bioRxiv Science⌕ Search

Biology subjects

Bay, K.

Publications and source records attributed to Bay, K..

2 recordsLinked to original sources

Uncovering the Design Rules for Sustainable Growth of Mineralized Mycomaterials

Mycomaterials, materials made from filamentous fungi, have several advantages over traditional materials, such as their genetic programmability and self-healing properties. However, their lack of mechanical strength and cost of production often constrain the applications they can be used in. In this work, we take inspiration from natural systems to overcome these challenges by elucidating design principles for mineralization-based enhancement of mechanical strength and synthetic lichen-based low-cost growth. We demonstrate that surface display of an enzyme from sea sponges, silicatein , on the hyphae of the filamentous fungus Aspergillus niger enables mineralization of polysilicate and that this does not impact fungal growth. We also show that this strategy can be extended to other silicatein variants and characterize how the degree of mineralization can be modulated. We then demonstrate that mineralization enhances the mechanical properties of the mycelium, including its tensile strength, modulus, and toughness. Finally, we show how these reinforced mycelia can be grown without external carbon sources using a synthetic lichen-based co-culture to facilitate low cost biomanufacturing. Together, our results lay the groundwork for the sustainable production of mineralized mycomaterials and create a new model system to study how mineralization impacts growth and mechanical properties. Significance StatementMaterials made from filamentous fungi, called mycomaterials, have several advantages over traditional materials, but their poor mechanical properties and relatively high production costs have limited their application. We elucidated design principles to enable tunable mineralization of fungal mycelium and have shown that it does not impact growth but significantly enhances mechanical strength. We have also shown that these reinforced mycelia can be grown without any external carbon in a synthetic lichen like consortia to minimize production costs. This work creates a novel experimental system to study how mineralization impacts growth and mechanical properties and will facilitate the broader application of mycomaterials in the future.

synthetic biology↗

Evidence of Absence Regression: A Binomial N-Mixture Model for Estimating Bird and Bat Fatalities at Wind Power Facilities

Estimating bird and bat fatalities caused by wind-turbine facilities is challenging when carcass counts are rare and produce counts that are either exactly zero or very near zero. The rarity of found carcasses is exacerbated when live members of a particular species are rare and when carcasses degrade quickly, are removed by scavengers, or are not detected by observers. With few observed carcass counts, common statistical methods like logistic, Poisson, or negative binomial regression are unreliable (statistically biased) and often fail to provide answers (i.e., fail to converge). Here, we propose a binomial N-mixture model that estimates fatality rates as well as the total number of carcass counts when these rates are expanded. Our model extends the evidence of absence model (Huso et al., 2015; Dalthorp, Huso, and Dail, 2017) by relating carcass deposition rates to study covariates and by incorporating terms that naturally scale counts from facilities of different sizes. Our model, which we call Evidence of Absence Regression (EoAR), can estimate the total number of birds or bats killed at a single wind energy facility or a fleet of wind energy facilities based on covariate values. Furthermore, with accurate prior distributions the models results are extremely robust to sparse data and unobserved combinations of covariate values. In this paper, we describe the model, show its low bias and high precision via computer simulation, and apply it to bat carcass counts observed at 21 wind energy facilities in Iowa.

ecology↗