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Simultaneous time-varying viscosity, elasticity, and mass measurements of single adherent cancer cells across cell cycle.

ABSTRACT: Biophysical studies on single cells have linked cell mechanics to physiology, functionality and disease. Evaluation of mass and viscoelasticity versus cell cycle can provide further insights into cell cycle progression and the uncontrolled proliferation of cancer. Using our pedestal microelectromechanical systems resonant sensors, we have developed a non-contact interferometric measurement technique that simultaneously tracks the dynamic changes in the viscoelastic moduli and mass of adherent colon (HT-29) and breast cancer (MCF-7) cells from the interphase through mitosis and then to the cytokinesis stages of their growth cycle. We show that by combining three optomechanical parameters in an optical path length equation and a two-degree-of-freedom model, we can simultaneously extract the viscoelasticity and mass as a function of the nano-scaled membrane fluctuation of each adherent cell. Our measurements are able to discern between soft and stiff cells across the cell cycle and demonstrated sharp viscoelastic changes due to cortical stiffening around mitosis. Cell rounding before division can be detected by measurement of mechanical coupling between the cells and the sensors. Our measurement device and method can provide for new insights into the mechanics of single adherent cells versus time.

SUBMITTER: Adeniba OO

PROVIDER: S-EPMC7393350 | biostudies-literature | 2020 Jul

REPOSITORIES: biostudies-literature

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Simultaneous time-varying viscosity, elasticity, and mass measurements of single adherent cancer cells across cell cycle.

Adeniba Olaoluwa O OO Corbin Elise A EA Ganguli Anurup A Kim Yongdeok Y Bashir Rashid R

Scientific reports 20200730 1

Biophysical studies on single cells have linked cell mechanics to physiology, functionality and disease. Evaluation of mass and viscoelasticity versus cell cycle can provide further insights into cell cycle progression and the uncontrolled proliferation of cancer. Using our pedestal microelectromechanical systems resonant sensors, we have developed a non-contact interferometric measurement technique that simultaneously tracks the dynamic changes in the viscoelastic moduli and mass of adherent co ...[more]

PMID: 32733047

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Project description:BackgroundBiochemical networks are often described through static or time-averaged measurements of the component macromolecules. Temporal variation in these components plays an important role in both describing the dynamical nature of the network as well as providing insights into causal mechanisms. Few methods exist, specifically for systems with many variables, for analyzing time series data to identify distinct temporal regimes and the corresponding time-varying causal networks and mechanisms.ResultsIn this study, we use well-constructed temporal transcriptional measurements in a mammalian cell during a cell cycle, to identify dynamical networks and mechanisms describing the cell cycle. The methods we have used and developed in part deal with Granger causality, Vector Autoregression, Estimation Stability with Cross Validation and a nonparametric change point detection algorithm that enable estimating temporally evolving directed networks that provide a comprehensive picture of the crosstalk among different molecular components. We applied our approach to RNA-seq time-course data spanning nearly two cell cycles from Mouse Embryonic Fibroblast (MEF) primary cells. The change-point detection algorithm is able to extract precise information on the duration and timing of cell cycle phases. Using Least Absolute Shrinkage and Selection Operator (LASSO) and Estimation Stability with Cross Validation (ES-CV), we were able to, without any prior biological knowledge, extract information on the phase-specific causal interaction of cell cycle genes, as well as temporal interdependencies of biological mechanisms through a complete cell cycle.ConclusionsThe temporal dependence of cellular components we provide in our model goes beyond what is known in the literature. Furthermore, our inference of dynamic interplay of multiple intracellular mechanisms and their temporal dependence on one another can be used to predict time-varying cellular responses, and provide insight on the design of precise experiments for modulating the regulation of the cell cycle.

