A Highlights from MBoC Selection: ER-associated retrograde SNAREs and the Dsl1 complex mediate an alternative,Sey1p-independent homotypic ER fusion pathway

The peripheral endoplasmic reticulum (ER) network is dynamically maintained by homotypic (ER–ER) fusion. In Saccharomyces cerevisiae, the dynamin-like GTPase Sey1p can mediate ER–ER fusion, but sey1Δ cells have no growth defect and only slightly perturbed ER structure. Recent work suggested that ER-localized soluble N-ethylmaleimide–sensitive factor attachment protein receptors (SNAREs) mediate a Sey1p-independent ER–ER fusion pathway. However, an alternative explanation—that the observed phenotypes arose from perturbed vesicle trafficking—could not be ruled out. In this study, we used candidate and synthetic genetic array (SGA) approaches to more fully characterize SNARE-mediated ER–ER fusion. We found that Dsl1 complex mutations in sey1Δ cells cause strong synthetic growth and ER structure defects and delayed ER–ER fusion in vivo, additionally implicating the Dsl1 complex in SNARE-mediated ER–ER fusion. In contrast, cytosolic coat protein I (COPI) vesicle coat mutations in sey1Δ cells caused no synthetic defects, excluding perturbed retrograde trafficking as a cause for the previously observed synthetic defects. Finally, deleting the reticulons that help maintain ER architecture in cells disrupted for both ER–ER fusion pathways caused almost complete inviability. We conclude that the ER SNAREs and the Dsl1 complex directly mediate Sey1p-independent ER–ER fusion and that, in the absence of both pathways, cell viability depends upon membrane curvature–promoting reticulons.     

Liquid Exfoliated Co(OH)2 Nanosheets as Low‐Cost,Yet High‐Performance,Catalysts for the Oxygen Evolution Reaction

Identifying cheap, yet effective, oxygen evolution catalysts is critical to the advancement of water splitting. Using liquid exfoliated Co(OH)₂ nanosheets as a model system, a simple procedure is developed to maximize the activity of any oxygen evolution reaction nanocatalyst. First the nanosheet edges are confirmed as the active areas by analyzing the catalytic activity as a function of nanosheet size. This allows the authors to select the smallest nanosheets (length ≈50 nm) as the best performing catalysts. While the number of active sites per unit electrode area can be increased via the electrode thickness, this is found to be impossible beyond ≈10 µm due to mechanical instabilities. However, adding carbon nanotubes increases both toughness and conductivity significantly. These enhancements mean that composite electrodes consisting of small Co(OH)₂ nanosheets and 10 wt% nanotubes can be made into freestanding films with thickness of up to 120 µm with no apparent electrical limitations. The presence of diffusion limitations results in an optimum electrode thickness of 70 µm, yielding a current density of 50 mA cm^?2 at an overpotential of 235 mV, close to the state of the art in the field. Applying this procedure to a high‐performance catalyst such as NiFeO_x should significantly surpass the state of the art.     

Using a FRET Library with Multiple Probe Pairs To Drive Monte Carlo Simulations of α-Synuclein

We describe a strategy for experimentally-constraining computational simulations of intrinsically disordered proteins (IDPs), using α-synuclein, an IDP with a central role in Parkinson’s disease pathology, as an example. Previously, data from single-molecule Förster Resonance Energy Transfer (FRET) experiments have been effectively utilized to generate experimentally constrained computational models of IDPs. However, the fluorophores required for single-molecule FRET experiments are not amenable to the study of short-range (<30 Å) interactions. Using ensemble FRET measurements allows one to acquire data from probes with multiple distance ranges, which can be used to constrain Monte Carlo simulations in PyRosetta. To appropriately employ ensemble FRET data as constraints, we optimized the shape and weight of constraining potentials to afford ensembles of structures that are consistent with experimental data. We also used this approach to examine the structure of α-synuclein in the presence of the compacting osmolyte trimethylamine-N-oxide. Despite significant compaction imparted by 2 M trimethylamine-N-oxide, the underlying ensemble of α-synuclein remains largely disordered and capable of aggregation, also in agreement with experimental data. These proof-of-concept experiments demonstrate that our modeling protocol enables one to efficiently generate experimentally constrained models of IDPs that incorporate atomic-scale detail, allowing one to study an IDP under a variety of conditions.     

A20 Deficiency in Lung Epithelial Cells Protects against Influenza A Virus Infection

A20 negatively regulates multiple inflammatory signalling pathways. We here addressed the role of A20 in club cells (also known as Clara cells) of the bronchial epithelium in their response to influenza A virus infection. Club cells provide a niche for influenza virus replication, but little is known about the functions of these cells in antiviral immunity. Using airway epithelial cell-specific A20 knockout (A20^AEC-KO) mice, we show that A20 in club cells critically controls innate immune responses upon TNF or double stranded RNA stimulation. Surprisingly, A20^AEC-KO mice are better protected against influenza A virus challenge than their wild type littermates. This phenotype is not due to decreased viral replication. Instead host innate and adaptive immune responses and lung damage are reduced in A20^AEC-KO mice. These attenuated responses correlate with a dampened cytotoxic T cell (CTL) response at later stages during infection, indicating that A20^AEC-KO mice are better equipped to tolerate Influenza A virus infection. Expression of the chemokine CCL2 (also named MCP-1) is particularly suppressed in the lungs of A20^AEC-KO mice during later stages of infection. When A20^AEC-KO mice were treated with recombinant CCL2 the protective effect was abrogated demonstrating the crucial contribution of this chemokine to the protection of A20^AEC-KO mice to Influenza A virus infection. Taken together, we propose a mechanism of action by which A20 expression in club cells controls inflammation and antiviral CTL responses in response to influenza virus infection.     

