Project description:Endocytosis is a fundamental process that controls protein/lipid composition of the plasma membrane, thereby shaping cellular metabolism, sensing, adhesion, signaling, and nutrient uptake. Endocytosis is essential for the cell to adapt to its surrounding environment, and a tight regulation of the endocytic mechanisms is required to maintain cell function and survival. This is particularly significant in the central nervous system (CNS), where composition of neuronal cell surface is crucial for synaptic functioning. In fact, distinct pathologies of the CNS are tightly linked to abnormal endolysosomal function, and several genome wide association analysis (GWAS) and biochemical studies have identified intracellular trafficking regulators as genetic risk factors for such pathologies. The sorting nexins (SNXs) are a family of proteins involved in protein trafficking regulation and signaling. SNXs dysregulation occurs in patients with Alzheimer's disease (AD), Down's syndrome (DS), schizophrenia, ataxia and epilepsy, among others, establishing clear roles for this protein family in pathology. Interestingly, restoration of SNXs levels has been shown to trigger synaptic plasticity recovery in a DS mouse model. This review encompasses an historical and evolutionary overview of SNXs protein family, focusing on its organization, phyla conservation, and evolution throughout the development of the nervous system during speciation. We will also survey SNXs molecular interactions and highlight how defects on SNXs underlie distinct pathologies of the CNS. Ultimately, we discuss possible strategies of intervention, surveying how our knowledge about the fundamental processes regulated by SNXs can be applied to the identification of novel therapeutic avenues for SNXs-related disorders.
Project description:Retromer is a phylogenetically conserved, multisubunit coat complex that controls endosomal protein trafficking and sorting. Mutations in the retromer gene VPS35 cause late-onset Parkinson disease, suggesting that trafficking defects cause neurodegeneration. Sorting nexins assist retromer to guide cell surface proteins to their assigned destinations, and our interest here is sorting nexin 3 (Snx3). Snx3 binds to membranes via a phox homolog (PX) domain that binds phosphatidylinositol 3-phosphate (PI3P), and in human cells its cargo proteins are the transferrin and Wnt receptors and the divalent metal ion transporter, whereas in yeast the best characterized cargo is the iron permease Ftr1. We recently discovered that α-synuclein inhibits Snx3-retromer recycling of Ftr1 in an unexpected way: α-synuclein, which avidly binds to negatively charged lipids, blocks the association of Snx3 to early endosomes. Here, we discuss mechanisms by which α-synuclein can disrupt Snx3-retromer-mediated recycling.
Project description:Rare members of environmental microbial communities are often overlooked and unexplored, primarily due to the lack of techniques capable of acquiring their genomes. Chloroflexi belong to one of the most understudied phyla, even though many of its members are ubiquitous in the environment and some play important roles in biochemical cycles or biotechnological applications. We here used a targeted cell-sorting approach, which enables the selection of specific taxa by fluorescent labeling and is compatible with subsequent single-cell genomics, to enrich for rare Chloroflexi species from a wastewater-treatment plant and obtain their genomes. The combined workflow was able to retrieve a substantially higher number of novel Chloroflexi draft genomes with much greater phylogenetical diversity when compared to a metagenomics approach from the same sample. The method offers an opportunity to access genetic information from rare biosphere members which would have otherwise stayed hidden as microbial dark matter and can therefore serve as an essential complement to cultivation-based, metagenomics, and microbial community-focused research approaches.
Project description:The ability to categorize emotions has long-term implications for children's social and emotional development. Therefore, identifying factors that influence early emotion categorization is of great importance. Yet, whether and how language impacts emotion category development is still widely debated. The present study aimed to assess how labels influence young children's ability to group faces into emotion categories for both earliest-learned and later-learned emotion categories. Across two studies, 128 two- and 3-year-olds (77 female; Mean age = 3.04 years; 35.9% White, 12.5% Multiple ethnicities or races, 6.3% Asian, 3.1% Black, and 42.2% not reported) were presented with three emotion categories (Study 1 = happy, sad, angry; Study 2 = surprised, disgusted, afraid). Children sorted 30 images of adults posing stereotypical facial expressions into one of the three categories. Children were randomly assigned to either hear the emotion labels before sorting (e.g., "happy faces go here") or were not given labels (e.g., "faces like this go here"). Study 1 results indicated no significant effects of labels for earlier-learned emotion categories, F(1, 60) = .94, p = .337, ηp² = .013. However, the Study 2 results revealed that labels improved emotion categorization for later-learned categories, F(1, 60) = 8.15, p = .006, ηp² = .024. Taken together, these results suggest that labels are important for emotion categorization, but the impact of labels may depend on children's familiarity with the emotion category. (PsycInfo Database Record (c) 2022 APA, all rights reserved).
Project description:ObjectiveTo characterize the health risk of enrollees in California's state-based insurance marketplace (Covered California) by metal tier, region, month of enrollment, and plan.Data source/study setting2014 Open-enrollment data from Covered California linked with 2012 hospitalization and emergency department (ED) visit records from statewide all-payer administrative databases.Data collection/extraction methodsChronic Illness and Disability Payment System (CDPS) health risk scores derived from an individual's age and sex from the enrollment file and the diagnoses captured in the hospitalization and ED records. CDPS scores were standardized by setting the average to 1.00.Principal findingsAmong the 1,286,089 enrollees, 120,573 (9.4 percent) had at least one ED visit and/or a hospitalization in 2012. Higher risk enrollees chose plans with greater actuarial value. The standardized CDPS health risk score was 11 percent higher in the first month of enrollment (1.08; 99 percent CI: 1.07-1.09) than the last month (0.97; 99 percent CI: 0.97-0.97). Four of the 12 plans enrolled 91 percent of individuals; their average health risk scores were each within 3 percent of the marketplace's statewide average.ConclusionsProviding health plans with a means to assess the health risk of their year 1 enrollees allowed them to anticipate whether they would receive or contribute payments to a risk-adjustment pool. After receiving these findings as a part of their negotiations with Covered California, health plans covering the majority of enrollees decreased their initially proposed 2015 rates, saving consumers tens of millions of dollars in potential premiums.
