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  1. Article ; Online: High-Throughput, High-Multiplex Digital Protein Detection with Attomolar Sensitivity.

    Wu, Connie / Dougan, Tyler J / Walt, David R

    ACS nano

    2022  Volume 16, Issue 1, Page(s) 1025–1035

    Abstract: A major challenge in many clinical diagnostic applications is the measurement of low-abundance proteins and other biomolecules in biological fluids. Digital technologies such as the digital enzyme-linked immunosorbent assay (ELISA) have enabled 1000-fold ...

    Abstract A major challenge in many clinical diagnostic applications is the measurement of low-abundance proteins and other biomolecules in biological fluids. Digital technologies such as the digital enzyme-linked immunosorbent assay (ELISA) have enabled 1000-fold increases in sensitivity over conventional protein detection methods. However, current digital ELISA technologies still possess insufficient sensitivities for many rare protein biomarkers and require specialized instrumentation or time-consuming workflows that have limited their widespread implementation. To address these challenges, we have developed a more sensitive and streamlined digital ELISA platform, Molecular On-bead Signal Amplification for Individual Counting (MOSAIC), which attains low attomolar limits of detection, with an order of magnitude enhancement in sensitivity over these other methods. MOSAIC uses a rapid, automatable flow cytometric readout that vastly increases throughput and is easily integrated into existing laboratory infrastructure. As MOSAIC provides high sampling efficiencies for rare target molecules, assay bead number can readily be tuned to enhance signal-to-background with high measurement precision. Furthermore, the solution-based signal readout of MOSAIC expands the number of analytes that can simultaneously be measured for higher-order multiplexing with femtomolar sensitivities or below, compared with microwell- or droplet-based digital methods. As a proof of principle, we apply MOSAIC toward improving the detectability of low-abundance cytokines in saliva and ultrasensitive multiplexed measurements of eight protein analytes in plasma and saliva. The attomolar sensitivity, high throughput, and broad multiplexing abilities of MOSAIC provide highly accessible and versatile ultrasensitive capabilities that can potentially accelerate protein biomarker discovery and diagnostic testing for diverse disease applications.
    MeSH term(s) Enzyme-Linked Immunosorbent Assay/methods ; Biomarkers ; Cytokines
    Chemical Substances Biomarkers ; Cytokines
    Language English
    Publishing date 2022-01-14
    Publishing country United States
    Document type Journal Article ; Research Support, Non-U.S. Gov't ; Research Support, N.I.H., Extramural
    ISSN 1936-086X
    ISSN (online) 1936-086X
    DOI 10.1021/acsnano.1c08675
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  2. Article ; Online: Viral taxonomy derived from evolutionary genome relationships.

    Dougan, Tyler J / Quake, Stephen R

    PloS one

    2019  Volume 14, Issue 8, Page(s) e0220440

    Abstract: We describe a new genome alignment-based model for understanding the diversity of viruses based on evolutionary genetic relationships. This approach uses information theory and a physical model to determine the information shared by the genes in two ... ...

    Abstract We describe a new genome alignment-based model for understanding the diversity of viruses based on evolutionary genetic relationships. This approach uses information theory and a physical model to determine the information shared by the genes in two genomes. Pairwise comparisons of genes from the viruses are created from alignments using NCBI BLAST, and their match scores are combined to produce a metric between genomes, which is in turn used to determine a global classification using the 5,817 viruses on RefSeq. In cases where there is no measurable alignment between any genes, the method falls back to a coarser measure of genome relationship: the mutual information of 4-mer frequency. This results in a principled model which depends only on the genome sequence, which captures many interesting relationships between viral families, and which creates clusters which correlate well with both the Baltimore and ICTV classifications. The incremental computational cost of classifying a novel virus is low and therefore newly discovered viruses can be quickly identified and classified. The model goes beyond alignment-free classifications by producing a full phylogeny similar to those constructed by virologists using qualitative features, while relying only on objective genes. These results bolster the case for mathematical models in microbiology which can characterize organisms using only their genetic material and provide an independent check for phylogenies constructed by humans, considerably faster and more cheaply than less modern approaches.
    MeSH term(s) Computational Biology ; Evolution, Molecular ; Genome, Viral ; Phylogeny ; Sequence Alignment ; Viruses/genetics
    Language English
    Publishing date 2019-08-14
    Publishing country United States
    Document type Journal Article
    ISSN 1932-6203
    ISSN (online) 1932-6203
    DOI 10.1371/journal.pone.0220440
    Database MEDical Literature Analysis and Retrieval System OnLINE

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