Dreissenid veliger dynamics along a nearshore to offshore transect in Lake Michigan

Dreissenid mussel veligers compose a substantial component of pelagic biomass in the Great Lakes, yet their dynamics are poorly understood. To evaluate seasonal, spatial, and inter-annual variation in veliger density, we used a 64-μm mesh plankton net (2008, 2013–2016) and a 153-μm mesh plankton net (2007–2016) to collect dreissenid veligers at nearshore (15–25?m depth), transitional (45?m) and offshore (93–110?m) sites in southeast Lake Michigan during March–December. We also evaluated trends in density of recently settled mussels relative to veliger abundance and the density of the standing stock of adult mussels. Veliger density peaked during both summer and fall at all sites, but peak densities in summer were generally higher nearshore, whereas peak densities in the fall were generally higher offshore. The density of veligers in the 153-μm net was overall 28% of that in the 64-μm net, but there was high variability in this comparison among months. Smaller veligers were much more abundant in the 64-μm net, but there was little difference in the size distribution and abundance between nets for the 210–300?μm size classes. Thus, the 153-μm net could still be a useful tool for assessing density trends of larger veligers just prior to their settlement. Newly settled mussels (≤2?mm) were most abundant in summer or fall at the nearshore and offshore sites but were nearly absent at the transitional site despite the high density of veligers there. Factors other than veliger density must play an important role in mussel recruitment.     

How to ‘find’ an error minimized genetic code: neutral emergence as an alternative to direct Darwinian selection for evolutionary optimization

Error minimization (EM) of the standard genetic code (SGC) refers to the assignment of amino acids to codons in such a way that the deleterious impact of mutations is reduced. The SGC is nearly optimal for the property of EM, compared to randomly generated codes, and prompts the question of how the property arose. Brute force searching of alternative genetic codes is unlikely to have occurred, given the high number of alternative codes. Therefore, a heuristic search of ‘code space’, the space of alternative codes, would have been necessary. Uncovering the nature of this heuristic search is key to understanding the evolution of the genetic code, and consequently the origin of life. Scenarios that rely on direct selection for the property of EM require codon reassignments to sample code space, but these are problematic mechanistically. Alternatively, it has been shown that EM may have emerged in a neutral fashion as a byproduct of the process of genetic code expansion. In this scenario, similar amino acids are added to similar codons via the gene duplication of tRNAs and aminoacyl-tRNA synthetases. Mimicking this process via simulation indeed produces high levels of EM in the resulting genetic codes. These observations imply that optimization has occurred by an alternative to direct selection, commonly viewed as the only form of evolutionary optimization followed in nature. I propose that the neutral emergence of EM produced by code expansion is a genetic algorithm but unlike direct selection, the local selection criterion (amino acid and codon similarity) is distant from the global fitness function (EM), leading to the emergent optimization of EM. By presenting this counter example I clarify how evolutionary optimization in biological systems is not restricted to direct selection, and emphasize that additional processes may lead to the production of beneficial traits, via ‘non-Darwinian optimization’.

     

Rationally Designed Polypharmacology: α-Helix Mimetics as Dual Inhibitors of the Oncoproteins Mcl-1 and HDM2

Protein–protein interactions (PPIs), many of which are dominated by α-helical recognition domains, play key roles in many essential cellular processes, and the dysregulation of these interactions can cause detrimental effects. For instance, aberrant PPIs involving the Bcl-2 protein family can lead to several diseases including cancer, neurodegenerative diseases, and diabetes. Interactions between Bcl-2 pro-life proteins, such as Mcl-1, and pro-death proteins, such as Bim, regulate the intrinsic pathway of apoptosis. p53, a tumor-suppressor protein, also has a pivotal role in apoptosis and is negatively regulated by its E3 ubiquitin ligase HDM2. Both Mcl-1 and HDM2 are upregulated in numerous cancers, and, interestingly, there is crosstalk between both protein pathways. Recently, synergy has been observed between Mcl-1 and HDM2 inhibitors. Towards the development of new anticancer drugs, we herein describe a polypharmacology approach for the dual inhibition of Mcl-1 and HDM2 by employing three densely functionalized isoxazoles, pyrazoles, and thiazoles as mimetics of key α-helical domains of their partner proteins.     

A boronic acid-based fluorescent hydrogel for monosaccharide detection

A boronic acid-based anthracene fluorescent probe was functionalised with an acrylamide unit to incorporate into a hydrogel system for monosaccharide detection. In solution, the fluorescent probe displayed a strong fluorescence turn-on response upon exposure to fructose, and an expected trend in apparent binding constants, as judged by a fluorescence response where D-fructose>D-galactose>D-mannose>D-glucose. The hydrogel incorporating the boronic acid monomer demonstrated the ability to detect monosaccharides by fluorescence with the same overall trend as the monomer in solution with the addition of D-fructose resulting in a 10-fold enhancement (≤0.25 mol/L).     

Improved Split-Plot and Multistratum Designs

Many industrial experiments involve some factors whose levels are harder to set than others. The best way to deal with these is to plan the experiment carefully as a split-plot, or more generally a multistratum, design. Several different approaches for constructing split-plot type response surface designs have been proposed in the literature since 2001, which has allowed experimenters to make better use of their resources by using more efficient designs than the classical balanced ones. One of these approaches, the stratum-by-stratum strategy has been shown to produce designs that are less efficient than locally D-optimal designs. An improved stratum-by-stratum algorithm is given, which, though more computationally intensive than the old one, makes better use of the advantages of this approach, that is, it can be used for any structure and does not depend on prior estimates of the variance components. This is shown to be almost as good as the locally optimal designs in terms of their own criteria and more robust across a range of criteria. Supplementary materials for this article are available online.