Attempted Integration of Multiple Species of Turaco Into a Mixed‐Species Aviary

Mixed‐species exhibits offer a variety of benefits but can be challenging to maintain due to difficulty in managing interspecific interactions. This is particularly true when little has been documented on the behavior of the species being mixed. This was the case when we attempted to house three species of turaco (family: Musophagidae) together with other species in a walk‐through aviary. To learn more about the behavior of great blue turacos, violaceous turacos, and white‐bellied gray go‐away birds, we supplemented opportunistic keeper observations with systematic data collection on their behavior, location, distance from other birds, and visibility to visitors. Keepers reported high levels of aggression among turacos, usually initiated by a go‐away bird or a violaceous turaco. Most aggression occurred during feedings or when pairs were defending nest sites. Attempts to reduce aggression by temporarily removing birds to holding areas and reintroducing them days later were ineffective. Systematic data collection revealed increased social behavior, including aggression, during breeding season in the violaceous turacos, as well as greater location fidelity. These behavioral cues may be useful in predicting breeding behavior in the future. Ultimately, we were only able to house three species of turaco together for a short time, and prohibitively high levels of conflict occurred when pairs were breeding. We conclude that mixing these three turaco species is challenging and may not be the most appropriate housing situation for them, particularly during breeding season. However, changes in turaco species composition, sex composition, or exhibit design may result in more compatible mixed‐turaco species groups. Zoo Biol. 32:216–221, 2013. © 2012 Wiley Periodicals, Inc.     

Significance of the Natural Occurrence of L‐ Versus D‐Pipecolic Acid: A Review

Pipecolic acid naturally occurs in microorganisms, plants, and animals, where it plays many roles, including the interactions between these organisms, and is a key constituent of many natural and synthetic bioactive molecules. This article provides a review of current knowledge on the natural occurrence of pipecolic acid and the known and potential significance of its L‐ and D‐enantiomers in different scientific disciplines. Knowledge gaps with perspectives for future research identified within this article include the roles of the L‐ versus the D‐enantiomer of pipecolic acid in plant resistance, nutrient acquisition, and decontamination of polluted soils, as well as rhizosphere ecology and medical issues. Chirality 25:823–831, 2013. © 2013 Wiley Periodicals, Inc.     

Atypical Antigen Recognition Mode of a Shark Immunoglobulin New Antigen Receptor (IgNAR) Variable Domain Characterized by Humanization and Structural Analysis

The immunoglobulin new antigen receptors (IgNARs) are a class of Ig-like molecules of the shark immune system that exist as heavy chain-only homodimers and bind antigens by their single domain variable regions (V-NARs). Following shark immunization and/or in vitro selection, V-NARs can be generated as soluble, stable, and specific high affinity monomeric binding proteins of ∼12 kDa. We have previously isolated a V-NAR from an immunized spiny dogfish shark, named E06, that binds specifically and with high affinity to human, mouse, and rat serum albumins. Humanization of E06 was carried out by converting over 60% of non-complementarity-determining region residues to those of a human germ line Vκ1 sequence, DPK9. The resulting huE06 molecules have largely retained the specificity and affinity of antigen binding of the parental V-NAR. Crystal structures of the shark E06 and its humanized variant (huE06 v1.1) in complex with human serum albumin (HSA) were determined at 3- and 2.3-Å resolution, respectively. The huE06 v1.1 molecule retained all but one amino acid residues involved in the binding site for HSA. Structural analysis of these V-NARs has revealed an unusual variable domain-antigen interaction. E06 interacts with HSA in an atypical mode that utilizes extensive framework contacts in addition to complementarity-determining regions that has not been seen previously in V-NARs. On the basis of the structure, the roles of various elements of the molecule are described with respect to antigen binding and V-NAR stability. This information broadens the general understanding of antigen recognition and provides a framework for further design and humanization of shark IgNARs.     

Dissecting a complex chemical stress: chemogenomic profiling of plant hydrolysates

The efficient production of biofuels from cellulosic feedstocks will require the efficient fermentation of the sugars in hydrolyzed plant material. Unfortunately, plant hydrolysates also contain many compounds that inhibit microbial growth and fermentation. We used DNA‐barcoded mutant libraries to identify genes that are important for hydrolysate tolerance in both Zymomonas mobilis (44 genes) and Saccharomyces cerevisiae (99 genes). Overexpression of a Z. mobilis tolerance gene of unknown function (ZMO1875) improved its specific ethanol productivity 2.4‐fold in the presence of miscanthus hydrolysate. However, a mixture of 37 hydrolysate‐derived inhibitors was not sufficient to explain the fitness profile of plant hydrolysate. To deconstruct the fitness profile of hydrolysate, we profiled the 37 inhibitors against a library of Z. mobilis mutants and we modeled fitness in hydrolysate as a mixture of fitness in its components. By examining outliers in this model, we identified methylglyoxal as a previously unknown component of hydrolysate. Our work provides a general strategy to dissect how microbes respond to a complex chemical stress and should enable further engineering of hydrolysate tolerance.     

