Cross-adaptation and molecular modeling study of receptor mechanisms common to four taste stimuli in humans

Psychophysical cross-adaptation experiments were performed with two carbohydrates, sucrose (SUC) and fructose (FRU), and two sweeteners, acesulfame-K (MOD) and dulcin (DUL). Seven subjects were asked to match concentrations that elicited the same intensity as a sucrose reference (30 g/l). Cross-adaptation levels were calculated as the ratio of isointense concentrations measured for a given stimulus before and under adaptation. On average, cross-adaptation between SUC and FRU is low and apparently reciprocal. By contrast, cross-adaptation between SUC and MOD is clearly non-reciprocal: SUC adapts MOD significantly (24%, P < 0.005), but MOD fails to adapt SUC (2%, P < 0.79). Significant and reciprocal cross-enhancement is observed between DUL and MOD (approximately -20%, P < 0.03), and also between SUC and DUL (approximately -15%, P < 0.08). In parallel, molecular modeling of the four tastants was performed in order to look for the 12 common binding motifs that were isolated on 14 other tastants in a previous study. SUC and FRU each display 10 out of the 12 binding motifs, whereas DUL and MOD only display four and five distinct motifs respectively and do not have any motif in common. Experimental cross-adaptation levels seem to correlate well with the number of motifs that molecules have in common. FRU and SUC share a majority of binding motifs and correlatively show mutual cross-adaptation. Four motifs of MOD are found among the 10 motifs of SUC, which may explain why SUC cross-adapts MOD but not vice versa. By contrast, DUL and MOD do not share any motif and do not cross- adapt. The various molecular mechanisms that may be responsible for cross-adaptation and/or cross-enhancement are discussed in light of our results.      

An approach to large scale identification of non-obvious structural similarities between proteins

Background

A new sequence independent bioinformatics approach allowing genome-wide search for proteins with similar three dimensional structures has been developed. By utilizing the numerical output of the sequence threading it establishes putative non-obvious structural similarities between proteins. When applied to the testing set of proteins with known three dimensional structures the developed approach was able to recognize structurally similar proteins with high accuracy.

Results

The method has been developed to identify pathogenic proteins with low sequence identity and high structural similarity to host analogues. Such protein structure relationships would be hypothesized to arise through convergent evolution or through ancient horizontal gene transfer events, now undetectable using current sequence alignment techniques. The pathogen proteins, which could mimic or interfere with host activities, would represent candidate virulence factors.The developed approach utilizes the numerical outputs from the sequence-structure threading. It identifies the potential structural similarity between a pair of proteins by correlating the threading scores of the corresponding two primary sequences against the library of the standard folds. This approach allowed up to 64% sensitivity and 99.9% specificity in distinguishing protein pairs with high structural similarity.

Conclusion

Preliminary results obtained by comparison of the genomes of Homo sapiens and several strains of Chlamydia trachomatis have demonstrated the potential usefulness of the method in the identification of bacterial proteins with known or potential roles in virulence.

     

The Interplay among Acorn Abundance and Rodent Behavior Drives the Spatial Pattern of Seedling Recruitment in Mature Mediterranean Oak Forests

The patterns of seedling recruitment in animal-dispersed plants result from the interactions among environmental and behavioral variables. However, we know little on the contribution and combined effect of both kinds of variables. We designed a field study to assess the interplay between environment (vegetation structure, seed abundance, rodent abundance) and behavior (seed dispersal and predation by rodents, and rooting by wild boars), and their contribution to the spatial patterns of seedling recruitment in a Mediterranean mixed-oak forest. In a spatially explicit design, we monitored intensively all environmental and behavioral variables in fixed points at a small spatial scale from autumn to spring, as well as seedling emergence and survival. Our results revealed that the spatial patterns of seedling emergence were strongly related to acorn availability on the ground, but not by a facilitationeffect of vegetation cover. Rodents changed seed shadows generated by mother trees by dispersing most seeds from shrubby to open areas, but the spatial patterns of acorn dispersal/predation had no direct effect on recruitment. By contrast, rodents had a strong impact on recruitment as pilferers of cached seeds. Rooting by wild boars also reduced recruitment by reducing seed abundance, but also by changing rodent’s behavior towards higher consumption of acorns in situ. Hence, seed abundance and the foraging behavior of scatter-hoarding rodents and wild boars are driving the spatial patterns of seedling recruitment in this mature oak forest, rather than vegetation features. The contribution of vegetation to seedling recruitment (e.g. facilitation by shrubs) may be context dependent, having a little role in closed forests, or being overridden by directed seed dispersal from shrubby to open areas. We warn about the need of using broad approaches that consider the combined action of environment and behavior to improve our knowledge on the dynamics of natural regeneration in forests.     

