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MICB 402 > Paper 5: DC, scRNAseq > Flashcards

Paper 5: DC, scRNAseq Flashcards

1
Q

what is the moral of the 6 blind men and the elephant

A
  • we can’t know the whole system by only studying its individual parts
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2
Q

systems biology

A
  • integrating and analyzing complex data sets using various experimental platforms and inter-disciplinary tools to better understand complex biological systems
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3
Q

mononuclear phagocyte system (MPS)

A
  • comprised of BM precursors, monocytes, tissue macrophages and DCs
  • cells of MPS are heterogenous based on ontogeny, phenotype, and function
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4
Q

before this study, what were the DC subtypes (2)

A
  • CD11C+ conventional DCs (cDCs) consisting of either CD141+ or CD1C+ cells
  • plasmacytoid DCs (pDCs) consisting of CD123+ cells
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5
Q

before this study, what was the known role of cDCs

A
  • effective at antigen-specific simulation of CD4+ and CD8+ T cells
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6
Q

before this study, what was the known role of pDCs

A
  • specialize in producing type I interferons in response to viruses
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7
Q

why was problematic about the previous classification of DC subsets (2)

A
  • definition of DCs was likely biased by limited markers available to identify, isolate, and manipulate the cells
  • these biases would alter the assignment of function and origin of each DC subtype
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8
Q

how did the paper overcome previous biases in DC classification

A
  • used single-cell RNA sequencing (scRNA-seq)
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9
Q

what strategy was used for the discovery and validation of DC and monocyte subtypes (7)

A
  1. perform scRNA-seq on cels
  2. identify clusters of cells similar to each other
  3. find discriminate markers per cluster
  4. isolate cells corresponding to key clusters using newly identified surface markers
  5. validate identity of sorted cells using scRNA-seq
  6. confirm existence of cell types in healthy individuals
  7. perform functional analyses for selected cell types
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10
Q

what was the purpose of figure 1

A
  • to perform single-cell profiling of blood DCs and monocytes and an unbiased classification of DCs
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11
Q

what was observed in figure 1A (2)

A
  • to analyze blood DC and monocyte populations, FACS is performed
  • to define subpopulations and identify useful markers for further isolation, scRNA-seq using modified Smart-Seq2 was used
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12
Q

what was used to obtain figure 1B

A
  • FACS
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13
Q

what was the observed in figure 1B (4)

A
  • CD11C+ and and CD11C- DC populations were separated using CD11C and HLA-DR markers
  • CD11C+ DCs, the cDCs, were further separated into CD141+CDC1- and CD141-CDC1+ populations
  • CD11C- DCs, the pDCs, were enriched for CD123+ expression
  • subpopulations not previously identified appeared in these graphs, for instance the CD11C-CD123- population of pDCs
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14
Q

what was observed in figure 1C (6)

A
  • 6 clusters observed in the t-SNE visualization:
    DC1: corresponds to known CD141+ cDCs
    DC2: contain known CD1C+ cDCs
    DC3: contain known CD1C+ cDCs
    DC4: contain poorly characterized CD141-CD1C- population
    DC5: does not correspond to any known blood DC subtype
    DC6: corresponds to known pDCs
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15
Q

what was observed in figure 1D

A
  • identification of 200+ genes that best classified cells into 6 populations
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16
Q

figure 1D: what are CLEC9A+ DCs/mapping of DC1 cluster (3)

A
  • they describe the DC population previously classified as CD141+ DCs
  • CD141 marker was a poor discriminator for the cluster as it was also expressed by cells captured in DC5 and DC6 populations
  • CLEC9A appears to be a perfect discriminative surface marker for DC1 cluster
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17
Q

figure 1D: what did the DC2 and DC3 clusters map to

A
  • CD1C+ DCs; CDC1 was the best and sole marker uniquely shared by both clusters
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18
Q

figure 1D: what did the DC4 cluster map to

A
  • CD141-CD1C- population
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19
Q

figure 1D: what did the DC5 cluster map to

A
  • best defined by surface markers AXL and SIGLEC6
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20
Q

figure 1D: what did DC6 cluster map to (2)

A
  • mapped to pDCs
  • common markers used to identify pDCs were also expressed in DC5 population, so new combination of markers that distinguish pDCs from DC5 population was identified
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21
Q

what were the functional findings from figure 1

A
  • identification of discriminative markers that can be used in combination to isolate cell populations corresponding to known DC subsets (with higher purity) as well as previously uncharacterized subsets
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22
Q

tSNE (3)

