A Flexible Chamber for Time-Lapse Live-Cell Imaging with Stimulated Raman Scattering Microscopy

Stimulated Raman scattering (SRS) microscopy is a label-free chemical imaging technology. Live-cell imaging with SRS has been demonstrated for many biological and biomedical applications. However, long-term time-lapse SRS imaging of live cells has not been widely adopted. SRS microscopy often uses a high numerical aperture (NA) water-immersion objective and a high NA oil-immersion condenser to achieve high-resolution imaging. In this case, the gap between the objective and the condenser is only a few millimeters. Therefore, most commercial stage-top environmental chambers cannot be used for SRS imaging because of their large thickness with a rigid glass cover. This paper describes the design and fabrication of a flexible chamber that can be used for time-lapse live-cell imaging with transmitted SRS signal detection on an upright microscope frame. The flexibility of the chamber is achieved by using a soft material - a thin natural rubber film. The new enclosure and chamber design can be easily added to an existing SRS imaging setup. The testing and preliminary results demonstrate that the flexible chamber system enables stable, long-term, time-lapse SRS imaging of live cells, which can be used for various bioimaging applications in the future.

Automated profiling of growth cone heterogeneity defines relations between morphology and motility

Growth cones are complex, motile structures at the tip of an outgrowing neurite. They often exhibit a high density of filopodia (thin actin bundles), which complicates the unbiased quantification of their morphologies by software. Contemporary image processing methods require extensive tuning of segmentation parameters, require significant manual curation, and are often not sufficiently adaptable to capture morphology changes associated with switches in regulatory signals. To overcome these limitations, we developed Growth Cone Analyzer (GCA). GCA is designed to quantify growth cone morphodynamics from time-lapse sequences imaged both in vitro and in vivo, but is sufficiently generic that it may be applied to nonneuronal cellular structures. We demonstrate the adaptability of GCA through the analysis of growth cone morphological variation and its relation to motility in both an unperturbed system and in the context of modified Rho GTPase signaling. We find that perturbations inducing similar changes in neurite length exhibit underappreciated phenotypic nuance at the scale of the growth cone.

A scanner system for high-resolution quantification of variation in root growth dynamics of Brassica rapa genotypes

The potential exists to breed for root system architectures that optimize resource acquisition. However, this requires the ability to screen root system development quantitatively, with high resolution, in as natural an environment as possible, with high throughput. This paper describes the construction of a low-cost, high-resolution root phenotyping platform, requiring no sophisticated equipment and adaptable to most laboratory and glasshouse environments, and its application to quantify environmental and temporal variation in root traits between genotypes of Brassica rapa L. Plants were supplied with a complete nutrient solution through the wick of a germination paper. Images of root systems were acquired without manual intervention, over extended periods, using multiple scanners controlled by customized software. Mixed-effects models were used to describe the sources of variation in root traits contributing to root system architecture estimated from digital images. It was calculated that between one and 43 replicates would be required to detect a significant difference (95% CI 50% difference between traits). Broad-sense heritability was highest for shoot biomass traits (>0.60), intermediate (0.25-0.60) for the length and diameter of primary roots and lateral root branching density on the primary root, and lower (<0.25) for other root traits. Models demonstrate that root traits show temporal variations of various types. The phenotyping platform described here can be used to quantify environmental and temporal variation in traits contributing to root system architecture in B. rapa and can be extended to screen the large populations required for breeding for efficient resource acquisition.