Beyond brain size: Uncovering the neural correlates of behavioral and cognitive specialization

© Comparative Cognition Society. Despite prolonged interest in comparing brain size and behavioral proxies of "intelligence" across taxa, the adaptive and cognitive significance of brain size variation remains elusive. Central to this problem is the continued focus on hominid cognition as a benchmark and the assumption that behavioral complexity has a simple relationship with brain size. Although comparative studies of brain size have been criticized for not reflecting how evolution actually operates, and for producing spurious, inconsistent results, the causes of these limitations have received little discussion. We show how these issues arise from implicit assumptions about what brain size measures and how it correlates with behavioral and cognitive traits. We explore how inconsistencies can arise through heterogeneity in evolutionary trajectories and selection pressures on neuroanatomy or neurophysiology across taxa. We examine how interference from ecological and life history variables complicates interpretations of brain-behavior correlations and point out how this problem is exacerbated by the limitations of brain and cognitive measures. These considerations, and the diversity of brain morphologies and behavioral capacities, suggest that comparative brain-behavior research can make greater progress by focusing on specific neuroanatomical and behavioral traits within relevant ecological and evolutionary contexts. We suggest that a synergistic combination of the "bottom-up" approach of classical neuroethology and the "top-down" approach of comparative biology/psychology within closely related but behaviorally diverse clades can limit the effects of heterogeneity, interference, and noise. We argue that this shift away from broad-scale analyses of superficial phenotypes will provide deeper, more robust insights into brain evolution

Ingredients for understanding brain and behavioral evolution: Ecology, phylogeny, and mechanism

This is the final version of the article. Available from The Comparative Cognition Society via the DOI in this record.Uncovering the neural correlates and evolutionary drivers of behavioral and cognitive traits has been held back by traditional perspectives on which correlations to look for-in particular, anthropocentric conceptions of cognition and coarse-grained brain measurements. We welcome our colleagues' comments on our overview of the field and their suggestions for how to move forward. Here, we counter, clarify, and extend some points, focusing on the merits of looking for the "best" predictor of cognitive ability, the sources and meaning of "noise," and the ways in which we can deduce and test meaningful conclusions from comparative analyses of complex traits

Proteomic Profile of Reversible Protein Oxidation Using PROP, Purification of Reversibly Oxidized Proteins

Signal transduction pathways that are modulated by thiol oxidation events are beginning to be uncovered, but these discoveries are limited by the availability of relatively few analytical methods to examine protein oxidation compared to other signaling events such as protein phosphorylation. We report here the coupling of PROP, a method to purify reversibly oxidized proteins, with the proteomic identification of the purified mixture using mass spectrometry. A gene ontology (GO), KEGG enrichment and Wikipathways analysis of the identified proteins indicated a significant enrichment in proteins associated with both translation and mRNA splicing. This methodology also enabled the identification of some of the specific cysteine residue targets within identified proteins that are reversibly oxidized by hydrogen peroxide treatment of intact cells. From these identifications, we determined a potential consensus sequence motif associated with oxidized cysteine residues. Furthermore, because we identified proteins and specific sites of oxidation from both abundant proteins and from far less abundant signaling proteins (e.g. hepatoma derived growth factor, prostaglandin E synthase 3), the results suggest that the PROP procedure was efficient. Thus, this PROP-proteomics methodology offers a sensitive means to identify biologically relevant redox signaling events that occur within intact cells

Bayesian Orthogonal Least Squares (BOLS) algorithm for reverse engineering of gene regulatory networks

