Biology subjects

Benz, A.

Publications and source records attributed to Benz, A..

6 recordsLinked to original sources

bioRxiv2025

Multifaceted Actions of Neurosteroids

Background and purposeNeurosteroids modulate neuronal function and are promising therapeutic agents for neuropsychiatric disorders. Neurosteroid analogues are approved for treating postpartum depression and are of interest in other disorders. GABA-A receptors are well characterized targets of natural neurosteroids, but other biological pathways are likely relevant to therapeutic mechanisms and/or to off-target effects. We performed hypothesis-generating in silico analyses and broad in vitro biological screens to assess the range of actions of neurosteroids analogues of varying structural attributes. Key ResultsWe employed in silico molecular similarity analysis and network pharmacology to elucidate likely targets. This analysis confirmed likely targets beyond GABA-A receptors. We then functionally screened 19 distinct neurosteroid structures across 78 targets representing interconnected signaling pathways, complemented with a limited screen of kinase activation. Results revealed unanticipated modulation of targets by neurosteroids with some structural selectivity. Many compounds-initiated androgen receptor translocation with little or no enantioselectivity. Modulation of multiple G-protein receptors was also unexpected. Conclusions and implicationsNeurosteroids are ascendant treatments in neuropsychiatry, but their full spectrum of actions remains unclear. This virtual and biological screening discovery approach opens new vistas for exploring mechanism of neurosteroids analogues. The multifaceted approach provides an unbiased, holistic exploration of the potential effects of neurosteroids across various molecular targets and provides a platform for future validation studies to aid drug discovery.

neuroscience↗

bioRxiv2024

δ-containing GABAA receptors on parvalbumin interneurons modulate neuronal excitability and network dynamics in the mouse medial prefrontal cortex

In medial prefrontal cortex (mPFC), fast-spiking parvalbumin (PV) interneurons regulate excitability and microcircuit oscillatory activity important for cognition. Although PV interneurons inhibit pyramidal neurons, they themselves express {delta} subunits of GABAA receptors important for slow inhibition. However, the specific contribution of {delta}-containing GABAA receptors to the function of PV interneurons in mPFC is unclear. We explored cellular, synaptic, and local-circuit activity in PV interneurons and pyramidal neurons in mouse mPFC after selectively deleting {delta} subunits in PV interneurons (cKO mice). In current-clamp recordings, cKO PV interneurons exhibited a higher frequency of action potentials and higher input resistance than wild type (WT) PV interneurons. Picrotoxin increased firing and GABA decreased firing in WT PV interneurons but not in cKO PV interneurons. The {delta}-preferring agonist THIP reduced spontaneous inhibitory postsynaptic currents in WT pyramidal neurons but not in cKO pyramidal neurons. In WT slices, depolarizing the network with 400 nM kainate increased firing of pyramidal neurons but had little effect on PV interneuron firing. By contrast, in cKO slices kainate recruited PV interneurons at the expense of pyramidal neurons. At the population level, kainate induced broadband increases in local field potentials in WT but not cKO slices. These results on cells and the network can be understood through increased excitability of cKO PV interneurons. In summary, our study demonstrates that {delta}-containing GABAA receptors in mPFC PV interneurons play a crucial role in regulating their excitability and the phasic inhibition of pyramidal neurons, elucidating intricate mechanisms governing cortical circuitry. Significance statementBy selectively deleting {delta}-containing GABAA receptors in PV interneurons, we demonstrate the importance of these receptors on PV interneuron excitability, synaptic inhibition of pyramidal neurons, and circuit function.

neuroscience↗

bioRxiv2024

AAnet resolves a continuum of spatially-localized cell states to unveil tumor complexity

Identifying functionally important cell states and structure within a heterogeneous tumor remains a significant biological and computational challenge. Moreover, current clustering or trajectory-based computational models are ill-equipped to address the notion that cancer cells reside along a phenotypic continuum. To address this, we present Archetypal Analysis network (AAnet), a neural network that learns key archetypal cell states within a phenotypic continuum of cell states in single-cell data. Applied to single-cell RNA sequencing data from pre-clinical models and a cohort of 34 clinical breast cancers, AAnet identifies archetypes that resolve distinct biological cell states and processes, including cell proliferation, hypoxia, metabolism and immune interactions. Notably, archetypes identified in primary tumors are recapitulated in matched liver, lung and lymph node metastases, demonstrating that a significant component of intratumoral heterogeneity is driven by cell intrinsic properties. Using spatial transcriptomics as orthogonal validation, AAnet-derived archetypes show discrete spatial organization within tumors, supporting their distinct archetypal biology. We further reveal that ligand:receptor cross-talk between cancer and adjacent stromal cells contributes to intra-archetypal biological mimicry. Finally, we use AAnet archetype identifiers to validate GLUT3 as a critical mediator of a hypoxic cell archetype harboring a cancer stem cell population, which we validate in human triple-negative breast cancer specimens. AAnet is a powerful tool to reveal functional cell states within complex samples from multimodal single-cell data.

bioinformatics↗

bioRxiv2024

A role for δ subunit-containing GABA-A receptors on parvalbumin positive neurons in maintaining electrocortical signatures of sleep states

