Biology subjects

Sims, S.

Publications and source records attributed to Sims, S..

6 recordsLinked to original sources

bioRxiv2024

Gene-Dose-Dependent Reduction Fshr Expression Improves Spatial Memory Deficits in Alzheimer's Mice

Alzheimers disease (AD) is a major progressive neurodegenerative disorder of the aging population. High post-menopausal levels of the pituitary gonadotropin follicle-stimulating hormone (FSH) are strongly associated with the onset of AD, and we have shown recently that FSH directly activates the hippocampal Fshr to drive AD-like pathology and memory loss in mice. To establish a role for FSH in memory loss, we used female 3xTg;Fshr+/+, 3xTg;Fshr+/- and 3xTg;Fshr-/- mice that were either left unoperated or underwent sham surgery or ovariectomy at 8 weeks of age. Unoperated and sham-operated 3xTg;Fshr-/-mice were implanted with 17{beta}-estradiol pellets to normalize estradiol levels. Morris Water Maze and Novel Object Recognition behavioral tests were performed to study deficits in spatial and recognition memory, respectively, and to examine the effects of Fshr depletion. 3xTg;Fshr+/+mice displayed impaired spatial memory at 5 months of age; both the acquisition and retrieval of the memory were ameliorated in 3xTg;Fshr-/- mice and, to a lesser extent, in 3xTg;Fshr+/- mice-- thus documenting a clear gene-dose-dependent prevention of hippocampal-dependent spatial memory impairment. At 5 and 10 months, sham-operated 3xTg;Fshr-/- mice showed better memory performance during the acquisition and/or retrieval phases, suggesting that Fshr deletion prevented the progression of spatial memory deficits with age. However, this prevention was not seen when mice were ovariectomized, except in the 10-month-old 3xTg;Fshr-/-mice. In the Novel Object Recognition test performed at 10 months, all groups of mice, except ovariectomized 3xTg;Fshr-/- mice showed a loss of recognition memory. Consistent with the neurobehavioral data, there was a gene-dose-dependent reduction mainly in the amyloid {beta}40 isoform in whole brain extracts. Finally, serum FSH levels <8 ng/mL in 16-month-old APP/PS1 mice were associated with better retrieval of spatial memory. Collectively, the data provide compelling genetic evidence for a protective effect of inhibiting FSH signaling on the progression of spatial and recognition memory deficits in mice, and lay a firm foundation for the use of an FSH-blocking agent for the early prevention of cognitive decline in postmenopausal women.

neuroscience↗

bioRxiv2024

Plural molecular and cellular mechanisms of pore domain KCNQ2 encephalopathy

KCNQ2 variants in children with neurodevelopmental impairment are difficult to assess due to their heterogeneity and unclear pathogenic mechanisms. We describe a child with neonatal-onset epilepsy, developmental impairment of intermediate severity, and KCNQ2 G256W heterozygosity. Analyzing prior KCNQ2 channel cryoelectron microscopy models revealed G256 as a node of an arch-shaped non-covalent bond network linking S5, the pore turret, and the ion path. Co-expression with G256W dominantly suppressed conduction by wild-type subunits in heterologous cells. Ezogabine partly reversed this suppression. G256W/+ mice have epilepsy leading to premature deaths. Hippocampal CA1 pyramidal cells from G256W/+ brain slices showed hyperexcitability. G256W/+ pyramidal cell KCNQ2 and KCNQ3 immunolabeling was significantly shifted from axon initial segments to neuronal somata. Despite normal mRNA levels, G256W/+ mouse KCNQ2 protein levels were reduced by about 50%. Our findings indicate that G256W pathogenicity results from multiplicative effects, including reductions in intrinsic conduction, subcellular targeting, and protein stability. These studies provide evidence for an unexpected and novel role for the KCNQ2 pore turret and introduce a valid animal model of KCNQ2 encephalopathy. Our results, spanning structure to behavior, may be broadly applicable because the majority of KCNQ2 encephalopathy patients share variants near the selectivity filter.

neuroscience↗

bioRxiv2022

Larger and more dentated hippocampal structure is associated with better memory in the oldest-old.

