scholarly journals High-Dimensional Single-Cell Cartography Reveals Novel Skeletal Muscle Resident Cell Populations

2018 ◽  
Author(s):  
Lorenzo Giordani ◽  
Gary J. He ◽  
Elisa Negroni ◽  
Hiroshi Sakai ◽  
Justin Y. C. Law ◽  
...  
Keyword(s):  
Skeletal Muscle ◽  
Single Cell ◽  
High Dimensional ◽  
Cell Populations ◽  
Resident Cell

scholarly journals High-Dimensional Single-Cell Cartography Reveals Novel Skeletal Muscle-Resident Cell Populations

2019 ◽  
Vol 74 (3) ◽  
pp. 609-621.e6 ◽  
Author(s):  
Lorenzo Giordani ◽  
Gary J. He ◽  
Elisa Negroni ◽  
Hiroshi Sakai ◽  
Justin Y.C. Law ◽  
...  
Keyword(s):  
Skeletal Muscle ◽  
Single Cell ◽  
High Dimensional ◽  
Cell Populations ◽  
Resident Cell

scholarly journals High-dimensional single-cell cartography reveals novel skeletal muscle resident cell populations

2018 ◽  
Author(s):  
Lorenzo Giordani ◽  
Gary J. He ◽  
Elisa Negroni ◽  
Hiroshi Sakai ◽  
Justin Y. C. Law ◽  
...  
Keyword(s):  
Skeletal Muscle ◽  
Single Cell ◽  
Muscle Tissue ◽  
Cell Types ◽  
Skeletal Muscle Tissue ◽  
High Dimensional ◽  
Cell Populations ◽  
Adult Tissue ◽  
Adult Skeletal Muscle ◽  
Different Cell Types

AbstractAdult tissue repair and regeneration require the activation of resident stem/progenitor cells that can self-renew and generate differentiated progeny. The regenerative capacity of skeletal muscle relies on muscle satellite cells (MuSCs) and their interplay with different cell types within the niche. Yet, our understanding of the cells that compose the skeletal muscle tissue is limited and molecular definitions of the principal cell types are lacking. Using a combined approach of single-cell RNA-sequencing and mass cytometry, we precisely mapped the different cell types in adult skeletal muscle tissue and highlighted previously overlooked populations. We identified known functional populations, characterized their gene signatures, and determined key markers. Among the ten main cell populations present in skeletal muscle, we found an unexpected complexity in the interstitial compartment and identified two new cell populations. One express the transcription factor Scleraxis and generate tenocyte-like cells. The second express smooth muscle and mesenchymal cell markers (SMMCs). While distinct from MuSCs, SMMCs are endowed with myogenic potential and promote MuSC engraftment following transplantation. Our high-dimensional single-cell atlas uncovers principles of an adult tissue composition and can be exploited to reveal unknown cellular sub-fractions that contribute to tissue regeneration.

scholarly journals Sensitive detection of rare disease-associated cell subsets via representation learning

2016 ◽  
Author(s):  
Eirini Arvaniti ◽  
Manfred Claassen
Keyword(s):  
Single Cell ◽  
Rare Disease ◽  
Peripheral Blood ◽  
Residual Disease ◽  
Representation Learning ◽  
High Dimensional ◽  
Cell Populations ◽  
Learning Approach ◽  
Paracrine Signaling ◽  
Minimal Residual

Rare cell populations play a pivotal role in the initiation and progression of diseases like cancer. However, the identification of such subpopulations remains a difficult task. This work describes CellCnn, a representation learning approach to detect rare cell subsets associated with disease using high dimensional single cell measurements. Using CellCnn, we identify paracrine signaling and AIDS onset associated cell subsets in peripheral blood, and minimal residual disease associated populations in leukemia with frequencies as low as 0.005%.

scholarly journals Single-cell analysis of the muscle stem cell hierarchy identifies heterotypic communication signals involved in skeletal muscle regeneration

2019 ◽  
Author(s):  
Andrea J. De Micheli ◽  
Paula Fraczek ◽  
Sharon Soueid-Baumgarten ◽  
Hiranmayi Ravichandran ◽  
Iwijn De Vlaminck ◽  
...  
Keyword(s):  
Skeletal Muscle ◽  
Stem Cell ◽  
Single Cell ◽  
Progenitor Cells ◽  
Muscle Regeneration ◽  
Cell Types ◽  
Myogenic Cell ◽  
Skeletal Muscle Regeneration ◽  
Cell Populations ◽  
Communication Signals

AbstractMuscle stem cells (MuSCs) are an essential adult stem cell population with the capacity to self-renew and regenerate muscle tissue. Functionally heterogeneous subpopulations of MuSCs have been identified based on their expression of myogenic regulatory factors and surface markers. However, a unified organization of muscle stem and progenitor cells and their subpopulations remains unresolved. Here, we performed temporal analysis of skeletal muscle regeneration using single-cell RNA-sequencing (scRNA-seq) of myotoxin-injured adult mouse hindlimb muscles. We generated over 34,000 single-cell transcriptomes spanning four muscle regeneration time-points and identified 15 distinct cell types, including a heterogeneous population of MuSCs and progenitor cells. Our analysis provides a hierarchical map of myogenic cell populations and identifies stage-specific regulatory programs that govern their contributions to muscle regeneration. In this transcriptomic atlas, we observed cell type-specific regenerative dynamics, exemplified by waves of transient amplification and diversification of multiple immune cell types and, subsequently, myogenic cells. Unbiased trajectory inference organized the myogenic cell populations within the atlas into a continuum, consisting of a hierarchy of quiescent MuSCs, cycling progenitors, committed myoblasts, and terminally differentiated myocytes. This myogenic trajectory matched prior understanding and also revealed that MuSC stages are defined by synchronous changes in regulatory factors, cell cycle-associated, and surface receptor gene expression. Lastly, we analyzed the transcriptomic atlas to identify over 100 candidate heterotypic communication signals between myogenic and non-myogenic cell populations, including many involving the fibroblast growth factor (FGF), Notch, and Syndecan receptor families and their associated ligands. Syndecan receptors were implicated in a large fraction of these cell communication interactions and were observed to exhibit transcriptional heterogeneity within the myogenic continuum. Using multiparameter mass cytometry (CyTOF), we confirmed that cycling MuSCs exhibit diversified Syndecan-1/2 expression, which suggests that dynamic alterations in Syndecan signaling interactions may coordinate stage-specific myogenic cell fate regulation. This scRNA-seq reference atlas provides a resolved hierarchical organization of myogenic subpopulations as a resource to investigate cell-cell interactions that regulate myogenic stem and progenitor cell fates in muscle regeneration.

