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The coordination between membrane trafficking and actomyosin networks is essential to the regulation of cell and tissue shape. Here, we examine Rab protein distributions during Drosophila epithelial tissue remodeling and show that Rab35 is dynamically planar polarized. Rab35 compartments are enriched at contractile interfaces of intercalating cells and provide the first evidence of interfacial monopolarity. When Rab35 function is disrupted, apical area oscillations still occur and contractile steps are observed. However, contractions are followed by reversals and interfaces fail to shorten, demonstrating that Rab35 functions as a ratchet ensuring unidirectional movement. Although actomyosin forces have been thought to drive interface contraction, initiation of Rab35 compartments does not require Myosin II function. However, Rab35 compartments do not terminate and continue to grow into large elongated structures following actomyosin disruption. Finally, Rab35 represents a common contractile cell-shaping mechanism, as mesoderm invagination fails in Rab35 compromised embryos and Rab35 localizes to constricting surfaces. Various stages of tissue morphogenesis involve the contraction of epithelial surfaces. Here, the authors identify the Rab GTPase Rab35 as an essential component of this contractile process, which functions as a membrane ratchet to ensure unidirectional movement of intercalating cells.

The organization of immune cells in human tumors is not well understood. Immunogenic tumors harbor spatially localized multicellular ‘immunity hubs’ defined by expression of the T cell-attracting chemokines CXCL10/CXCL11 and abundant T cells. Here, we examined immunity hubs in human pre-immunotherapy lung cancer specimens and found an association with beneficial response to PD-1 blockade. Critically, we discovered the stem-immunity hub, a subtype of immunity hub strongly associated with favorable PD-1-blockade outcome. This hub is distinct from mature tertiary lymphoid structures and is enriched for stem-like TCF7 + PD-1 + CD8 + T cells, activated CCR7 + LAMP3 + dendritic cells and CCL19 + fibroblasts as well as chemokines that organize these cells. Within the stem-immunity hub, we find preferential interactions between CXCL10 + macrophages and TCF7 − CD8 + T cells as well as between mature regulatory dendritic cells and TCF7 + CD4 + and regulatory T cells. These results provide a picture of the spatial organization of the human intratumoral immune response and its relevance to patient immunotherapy outcomes. The spatial organization of cells in solid tumors is considered to be important for immune response and response to therapy. Here the authors use multiomics including spatial transcriptomics of human lung tumors prior to patients being treated and show among other things an association of stem-immunity hubs rich in stem-like CD8 + T cells with positive response to anti-PD-1 therapy.

Epithelial tubules form critical structures in various body tissues; however, since they are difficult to access experimentally, their architecture and dynamics are not well understood. Here we examine the dynamic remodeling of epithelial tubes in vivo using a novel and uniquely accessible model system: the extracorporeal vasculature of Botryllus schlosseri (sea squirt). In Botryllus, massive retraction of blood vessels can be triggered without loss of barrier function, through (i) disrupting collagen crosslinking in the basement membrane using β-aminopropionitrile (BAPN); or (ii) disrupting the integrin pathway through inhibition of focal adhesion kinase (FAK). We performed stereographic projections of 3-dimensional high-resolution confocal scans to generate ‘unwrapped’ 2-dimensional maps of the cylindrical blood vessels, on which we performed quantitative analysis to characterize epithelial morphology in vivo. In normal vessels, we found the cells to be planar polarized with curvature-dependent axial elongation of cells, and a robust circumferential alignment of actin bundles. While we found no measurable differences in morphology between normal and BAPN treated vessels, FAK-inhibited vessels have significantly smaller cells with a significant loss of preferential axial cell orientation and a loss of actin bundles. Our results demonstrate the feasibility of Botryllus schlosseri for imaging-based studies of dynamic epithelial remodeling and the mechanics of epithelial tubes; in addition, they suggest a critical role of integrin in the direction sensing mechanisms.In a second on going study, we are analyzing the 3-dimensional confocal scans of live vasculature. We were able to successfully produce the stereographic projections of the live blood vessels under control, BAPN treated and FAK inhibitor treated conditions and are working on extracting the morphological properties. We hope to identify and quantify the multiple mechanisms used by regressing Botryllus vasculature.In a third on going study, we are studying the blood flow rates and the branching behaviors of blood vessels in old and young Botryllus schlosseri. While slowing of blood flow and narrowing of blood vessels was visually shown to be the first stage of aging in seasquirts, no quantification has been done about the same. We find that blood vessels significantly narrow down in older animals and are working on quantifying the amount of branching in old and young animals.In a fourth and final study, the role of membrane tracking protein Rab35 on interface shortening during germband extension in Drosophila melanogaster was studied. Germband extension (GBE) is a developmental process that drives non-uniform tissue elongation through oriented cell intercalation. During GBE, interfaces along the dorsal-ventral (DV) axis shrink and new interfaces are formed along the AP axis. The results of this study showed that Rab35 compartments are enriched at the actively contracting interfaces and the disruption of Rab35 lead to failure of interface shortening.As each of these projects is different from one another thus making it difficult to form a single narrative, I only talk about the first study in this thesis .

