shrubs and small trees in Southern Siberia, whose wood structure varies from ring-porous to diffuse-porous, with different spatial organizations of vessels. A two-step transformation of wood cross-section photographs by smoothing and Otsu's classification algorithm was proposed to separate images into cell wall areas and empty spaces within (lumen) and between cells. Good synchronicity between measurements within the ring allowed us to create profiles of wood porosity (proportion of empty spaces) describing the growth ring structure and capturing inter-annual differences between rings. For longer-lived species, 14-32-year series from at least ten specimens were measured. Their analysis revealed that maximum (for all wood types), mean, and minimum porosity (for diffuse-porous wood) in the ring have common external signals, mostly independent of ring width, i.e., they can be used as ecological indicators. Further research directions include a comparison of this method with other approaches in densitometry, clarification of sample processing, and the extraction of ecologically meaningful data from wood structures.

Single-cell multiplex chromatin and RNA interactions in ageing human brain

Dynamically organized chromatin complexes often involve multiplex chromatin interactions and sometimes chromatin-associated RNA1–3. Chromatin complex compositions change during cellular differentiation and ageing, and are expected to be highly heterogeneous among terminally differentiated single cells4–7. Here we introduce the multinucleic acid interaction mapping in single cells (MUSIC) technique for concurrent profiling of multiplex chromatin interactions, gene expression and RNA–chromatin associations within individual nuclei. When applied to 14 human frontal cortex samples from older donors, MUSIC delineated diverse cortical cell types and states. We observed that nuclei exhibiting fewer short-range chromatin interactions were correlated with both an ‘older’ transcriptomic signature and Alzheimer’s disease pathology. Furthermore, the cell type exhibiting chromatin contacts between cis expression quantitative trait loci and a promoter tends to be that in which these cis expression quantitative trait loci specifically affect the expression of their target gene. In addition, female cortical cells exhibit highly heterogeneous interactions between XIST non-coding RNA and chromosome X, along with diverse spatial organizations of the X chromosomes. MUSIC presents a potent tool for exploration of chromatin architecture and transcription at cellular resolution in complex tissues.

ScBOL: a universal cell type identification framework for single-cell and spatial transcriptomics data.

Over the past decade, single-cell transcriptomic technologies have experienced remarkable advancements, enabling the simultaneous profiling of gene expressions across thousands of individual cells. Cell type identification plays an essential role in exploring tissue heterogeneity and characterizing cell state differences. With more and more well-annotated reference data becoming available, massive automatic identification methods have sprung up to simplify the annotation process on unlabeled target data by transferring the cell type knowledge. However, in practice, the target data often include some novel cell types that are not in the reference data. Most existing works usually classify these private cells as one generic 'unassigned' group and learn the features of known and novel cell types in a coupled way. They are susceptible to the potential batch effects and fail to explore the fine-grained semantic knowledge of novel cell types, thus hurting the model's discrimination ability. Additionally, emerging spatial transcriptomic technologies, such as in situ hybridization, sequencing and multiplexed imaging, present a novel challenge to current cell type identification strategies that predominantly neglect spatial organization. Consequently, it is imperative to develop a versatile method that can proficiently annotate single-cell transcriptomics data, encompassing both spatial and non-spatial dimensions. To address these issues, we propose a new, challenging yet realistic task called universal cell type identification for single-cell and spatial transcriptomics data. In this task, we aim to give semantic labels to target cells from known cell types and cluster labels to those from novel ones. To tackle this problem, instead of designing a suboptimal two-stage approach, we propose an end-to-end algorithm called scBOL from the perspective of Bipartite prototype alignment. Firstly, we identify the mutual nearest clusters in reference and target data as their potential common cell types. On this basis, we mine the cycle-consistent semantic anchor cells to build the intrinsic structure association between two data. Secondly, we design a neighbor-aware prototypical learning paradigm to strengthen the inter-cluster separability and intra-cluster compactness within each data, thereby inspiring the discriminative feature representations. Thirdly, driven by the semantic-aware prototypical learning framework, we can align the known cell types and separate the private cell types from them among reference and target data. Such an algorithm can be seamlessly applied to various data types modeled by different foundation models that can generate the embedding features for cells. Specifically, for non-spatial single-cell transcriptomics data, we use the autoencoder neural network to learn latent low-dimensional cell representations, and for spatial single-cell transcriptomics data, we apply the graph convolution network to capture molecular and spatial similarities of cells jointly. Extensive results on our carefully designed evaluation benchmarks demonstrate the superiority of scBOL over various state-of-the-art cell type identification methods. To our knowledge, we are the pioneers in presenting this pragmatic annotation task, as well as in devising a comprehensive algorithmic framework aimed at resolving this challenge across varied types of single-cell data. Finally, scBOL is implemented in Python using the Pytorch machine-learning library, and it is freely available at https://github.com/aimeeyaoyao/scBOL.

