No abstract

Lipid nanoparticles (LNP) are the leading systems for in vivo delivery of small interfering RNA (siRNA) for therapeutic applications. Formulation of LNP siRNA systems requires rapid mixing of solutions containing cationic lipid with solutions containing siRNA. Current formulation procedures employ macroscopic mixing processes to produce systems 70-nm diameter or larger that have variable siRNA encapsulation efficiency, homogeneity, and reproducibility. Here, we show that microfluidic mixing techniques, which permit millisecond mixing at the nanoliter scale, can reproducibly generate limit size LNP siRNA systems 20 nm and larger with essentially complete encapsulation of siRNA over a wide range of conditions with polydispersity indexes as low as 0.02. Optimized LNP siRNA systems produced by microfluidic mixing achieved 50% target gene silencing in hepatocytes at a dose level of 10 µg/kg siRNA in mice. We anticipate that microfluidic mixing, a precisely controlled and readily scalable technique, will become the preferred method for formulation of LNP siRNA delivery systems.

The genome sequence of T. parva shows remarkable differences from the other apicomplexan genomes sequenced to date. It provides significant improvements in our understanding of the metabolic capabilities of T. parva and a foundation for studying parasite-induced host cell transformation and constitutes a critical knowledge base for a pathogen of significance to agriculture in Africa. Mining of sequence data has already proved useful in the search for candidate vaccine antigens (3).

A long-sought milestone in microfluidics research has been the development of integrated technology for scalable analysis of transcription in single cells. Here we present a fully integrated microfluidic device capable of performing high-precision RT-qPCR measurements of gene expression from hundreds of single cells per run. Our device executes all steps of single-cell processing, including cell capture, cell lysis, reverse transcription, and quantitative PCR. In addition to higher throughput and reduced cost, we show that nanoliter volume processing reduced measurement noise, increased sensitivity, and provided single nucleotide specificity. We apply this technology to 3,300 single-cell measurements of ( i ) miRNA expression in K562 cells, ( ii ) coregulation of a miRNA and one of its target transcripts during differentiation in embryonic stem cells, and ( iii ) single nucleotide variant detection in primary lobular breast cancer cells. The core functionality established here provides the foundation from which a variety of on-chip single-cell transcription analyses will be developed.

SummaryAccurate measurement of clonal genotypes, mutational processes, and replication states from individual tumor-cell genomes will facilitate improved understanding of tumor evolution. We have developed DLP+, a scalable single-cell whole-genome sequencing platform implemented using commodity instruments, image-based object recognition, and open source computational methods. Using DLP+, we have generated a resource of 51,926 single-cell genomes and matched cell images from diverse cell types including cell lines, xenografts, and diagnostic samples with limited material. From this resource we have defined variation in mitotic mis-segregation rates across tissue types and genotypes. Analysis of matched genomic and image measurements revealed correlations between cellular morphology and genome ploidy states. Aggregation of cells sharing copy number profiles allowed for calculation of single-nucleotide resolution clonal genotypes and inference of clonal phylogenies and avoided the limitations of bulk deconvolution. Finally, joint analysis over the above features defined clone-specific chromosomal aneuploidy in polyclonal populations.