Episodic memory is widely recognized as a critically important aspect of cognition that is often impacted by cognitive and brain aging. Prior work has shown that episodic memory is related to the presence of teeth-like folds on the dentate gyrus, called dentation. We hypothesized that episodic memory performance relates to overall hippocampal structure (i.e., dentation and volume) in an oldest-old cohort. We used data from the McKnight Brain Aging Registry, which consisted of cognitively healthy 85+-year-old adults. We conducted a canonical correlation analysis on 111 participants between a set of episodic memory tests and a set of characterizations of hippocampal structure. The analysis yielded a strong canonical correlation between episodic memory and hippocampal structure (r = 0.491, p = <0.001). The results suggest there is a connection between hippocampal morphology and function in the oldest-old. Our findings suggest that dentation may play an important role in relation to the individual differences observed in episodic memory performance among the oldest old and that hippocampal structure supports healthy cognitive aging. HighlightsO_LIWe characterized hippocampal dentation in a healthy oldest-old sample. C_LIO_LIHippocampal structure is related to episodic memory in healthy oldest-old adults. C_LIO_LIMemory functioning is related to both hippocampal volume and dentation. C_LI

neuroscience↗

bioRxiv2019

In vitro comparison of the internal ribosomal entry site activity from rodent hepacivirus and pegivirus

The 5 untranslated region (5 UTR) of rodent hepacivirus (RHV) and pegivirus (RPgV) contain sequence homology to the HCV type IV internal ribosome entry sites (IRES). Utilizing a monocistronic expression vector with an RNA polymerase I promoter to drive transcription we show cell-specific IRES translation and regions within the IRES required for full functionality. Focusing on RHV we further pseudotyped lentivirus with RHV and showed cell surface expression of the envelope proteins and transduction of murine hepatocytes.

microbiology↗

bioRxiv2018

Fast estimation of genetic relatedness between members of heterogeneous populations of closely related genomic variants

Many biological analysis tasks require extraction of families of genetically similar sequences from large datasets produced by Next-generation Sequencing (NGS). Such tasks include detection of viral transmissions by analysis of all genetically close pairs of sequences from viral datasets sampled from infected individuals or studying of evolution of viruses or immune repertoires by analysis of network of intra-host viral variants or antibody clonotypes formed by genetically close sequences. The most obvious na{iota}eve algorithms to extract such sequence families are impractical in light of the massive size of modern NGS datasets. In this paper, we present fast and scalable k-mer-based framework to perform such sequence similarity queries efficiently, which specifically targets data produced by deep sequencing of heterogeneous populations such as viruses. The tool is freely available for download at https://github.com/vyacheslav-tsivina/signature-sj

bioinformatics↗

bioRxiv2017

Cell cycle time series gene expression data encoded as cyclic attractors in Hopfield systems

Modern time series gene expression and other omics data sets have enabled unprecedented resolution of the dynamics of cellular processes such as cell cycle and response to pharmaceutical compounds. In anticipation of the proliferation of time series data sets in the near future, we use the Hopfield model, a recurrent neural network based on spin glasses, to model the dynamics of cell cycle in HeLa (human cervical cancer) and S. cerevisiae cells. We study some of the rich dynamical properties of these cyclic Hopfield systems, including the ability of populations of simulated cells to recreate experimental expression data and the effects of noise on the dynamics. Next, we use a genetic algorithm to identify sets of genes which, when selectively inhibited by local external fields representing gene silencing compounds such as kinase inhibitors, disrupt the encoded cell cycle. We find, for example, that inhibiting the set of four kinases BRD4, MAPK1, NEK7, and YES1 in HeLa cells causes simulated cells to accumulate in the M phase. Finally, we suggest possible improvements and extensions to our model.\n\nAuthor SummaryCell cycle - the process in which a parent cell replicates its DNA and divides into two daughter cells - is an upregulated process in many forms of cancer. Identifying gene inhibition targets to regulate cell cycle is important to the development of effective therapies. Although modern high throughput techniques offer unprecedented resolution of the molecular details of biological processes like cell cycle, analyzing the vast quantities of the resulting experimental data and extracting actionable information remains a formidable task. Here, we create a dynamical model of the process of cell cycle using the Hopfield model (a type of recurrent neural network) and gene expression data from human cervical cancer cells and yeast cells. We find that the model recreates the oscillations observed in experimental data. Tuning the level of noise (representing the inherent randomness in gene expression and regulation) to the \"edge of chaos\" is crucial for the proper behavior of the system. We then use this model to identify potential gene targets for disrupting the process of cell cycle. This method could be applied to other time series data sets and used to predict the effects of untested targeted perturbations.

systems biology↗