A
  • t-stochastic neighbour embedding algorithm
  • dimensionality reduction algorithm that preserves the single cell resolution of data while capturing non-linear relationships present in the data
  • essentially separates single cells into distinct categories/types based on commonalities among cell types
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23
Q

what is the purpose of figure 2

A
  • to define and validate the existence of CD1C+ DC subsets
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24
Q

what was observed in figure 2A (2)

A
  • CD1C_B (DC3) were distinguished by their expression of acute and chronic inflammatory genes
  • CD1C_A (DC2) were distinguished by slightly higher levels of MHC class II genes
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25
Q

what was observed in figure 2B

A
  • isolation of cells by flow cytometry
  • use of CD32B cell marker for CD1C_A DCs
  • use of CD163 and CD36 cell markers for CD1C_B DCs
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26
Q

what was observed in figure 2C

A
  • scRNA-seq of isolated cells from each subset reflect the original split observed in the CD1C+ DCs
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27
Q

what is CSFE (2)

A
  • a graph that illustrates the rates of proliferating cells
  • proliferating cells will be more diluted in dye used for CSFE and will appear in less values on the CSFE plot
28
Q

what was observed in figure 2D (2)

A
  • CD1C_A and CD1C_B DC subsets are potent stimulators of naive T cell proliferation
  • this is consistent with the known function of cDCs and is different from monocyte and pDC functions
29
Q

what were the findings of figure 2

A
  • scRNA-seq revealed heterogeneity in CD1C_ DCs and a new hypotheses about their function
30
Q

what was the purpose of figure 3 (2)

A
  • to investigate monocyte subsets and their relationships to DC subsets
  • some key genes known to be associated with monocytes were also expressed by CD1C_B and CD141-CD1C- cells
31
Q

what was observed in figure 3A (2)

A
  • blood monocytes were profiled using CD14 and CD16, which are established markers of monocytes
  • 3 subsets shown: CD14++CD16- (classical), CD14++CD16+ (intermediate), and CD14+CD16++ (non-classical)
32
Q

what was observed in figure 3B

A
  • four clusters of monocytes shown in the tSNE plot
33
Q

figure 3C: monocyte classifications (4)

A
  • Mono1 contained CD14++CD16- (classical) monocytes
  • Mono2 contained CD14+CD16++ (non-classical) monocytes
  • Mono3 contained monocytes with unique combination of genes that have potential to affect cell cycle, differentiation, and trafficking
  • Mono4 contained monocytes that expressed cytotoxic gene signature
34
Q
  • what type of population are intermediate monocytes
A
  • the previously classified intermediate monocyte (CD14++CD16+) was a heterogenous population of monocytes
35
Q

what was observed in figure 3C

A
  • Mono 2 seemed to have similar gene expression to DC4s
  • Mono 3 and Mono 1 seemed to have similar gene expression
36
Q

what was the purpose of figure 4

A
  • to investigate the AXL+SIGLEC6+ population and its relation to cDCs and pDCs
37
Q

what was observed in figure 4A

A
  • the DC5 population is defined by its unique expression levels of AXL and SIGLEC6 markers compared to the other DC subsets
38
Q

what was observed in figure 4B (2)

A
  • confirmation of the existence of AXL+SIGLEC6+ (AS) DCs within original DC gate using flow cytometry analysis of peripheral blood mononuclear cells
  • use of combinatorial expression of AXL, SIGLEC6+, CD123, and CD11C at protein levels allowed for isolation of 2 AS DC subtypes
39
Q

what was observed in figure 4C

A
  • newly sorted DC cells clustered together with original cluster, validating the enrichment strategy
40
Q

what was observed in figure 4E

A
  • AS DCs exhibited a spectrum of states based on gene expression defined by cells enriched for pDC-like signature (CD123) and cells enriched for cDC-like signature (CD11C)
  • use of combinatorial expression of AXL, SIGLEC6+, CD123, and CD11C at mRNA levels allowed for isolation of 2 AS DC subtypes
41
Q

what was observed in figure 4F

A
  • two AS DC subtypes represented very small fraction of Lin-HLA-DR+ populations
42
Q

what was observed in figure 4G

A
  • tSNE analysis of flow cytometry data shows that the AS DC subpopulations are located at the base of the CD1C+ DC cluster and adjacent to the pDC cluster
43
Q

what are the findings from figure 4

A
  • AS DCs are related, but not identical to cDCs or pDCs
44
Q

what is the purpose of figure 5

A
  • to distinguish pDCs (DC6) from AS DCs (DC5) in terms of gene expression and function as they share expression of many genes
45
Q

what was observed in figure 5A (2)