<p>Abstract</p> <p>Background</p> <p>A reverse engineering of gene regulatory network with large number of genes and limited number of experimental data points is a computationally challenging task. In particular, reverse engineering using linear systems is an underdetermined and ill conditioned problem, i.e. the amount of microarray data is limited and the solution is very sensitive to noise in the data. Therefore, the reverse engineering of gene regulatory networks with large number of genes and limited number of data points requires rigorous optimization algorithm.</p> <p>Results</p> <p>This study presents a novel algorithm for reverse engineering with linear systems. The proposed algorithm is a combination of the orthogonal least squares, second order derivative for network pruning, and Bayesian model comparison. In this study, the entire network is decomposed into a set of small networks that are defined as unit networks. The algorithm provides each unit network with P(D|H_i), which is used as confidence level. The unit network with higher P(D|H_i) has a higher confidence such that the unit network is correctly elucidated. Thus, the proposed algorithm is able to locate true positive interactions using P(D|H_i), which is a unique property of the proposed algorithm.</p> <p>The algorithm is evaluated with synthetic and <it>Saccharomyces cerevisiae </it>expression data using the dynamic Bayesian network. With synthetic data, it is shown that the performance of the algorithm depends on the number of genes, noise level, and the number of data points. With Yeast expression data, it is shown that there is remarkable number of known physical or genetic events among all interactions elucidated by the proposed algorithm.</p> <p>The performance of the algorithm is compared with Sparse Bayesian Learning algorithm using both synthetic and <it>Saccharomyces cerevisiae </it>expression data sets. The comparison experiments show that the algorithm produces sparser solutions with less false positives than Sparse Bayesian Learning algorithm.</p> <p>Conclusion</p> <p>From our evaluation experiments, we draw the conclusion as follows: 1) Simulation results show that the algorithm can be used to elucidate gene regulatory networks using limited number of experimental data points. 2) Simulation results also show that the algorithm is able to handle the problem with noisy data. 3) The experiment with Yeast expression data shows that the proposed algorithm reliably elucidates known physical or genetic events. 4) The comparison experiments show that the algorithm more efficiently performs than Sparse Bayesian Learning algorithm with noisy and limited number of data.</p

CyclinPred: A SVM-Based Method for Predicting Cyclin Protein Sequences

Functional annotation of protein sequences with low similarity to well characterized protein sequences is a major challenge of computational biology in the post genomic era. The cyclin protein family is once such important family of proteins which consists of sequences with low sequence similarity making discovery of novel cyclins and establishing orthologous relationships amongst the cyclins, a difficult task. The currently identified cyclin motifs and cyclin associated domains do not represent all of the identified and characterized cyclin sequences. We describe a Support Vector Machine (SVM) based classifier, CyclinPred, which can predict cyclin sequences with high efficiency. The SVM classifier was trained with features of selected cyclin and non cyclin protein sequences. The training features of the protein sequences include amino acid composition, dipeptide composition, secondary structure composition and PSI-BLAST generated Position Specific Scoring Matrix (PSSM) profiles. Results obtained from Leave-One-Out cross validation or jackknife test, self consistency and holdout tests prove that the SVM classifier trained with features of PSSM profile was more accurate than the classifiers based on either of the other features alone or hybrids of these features. A cyclin prediction server- CyclinPred has been setup based on SVM model trained with PSSM profiles. CyclinPred prediction results prove that the method may be used as a cyclin prediction tool, complementing conventional cyclin prediction methods

Looking on the bright side: biased attention and the human serotonin transporter gene

Humans differ in terms of biased attention for emotional stimuli and these biases can confer differential resilience and vulnerability to emotional disorders. Selective processing of positive emotional information, for example, is associated with enhanced sociability and well-being while a bias for negative material is associated with neuroticism and anxiety. A tendency to selectively avoid negative material might also be associated with mental health and well-being. The neurobiological mechanisms underlying these cognitive phenotypes are currently unknown. Here we show for the first time that allelic variation in the promotor region of the serotonin transporter gene (5-HTTLPR) is associated with differential biases for positive and negative affective pictures. Individuals homozygous for the long allele (LL) showed a marked bias to selectively process positive affective material alongside selective avoidance of negative affective material. This potentially protective pattern was absent among individuals carrying the short allele (S or SL). Thus, allelic variation on a common genetic polymorphism was associated with the tendency to selectively process positive or negative information. The current study is important in demonstrating a genotype-related alteration in a well-established processing bias, which is a known risk factor in determining both resilience and vulnerability to emotional disorders

