The ASCIZ-DYNLL1 axis promotes 53BP1-dependent non-homologous end joining and PARP inhibitor sensitivity

53BP1 controls a specialized non-homologous end joining (NHEJ) pathway that is essential for adaptive immunity, yet oncogenic in BRCA1 mutant cancers. Intra-chromosomal DNA double-strand break (DSB) joining events during immunoglobulin class switch recombination (CSR) require 53BP1. However, in BRCA1 mutant cells, 53BP1 blocks homologous recombination (HR) and promotes toxic NHEJ, resulting in genomic instability. Here, we identify the protein dimerization hub—DYNLL1—as an organizer of multimeric 53BP1 complexes. DYNLL1 binding stimulates 53BP1 oligomerization, and promotes 53BP1’s recruitment to, and interaction with, DSB-associated chromatin. Consequently, DYNLL1 regulates 53BP1-dependent NHEJ: CSR is compromised upon deletion of Dynll1 or its transcriptional regulator Asciz, or by mutation of DYNLL1 binding motifs in 53BP1; furthermore, Brca1 mutant cells and tumours are rendered resistant to poly-ADP ribose polymerase (PARP) inhibitor treatments upon deletion of Dynll1 or Asciz. Thus, our results reveal a mechanism that regulates 53BP1-dependent NHEJ and the therapeutic response of BRCA1-deficient cancers

Proceedings of the 11th Annual Deep Brain Stimulation Think Tank: pushing the forefront of neuromodulation with functional network mapping, biomarkers for adaptive DBS, bioethical dilemmas, AI-guided neuromodulation, and translational advancements

The Deep Brain Stimulation (DBS) Think Tank XI was held on August 9–11, 2023 in Gainesville, Florida with the theme of “Pushing the Forefront of Neuromodulation”. The keynote speaker was Dr. Nico Dosenbach from Washington University in St. Louis, Missouri. He presented his research recently published in Nature inn a collaboration with Dr. Evan Gordon to identify and characterize the somato-cognitive action network (SCAN), which has redefined the motor homunculus and has led to new hypotheses about the integrative networks underpinning therapeutic DBS. The DBS Think Tank was founded in 2012 and provides an open platform where clinicians, engineers, and researchers (from industry and academia) can freely discuss current and emerging DBS technologies, as well as logistical and ethical issues facing the field. The group estimated that globally more than 263,000 DBS devices have been implanted for neurological and neuropsychiatric disorders. This year's meeting was focused on advances in the following areas: cutting-edge translational neuromodulation, cutting-edge physiology, advances in neuromodulation from Europe and Asia, neuroethical dilemmas, artificial intelligence and computational modeling, time scales in DBS for mood disorders, and advances in future neuromodulation devices

Optimal Entrainment of Heterogeneous Noisy Neurons

We develop a methodology to design a stimulus optimized to entrain nonlinear, noisy limit cycle oscillators with uncertain properties. Conditions are derived which guarantee that the stimulus will entrain the oscillators despite these uncertainties. Using these conditions, we develop an energy optimal control strategy to design an efficient entraining stimulus and apply it to numerical models of noisy phase oscillators and to in vitro hippocampal neurons. In both instances, the optimal stimuli outperform other similar but suboptimal entraining stimuli. Because this control strategy explicitly accounts for both noise and inherent uncertainty of model parameters, it could have experimental relevance to neural circuits where robust spike timing plays an important role

Effects of phasic stimulation with a single pulse on the population oscillation can be predicted using the PRC.

<p>Top: Population PRC, as calculated in a previous paper [<a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1005011#pcbi.1005011.ref020" target="_blank">20</a>]. Middle: Single pulse predictions determined from the slope of the PRC. Prediction of which stimulus phases will desynchronize the population oscillation (below the red line) and which will enhance the oscillation (above the red line). Bottom: Ratio of Beta (31–36 Hz) to Gamma (60–64 Hz) power as a function of the stimulus phase, shown as a percent change from stimulation off condition (red line). Stimulating early in the phase suppresses the 34 Hz oscillation, while stimulating late in the phase enhances it.</p

The phase response curve (PRC) can be used to predict the effects of phasic stimulation on the 34 Hz parkinsonian oscillation seen in the HM model.

<p>Top: PRCs estimated using, 1 (solid black) and 3 (red) stimulus pulses per cycle. Assuming each no interactions between pulses, the PRC for three pulses is predicted (dotted black) from the single pulse PRC. The difference seen between the prediction (dotted black) and the PRC etimated using 3 pulses (red) indicates there are higher order effects. Middle: Predictions from the single pulse PRC (black) and the 3 stimuli PRC (red). Stimulating at phases where the curve is below zero is predicted to desynchronize the oscillation. Bottom: Ratio of Beta (31–36 Hz) to Gamma (60–64 Hz) amplitude as a function of stimulus phase, shown as a percent change from stimulation off (black line at y = 0). Stimulating early in the phase suppresses the 34 Hz oscillation, while stimulating late in the phase enhances it. This matches with predictions made using the PRC (middle). Furthermore, 3 pulses per cycle result in a stronger modulation of the 34 Hz oscillation.</p

Rastergrams from the external globus pallidus of the Hahn & McIntyre model.

<p>Left) No stimulation, Middle) Closed-loop phasic burst stimulation at a phase which disrupts the 34 Hz oscillation (phase = 0.3); Right) Closed-loop phasic burst stimulation at a phase which enhances the 34 Hz oscillation (phase = 0.7).</p