Single-Cell Genetic Analysis Using Automated Microfluidics to Resolve Somatic Mosaicism

Somatic mosaicism occurs throughout normal development and contributes to numerous disease etiologies, including tumorigenesis and neurological disorders. Intratumor genetic heterogeneity is inherent to many cancers, creating challenges for effective treatments. Unfortunately, analysis of bulk DNA masks subclonal phylogenetic architectures created by the acquisition and distribution of somatic mutations amongst cells. As a result, single-cell genetic analysis is becoming recognized as vital for accurately characterizing cancers. Despite this, methods for single-cell genetics are lacking. Here we present an automated microfluidic workflow enabling efficient cell capture, lysis, and whole genome amplification (WGA). We find that ~90% of the genome is accessible in single cells with improved uniformity relative to current single-cell WGA methods. Allelic dropout (ADO) rates were limited to 13.75% and variant false discovery rates (SNV FDR) were 4.11x10^-6, on average. Application to ER-/PR-/HER2+ breast cancer cells and matched normal controls identified novel mutations that arose in a subpopulation of cells and effectively resolved the segregation of known cancer-related mutations with single-cell resolution. Finally, we demonstrate effective cell classification using mutation profiles with 10X average exome coverage depth per cell. Our data demonstrate an efficient automated microfluidic platform for single-cell WGA that enables the resolution of somatic mutation patterns in single cells.     

Single-cell exome sequencing reveals single-nucleotide mutation characteristics of a kidney tumor

Clear cell renal cell carcinoma (ccRCC) is the most common kidney cancer and has very few mutations that are shared between different patients. To better understand the intratumoral genetics underlying mutations of ccRCC, we carried out single-cell exome sequencing on a ccRCC tumor and its adjacent kidney tissue. Our data indicate that this tumor was unlikely to have resulted from mutations in VHL and PBRM1. Quantitative population genetic analysis indicates that the tumor did not contain any significant clonal subpopulations and also showed that mutations that had different allele frequencies within the population also had different mutation spectrums. Analyses of these data allowed us to delineate a detailed intratumoral genetic landscape at a single-cell level. Our pilot study demonstrates that ccRCC may be more genetically complex than previously thought and provides information that can lead to new ways to investigate individual tumors, with the aim of developing more effective cellular targeted therapies.     

肺癌循环肿瘤细胞的单细胞EGFR基因突变检测

循环肿瘤细胞（Circulating tumor cells,CTCs）是从肿瘤原发病灶脱落并侵入外周血循环的肿瘤细胞。由于CTCs存在较大的异质性,其与癌症发展转移密切相关,但目前尚缺乏有效的CTCs单细胞异质性检测方法。鉴于此,本文发展了在单细胞层面对CTCs进行基因突变的检测方法并用于单个肺癌CTC的EGFR（Epidermal growth factor receptor）基因突变检测。首先用集成式微流控系统完成血液中稀有CTCs的捕获,接着将CTCs释放入含有多个微孔的微阵列芯片中,得到含有单个CTC的微孔,通过显微操作将单个CTC转入PCR管内完成单细胞基因组的放大,并进行单细胞的EGFR基因突变检测。以非小细胞肺癌细胞系A549、NCI-H1650和NCI-H1975为样本,通过芯片与毛细管修饰、引物扩增条件（复性温度、循环次数）的优化,结果显示在复性温度59℃、30个循环次数的条件下,引物扩增效果最优。利用该方法成功地对非小细胞肺癌（Non-small cell lung cancer, NSCLC）患者的血液样本进行了测试。从患者2 mL血液中获取5个CTCs,分别对其EGFR基因的第18、19、20、21外显子进行测序,发现该患者CTCs均为EGFR野生型。研究结果证明此检测方法可以灵敏地用于单个CTC基因突变的检测,在临床研究上具有重要的指导意义。     

