bioRxiv Science⌕ Search

Biology subjects

Barret, S.

Publications and source records attributed to Barret, S..

2 recordsLinked to original sources

A bifunctional RNase H protein supports DNA replication and transcription in nucleus-forming Chimalliviridae phages

Jumbo bacteriophages of the Chimalliviridae family replicate their genomes within a proteinaceous phage nucleus that spatially segregates viral DNA replication and transcription from translation. While the phage nucleus protects viral DNA from host defenses, it also imposes unique constraints on genome replication and gene expression. Here we identify the phage-encoded protein Rhc (RNase H-clamp) as a central mediator of genome transactions within the phage nucleus. Using the Escherichia coli infecting bacteriophage Goslar, we show that Rhc functions as an essential component of a non-canonical three-subunit DNA polymerase complex composed of DNAPN, DNAPC and Rhc. Rhc physically interacts with the DNAPC subunit, and both the catalytic activity of Rhc's N-terminal RNase H domain and its C-terminal sliding clamp-derived DNA binding domain are required for genome replication, nuclear maturation, and productive infection. Further, Goslar Rhc also supports transcription within the phage nucleus through a function that is separable from its DNA replication function. Rhc depletion results in reduced transcription of a subset of late genes, in a pattern that suggests a role for Rhc in resolving R-loops. Imaging and cryo-electron tomography reveal that loss of Rhc arrests phage development at a nascent nuclear stage, uncoupling nuclear assembly from maturation. Together, these findings identify Rhc as a multifunctional nuclear factor that mediates both DNA replication and transcription in nucleus-forming jumbo phages, revealing how viruses repurpose a conserved enzymatic activity to coordinate gene expression within a compartmentalized replication environment.

cell biology↗

An Open-Source Deep Learning-Based GUI Toolbox For Automated Auditory Brainstem Response Analyses (ABRA)

Hearing loss is a pervasive global health challenge with profound impacts on communication, cognitive function, and quality of life. Recent studies have established age-related hearing loss as a significant risk factor for dementia, highlighting the importance of hearing loss research. Auditory brainstem responses (ABRs), which are electrophysiological recordings of acoustically evoked synchronized neural activity from the auditory nerve and brainstem, serve as in vivo correlates for sensory hair cell and synaptic function, hearing sensitivity, and other critical readouts of auditory pathway physiology, making them highly valuable for both basic neuroscience and clinical research. Despite their utility, traditional ABR analyses rely heavily on subjective manual interpretation, which may introduce variability and pose challenges for reproducibility across studies. Here, we introduce Auditory Brainstem Response Analyzer (ABRA), a novel suite of open-source ABR analysis tools powered by deep learning, which automates and standardizes ABR waveform analysis. ABRA employs convolutional neural networks trained on diverse datasets collected from multiple experimental settings, achieving rapid and unbiased extraction of key ABR metrics, including peak amplitude, latency, and auditory threshold estimates. We demonstrate that ABRAs deep learning models provide performance comparable to expert human annotators while dramatically reducing analysis time and enhancing reproducibility across datasets from different laboratories. By bridging hearing research, sensory neuroscience, and advanced computational techniques, ABRA facilitates broader interdisciplinary insights into auditory function. An online version of the tool is available for use at no cost at https://abra.ucsd.edu.

neuroscience↗