scholarly journals High-Dimensional and Single-Cell Transcriptome Analysis of AITL Tumor Microenvironment Reveals Gross Expansion of Novel Dysfunctional CD8+ T Cell Populations, Global Shift in B Cell Phenotypes

Blood ◽  
2020 ◽  
Vol 136 (Supplement 1) ◽  
pp. 42-43
Author(s):  
Joshua C. Pritchett ◽  
Zhi-Zhang Yang ◽  
Hyojin Kim ◽  
Jose C Villasboas ◽  
Andrew L. Feldman ◽  
...  
Keyword(s):  
T Cell ◽  
B Cell ◽  
Single Cell ◽  
Transcriptome Analysis ◽  
Research Funding ◽  
High Dimensional ◽  
Cell Populations ◽  
Cell Transcriptome ◽  
Single Cell Transcriptome ◽  
Cell Phenotypes

BACKGROUND: Angioimmunoblastic T cell lymphoma (AITL) has a unique histological profile comprised of a relatively small number of malignant CD4+ T-cells of TFH phenotype inter-mixed with an extensive infiltrate of multi-lineage immune cells. In our study, we have utilized mass cytometry, high-dimensional analysis, and single-cell transcriptome analysis to provide novel insights into the unique phenotypes that comprise this intra-tumoral microenvironment. We then extended this work to explore clinical associations including peripheral serum analysis of AITL patients and normal controls. To our knowledge, this represents the first such analysis of its kind in AITL. METHODS: We designed two novel CyTOF antibody (Ab) panels to identify and characterize cells of T, B, NK, monocyte and fDC lineages. Samples analyzed included a cohort of 25 biopsy specimens from 8 histologically confirmed AITL patients (5 lymph node (LN), 3 spleen (SP)) and 17 normal controls across key comparator immune tissue types (7 LN, 6 SP, 4 tonsil (TL)). Extensive high-dimensional analysis of CyTOF data was then performed to provide novel insights into key phenotypes and trends of malignant and non-malignant populations in AITL. We then performed CITE-Seq on control and AITL samples to gain further insight into the RNA transcriptome of key T cell populations at the cellular level. Finally, peripheral serum analysis of cytokines, soluble immune receptors, and ligands were then measured by multiplex ELISA from a separate cohort of 22 samples (5 AITL, 17 control) distinct from the individuals analyzed in the original high-dimensional study cohort. RESULTS: While the presence of "reactive" CD8+ populations is a known histologic hallmark of AITL, we describe the gross expansion of novel CD8+ populations with distinctive immunophenotypic features which have not previously been detailed in this malignancy. Using single-cell protein expression data from CyTOF, these expanded CD8+ populations can be broadly categorized as "effector memory" (CCR7-, CD45RO+, CD45RA-) and further characterized phenotypically by markers of progressive exhaustion, checkpoint inhibition, and terminal differentiation (PD1++, TIGIT++, ICOS+, TIM3+). Further analysis of the single-cell transcriptome from these expanded CD8+ populations via CITE-Seq revealed an expression signature consistent with dysfunction and limited cytotoxic activity (including significant down-regulation of granzyme, perforin, and IFN-g) when compared to benign and malignant controls. Interestingly, when compared to CD8+ populations of identical phenotype found in control tissues, these cells also featured marked upregulation of XCL2 and XCL1 in AITL. Additionally, global shifts in infiltrating CD19+ B cell phenotypes were seen in AITL, marked specifically by diminished expression of both CXCR5 and CD73. Finally, soluble PD-1 and other key immune molecules implicated in the expanded tumor microenvironment were found to be significantly increased in the peripheral serum of AITL patients compared to controls (1567.9 pg/mL (1109.3 S.E.) in AITL vs 29.79 (8.84 S.E.) in controls; P<0.0001). CONCLUSIONS: High-dimensional and single-cell transcriptome analysis of the AITL microenvironment yielded several novel insights which have not been previously described in this malignancy. Highlights include the gross expansion of distinct CD8+ populations - the majority of which are of an exhausted, dysfunctional phenotype featuring marked upregulation of XCL2 and XCL1 - and the global loss of CXCR5 and CD73 expression among AITL CD19+ B cell populations. Taken together, this suggests the presence of aberrant non-malignant immune subsets within the AITL microenvironment which may contribute to novel mechanisms of immune escape. Disclosures Cerhan: NanoString: Research Funding; BMS/Celgene: Research Funding. Ansell:Bristol Myers Squibb: Research Funding; ADC Therapeutics: Research Funding; Seattle Genetics: Research Funding; Regeneron: Research Funding; Affimed: Research Funding; AI Therapeutics: Research Funding; Trillium: Research Funding; Takeda: Research Funding.

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