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  1. Abstract Numerous intra- and inter-chromosomal contacts have been mapped in eukaryotic genomes, but it remains challenging to link these 3D structures to their regulatory functions. To establish the causal relationships between chromosome conformation and genome functions, we  develop a method, Chemically Induced Chromosomal Interaction (CICI), to selectively perturb the chromosome conformation at targeted loci. Using this method, long-distance chromosomal interactions can be induced dynamically between intra- or inter-chromosomal loci pairs, including the ones with very low Hi-C contact frequencies. Measurement of CICI formation time allows us to probe chromosome encounter dynamics between different loci pairs across the cell cycle. Wemore »also conduct two functional tests of CICI. We perturb the chromosome conformation near a DNA double-strand break and observe altered donor preference in homologous recombination; we force interactions between early and late-firing DNA replication origins and find no significant changes in replication timing. These results suggest that chromosome conformation plays a deterministic role in homology-directed DNA repair, but not in the establishment of replication timing. Overall, our study demonstrates that CICI is a powerful tool to study chromosome dynamics and 3D genome function.« less
    Free, publicly-accessible full text available December 1, 2023
  2. Abstract Two common hemoglobinopathies, sickle cell disease (SCD) and β-thalassemia, arise from genetic mutations within the β-globin gene. In this work, we identified a 500-bp motif (Fetal Chromatin Domain, FCD) upstream of human ϒ-globin locus and showed that the removal of this motif using CRISPR technology reactivates the expression of ϒ-globin. Next, we present two different cell morphology-based machine learning approaches that can be used identify human blood cells (KU-812) that harbor CRISPR-mediated FCD genetic modifications. Three candidate models from the first approach, which uses multilayer perceptron algorithm (MLP 20-26, MLP26-18, and MLP 30-26) and flow cytometry-derived cellular data, yieldedmore »0.83 precision, 0.80 recall, 0.82 accuracy, and 0.90 area under the ROC (receiver operating characteristic) curve when predicting the edited cells. In comparison, the candidate model from the second approach, which uses deep learning (T2D5) and DIC microscopy-derived imaging data, performed with less accuracy (0.80) and ROC AUC (0.87). We envision that equivalent machine learning-based models can complement currently available genotyping protocols for specific genetic modifications which result in morphological changes in human cells.« less
    Free, publicly-accessible full text available December 1, 2023
  3. Free, publicly-accessible full text available July 11, 2023
  4. CRISPR-engineered physical unclonable functions establish a foundational security technology for provenance attestation protocols.
    Free, publicly-accessible full text available May 6, 2023
  5. Free, publicly-accessible full text available July 13, 2023
  6. Atomically dispersed and nitrogen-coordinated single Ni sites ( i.e. , NiN x moieties) embedded in partially graphitized carbon have emerged as effective catalysts for CO 2 electroreduction to CO. However, much mystery remains behind the extrinsic and intrinsic factors that govern the overall catalytic CO 2 electrolysis performance. Here, we designed a high-performance single Ni site catalyst through elucidating the structural evolution of NiN x sites during thermal activation and other critical external factors ( e.g. , carbon particle sizes and Ni content) by using Ni–N–C model catalysts derived from nitrogen-doped carbon carbonized from a zeolitic imidazolate framework (ZIF)-8. Themore »N coordination, metal–N bond length, and thermal wrinkling of carbon planes in Ni–N–C catalysts significantly depend on thermal temperatures. Density functional theory (DFT) calculations reveal that the shortening Ni–N bonds in compressively strained NiN 4 sites could intrinsically enhance the CO 2 RR activity and selectivity of the Ni–N–C catalyst. Notably, the NiN 3 active sites with optimal local structures formed at higher temperatures ( e.g. , 1200 °C) are intrinsically more active and CO selective than NiN 4 , providing a new opportunity to design a highly active catalyst via populating NiN 3 sites with increased density. We also studied how morphological factors such as the carbon host particle size and Ni loading alter the final catalyst structure and performance. The implementation of this catalyst in an industrial flow-cell electrolyzer demonstrated an impressive performance for CO generation, achieving a current density of CO up to 726 mA cm −2 with faradaic efficiency of CO above 90%, representing one of the best catalysts for CO 2 reduction to CO.« less
    Free, publicly-accessible full text available May 18, 2023
  7. Free, publicly-accessible full text available March 1, 2023
  8. Free, publicly-accessible full text available April 1, 2023
  9. Pham, Khanh D. ; Chen, Genshe (Ed.)
    Free, publicly-accessible full text available January 1, 2023
  10. Free, publicly-accessible full text available December 14, 2022