Biology subjects

Taylor, K. R.

Publications and source records attributed to Taylor, K. R..

3 recordsLinked to original sources

bioRxiv2022

Mild respiratory SARS-CoV-2 infection can cause multi-lineage cellular dysregulation and myelin loss in the brain

Survivors of Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) infection frequently experience lingering neurological symptoms, including impairment in attention, concentration, speed of information processing and memory. This long-COVID cognitive syndrome shares many features with the syndrome of cancer therapy-related cognitive impairment (CRCI). Neuroinflammation, particularly microglial reactivity and consequent dysregulation of hippocampal neurogenesis and oligodendrocyte lineage cells, is central to CRCI. We hypothesized that similar cellular mechanisms may contribute to the persistent neurological symptoms associated with even mild SARS-CoV-2 respiratory infection. Here, we explored neuroinflammation caused by mild respiratory SARS-CoV-2 infection - without neuroinvasion - and effects on hippocampal neurogenesis and the oligodendroglial lineage. Using a mouse model of mild respiratory SARS-CoV-2 infection induced by intranasal SARS-CoV-2 delivery, we found white matter-selective microglial reactivity, a pattern observed in CRCI. Human brain tissue from 9 individuals with COVID-19 or SARS-CoV-2 infection exhibits the same pattern of prominent white matter-selective microglial reactivity. In mice, pro-inflammatory CSF cytokines/chemokines were elevated for at least 7-weeks post-infection; among the chemokines demonstrating persistent elevation is CCL11, which is associated with impairments in neurogenesis and cognitive function. Humans experiencing long-COVID with cognitive symptoms (48 subjects) similarly demonstrate elevated CCL11 levels compared to those with long-COVID who lack cognitive symptoms (15 subjects). Impaired hippocampal neurogenesis, decreased oligodendrocytes and myelin loss in subcortical white matter were evident at 1 week, and persisted until at least 7 weeks, following mild respiratory SARS-CoV-2 infection in mice. Taken together, the findings presented here illustrate striking similarities between neuropathophysiology after cancer therapy and after SARS-CoV-2 infection, and elucidate cellular deficits that may contribute to lasting neurological symptoms following even mild SARS-CoV-2 infection.

neuroscience↗

bioRxiv2021

Glioma synapses recruit mechanisms of adaptive plasticity

The nervous system plays an increasingly appreciated role in the regulation of cancer. In malignant gliomas, neuronal activity drives tumor progression not only through paracrine signaling factors such as neuroligin-3 and brain-derived neurotrophic factor (BDNF)1-3, but also through electrophysiologically functional neuron-to-glioma synapses4-6. Malignant synapses are mediated by calcium-permeable AMPA (-amino-3-hydroxy-5-methyl-4-isoxazole propionic acid) receptors in both pediatric and adult high-grade gliomas4, 5, and consequent depolarization of the glioma cell membrane drives tumor proliferation4. The nervous system exhibits plasticity of both synaptic connectivity and synaptic strength, contributing to neural circuit form and functions. In health, one factor that promotes plasticity of synaptic connectivity7, 8 and strength9-13 is activity-regulated secretion of the neurotrophin BDNF. Here, we show that malignant synapses exhibit similar plasticity regulated by BDNF-TrkB (tropomyosin receptor kinase B) signaling. Signaling through the receptor TrkB14, BDNF promotes AMPA receptor trafficking to the glioma cell membrane, resulting in increased amplitude of glutamate-evoked currents in the malignant cells. This potentiation of malignant synaptic strength shares mechanistic features with the long-term potentiation (LTP)15-23 that is thought to contribute to memory and learning in the healthy brain22 24-27 28, 29. BDNF-TrkB signaling also regulates the number of neuron-to-glioma synapses. Abrogation of activity-regulated BDNF secretion from the brain microenvironment or loss of TrkB in human glioma cells exerts growth inhibitory effects in vivo and in neuron:glioma co-cultures that cannot be explained by classical growth factor signaling alone. Blocking TrkB genetically or pharmacologically abrogates these effects of BDNF on glioma synapses and substantially prolongs survival in xenograft models of pediatric glioblastoma and diffuse intrinsic pontine glioma (DIPG). Taken together, these findings indicate that BDNF-TrkB signaling promotes malignant synaptic plasticity and augments tumor progression.

neuroscience↗

bioRxiv2021

Effective gene expression prediction from sequence by integrating long-range interactions

The next phase of genome biology research requires understanding how DNA sequence encodes phenotypes, from the molecular to organismal levels. How noncoding DNA determines gene expression in different cell types is a major unsolved problem, and critical downstream applications in human genetics depend on improved solutions. Here, we report substantially improved gene expression prediction accuracy from DNA sequence through the use of a new deep learning architecture called Enformer that is able to integrate long-range interactions (up to 100 kb away) in the genome. This improvement yielded more accurate variant effect predictions on gene expression for both natural genetic variants and saturation mutagenesis measured by massively parallel reporter assays. Notably, Enformer outperformed the best team on the critical assessment of genome interpretation (CAGI5) challenge for noncoding variant interpretation with no additional training. Furthermore, Enformer learned to predict promoter-enhancer interactions directly from DNA sequence competitively with methods that take direct experimental data as input. We expect that these advances will enable more effective fine-mapping of growing human disease associations to cell-type-specific gene regulatory mechanisms and provide a framework to interpret cis-regulatory evolution. To foster these downstream applications, we have made the pre-trained Enformer model openly available, and provide pre-computed effect predictions for all common variants in the 1000 Genomes dataset. One-sentence summaryImproved noncoding variant effect prediction and candidate enhancer prioritization from a more accurate sequence to expression model driven by extended long-range interaction modelling.

genomics↗