Biology subjects

Gifford, R.

Publications and source records attributed to Gifford, R..

5 recordsLinked to original sources

bioRxiv2026

Neuronal Population Effects of Ketamine on Human Brain Organoids

Ketamines rapid neuropsychiatric actions emerge from interactions that span receptors, cells, and circuits, but their net effects on human neuronal population dynamics remain incompletely defined. Here we combine human dorsal forebrain organoids with high-density microelectrode arrays (MEAs) to quantify ketamines effects from spikes to networks. In 6-month-old organoids, acute ketamine (20{square}g/mL) abolished population bursting while neuronal firing continued mostly unchanged. Spike sorting revealed that mean firing rates declined but not silenced after ketamine Reductions were concentrated within a subset of burst-driver units previously defined as "backbone". Functional connectivity, estimated with the spike time tiling coefficient (STTC), decreased globally after ketamine. Backbone units displayed elevated connectivity at baseline but were functionally disconnected by ketamine. Graph construction from STTC uncovered widespread network reconfiguration, characterized by redistribution of edges from backbone to non-backbone units leading to loss of hubs and less-interconnected communities. Re-exposure after chronic ketamine treatment no longer silenced population bursting, indicating tolerance. Together, these results show that ketamine acutely silences human organoid networks by disconnecting backbone units, while chronic exposure induces tolerance to re-silencing while reducing the number of backbone units and leaving the network less active and less connected. The organoid-MEA platform provides a scalable, human-relevant system for dissecting circuit-level drug effects.

neuroscience↗

bioRxiv2025

MatClassRSA v2 release: A MATLAB toolbox for M/EEG classification, proximity matrix construction, and visualization

MatClassRSA is a MATLAB toolbox that performs magnetoen-cephalography and electroencephalography (M/EEG) classification and other analyses related to Representational Similarity Analysis (RSA). The toolbox is designed for cognitive neuroscience researchers who wish to perform classification-based decoding analyses of their data--often repeated trials of evoked responses--or derive Representational Dissimilarity Matrices (RDMs) as input to RSA. Organized as a collection of usercalled functions, MatClassRSA v2 comprises five main modules: Preprocessing, Reliability, Classification, RDM Computation, and Visualization. The Classification module supports multiple classifiers (LDA, RF, SVM) and classification schemes (e.g., multiclass, pairwise, cross-validated, train-test, hyperparameter optimization) and offers basic statistical analyses via permutation testing. Functions in other modules include, for example, trial-averaging and noise normalization; reliability estimation; non-classification RDM construction; and hierarchical and non-hierarchical clustering visualizations. The toolbox is freely available on GitHub under an MIT license and includes the main codebase, a User Manual, example function calls, and illustrative analyses. This preprint provides a general background of M/EEG classification for RSA as well as a narrative overview of the v2 MatClassRSA release, its updated functionalities, and illustrative analyses performed using the toolbox.

neuroscience↗

bioRxiv2025

Identifying genomic surveillance gaps in Africa for the global public health response to West Nile Virus

BackgroundWest Nile Virus (WNV) is a zoonotic flavivirus of significant One Health relevance and is classified as a priority pathogen with a high-risk of causing public health emergencies of global concern. WNV is endemic to Africa; however, the availability of genomic sequences from the continent remains limited. MethodsWe review the extent of polymerase chain reaction testing and genomic sequencing of WNV conducted across Africa. Using phylogeographic methods, we map the spatiotemporal spread of the virus across the continent and globally. FindingsOur study shows that WNV has been detected in 39 African countries (including Comoros, Seychelles, and Mauritius), the Canary Islands, and Reunion Island. Publications including molecular data originate from 24 countries; however, genomic sequences are publicly available for only 16 countries. We identify regions with detected viral circulation but lacking molecular surveillance. Further, we list such regions that overlap with Key Biodiversity Areas (sites harbouring significant bird diversity) as they may host high viral circulation, and high human population density that may be susceptible to spillover. InterpretationWe recognise significant knowledge gaps on the true disease burden, molecular epidemiology, and distribution of WNV in Africa. Addressing these gaps requires an integrated One Health surveillance approach which is challenging to establish. We propose three key surveillance needs as potential starting points to improve our understanding of the virus in Africa to strengthen the global public health response to this disease. FundingRockefeller Foundation, the National Institute of Health USA, Institute of Human Virology Nigeria, Global Health EDCTP3 Joint Undertaking, the Health Emergency Preparedness and Response Umbrella Program, managed by the World Bank Group, the Medical Research Foundation, and the Wellcome Trust.

molecular biology↗

bioRxiv2022

Co-option of endogenous retroviruses through genetic escape from TRIM28 repression