A
  • genes specifically expressed by pDCs, but not AS DCs, were associated with the known biological properties of pDCs
  • AS DCs expressed cDC markers
46
Q

what was observed in figure 5B (2)

A
  • pDCs were morphologically distinct from AS DCs
  • AS DCs possessed same cerebriform nucleus and cytoplasmic features of cDCs
47
Q

what was observed in figure 5C (2)

A
  • pure pDCs produced hallmark cytokine IFN-a, while AS DCs produced negligible amounts upon TLR9 stimulation
  • 1 AS DC subset produced similar amounts of IL-12p70 to cDCs, while pure pDCs and other other AS DC subset did not produce IL-12p70
48
Q

what was observed in figure 5D

A
  • pure pDCs induced little T cell proliferation compared to non-pure pDCs (pDCs with AS DC contamination) in response to LPS stimulation
49
Q

what was observed in figure 5E (2)

A
  • both AS DC subtypes were potent stimulators of CD4+ and CD8+ T cell proliferation, unlike pDCs
  • AS DC subtype stimulation was slightly superior to cDCs
50
Q

what was observed in figure 5F

A
  • AS DCs were found adjacent to CD3+ T cells and admixed with CD123+AXL- pDCs
  • flow cytometry showed that CD123+CD11C- AS DCs represented 0.7% and CD123-CD11C+ AS DCs represented 1.7% of the CD45+LIN-HLA-DR+ fraction
51
Q

what are the findings from figure 5 (2)

A
  • pure pDCs do not up-regulate CD86, a co-stimulator, and are diminished in ability to induce T cell proliferation when AS DCs are filtered out
  • AS DCs are able to stimulate T cells and are present in the T cell zones of the tonsils
52
Q

what is the purpose of figure 6 (2)

A
  • identify circulating CD100^hiCD34^int cDC progenitors (A-E)
  • map malignant cells from patients to healthy DC atlas (G)
53
Q

what is observed in figure 6A

A
  • interrogation of CD11C-CD123- cells identified new cluster of cells not previously thought to include DCs
54
Q

what was observed in figure 6B

A
  • after culture, cells isolated from CD11C-CD123- gate gave rise to CLEC9A+ and CD1C+ DCs, but not pDCs
55
Q

what was observed in figure 6C

A
  • only CD100^hiCD34^int cells generated CLEC9A+ and CD1C+ DCs
56
Q

what was observed in figure 6D (2)

A
  • CD100^hiCD34^int progenitors existed at ~0.02% of the LIN-HLA-DR+ fraction
  • cells were morphologically primitive, possessing high nuclear-to-cytoplasmic ratios and circular/indented nuclei in contrast to more developed cells
57
Q

what was observed in figure 6E

A
  • CD100^hiCD34^int cells retain a significant proliferative profile
58
Q

what experiment was conducted in figure 6G

A
  • blastic plasmacytoid DC neoplasm (BPDCN), a rare and aggressive cancer, was compared with healthy DC populations using scRNA-seq
59
Q

key findings and applications: DC1

A
  • CLEC9A is better marker than CD141 for cross-presenting DCs
60
Q

key findings and applications: DC2

A
  • higher expression of MHC class II genes
61
Q

key findings and applications: DC3 (2)

A
  • higher expression of inflammatory genes
  • transcriptionally related to mono1 (CD14+)
62
Q

key findings and applications: DC4

A
  • transcriptionally related to Mono2 (CD16+)
63
Q

key findings and applications: DC5 (5)

A
  • new cDC population, AS DCs, including 2 subtypes
  • captured in pDC and CD1C+ DC gate
  • potent inducer of T cell proliferation
  • co-localizes with T cells in situ
  • new target for vaccine strategy
64
Q

key findings and applications: DC6 (2)

A
  • “pure” pDC lacks several DC-like properties
  • main role in type 1 interferon-production
65
Q

key findings and applications: cDC progenitors (4)

A
  • DC progenitor for CD1C+ and CLEC9A+ cDC
  • retain proliferative potential
  • therapeutic target accessible in bloodstream
  • new source for better in vitro DC model
66
Q

key findings and applications: Mono3 and Mono4

A
  • higher expression in cell cycle and trafficking genes (M3) and cytotoxic genes (M4)

MICB 402 (11 decks)

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