Sequencing of human genomes extracted from single cancer cells isolated in a valveless microfluidic device

Rapid microfluidics prototyping through variotherm desktop injection molding for multiplex diagnostics

In this work, we demonstrate an inexpensive method of prototyping microfluidics using a desktop injection molding machine. A centrifugal microfluidic device with a novel central filling mechanism was developed to demonstrate the technique. We overcame the limitations of desktop machines in replicating microfluidic features by variotherm heating and cooling the mold between 50 °C and 110 °C within two minutes. Variotherm heating enabled good replication of microfeatures, with a coefficient of variation averaging only 3.6% attained for the measured widths of 100 μm wide molded channels. Using this methodology, we produced functional polystyrene centrifugal microfluidic chips, capable of aliquoting fluids into 5.0 μL reaction chambers with 97.5% accuracy. We performed allele-specific loop-mediated isothermal amplification (AS-LAMP) reactions for genotyping CYP2C19 alleles on these chips. Readouts were generated using optical pH sensors integrated onto chips, by drop-casting sensor precursor solutions into reaction chambers before final chip assembly. Positive reactions could be discerned by decreases in pH sensor fluorescence, thresholded against negative control reactions lacking the primers for nucleic acid amplification and with time-to-results averaging 38 minutes. Variotherm desktop injection molding can enable researchers to prototype microfluidic devices more cost-effectively, in an iterative fashion, due to reduced costs of smaller, in-house molds. Designs prototyped this way can be directly translated to mass production, enhancing their commercialization potential and positive impacts.

Frontiers in single cell analysis: multimodal technologies and their clinical perspectives

Single cell multimodal analysis is at the frontier of single cell research: it defines the roles and functions of distinct cell types through simultaneous analysis to provide unprecedented insight into cellular processes. Current single cell approaches are rapidly moving toward multimodal characterizations. It replaces one-dimensional single cell analysis, for example by allowing for simultaneous measurement of transcription and post-transcriptional regulation, epigenetic modifications and/or surface protein expression. By providing deeper insights into single cell processes, multimodal single cell analyses paves the way to new understandings in various cellular processes such as cell fate decisions, physiological heterogeneity or genotype-phenotype linkages. At the forefront of this, microfluidics is key for high-throughput single cell analysis. Here, we present an overview of the recent multimodal microfluidic platforms having a potential in biomedical research, with a specific focus on their potential clinical applications.

Microfluidics applications for high-throughput single cell sequencing

The inherent heterogeneity of individual cells in cell populations plays significant roles in disease development and progression, which is critical for disease diagnosis and treatment. Substantial evidences show that the majority of traditional gene profiling methods mask the difference of individual cells. Single cell sequencing can provide data to characterize the inherent heterogeneity of individual cells, and reveal complex and rare cell populations. Different microfluidic technologies have emerged for single cell researches and become the frontiers and hot topics over the past decade. In this review article, we introduce the processes of single cell sequencing, and review the principles of microfluidics for single cell analysis. Also, we discuss the common high-throughput single cell sequencing technologies along with their advantages and disadvantages. Lastly, microfluidics applications in single cell sequencing technology for the diagnosis of cancers and immune system diseases are briefly illustrated.

Experimental and bioinformatics considerations in cancer application of single cell genomics

Single cell genomics offers an unprecedented resolution to interrogate genetic heterogeneity in a patient's tumour at the intercellular level. However, the DNA yield per cell is insufficient for today's sequencing library preparation protocols. This necessitates DNA amplification which is a key source of experimental noise. We provide an evaluation of two protocols using micro-fluidics based amplification for whole exome sequencing, which is an experimental scenario commonly used in single cell genomics. The results highlight their respective biases and relative strengths in identification of single nucleotide variations. Towards this end, we introduce a workflow SoVaTSiC, which allows for quality evaluation and somatic variant identification of single cell data. As proof of concept, the framework was applied to study a lung adenocarcinoma tumour. The analysis provides insights into tumour phylogeny by identifying key mutational events in lung adenocarcinoma evolution. The consequence of this inference is supported by the histology of the tumour and demonstrates usefulness of the approach.

