Comparative psychology and the grand challenge of drug discovery in psychiatry and neurodegeneration

Drug discovery for brain disorders is undergoing a period of upheaval. Faced with an empty drug pipeline and numerous failures of potential new drugs in clinical trials, many large pharmaceutical companies have been shrinking or even closing down their research divisions that focus on central nervous system (CNS) disorders. In this paper, we argue that many of the difficulties facing CNS drug discovery stem from a lack of robustness in pre-clinical (i.e., non-human animal) testing. There are two main sources for this lack of robustness. First, there is the lack of replicability of many results from the pre-clinical stage, which we argue is driven by a combination of publication bias and inappropriate selection of statistical and experimental designs. Second, there is the frequent failure to translate results in non-human animals to parallel results in humans in the clinic. This limitation can only be overcome by developing new behavioral tests for non-human animals that have predictive, construct, and etiological validity. Here, we present these translational difficulties as a “grand challenge” to researchers from comparative cognition, who are well positioned to provide new methods for testing behavior and cognition in non-human animals. These new experimental protocols will need to be both statistically robust and target behavioral and cognitive processes that allow for better connection with human CNS disorders. Our hope is that this downturn in industrial research may represent an opportunity to develop new protocols that will re-kindle the search for more effective and safer drugs for CNS disorders.     

Behavioral differentiation during collective building in wild mice Mus spicilegus

Although well documented in social insects, the possibility of behavioral differentiation during collective building has been poorly studied in mammals. In this context, the mound-building mouse Mus spicilegus is an interesting model. Under natural conditions, juveniles from different litters gather vegetal material and build a sophisticated structure, the mound, under which the mice will spend winter. The first steps of this complex building process may be elicited under laboratory conditions by offering cotton balls as building material. Spatio-temporal distribution of both animals and cotton balls was automatically recorded by RFID (Radio-Frequency Identification Device) technique. Our results revealed a behavioral differentiation during a collective building task. In a group of six individuals, only two mice (called carriers) transported 80% of the building material whereas the contribution of the remaining mice was weak or even non-existent. The proportion of carriers was constant in all of the six groups studied. This behavioral differentiation was implemented immediately after the building material was made available and remained stable during the 4 days of experiment. The high contribution level of carriers did not result from resource monopolization, nor did it depend on the gender or parental origin of the mice.     

Structure-based phylogeny of polyene macrolide antibiotic glycosyltransferases

Antibiotic glycosyltransferases (AGts) attach unusual deoxy-sugars to aglycons so antibiotics can exert function. It has been reported that polyene macrolide (PEM) AGts have different evolutionary origin when compared with other polyketide AGts, and our previous analysis have suggested that they could be results of horizontal gene transfer (HGT) from eukaryotes. In this paper, we compared the structures of PEM AGts with structures of eukaryotes and other AGts, and then built models of the representative PEM AGts and GT-1 glycosyltransferases. We also constructed the Neighbor-Joining (NJ) trees based on the normalized Root Mean Square (RMS) distance, the Bayesian tree guided by structural alignments, and carried out analysis on several key conserved residues in PEM AGts. The NJ tree showed a close relationship between PEM AGts and eukaryotic glycosyltransferases, and Bayesian tree further supported their affinity with UDP-glucuronosyltransferases (UGTs). Analysis on key conserved residues showed that PEM AGts may have similar interaction mechanism such as in the formation of hydrogen bonds as eukaryotic glycosyltransferases. Using structure-based phylogenetic approaches, this study further supported that PEM AGts were the result of HGT between prokaryotes and eukaryotes.     

