Mutagenesis of Trichoderma reesei endoglucanase I: impact of expression host on activity and stability at elevated temperatures.

BackgroundTrichoderma reesei is a key cellulase source for economically saccharifying cellulosic biomass for the production of biofuels. Lignocellulose hydrolysis at temperatures above the optimum temperature of T. reesei cellulases (~50°C) could provide many significant advantages, including reduced viscosity at high-solids loadings, lower risk of microbial contamination during saccharification, greater compatibility with high-temperature biomass pretreatment, and faster rates of hydrolysis. These potential advantages motivate efforts to engineer T. reesei cellulases that can hydrolyze lignocellulose at temperatures ranging from 60-70°C.ResultsA B-factor guided approach for improving thermostability was used to engineer variants of endoglucanase I (Cel7B) from T. reesei (TrEGI) that are able to hydrolyze cellulosic substrates more rapidly than the recombinant wild-type TrEGI at temperatures ranging from 50-70°C. When expressed in T. reesei, TrEGI variant G230A/D113S/D115T (G230A/D113S/D115T Tr_TrEGI) had a higher apparent melting temperature (3°C increase in Tm) and improved half-life at 60°C (t1/2 = 161 hr) than the recombinant (T. reesei host) wild-type TrEGI (t1/2 = 74 hr at 60°C, Tr_TrEGI). Furthermore, G230A/D113S/D115T Tr_TrEGI showed 2-fold improved activity compared to Tr_TrEGI at 65°C on solid cellulosic substrates, and was as efficient in hydrolyzing cellulose at 60°C as Tr_TrEGI was at 50°C. The activities and stabilities of the recombinant TrEGI enzymes followed similar trends but differed significantly in magnitude depending on the expression host (Escherichia coli cell-free, Saccharomyces cerevisiae, Neurospora crassa, or T. reesei). Compared to N.crassa-expressed TrEGI, S. cerevisiae-expressed TrEGI showed inferior activity and stability, which was attributed to the lack of cyclization of the N-terminal glutamine in Sc_TrEGI and not to differences in glycosylation. N-terminal pyroglutamate formation in TrEGI expressed in S. cerevisiae was found to be essential in elevating its activity and stability to levels similar to the T. reesei or N. crassa-expressed enzyme, highlighting the importance of this ubiquitous modification in GH7 enzymes.ConclusionStructure-guided evolution of T. reesei EGI was used to engineer enzymes with increased thermal stability and activity on solid cellulosic substrates. Production of TrEGI enzymes in four hosts highlighted the impact of the expression host and the role of N-terminal pyroglutamate formation on the activity and stability of TrEGI enzymes

Human and environmental controls over aboveground carbon storage in Madagascar

Background: Accurate, high-resolution mapping of aboveground carbon density (ACD, Mg C ha-1) could provide insight into human and environmental controls over ecosystem state and functioning, and could support conservation and climate policy development. However, mapping ACD has proven challenging, particularly in spatially complex regions harboring a mosaic of land use activities, or in remote montane areas that are difficult to access and poorly understood ecologically. Using a combination of field measurements, airborne Light Detection and Ranging (LiDAR) and satellite data, we present the first large-scale, high-resolution estimates of aboveground carbon stocks in Madagascar. Results: We found that elevation and the fraction of photosynthetic vegetation (PV) cover, analyzed throughout forests of widely varying structure and condition, account for 27-67 % of the spatial variation in ACD. This finding facilitated spatial extrapolation of LiDAR-based carbon estimates to a total of 2,372,680 ha using satellite data. Remote, humid sub-montane forests harbored the highest carbon densities, while ACD was suppressed in dry spiny forests and in montane humid ecosystems, as well as in most lowland areas with heightened human activity. Independent of human activity, aboveground carbon stocks were subject to strong physiographic controls expressed through variation in tropical forest canopy structure measured using airborne LiDAR. Conclusions: High-resolution mapping of carbon stocks is possible in remote regions, with or without human activity, and thus carbon monitoring can be brought to highly endangered Malagasy forests as a climate-change mitigation and biological conservation strategy

Old Tools, New Ways of Using Them: Harnessing Expert Opinions to Plan for Surprise in Marine Socio-Ecological Systems

Copyright © 2019 Gladstone-Gallagher, Hope, Bulmer, Clark, Stephenson, Mangan, Rullens, Siwicka, Thomas, Pilditch, Savage and Thrush. With globally accelerating rates of environmental disturbance, coastal marine ecosystems are increasingly prone to non-linear regime shifts that result in a loss of ecosystem function and services. A lack of early-detection methods, and an over reliance on limits-based approaches means that these tipping points manifest as surprises. Consequently, marine ecosystems are notoriously difficult to manage, and scientists, managers, and policy makers are paralyzed in a spiral of ecosystem degradation. This paralysis is caused by the inherent need to quantify the risk and uncertainty that surrounds every decision. While progress toward forecasting tipping points is ongoing and important, an interim approach is desperately needed to enable scientists to make recommendations that are credible and defensible in the face of deep uncertainty. We discuss how current tools for developing risk assessments and scenario planning, coupled with expert opinions, can be adapted to bridge gaps in quantitative data, enabling scientists and managers to prepare for many plausible futures. We argue that these tools are currently underutilized in a marine cumulative effects context but offer a way to inform decisions in the interim while predictive models and early warning signals remain imperfect. This approach will require redefining the way we think about managing for ecological surprise to include actions that not only limit drivers of tipping points but increase socio-ecological resilience to yield satisfactory outcomes under multiple possible futures that are inherently uncertain

