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Biology subjects

Lemmex, A. C.

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

4 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↗

Sequence-directed covalent protein-RNA linkages using engineered HUH-Tags

Replication-initiating HUH-endonucleases (Reps) are enzymes that form covalent bonds with single-stranded DNA (ssDNA) in a sequence specific manner to initiate rolling circle replication. These nucleases have been co-opted for use in biotechnology as sequence specific protein-ssDNA bioconjugation fusion partners dubbed HUH-tags. Here, we describe the engineering and in vitro characterization of a series of laboratory evolved HUH-tags capable of forming robust sequence-directed covalent bonds with unmodified RNA substrates. We show that promiscuous Rep-RNA interaction can be enhanced through directed evolution from nearly undetectable levels in wildtype enzymes to robust reactivity in final engineered iterations. Taken together, these engineered HUH-tags represent a promising platform for enabling site-specific protein-RNA covalent bioconjugation in vitro, potentially mediating a host of new applications and offering a valuable addition to the HUH-tag repertoire.

biochemistry↗

HUHgle: An Interactive Substrate Design Tool for Covalent Protein-ssDNA Labeling Using HUH-tags

HUH-tags have emerged as versatile fusion partners that mediate sequence specific protein-ssDNA bioconjugation through a simple and efficient reaction. Here we present HUHgle, a python-based interactive tool for the visualization, design, and optimization of substrates for HUH-tag mediated covalent labeling of proteins of interest with ssDNA substrates of interest. HUHgle streamlines design processes by integrating an intuitive plotting interface with a search function capable of predicting and displaying protein-ssDNA bioconjugate formation efficiency and specificity in proposed HUH-tag/ssDNA sequence combinations. Validation demonstrates that HUHgle accurately predicts product formation of HUH-tag mediated bioconjugation for single- and orthogonal-labeling reactions. In order to maximize the accessibility and utility of HUHgle, we have implemented it as a user-friendly Google Colab notebook which facilitates broad use of this tool, regardless of coding expertise. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=130 SRC="FIGDIR/small/585203v1_ufig1.gif" ALT="Figure 1"> View larger version (30K): org.highwire.dtl.DTLVardef@1a1bbforg.highwire.dtl.DTLVardef@13d218org.highwire.dtl.DTLVardef@146478corg.highwire.dtl.DTLVardef@1034a6b_HPS_FORMAT_FIGEXP M_FIG C_FIG

bioinformatics↗

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↗