A GWAS assessment of the contribution of genomic imprinting to the variation of body mass index in mice

Background

Genomic imprinting is an epigenetic mechanism that can lead to differential gene expression depending on the parent-of-origin of a received allele. While most studies on imprinting address its underlying molecular mechanisms or attempt at discovering genomic regions that might be subject to imprinting, few have focused on the amount of phenotypic variation contributed by such epigenetic process. In this report, we give a brief review of a one-locus imprinting model in a quantitative genetics framework, and provide a decomposition of the genetic variance according to this model. Analytical deductions from the proposed imprinting model indicated a non-negligible contribution of imprinting to genetic variation of complex traits. Also, we performed a whole-genome scan analysis on mouse body mass index (BMI) aiming at revealing potential consequences when existing imprinting effects are ignored in genetic analysis.

Results

10,021 SNP markers were used to perform a whole-genome single marker regression on mouse BMI using an additive and an imprinting model. Markers significant for imprinting indicated that BMI is subject to imprinting. Marked variance changed from 1.218 ×10⁻⁴ to 1.842 ×10⁻⁴ when imprinting was considered in the analysis, implying that one third of marked variance would be lost if existing imprinting effects were not accounted for. When both marker and pedigree information were used, estimated heritability increased from 0.176 to 0.195 when imprinting was considered.

Conclusions

When a complex trait is subject to imprinting, using an additive model that ignores this phenomenon may result in an underestimate of additive variability, potentially leading to wrong inferences about the underlying genetic architecture of that trait. This could be a possible factor explaining part of the missing heritability commonly observed in genome-wide association studies (GWAS).     

Deficiency in the mitochondrial apoptotic pathway reveals the toxic potential of autophagy under ER stress conditions

Endoplasmic reticulum (ER) stress-induced cell death is normally associated with activation of the mitochondrial apoptotic pathway, which is characterized by CYCS (cytochrome c, somatic) release, apoptosome formation, and caspase activation, resulting in cell death. In this study, we demonstrate that under conditions of ER stress cells devoid of CASP9/caspase-9 or BAX and BAK1, and therefore defective in the mitochondrial apoptotic pathway, still undergo a delayed form of cell death associated with the activation of caspases, therefore revealing the existence of an alternative stress-induced caspase activation pathway. We identified CASP8/caspase-8 as the apical protease in this caspase cascade, and found that knockdown of either of the key autophagic genes, ATG5 or ATG7, impacted on CASP8 activation and cell death induction, highlighting the crucial role of autophagy in the activation of this novel ER stress-induced death pathway. In line with this, we identified a protein complex composed of ATG5, FADD, and pro-CASP8 whose assembly coincides with caspase activation and cell death induction. Together, our results reveal the toxic potential of autophagy in cells undergoing ER stress that are defective in the mitochondrial apoptotic pathway, and suggest a model in which the autophagosome functions as a platform facilitating pro-CASP8 activation. Chemoresistance, a common problem in the treatment of cancer, is frequently caused by the downregulation of key mitochondrial death effector proteins. Alternate stress-induced apoptotic pathways, such as the one described here, may become of particular relevance for tackling the problem of chemoresistance in cancer cells.     

An improved formulation of the zirconyl hematoxylin stain for acidic mucins

Zirconyl hematoxylin stains acidic mucins darkly and specifically using a solution of 100 mg hematoxylin, 5 ml ethanol, 5 ml 0.5% sodium iodate, 400 mg zirconyl chloride octahydrate, and 30 ml 25% aqueous glycerol. The stain is especially advantageous for studying goblet cells and Paget cells.     

