Literature DB >> 31902202

Fractal LAMP: Label-Free Analysis of Fractal Precipitate for Digital Loop-Mediated Isothermal Nucleic Acid Amplification.

Hector E Muñoz1, Carson T Riche1, Janay E Kong1, Mark van Zee1, Omai B Garner2, Aydogan Ozcan1,3,4, Dino Di Carlo1,4,5.   

Abstract

Nucleic acid amplification assays including loop-mediated isothermal amplification (LAMP) are routinely used in diagnosing diseases and monitoring water and food quality. The results of amplification in these assays are commonly measured with an analog fluorescence readout, which requires specialized optical equipment and can lack quantitative precision. Digital analysis of amplification in small fluid compartments based on exceeding a threshold fluorescence level can enhance the quantitative precision of nucleic acid assays (i.e., digital nucleic acid amplification assays), but still requires specialized optical systems for fluorescence readout and the inclusion of a fluorescent dye. Here, we report Fractal LAMP, an automated method to detect amplified DNA in subnanoliter scale droplets following LAMP in a label-free manner. Our computer vision algorithm achieves high accuracy detecting DNA amplification in droplets by identifying LAMP byproducts that form fractal structures observable in brightfield microscopy. The capabilities of Fractal LAMP are further realized by developing a Bayesian model to estimate DNA concentrations for unknown samples and a bootstrapping method to estimate the number of droplets required to achieve target limits of detection. This digital, label-free assay has the potential to lower reagent and reader cost for nucleic acid measurement while maintaining high quantitative accuracy over 3 orders of magnitude of concentration.

Keywords:  Bayesian model; bootstrapping; digital analysis; fractal LAMP; nucleic acid amplification test

Year:  2020        PMID: 31902202     DOI: 10.1021/acssensors.9b01974

Source DB:  PubMed          Journal:  ACS Sens        ISSN: 2379-3694            Impact factor:   7.711


  4 in total

1.  Multiplex Digital MicroRNA Detection Using Cross-Inhibitory DNA Circuits.

Authors:  Yannick Rondelez; Guillaume Gines
Journal:  ACS Sens       Date:  2020-07-25       Impact factor: 7.711

2.  Deep-dLAMP: Deep Learning-Enabled Polydisperse Emulsion-Based Digital Loop-Mediated Isothermal Amplification.

Authors:  Linzhe Chen; Jingyi Ding; Hao Yuan; Chi Chen; Zida Li
Journal:  Adv Sci (Weinh)       Date:  2022-01-24       Impact factor: 16.806

Review 3.  Recent advances in detection technologies for COVID-19.

Authors:  Tingting Han; Hailin Cong; Youqing Shen; Bing Yu
Journal:  Talanta       Date:  2021-06-12       Impact factor: 6.057

4.  High-throughput selection of cells based on accumulated growth and division using PicoShell particles.

Authors:  Mark van Zee; Joseph de Rutte; Rose Rumyan; Cayden Williamson; Trevor Burnes; Randor Radakovits; Andrew Sonico Eugenio; Sara Badih; Sohyung Lee; Dong-Hyun Lee; Maani Archang; Dino Di Carlo
Journal:  Proc Natl Acad Sci U S A       Date:  2022-01-25       Impact factor: 12.779

  4 in total

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