Project description:We introduce a microfluidic platform that enables single-cell mass and growth rate measurements upstream of single-cell RNA-sequencing (scRNA-seq) to generate paired single-cell biophysical and transcriptional data sets. Biophysical measurements are collected with a serial suspended microchannel resonator platform (sSMR) that utilizes automated fluidic state switching to load individual cells at fixed intervals, achieving a throughput of 120 cells per hour. Each single-cell is subsequently captured downstream for linked molecular analysis using an automated collection system. From linked measurements of a murine leukemia (L1210) and pro-B cell line (FL5.12), we identify gene expression signatures that correlate significantly with cell mass and growth rate. In particular, we find that both cell lines display a cell-cycle signature that correlates with cell mass, with early and late cell-cycle signatures significantly enriched amongst genes with negative and positive correlations with mass, respectively. FL5.12 cells also show a significant correlation between single-cell growth efficiency and a G1-S transition signature, providing additional transcriptional evidence for a phenomenon previously observed through biophysical measurements alone. Importantly, the throughput and speed of our platform allows for the characterization of phenotypes in dynamic cellular systems. As a proof-of principle, we apply our system to characterize activated murine CD8+ T cells and uncover two unique features of CD8+ T cells as they become proliferative in response to activation: i) the level of coordination between cell cycle gene expression and cell mass increases, and ii) translation-related gene expression increases and shows a correlation with single-cell growth efficiency. Overall, our approach provides a new means of characterizing the transcriptional mechanisms of normal and dysfunctional cellular mass and growth rate regulation across a range of biological contexts.

Project description:STUDY QUESTION:Does ambient air pollution affect fecundability? SUMMARY ANSWER:While cycle-average air pollution exposure was not associated with fecundability, we observed some associations for acute exposure around ovulation and implantation with fecundability. WHAT IS KNOWN ALREADY:Ambient air pollution exposure has been associated with adverse pregnancy outcomes and decrements in semen quality. STUDY DESIGN, SIZE, DURATION:The LIFE study (2005-2009), a prospective time-to-pregnancy study, enrolled 501 couples who were followed for up to one year of attempting pregnancy. PARTICIPANTS/MATERIALS, SETTING, METHODS:Average air pollutant exposure was assessed for the menstrual cycle before and during the proliferative phase of each observed cycle (n = 500 couples; n = 2360 cycles) and daily acute exposure was assessed for sensitive windows of each observed cycle (n = 440 couples; n = 1897 cycles). Discrete-time survival analysis modeled the association between fecundability and an interquartile range increase in each pollutant, adjusting for co-pollutants, site, age, race/ethnicity, parity, body mass index, smoking, income and education. MAIN RESULTS AND THE ROLE OF CHANCE:Cycle-average air pollutant exposure was not associated with fecundability. In acute models, fecundability was diminished with exposure to ozone the day before ovulation and nitrogen oxides 8 days post ovulation (fecundability odds ratio [FOR] 0.83, 95% confidence interval [CI]: 0.72, 0.96 and FOR 0.84, 95% CI: 0.71, 0.99, respectively). However, particulate matter ≤10 microns 6 days post ovulation was associated with greater fecundability (FOR 1.25, 95% CI: 1.01, 1.54). LIMITATIONS, REASONS FOR CAUTION:Although our study was unlikely to be biased due to confounding, misclassification of air pollution exposure and the moderate study size may have limited our ability to detect an association between ambient air pollution and fecundability. WIDER IMPLICATIONS OF THE FINDINGS:While no associations were observed for cycle-average ambient air pollution exposure, consistent with past research in the United States, exposure during critical windows of hormonal variability was associated with prospectively measured couple fecundability, warranting further investigation. STUDY FUNDING/COMPETING INTEREST(S):This work was supported by the Intramural Research Program of the Eunice Kennedy Shriver National Institute of Child Health and Human Development (Longitudinal Investigation of Fertility and the Environment study contract nos. #N01-HD-3-3355, NO1-HD-#-3356, N01-HD-3-3358 and the Air Quality and Reproductive Health Study Contract No. HHSN275200800002I, Task Order No. HHSN27500008). We declare no conflict of interest.

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Simultaneous time-varying viscosity, elasticity, and mass measurements of single adherent cancer cells across cell cycle.

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Simultaneous time-varying viscosity, elasticity, and mass measurements of single adherent cancer cells across cell cycle.

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