Prolonged cigarette smoke exposure alters mitochondrial structure and function in airway epithelial cells

Background

Cigarette smoking is the major risk factor for COPD, leading to chronic airway inflammation. We hypothesized that cigarette smoke induces structural and functional changes of airway epithelial mitochondria, with important implications for lung inflammation and COPD pathogenesis.

Methods

We studied changes in mitochondrial morphology and in expression of markers for mitochondrial capacity, damage/biogenesis and fission/fusion in the human bronchial epithelial cell line BEAS-2B upon 6-months from ex-smoking COPD GOLD stage IV patients to age-matched smoking and never-smoking controls.

Results

We observed that long-term CSE exposure induces robust changes in mitochondrial structure, including fragmentation, branching and quantity of cristae. The majority of these changes were persistent upon CSE depletion. Furthermore, long-term CSE exposure significantly increased the expression of specific fission/fusion markers (Fis1, Mfn1, Mfn2, Drp1 and Opa1), oxidative phosphorylation (OXPHOS) proteins (Complex II, III and V), and oxidative stress (Mn-SOD) markers. These changes were accompanied by increased levels of the pro-inflammatory mediators IL-6, IL-8, and IL-1β. Importantly, COPD primary bronchial epithelial cells (PBECs) displayed similar changes in mitochondrial morphology as observed in long-term CSE-exposure BEAS-2B cells. Moreover, expression of specific OXPHOS proteins was higher in PBECs from COPD patients than control smokers, as was the expression of mitochondrial stress marker PINK1.

Conclusion

The observed mitochondrial changes in COPD epithelium are potentially the consequence of long-term exposure to cigarette smoke, leading to impaired mitochondrial function and may play a role in the pathogenesis of COPD.     

What does biologically meaningful mean? A perspective on gene regulatory network validation

Gene regulatory networks (GRNs) are rapidly being delineated, but their quality and biological meaning are often questioned. Here, I argue that biological meaning is challenging to define and discuss reasons why GRN validation should be interpreted cautiously.     

Predicting expected progeny difference for marbling score in Angus cattle using artificial neural networks and Bayesian regression models

Background

Artificial neural networks (ANN) mimic the function of the human brain and are capable of performing massively parallel computations for data processing and knowledge representation. ANN can capture nonlinear relationships between predictors and responses and can adaptively learn complex functional forms, in particular, for situations where conventional regression models are ineffective. In a previous study, ANN with Bayesian regularization outperformed a benchmark linear model when predicting milk yield in dairy cattle or grain yield of wheat. Although breeding values rely on the assumption of additive inheritance, the predictive capabilities of ANN are of interest from the perspective of their potential to increase the accuracy of prediction of molecular breeding values used for genomic selection. This motivated the present study, in which the aim was to investigate the accuracy of ANN when predicting the expected progeny difference (EPD) of marbling score in Angus cattle. Various ANN architectures were explored, which involved two training algorithms, two types of activation functions, and from 1 to 4 neurons in hidden layers. For comparison, BayesCπ models were used to select a subset of optimal markers (referred to as feature selection), under the assumption of additive inheritance, and then the marker effects were estimated using BayesCπ with π set equal to zero. This procedure is referred to as BayesCpC and was implemented on a high-throughput computing cluster.

Results

The ANN with Bayesian regularization method performed equally well for prediction of EPD as BayesCpC, based on prediction accuracy and sum of squared errors. With the 3K-SNP panel, for example, prediction accuracy was 0.776 using BayesCpC, and ranged from 0.776 to 0.807 using BRANN. With the selected 700-SNP panel, prediction accuracy was 0.863 for BayesCpC and ranged from 0.842 to 0.858 for BRANN. However, prediction accuracy for the ANN with scaled conjugate gradient back-propagation was lower, ranging from 0.653 to 0.689 with the 3K-SNP panel, and from 0.743 to 0.793 with the selected 700-SNP panel.

Conclusions

ANN with Bayesian regularization performed as well as linear Bayesian regression models in predicting additive genetic values, supporting the idea that ANN are useful as universal approximators of functions of interest in breeding contexts.