Experimental Tests of the Function and Flexibility of Song Consistency in a Wild Bird

Measures of bird song that capture aspects of motor performance, such as consistency, have become a major focus in understanding sexual selection on song. Despite accumulating evidence that consistency is related to reproductive success in many species, the relative importance of male–male interactions and female–male interactions is still unclear. We studied the function and flexibility of song consistency and song rate in common yellowthroat warblers (Geothlypis trichas). A previous study of this population found that song consistency—measured as the amount of variability within a bout of songs—was positively correlated with the likelihood of siring extrapair young. In this study, we conducted two experiments aimed at testing (1) the role of song consistency and rate in mediating male–male and male–female interactions and (2) whether song effort is flexibly adjusted to changes in social context. In the first experiment, we simulated a male territorial intrusion with song playbacks that varied in consistency and rate; focal males responded aggressively to playbacks, but their response did not differ with playback consistency or rate. In the second experiment, we presented focal males with a taxidermic female mount and female vocalizations; focal males approached the speaker, but continued to sing and did not perform the aggressive rattle vocalization observed during male encounters. Immediately after the simulated female encounter, focal males increased in song consistency. Taken together, our results are most consistent with the hypothesis that song consistency in common yellowthroats is primarily a female‐directed signal that is actively adjusted in response to rapidly changing social conditions.     

Forest biomass energy: assessing atmospheric carbon impacts by discounting future carbon flows

Although forest biomass energy was long assumed to be carbon neutral, many studies show delays between forest biomass carbon emissions and sequestration, with biomass carbon causing climate change damage in the interim. While some models suggest that these primary biomass carbon effects may be mitigated by induced market effects, for example, from landowner decisions to increase afforestation due to higher biomass prices, the delayed carbon sequestration of biomass energy systems still creates considerable scientific debate (i.e., how to assess effects) and policy debate (i.e., how to act given these effects). Forests can be carbon sinks, but their carbon absorption capacity is finite. Filling the sink with fossil fuel carbon thus has a cost, and conversely, harvesting a forest for biomass energy – which depletes the carbon sink – creates potential benefits from carbon sequestration. These values of forest carbon sinks have not generally been considered. Using data from the 2010 Manomet Center for Conservation Sciences ‘Biomass sustainability and carbon policy study’ and a model of forest biomass carbon system dynamics, we investigate how discounting future carbon flows affects the comparison of biomass energy to fossil fuels in Massachusetts, USA. Drawing from established financial valuation metrics, we calculate internal rates of return (IRR) as explicit estimates of the temporal values of forest biomass carbon emissions. Comparing these IRR to typical private discount rates, we find forest biomass energy to be preferred to fossil fuel energy in some applications. We discuss possible rationales for zero and near‐zero social discount rates with respect to carbon emissions, showing that social discount rates depend in part on expectations about how climate change affects future economic growth. With near‐zero discount rates, forest biomass energy is preferred to fossil fuels in all applications studied. Higher IRR biomass energy uses (e.g., thermal applications) are preferred to lower IRR uses (e.g., electricity generation without heat recovery).     

Measuring the Quality of University Lectures: Development and Validation of the Instructional Skills Questionnaire (ISQ)

In higher education, student ratings are often used to evaluate and improve the quality of courses and professors’ instructional skills. Unfortunately, student-rating questionnaires rarely generate specific feedback for professors to improve their instructional skills. The impact of student ratings on professors’ instructional skills has proven to be low. This study concerns the psychometric properties of the Instructional Skills Questionnaire (ISQ), a new theory-based student-rating-of-teaching questionnaire with specific questions concerning lecturing skills. The ISQ is administered after a single lecture. This way, it serves as a formative feedback instrument for university professors during courses to assist them to improve and (re-) evaluate their skills if necessary. The ISQ contains seven dimensions of professors’ instructional skills and three student (self perceived) learning outcomes. In this study, Dutch students in 75 courses rated three 90-minute lectures (T1, T2 and T3) of their respective professors using the ISQ. In total, 14,298 ISQ-forms were used to rate 225 lectures. The teacher level reliabilities of the seven dimensions were found to be good at each measurement occasion. In addition, confirmatory multilevel factor analysis confirmed a seven dimensional factor structure at the teacher level at each measurement occasion. Furthermore, specific teacher level factors significantly predicted students’ (self-assessed) learning outcomes. These results partly supported the proposed theoretical framework on the relationship between the ISQ teaching dimensions and the student learning process, and provided evidence for the construct validity of the instrument. In sum, the ISQ is found to be a reliable and valid instrument, which can be used by professors and faculty development centers to assess and improve university teaching.