High resolution array-CGH analysis of single cells

Heterogeneity in the genome copy number of tissues is of particular importance in solid tumor biology. Furthermore, many clinical applications such as pre-implantation and non-invasive prenatal diagnosis would benefit from the ability to characterize individual single cells. As the amount of DNA from single cells is so small, several PCR protocols have been developed in an attempt to achieve unbiased amplification. Many of these approaches are suitable for subsequent cytogenetic analyses using conventional methodologies such as comparative genomic hybridization (CGH) to metaphase spreads. However, attempts to harness array-CGH for single-cell analysis to provide improved resolution have been disappointing. Here we describe a strategy that combines single-cell amplification using GenomePlex library technology (GenomePlex^® Single Cell Whole Genome Amplification Kit, Sigma-Aldrich, UK) and detailed analysis of genomic copy number changes by high-resolution array-CGH. We show that single copy changes as small as 8.3 Mb in single cells are detected reliably with single cells derived from various tumor cell lines as well as patients presenting with trisomy 21 and Prader–Willi syndrome. Our results demonstrate the potential of this technology for studies of tumor biology and for clinical diagnostics.     

Continuous cultivation of fission yeast: Analysis of single-cell protein synthesis kinetics

A fundamental problem in microbial reactor analysis is identification of the relationship between environment and individual cell metabolic activity. Population balance equations provide a link between experimental measurements of composition frequency functions in microbial populations on the one hand and macromolecular synthesis kinetics and cell division control parameters for single cells on the other. Flow microfluorometry measurements of frequency functions for single-cell protein content in Schizosaccharomyces pombe in balanced exponential growth have been analyzed by two different methods. One approach utilizes the integrated form of the population balance equation known as the Collins-Richmond equation, and the other method involves optimization of parameters in assumed kinetic and cell division functional forms in order to best fit measured frequency functions with corresponding model solutions. Both data interpretation techniques indicate that rates of protein synthesis increase most in small protein content cells as the population specific growth rate increases, leading to parabolic single-cell protein synthesis kinetics at large specific growth rates. Utilization of frequency function data for an asynchronous population is shown in this case to be a far more sensitive method for determination of single-cell kinetics than is monitoring the metabolic dynamics of a single cell or, equivalently, synchronous culture analyses.     

Whole Exome Sequencing and Homozygosity Mapping Identify Mutation in the Cell Polarity Protein GPSM2 as the Cause of Nonsyndromic Hearing Loss DFNB82

Massively parallel sequencing of targeted regions, exomes, and complete genomes has begun to dramatically increase the pace of discovery of genes responsible for human disorders. Here we describe how exome sequencing in conjunction with homozygosity mapping led to rapid identification of the causative allele for nonsyndromic hearing loss DFNB82 in a consanguineous Palestinian family. After filtering out worldwide and population-specific polymorphisms from the whole exome sequence, only a single deleterious mutation remained in the homozygous region linked to DFNB82. The nonsense mutation leads to an early truncation of the G protein signaling modulator GPSM2, a protein that is essential for maintenance of cell polarity and spindle orientation. In the mouse inner ear, GPSM2 is localized to apical surfaces of hair cells and supporting cells and is most highly expressed during embryonic development. Identification of GPSM2 as essential to the development of normal hearing suggests dysregulation of cell polarity as a mechanism underlying hearing loss.     

Single-cell exome sequencing and monoclonal evolution of a JAK2-negative myeloproliferative neoplasm

Tumor heterogeneity presents a challenge for inferring clonal evolution and driver gene identification. Here, we describe a method for analyzing the cancer genome at a single-cell nucleotide level. To perform our analyses, we first devised and validated a high-throughput whole-genome single-cell sequencing method using two lymphoblastoid cell line single cells. We then carried out whole-exome single-cell sequencing of 90 cells from a JAK2-negative myeloproliferative neoplasm patient. The sequencing data from 58 cells passed our quality control criteria, and these data indicated that this neoplasm represented a monoclonal evolution. We further identified essential thrombocythemia (ET)-related candidate mutations such as SESN2 and NTRK1, which may be involved in neoplasm progression. This pilot study allowed the initial characterization of the disease-related genetic architecture at the single-cell nucleotide level. Further, we established a single-cell sequencing method that opens the way for detailed analyses of a variety of tumor types, including those with high genetic complex between patients.     

