74 research outputs found

    Transcriptional profiles for distinct aggregation states of mutant Huntingtin exon 1 protein unmask new Huntington's disease pathways

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    Huntington's disease is caused by polyglutamine (polyQ)-expansion mutations in the CAG tandem repeat of the Huntingtin gene. The central feature of Huntington's disease pathology is the aggregation of mutant Huntingtin (Htt) protein into micrometer-sized inclusion bodies. Soluble mutant Htt states are most proteotoxic and trigger an enhanced risk of death whereas inclusions confer different changes to cellular health, and may even provide adaptive responses to stress. Yet the molecular mechanisms underpinning these changes remain unclear. Using the flow cytometry method of pulse-shape analysis (PulSA) to sort neuroblastoma (Neuro2a) cells enriched with mutant or wild-type Htt into different aggregation states, we clarified which transcriptional signatures were specifically attributable to cells before versus after inclusion assembly. Dampened CREB signalling was the most striking change overall and invoked specifically by soluble mutant Httex1 states. Toxicity could be rescued by stimulation of CREB signalling. Other biological processes mapped to different changes before and after aggregation included NF-kB signalling, autophagy, SUMOylation, transcription regulation by histone deacetylases and BRD4, NAD+ biosynthesis, ribosome biogenesis and altered HIF-1 signalling. These findings open the path for therapeutic strategies targeting key molecular changes invoked prior to, and subsequently to, Httex1 aggregation.This work was supported by grants to DMH from the Australian Research Council (grant number FT120100039); grants/fellowships from the National Health and Medical Research Council Project to DMH (grant numbers APP1049458, APP1049459 and APP1102059), and a grant from the Hereditary Disease Foundation (USA). AJH is an NHMRC Principal Research Fellow

    PERCEPT: Replacing binary p-value thresholding with scaling for more nuanced identification of sample differences

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    Summary: Key to a biologists’ capacity to understand data is the ability to make meaningful conclusions about differences in experimental observations. Typically, data are noisy, and conventional methods rely on replicates to average out noise and enable univariate statistical tests to assign p-values. Yet thresholding p-values to determine significance is controversial and often misleading, especially for omics datasets with few replicates. This study introduces PERCEPT, an alternative that transforms data using an ad-hoc scaling factor derived from p-values. By applying this method, low confidence effects are suppressed compared to high confidence ones, enabling clearer patterns to emerge from noisy datasets. The effectiveness of PERCEPT scaling is demonstrated using simulated datasets and published omics studies. The approach reduces the exclusion of datapoints, enhances accuracy, and enables nuanced interpretation of data. PERCEPT is easy to apply for the non-expert in statistics and provides researchers a straightforward way to improve data-driven analyses

    Protein painting reveals pervasive remodeling of conserved proteostasis machinery in response to pharmacological stimuli.

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    The correct spatio-temporal organization of the proteome is essential for cellular homeostasis. However, a detailed mechanistic understanding of this organization and how it is altered in response to external stimuli in the intact cellular environment is as-yet unrealized. 'Protein painting methods provide a means to address this gap in knowledge by monitoring the conformational status of proteins within cells at the proteome-wide scale. Here, we demonstrate the ability of a protein painting method employing tetraphenylethene maleimide (TPE-MI) to reveal proteome network remodeling in whole cells in response to a cohort of commonly used pharmacological stimuli of varying specificity. We report specific, albeit heterogeneous, responses to individual stimuli that coalesce on a conserved set of core cellular machineries. This work expands our understanding of proteome conformational remodeling in response to cellular stimuli, and provides a blueprint for assessing how these conformational changes may contribute to disorders characterized by proteostasis imbalance

    Analyzing modifiers of protein aggregation in C. elegans by native agarose gel electrophoresis

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    The accumulation of specific aggregation-prone proteins during aging is thought to be involved in several diseases, most notably Alzheimer's and Parkinson's disease as well as polyglutamine expansion disorders such as Huntington's disease. Caenorhabditis elegans disease models with transgenic expression of fluorescently tagged aggregation-prone proteins have been used to screen for genetic modifiers of aggregation. To establish the role of modifying factors in the generation of aggregation intermediates, a method has been developed using native agarose gel electrophoresis (NAGE) that enables parallel screening of aggregation patterns of fluorescently labeled aggregation-prone proteins. Together with microscopy-based genetic screens this method can be used to identify modifiers of protein aggregation and characterize their molecular function. Although described here for analyzing aggregates in C. elegans, NAGE can be adjusted for use in other model organisms as well as for cultured cells
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