Publications by authors named "L L Ozbun"

Alternative lengthening of telomeres (ALT) is a telomerase-independent and recombination-based mechanism used by approximately 15% of human cancers to maintain telomere length and to sustain proliferation. ALT-positive cells display unique features that could be exploited for tailored cancer therapies. A key limitation for the development of ALT-specific treatments is the lack of an assay to detect ALT-positive cells that is easy to perform and that can be scaled up.

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  • Restricting the histone variant CENP-A to centromeres is crucial for preventing chromosomal instability (CIN), as its mislocalization contributes to CIN across various organisms including yeast, flies, and humans.
  • A high-throughput RNAi screening in HeLa cells pinpointed key factors that maintain proper localization of overexpressed CENP-A, with histone chaperones CHAF1B and CHAF1A being significant candidates.
  • Experiments revealed that CHAF1B depletion led to CENP-A mislocalization and CIN, while DAXX, a chaperone linked to histone H3.3, exacerbated this mislocalization in CHAF1B-depleted
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The cohesin complex is central to chromatin looping, but mechanisms by which these long-range chromatin interactions are formed and persist remain unclear. We demonstrate that interactions between a transcription factor (TF) and the cohesin loader NIPBL regulate enhancer-dependent gene activity. Using mass spectrometry, genome mapping, and single-molecule tracking methods, we demonstrate that the glucocorticoid (GC) receptor (GR) interacts with NIPBL and the cohesin complex at the chromatin level, promoting loop extrusion and long-range gene regulation.

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  • Deep learning is becoming the preferred method for automatic nucleus segmentation in biological image analysis.
  • Researchers developed a pipeline to evaluate various nuclear segmentation models and training strategies using small, custom annotated datasets with augmentation.
  • Their findings suggest that techniques like transfer learning and careful tuning of training parameters can produce effective models that outperform some existing deep learning models, allowing for collaborative improvements across labs and institutions.
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One of the hallmarks of cancer is hromosome stability (CIN), which leads to aneuploidy, translocations, and other chromosome aberrations. However, in the vast majority of human tumors the molecular basis of CIN remains unknown, partly because not all genes controlling chromosome transmission have yet been identified. To address this question, we developed an experimental high-throughput imaging (HTI) siRNA assay that allows the identification of novel CIN genes.

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