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Sorting real-time fluorescence and deformability cytometry (soRT-FDC) - manuscript data

This dataset contains results presented in Nawaz, Urbanska, Herbig et al manuscript entitled ‘ Using real-time fluorescence and deformability cytometry and deep learning to transfer molecular specificity to label-free sorting ’ available on bioRxiv (https://doi.org/10.1101/862227) and includes:

(i) 29 '*.rtdc' files containing measurements performed with real time fluorescence and deformability cytometry [1,2]

(ii) 1 '*.fcs' file containing a measurement performed with a standard flow cytometer (BD LSR II, BD Biosciences)

(iii) 1 '*.xlsx' file containing results from AFM-based indentation experiments.

Sorting real-time fluorescence and deformability cytometry (soRT-FDC) is a robust sorting platform, combining image-based morphological cell analysis with mechanical characterisation and subsequent active sorting by feeding real-time fluorescence and deformability cytometry (RT-FDC) [2] information to a down-stream SSAW-based cell sorter [3].

Each filename of this dataset starts with the name of the figure to which the datafile corresponds. The measured samples are briefly described below. The 'Initial' measurements refer to the samples used for sorting, and the 'Target' measurements to the samples collected in the target outlet after sorting. For more detailed description of samples please refer to the manuscript.

The '*.rtdc' files are HDF5 files and can be analysed using a Python library called dclab [4], or a software called Shape-Out [5]. They can also be opened using other HDF viewer programs.

[1] Otto et al., "Real-time deformability cytometry: on-the-fly cell mechanical phenotyping". Nature Methods, 12(3):199–202, 2015. doi:10.1038/nmeth.3281.

[2] Rosendahl et al., "Real-time fluorescence and deformability cytometry". Nature Methods, 15(5):355–358, 2018. doi:10.1038/nmeth.4639.

[3] Nawaz et al., “Acoustofluidic Fluorescence Activated Cell Sorter”. Analitycial Chemistry 87(24): 12051–12058, 2015. doi: doi.org/10.1021/acs.analchem.5b02398

[4] https://github.com/ZellMechanik-Dresden/dclab

[5] https://github.com/ZellMechanik-Dresden/ShapeOut

Figure1d_01_Beads_FL_Initial.rtdc, Figure1d_02_Beads_FL_Target.rtdc

sample: 1:5 mixture of polyacrylamide microgel beads labeled with AlexaFluor488 and unlabeled ones, these beads were produced in house; sorted for fluorescence

sorting gates: FL-1 maximum 1000 – 10000, area ratio: 1.0 - 1.1

Figure1d_03_Beads_Size_Initial.rtdc, Figure1d_04_Beads_Size_Target.rtdc

sample: 1:6 mixture of 13.79 ± 0.59 μm silica beads (SiO2-F-L3519-1; Microparticles, Germany) and 17.23 ± 0.24 μm poly(methyl methacrylate) beads (PMMM-F-B1423; Microparticles); sorted for size

sorting gates: size 220 – 300 μm2, def 0.00 – 0.01, are ratio 1.0 – 1.1

Figure1d_05_Beads_DefSize_Initial.rtdc, Figure1d_06_Beads_DefSize_Target.rtdc

sample: a mixture of two polyacrylamide microgel bead populations of different stiffness, these beads were produced in house; sorted for deformation and size

sorting gates: size 95 – 105 μm2, def 0.000 – 0.016, are ratio 1.0 – 1.1

Figure2b_Blood_Initial_Inlet.rtdc

sample: RBC-depleted blood sample analysed in the inlet region of the chip

Figure2c_Blood_Initial_Channel.rtdc

sample: RBC-depleted blood sample analysed in the usual ROI at the end of the constricting channel