GABAA receptors containing {delta} subunits have been shown to mediate tonic/slow inhibition in the CNS. These receptors are typically found extrasynaptically and are activated by relatively low levels of ambient GABA in the extracellular space. In the mouse neocortex, {delta} subunits are expressed on the surface of some pyramidal cells as well as on parvalbumin positive (PV+) interneurons. An important function of PV+ interneurons is the organization of coordinated network activity that can be measured by EEG; however, it remains unclear what role tonic/slow inhibitory control of PV+ neurons may play in shaping oscillatory activity. After confirming a loss of functional {delta} mediated tonic currents in PV cells in cortical slices from mice lacking Gabrd in PV+ neurons (PV {delta}cKO), we performed EEG recordings to survey network activity across wake and sleep states. PV {delta}cKO mice showed altered spectral content of EEG during NREM and REM sleep that was a result of increased oscillatory activity in NREM and the emergence of transient high amplitude bursts of theta frequency activity during REM. Viral reintroduction of Gabrd to PV+ interneurons in PV {delta}cKO mice rescued REM EEG phenotypes, supporting an important role for {delta} subunit mediated inhibition of PV+ interneurons for maintaining normal REM cortical oscillations. Significance statementThe impact on cortical EEG of inhibition on PV+ neurons was studied by deleting a GABAA receptor subunit selectively from these neurons. We discovered unexpected changes at low frequencies during sleep that were rescued by viral reintroduction.

neuroscience↗

bioRxiv2023

Periodic and aperiodic changes to cortical EEG in response to pharmacological manipulation

Cortical electroencephalograms (EEG) may help understanding of neuropsychiatric illness and new treatment mechanisms. The aperiodic component (1/f) of EEG power spectra is often treated as noise, but recent studies suggest that changes to the aperiodic exponent of power spectra may reflect changes in excitation/inhibition (E/I) balance, a concept linked to antidepressant effects, epilepsy, autism, and other clinical conditions. One confound of previous studies is behavioral state, because factors associated with behavioral state other than E/I ratio may alter EEG parameters. Thus, to test the robustness of the aperiodic exponent as a predictor of E/I ratio, we analyzed active exploration in mice using video EEG following various pharmacological manipulations with the Fitting Oscillations & One Over F (FOOOF) algorithm. We found that GABAA receptor (GABAAR) positive allosteric modulators increased the aperiodic exponent, consistent with the hypothesis that an increased exponent signals enhanced cortical inhibition, but other drugs (ketamine and GABAAR antagonists at sub-convulsive doses) did not follow the prediction. To tilt E/I ratio more selectively toward excitation, we suppressed the activity of parvalbumin (PV) interneurons with Designer Receptors Exclusively Activated by Designer Drugs (DREADDs). Contrary to our expectations and studies demonstrating increased cortical activity following PV suppression, circuit disinhibition with the DREADD increased the aperiodic exponent. We conclude that the aperiodic exponent of EEG power spectra does not yield a universally reliable marker of E/I ratio. Alternatively, the concept of E/I state may be sufficiently oversimplified that it cannot be mapped readily onto an EEG parameter. Significance StateBmentNeuropsychiatric illness is widely prevalent and debilitating. Causes are not well understood, but some hypotheses point toward altered excitation/inhibition (E/I) balance. Here, we use cortical electroencephalograms (EEG) in mice, given applicability of cortical EEG across species, and evaluate the impact of validated drugs, including anxiolytics (pentobarbital and diazepam), along with novel rapid-acting antidepressants (ketamine and allopregnanolone). We focus on analyzing the aperiodic component of EEG power spectra, which may be associated with changes in E/I ratio. We show that aperiodic exponent of EEG power spectra is not a reliable marker of E/I ratio. Moreover, the concept of E/I ratio may be too broad and complex to be defined by an EEG parameter.

neuroscience↗

bioRxiv2022

Temporal PHATE: A multi-view manifold learningmethod for brain state trajectories

1The complexity and intelligence of the brain give the illusion that measurements of brain activity will have intractably high dimensionality, rife with collection and biological noise. Nonlinear dimensionality reduction methods like UMAP and t-SNE have proven useful for high-throughput biomedical data. However, they have not been used extensively for brain imaging data such as from functional magnetic resonance imaging (fMRI), a noninvasive, secondary measure of neural activity over time containing redundancy and co-modulation from neural population activity. Here we introduce a nonlinear manifold learning algorithm for timeseries data like fMRI, called temporal potential of heat-diffusion for affinity-based transition embedding (T-PHATE). In addition to recovering a lower intrinsic dimensionality from timeseries data, T-PHATE exploits autocorrelative structure within the data to faithfully denoise dynamic signals and learn activation manifolds. We empirically validate T-PHATE on three human fMRI datasets, showing that T-PHATE significantly improves data visualization, classification, and segmentation of the data relative to several other state-of-the-art dimensionality reduction benchmarks.These notable improvements suggest many potential applications of T-PHATE to other high-dimensional datasets of temporally-diffuse processes.

neuroscience↗