The genetic basis of behavioral isolation between Drosophila mauritiana and D. sechellia

Understanding how species form is a fundamental question in evolutionary biology. Identifying the genetic bases of barriers that prevent gene flow between species provides insight into how speciation occurs. Here, I analyze a poorly understood reproductive isolating barrier, prezygotic reproductive isolation. I perform a genetic analysis of prezygotic isolation between two closely related species of Drosophila, D. mauritiana and D. sechellia. I first confirm the existence of strong behavioral isolation between D. mauritiana females and D. sechellia males. Next, I examine the genetic basis of behavioral isolation by (1) scanning an existing set of introgression lines for chromosomal regions that have a large effect on isolation; and (2) mapping quantitative trait loci (QTL) that underlie behavioral isolation via backcross analysis. In particular, I map QTL that determine whether a hybrid backcross female and a D. sechellia male will mate. I identify a single significant QTL, on the X chromosome, suggesting that few major-effect loci contribute to behavioral isolation between these species. In further work, I refine the map position of the QTL to a small region of the X chromosome.     

Systematic investigation of Amphioxus (Branchiostoma floridae) microRNAs

Ascaris lumbricoides and Ascaris suum are parasitic nematodes living in the small intestine of humans and pigs, and can cause the disease ascariasis. For long, there has been controversy as to whether the two ascaridoid taxa represent the same species due to their significant resemblances in morphology. However, the complete mitochondrial (mt) genome data have been lacking for A. lumbricoides in spite of human and animal health significance and socio-economic impact globally of these parasites. In the present study, we sequenced the complete mt genomes of A. lumbricoides and A. suum (China isolate), which was 14,303 bp and 14,311 bp in size, respectively. The identity of the mt genomes was 98.1% between A. lumbricoides and A. suum (China isolate), and 98.5% between A. suum (China isolate) and A. suum (USA isolate). Both genomes are circular, and consist of 36 genes, including 12 genes for proteins, 2 genes for rRNA and 22 genes for tRNA, which are consistent with that of all other species of ascaridoid studied to date. All genes are transcribed in the same direction and have a nucleotide composition high in A and T (71.7% for A. lumbricoides and 71.8% for A. suum). The AT bias had a significant effect on both the codon usage pattern and amino acid composition of proteins. Phylogenetic analyses of A. lumbricoides and A. suum using concatenated amino acid sequences of 12 protein-coding genes, with three different computational algorithms (Bayesian analysis, maximum likelihood and maximum parsimony) all clustered in a clade with high statistical support, indicating that A. lumbricoides and A. suum was very closely related. These mt genome data and the results provide some additional genetic evidence that A. lumbricoides and A. suum may represent the same species. The mt genome data presented in this study are also useful novel markers for studying the molecular epidemiology and population genetics of Ascaris.     

Information‐theoretic model selection affects home‐range estimation and habitat preference inference: a case study of male Reeves’s Pheasants Syrmaticus reevesii

Reeves’s Pheasant Syrmaticus reevesii is a vulnerable forest bird inhabiting broadleaved habitats dominated by oaks Quercus spp. in central China. Identifying home‐ranges and habitat associations is important for understanding the biology of this species and developing effective management and conservation plans. We used information‐theoretic criteria to evaluate the relative performance of four parametric (exponential power, one‐mode bivariate normal, two‐mode bivariate normal and two‐mode bivariate circle) and two non‐parametric models (adaptive and fixed kernel) for estimating home‐ranges and habitat associations of Reeves’s Pheasants. For parametric models, Akaike’s information criterion (AIC_c) and the likelihood cross‐validation criterion (CVC) were relatively consistent in ranking the bivariate exponential power model the least acceptable, whereas the two‐mode bivariate models performed better. The CVC suggested that kernel models, particularly the adaptive kernel, performed best among all six models evaluated. The average core area and 95% contour area based on the model with greatest support were 6.1 and 54.9 ha, respectively, and were larger than those estimated from other models. The discrepancy in estimates between models with highest and the lowest support decreased as the contour size increased; however, home‐range shapes differed between models. Minimum convex polygons that removed 5% of extreme data points (MCP95) were roughly half the size of home‐ranges based on kernel models. Estimates of home‐range and model evaluation were not affected by sample size (> 50 observations for each bird). Inference about habitat preference based on composition analysis and home‐range overlap varied between models. That with strongest support suggested that Reeves’s Pheasants selected mature fir and mixed forest, avoided farmland, and had mean among‐individual home‐range overlaps of 20%. We recommend non‐parametric methods, particularly the adaptive kernel method, for estimating home‐ranges and core areas for species with complex multi‐polar habitat preferences in heterogeneous environments with large habitat patches. However, we caution against the traditional convenience of using a single model to estimate home‐ranges and recommend exploration of multiple models for describing and understanding the ecological processes underlying space use and habitat associations.     

