Partial Loss of Ataxin-1 Function Contributes to Transcriptional Dysregulation in Spinocerebellar Ataxia Type 1 Pathogenesis

Spinocerebellar ataxia type 1 (SCA1) is a dominantly inherited neurodegenerative disease caused by expansion of a CAG repeat that encodes a polyglutamine tract in ATAXIN1 (ATXN1). Molecular and genetic data indicate that SCA1 is mainly caused by a gain-of-function mechanism. However, deletion of wild-type ATXN1 enhances SCA1 pathogenesis, whereas increased levels of an evolutionarily conserved paralog of ATXN1, Ataxin 1-Like, ameliorate it. These data suggest that a partial loss of ATXN1 function contributes to SCA1. To address this possibility, we set out to determine if the SCA1 disease model (Atxn1154Q/+ mice) and the loss of Atxn1 function model (Atxn1−/− mice) share molecular changes that could potentially contribute to SCA1 pathogenesis. To identify transcriptional changes that might result from loss of function of ATXN1 in SCA1, we performed gene expression microarray studies on cerebellar RNA from Atxn1−/− and Atxn1154Q/+ cerebella and uncovered shared gene expression changes. We further show that mild overexpression of Ataxin-1-Like rescues several of the molecular and behavioral defects in Atxn1−/− mice. These results support a model in which Ataxin 1-Like overexpression represses SCA1 pathogenesis by compensating for a partial loss of function of Atxn1. Altogether, these data provide evidence that partial loss of Atxn1 function contributes to SCA1 pathogenesis and raise the possibility that loss-of-function mechanisms contribute to other dominantly inherited neurodegenerative diseases

Guidelines for the use and interpretation of assays for monitoring autophagy (3rd edition)

In 2008 we published the first set of guidelines for standardizing research in autophagy. Since then, research on this topic has continued to accelerate, and many new scientists have entered the field. Our knowledge base and relevant new technologies have also been expanding. Accordingly, it is important to update these guidelines for monitoring autophagy in different organisms. Various reviews have described the range of assays that have been used for this purpose. Nevertheless, there continues to be confusion regarding acceptable methods to measure autophagy, especially in multicellular eukaryotes. For example, a key point that needs to be emphasized is that there is a difference between measurements that monitor the numbers or volume of autophagic elements (e.g., autophagosomes or autolysosomes) at any stage of the autophagic process versus those that measure fl ux through the autophagy pathway (i.e., the complete process including the amount and rate of cargo sequestered and degraded). In particular, a block in macroautophagy that results in autophagosome accumulation must be differentiated from stimuli that increase autophagic activity, defi ned as increased autophagy induction coupled with increased delivery to, and degradation within, lysosomes (inmost higher eukaryotes and some protists such as Dictyostelium ) or the vacuole (in plants and fungi). In other words, it is especially important that investigators new to the fi eld understand that the appearance of more autophagosomes does not necessarily equate with more autophagy. In fact, in many cases, autophagosomes accumulate because of a block in trafficking to lysosomes without a concomitant change in autophagosome biogenesis, whereas an increase in autolysosomes may reflect a reduction in degradative activity. It is worth emphasizing here that lysosomal digestion is a stage of autophagy and evaluating its competence is a crucial part of the evaluation of autophagic flux, or complete autophagy. Here, we present a set of guidelines for the selection and interpretation of methods for use by investigators who aim to examine macroautophagy and related processes, as well as for reviewers who need to provide realistic and reasonable critiques of papers that are focused on these processes. These guidelines are not meant to be a formulaic set of rules, because the appropriate assays depend in part on the question being asked and the system being used. In addition, we emphasize that no individual assay is guaranteed to be the most appropriate one in every situation, and we strongly recommend the use of multiple assays to monitor autophagy. Along these lines, because of the potential for pleiotropic effects due to blocking autophagy through genetic manipulation it is imperative to delete or knock down more than one autophagy-related gene. In addition, some individual Atg proteins, or groups of proteins, are involved in other cellular pathways so not all Atg proteins can be used as a specific marker for an autophagic process. In these guidelines, we consider these various methods of assessing autophagy and what information can, or cannot, be obtained from them. Finally, by discussing the merits and limits of particular autophagy assays, we hope to encourage technical innovation in the field

Innovative approach for self-management and social welfare of children with cystic fibrosis in Europe: Development, validation and implementation of an mHealth tool (MyCyFAPP)

