A numerical model for the oxygenation of blood in lung capillaries--effect of nth order one-step kinetics of oxygen uptake by haemoglobin

A numerical model is described for the oxygenation of blood in lung capillaries by considering the transport mechanisms of molecular diffusion, convection and the facilitated diffusion due to the presence of haemoglobin. In order to represent the oxygen dissociation curve accurately in the model, the nth order one-step kinetics of oxygen uptake by haemoglobin has been used. The resulting system of coupled, non-linear partial differential equations is solved numerically. It is shown that the blood is required to traverse a larger distance in the capillary before becoming fully oxygenated with nth order one-step kinetics in comparison to first-order one-step kinetics.     

Translation efficiency in humans: tissue specificity,global optimization and differences between developmental stages

Various studies in unicellular and multicellular organisms have shown that codon bias plays a significant role in translation efficiency (TE) by co-adaptation to the tRNA pool. Yet, in humans and other mammals the role of codon bias is still an open question, with contradictory results from different studies. Here we address this question, performing a large-scale tissue-specific analysis of TE in humans, using the tRNA Adaptation Index (tAI) as a direct measure for TE. We find tAI to significantly correlate with expression levels both in tissue-specific and in global expression measures, testifying to the TE of human tissues. Interestingly, we find significantly higher correlations in adult tissues as opposed to fetal tissues, suggesting that the tRNA pool is more adjusted to the adult period. Optimization based analysis suggests that the tRNA pool—codon bias co-adaptation is globally (and not tissue-specific) driven. Additionally, we find that tAI correlates with several measures related to the protein functionally importance, including gene essentiality. Using inferred tissue-specific tRNA pools lead to similar results and shows that tissue-specific genes are more adapted to their tRNA pool than other genes and that related sets of functional gene groups are translated efficiently in each tissue. Similar results are obtained for other mammals. Taken together, these results demonstrate the role of codon bias in TE in humans, and pave the way for future studies of tissue-specific TE in multicellular organisms.     

Network-Free Inference of Knockout Effects in Yeast

Perturbation experiments, in which a certain gene is knocked out and the expression levels of other genes are observed, constitute a fundamental step in uncovering the intricate wiring diagrams in the living cell and elucidating the causal roles of genes in signaling and regulation. Here we present a novel framework for analyzing large cohorts of gene knockout experiments and their genome-wide effects on expression levels. We devise clustering-like algorithms that identify groups of genes that behave similarly with respect to the knockout data, and utilize them to predict knockout effects and to annotate physical interactions between proteins as inhibiting or activating. Differing from previous approaches, our prediction approach does not depend on physical network information; the latter is used only for the annotation task. Consequently, it is both more efficient and of wider applicability than previous methods. We evaluate our approach using a large scale collection of gene knockout experiments in yeast, comparing it to the state-of-the-art SPINE algorithm. In cross validation tests, our algorithm exhibits superior prediction accuracy, while at the same time increasing the coverage by over 25-fold. Significant coverage gains are obtained also in the annotation of the physical network.     

Molecular chaperones DnaK and DnaJ share predicted binding sites on most proteins in the E. coli proteome

In Escherichia coli, the molecular chaperones DnaK and DnaJ cooperate to assist the folding of newly synthesized or unfolded polypeptides. DnaK and DnaJ bind to hydrophobic motifs in these proteins and they also bind to each other. Together, this system is thought to be sufficiently versatile to act on the entire proteome, which creates interesting challenges in understanding the interactions between DnaK, DnaJ and their thousands of potential substrates. To address this question, we computationally predicted the number and frequency of DnaK- and DnaJ-binding motifs in the E. coli proteome, guided by free energy-based binding consensus motifs. This analysis revealed that nearly every protein is predicted to contain multiple DnaK- and DnaJ-binding sites, with the DnaJ sites occurring approximately twice as often. Further, we found that an overwhelming majority of the DnaK sites partially or completely overlapped with the DnaJ-binding motifs. It is well known that high concentrations of DnaJ inhibit DnaK-DnaJ-mediated refolding. The observed overlapping binding sites suggest that this phenomenon may be explained by an important balance in the relative stoichiometry of DnaK and DnaJ. To test this idea, we measured the chaperone-assisted folding of two denatured substrates and found that the distribution of predicted DnaK- and DnaJ-binding sites was indeed a good predictor of the optimal stoichiometry required for folding. These studies provide insight into how DnaK and DnaJ might cooperate to maintain global protein homeostasis.     

RNA Splicing Is Responsive to MBNL1 Dose

Myotonic dystrophy (DM1) is a highly variable, multi-system disorder resulting from the expansion of an untranslated CTG tract in DMPK. In DM1 expanded CUG repeat RNAs form hairpin secondary structures that bind and aberrantly sequester the RNA splice regulator, MBNL1. RNA splice defects resulting as a consequence of MBNL1 depletion have been shown to play a key role in the development of DM1 pathology. In patient populations, both the number and severity of DM1 symptoms increase broadly as a function of CTG tract length. However significant variability in the DM1 phenotype is observed in patients encoding similar CTG repeat numbers. Here we demonstrate that a gradual decrease in MBNL1 levels results both in the expansion of the repertoire of splice defects and an increase in the severity of the splice alterations. Thus, MBNL1 loss does not have an all or none outcome but rather shows a graded effect on the number and severity of the ensuing splice defects. Our results suggest that once a critical threshold is reached, relatively small dose variations of free MBNL1 levels, which may reflect modest changes in the size of the CUG tract or the extent of hairpin secondary structure formation, can significantly alter the number and severity of splice abnormalities and thus contribute to the phenotype variability observed in DM1 patients.