The species–area relationship in centipedes (Myriapoda: Chilopoda): a comparison between Mediterranean island groups

The present study article examines the shapes of centipede species–area relationships (SARs) in the Mediterranean islands, compares the results of the linear form of the power model between archipelagos, discusses biological significance of the power model parameters with other taxa on the Aegean archipelago, and tests for a significant small‐island effect (SIE). We used 11 models to test the SARs and we compared the quality‐of‐fit of all candidate models. The power function ranked first and Z‐values was in the range 0.106–0.334. We assessed the presence of SIEs by fitting both a continuous and discontinuous breakpoint regression model. The continuous breakpoint regression functions never performed much better than the closest discontinuous model as a predictor of centipede species richness. We suggest that the relatively low Z‐values in our data partly reflect better dispersal abilities in centipedes than in other soil invertebrate taxa. Longer periods of isolation and more recent island formation may explain the somewhat lower constant c in the western Mediterranean islands compared to the Aegean islands. Higher breakpoint values in the western Mediterranean may also be a result of larger distance to the mainland and longer separation times. Despite the differences in the geological history and the idiosyncratic features of the main island groups considered, the overall results are quite similar and this could be assigned to the ability of centipedes to disperse across isolation barriers. © 2011 The Linnean Society of London, Biological Journal of the Linnean Society, 2012, 105 , 146–159.     

Modelling seasonal increments in size to determine the onset of annual growth in fishes

A new method based on modelling of seasonal growth increments ( G _SI) in total length was found useful for assessing the date of onset of annual growth for 16 fish species in a temperate fluvial lake. Model comparisons indicated that polynomial (linear or quadratic) functions provided better fits to seasonal growth and were more likely to avoid convergence problems than alternative non-linear models. There was little evidence for differences in the date of onset of growth between years, nor among age classes within individual species. The onset of growth also was to some extent synchronized among species and was concentrated within a narrow temporal window of c. 2 weeks, between 18 May and 2 June, which corresponded to mean water temperatures between 16·1 and 17·3° C. There was no apparent relationship between date of onset and species' thermal preferenda or thermal preferences. By producing a point estimate along with appropriate 95% CI, the G _SI method provides useful information on the onset of growth and the uncertainty about that estimate. The G _SI analyses can contribute to a better understanding of environmental influences on the onset of growth and the length of the growing season, and of thermal thresholds for growth, including their use in calculation of degree-day metrics.     

Collective decision-making and behavioral polymorphism in group living organisms

Collective foraging in group living animal populations displaying behavioral polymorphism is considered. Using mathematical modeling it is shown that symmetric, spatially homogeneous (food sources are used equally) and asymmetric, spatially inhomogeneous (only one food source is used) regimes can coexist, as a result of differential amplification of choice depending on behavioral type. The model accounts for recent experimental results on social caterpillars not only confirming this coexistence, but also showing the relationship between the two types of regime and the ratio of active to inactive individuals.     

Expected utility violations evolve under status-based selection mechanisms

The expected utility theory of decision making under uncertainty, a cornerstone of modern economics, assumes that humans linearly weight “utilities” for different possible outcomes by the probabilities with which these outcomes occur. Despite the theory's intuitive appeal, both from normative and from evolutionary perspectives, many experiments demonstrate systematic, though poorly understood, patterns of deviation from EU predictions. This paper offers a novel theoretical account of such patterns of deviation by demonstrating that EU violations can emerge from evolutionary selection when individual “status” affects inclusive fitness. In humans, battles for resources and social standing involve high-stakes decision making, and assortative mating ensures that status matters for fitness outcomes. The paper therefore proposes grounding the study of decision making under uncertainty in an evolutionary game-theoretic framework.