Research ArticleSYSTEMS BIOLOGY

Ultra-multiplexed analysis of single-cell dynamics reveals logic rules in differentiation

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Science Advances  03 Apr 2019:
Vol. 5, no. 4, eaav7959
DOI: 10.1126/sciadv.aav7959
  • Fig. 1 Ultra-multiplexed, automated cell culture system for dynamical live-cell analysis.

    The microfluidic device contains 1500 independently programmable culture chambers. During a 1-week experiment, the device performs nearly 106 pipetting steps to create and maintain distinct culture conditions in each of the chambers. (A) Each chamber can execute a distinct dynamic culture program (combinations, timed sequences, sine waves, etc.) where the fluidic composition can be changed when desired, and dynamic processes (i.e., NF-κB localization or Hes5 expression) are tracked with single-cell resolution. An on-chip nanoliter multiplexer measures several fluids and mixes them at predetermined ratios to create complex chemical inputs. A peristaltic pump delivers inputs to any given chamber. For the combinatorial input scenario, several chemicals are mixed and delivered to the cells continuously. In sequential inputs, signaling molecules are changed with a programmed time interval (Δt = 1 day). a.u., arbitrary units. (B) The system can culture adherent or nonadherent cells in either suspension mode, monolayer populations, or 3D format using hydrogels. The novel two-layer geometry of the culture chambers allows diffusion-based media delivery to create a stable environment for cells, and provides the additional ability of single-cell tracking of even nonadherent cells during dynamical stimulation. (C) Left: Two-layer cell chamber design allows diffusion- or flow-based media delivery, 3D cell culture, immobilization of nonadherent cells by gravity, and automated cell retrieval. Middle: Fluid mechanical simulations indicate the flow rates for diffusion-based media delivery and cell retrieval via direct flow. Right: Each chamber is controlled by a network of dedicated channels and membrane valves that automate various cell culture procedures. (D) Cells can be immunostained in the chip. The system is integrated to a fluorescent microscope and can automatically track individual cells in time-lapse experiments. Single cells or populations of interest can be automatically retrieved from individual chambers for off-chip analysis or expansion. GFP, green fluorescent protein; RFP, red fluorescent protein. (E) Primary cells (e.g., mouse NSCs and human HSCs) and cell lines (e.g., Jurkat T cells and mouse fibroblasts) are viably cultured and maintained on chip for weeks. Growth rates equal or better than the well plate culture are achieved through frequent diffusion-based media delivery while maintaining an unperturbed microenvironment.

  • Fig. 2 High-throughput dynamical analysis of NSC differentiation.

    Millions of single-cell images are generated and automatically analyzed in live-cell signaling factor stimulation measurements, and few example datasets are shown here. (A) Time-lapse bright-field (BF) (top) and epifluorescence (bottom) images of NSCs cultured with PDGF (100 ng/ml). Scale bars, 100 μm. (B) Histogram of Hes5-GFP expression in NSCs before (red) and after (black) 1-week culture with PDGF (100 ng/ml). High levels of Hes5 in NSCs indicate maintenance of stem cell state, while reduced Hes5 indicates progress toward differentiation. (C) Enlarged bright-field (top) and corresponding epifluorescence (bottom) images of NSCs shown in (A), cultured on chip with PDGF (100 ng/ml). Selected cells were indicated by arrows and individually tracked over 40 hours during on-chip culture. (D) Lineage tracing (top) and Hes5-GFP expression level (bottom) for the three selected cells in (C). Distinct proliferation patterns were observed despite similar Hes5-GFP level. (E) We show examples of quantitative analysis of mouse NSC growth and Hes5 expression in different culture conditions. Each culture contains either a single ligand or a mixture of ligands that are highly expressed in developing mouse brain, including PDGF, CXCL, PACAP, EGF, Jagged, or DLL. Hes5 expression rate and variability significantly depend on signaling molecules present in culture chambers.

  • Fig. 3 High-throughput analysis of NSC dynamics reveals signaling logic rules in differentiation.