Integrating single cell RNA-seq profiles is posing new challenges as datasets are rapidly expanding, now with over 100 million cells in the public domain. We present the latest version of the Harmony integration software, which efficiently scales to >100M cells and >1K datasets without specialized hardware. Moreover, optimizations to the underlying algorithm help prevent overintegration in biologically heterogeneous datasets. Harmony2 enables efficient, accurate integration of large, complex single-cell atlases.

Treatment-refractory rheumatoid arthritis (RA) is a major unmet need, and the mechanisms driving treatment resistance are poorly understood. To identify molecular determinants of RA non-remission, we performed spatial transcriptomic profiling on pre- and post-treatment synovial tissue biopsies from treatment naïve patients who received conventional DMARDs or adalimumab for 6 months. In the baseline biopsies of non-remission patients, we identified significant expansion of fibrogenic fibroblasts marked by high expression of , a fibrosis-associated extracellular matrix protein. hi fibroblasts localized to perivascular niches that, unexpectedly, served as transcriptional hubs for TGFβ activity. We identified endothelial-derived Notch signaling as an upstream regulator of fibroblast TGFβ signaling via its dual role in driving TGFβ isoform expression and suppressing TGFβ receptors, generating a proximal-distal gradient of TGFβ activity. Further, disruption of steady-state Notch signaling enabled fibrogenic fibroblast activation. Analysis of post-treatment biopsies revealed marked expansion of hi fibroblasts in non-remission RA patients, despite evidence of successful immune cell depletion, suggesting a spatiotemporal process of fibrogenic remodeling linked to treatment resistance. Collectively, our data implicates targeting of TGFβ signaling to prevent exuberant synovial tissue fibrosis as a potential therapeutic strategy for refractory RA.

The organization of immune cells in human tumors is not well understood. Immunogenic tumors harbor spatially-localized multicellular 'immunity hubs' defined by expression of the T cell-attracting chemokines CXCL10/CXCL11 and abundant T cells. Here, we examined immunity hubs in human pre-immunotherapy lung cancer specimens, and found that they were associated with beneficial responses to PD-1-blockade. Immunity hubs were enriched for many interferon-stimulated genes, T cells in multiple differentiation states, and CXCL9/10/11 + macrophages that preferentially interact with CD8 T cells. Critically, we discovered the stem-immunity hub, a subtype of immunity hub strongly associated with favorable PD-1-blockade outcomes, distinct from mature tertiary lymphoid structures, and enriched for stem-like TCF7+PD-1+ CD8 T cells and activated CCR7 + LAMP3 + dendritic cells, as well as chemokines that organize these cells. These results elucidate the spatial organization of the human intratumoral immune response and its relevance to patient immunotherapy outcomes.The organization of immune cells in human tumors is not well understood. Immunogenic tumors harbor spatially-localized multicellular 'immunity hubs' defined by expression of the T cell-attracting chemokines CXCL10/CXCL11 and abundant T cells. Here, we examined immunity hubs in human pre-immunotherapy lung cancer specimens, and found that they were associated with beneficial responses to PD-1-blockade. Immunity hubs were enriched for many interferon-stimulated genes, T cells in multiple differentiation states, and CXCL9/10/11 + macrophages that preferentially interact with CD8 T cells. Critically, we discovered the stem-immunity hub, a subtype of immunity hub strongly associated with favorable PD-1-blockade outcomes, distinct from mature tertiary lymphoid structures, and enriched for stem-like TCF7+PD-1+ CD8 T cells and activated CCR7 + LAMP3 + dendritic cells, as well as chemokines that organize these cells. These results elucidate the spatial organization of the human intratumoral immune response and its relevance to patient immunotherapy outcomes.

