NOVAsort for error-free droplet microfluidics.

High-throughput screening techniques are pivotal to unlocking the mysteries of biology. Yet, the promise of droplet microfluidics in enabling single-cell resolution, ultra-high-throughput screening remains largely unfulfilled. Droplet sorting errors caused by polydisperse droplet sizes that are often inevitable in multi-step assays have severely limited the effectiveness and utility of this technique, especially when screening large libraries.

High-Efficiency Interdigitated Electrode-Based Droplet Merger for Enabling Error-Free Droplet Microfluidic Systems.

Merging two droplets into a droplet to add and mix two contents is one of the common droplet microfluidic functions with droplet generation and sorting, performing broad ranges of biological and chemical assays in droplets. However, traditional droplet-merging techniques often encounter unsynchronized droplets, causing overmerging or mis-merging, and unwanted merging outside of the desired zone. This is more severe when the incoming droplets to be merged are polydisperse in their sizes, often observed in assays that require long-term incubation, elevated-temperature, and/or multiple droplet processing steps.

An ultra high-efficiency droplet microfluidics platform using automatically synchronized droplet pairing and merging.

Droplet microfluidics systems hold great promise in their ability to conduct high-throughput assays for a broad range of life science applications. Despite their promise in the field and capability to conduct complex liquid handling steps, currently, most droplet microfluidic systems used for real assays utilize only a few droplet manipulation steps connected in series, and are often not integrated together on a single chip or platform. This is due to the fact that linking multiple sequential droplet functions within a single chip to operate at high efficiency over long periods of time remains technically challenging.

High-throughput droplet microfluidics screening platform for selecting fast-growing and high lipid-producing microalgae from a mutant library.

Biofuels derived from microalgal lipids have demonstrated a promising potential as future renewable bioenergy. However, the production costs for microalgae-based biofuels are not economically competitive, and one strategy to overcome this limitation is to develop better-performing microalgal strains that have faster growth and higher lipid content through genetic screening and metabolic engineering. In this work, we present a high-throughput droplet microfluidics-based screening platform capable of analyzing growth and lipid content in populations derived from single cells of a randomly mutated microalgal library to identify and sort variants that exhibit the desired traits such as higher growth rate and increased lipid content.

A droplet microfluidics platform for rapid microalgal growth and oil production analysis.

Microalgae have emerged as a promising source for producing future renewable biofuels. Developing better microalgal strains with faster growth and higher oil production rates is one of the major routes towards economically viable microalgal biofuel production. In this work, we present a droplet microfluidics-based microalgae analysis platform capable of measuring growth and oil content of various microalgal strains with single-cell resolution in a high-throughput manner.

A three-dimensional electrode for highly efficient electrocoalescence-based droplet merging.

Droplet merging is one of the key functions in the ever-widening applications of droplet microfluidics. Enhancing the efficiency of electric field-based droplet merging, namely electrocoalescence, can lead to an increase in platform stability and overcome one of the major bottlenecks in further improving throughputs of droplet microfluidic systems. In this work, a paired three-dimensional (3D) electrode design that can provide a uniform electric field within a droplet merging region, which is also properly aligned with the droplet dipole moments for highly efficient electrocoalescence is presented.

Genes encoding critical transcriptional activators for murine neural tube development and human spina bifida: a case-control study.

Background: Spina bifida is a malformation of the neural tube and is the most common of neural tube defects (NTDs). The etiology of spina bifida is largely unknown, although it is thought to be multi-factorial, involving multiple interacting genes and environmental factors. Mutations in transcriptional co-activator genes-Cited2, p300, Cbp, Tfap2α, Carm1 and Cart1 result in NTDs in murine models, thus prompt us to investigate whether homologues of these genes are associated with NTDs in humans.