Genome-wide single-cell analysis of recombination activity and de novo mutation rates in human sperm

Meiotic recombination and de novo mutation are the two main contributions toward gamete genome diversity, and many questions remain about how an individual human's genome is edited by these two processes. Here, we describe a high-throughput method for single-cell whole-genome analysis that was used to measure the genomic diversity in one individual's gamete genomes. A microfluidic system was used for highly parallel sample processing and to minimize nonspecific amplification. High-density genotyping results from 91 single cells were used to create a personal recombination map, which was consistent with population-wide data at low resolution but revealed significant differences from pedigree data at higher resolution. We used the data to test for meiotic drive and found evidence for gene conversion. High-throughput sequencing on 31 single cells was used to measure the frequency of large-scale genome instability, and deeper sequencing of eight single cells revealed de novo mutation rates with distinct characteristics.     

Exome Sequencing in Classic Hairy Cell Leukaemia Reveals Widespread Variation in Acquired Somatic Mutations between Individual Tumours Apart from the Signature BRAF V(600)E Lesion

In classic Hairy cell leukaemia (HCLc), a single case has thus far been interrogated by whole exome sequencing (WES) in a treatment naive patient, in which BRAF V(600)E was identified as an acquired somatic mutation and confirmed as occurring near-universally in this form of disease by conventional PCR-based cohort screens. It left open however the question whether other genome-wide mutations may also commonly occur at high frequency in presentation HCLc disease. To address this, we have carried out WES of 5 such typical HCLc cases, using highly purified splenic tumour cells paired with autologous T cells for germline. Apart from BRAF V(600)E, no other recurrent somatic mutation was identified in these HCLc exomes, thereby excluding additional acquired mutations as also prevalent at a near-universal frequency in this form of the disease. These data then place mutant BRAF at the centre of the neoplastic drive in HCLc. A comparison of our exome data with emerging genetic findings in HCL indicates that additional somatic mutations may however occur recurrently in smaller subsets of disease. As mutant BRAF alone is insufficient to drive malignant transformation in other histological cancers, it suggests that individual tumours utilise largely differing patterns of genetic somatic mutations to coalesce with BRAF V(600)E to drive pathogenesis of malignant HCLc disease.     

Enchanced accuracy of coliform testing in seawater by a modification of the most-probable-number method.

A 1-year study of marine water sample from six beach locations showed that the most-probable-number method failed to recover significant numbers of coli-forms. Modifying this method by transferring, after 48 h, presumptive negatives (growth and no gas production) to confirmed and fecal coliform media significantly improved recovery. Tests which were presumptive negative but confirmed as fecal coliform positive were designated as false negatives. Most-probable-number method false negatives occurred throughout the year, with 143 of 270 samples collected producing false negatives. More than 50% of fecal coliform false-negative isolates were Escherichia coli. Inclusion of false-negative tubes into the coliform most-probable-number method data resulted in increased violation of the California ocean water contact sports standard at all sites. More than 20% of the samples collected were in violation of this standard. These data indicate that modification of the most-probable-number method increases detection of coliform numbers in the marine environment.     

Enchanced accuracy of coliform testing in seawater by a modification of the most-probable-number method.

A 1-year study of marine water sample from six beach locations showed that the most-probable-number method failed to recover significant numbers of coli-forms. Modifying this method by transferring, after 48 h, presumptive negatives (growth and no gas production) to confirmed and fecal coliform media significantly improved recovery. Tests which were presumptive negative but confirmed as fecal coliform positive were designated as false negatives. Most-probable-number method false negatives occurred throughout the year, with 143 of 270 samples collected producing false negatives. More than 50% of fecal coliform false-negative isolates were Escherichia coli. Inclusion of false-negative tubes into the coliform most-probable-number method data resulted in increased violation of the California ocean water contact sports standard at all sites. More than 20% of the samples collected were in violation of this standard. These data indicate that modification of the most-probable-number method increases detection of coliform numbers in the marine environment.     

A Theoretical Analysis of the Effects of Tumor-Treating Electric Fields on Single Cells

Tumor-treating fields (TTFields) are low-intensity and intermediate-frequency alternating electric fields that have been found to inhibit tumor cell growth. While effective, the mechanism by which TTFields affect cell growth is not yet clearly understood. Although numerous mathematical studies on the effects of electromagnetic fields on single cells exist, the effect of TTFields on single cells have been analyzed less frequently. The goal of this study is to explore through a mathematical analysis the effects of TTFields on single cells, with particular emphasis on the thermal effect. We examine herein two single-cell models, a simplified spheroidal model and a simulation of a U-87 MG glioblastoma cell model obtained from microscopic images. A finite element method is used to analyze the electric field distribution, electromagnetic loss, and thermal field distribution. The results further prove that the electric field in the cytoplasm is too weak and its thermal damage can be excluded as a mechanism for cell death in TTFields. Bioelectromagnetics. 2020;41:438–446. © 2020 Bioelectromagnetics Society.     

