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.

Quantitative accounting of dye leakage and photobleaching in single lipid vesicle measurements: Implications for biomacromolecular interaction analysis.

Highly parallel measurements on single, tethered lipid vesicles enable real-time monitoring of dynamic membrane interactions of relevance to medical, pharmaceutical, and biotechnological applications. Monitoring the time-dependent release of entrapped fluorescent dyes is a popular measurement approach, although it is often challenging to accurately extract quantitative biochemical parameters. Key issues include dye leakage and imaging-related photobleaching, and corrective measures are needed. Herein, we present an extended analytical framework to collect and interpret time-lapsed fluorescence microscopy imaging data, and demonstrate its utility for tracking membrane-peptide interactions. Our approach is focused on improving platform design and data analysis. First, we identified suitable membrane compositions to minimize dye leakage while enhancing the biomimetic character of lipid vesicles. Second, a data normalization procedure was developed to correct for experimental artifacts, namely dye leakage and photobleaching, and hence improve measurement accuracy. This analytical procedure was applied to experimentally determine the rate of peptide-induced pore formation in single lipid vesicles, and there was up to a nearly three-fold decrease in the measured rate, as compared to uncorrected data. Taken together, the results present a broadly applicable analytical framework to account for experimental artifacts and improve measurement accuracy in highly parallel, single lipid vesicle arrays.

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.

Choosing the best embryo by time lapse versus standard morphology.

Within the past few years the morphological evaluation of in vitro fertilized embryos has been extended to include continuous surveillance, enabled by the introduction of time-lapse incubators developed specifically for IVF treatment. As a result time-lapse monitoring has been implemented in many clinics worldwide. The proposed benefits compared with culture in a standard incubator and fixed time-point evaluation are uninterrupted culture, a flexible workflow in the laboratory, and improved embryo selection. The latter is based on the reasonable assumption that more frequent observations will provide substantially more information on the relationship between development, timing, and embryo viability. Several retrospective studies have confirmed a relationship between time-lapse parameters and embryo viability evaluated by developmental competence, aneuploidy, and clinical pregnancy. Furthermore a much anticipated randomized study has shown improved pregnancy rates (PRs) after culture in a time-lapse incubator combined with selection using a hierarchical time-lapse selection model. At present this is the only randomized study on possible benefits of time lapse in human embryology. Strict evidence may still seem too weak to introduce time lapse in routine clinical setting. This aim of this review is therefore to perform a balanced discussion of the evidence for time-lapse monitoring.

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.

Noise-free accurate count of microbial colonies by time-lapse shadow image analysis.

Microbial colonies in food matrices could be counted accurately by a novel noise-free method based on time-lapse shadow image analysis. An agar plate containing many clusters of microbial colonies and/or meat fragments was trans-illuminated to project their 2-dimensional (2D) shadow images on a color CCD camera. The 2D shadow images of every cluster distributed within a 3-mm thick agar layer were captured in focus simultaneously by means of a multiple focusing system, and were then converted to 3-dimensional (3D) shadow images. By time-lapse analysis of the 3D shadow images, it was determined whether each cluster comprised single or multiple colonies or a meat fragment. The analytical precision was high enough to be able to distinguish a microbial colony from a meat fragment, to recognize an oval image as two colonies contacting each other, and to detect microbial colonies hidden under a food fragment. The detection of hidden colonies is its outstanding performance in comparison with other systems. The present system attained accuracy for counting fewer than 5 colonies and is therefore of practical importance.