Publications by authors named "Suoqin Jin"

Article Synopsis
  • Rosacea is a chronic skin condition, and this study reveals that unique cell changes in the skin of affected patients may involve a specific type of keratinocyte damaged by IFNγ signaling.* -
  • Research indicates that rosacea is characterized by an increase in various inflammatory cells and dysfunctional vascular cells, which contribute to its symptoms.* -
  • Fibroblasts are identified as central players in producing inflammatory signals related to rosacea, and targeting these cells could be a potential strategy for treating the condition.*
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Recent advances in single-cell sequencing technologies offer an opportunity to explore cell-cell communication in tissues systematically and with reduced bias. A key challenge is integrating known molecular interactions and measurements into a framework to identify and analyze complex cell-cell communication networks. Previously, we developed a computational tool, named CellChat, that infers and analyzes cell-cell communication networks from single-cell transcriptomic data within an easily interpretable framework.

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Objective: Owing to the heterogeneity in the evolution of cancer, distinguishing between diverse growth patterns and predicting long-term outcomes based on short-term measurements poses a great challenge.

Methods: A novel multiscale framework is proposed to unravel the connections between the population dynamics of cancer growth (i.e.

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Background: Endometrial Cancer (EC) is one of the most prevalent malignancies that affect the female population globally. In the context of immunotherapy, Tumor Mutation Burden (TMB) in the DNA polymerase epsilon (POLE) subtype of this cancer holds promise as a viable therapeutic target.

Methods: We devised a method known as NEM-TIE to forecast the TMB status of patients with endometrial cancer.

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Background: The oocyte-to-embryo transition (OET) converts terminally differentiated gametes into a totipotent embryo and is critically controlled by maternal mRNAs and proteins, while the genome is silent until zygotic genome activation. How the transcriptome, translatome, and proteome are coordinated during this critical developmental window remains poorly understood.

Results: Utilizing a highly sensitive and quantitative mass spectrometry approach, we obtain high-quality proteome data spanning seven mouse stages, from full-grown oocyte (FGO) to blastocyst, using 100 oocytes/embryos at each stage.

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Niche signals maintain stem cells in a prolonged quiescence or transiently activate them for proper regeneration. Altering balanced niche signalling can lead to regenerative disorders. Melanocytic skin nevi in human often display excessive hair growth, suggesting hair stem cell hyperactivity.

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Radiomics, providing quantitative data extracted from medical images, has emerged as a critical role in diagnosis and classification of diseases such as glioma. One main challenge is how to uncover key disease-relevant features from the large amount of extracted quantitative features. Many existing methods suffer from low accuracy or overfitting.

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Spinal motor neurons (MNs) integrate sensory stimuli and brain commands to generate movements. In vertebrates, the molecular identities of the cardinal MN types such as those innervating limb versus trunk muscles are well elucidated. Yet the identities of finer subtypes within these cell populations that innervate individual muscle groups remain enigmatic.

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Although single-cell sequencing has provided a powerful tool to deconvolute cellular heterogeneity of diseases like cancer, extrapolating clinical significance or identifying clinically-relevant cells remains challenging. Here, we propose a novel computational method scAB, which integrates single-cell genomics data with clinically annotated bulk sequencing data via a knowledge- and graph-guided matrix factorization model. Once combined, scAB provides a coarse- and fine-grain multiresolution perspective of phenotype-associated cell states and prognostic signatures previously not visible by single-cell genomics.

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Delayed and often impaired wound healing in the elderly presents major medical and socioeconomic challenges. A comprehensive understanding of the cellular/molecular changes that shape complex cell-cell communications in aged skin wounds is lacking. Here, we use single-cell RNA sequencing to define the epithelial, fibroblast, immune cell types, and encompassing heterogeneities in young and aged skin during homeostasis and identify major changes in cell compositions, kinetics, and molecular profiles during wound healing.

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Article Synopsis
  • Calcium imaging allows researchers to record many neurons at once while they perform complex tasks, but tracking these cells over time is challenging due to movements and changes in the imaging setup.
  • The authors introduce a new method called SCOUT that uses advanced techniques to track individual cells across multiple experiments, making it easier to identify and monitor cell populations.
  • SCOUT outperforms previous tracking methods in various testing conditions, especially when cell positions shift or when the quality of neural data is not ideal.
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Tissue development and homeostasis require coordinated cell-cell communication. Recent advances in single-cell sequencing technologies have emerged as a revolutionary method to reveal cellular heterogeneity with unprecedented resolution. This offers a great opportunity to explore cell-cell communication in tissues systematically and comprehensively, and to further identify signaling mechanisms driving cell fate decisions and shaping tissue phenotypes.