Project description:This study aims to understand participant priorities in their personal recovery journey and their perspectives of recovery domains.A card sort data gathering technique was employed to elicit priorities in recovery from consumers in supportive housing programs serving formerly homeless adults with severe mental illnesses in New York City. Participants (N=38) were asked to sort 12 cards printed with recovery domains in order of importance and describe the meaning attached to each domain.Mental health (95%), physical health (89%), and housing (92%) were the domains most frequently included and prioritized in the top three rankings. Family (76%) and partner (74%) were also frequently included and endorsed as most important second only to mental health. Housing was prioritized yet rated most important less often (58%). Work, school, hobbies, program, friends and neighborhood were less frequently endorsed. 'Card sort talk' revealed critical understanding of participants' priorities and their reasons for endorsing other domains less frequently.Most important to participants was regaining functional independence through improved mental and physical health and access to housing. With underlying principles of efficiency and empowerment, card sort is a promising engagement technique for providers to elicit consumer priorities in their own recovery.
Project description:Aquatic ecosystems in the High Arctic are facing unprecedented changes as a result of global warming effects on the cryosphere. Snow pack is a central feature of northern landscapes, but the snow microbiome and its microbial connectivity to adjacent and downstream habitats have been little explored. To evaluate these aspects, we sampled along a hydrologic continuum at Ward Hunt Lake (latitude 83°N) in the Canadian High Arctic, from snow banks, water tracks in the permafrost catchment, the upper and lower strata of the lake, and the lake outlet and its coastal marine mixing zone. The microbial communities were analyzed by high-throughput sequencing of 16 and 18S rRNA to determine the composition of potentially active Bacteria, Archaea and microbial Eukarya. Each habitat had distinct microbial assemblages, with highest species richness in the subsurface water tracks that connected the melting snow to the lake. However, up to 30% of phylotypes were shared along the hydrologic continuum, showing that many taxa originating from the snow can remain in the active fraction of downstream microbiomes. The results imply that changes in snowfall associated with climate warming will affect microbial community structure throughout all spatially connected habitats within snow-fed polar ecosystems.
Project description:The Arctic is warming - fast. Microbes in the Arctic play pivotal roles in feedbacks that magnify the impacts of Arctic change. Understanding the genome evolution, diversity and dynamics of Arctic microbes can provide insights relevant for both fundamental microbiology and interdisciplinary Arctic science. Within this synthesis, we highlight four key areas where genomic insights to the microbial dimensions of Arctic change are urgently required: the changing Arctic Ocean, greenhouse gas release from the thawing permafrost, 'biological darkening' of glacial surfaces, and human activities within the Arctic. Furthermore, we identify four principal challenges that provide opportunities for timely innovation in Arctic microbial genomics. These range from insufficient genomic data to develop unifying concepts or model organisms for Arctic microbiology to challenges in gaining authentic insights to the structure and function of low-biomass microbiota and integration of data on the causes and consequences of microbial feedbacks across scales. We contend that our insights to date on the genomics of Arctic microbes are limited in these key areas, and we identify priorities and new ways of working to help ensure microbial genomics is in the vanguard of the scientific response to the Arctic crisis.
Project description:Environmental bulk samples often contain many different taxa that vary several orders of magnitude in biomass. This can be problematic in DNA metabarcoding and metagenomic high-throughput sequencing approaches, as large specimens contribute disproportionately high amounts of DNA template. Thus, a few specimens of high biomass will dominate the dataset, potentially leading to smaller specimens remaining undetected. Sorting of samples by specimen size (as a proxy for biomass) and balancing the amounts of tissue used per size fraction should improve detection rates, but this approach has not been systematically tested. Here, we explored the effects of size sorting on taxa detection using two freshwater macroinvertebrate bulk samples, collected from a low-mountain stream in Germany. Specimens were morphologically identified and sorted into three size classes (body size < 2.5 × 5, 5 × 10, and up to 10 × 20 mm). Tissue powder from each size category was extracted individually and pooled based on tissue weight to simulate samples that were not sorted by biomass ("Unsorted"). Additionally, size fractions were pooled so that each specimen contributed approximately equal amounts of biomass ("Sorted"). Mock samples were amplified using four different DNA metabarcoding primer sets targeting the Cytochrome c oxidase I (COI) gene. Sorting taxa by size and pooling them proportionately according to their abundance lead to a more equal amplification of taxa compared to the processing of complete samples without sorting. The sorted samples recovered 30% more taxa than the unsorted samples at the same sequencing depth. Our results imply that sequencing depth can be decreased approximately fivefold when sorting the samples into three size classes and pooling by specimen abundance. Even coarse size sorting can substantially improve taxa detection using DNA metabarcoding. While high-throughput sequencing will become more accessible and cheaper within the next years, sorting bulk samples by specimen biomass or size is a simple yet efficient method to reduce current sequencing costs.