-
[
Biophys J,
2019]
Protein misfolding and overloaded proteostasis networks underlie a range of neurodegenerative diseases. Nocures exist for these diseases, but developing effective therapeutic agents targeting the toxic, misfolded protein species in disease is one promising strategy. AAA+ (ATPases associated with diverse cellular activities) protein translocases, which naturally unfold and translocate substrate proteins, could be potent therapeutic agents to disassemble toxic protein conformers in neurodegenerative disease. Here, we discuss repurposing AAA+ protein translocases Hsp104 and proteasome-activating nucleotidase (PAN) to alleviate the toxicity from protein misfolding in neurodegenerative disease. Hsp104 effectively protects various animal models from neurodegeneration underpinned by protein misfolding, and enhanced Hsp104 variants strongly counter neurodegenerative disease-associated protein misfolding toxicity in yeast, Caenorhabditis elegans, and mammalian cells. Similarly, a recently engineered PAN variant (PAN<sup>et</sup>) mitigates photoreceptor degeneration instigated by protein misfoldingin a mouse model of retinopathy. Further study and engineering of AAA+ translocases like Hsp104 and PAN will reveal promising agents to combat protein misfolding toxicity in neurodegenerative disease.
-
[
Sci Prog,
2024]
Establishing a functional nervous system is a complex process requiring tightly controlled gene expression programs to achieve the correct differentiation of distinct neuronal subtypes. The molecular programs required for neurons to acquire neuron-type-specific, and core pan-neuronal features mostly rely on sequence-specific transcription factors (TFs), which recognize and bind to cis-regulatory motifs present in the promoters of target genes. Recently, we investigated the role and mode of action of the NF-Y complex, a ubiquitously expressed transcriptional master regulator, in the <i>Caenorhabditis elegans</i> nervous system. We found that NFYA-1 is a pervasive regulator of neuron-specific and pan-neuronal gene batteries that are essential for neuronal development and function. Furthermore, we concluded that NFYA-1 acts cell autonomously by either directly binding to conserved motifs in target gene promoter regions or indirectly by regulating other transcriptional regulators to fine-tune gene expression. However, further studies are required to fully define the impact of the NF-Y complex on nervous system regulatory networks and how NF-Y coordinates with other TFs in this regard.
-
[
Biochem Soc Trans,
2004]
IFT (intraflagellar transport) assembles and maintains sensory cilia on the dendritic endings of chemosensory neurons within the nematode Caenorhabditis elegans. During IFT, macromolecular protein complexes called IFT particles (which carry ciliary precursors) are moved from the base of the sensory cilium to its distal tip by anterograde IFT motors (kinesin-II and Osm-3 kinesin) and back to the base by retrograde IFT-dynein [Rosenbaum and Witman (2002) Nat. Rev. Mol. Cell Biol. 3, 813-825; Scholey (2003) Annu. Rev. Cell Dev. Biol. 19, 423-443; and Snell, Pan and Wang (2004) Cell 117, 693-697]. In the present study, we describe the protein machinery of IFT in C. elegans, which we have analysed using time-lapse fluorescence microscopy of green fluorescent protein-fusion proteins in concert with ciliary mutants.
-
[
Biochim Biophys Acta,
2017]
The development of new microscopy techniques for super-resolved, long-term monitoring of cellular and subcellular dynamics in living organisms is revealing new fundamental aspects of tissue development and repair. However, new microscopy approaches present several challenges. In addition to unprecedented requirements for data storage, the analysis of high resolution, time-lapse images is too complex to be done manually. Machine learning techniques are ideally suited for the (semi-)automated analysis of multidimensional image data. In particular, support vector machines (SVMs), have emerged as an efficient method to analyze microscopy images obtained from animals. Here, we discuss the use of SVMs to analyze in vivo microscopy data. We introduce the mathematical framework behind SVMs, and we describe the metrics used by SVMs and other machine learning approaches to classify image data. We discuss the influence of different SVM parameters in the context of an algorithm for cell segmentation and tracking. Finally, we describe how the application of SVMs has been critical to study protein localization in yeast screens, for lineage tracing in C. elegans, or to determine the developmental stage of Drosophila embryos to investigate gene expression dynamics. We propose that SVMs will become central tools in the analysis of the complex image data that novel microscopy modalities have made possible. This article is part of a Special Issue entitled: Biophysics in Canada, edited by Lewis Kay, John Baenziger, Albert Berghuis and Peter Tieleman.
-
[
Mol Genet Metab,
2011]
Mucolipidosis type IV (MLIV) is a neurodevelopmental as well as neurodegenerative disorder with severe psychomotor developmental delay, progressive visual impairment, and achlorydria. It is characterized by the presence of lysosomal inclusions in many cell types in patients. MLIV is an autosomal recessive disease caused by mutations in MCOLN1, which encodes for mucolipin-1, a member of the transient receptor potential (TRP) cation channel family. Although approximately 70-80% of patients identified are Ashkenazi Jewish, MLIV is a pan-ethnic disorder. Importantly, while MLIV is thought to be a rare disease, its frequency may be greater than currently appreciated, for its common presentation as a cerebral palsy-like encephalopathy can lead to misdiagnosis. Moreover, patients with milder variants are often not recognized as having MLIV. This review provides an update on the ethnic distribution, clinical manifestations, laboratory findings, methods of diagnosis, molecular genetics, differential diagnosis, and treatment of patients with MLIV. An enhanced awareness of the manifestations of this disorder may help to elucidate the true frequency and range of symptoms associated with MLIV, providing insight into the pathogenesis of this multi-system disease.