3D imaging of sex-sorted bovine spermatozoon locomotion, head spin and flagellum beating.

With the advent of sperm sex sorting methods and computer-aided sperm analysis platforms, comparative 2D motility studies showed that there is no significant difference in the swimming speeds of X-sorted and Y-sorted sperm cells, clarifying earlier misconceptions. However, other differences in their swimming dynamics might have been undetectable as conventional optical microscopes are limited in revealing the complete 3D motion of free-swimming sperm cells, due to poor depth resolution and the trade-off between field-of-view and spatial resolution. Using a dual-view on-chip holographic microscope, we acquired the full 3D locomotion of 235X-sorted and 289 Y-sorted bovine sperms, precisely revealing their 3D translational head motion and the angular velocity of their head spin as well as the 3D flagellar motion. Our results confirmed that various motility parameters remain similar between X- and Y-sorted sperm populations; however, we found out that there is a statistically significant difference in Y-sorted bovine sperms' preference for helix-shaped 3D swimming trajectories, also exhibiting an increased linearity compared to X-sorted sperms. Further research on e.g., the differences in the kinematic response of X-sorted and Y-sorted sperm cells to the surrounding chemicals and ions might shed more light on the origins of these results.

Label-free 3D computational imaging of spermatozoon locomotion, head spin and flagellum beating over a large volume.

We report a high-throughput and label-free computational imaging technique that simultaneously measures in three-dimensional (3D) space the locomotion and angular spin of the freely moving heads of microswimmers and the beating patterns of their flagella over a sample volume more than two orders-of-magnitude larger compared to existing optical modalities. Using this platform, we quantified the 3D locomotion of 2133 bovine sperms and determined the spin axis and the angular velocity of the sperm head, providing the perspective of an observer seated at the moving and spinning sperm head. In this constantly transforming perspective, flagellum-beating patterns are decoupled from both the 3D translation and spin of the head, which provides the opportunity to truly investigate the 3D spatio-temporal kinematics of the flagellum. In addition to providing unprecedented information on the 3D locomotion of microswimmers, this computational imaging technique could also be instrumental for micro-robotics and sensing research, enabling the high-throughput quantification of the impact of various stimuli and chemicals on the 3D swimming patterns of sperms, motile bacteria and other micro-organisms, generating new insights into taxis behaviors and the underlying biophysics.

Computational imaging of sperm locomotion.

Not only essential for scientific research, but also in the analysis of male fertility and for animal husbandry, sperm tracking and characterization techniques have been greatly benefiting from computational imaging. Digital image sensors, in combination with optical microscopy tools and powerful computers, have enabled the use of advanced detection and tracking algorithms that automatically map sperm trajectories and calculate various motility parameters across large data sets. Computational techniques are driving the field even further, facilitating the development of unconventional sperm imaging and tracking methods that do not rely on standard optical microscopes and objective lenses, which limit the field of view and volume of the semen sample that can be imaged. As an example, a holographic on-chip sperm imaging platform, only composed of a light-emitting diode and an opto-electronic image sensor, has emerged as a high-throughput, low-cost and portable alternative to lens-based traditional sperm imaging and tracking methods. In this approach, the sample is placed very close to the image sensor chip, which captures lensfree holograms generated by the interference of the background illumination with the light scattered from sperm cells. These holographic patterns are then digitally processed to extract both the amplitude and phase information of the spermatozoa, effectively replacing the microscope objective lens with computation. This platform has further enabled high-throughput 3D imaging of spermatozoa with submicron 3D positioning accuracy in large sample volumes, revealing various rare locomotion patterns. We believe that computational chip-scale sperm imaging and 3D tracking techniques will find numerous opportunities in both sperm related research and commercial applications.

Computational sensing of herpes simplex virus using a cost-effective on-chip microscope.

Caused by the herpes simplex virus (HSV), herpes is a viral infection that is one of the most widespread diseases worldwide. Here we present a computational sensing technique for specific detection of HSV using both viral immuno-specificity and the physical size range of the viruses. This label-free approach involves a compact and cost-effective holographic on-chip microscope and a surface-functionalized glass substrate prepared to specifically capture the target viruses. To enhance the optical signatures of individual viruses and increase their signal-to-noise ratio, self-assembled polyethylene glycol based nanolenses are rapidly formed around each virus particle captured on the substrate using a portable interface. Holographic shadows of specifically captured viruses that are surrounded by these self-assembled nanolenses are then reconstructed, and the phase image is used for automated quantification of the size of each particle within our large field-of-view, ~30 mm2. The combination of viral immuno-specificity due to surface functionalization and the physical size measurements enabled by holographic imaging is used to sensitively detect and enumerate HSV particles using our compact and cost-effective platform. This computational sensing technique can find numerous uses in global health related applications in resource-limited environments.

Computational On-Chip Imaging of Nanoparticles and Biomolecules using Ultraviolet Light.

Significant progress in characterization of nanoparticles and biomolecules was enabled by the development of advanced imaging equipment with extreme spatial-resolution and sensitivity. To perform some of these analyses outside of well-resourced laboratories, it is necessary to create robust and cost-effective alternatives to existing high-end laboratory-bound imaging and sensing equipment. Towards this aim, we have designed a holographic on-chip microscope operating at an ultraviolet illumination wavelength (UV) of 266 nm. The increased forward scattering from nanoscale objects at this short wavelength has enabled us to detect individual sub-30 nm nanoparticles over a large field-of-view of >16 mm2 using an on-chip imaging platform, where the sample is placed at ≤0.5 mm away from the active area of an opto-electronic sensor-array, without any lenses in between. The strong absorption of this UV wavelength by biomolecules including nucleic acids and proteins has further enabled high-contrast imaging of nanoscopic aggregates of biomolecules, e.g., of enzyme Cu/Zn-superoxide dismutase, abnormal aggregation of which is linked to amyotrophic lateral sclerosis (ALS) - a fatal neurodegenerative disease. This UV-based wide-field computational imaging platform could be valuable for numerous applications in biomedical sciences and environmental monitoring, including disease diagnostics, viral load measurements as well as air- and water-quality assessment.