Does musical enrichment enhance the neural coding of syllables? Neuroscientific interventions and the importance of behavioral data

A commentary on: Music enrichment programs improve the neural encoding of speech in at-risk children by Kraus, N., Slater, J., Thompson, E. C., Hornickel, J., Strait, D. L., Nicol, T., et al. (2014). J. Neurosci. 34, 11913–11918. doi: 10.1523/JNEUROSCI.1881-14.201

Multiple stressor effects on marine infauna: responses of estuarine taxa and functional traits to sedimentation, nutrient and metal loading

Sedimentation, nutrients and metal loading to coastal environments are increasing, associated with urbanization and global warming, hence there is a growing need to predict ecological responses to such change. Using a regression technique we predicted how maximum abundance of 20 macrobenthic taxa and 22 functional traits separately and interactively responded to these key stressors. The abundance of most taxa declined in response to sedimentation and metal loading while a unimodal response was often associated with nutrient loading. Optimum abundances for both taxa and traits occurred at relatively low stressor levels, highlighting the vulnerability of estuaries to increasing stressor loads. Individual taxa were more susceptible to stress than traits, suggesting that functional traits may be less sensitive for detecting changes in ecosystem health. Multiplicative effects were more common than additive interactions. The observed sensitivity of most taxa to increasing sedimentation and metal loading and the documented interaction effects between multiple stressors have important implications for understanding and managing the ecological consequences of eutrophication, sedimentation and contaminants on coastal ecosystems

Observations with the Differential Speckle Survey Instrument. X. Preliminary Orbits of K Dwarf Binaries and Other Stars

This paper details speckle observations of binary stars taken at the Lowell Discovery Telescope, the WIYN Telescope, and the Gemini telescopes between 2016 January and 2019 September. The observations taken at Gemini and Lowell were done with the Differential Speckle Survey Instrument (DSSI), and those done at WIYN were taken with the successor instrument to DSSI at that site, the NN-EXPLORE Exoplanet Star and Speckle Imager (NESSI). In total, we present 378 observations of 178 systems and we show that the uncertainty in the measurement precision for the combined data set is ~2 mas in separation, ~1-2 degrees in position angle depending on the separation, and $\sim$0.1 magnitudes in magnitude difference. Together with data already in the literature, these new results permit 25 visual orbits and one spectroscopic-visual orbit to be calculated for the first time. In the case of the spectroscopic-visual analysis, which is done on the trinary star HD 173093, we calculate masses with precision of better than 1% for all three stars in that system. Twenty-one of the visual orbits calculated have a K dwarf as the primary star; we add these to the known orbits of K dwarf primary stars and discuss the basic orbital properties of these stars at this stage. Although incomplete, the data that exist so far indicate that binaries with K dwarf primaries tend not to have low-eccentricity orbits at separations of one to a few tens of AU, that is, on solar-system scales

Ultrafast Radiographic Imaging and Tracking: An overview of instruments, methods, data, and applications

Ultrafast radiographic imaging and tracking (U-RadIT) use state-of-the-art ionizing particle and light sources to experimentally study sub-nanosecond dynamic processes in physics, chemistry, biology, geology, materials science and other fields. These processes, fundamental to nuclear fusion energy, advanced manufacturing, green transportation and others, often involve one mole or more atoms, and thus are challenging to compute by using the first principles of quantum physics or other forward models. One of the central problems in U-RadIT is to optimize information yield through, e.g. high-luminosity X-ray and particle sources, efficient imaging and tracking detectors, novel methods to collect data, and large-bandwidth online and offline data processing, regulated by the underlying physics, statistics, and computing power. We review and highlight recent progress in: a.) Detectors; b.) U-RadIT modalities; c.) Data and algorithms; and d.) Applications. Hardware-centric approaches to U-RadIT optimization are constrained by detector material properties, low signal-to-noise ratio, high cost and long development cycles of critical hardware components such as ASICs. Interpretation of experimental data, including comparisons with forward models, is frequently hindered by sparse measurements, model and measurement uncertainties, and noise. Alternatively, U-RadIT makes increasing use of data science and machine learning algorithms, including experimental implementations of compressed sensing. Machine learning and artificial intelligence approaches, refined by physics and materials information, may also contribute significantly to data interpretation, uncertainty quantification and U-RadIT optimization.Comment: 51 pages, 31 figures; Overview of ultrafast radiographic imaging and tracking as a part of ULITIMA 2023 conference, Mar. 13-16,2023, Menlo Park, CA, US