Supplemental Information. Histo-Cytometry: A Method for Highly Multiplex. Quantitative Tissue Imaging Analysis Applied to

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1 Immunity, Volume 37 Supplemental Information Histo-Cytometry: A Method for Highly Multiplex Quantitative Tissue Imaging Analysis Applied to Dendritic Cell Subset Microanatomy in Lymph Nodes Michael Y. Gerner, Wolfgang Kastenmuller, Ina Ifrim, Juraj Kabat, and Ronald N. Germain Supplemental Data Inventory Supplemental Experimental Procedures o Microscopy and Histo-Cytometry o Antibodies Supplemental Figure Legends o Figure S1 related to Figure 1 o Figure S2 related to Figure 2 o Figure S3 related to Figure 3 o Figure S4 related to Figure 5 o Figure S5 related to Figure 6

2 Supplemental Experimental Procedures Microscopy and Histo-Cytometry LNs were harvested and fixed with 0.05 M phosphate buffer containing 0.1 M L- lysine (ph 7.4), 2 mg/ml NaIO4, and 10mg/ml paraformaldehyde over night at 4 Celsius and then equilibrated in 30% sucrose solution for another 24 hours. Tissues were then frozen in OCT and stored at -80 Celsius. Multiple LN sagittal 20μm sections were then made with a Leica cryostat, to make sure that imaged tissue cross-sections contained all known representative LN regions and cellular populations. Sections were blocked for 1-2hr with a 1% normal mouse serum and bovine serum albumin block solution containing 0.3% Triton X-100. Sections to be stained with biotin-conjugated antibodies were first pre-incubated with an Avidin/Biotin blocking solution (Invitrogen) for 30 minutes at room temperature (RT). Sections were then stained with appropriate primary and secondary antibodies, or directly conjugated antibodies where possible. Each antibody incubation step was conducted for a minimum of 8 hours in a dark, humidifier chamber at 4 Celsius. We devised a panel of organic fluorophores that allowed spectral separation of the emissions by photon collection using separate detectors, largely relying on: Brilliant Violet 421, Pacific Blue, Alexa 488, Alexa 546/555, Alexa 594, Alexa 647, Alexa 700, and in some instances Alexa 750. Quantum dot stains, while useful on their own, were not included in panels with organic fluorochromes due to long-term incompatibility with aqueous mounting media needed to prevent rapid bleaching of the organic dyes (data not shown). We utilized either a Zeiss 710 or Leica SP5 confocal microscope with a motorized stage for tiled imaging. We found that high NA (1.25 or above) objectives with 40x magnification along with additional optical zoom (1.2-2 x)

3 provided us with sufficiently resolved and smoothly tiled images, and allowed for sampling of multiple tissue sections in a single session, although lower NA (0.8) and magnification (20x) objectives could be used for examining stains on non-clustered COI in tissues without neighboring non-coi specific signal. Imaged voxels ranged in size from nm in lateral and μm in axial directions (with higher resolution utilized for samples with densely distributed stains), and images were taken at 1024x1024 voxel density. Fluorophores were excited with the 405, 488, 561, 594, and 633 laser lines (optionally with 670nm from a white light laser for the Alexa 700 and 750 fluorophores), and fluorescence was detected with emission-optimized wavelength ranges for specific detector channels. To minimize fluorophore spectral spillover, we utilized sequential laser excitation and detection (405, 561, 594 laser excitation in first sequential, 488 and 633 excitation in the second sequential). Images were deconvolved using Huygen's Essential software (Scientific Volume Imaging), which was essential for enhancing appropriate spatial signal allocation and cellular discrimination in densely stained samples. Imaris software (Bitplane Scientific Software) was then used to conduct all other image manipulations. To compensate for fluorophore spillover, we devised an algorithm based on published compensation formulas (Fig. S1)(Roederer, 2002). For this purpose, in addition to our multiple-stained experimental tissues, we acquired images of single stained (SS) tissue controls. It is important to note that as long as there are discrete populations of cells that are well separated spatially and are specifically stained, multiple fluorophore-antibody staining on the same tissue can be used for spillover compensation determination. Utilizing the Surface Creation Wizard in Imaris, we created surface objects around the positively

