High-resolution myogenic lineage mapping by single-cell mass cytometry
NATURE CELL BIOLOGY
2017; 19 (5): 558-?
Muscle regeneration is a dynamic process during which cell state and identity change over time. A major roadblock has been a lack of tools to resolve a myogenic progression in vivo. Here we capitalize on a transformative technology, single-cell mass cytometry (CyTOF), to identify in vivo skeletal muscle stem cell and previously unrecognized progenitor populations that precedeádifferentiation. We discovered two cell surface markers, CD9 and CD104, whose combined expression enabled inávivoáidentification and prospective isolation of stem and progenitor cells. Data analysis using the X-shift algorithm paired withásingle-cell force-directed layout visualization defined a molecular signature of the activated stem cell state (CD44(+)/CD98(+)/MyoD(+)) and delineated a myogenic trajectory during recovery from acute muscle injury. Our studies uncover the dynamics of skeletal muscle regeneration in vivo and pave the way for the elucidation of the regulatory networks that underlie cell-state transitions in muscle diseases and ageing.
View details for DOI 10.1038/ncb3507
View details for Web of Science ID 000400376100019
View details for PubMedID 28414312
Diabetes-linked transcription factor HNF4a regulates metabolism of endogenous methylarginines and ▀-aminoisobutyric acid by controlling expression of alanine-glyoxylate aminotransferase 2.
2016; 6: 35503-?
Elevated levels of circulating asymmetric and symmetric dimethylarginines (ADMA and SDMA) predict and potentially contribute to end organ damage in cardiovascular diseases. Alanine-glyoxylate aminotransferase 2 (AGXT2) regulates systemic levels of ADMA and SDMA, and also of beta-aminoisobutyric acid (BAIB)-a modulator of lipid metabolism. We identified a putative binding site for hepatic nuclear factor 4 ? (HNF4?) in AGXT2 promoter sequence. In a luciferase reporter assay we found a 75% decrease in activity of Agxt2 core promoter after disruption of the HNF4? binding site. Direct binding of HNF4? to Agxt2 promoter was confirmed by chromatin immunoprecipitation assay. siRNA-mediated knockdown of Hnf4a led to an almost 50% reduction in Agxt2 mRNA levels in Hepa 1-6 cells. Liver-specific Hnf4a knockout mice exhibited a 90% decrease in liver Agxt2 expression and activity, and elevated plasma levels of ADMA, SDMA and BAIB, compared to wild-type littermates. Thus we identified HNF4? as a major regulator of Agxt2 expression. Considering a strong association between human HNF4A polymorphisms and increased risk of type 2 diabetes our current findings suggest that downregulation of AGXT2 and subsequent impairment in metabolism of dimethylarginines and BAIB caused by HNF4? deficiency might contribute to development of cardiovascular complications in diabetic patients.
View details for DOI 10.1038/srep35503
View details for PubMedID 27752141
View details for PubMedCentralID PMC5067591
- Diabetes-linked transcription factor HNF4 alpha regulates metabolism of endogenous methylarginines and beta-aminoisobutyric acid by controlling expression of alanine-glyoxylate aminotransferase 2 SCIENTIFIC REPORTS 2016; 6
Automated mapping of phenotype space with single-cell data
2016; 13 (6): 493-?
Accurate identification of cell subsets in complex populations is key to discovering novelty in multidimensional single-cell experiments. We present X-shift (http://web.stanford.edu/~samusik/vortex/), an algorithm that processes data sets using fast k-nearest-neighbor estimation of cell event density and arranges populations by marker-based classification. X-shift enables automated cell-subset clustering and access to biological insights that 'prior knowledge' might prevent the researcher from discovering.
View details for DOI 10.1038/NMETH.3863
View details for Web of Science ID 000377480100015
View details for PubMedID 27183440
View details for PubMedCentralID PMC4896314
Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing
2016; 22: 557-563
Recent technological developments allow gathering single-cell measurements across different domains (genomic, transcriptomics, proteomics, imaging etc). Sophisticated computational algorithms are required in order to harness the power of single-cell data. This session is dedicated to computational methods for single-cell analysis in various biological domains, modelling of population heterogeneity, as well as translational applications of single cell data.
View details for PubMedID 27897006
Mass Cytometric Functional Profiling of Acute Myeloid Leukemia Defines Cell-Cycle and Immunophenotypic Properties That Correlate with Known Responses to Therapy.
2015; 5 (9): 988-1003
Acute myeloid leukemia (AML) is characterized by a high relapse rate that has been attributed to the quiescence of leukemia stem cells (LSCs), which renders them resistant to chemotherapy. However, this hypothesis is largely supported by indirect evidence and fails to explain the large differences in relapse rates across AML subtypes. To address this, bone marrow aspirates from 41 AML patients and five healthy donors were analyzed by high-dimensional mass cytometry. All patients displayed immunophenotypic and intracellular signaling abnormalities within CD34+CD38low populations and several karyotype and genotype-specific surface marker patterns were identified. The immunophenotypic stem and early progenitor cell populations from patients with clinically favorable core-binding factor AML demonstrated a five-fold higher fraction of cells in S-phase compared to other AML samples. Conversely, LSCs in less clinically favorable FLT3-ITD AML exhibited dramatic reductions in S-phase fraction. Mass cytometry also allowed direct observation of the in vivo effects of cytotoxic chemotherapy.
View details for DOI 10.1158/2159-8290.CD-15-0298
View details for PubMedID 26091827