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Abstract Circulating tumor cell clusters (CTCCs) are rare cellular events found in the blood stream of metastatic tumor patients. Despite their scarcity, they represent an increased risk for metastasis. Label-free detection methods of these events remain primarily limited to in vitro microfluidic platforms. Here, we expand on the use of confocal backscatter and fluorescence flow cytometry (BSFC) for label-free detection of CTCCs in whole blood using machine learning for peak detection/classification. BSFC uses a custom-built flow cytometer with three excitation wavelengths (405 nm, 488 nm, and 633 nm) and five detectors to detect CTCCs in whole blood based on corresponding scattering and fluorescence signals. In this study, detection of CTCC-associated GFP fluorescence is used as the ground truth to assess the accuracy of endogenous back-scattered light-based CTCC detection in whole blood. Using a machine learning model for peak detection/classification, we demonstrated that the combined use of backscattered signals at the three wavelengths enable detection of ~ 93% of all CTCCs larger than two cells with a purity of > 82% and an overall accuracy of > 95%. The high level of performance established through BSFC and machine learning demonstrates the potential for label-free detection and monitoring of CTCCs in whole blood. Further developments of label-free BSFC to enhance throughput could lead to important applications in the isolation of CTCCs in whole blood with minimal disruption and ultimately their detection in vivo.
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Engineering a PbrR-Based Biosensor for Cell-Free Detection of Lead at the Legal Limit
Industrialization and failing infrastructure have led to a growing number of irreversible health conditions resulting from chronic lead exposure. While state-of- the-art analytical chemistry methods provide accurate and sensitive detection of lead, they are too slow, expensive, and centralized to be accessible to many. Cell-free biosensors based on allosteric transcription factors (aTFs) can address the need for accessible, on-demand lead detection at the point of use. However, known aTFs, such as PbrR, are unable to detect lead at concentrations regulated by the Environmental Protection Agency (24−72 nM). Here, we develop a rapid cell-free platform for engineering aTF biosensors with improved sensitivity, selectivity, and dynamic range characteristics. We apply this platform to engineer PbrR mutants for a shift in limit of detection from 10 μM to 50 nM lead and demonstrate use of PbrR as a cell-free biosensor. We envision that our workflow could be applied to engineer any aTF.
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- PAR ID:
- 10550471
- Publisher / Repository:
- American Chemical Society
- Date Published:
- Journal Name:
- ACS Synthetic Biology
- Volume:
- 13
- Issue:
- 9
- ISSN:
- 2161-5063
- Page Range / eLocation ID:
- 3003 to 3012
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.1021/acssynbio.4c00456