4 stained cells in each SS control image. The statistics for the SS surface objects were then exported into Excel and the compensation spillover coefficient was calculated for each fluorophore using the formula: S A>B = B DET /A DET. Here S A>B is the spillover coefficient for fluorophore A into detector for fluorophore B, A DET and B DET are the sum intensities for each surface object in detector A and B for the fluorophore A's SS image. A pairwise compensation formula was then used: B COMP = (B DET - (A DET x S A>B )) / (1 - S A>B x S B>A ), where B COMP is the compensated channel B after removal of spillover from channel A. In complex situations involving more than two interacting fluorophores, the inverse matrix (M) of the spillover coefficients was calculated in Excel and applied according to Channel COMP =Channel DET x M -1. The spectral spillovers were removed for the channels exhibiting crosstalk with the built-in Imaris MATLAB Xtensions Channel Arithmetics module (Fig. S1). To create selective Boolean gates for voxel masking, we visually determined the cutoff thresholds for the parameters involved in either positive or negative mask specification. Threshold identification was expedited by utilizing the Surface Creation Wizard that provided automatic threshold identification and value-based visual surface thresholding around the positively stained cells (Fig. S2). These values were then used in the Imaris colocalization module to create a binary masking channel specific for the desired voxels corresponding to the COI, by utilizing the masking histogram for one channel and the 2D voxel intensity scattergram for two additional channels. This COI channel was then used to further mask all parameters of interest (Fig. S2). These masked parameters could then be directly visualized for analyzing cellular distribution. Imaris surface creation module was then used to create smoothed volumetric cell

5 surface renderings, based on the mask-restricted surface COI stains, and separated into discrete cellular objects via the built-in seeded watershed segmentation algorithms for intensity-based object detection/separation. In select experiments, cellular nuclei were co-stained with TO-PRO-5 Iodide at 1μm for 30min (Invitrogen), excited at 640nm using a white light laser and detected in the nm emission range. Images were deconvolved, compensated, and nuclear surfaces were created using the Imaris surface creation module (nhisto). The close juxtaposition of plasma membranes, and thus surface stained antibodies, to the cell nuclei in resting T and B lymphocytes leads to a certain amount of photon colocalization between the nuclear and surface stains. This surface stain fluorescence could then be quantified and used to gate and quantify all the resting lymphocyte populations in the imaged volume (see below). The channel statistics for all surfaces were exported into Excel (Microsoft) and mean voxel fluorescence was plotted in Flowjo software by utilizing the Text to FCS conversion utility (TreeStar Inc). We analyzed the mean voxel intensities for the different gated parameters inside each surface instead of the total sum of voxel intensities, as the intensity sum was highly dependent on the exact object volume. In some circumstances, surface objects with volumes and/or marker expression levels clearly outside of the overall surface distribution introduced significant noise to the population distributions in other channels, and were then filtered out of the final gating analysis. Minimum distance measurements were computed through calculating the distances (d) between all the points of interest via: d = sqrt ((x 1 -x 2 ) 2 +(y 1 -y 2 ) 2 ), and then finding the minimum using the built-in Excel function. All presented images were obtained in the

6 Imaris Snapshot module by displaying volumetric parameters in normal shading mode. To enhance visual clarity, the presented images were manipulated in Imaris and Photoshop to improve Antibodies Combinations of polyclonal, monoclonal primary, and directly-conjugated antibodies were used for immunofluorescence microscopy. Antibodies specific for: CD45.1 clone A20, CD45.2 clone 104, I-A/I-E MHC-II clone M5/ , B220 clone RA3-6B2, CD3 clone 17A2, CD4 clone RM4-5, CD8 clone Brilliant Violet 421 and CD11b clone M1/70 Brilliant Violet 421 were purchased from Biolegend. We also utilized: CD11c clone N418 (ebioscience), CD8 clone 5H10 (Invitrogen), Ki-67 clone B56 (BD Pharmingen), CD69 polyclonal goat AF2386 (R&D Systems), Lyve1 polyclonal rabbit (Acris GmbH), CD11b clone 5C6 (AbD Serotec), and CD207 Langerin polyclonal rabbit PA (Thermo Scientific). Species-specific and streptavidin secondary antibodies conjugated to different Alexa fluorophores were purchased from Invitrogen. Brilliant violet 421 streptavidin and rabbit specific secondaries were obtained from Biolegend.

