Distance-based analysis of variance for brain connectivity

The field of neuroimaging dedicated to mapping connections in the brain is increasingly being recognized as key for understanding neurodevelopment and pathology. Networks of these connections are quantitatively represented using complex structures, including matrices, functions, and graphs, which require specialized statistical techniques for estimation and inference about developmental and disorder-related changes. Unfortunately, classical statistical testing procedures are not well suited to high-dimensional testing problems. In the context of global or regional tests for differences in neuroimaging data, traditional analysis of variance (ANOVA) is not directly applicable without first summarizing the data into univariate or low-dimensional features, a process that might mask the salient features of high-dimensional distributions. In this work, we consider a general framework for two-sample testing of complex structures by studying generalized within-group and between-group variances based on distances between complex and potentially high-dimensional observations. We derive an asymptotic approximation to the null distribution of the ANOVA test statistic, and conduct simulation studies with scalar and graph outcomes to study finite sample properties of the test. Finally, we apply our test to our motivating study of structural connectivity in autism spectrum disorder.     

Evidence and hypothesis in biogeography

Evidence can provide support for or against a particular biogeographical hypothesis. Treating a hypothesis as if it were evidence or an empirical observation confounds many biogeographical analyses. We focus on two recent publications that address, in part, the evolution of the biota of Sulawesi, the large Indonesian island in the centre of the Indo‐Australian Archipelago. Many biogeographical explanations are hampered by invoking simple notions of mechanism or process – dispersal and vicariance – or constraints, such as dispersal from a centre of origin, and, in so doing, dismiss more complex geological phenomena such as emergent volcanoes within island chains or composite areas as irrelevant. Moreover, they do not search for, therefore never discover, biogeographical patterns that may better explain the distribution of biota through time.     

Comparison of 26 Sphingomonad Genomes Reveals Diverse Environmental Adaptations and Biodegradative Capabilities

Sphingomonads comprise a physiologically versatile group within the Alphaproteobacteria that includes strains of interest for biotechnology, human health, and environmental nutrient cycling. In this study, we compared 26 sphingomonad genome sequences to gain insight into their ecology, metabolic versatility, and environmental adaptations. Our multilocus phylogenetic and average amino acid identity (AAI) analyses confirm that Sphingomonas, Sphingobium, Sphingopyxis, and Novosphingobium are well-resolved monophyletic groups with the exception of Sphingomonas sp. strain SKA58, which we propose belongs to the genus Sphingobium. Our pan-genomic analysis of sphingomonads reveals numerous species-specific open reading frames (ORFs) but few signatures of genus-specific cores. The organization and coding potential of the sphingomonad genomes appear to be highly variable, and plasmid-mediated gene transfer and chromosome-plasmid recombination, together with prophage- and transposon-mediated rearrangements, appear to play prominent roles in the genome evolution of this group. We find that many of the sphingomonad genomes encode numerous oxygenases and glycoside hydrolases, which are likely responsible for their ability to degrade various recalcitrant aromatic compounds and polysaccharides, respectively. Many of these enzymes are encoded on megaplasmids, suggesting that they may be readily transferred between species. We also identified enzymes putatively used for the catabolism of sulfonate and nitroaromatic compounds in many of the genomes, suggesting that plant-based compounds or chemical contaminants may be sources of nitrogen and sulfur. Many of these sphingomonads appear to be adapted to oligotrophic environments, but several contain genomic features indicative of host associations. Our work provides a basis for understanding the ecological strategies employed by sphingomonads and their role in environmental nutrient cycling.     

The Effect of Social Hierarchy on Captive Coyote (Canis latrans) Foraging Behavior

Foraging efficiency of individuals in pack forming species may be influenced by social dynamics within a pack. The effects of social hierarchy in particular may influence individual foraging behavior in canids, such as coyotes (Canis latrans). To examine the impact of social hierarchy on foraging behavior, we tested 16 captive coyotes in eight naturally established dominant–subordinate pairs, using the guesser–knower paradigm. We measured the efficiency of subordinate coyotes to relocate a food resource when alone and then allowed pairs to forage together, such that subordinates had prior knowledge of food location but dominants did not. To determine whether (1) subordinates used a direct or discursive strategy to obtain food in the presence of a dominant and (2) dominants used an exploitative or independent strategy to obtain food in the presence of a subordinate with previous knowledge, we measured their search efficiency (e.g., correct choice of area, feeder, and latency to correct feeder). Results showed subordinates learned to relocate food and increase efficiency when alone. In a social context, however, subordinate efficiency decreased. That is, subordinates approached the correct area, but searched more feeders before finding the correct one. Dominants initially used an independent search strategy but then quickly displaced the subordinate and monopolized the resource, reducing subordinate efficiency further. Despite continual displacement and reduction in efficiency, subordinates did not alter their foraging strategy over time. Our results suggest prior information can improve individual foraging advantage, but that social status strongly impacts individual foraging efficiency in social species such as coyotes.     

New Insights into the Interdependence between Amino Acid Stereochemistry and Protein Structure

To successfully design new proteins and understand the effects of mutations in natural proteins, we must understand the geometric and physicochemical principles underlying protein structure. The side chains of amino acids in peptides and proteins adopt specific dihedral angle combinations; however, we still do not have a fundamental quantitative understanding of why some side-chain dihedral angle combinations are highly populated and others are not. Here we employ a hard-sphere plus stereochemical constraint model of dipeptide mimetics to enumerate the side-chain dihedral angles of leucine (Leu) and isoleucine (Ile), and identify those conformations that are sterically allowed versus those that are not as a function of the backbone dihedral angles ? and ψ. We compare our results with the observed distributions of side-chain dihedral angles in proteins of known structure. With the hard-sphere plus stereochemical constraint model, we obtain agreement between the model predictions and the observed side-chain dihedral angle distributions for Leu and Ile. These results quantify the extent to which local, geometrical constraints determine protein side-chain conformations.     

Psammaplysin F: A unique inhibitor of bacterial chromosomal partitioning

Described is the antibiotic activity of a marine natural product. Psammaplysin F (1) inhibited the growth of four Gram-positive strains by >80% at 50 μM, and the amine at position C-20 is responsible for the observed antibacterial activity. When tested against two strains of methicillin resistant Staphylococcus aureus (MRSA), the minimum inhibitory concentrations (MICs) for psammaplysin F (40–80 μM) were similar to the structurally-related alkaloid psammaplysin H (2). Psammaplysin F (1) increased membrane permeability by two to four-fold compared to psammaplysin H (2) or control-treated bacteria, respectively. Unlike psammaplysin H (2), we show that psammaplysin F (1) inhibits equal partitioning of DNA into each daughter cell, suggesting that this natural product is a unique prokaryotic cell division inhibitor.