High-Throughput Imaging of Blood Flow Reveals Developmental Changes in Distribution Patterns of Hemodynamic Quantities in Developing Zebrafish

Mechanical forces from blood flow and pressure (hemodynamic forces) contribute to the formation and shaping of the blood vascular network during embryonic development. Previous studies have demonstrated that hemodynamic forces regulate signaling and gene expression in endothelial cells that line the inner surface of vascular tubes, thereby modifying their cellular state and behavior. Given its important role in vascular development, we still know very little about the quantitative aspects of hemodynamics that endothelial cells experience due to the difficulty in measuring forces in vivo. In this study, we sought to determine the magnitude of wall shear stress (WSS) exerted on ECs by blood flow in different vessel types and how it evolves during development. Utilizing the zebrafish as a vertebrate model system, we have established a semi-automated high-throughput fluorescent imaging system to capture the flow of red blood cells in an entire zebrafish between 2- and 6-day post-fertilization (dpf). This system is capable of imaging up to 50 zebrafish at a time. A semi-automated analysis method was developed to calculate WSS in zebrafish trunk vessels. This was achieved by measuring red blood cell flow using particle tracking velocimetry analysis, generating a custom-made script to measure lumen diameter, and measuring local tube hematocrit levels to calculate the effective blood viscosity at each developmental stage. With this methodology, we were able to determine WSS magnitude in different vessels at different stages of embryonic and larvae growth and identified developmental changes in WSS, with absolute levels of peak WSS in all vessel types falling to levels below 0.3 Pa at 6 dpf. Additionally, we discovered that zebrafish display an anterior-to-posterior trend in WSS at each developmental stage.

. Validation of the TrackMate obtained velocities. The movement of the same red blood cell (RBC) in zebrafish #28 of the 2 dpf set imaged under 180 fps is shown in (A). For the validation, the velocity against time profile of the tracked RBC was obtained using TrackMate software and compared against the manual tracking calculation (B). The TrackMate software tracking algorithm provided velocity values in close correspondence with the manual tracking method.  Figure S2. Fåhraeus-Lindqvist (FL) effect model for microvessels, where the blood viscosity is dependent on plasma viscosity, lumen tube hematocrit (Ht) and vessel lumen diameter; these calculations are performed using equations 13 to 17 of the main article: Biphasic viscosity against vessel diameter behavior for blood flow in microvessels with a comparatively wide range of diameters over which viscosity reduces with diameter reduction (A and B) and a trend reversal at capillary diameters (C). Examples of the FL effect model is showed on whole blood with plasma viscosity of 0.0012 Pa·s (i) and 0.00146 Pa·s (ii).
Micro to macroscale range FL effect: viscosity reduction with diameter reduction at zebrafish micro-vessel ranges

A B C
Trend reversal at capillary sizes i ii i ii i ii Figure S3. Zebrafish heart rate across development for two different experiment sets. Circle points indicate the mean level heartbeat, and whisker bars represent the standard deviation ranges. Set A (blue): 6, 15, 26, 34, 32 and 15 zebrafish were measured for heart rate at 1, 2, 3, 4, 5 and 6 dpf. Set B (green): 18, 30, 32, 38, 35 and 29 zebrafish were measured for heart rate at 1, 2, 3, 4, 5 and 6 dpf. Set B zebrafish were used for all analysis performed and discussed in the main article. The average of two sets data (red) is a pooling of set A and set B data.   Figure S5. Validation of lumen diameter assessment by comparing method in paper (red) against EC marker peak to peak distance assessment (green) for the DA/CA (Ai), PCV/CV (Bi) and ISV (Ci). Judging against the hematocrit in Aii, Bii and Cii, the discrepancy between the two methods grows as vessel lumen diameters decrease and hematocrits become vanishingly low (hematocrit fraction < 0.01). Figure S6. Examples of the DA/CA diameter calculation using the dsRed signal and compared against the peak to peak distance evaluation from the kdrl:EGFP lumen EC marker signal. First the RBC core width is estimated using Eqn.
(2) in the main text after applying a supergaussian fitting (red dash) of the maximum projection signal (red bold). The RBC core width ( ) is determined by the full-width half maximum of the super-gaussian and is shown by the purple dash lines in the graphs. Evaluation of the CFL thickness ( ) was performed iteratively using Eqn. (5) and lumen width ( ) was updated iteratively using Eqn. (7) until the iteration residual fell < 0.001. Figure S7. Examples of the PCV/CV diameter calculation using the dsRed signal and compared against the peak to peak distance evaluation from the kdrl:EGFP lumen EC marker signal. First the RBC core width is estimated using Eqn.(2) in the main text after applying a supergaussian fitting (red dash) of the maximum projection signal (red bold). The RBC core width ( ) is determined by the full-width half maximum of the supergaussian and is shown by the purple dash lines in the graphs. Evaluation of the CFL thickness ( ) was performed iteratively using Eqn. (5) and lumen width ( ) was updated iteratively using Eqn. (7) until the iteration residual fell < 0.001. Figure S8. Examples of the ISV diameter calculation using the dsRed signal and compared against the peak to peak distance evaluation from the kdrl:EGFP lumen EC marker signal. First the RBC core width is estimated using Eqn.(2) in the main text after applying a supergaussian fitting (red dash) of the maximum projection signal (red bold). The RBC core width ( ) is determined by the full-width half maximum of the super-gaussian and is shown by the purple dash lines in the graphs. Evaluation of the CFL thickness ( ) was performed iteratively using Eqn. (5) and lumen width ( ) was updated iteratively using Eqn. (7) until the iteration residual fell < 0.001.