7 Figures S1 S5 Figure S1

8 Figure S1. Histo-Cytometry Spillover Compensation and Voxel Gating. Singlestained tissue sections were imaged using the same parameters as for the multiplestained experimental sections (A). Here, fluorophore A single stained tissue was exhibiting spillover into the neighboring detector B intended for fluorophore B (A, left). 3D surfaces were generated based on the channel A signal and statistics were exported for the determining the spillover coefficient and the compensation correction (A, middle). Calculated compensation correction was applied to remove spillover in channel B (A, right). Inguinal LN sections were stained with the indicated antibodies (B). Yellow arrowhead points to the MHC-II + CD11c - (B220 or CD3) + cells in the B cell follicle (B cells), and white arrowhead points to the MHC-II + CD11c + (B220 or CD3) - cells (DC) in the interfollicular zone. Signal thresholds were manually determined using the Imaris Surface Creation module (C), and were used for creation of a novel binary DC channel in the Imaris Colocalization module (D). Binary DC channel was then used for masking other channels of interest (CD11c and MHC-II shown) for their original signal intensities, thus restricting analysis specifically to the binary DC voxels (E). Notice the selective removal of B cell-associated (yellow arrowhead) and retention of the DC-associated (white arrowhead) DC-gated MHC-II signal (E).

9 Figure S2

10 Figure S2. Nucleus-based Histo-Cytometry for Identification and Quantification of All Resting Lymphocytes. Irradiated CD recipients were injected with a 1:99, 5:95, or 10:90 mixture of CD to CD donor BM and were allowed to reconstitute for 6 weeks, after which contra-lateral inguinal LN were taken for comparative analysis by flow cytometry and nuclear-based Histo-Cytometry (nhisto). LN sections were stained with a panel of indicated antibodies and imaged (A). Nuclear staining TO-PRO-5 Iodide allowed surface segmentation of all nuclear events via standard watershed-based Imaris segmentation (yellow squares indicate the center of each nuclear surface) (A). Nuclear surfaces were exported and analyzed for various lymphocyte subsets and compared to flow cytometric data (B). Quantification of CD T and B lymphocyte frequencies in animals with 1, 5 and 10% CD seeded frequency by flow cytometry, Histo-Cytometry and nhisto (C). Quantification of CD T and B lymphocyte frequencies in animals with 99, 95 and 90% CD seeded frequency by flow cytometry and nhisto (D).

11 Figure S3

12 Figure S3. Measuring T cell Activation by Flow Cytometry and Histo-Cytometry. Total recovery of T cell populations in LN at indicated time-points after OVA-conjugated beads and CpG immunization as enumerated by flow cytometric analysis is displayed (A). 38hr post immunization, dln were microscopically analyzed for CD69 expression by OT-I and OT-II T cells in relation to OVA-bead localization (B). Expanded information on the dataset presented in Figure 3. Flow cytometry and Histo-Cytometry analyses of OT-I, OT-II, and control SMARTA T cell phenotypic changes at the specified time-points are displayed (C). N=3 for each time-point. Error bars represent the SD.

13 Figure S4

14 Figure S4. Resident DC Gating and LN Zone Distribution. Expanded information on the Histo-Cytometry imaging information presented in Figure 5 (A, B). CD207 + DC surfaces from BATF3.HET LN were examined for MHC-II and CD11c expression and were used for threshold cutoff determination for resident and migratory DC gating (A). Original (non-gated) CD8, CD11c, MHC-II, and Lyve-1 signals provided a clear separation of the LN into discrete zones: lymphatic, inter-follicular, T zone, and B zone (B, left). These zones were outlined and used to assess the distribution of total gated CD11c signal, representing DC (B, middle), as well as the various DC subset surfaces, as assessed by the gating presented in Figure 5 (B, right). Popliteal (C-E) and inguinal (F) LN sections from CD11c-YFP mice were stained with the indicated antibodies and imaged. CD11c + MHC-II + CD3 - B220 - voxels were used to create a masking channel for further gating and visualization of the CD8 and CD11b signal (C). DC surface statistics were used for Histo-Cytometry identification and spatial visualization of resident CD8 + and CD11b + DC subsets (D). Localization of distinct DC subsets to the indicated LN zones was quantified (E). Alternative staining of CD8 + resident DC with CD205 yields similar subset distribution as that obtained with CD8-based population identification (F). N=3. Error bars represent the SD.

15 Figure S5 Figure S5. Migratory DC Subset Localization. Auricular LN sections from untreated mice (steady-state, left) or after skin-irritation (right) were analyzed for migratory DC subset composition and phenotype (top), as well as for spatial localization and distance to LN lobe center (bottom) via Histo-Cytometry (A). Inguinal LNs from CD11c-YFP reporter mice were analyzed for migratory DC subset composition, localization and distance from LN lobe center (B). Representative of at least two independent experiments.