Microfluidic Single-Cell Omics Analysis

The commonly existing cellular heterogeneity plays a critical role in biological processes such as embryonic development, cell differentiation, and disease progress. Single-cell omics-based heterogeneous studies have great significance for identifying different cell populations, discovering new cell types, revealing informative cell features, and uncovering significant interrelationships between cells. Recently, microfluidics has evolved to be a powerful technology for single-cell omics analysis due to its merits of throughput, sensitivity, and accuracy. Herein, the recent advances of microfluidic single-cell omics analysis, including different microfluidic platform designs, lysis strategies, and omics analysis techniques, are reviewed. Representative applications of microfluidic single-cell omics analysis in complex biological studies are then summarized. Finally, a few perspectives on the future challenges and development trends of microfluidic-assisted single-cell omics analysis are discussed.

Device for whole genome sequencing single circulating tumor cells from whole blood

Whole-genome sequencing on circulating tumor cells (CTCs) at the single cell level has recently been found helpful for precision medicine, as the oncogenic profiles of single CTCs are useful for discovering oncogenic mutation heterogeneities and guiding/adjusting cancer treatment. To overcome the limits of existing methods of single CTC sequencing, in which CTC enrichment, identification and gene amplification are performed by discrete modules, this study presents a novel method in which all processing steps from blood sample collection to preparation of gene amplification products for sequencers are finished in a single microfluidic chip. This microfluidic chip comprehensively performs blood filtering, CTC enrichment, CTC identification/isolation, CTC lysis and whole genome amplification (WGA) at the single cell level. By sequencing single CTCs from clinical blood samples with pointing key driver and drug-resistance mutations, the novel microfluidic chip was validated to be capable of genetically profiling single CTCs with minimum cell loss/human labor, and more importantly, high accuracy and repeatability, which are crucial factors for promoting clinical application of single CTC sequencing.

Single-Cell Omics Analyses Enabled by Microchip Technologies

Single-cell omics studies provide unique information regarding cellular heterogeneity at various levels of the molecular biology central dogma. This knowledge facilitates a deeper understanding of how underlying molecular and architectural changes alter cell behavior, development, and disease processes. The emerging microchip-based tools for single-cell omics analysis are enabling the evaluation of cellular omics with high throughput, improved sensitivity, and reduced cost. We review state-of-the-art microchip platforms for profiling genomics, epigenomics, transcriptomics, proteomics, metabolomics, and multi-omics at single-cell resolution. We also discuss the background of and challenges in the analysis of each molecular layer and integration of multiple levels of omics data, as well as how microchip-based methodologies benefit these fields. Additionally, we examine the advantages and limitations of these approaches. Looking forward, we describe additional challenges and future opportunities that will facilitate the improvement and broad adoption of single-cell omics in life science and medicine.

Single-molecule DNA-mapping and whole-genome sequencing of individual cells

To elucidate cellular diversity and clonal evolution in tissues and tumors, one must resolve genomic heterogeneity in single cells. To this end, we have developed low-cost, mass-producible micro-/nanofluidic chips for DNA extraction from individual cells. These chips have modules that collect genomic DNA for sequencing or map genomic structure directly, on-chip, with denaturation-renaturation (D-R) optical mapping [Marie R, et al. (2013) Proc Natl Acad Sci USA 110:4893-4898]. Processing of single cells from the LS174T colorectal cancer cell line showed that D-R mapping of single molecules can reveal structural variation (SV) in the genome of single cells. In one experiment, we processed 17 fragments covering 19.8 Mb of the cell's genome. One megabase-large fragment aligned well to chromosome 19 with half its length, while the other half showed variable alignment. Paired-end single-cell sequencing supported this finding, revealing a region of complexity and a 50-kb deletion. Sequencing struggled, however, to detect a 20-kb gap that D-R mapping showed clearly in a megabase fragment that otherwise mapped well to the reference at the pericentromeric region of chromosome 4. Pericentromeric regions are complex and show substantial sequence homology between different chromosomes, making mapping of sequence reads ambiguous. Thus, D-R mapping directly, from a single molecule, revealed characteristics of the single-cell genome that were challenging for short-read sequencing.