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. Considering sequential manipulation is often required to conduct high-throughput screening assays on large cellular and molecular libraries, advancements in sequential operation and integration are required to advance the field. This current limitation greatly reduces the type of assays that can be realized in a high-throughput droplet format and becomes more prevalent in large library screening applications. Here we present an integrated multi-layer droplet microfluidic platform that can handle large numbers of droplets with high efficiency and minimum error. The platform combines two-photon photolithography-fabricated curved microstructures that allow high-efficiency (99.9%) re-flow of droplets and a unique droplet cleaving that automatically synchronizes paired droplets enabling high-efficiency (99.9%) downstream merging. We demonstrate that this method is applicable to a broad range of droplet sizes, including relatively large droplet sizes (hundreds of micrometers in diameter) that are typically more difficult to manipulate with high efficiency, yet are required in many cell assay applications requiring large organisms or multiple incubation steps. The utility of this highly efficient integrated droplet microfluidic platform was demonstrated by conducting a mock antibiotic screening assay against a bacterial pathogen. The approach and system presented here provides new avenues for the realization of ultra-high-efficiency multi-step droplet microfluidic systems with minimal error.

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. By encapsulating single cells into water-in-oil emulsion droplets, each variant was separately cultured inside an individual droplet that functioned as an independent bioreactor. In conjunction with an on-chip fluorescent lipid staining process within droplets, microalgal growth and lipid content were characterized by measuring chlorophyll and BODIPY fluorescence intensities through an integrated optical detection system in a flow-through manner. Droplets containing cells with higher growth and lipid content were selectively retrieved and further analyzed off-chip. The growth and lipid content screening capabilities of the developed platform were successfully demonstrated by first carrying out proof-of-concept screening using known Chlamydomonas reinhardtii mutants. The platform was then utilized to screen an ethyl methanesulfonate (EMS)-mutated C. reinhardtii population, where eight potential mutants showing faster growth and higher lipid content were selected from 200,000 examined samples, demonstrating the capability of the platform as a high-throughput screening tool for microalgal biofuel development.

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.

Methods

Data and biological samples from 297 spina bifida cases and 300 controls were derived from a population-based case-control study conducted in California. 37 SNPs within CITED2, EP300, CREBBP, TFAP2A, CARM1 and ALX1 were genotyped using an ABI SNPlex assay. Odds ratios and 95% confidence intervals were calculated for alleles, genotypes and haplotypes to evaluate the risk for spina bifida.

Results

Several SNPs showed increased or decreased risk, including CITED2 rs1131431 (OR = 5.32, 1.04~27.30), EP300 rs4820428 (OR = 1.30, 1.01~1.67), EP300 rs4820429 (OR = 0.50, 0.26~0.50, in whites, OR = 0.7, 0.49~0.99 in all subjects), EP300 rs17002284 (OR = 0.43, 0.22~0.84), TFAP2A rs3798691 (OR = 1.78, 1.13~2.87 in Hispanics), CREBBP rs129986 (OR = 0.27, 0.11~0.69), CARM1 rs17616105 (OR = 0.41, 0.22~0.72 in whites). In addition, one haplotype block in EP300 and one in TFAP2A appeared to be associated with increased risk.

Conclusions

Modest associations were observed in CITED2, EP300, CREBBP, TFAP2A and CARM1 but not ALX1. However, these modest associations were not statistically significant after correction for multiple comparisons. Searching for potential functional variants and rare causal mutations is warranted in these genes.