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Identification of intercellular signaling changes across multiple single-cell RNA-sequencing (scRNA-seq) datasets as well as how intercellular communications affect intracellular transcription factors (TFs) to regulate target genes is crucial in understanding how distinct cell states respond to evolution, perturbations, and diseases. Here, we first generalized our previously developed tool CellChat, enabling flexible comparison analysis of cell-cell communication networks across any number of scRNA-seq datasets from interrelated biological conditions. This greatly facilitates the ready detection of signaling changes of cell-cell communication in response to any biological perturbations.

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Cell-cell communication is a fundamental process that shapes biological tissue. Historically, studies of cell-cell communication have been feasible for one or two cell types and a few genes. With the emergence of single-cell transcriptomics, we are now able to examine the genetic profiles of individual cells at unprecedented scale and depth.

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Understanding global communications among cells requires accurate representation of cell-cell signaling links and effective systems-level analyses of those links. We construct a database of interactions among ligands, receptors and their cofactors that accurately represent known heteromeric molecular complexes. We then develop CellChat, a tool that is able to quantitatively infer and analyze intercellular communication networks from single-cell RNA-sequencing (scRNA-seq) data.

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The interfollicular epidermis (IFE) forms a water-tight barrier that is often disrupted in inflammatory skin diseases. During homeostasis, the IFE is replenished by stem cells in the basal layer that differentiate as they migrate toward the skin surface. Conventionally, IFE differentiation is thought to be stepwise as reflected in sharp boundaries between its basal, spinous, granular and cornified layers.

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Our knowledge of transcriptional heterogeneities in epithelial stem and progenitor cell compartments is limited. Epidermal basal cells sustain cutaneous tissue maintenance and drive wound healing. Previous studies have probed basal cell heterogeneity in stem and progenitor potential, but a comprehensive dissection of basal cell dynamics during differentiation is lacking.

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The circadian clock coordinates a variety of immune responses with signals from the external environment to promote survival. We investigated the potential reciprocal relationship between the circadian clock and skin inflammation. We treated mice topically with the Toll-like receptor 7 (TLR7) agonist imiquimod (IMQ) to activate IFN-sensitive gene (ISG) pathways and induce psoriasiform inflammation.

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Simultaneous measurements of transcriptomic and epigenomic profiles in the same individual cells provide an unprecedented opportunity to understand cell fates. However, effective approaches for the integrative analysis of such data are lacking. Here, we present a single-cell aggregation and integration (scAI) method to deconvolute cellular heterogeneity from parallel transcriptomic and epigenomic profiles.

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Recent anatomical evidence suggests a functionally significant back-projection pathway from the subiculum to the CA1. Here we show that the afferent circuitry of CA1-projecting subicular neurons is biased by inputs from CA1 inhibitory neurons and the visual cortex, but lacks input from the entorhinal cortex. Efferents of the CA1-projecting subiculum neurons also target the perirhinal cortex, an area strongly implicated in object-place learning.

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Single cell technologies provide an unprecedented opportunity to explore the heterogeneity in a biological process at the level of single cells. One major challenge in analyzing single cell data is to identify cell subpopulations, stable cell states, and cells in transition between states. To elucidate the transition mechanisms in cell fate dynamics, it is highly desirable to quantitatively characterize cellular states and intermediate states.

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Article Synopsis
  • During skin wound healing in adult mice, hair follicles and adipocytes regenerate, with adipocytes coming from specialized contractile fibroblasts called myofibroblasts.
  • Researchers utilized single-cell RNA-sequencing to identify twelve different clusters of wound fibroblasts, revealing various stages of differentiation and distinct lineages.
  • The study found that some fibroblasts originate from hematopoietic (blood-related) cells, which contribute to myofibroblast and adipocyte regeneration, highlighting the diverse nature of fibroblasts during wound healing.
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Motivation: Single-cell RNA-sequencing (scRNA-seq) offers unprecedented resolution for studying cellular decision-making processes. Robust inference of cell state transition paths and probabilities is an important yet challenging step in the analysis of these data.

Results: Here we present scEpath, an algorithm that calculates energy landscapes and probabilistic directed graphs in order to reconstruct developmental trajectories.

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The control of complex networks is one of the most challenging problems in the fields of biology and engineering. In this study, the authors explored the controllability and control energy of several signalling networks, which consisted of many interconnected pathways, including networks with a bow-tie architecture. On the basis of the theory of structure controllability, they revealed that biological mechanisms, such as cross-pathway interactions, compartmentalisation and so on make the networks easier to fully control.

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