Biology subjects

Khosla, K.

Publications and source records attributed to Khosla, K..

3 recordsLinked to original sources

bioRxiv2023

A machine vision guided robot for fully automated embryonic microinjection

Microinjection is a widely used technique for transgenesis, mutagenesis, cell labeling, cryopreservation, and in vitro fertilization in multiple single and multicellular organisms. Microinjection requires specialized skills acquired for each target organism and involves rate limiting and labor-intensive preparatory steps. Here we constructed a machine vision (MV) guided generalized robot that fully automates the process of microinjection in fruit fly (Drosophila melanogaster) and zebrafish (Danio rerio) embryos. The robot uses machine learning (ML) models trained to detect individual embryos in images of agar plates, and models trained to identify specific anatomical locations within each embryo in 3D space using dual view microscopes. The robot uses this information to serially perform microinjection in each detected embryo without any human intervention. We constructed and used three such robots to automatically microinject tens of thousands of Drosophila and zebrafish embryos. We systematically optimized robotic microinjection for each species and validated the use of the robot by performing routine transgenesis with proficiency comparable to highly skilled human practitioners while achieving up to 4x increases in microinjection throughput in Drosophila. The automated microinjection robot was utilized to microinject pools of over 20,000 uniquely barcoded plasmids into 1,713 embryos in two days to rapidly generate more than 400 unique transgenic Drosophila lines. This high throughput microinjection experiment enabled a novel measurement of the number of independent germline integration events per successfully injected embryo. Finally, we showed that robotic microinjection of cryoprotective agents in zebrafish embryos significantly improves vitrification rates and survival of cryopreserved embryos post-thaw as compared to manual microinjection, opening the tantalizing possibility of large-scale cryobanking of aquatic species at an industrial scale. We anticipate that this versatile automated microinjection system can be applied to carry out microinjection for genome-wide manipulation and cryopreservation at scale in a wide range of other organisms.

genetics↗

bioRxiv2023

The first proof of concept demonstration of nanowarming in coral tissue

Climate change is causing ocean acidification and warming, resulting in mass bleaching and death of corals globally. Cryopreservation and biobanking to secure the genetics of threatened populations is currently limited to coral sperm and larvae, which are only available during brief annual spawning events and are impacted by ocean warming, so there is an urgent need for methods to enable biobanking activities year-round. Here, we used vitrification and nanowarming to successfully recover adult coral tissues in a novel sample type, the single-polyp microfragment (SPMF). Fluorescence and confocal microscopy showed clearly defined tissues and green fluorescent protein fluorescence around the polyp mouth post-warming in 43.3% of SPMFs at 24 hours post-warming, and 30.0% at one month. These advances provide a basis for continued research and development of a field-ready protocol for cryopreservation of adult coral tissues, to permit biobanking of threatened coral species throughout the year and support reef restoration efforts.

ecology↗

bioRxiv2019

Distance preserving dimension reduction withlocal-topology based scaling for improvedclassification of Biomedical data-sets.

Dimension reduction is often used for several procedures of analysis of high dimensional biomedical data-sets such as classification or outlier detection. To improve performance of such data-mining steps, preserving both distance information and local topology among data-points could be more useful than giving priority to visualisation in low dimension. Therefore, we introduce topology preserving distance scaling (TPDS) to augment dimension reduction method meant to reproduce distance information in higher dimension. Our approach involves distance inflation to preserve local topology to avoid collapse during distance preservation based optimisation. Applying TPDS on diverse biomedical data-sets revealed that besides providing better visualisation than typical distance preserving methods, TPDS leads to better classification of data points in reduced dimension. For data-sets with outliers, the approach of TPDS also proves to be useful, even for purely distance-preserving method for achieving better convergence.

bioinformatics↗