Endogenous retroviruses (ERVs) have rewired host gene networks through co-option of their enhancers. To explore which ERVs get co-opted and why, we tracked the epigenetic fate of murine IAPEz elements using an in vitro model of embryonic stem cell (ESC) to neural progenitor cell (NPC) differentiation. TRIM28-repression depended on a 190bp sequence, previously shown to confer IAPEzs with retrotransposition activity. A subset of IAPEzs ([~]15%) exhibit genetic divergence from this sequence, which we term escapees. While repressed IAPEzs succumb to a previously undocumented epigenetic handover from H3K9me3 in ESCs to H3K27me3 in NPCs, escapee IAPEzs evade repression, resulting in their transcriptional derepression in NPCs. Escapee IAPEzs enhance expression of nearby neural genes and contribute to gene expression differences between mouse strains, which we discern by employing IAPEz insertion polymorphisms. In sum, co-opted ERVs stem from genetic escapees that have lost vital sequences required for both TRIM28 restriction and autonomous retrotransposition. HIGHLIGHTSO_LITracking the epigenetic fate of ERVs through neural differentiation reveals which ERVs are subject to co-option and why. C_LIO_LIMost ERVs succumb to H3K9me3 deposition in ESCs with H3K27me3 memory in NPCs. C_LIO_LIERVs that act as enhancers to nearby neural genes have undergone genetic escape from TRIM28 repression. C_LIO_LIEpigenetic evasion is an evolutionary trade-off that comes with loss of sequences necessary for retrotransposition. C_LI O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=130 SRC="FIGDIR/small/497016v1_ufig1.gif" ALT="Figure 1"> View larger version (21K): org.highwire.dtl.DTLVardef@175b6c0org.highwire.dtl.DTLVardef@1313692org.highwire.dtl.DTLVardef@1f5e33forg.highwire.dtl.DTLVardef@1a5ad3_HPS_FORMAT_FIGEXP M_FIG O_FLOATNOGraphical abstract.C_FLOATNO C_FIG

molecular biology↗

bioRxiv2021

Emergence of compensatory mutations reveal the importance of electrostatic interactions between HIV-1 integrase and genomic RNA

ABSTRACTHIV-1 integrase (IN) has a non-catalytic function in virion maturation through its binding to the viral RNA genome (gRNA). Allosteric integrase inhibitors (ALLINIs) and class II IN substitutions inhibit IN-gRNA binding and result in non-infectious viruses marked by mislocalization of the gRNA within virions. HIV-1 IN utilizes basic residues within its C-terminal domain (CTD) to bind to the gRNA. However, the molecular nature of how these residues mediate gRNA binding and whether other regions of IN are involved remain unknown. To address this, we have isolated compensatory substitutions in the background of a class II IN mutant virus bearing R269A/K273A substitutions within the IN-CTD. We found that the nearby D256N and D270N compensatory substitutions restored the ability of IN to bind gRNA and led to the formation of mature infectious virions. Reinstating the local positive charge of the IN-CTD through individual D256R, D256K, D278R and D279R substitutions was sufficient to restore IN-RNA binding and infectivity for the IN R269A/K273A as well as the IN R262A/R263A class II mutants. Structural modeling suggested that compensatory substitutions in the D256 residue created an additional interaction interface for gRNA binding. Finally, HIV-1 IN R269A/K273A, but not IN R262A/R263A, bearing compensatory mutations was more sensitive to ALLINIs providing key genetic evidence that specific IN residues required for RNA binding also influence ALLINI activity. Taken together, our findings highlight the essential role of CTD in gRNA binding and ALLINI sensitivity, and reveal the importance of pliable electrostatic interactions between the IN- CTD and the gRNA. IMPORTANCEIn addition to its catalytic function, HIV-1 integrase (IN) binds to the viral RNA genome (gRNA) through positively charged residues within its C-terminal domain (CTD) and regulates proper virion maturation. Here we show that compensatory mutations in nearby acidic residues (i.e. D256N and D270N) restore the ability to bind gRNA for IN variants bearing substitutions in these positively charged CTD residues. Similarly, charge reversals through individual D-to-R and D-to-K substitutions at these positions enabled the respective IN mutants to bind gRNA and restore virion infectivity. Further, we show that specific residues within the IN-CTD required for RNA binding also influence sensitivity to allosteric integrase inhibitors, a class of novel IN- targeting compounds that target the non-catalytic function of IN. Taken together, our findings reveal the importance of electrostatic interactions in IN-gRNA binding and provide key evidence for a crucial role of the IN-CTD in allosteric integrase inhibitor mechanism of action.

microbiology↗