Niclosamide Prevents the Formation of Large Ubiquitin-Containing Aggregates Caused by Proteasome Inhibition

Protein aggregation is a hallmark of many neurodegenerative diseases and has been linked to the failure to degrade misfolded and damaged proteins. In the cell, aberrant proteins are degraded by the ubiquitin proteasome system that mainly targets short-lived proteins, or by the lysosomes that mostly clear long-lived and poorly soluble proteins. Both systems are interconnected and, in some instances, autophagy can redirect proteasome substrates to the lysosomes.To better understand the interplay between these two systems, we established a neuroblastoma cell population stably expressing the GFP-ubiquitin fusion protein. We show that inhibition of the proteasome leads to the formation of large ubiquitin-containing inclusions accompanied by lower solubility of the ubiquitin conjugates. Strikingly, the formation of the ubiquitin-containing aggregates does not require ectopic expression of disease-specific proteins. Moreover, formation of these focused inclusions caused by proteasome inhibition requires the lysine 63 (K63) of ubiquitin. We then assessed selected compounds that stimulate autophagy and found that the antihelmintic chemical niclosamide prevents large aggregate formation induced by proteasome inhibition, while the prototypical mTORC1 inhibitor rapamycin had no apparent effect. Niclosamide also precludes the accumulation of poly-ubiquitinated proteins and of p62 upon proteasome inhibition. Moreover, niclosamide induces a change in lysosome distribution in the cell that, in the absence of proteasome activity, may favor the uptake into lysosomes of ubiquitinated proteins before they form large aggregates.Our results indicate that proteasome inhibition provokes the formation of large ubiquitin containing aggregates in tissue culture cells, even in the absence of disease specific proteins. Furthermore our study suggests that the autophagy-inducing compound niclosamide may promote the selective clearance of ubiquitinated proteins in the absence of proteasome activity

A compendium of multi-omic sequence information from the Saanich Inlet water column.

Marine oxygen minimum zones (OMZs) are widespread regions of the ocean that are currently expanding due to global warming. While inhospitable to most metazoans, OMZs are hotspots for microbial mediated biogeochemical cycling of carbon, nitrogen and sulphur, contributing disproportionately to marine nitrogen loss and climate active trace gas production. Our current understanding of microbial community responses to OMZ expansion is limited by a lack of time-resolved data sets linking multi-omic sequence information (DNA, RNA, protein) to geochemical parameters and process rates. Here, we present six years of time-resolved multi-omic observations in Saanich Inlet, a seasonally anoxic fjord on the coast of Vancouver Island, British Columbia, Canada that undergoes recurring changes in water column oxygenation status. This compendium provides a unique multi-omic framework for studying microbial community responses to ocean deoxygenation along defined geochemical gradients in OMZ waters

Saanich_TimeSeries_Historical_O2_DATA

Historical dissolved oxygen winkler measurements at Station S3 in Saanich Inlet from 1953 to 2007. This data includes, geographical coordinates, date (year and month), depth (meters), temperature (celcius degrees), salinity (PSU), density (sigma-theta), oxygen (milliliter per liter and micromolar). For detailed methods see the manuscript

Saanich_TimeSeries_Chemical

Chemical bottle data collected from Station S3 (-123.505, 48.59166667) in Saanich Inlet, BC, Canada. This data includes unique geographical coordinates for sampling station (Decimal degrees), Numerical identifier of individual cruises (Numeric string), Date of cruise (YY-MM-DD), Sampling depth (Meters), Oxygen concentration calculated from CTD SBE (Micromolar), Phosphate (Bran Luebbe AutoAnalyser - colorimetric) (Micromolar), Silicate (Bran Luebbe AutoAnalyser - colorimetric) (Micromolar), Nitrate (Bran Luebbe AutoAnalyser - colorimetric) (Micromolar), Average Ammonium (fluorometric) (Micromolar), Average Nitrite (colorimetric) (Micromolar), Average Hydrogen sulfide (colorimetric) (Micromolar), Cell counts value quantified by flow cytometry (Number of cells per millilitre (cells/mL)), Average concentration of Nitrogen gas (headspace) (Micromolar), Standard deviation for Nitrogen gas, Average concentration of Oxygen (headspace) (Micromolar), Standard deviation for Oxygen, Average concentration of Carbon dioxide (headspace) (Micromolar), Standard deviation for Carbon dioxide, Average concentration of Nitrous oxide (headspace or automated purge-and-trap) (Micromolar), Standard deviation for Nitrous oxide, Average concentration of Methane (headspace or automated purge-and-trap) (Nanomolar), Standard deviation for Methane. For detailed description of methods see manuscript

Saanich_TimeSeries_CTD_DATA

CTD data from Station S3 in Saanich Inlet. This data includes unique geographical coordinates for sampling station (Decimal degrees), Numerical identifier of individual cruises (Numeric string), Date of cruise (YY-MM-DD), CTD pressure measurement in intervals of 1 meter (Decibars), CTD temperature (Celsius degrees), CTD conductivity (Millisiemens per centimetre), CTD fluorometer chlorophyll measurement (Chlorophyll concentration in milligram per cubic meter), CTD transmissometer measurement (Light transmission), CTD Photosintentically active radiation (PAR) measurement (Irradiance), CTD Dissolved oxygen sensor measurement (SBE) (Volts), Oxygen concentration based on CTD Oxygen SBE (Micromolar), CTD salinity measurement at each pressure point (Practical salinity unit), CTD density measurement at each pressure point (Sigma-theta). For detailed description on methods see manuscript

Saanich_TimeSeries_Winkler_DATA

Dissolved oxygen winkler measurements at Station S3 in Saanich Inlet from 2008-2014. This data includes unique geographical coordinates, date (year and month), depth (meters) and oxygen concentration (micromolar). See manuscript for detailed methods

High-resolution phylogenetic microbial community profiling

Over the past decade, high-throughput short-read 16S rRNA gene amplicon sequencing has eclipsed clone-dependent long-read Sanger sequencing for microbial community profiling. The transition to new technologies has provided more quantitative information at the expense of taxonomic resolution with implications for inferring metabolic traits in various ecosystems. We applied single-molecule real-time sequencing for microbial community profiling, generating full-length 16S rRNA gene sequences at high throughput, which we propose to name PhyloTags. We benchmarked and validated this approach using a defined microbial community. When further applied to samples from the water column of meromictic Sakinaw Lake, we show that while community structures at the phylum level are comparable between PhyloTags and Illumina V4 16S rRNA gene sequences (iTags), variance increases with community complexity at greater water depths. PhyloTags moreover allowed less ambiguous classification. Last, a platform-independent comparison of PhyloTags and in silico generated partial 16S rRNA gene sequences demonstrated significant differences in community structure and phylogenetic resolution across multiple taxonomic levels, including a severe underestimation in the abundance of specific microbial genera involved in nitrogen and methane cycling across the Lake's water column. Thus, PhyloTags provide a reliable adjunct or alternative to cost-effective iTags, enabling more accurate phylogenetic resolution of microbial communities and predictions on their metabolic potential