Ai Bi
Aii Figure S9. Validation of the direct correspondence between heartbeat rate and velocity pulsation frequency in the DA. Using zebrafish C2 of the validation experiments data set, the velocity pulsation was monitored in the anterior region of the DA in (boxed region in Ai) and a pulsation frequency of 180 bpm was obtained based on the observation of 30 pulsation cycles over 10 seconds of velocity sampling (Aii). The heartbeat in C2 was obtained by examining the heart wall displacement along the yellow arrow line indicated in Bi: Kymograph pattern along this line presented 12 wall pulsation cycles over 4 seconds, which works out to be a heartrate of 180 bpm (Bii). Since both methods indicated the same 180 bpm frequency, the assumption that velocity pulsation in the DA gives the heartbeat rate is a valid assumption.   Legend for supplemental videos Video 1: Representative RBC flow in zebrafish from the high throughput experiment at 2 dpf. Shown in the video is zebrafish #28 from the 2 dpf population group with flow recorded at 180 fps for 1000 frames. The video is played back at 180 fps.
Video 2: Representative RBC flow in zebrafish from the high throughput experiment at 3 dpf. Shown in the video is zebrafish #30 from the 3 dpf population group with flow recorded at 180 fps for 1000 frames. The video is played back at 180 fps.
Video 3: Representative RBC flow in zebrafish from the high throughput experiment at 4 dpf. Shown in the video is zebrafish #37 from the 4 dpf population group with flow recorded at 120 fps for 1000 frames. The video is played back at 120 fps.
Video 4: Representative RBC flow in zebrafish from the high throughput experiment at 5 dpf. Shown in the video is zebrafish #33 from the 5 dpf population group with flow recorded at 100 fps for 1000 frames. The video is played back at 100 fps.
Video 5: Representative RBC flow in zebrafish from the high throughput experiment at 6 dpf. Shown in the video is zebrafish #29 from the 6 dpf population group with flow recorded at 100 fps for 1000 frames. The video is played back at 100 fps.
Video 6: RBC flow in zebrafish at 2 dpf imaged at 80x magnification for the validation experiments. Shown in the video is zebrafish C1 that received control morpholino treatment resulting in normal hematocrit levels. The blood flow was recorded at 100 fps for 2000 frames. The video is played back at 100 fps.
Video 7: RBC flow in zebrafish at 2 dpf imaged at 80x magnification for the validation experiments. Shown in the video is zebrafish C2 that received control morpholino treatment resulting in normal hematocrit levels. The blood flow was recorded at 100 fps for 2000 frames. The video is played back at 100 fps.
Video 8: RBC flow in zebrafish at 2 dpf imaged at 80x magnification for the validation experiments. Shown in the video is zebrafish M1 that received gata1 morpholino treatment resulting in moderately reduced hematocrit levels. The blood flow was recorded at 100 fps for 2000 frames. The video is played back at 100 fps.
Video 9: RBC flow in zebrafish at 2 dpf imaged at 80x magnification for the validation experiments. Shown in the video is zebrafish M2 that received gata1 morpholino treatment resulting in moderately reduced hematocrit levels. The blood flow was recorded at 100 fps for 2000 frames. The video is played back at 100 fps.
Video 10: RBC flow in zebrafish at 2 dpf imaged at 80x magnification for the validation experiments. Shown in the video is zebrafish M3 that received gata1 morpholino treatment resulting in moderately reduced hematocrit levels. The blood flow was recorded at 100 fps for 2000 frames. The video is played back at 100 fps.
Video 11: RBC flow in zebrafish at 2 dpf imaged at 80x magnification for the validation experiments. Shown in the video is zebrafish M4 that received gata1 morpholino treatment resulting in greatly reduced hematocrit levels. The blood flow was recorded at 100 fps for 2000 frames. The video is played back at 100 fps.
Video12: RBC flow in zebrafish at 2 dpf imaged at 80x magnification for the validation experiments. Shown in the video is zebrafish M5 that received gata1 morpholino treatment resulting in greatly reduced hematocrit levels. The blood flow was recorded at 100 fps for 2000 frames. The video is played back at 100 fps.
SV13: Video montage showing the spatial distribution map of hemodynamic and morphological data in all zebrafish obtained from the high throughput experiment after automated spatial bin averaging