    (A) NSCs were stimulated in two types of experiments: combinatorial stimulation and sequential stimulation. During combinatorial stimulation, the microfluidic device delivered all possible combinations of DLL, EGF, Jagged, PACAP, CXCL, and PDGF to distinct culture chambers and maintained these conditions for 6 days. During sequential stimulation, the environmental ligands were replaced daily during the 6-day experiments. Cell numbers and single-cell Hes5-GFP and Dcx-RFP expressions were recorded in each chamber over time. (B) Example datasets from one experiment. Signal-induced changes in NSC cell count (top), Hes5-GFP expression (middle), and Dcx expression (bottom) at day 6 are plotted as heat maps, together with the color-coded bars indicating the combinatorial and sequential signal inputs. The white squares show input conditions with the following ligand combinations and sequences: (1) DLL + EGF, (2) JaggedCXCLPDGFPACAPEGFDLL , and (3) CXCLPDGFPACAPEGFDLLJagged. (C) Single-cell tracking reveals the dynamic variations in cell numbers and Hes5 and Dcx levels during 6 days of single ligand treatment, with PACAP or PDGF. The bottom row histograms show results of statistical analyses indicating the influence of PDGF on cell growth or Hes5 level in different experiments that also contain other ligands. Each bar represents a distinct culture experiment. (D) Statistical analysis of cell count and Hes5 and Dcx expression using all 720 sequential experiments via Wilcoxon rank-sum test. Y axes show the percentage change of cell numbers and Hes5 and Dcx expression compared to controls (i.e., the effect size) for each ligand input, and the x axes show the corresponding adjusted P value. The data are presented with colored bubbles, where the bubble’s diameter is proportional to the negative logarithm of adjusted P value, and Bubble’s color encodes percentage change (green for increase, red for decrease; stronger effect shown in more opaque color). Few selected inputs with high significance or large effect size are annotated with numbers 1 to 7 and are described in lower tables. (E) Decision trees are used to visualize the signaling paths toward NSC differentiation or self-maintenance, each of which shows a statistically significant monotonic increase (green paths) or monotonic decrease (red paths) in cell counts and Hes5 and Dcx expression. Each decision tree node includes a median value (color-coded as above) and median absolute deviation (in brackets) of measured values. On the connecting path between nodes, we show the decision attribute to be satisfied for splitting the tree, and the percentage change in cell count and Hes5 expression or Dcx expression (adjusted P value indicated by asterisks). Signaling logic rules resulting from the decision trees are listed below. Notations of “=>” and “=|” denote “promote” and “prohibit,” respectively.

  • Fig. 4 Statistical analysis of dynamic stimulation experiments uncovers signaling principles in NSC differentiation and self-maintenance.

    (A) Dynamic changes in cell number and Hes5 level plotted for two ligand combinations containing (DLL, EGF, PDGF) or (Jagged, EGF, PDGF). Dots are single-cell values, and dashed lines indicate population mean. The change in Hes5 expression can be directed from increase to decrease by only changing one ligand in the combination. (B) Comparison of two distinct sequential inputs highlights the importance of input sequence and timing. In both experiments, cells received the same six ligands, but in different orders. Changing the order of a single ligand (e.g., EGF from day 2 to day 6) directs NSCs to different cell fate. (C) Comparison of optimal and nonoptimal input ligand sequences that lead to monotonic changes in cell counts or Hes5 expression. Numbers in boxes indicate median value (color-coded) and median absolute deviation (in brackets) of cell count or Hes5 expression. ns, nonsignificant changes. Optimal paths are highlighted in green (increase) or red (decrease), while the alternatives paths are highlighted in black. (D) Increasing number of ligands in a stimulation experiment overall suppresses NSC proliferation, whereas reducing the ligand numbers enhances the stem cell pool. Including more ligands in experiments led to a reduction of the proliferation rate, while the Hes5 level remained relatively unchanged. Error bars indicate variability of individual experiments from the mean. (E) Synergy and antagonism between signaling molecules. The combination of two ligands may lead to enhanced (synergistic) or reduced (antagonistic) effect compared to experiments that use these molecules in isolation. At the top, synergy and antagonism for NSC ligands are defined. Rows at the bottom show actual molecules that are synergistic (green) or antagonistic (red) toward cell proliferation or Hes5 expression. Measured percent changes from controls are also indicated. (F) In sequential stimulation experiments, certain ligands assume context-dependent roles determined by timing of their introduction or the preconditions before use of that ligand. Boxes indicate the identity of ligands used in each day. X in brackets indicate that the exact identity of the ligand in that day does not change the outcome. (G) Multiple input conditions lead to similar change in cell numbers and Hes5 levels, suggesting redundancy in NSC signaling pathways. Example redundant pathways are color-coded. Numbers indicate percent change resulting from stimulation with ligands. (H) Cell fate toward differentiation or self-renewal may be decided by certain early signals, indicating early commitment toward self-renewal (PDGF-day1DLL-day2Jagged-day3) or differentiation (DLL-day1PDGF-day2CXCL-day3) (see table S2 for percentage change and P values associated with each condition).