Introduction: For the optimal management of children with cystic fibrosis, there are currently no efficient tools for the precise adjustment of pancreatic enzyme replacement therapy, either for advice on appropriate dietary intake or for achieving an optimal nutrition status. Therefore, we aim to develop a mobile application that ensures a successful nutritional therapy in children with cystic fibrosis. Methods and analysis: A multidisciplinary team of 12 partners coordinate their efforts in 9 work packages that cover the entire so-called ‘from laboratory to market’ approach by means of an original and innovative co-design process. A cohort of 200 patients with cystic fibrosis aged 1–17 years are enrolled. We will develop an innovative, clinically tested mobile health application for patients and health professionals involved in cystic fibrosis management. The mobile application integrates the research knowledge and innovative tools for maximising self-management with the aim of leading to a better nutritional status, quality of life and disease prognosis. Bringing together different and complementary areas of knowledge is fundamental for tackling complex challenges in disease treatment, such as optimal nutrition and pancreatic enzyme replacement therapy in cystic fibrosis. Patients are expected to benefit the most from the outcomes of this innovative project. Ethics and dissemination: The project is approved by the Ethics Committee of the coordinating organisation, Hospital Universitari La Fe (Ref: 2014/ 0484). Scientific findings will be disseminated via journals and conferences addressed to clinicians, food scientists, information and communications technology experts and patients. The specific dissemination working group within the project will address the wide audience communication through the website (http://www. mycyfapp.eu), the social networks and the newsletter.publishedVersio

Pharmacometabolomic Signature of Ataxia SCA1 Mouse Model and Lithium Effects

<div><p>We have shown that lithium treatment improves motor coordination in a spinocerebellar ataxia type 1 (SCA1) disease mouse model (<i>Sca1^154Q/+</i>). To learn more about disease pathogenesis and molecular contributions to the neuroprotective effects of lithium, we investigated metabolomic profiles of cerebellar tissue and plasma from SCA1-model treated and untreated mice. Metabolomic analyses of wild-type and <i>Sca1^154Q/+</i> mice, with and without lithium treatment, were performed using gas chromatography time-of-flight mass spectrometry and BinBase mass spectral annotations. We detected 416 metabolites, of which 130 were identified. We observed specific metabolic perturbations in <i>Sca1^154Q/+</i> mice and major effects of lithium on metabolism, centrally and peripherally. Compared to wild-type, <i>Sca1^154Q/+</i> cerebella metabolic profile revealed changes in glucose, lipids, and metabolites of the tricarboxylic acid cycle and purines. Fewer metabolic differences were noted in <i>Sca1^154Q/+</i> mouse plasma versus wild-type. In both genotypes, the major lithium responses in cerebellum involved energy metabolism, purines, unsaturated free fatty acids, and aromatic and sulphur-containing amino acids. The largest metabolic difference with lithium was a 10-fold increase in ascorbate levels in wild-type cerebella (p<0.002), with lower threonate levels, a major ascorbate catabolite. In contrast, <i>Sca1^154Q/+</i> mice that received lithium showed no elevated cerebellar ascorbate levels. Our data emphasize that lithium regulates a variety of metabolic pathways, including purine, oxidative stress and energy production pathways. The purine metabolite level, reduced in the <i>Sca1^154Q/+</i> mice and restored upon lithium treatment, might relate to lithium neuroprotective properties.</p></div

Effect of lithium treatment on cerebellum metabolome.

<p>Metabolic network of wild-type and <i>Sca1^154Q/+</i> cerebellum phenotypes. <b>A.</b> Wild-type mice. <b>B.</b> SCA1 knock-in mice. Red nodes: Increased metabolite levels under Lithium treatment; blue nodes: decreased levels. Node shades indicate ANOVA significance levels, node size reflect differences in magnitude of regulation. Red lines: reactant pair relationships obtained from the KEGG reaction pair database. Yellow solid lines: chemical similarity >0.5 Tanimoto score (Tanimoto scores range between 0 to 1, where 1 reflects identical structures). Yellow broken lines: chemically closest structure at <0.5 Tanimoto scores. Green circles group significant compounds that changed only in the Wild-type genotype. Orange circles group significant compounds that changed in both genotypes.</p

Genotype effect on metabolic profiles: Significantly different metabolites comparing wild-type versus <i>Sca1^154Q/+</i> mice under control conditions.

<p>Notes: Bold indicates statistical significance. One-way analysis of variance performed separately for cerebellum and blood plasma (see <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0070610#pone-0070610-g002" target="_blank">Figure 2</a> and supplemental <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0070610#pone-0070610-g001" target="_blank">Figure 1</a> for box-whisker plots). Abbreviation: NIST, National Institute of Standards and Technology.</p

Effect of Lithium treatment on blood plasma metabolic profile: Significantly different metabolites comparing Lithium treatment versus control conditions.

<p>Note: Bold indicates statistical significance. One-way ANOVA performed separately for wild-type and <i>Sca1^154Q/+</i> mice (see supplemental <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0070610#pone-0070610-g002" target="_blank">Figure 2</a> for box-whisker plots). Abbreviation: Li, Lithium.</p