Figure2d_Blood_Target_RBCs.rtdc

sample: RBC-depleted blood, sorted RBCs

sorting gates: size 25 – 65 μm2, def 0.16 – 0.40, are ratio 1.0 – 1.1

Figure2e_Blood_Target_ly.rtdc

sample: RBC-depleted blood, sorted lymphocytes

sorting gates: size 25 – 45 μm2, def 0.00 – 0.10, are ratio 1.0 – 1.1

Figure2f_Blood_Target_my.rtdc

sample: RBC-depleted blood, sorted myeloid cells

sorting gates: size 53 – 120 μm2, def 0.00 – 0.15, are ratio 1.0 – 1.1

Figure3_Blood_Initial.rtdc, Figure3_Blood_Target_neuBr.rtdc

sample: RBC-depleted blood, brightness-based neutrophils sorting*

sorting gates: size 56 – 100 μm2, brightness 75 – 78, are ratio 1.0 – 1.1

Figure4_Blood_DNN_Training(1).rtdc, Figure4_Blood_DNN_Training(2).rtdc

sample: RBC-depleted blood, datasets for training of deep neural network (DNN)*

Figure4_Blood_DNN_Validation.rtdc

sample: RBC-depleted blood, dataset for validation of trained DNN*

Figure4d_Blood_Initial.rtdc, Figure4e_Blood_Target_neuDNN.rtdc

sample: RBC-depleted blood, DNN-based neutrophil sorting*

*for identification of neutrophils (CD66+/CD14−), these samples were stained with APC-conjugated anti-human CD14 (dilution 1:20, #17- 809 0149-42, eBioscience, CA, USA; recorded with FL-3 channel) and PE-conjugated anti-human CD66a/c/e (dilution 1:40, 810 #34303, BioLegend, CA, USA; recorded with FL-2 channel); for cross-talk compensation of the fluorescence signal in channels FL-2 and FL-3 for these samples introduce the following correction factor in the ShapeOut software: spill from channel 2 to 3 = 0.025, spill from channel 3 to 2 = 0.100

SFigure2a_BeadMix_RT-FDC.rtdc, SFigure2b_BeadMix_soRT-FDC.rtdc, SFigure2c_BeadMix_FC.fcs

sample: a mixture of 4 bead types with different diameter, each made of different material:

9.78 ± 0.15 μm melamine beads (MF-FluoBlau-L948),

13.79 ± 0.59 μm silica beads (SiO2-F-L3519-1),

15.21 ± 0.31 μm polystyrene beads (PS/Q-F-KM194),

17.23 ± 0.24 μm poly(methyl methacrylate) beads (PMMM-F-B1423),

all purchased from Microparticles, Germany.

SFigure3a_Beads_FLDef_Initial.rtdc, SFigure3a_Beads_FLDef_Target.rtdc

sample: a mixture of fluorescent and non-fluorescent polyacrylamide beads with different mechanical properties, these beads were produced in house; sorted for fluorescence and deformation

sorting gates: FL-1 maximum 1000 – 10000, def 0.01 – 0.02, are ratio 1.0 – 1.1

SFigure3b_Beads_BrSize_Initial.rtdc, SFigure3b_Beads_BrSize_Target.rtdc

sample: a mixture of 4 bead types as in SFigure2; sorted for brightness and size

sorting gates: size 160 – 240 μm2, brightness 75 – 85, are ratio 1.0 – 1.1

SFigure4a_Kc167_HL60_Size_Initial.rtdc, SFigure4b_Kc167_HL60_Size_Target.rtdc

sample: a mixture of Kc167 Drosophila cells and HL60/S4 human promyelocytic leukaemia cells, sorted for size

sorting gates: size 25 – 77 μm2, def 0.00 – 0.15, are ratio 1.0 – 1.1

SFigure5a_RBC_Def_Initial.rtdc, SFigure5b_RBC_Def_Target1.rtdc, SFigure5c_RBC_Def_Target2.rtdc

sample: blood anticoagulated with citrate, RBCs sorted for deformation

sorting gates: def 0.15 – 0.40 (Target1) / def 0.00 – 0.10 (Target2), are ratio 1.0 – 1.2

SFigure7_AFM_AfterSorting.xlsx

sample: HL60/S4 cells collected after sorting experiment; the initial sample was prepared as for the soRT-FDC experiment but not loaded onto the chip, the default sample was collected in the default outlet, i.e., run through the sorting chip but not exposed to SSAW, and the target sample corresponds to cells exposed to SSAW; reported values correspond to apparent Young’s modulus estimated from AFM indentation experiments

Data and Resources

Additional Info

Field Value
Last Updated September 16, 2020, 18:51 (+0200)
Created September 16, 2020, 17:59 (+0200)
Authors Ahmad Ahsan Nawaz, Marta Urbanska, Maik Herbig, Martin Nötzel, Martin Kräter, Philipp Rosendahl, Christoph Herold, Nicole Töpfner, Marketa Kubankova, Ruchi Goswami, Shada Abuhattum, Felix Reichel, Paul Müller, Anna Taubenberger, Salvatore Girardo, Angela Jacobi, Jochen Guck
DOI 10.6084/m9.figshare.11302595.v1
References doi:10.1101/862227 doi:10.1038/nmeth.3281 doi:10.1038/nmeth.4639 doi:10.1021/acs.analchem.5b02398 https://github.com/ZellMechanik-Dresden/dclab https://github.com/ZellMechanik-Dresden/ShapeOut
License Creative Commons Public Domain Dedication
Dataset ID e61bb335-3523-e539-78d1-0720ad5a99f1