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Lemmex, A. C.

Publications and source records attributed to Lemmex, A. C..

2 recordsLinked to original sources

Programmable Antibody-DNA Conjugation via HUH-Tags Enables Quantitative Measurement of Receptor-Specific Adhesion Dynamics

Antibody-DNA oligonucleotide conjugates (AOCs) are widely used for molecular assembly and cellular analysis, yet current approaches for generating these conjugates often rely on nonspecific chemistries that produce heterogeneous products. Here, we present two complementary strategies for generating site-specific AOCs using covalent DNA-linking HUH endonucleases. In one approach, recombinant antibodies are genetically fused to HUH-tags to enable direct, site-specific DNA conjugation. In the second, off-the-shelf antibodies are indirectly linked to HUH-tags using a photocrosslinkable Protein G-HUH fusion, enabling covalent Fc-directed attachment. Both strategies yield homogeneous AOCs while preserving antigen binding affinity. We apply these conjugates to a DNA-based mechanochemical assay, termed rupture-and-deliver tension gauge tethers (RAD-TGTs), which converts receptor-mediated adhesion forces into intracellular delivery of a fluorescent oligonucleotide payload. By tuning duplex stability, we define adhesion dynamics across multiple mechanical regimes. Using HER2- and beta1-integrin-targeting AOCs, we identify receptor-specific adhesion signatures and uncover cooperative interactions between receptor systems in a panel of cancer cell lines. Dual-color probes enable multiplexed single-cell mechanical phenotyping, and application to primary NK cells reveals dose-dependent responses to integrin modulators. These results establish a generalizable platform for site-defined AOC generation and for quantitative, high-throughput measurement of receptor-mediated adhesion dynamics.

bioengineering

Accelerating structure-function mapping using the ViVa webtool to mine natural variation

Thousands of sequenced genomes are now publicly available capturing a significant amount of natural variation within plant species; yet, much of this data remains inaccessible to researchers without significant bioinformatics experience. Here, we present a webtool called ViVa (Visualizing Variation) which aims to empower any researcher to take advantage of the amazing genetic resource collected in the Arabidopsis thaliana 1001 Genomes Project (http://1001genomes.org). ViVa facilitates data mining on the gene, gene family or gene network level. To test the utility and accessibility of ViVa, we assembled a team with a range of expertise within biology and bioinformatics to analyze the natural variation within the well-studied nuclear auxin signaling pathway. Our analysis has provided further confirmation of existing knowledge and has also helped generate new hypotheses regarding this well studied pathway. These results highlight how natural variation could be used to generate and test hypotheses about less studied gene families and networks, especially when paired with biochemical and genetic characterization. ViVa is also readily extensible to databases of interspecific genetic variation in plants as well as other organisms, such as the 3,000 Rice Genomes Project (http://snp-seek.irri.org/) and human genetic variation (https://www.ncbi.nlm.nih.gov/clinvar/).

bioinformatics