Stand-replacing wildfires alter the community structure of wood-inhabiting fungi in southwestern ponderosa pine forests of the USA

Increases in stand-replacing wildfires in the western USA have widespread implications for ecosystem carbon (C) cycling, in part because the decomposition of trees killed by fire can be a long-term source of CO₂ to the atmosphere. Knowledge of the composition and function of decay fungi communities may be important to understanding how wildfire alters C cycles. We assessed the effects of stand-replacing wildfires on the community structure of wood-inhabiting fungi along a 32-yr wildfire chronosequence. Fire was associated with low species richness for up to 4 yr and altered species composition relative to unburned forest for the length of the chronosequence. A laboratory incubation demonstrated that species varied in their capacity to decompose wood; Hypocrea lixii, an indicator of the most recent burn, caused the lowest decomposition rate. Our results show that stand-replacing wildfires have long-term effects on fungal communities, which may have consequences for wood decomposition and C cycling.     

Using Linkage Analysis to Detect Gene-Gene Interactions. 2. Improved Reliability and Extension to More-Complex Models

Detecting gene-gene interaction in complex diseases has become an important priority for common disease genetics, but most current approaches to detecting interaction start with disease-marker associations. These approaches are based on population allele frequency correlations, not genetic inheritance, and therefore cannot exploit the rich information about inheritance contained within families. They are also hampered by issues of rigorous phenotype definition, multiple test correction, and allelic and locus heterogeneity. We recently developed, tested, and published a powerful gene-gene interaction detection strategy based on conditioning family data on a known disease-causing allele or a disease-associated marker allele⁴. We successfully applied the method to disease data and used computer simulation to exhaustively test the method for some epistatic models. We knew that the statistic we developed to indicate interaction was less reliable when applied to more-complex interaction models. Here, we improve the statistic and expand the testing procedure. We computer-simulated multipoint linkage data for a disease caused by two interacting loci. We examined epistatic as well as additive models and compared them with heterogeneity models. In all our models, the at-risk genotypes are “major” in the sense that among affected individuals, a substantial proportion has a disease-related genotype. One of the loci (A) has a known disease-related allele (as would have been determined from a previous analysis). We removed (pruned) family members who did not carry this allele; the resultant dataset is referred to as “stratified.” This elimination step has the effect of raising the “penetrance” and detectability at the second locus (B). We used the lod scores for the stratified and unstratified data sets to calculate a statistic that either indicated the presence of interaction or indicated that no interaction was detectable. We show that the new method is robust and reliable for a wide range of parameters. Our statistic performs well both with the epistatic models (false negative rates, i.e., failing to detect interaction, ranging from 0 to 2.5%) and with the heterogeneity models (false positive rates, i.e., falsely detecting interaction, ≤1%). It works well with the additive model except when allele frequencies at the two loci differ widely. We explore those features of the additive model that make detecting interaction more difficult. All testing of this method suggests that it provides a reliable approach to detecting gene-gene interaction.     

Detection of silent cells,synchronization and modulatory activity in developing cellular networks

Developing networks in the immature nervous system and in cellular cultures are characterized by waves of synchronous activity in restricted clusters of cells. Synchronized activity in immature networks is proposed to regulate many different developmental processes, from neuron growth and cell migration, to the refinement of synapses, topographic maps, and the mature composition of ion channels. These emergent activity patterns are not present in all cells simultaneously within the network and more immature “silent” cells, potentially correlated with the presence of silent synapses, are prominent in different networks during early developmental periods. Many current network analyses for detection of synchronous cellular activity utilize activity‐based pixel correlations to identify cellular‐based regions of interest (ROIs) and coincident cell activity. However, using activity‐based correlations, these methods first underestimate or ignore the inactive silent cells within the developing network and second, are difficult to apply within cell‐dense regions commonly found in developing brain networks. In addition, previous methods may ignore ROIs within a network that shows transient activity patterns comprising both inactive and active periods. We developed analysis software to semi‐automatically detect cells within developing neuronal networks that were imaged using calcium‐sensitive reporter dyes. Using an iterative threshold, modulation of activity was tracked within individual cells across the network. The distribution pattern of both inactive and active, including synchronous cells, could be determined based on distance measures to neighboring cells and according to different anatomical layers. © 2015 Wiley Periodicals, Inc. Develop Neurobiol 76: 357–374, 2016