The p53R172H Mutant Does Not Enhance Hepatocellular Carcinoma Development and Progression

Hepatocellular carcinoma is a highly deadly malignancy, accounting for approximately 800,000 deaths worldwide every year. Mutation of the p53 tumor suppressor gene is a common genetic change in HCC, present in 30% of cases. p53^R175H (corresponding to p53^R172H in mice) is a hotspot for mutation that demonstrates “prometastatic” gain-of-function in other cancer models. Since the frequency of p53 mutation increases with tumor grade in HCC, we hypothesized that p53^R172H is a gain-of-function mutation in HCC that contributes to a decrease in tumor-free survival and an increase in metastasis. In an HCC mouse model, we found that p53^R172H/flox mice do not have decreased survival, increased tumor incidence, or increased metastasis, relative to p53^flox/flox littermates. Analysis of cell lines derived from both genotypes indicated that there are no differences in anchorage-independent growth and cell migration. However, shRNA-mediated knockdown of mutant p53 in p53^R172H-expressing HCC cell lines resulted in decreased cell migration and anchorage-independent growth. Thus, although p53 mutant-expressing cells and tumors do not have enhanced properties relative to their p53 null counterparts, p53^R172H-expressing HCC cells depend on this mutant for their transformation. p53 mutants have been previously shown to bind and inhibit the p53 family proteins p63 and p73. Interestingly, we find that the levels of p63 and p73 target genes are similar in p53 mutant and p53 null HCC cells. These data suggest that pathways regulated by these p53 family members are similarly impacted by p53^R172H in mutant expressing cells, and by alternate mechanisms in p53 null cells, resulting in equivalent phenotypes. Consistent with this, we find that p53 null HCC cell lines display lower levels of the TA isoforms of p63 and p73 and higher levels of ΔNp63. Taken together these data point to the importance of p63 and p73 in constraining HCC progression.     

单个肿瘤细胞测序研究进展

肿瘤是机体在各种致癌因素作用下,遗传物质受损导致特定细胞失去对正常生长调控,引起其克隆性异常增生而形成的恶性赘生物。随着单细胞分离技术及单细胞测序技术日益成熟,单个肿瘤细胞全基因组测序已成为肿瘤研究的一个崭新的领域。该文就对单个肿瘤细胞的获取及单个肿瘤细胞测序研究进展进行综述。     

Quartz-Seq: a highly reproducible and sensitive single-cell RNA sequencing method,reveals non-genetic gene-expression heterogeneity

Development of a highly reproducible and sensitive single-cell RNA sequencing (RNA-seq) method would facilitate the understanding of the biological roles and underlying mechanisms of non-genetic cellular heterogeneity. In this study, we report a novel single-cell RNA-seq method called Quartz-Seq that has a simpler protocol and higher reproducibility and sensitivity than existing methods. We show that single-cell Quartz-Seq can quantitatively detect various kinds of non-genetic cellular heterogeneity, and can detect different cell types and different cell-cycle phases of a single cell type. Moreover, this method can comprehensively reveal gene-expression heterogeneity between single cells of the same cell type in the same cell-cycle phase.     

Distinguishing between linear and exponential cell growth during the division cycle: Single-cell studies, cell-culture studies, and the object of cell-cycle research

Background  

Two approaches to understanding growth during the cell cycle are single-cell studies, where growth during the cell cycle of a single cell is measured, and cell-culture studies, where growth during the cell cycle of a large number of cells as an aggregate is analyzed. Mitchison has proposed that single-cell studies, because they show variations in cell growth patterns, are more suitable for understanding cell growth during the cell cycle, and should be preferred over culture studies. Specifically, Mitchison argues that one can glean the cellular growth pattern by microscopically observing single cells during the division cycle. In contrast to Mitchison's viewpoint, it is argued here that the biological laws underlying cell growth are not to be found in single-cell studies. The cellular growth law can and should be understood by studying cells as an aggregate.