Recent in vitro and in vivo studies have highlighted the importance of the cell nucleus in governing migration through confined environments. Microfluidic devices that mimic the narrow interstitial spaces of tissues have emerged as important tools to study cellular dynamics during confined migration, including the consequences of nuclear deformation and nuclear envelope rupture. However, while image acquisition can be automated on motorized microscopes, the analysis of the corresponding time-lapse sequences for nuclear transit through the pores and events such as nuclear envelope rupture currently requires manual analysis. In addition to being highly time-consuming, such manual analysis is susceptible to person-to-person variability. Studies that compare large numbers of cell types and conditions therefore require automated image analysis to achieve sufficiently high throughput. Here, we present an automated image analysis program to register microfluidic constrictions and perform image segmentation to detect individual cell nuclei. The MATLAB program tracks nuclear migration over time and records constriction-transit events, transit times, transit success rates, and nuclear envelope rupture. Such automation reduces the time required to analyze migration experiments from weeks to hours, and removes the variability that arises from different human analysts. Comparison with manual analysis confirmed that both constriction transit and nuclear envelope rupture were detected correctly and reliably, and the automated analysis results closely matched a manual analysis gold standard. Applying the program to specific biological examples, we demonstrate its ability to detect differences in nuclear transit time between cells with different levels of the nuclear envelope proteins lamin A/C, which govern nuclear deformability, and to detect an increase in nuclear envelope rupture duration in cells in which CHMP7, a protein involved in nuclear envelope repair, had been depleted. The program thus presents a versatile tool for the study of confined migration and its effect on the cell nucleus.

Mutation data reveal the dynamic equilibrium between DNA damage and repair processes in cells and are indispensable to the understanding of age-related diseases, tumor evolution, and the acquisition of drug resistance. However, available genome-wide methods have a limited ability to resolve rare somatic variants and the relationships between these variants. Here, we present lineage sequencing, a new genome sequencing approach that enables somatic event reconstruction by providing quality somatic mutation call sets with resolution as high as the single-cell level in subject lineages. Lineage sequencing entails sampling single cells from a population and sequencing subclonal sample sets derived from these cells such that knowledge of relationships among the cells can be used to jointly call variants across the sample set. This approach integrates data from multiple sequence libraries to support each variant and precisely assigns mutations to lineage segments. We applied lineage sequencing to a human colon cancer cell line with a DNA polymerase epsilon (POLE) proofreading deficiency (HT115) and a human retinal epithelial cell line immortalized by constitutive telomerase expression (RPE1). Cells were cultured under continuous observation to link observed single-cell phenotypes with single-cell mutation data. The high sensitivity, specificity, and resolution of the data provide a unique opportunity for quantitative analysis of variation in mutation rate, spectrum, and correlations among variants. Our data show that mutations arrive with nonuniform probability across sublineages and that DNA lesion dynamics may cause strong correlations between certain mutations.

Aberrations in nuclear size and shape are commonly used to identify cancerous tissue. However, it remains unclear whether the disturbed nuclear structure directly contributes to the cancer pathology or is merely a consequence of other events occurring during tumorigenesis. Here, we show that highly invasive and proliferative breast cancer cells frequently exhibit Akt-driven lower expression of the nuclear envelope proteins lamin A/C, leading to increased nuclear deformability that permits enhanced cell migration through confined environments that mimic interstitial spaces encountered during metastasis. Importantly, increasing

Aberrations in nuclear size and shape are commonly used to identify cancerous tissue. However, it remains unclear whether the disturbed nuclear structure directly contributes to the cancer pathology or is merely a consequence of other events occurring during tumorigenesis. Here, we show that highly invasive and proliferative breast cancer cells have lower expression of the nuclear envelope proteins lamin A/C, leading to increased nuclear deformability that permits enhanced cell migration through confined environments that mimic interstitial spaces encountered during metastasis. Importantly, increasing lamin A/C expression in highly invasive breast cancer cells altered expression of numerous other proteins implicated in metastatic progression. Further supporting an important role of lamins in breast cancer metastasis, analysis of lamin levels in human breast tumors revealed a significant association between lower lamin A levels and decreased disease-free survival. These findings suggest that downregulation of lamin A/C may influence both biochemical and physical properties of the cell to promote breast cancer metastatic progression.