Quantitative Cell Cycle Analysis Based on an Endogenous All-in-One Reporter for Cell Tracking and Classification.
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ABSTRACT:
SUBMITTER: Zerjatke T
PROVIDER: S-EPMC5464964 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Beyond the more conventional single-cell segmentation and tracking, single-cell cycle dynamics is gaining a growing interest in the field of cell biology. Thanks to sophisticated systems, such as the fluorescent ubiquitination-based cell cycle indicator (FUCCI), it is now possible to study cell proliferation, migration, changes in nuclear morphology and single cell cycle dynamics, quantitatively and in real time. In this work, we introduce FUCCItrack, an all-in-one, semi-automated software to segment, track and visualize FUCCI modified cell lines. A user-friendly complete graphical user interface is presented to record and quantitatively analyze both collective cell proliferation as well as single cell information, including migration and changes in nuclear or cell morphology as a function of cell cycle. To enable full control over the analysis, FUCCItrack also contains features for identification of errors and manual corrections.
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Project description:Background and Objectives: Digital health and personalized medicine are advancing at an unprecedented pace. Users can document their menstrual cycle data in a variety of ways, including smartphone applications (apps), temperature tracking devices, and at-home urine hormone tests. Understanding the needs and goals of women using menstrual cycle tracking technologies is the first step to making these technologies more evidence based. The purpose of this study was to examine the current use of these technologies and explore how they are being used within the context of common hormonal and reproductive disorders, like polycystic ovary syndrome (PCOS), endometriosis, and infertility. Materials and Methods: This was a cross-sectional study evaluating menstrual cycle tracking technology use. Participants were recruited in January-March 2023 using social media groups and a Marquette Method instructor email listserv. Data were collected using an electronic survey with Qualtrics. Data collected included participant demographics, menstrual cycle characteristics, reproductive health history, and menstrual cycle tracking behavior. Results: Three-hundred and sixty-eight participants were included in the analysis. Women had various motivations for tracking their menstrual cycles. Most participants (72.8%) selected "to avoid getting pregnant" as the primary motivation. Three hundred and fifty-six participants (96.7%) reported using a fertility awareness-based method to track and interpret their menstrual cycle data. The Marquette Method, which utilizes urine hormone tracking, was the most frequently used method (n = 274, 68.2%). The most frequently used cycle technology was a urine hormone test or monitor (n = 299, 81.3%), followed by a smartphone app (n = 253, 68.8%), and a temperature tracking device (n = 116, 31.5%). Women with PCOS (63.6%), endometriosis (61.8%), and infertility (75%) in our study reported that the use of tracking technologies aided in the diagnosis. Most participants (87.2%) reported a high degree of satisfaction with their use and that they contributed to their reproductive health knowledge (73.9%). Conclusions: Women in our study reported avoiding pregnancy as their primary motivation for using menstrual cycle tracking technologies, with the most frequently used being a urine hormone test or monitor. Our study results emphasize the need to validate these technologies to support their use for family planning. Given that most women in this study reported using a fertility awareness-based method, the results cannot be generalized to all users of menstrual cycle tracking technologies.
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Project description:Cell behaviors are reflections of intracellular tension dynamics and play important roles in many cellular processes. In this study, temporal variations in cell geometry and cell motion through cell cycle progression were quantitatively characterized via automated cell tracking for MCF-10A non-transformed breast cells, MCF-7 non-invasive breast cancer cells, and MDA-MB-231 highly metastatic breast cancer cells. A new cell segmentation method, which combines the threshold method and our modified edge based active contour method, was applied to optimize cell boundary detection for all cells in the field-of-view. An automated cell-tracking program was implemented to conduct live cell tracking over 40 hours for the three cell lines. The cell boundary and location information was measured and aligned with cell cycle progression with constructed cell lineage trees. Cell behaviors were studied in terms of cell geometry and cell motion. For cell geometry, cell area and cell axis ratio were investigated. For cell motion, instantaneous migration speed, cell motion type, as well as cell motion range were analyzed. We applied a cell-based approach that allows us to examine and compare temporal variations of cell behavior along with cell cycle progression at a single cell level. Cell body geometry along with distribution of peripheral protrusion structures appears to be associated with cell motion features. Migration speed together with motion type and motion ranges are required to distinguish the three cell-lines examined. We found that cells dividing or overlapping vertically are unique features of cell malignancy for both MCF-7 and MDA-MB-231 cells, whereas abrupt changes in cell body geometry and cell motion during mitosis are unique to highly metastatic MDA-MB-231 cells. Taken together, our live cell tracking system serves as an invaluable tool to identify cell behaviors that are unique to malignant and/or highly metastatic breast cancer cells.
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Project description:Transcriptional dynamics of cancer cells govern cell fate decisions and are therapeutically actionable drug targets. In this study, we engineered a circulating cancer cell line that secretes a luciferase reporter to capture constitutive and circadian clock-driven transcription dynamics over the course of a day. Engineered human leukemic T cells (Jurkat) were observed to rhythmically secrete luciferase in a continuous flow cell culture system. When transplanted in vivo, engineered leukemic cells caused circadian plasma luciferase activity and had expected pathological signs of leukemic disease. This technique is rapid and noninvasive, requiring only a few microliters of media or blood, and can aid in investigating relationships between in vivo cancer cell signaling and behavior, such as diet or sleep.
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Project description:The Fluorescent Ubiquitination-based Cell Cycle Indicator (FUCCI) system can be used not only to study gene expression at a specific cell cycle stage, but also to monitor cell cycle transitions in real time. In this study, we used a single clone of FUCCI-expressing HeLa cells (FUCCI-HeLa cells) and monitored the cell cycle in individual live cells over time by determining the ratios between red fluorescence (RF) of RFP-Cdt1 and green fluorescence (GF) of GFP-Geminin. Cytotoxic and cytostatic compounds, the latter of which induced G2 or mitotic arrest, were identified based on periodic cycling of the RF/GF and GF/RF ratios in FUCCI-HeLa cells treated with anti-cancer drugs. With this cell cycle monitoring system, ten flavonoids were screened. Of these, apigenin and luteolin, which have a flavone backbone, were cytotoxic, whereas kaempferol, which has a flavonol backbone, was cytostatic and induced G2 arrest. In summary, we developed a system to quantitatively monitor the cell cycle in real time. This system can be used to identify novel compounds that modulate the cell cycle and to investigate structure-activity relationships.
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