Interleukin (IL)-17A is a key driver of Spondyloarthritis (SpA) joint pathology. We aimed to identify its cellular source in synovial tissue from patients with two forms of SpA namely Axial SpA (AxSpA) and Psoriatic arthritis (PsA). Synovial tissue from patients with SpA was profiled using single-cell RNA sequencing (scRNA-seq: AxSpA, n=5 and PsA, n=6) or spatial RNA profiling (PsA, n=4). CellPhoneDB was used to infer cell–cell communication. Tissue resident memory Th17 (TRM17)-like cells were generated in vitro using blood memory CD4+ T cells from SpA patients. An epigenetic inhibitor library, siRNA and clustered regularly interspaced short palindromic repeats (CRISPR) were used to identify epigenetic regulator(s) for TRM17. scRNA-seq showed that CD4+CXCR6+ TRM17 cells are the predominant spontaneous IL17A producers in SpA synovium. Cell-cell communication and single-cell spatial analysis support the interaction between TRM17 and CLEC10A+ dendritic cells, which were activated in SpA. Both sublining and lining fibroblasts in SpA synovium showed evidence of IL-17A activation. In vitro-generated CD4+ TRM17-like cells phenocopied joint tissue TRM17, producing IL-17A/F upon T cell receptor (TCR) stimulation, which was further enhanced by cytokines. Perturbation of BRD1 inhibited the generation of TRM17-like cells. CD4+ TRM17 cells are the predominant source of IL-17A in SpA synovial tissue. TCR stimulation is essential for the secretion of IL-17A by CD4+TRM17-like cells. The epigenetic regulator BRD1 contributes to the generation of CD4+TRM17. Depleting CD4+TRM17 cells in SpA is thus a therapeutic strategy with potential to induce long-term remission. Interleukin (IL)-17A plays a key role in the immunopathogenesis of Spondyloarthritis (SpA), but its cellular source in joint tissue has not been determined previously. The induction and accumulation of CD4+ tissue resident memory Th17 (TRM17) cells following the clearance of pathogens has been described in skin, lung and kidney. Whether CD4+ TRM17 cells also accumulate in the joint and contribute to the pathology of SpA is not clear. CD4+ TRM17 cells are present in SpA synovial tissue and are the predominant source of IL17A CD4+ TRM17 cells in SpA joints express IL17A without any in vitro exogenous stimulation T cell receptor (TCR) rather than cytokine stimulation is essential for IL-17A production by CD4+ TRM17-like cells The epigenetic regulator BRD1 contributes to the generation of CD4+ TRM17-like cells. Our findings identify CD4+ TRM17 cells as the primary source of IL-17A in SpA synovium, a previously unrecognized role for these cells. Key questions remain: How do CD4+ TRM17 cells relate to IL-17A producers in synovial fluid? What mechanisms induce and maintain them in the joint? How do they interact with other cells to promote arthritis? These questions warrant further investigation. In addition, our data suggest that targeting CD4+ TRM17 cells, the “factory” of IL-17A in SpA synovial tissue, has the potential to induce long-term remission, encouraging future efforts to develop new therapies to deplete CD4+ TRM17 cells in SpA.