Cell Cycle-Related Cyclin B1 Quantification

To obtain non-relative measures of cell proteins, purified preparations of the same proteins are used as standards in Western blots. We have previously quantified SV40 large T antigen expressed over a several fold range in different cell lines and correlated the average number of molecules to average fluorescence obtained by cytometry and determined cell cycle phase related expression by calculation from multi-parametric cytometry data. Using a modified approach, we report quantification of endogenous cyclin B1 and generation of the cell cycle time related expression profile.Recombinant cyclin B1 was purified from a baculovirus lysate using an antibody affinity column and concentrated. We created fixed cell preparations from nocodazole-treated (high cyclin B1) and serum starved (low cyclin B1) PC3 cells that were either lyophilized (for preservation) or solubilized. The lysates and purified cyclin B1 were subjected to Western blotting; the cell preparations were subjected to cytometry, and fluorescence was correlated to molecules. Three untreated cell lines (K562, HeLa, and RKO) were prepared for cytometry without lyophilization and also prepared for Western blotting. These were quantified by Western blotting and by cytometry using the standard cell preparations.The standard cell preparations had 1.5 x 10(5) to 2.5 x 10(6) molecules of cyclin B1 per cell on average (i.e., 16-fold range). The average coefficient of variation was 24%. Fluorescence varied 12-fold. The relationship between molecules/cell (Western blot) and immunofluorescence (cytometry) was linear (r(2) = 0.87). Average cyclin B1 levels for the three untreated cell lines determined by Western blotting and cytometry agreed within a factor of 2. The non-linear rise in cyclin B1 in S phase was quantified from correlated plots of cyclin B1 and DNA content. The peak levels achieved in G2 were similar despite differences in lineage, growth conditions, and rates of increase through the cell cycle (range: 1.6-2.2 x 10(6) molecules per cell).Net cyclin B1 expression begins in G1 in human somatic cells lines; increases non-linearly with variation in rates of accumulation, but peaks at similar peak values in different cell lines growing under different conditions. This suggests tight quantitative end point control

Cdc48 and Cofactors Npl4-Ufd1 Are Important for G1 Progression during Heat Stress by Maintaining Cell Wall Integrity in Saccharomyces cerevisiae

The ubiquitin-selective chaperone Cdc48, a member of the AAA (ATPase Associated with various cellular Activities) ATPase superfamily, is involved in many processes, including endoplasmic reticulum-associated degradation (ERAD), ubiquitin- and proteasome-mediated protein degradation, and mitosis. Although Cdc48 was originally isolated as a cell cycle mutant in the budding yeast Saccharomyces cerevisiae, its cell cycle functions have not been well appreciated. We found that temperature-sensitive cdc48-3 mutant is largely arrested at mitosis at 37°C, whereas the mutant is also delayed in G1 progression at 38.5°C. Reporter assays show that the promoter activity of G1 cyclin CLN1, but not CLN2, is reduced in cdc48-3 at 38.5°C. The cofactor npl4-1 and ufd1-2 mutants also exhibit G1 delay and reduced CLN1 promoter activity at 38.5°C, suggesting that Npl4-Ufd1 complex mediates the function of Cdc48 at G1. The G1 delay of cdc48-3 at 38.5°C is a consequence of cell wall defect that over-activates Mpk1, a MAPK family member important for cell wall integrity in response to stress conditions including heat shock. cdc48-3 is hypersensitive to cell wall perturbing agents and is synthetic-sick with mutations in the cell wall integrity signaling pathway. Our results suggest that the cell wall defect in cdc48-3 is exacerbated by heat shock, which sustains Mpk1 activity to block G1 progression. Thus, Cdc48-Npl4-Ufd1 is important for the maintenance of cell wall integrity in order for normal cell growth and division

Multisite Phosphorylation Provides an Effective and Flexible Mechanism for Switch-Like Protein Degradation