Supplementary Materials

  • Supplementary material for this article is available at http://advances.sciencemag.org/cgi/content/full/5/4/eaav7959/DC1

    Section S1. Temporal and spatial concentration distribution within the cell culture chambers

    Section S2. Single 3T3 fibroblast cell culture and stimulation on chip

    Section S3. Culture and stimulation of human and mouse HSCs on chip

    Section S4. Culture and stimulation of NSC spheres on chip

    Section S5. Combinatorial and sequential experiments performed in 96-well plates

    Section S6. Extended discussion of high-throughput combinatorial and sequential input studies

    Section S7. Hes5 expression as a valid marker for NSC stemness

    Section S8. Immunostaining on chip and determining NSC phenotypes

    Section S9. Statistical analysis of combinatorial and sequential results

    Section S10. NSC single-cell tracking during combinatorial and sequential stimulation

    Fig. S1. Experimental characterization of concentration variations during medium exchange.

    Fig. S2. Assessment of the microfluidic system for dynamical cell culture and NF-κB signaling.

    Fig. S3. Culture and stimulation of human HSCs on chip.

    Fig. S4. Hes5 and Dcx expression regulating NSC cellular behavior.

    Fig. S5. Combinatorial and sequential stimulation of six ligands regulating NSC self-renewal and differentiation.

    Fig. S6. Correlation between Hes5 expression and NSC stemness.

    Fig. S7. Combinatorial and sequential inputs regulating NSC proliferation, Hes5, and Dcx expression.

    Fig. S8. Effect of various stimulation conditions on NSC cell fate subjected to statistical analysis.

    Table S1. Microenvironment exposed to six single ligands and combinatorial and sequential ligand inputs (note: the order of the ligands in the table represents the order of ligands introduced into the microenvironments on daily bases).

    Table S2. Statistical analysis results associated with sequential and combinatorial inputs of six ligands based on cell count measurements and Hes5 and Dcx expression level.

    Movie S1. COMSOL simulation and time-lapse video of fluid exchange in a unit chamber on the chip.

    Movie S2. Redistribution of GFP after medium exchange and all valves are closed.

    Movie S3. Retrieval of adherent cells (3T3, left) and suspension-cultured cells (Jurkat, right) from the chip.

    Movie S4. Stimulation of 3T3 cells by sinusoidal TNF-α inputs.

    Movie S5. Cell tracking videos of NSC spheres (top) and monolayer (bottom).

  • Supplementary Materials

    The PDF file includes:

    • Section S1. Temporal and spatial concentration distribution within the cell culture chambers
    • Section S2. Single 3T3 fibroblast cell culture and stimulation on chip
    • Section S3. Culture and stimulation of human and mouse HSCs on chip
    • Section S4. Culture and stimulation of NSC spheres on chip
    • Section S5. Combinatorial and sequential experiments performed in 96-well plates
    • Section S6. Extended discussion of high-throughput combinatorial and sequential input studies
    • Section S7. Hes5 expression as a valid marker for NSC stemness
    • Section S8. Immunostaining on chip and determining NSC phenotypes
    • Section S9. Statistical analysis of combinatorial and sequential results
    • Section S10. NSC single-cell tracking during combinatorial and sequential stimulation
    • Fig. S1. Experimental characterization of concentration variations during medium exchange.
    • Fig. S2. Assessment of the microfluidic system for dynamical cell culture and NF-κB signaling.
    • Fig. S3. Culture and stimulation of human HSCs on chip.
    • Fig. S4. Hes5 and Dcx expression regulating NSC cellular behavior.
    • Fig. S5. Combinatorial and sequential stimulation of six ligands regulating NSC self-renewal and differentiation.
    • Fig. S6. Correlation between Hes5 expression and NSC stemness.
    • Fig. S7. Combinatorial and sequential inputs regulating NSC proliferation, Hes5, and Dcx expression.
    • Fig. S8. Effect of various stimulation conditions on NSC cell fate subjected to statistical analysis.
    • Legends for tables S1 and S2
    • Legends for movies S1 to S5

    Download PDF

    Other Supplementary Material for this manuscript includes the following:

    • Table S1 (Microsoft Excel format). Microenvironment exposed to six single ligands and combinatorial and sequential ligand inputs (note: the order of the ligands in the table represents the order of ligands introduced into the microenvironments on daily bases).
    • Table S2 (Microsoft Excel format). Statistical analysis results associated with sequential and combinatorial inputs of six ligands based on cell count measurements and Hes5 and Dcx expression level.
    • Movie S1 (.mov format). COMSOL simulation and time-lapse video of fluid exchange in a unit chamber on the chip.
    • Movie S2 (.avi format). Redistribution of GFP after medium exchange and all valves are closed.
    • Movie S3 (.mov format). Retrieval of adherent cells (3T3, left) and suspension-cultured cells (Jurkat, right) from the chip.
    • Movie S4 (.avi format). Stimulation of 3T3 cells by sinusoidal TNF-α inputs.
    • Movie S5 (.avi format). Cell tracking videos of NSC spheres (top) and monolayer (bottom).

    Files in this Data Supplement:

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