Current rheumatoid arthritis (RA) treatments do not restore immune tolerance. Investigating dendritic cell (DC) populations in human synovial tissue (ST) may reveal pathways to re-instate tolerance in RA. With single-cell and spatial-transcriptomics of synovial tissue biopsies, validated by micro co-culture systems, we identified condition and niche-specific myeloid DC clusters with distinct differentiation trajectories and functions. Healthy synovium contains a unique tolerogenic AXLpos DC2 cluster in the superficial sublining layer. In active RA, a macrophage-rich lining-layer niche becomes populated with inflammatory DC3 clusters that specifically activate memory CCL5pos TEM and CCL5posCXCL13pos TPH, promoting synovitis. In the sublining lymphoid niche, CCR7pos DC2 mReg specifically interact with naïve-T-cells, potentially driving the local expansion of new effector T-cells. Sustained remission sees the resolution of these niches but lacks the recovery of tolerogenic AXLpos DC2, indicating latent potential for disease flare. A human RA disease-flare model showed that the activation of blood predecessor of ST-DC3 clusters precedes the onset of inflammation in joints. Therapeutic strategies targeting pathogenic ST-DC3 clusters, or reinstating tolerogenic AXLpos DC2, may restore immune homeostasis in RA. Deconstruction of human RA synovium, using single-cell spatial transcriptomics and micro-culture systems, reveals distinct neighbourhoods within the synovial architecture across health, and RA patients with active disease or sustained remission. Discrete niches are identified that contain distinct myeloid DC clusters that differ in frequency, differentiation trajectories, and effector functions. Human RA synovium exhibits condition and niche specific myeloid DC clusters that vary in their tissue differentiation trajectories and functions. ST-CD14pos DC3 (iDC3) support inflammatory CCL5pos TEM and CCL5pos TPH cell activation in the hyperplastic lining layer. ST-CCR7pos DC2 (mReg), driven by MIR155, interact with naïve-T-cells in sublining lymphoid niches. A specific inflammatory signature of blood predecessors of ST-DC3s predict flare in RA.

Objectives: Approximately 20–30% of patients with COVID-19 require hospitalization, and 5–12% may require critical care in an intensive care unit (ICU). A rapid surge in cases of severe COVID-19 will lead to a corresponding surge in demand for ICU care. Because of constraints on resources, frontline healthcare workers may be unable to provide the frequent monitoring and assessment required for all patients at high risk of clinical deterioration. We developed a machine learning-based risk prioritization tool that predicts ICU transfer within 24 h, seeking to facilitate efficient use of care providers’ efforts and help hospitals plan their flow of operations. Methods: A retrospective cohort was comprised of non-ICU COVID-19 admissions at a large acute care health system between 26 February and 18 April 2020. Time series data, including vital signs, nursing assessments, laboratory data, and electrocardiograms, were used as input variables for training a random forest (RF) model. The cohort was randomly split (70:30) into training and test sets. The RF model was trained using 10-fold cross-validation on the training set, and its predictive performance on the test set was then evaluated. Results: The cohort consisted of 1987 unique patients diagnosed with COVID-19 and admitted to non-ICU units of the hospital. The median time to ICU transfer was 2.45 days from the time of admission. Compared to actual admissions, the tool had 72.8% (95% CI: 63.2–81.1%) sensitivity, 76.3% (95% CI: 74.7–77.9%) specificity, 76.2% (95% CI: 74.6–77.7%) accuracy, and 79.9% (95% CI: 75.2–84.6%) area under the receiver operating characteristics curve. Conclusions: A ML-based prediction model can be used as a screening tool to identify patients at risk of imminent ICU transfer within 24 h. This tool could improve the management of hospital resources and patient-throughput planning, thus delivering more effective care to patients hospitalized with COVID-19.

Early detection of patients at risk for clinical deterioration is crucial for timely intervention. Traditional detection systems rely on a limited set of variables and are unable to predict the time of decline. We describe a machine learning model called MEWS++ that enables the identification of patients at risk of escalation of care or death six hours prior to the event. A retrospective single-center cohort study was conducted from July 2011 to July 2017 of adult (age > 18) inpatients excluding psychiatric, parturient, and hospice patients. Three machine learning models were trained and tested: random forest (RF), linear support vector machine, and logistic regression. We compared the models’ performance to the traditional Modified Early Warning Score (MEWS) using sensitivity, specificity, and Area Under the Curve for Receiver Operating Characteristic (AUC-ROC) and Precision-Recall curves (AUC-PR). The primary outcome was escalation of care from a floor bed to an intensive care or step-down unit, or death, within 6 h. A total of 96,645 patients with 157,984 hospital encounters and 244,343 bed movements were included. Overall rate of escalation or death was 3.4%. The RF model had the best performance with sensitivity 81.6%, specificity 75.5%, AUC-ROC of 0.85, and AUC-PR of 0.37. Compared to traditional MEWS, sensitivity increased 37%, specificity increased 11%, and AUC-ROC increased 14%. This study found that using machine learning and readily available clinical data, clinical deterioration or death can be predicted 6 h prior to the event. The model we developed can warn of patient deterioration hours before the event, thus helping make timely clinical decisions.