Phosphorylation-triggered degradation is a common strategy for elimination of regulatory proteins in many important cell signaling processes. Interesting examples include cyclin-dependent kinase inhibitors such as p27 in human and Sic1 in yeast, which play crucial roles during the G1/S transition in the cell cycle. In this work, we have modeled and analyzed the dynamics of multisite-phosphorylation-triggered protein degradation systematically. Inspired by experimental observations on the Sic1 protein and a previous intriguing theoretical conjecture, we develop a model to examine in detail the degradation dynamics of a protein featuring multiple phosphorylation sites and a threshold site number for elimination in response to a kinase signal. Our model explains the role of multiple phosphorylation sites, compared to a single site, in the regulation of protein degradation. A single-site protein cannot convert a graded input of kinase increase to much sharper output, whereas multisite phosphorylation is capable of generating a highly switch-like temporal profile of the substrate protein with two characteristics: a temporal threshold and rapid decrease beyond the threshold. We introduce a measure termed temporal response coefficient to quantify the extent to which a response in the time domain is switch-like and further investigate how this property is determined by various factors including the kinase input, the total number of sites, the threshold site number for elimination, the order of phosphorylation, the kinetic parameters, and site preference. Some interesting and experimentally verifiable predictions include that the non-degradable fraction of the substrate protein exhibits a more switch-like temporal profile; a sequential system is more switch-like, while a random system has the advantage of increased robustness; all the parameters, including the total number of sites, the threshold site number for elimination and the kinetic parameters synergistically determine the exact extent to which the degradation profile is switch-like. Our results suggest design principles for protein degradation switches which might be a widespread mechanism for precise regulation of cellular processes such as cell cycle progression

Evaluation of intracellular signalling pathways in response to insulin-like growth factor I in apoptotic-resistant activated human hepatic stellate cells

BACKGROUND: Human hepatic stellate cells have been shown to be resistant to apoptotic stimuli. This is likely dependent on the activation of anti-apoptotic pathways upon transition of these cells to myofibroblast-like cells. In particular, previous studies have demonstrated an increased expression of the anti-apoptotic protein Bcl-2 and a decreased expression of the pro-apoptotic protein Bax during the transition of the hepatic stellate cell phenotype from quiescent to myofibroblast-like cells. However, the role and expression of other key anti-apoptotic and survival pathways elicited by polypeptide growth factors involved in the chronic wound healing process remain to be elucidated. In particular, insulin growth factor-I promotes chemotactic and mitogenic effects in activated human hepatic stellate cells and these effects are mediated by the activation of PI 3-K. The role of insulin growth factor-I as a survival factor in human hepatic stellate cells needs to be substantiated. The aim of this study was to evaluate the involvement of other key anti-apoptotic pathways such as PI-3K/Akt/p-Bad in response to insulin growth factor-I. RESULTS: Insulin growth factor-I induced activation of Akt followed by Bad phosphorylation after 15 minutes of incubation. These effects were PI-3k dependent since selective inhibitors of this molecule, wortmannin and LY294002, inhibited both Akt and Bad phosphorylation. The effect of insulin growth factor-I on the activation of two downstream targets of Akt activation, that is, GSK3 and FHKR, both implicated in the promotion of cell survival was also investigated. Both targets became phosphorylated after 15 minutes of incubation, and these effects were also PI-3K-dependent. Despite the activation of this survival pathway insulin growth factor-I did not have a remarkable biological effect, probably because other insulin growth factor-I-independent survival pathways were already maximally activated in the process of hepatic stellate cell activation. However, after incubation of the cells with a strong apoptotic stimuli such as Fas ligand+cycloheximide, a small percentage of hepatic stellate cells underwent programmed cell death that was partially rescued by insulin growth factor-I. CONCLUSION: In addition to Bcl-2, several other anti-apoptotic pathways are responsible for human hepatic stellate cell resistance to apoptosis. These features are relevant for the progression and limited reversibility of liver fibrosis in humans