SpatialcoGCN: deconvolution and spatial information-aware simulation of spatial transcriptomics data via deep graph co-embedding.

Spatial transcriptomics (ST) data have emerged as a pivotal approach to comprehending the function and interplay of cells within intricate tissues. Nonetheless, analyses of ST data are restricted by the low spatial resolution and limited number of ribonucleic acid transcripts that can be detected with several popular ST techniques. In this study, we propose that both of the above issues can be significantly improved by introducing a deep graph co-embedding framework. First, we establish a self-supervised, co-graph convolution network-based deep learning model termed SpatialcoGCN, which leverages single-cell data to deconvolve the cell mixtures in spatial data. Evaluations of SpatialcoGCN on a series of simulated ST data and real ST datasets from human ductal carcinoma in situ, developing human heart and mouse brain suggest that SpatialcoGCN could outperform other state-of-the-art cell type deconvolution methods in estimating per-spot cell composition. Moreover, with competitive accuracy, SpatialcoGCN could also recover the spatial distribution of transcripts that are not detected by raw ST data. With a similar co-embedding framework, we further established a spatial information-aware ST data simulation method, SpatialcoGCN-Sim. SpatialcoGCN-Sim could generate simulated ST data with high similarity to real datasets. Together, our approaches provide efficient tools for studying the spatial organization of heterogeneous cells within complex tissues.

StDiff: a diffusion model for imputing spatial transcriptomics through single-cell transcriptomics.

Spatial transcriptomics (ST) has become a powerful tool for exploring the spatial organization of gene expression in tissues. Imaging-based methods, though offering superior spatial resolutions at the single-cell level, are limited in either the number of imaged genes or the sensitivity of gene detection. Existing approaches for enhancing ST rely on the similarity between ST cells and reference single-cell RNA sequencing (scRNA-seq) cells. In contrast, we introduce stDiff, which leverages relationships between gene expression abundance in scRNA-seq data to enhance ST. stDiff employs a conditional diffusion model, capturing gene expression abundance relationships in scRNA-seq data through two Markov processes: one introducing noise to transcriptomics data and the other denoising to recover them. The missing portion of ST is predicted by incorporating the original ST data into the denoising process. In our comprehensive performance evaluation across 16 datasets, utilizing multiple clustering and similarity metrics, stDiff stands out for its exceptional ability to preserve topological structures among cells, positioning itself as a robust solution for cell population identification. Moreover, stDiff's enhancement outcomes closely mirror the actual ST data within the batch space. Across diverse spatial expression patterns, our model accurately reconstructs them, delineating distinct spatial boundaries. This highlights stDiff's capability to unify the observed and predicted segments of ST data for subsequent analysis. We anticipate that stDiff, with its innovative approach, will contribute to advancing ST imputation methodologies.

Managing urban agglomeration processes in Russia in the context of agglomerative and socio-economic development

Studies on urban agglomeration typically focus on the management of urban agglomerations as special types of spatial organization. The problem of finding an adequate management model which accounts for the level of spatial connectivity and socio-economic development of a given territory remains in the background. This article identifies urban agglomeration management models in Russia which account for the agglomerative and socio-economic development of a given territory. A methodology for assessing urban agglomeration processes is presented which, unlike existing methodologies, includes an assessment of agglomeration maturity and an assessment of the socio-economic development of urban agglomerations. This methodology is based on conceptual platforms within spatial development theory; new economic geography; and agglomeration theory and cluster development. The methodology was tested on the data of Chelyabinsk Region agglomerations. The study determined that the Chelyabinsk and Gorniy Ural agglomerations are socio-economically developed and highly agglomerated, while the Magnitogorsk agglomeration shows high socio-economic development and low agglomeration. The conurbations are underdeveloped in both areas. The paper gives several recommendations on methods for choosing urban agglomeration management models. The developed methodology can be used to assess agglomerations across Russia and to choose the most adequate management model for a territory depending on its agglomerative and socio-economic development.