pH-Dependent Conformational Changes in Proteins and Their Effect on Experimental pKas: The Case of Nitrophorin 4

The acid-base behavior of amino acids is an important subject of study due to their prominent role in enzyme catalysis, substrate binding and protein structure. Due to interactions with the protein environment, their pK_as can be shifted from their solution values and, if a protein has two stable conformations, it is possible for a residue to have different “microscopic”, conformation-dependent pK_a values. In those cases, interpretation of experimental measurements of the pK_a is complicated by the coupling between pH, protonation state and protein conformation. We explored these issues using Nitrophorin 4 (NP4), a protein that releases NO in a pH sensitive manner. At pH 5.5 NP4 is in a closed conformation where NO is tightly bound, while at pH 7.5 Asp30 becomes deprotonated, causing the conformation to change to an open state from which NO can easily escape. Using constant pH molecular dynamics we found two distinct microscopic Asp30 pK_as: 8.5 in the closed structure and 4.3 in the open structure. Using a four-state model, we then related the obtained microscopic values to the experimentally observed “apparent” pK_a, obtaining a value of 6.5, in excellent agreement with experimental data. This value must be interpreted as the pH at which the closed to open population transition takes place. More generally, our results show that it is possible to relate microscopic structure dependent pKa values to experimentally observed ensemble dependent apparent pK_as and that the insight gained in the relatively simple case of NP4 can be useful in several more complex cases involving a pH dependent transition, of great biochemical interest.     

Quality of computationally inferred gene ontology annotations

Gene Ontology (GO) has established itself as the undisputed standard for protein function annotation. Most annotations are inferred electronically, i.e. without individual curator supervision, but they are widely considered unreliable. At the same time, we crucially depend on those automated annotations, as most newly sequenced genomes are non-model organisms. Here, we introduce a methodology to systematically and quantitatively evaluate electronic annotations. By exploiting changes in successive releases of the UniProt Gene Ontology Annotation database, we assessed the quality of electronic annotations in terms of specificity, reliability, and coverage. Overall, we not only found that electronic annotations have significantly improved in recent years, but also that their reliability now rivals that of annotations inferred by curators when they use evidence other than experiments from primary literature. This work provides the means to identify the subset of electronic annotations that can be relied upon-an important outcome given that >98% of all annotations are inferred without direct curation.     

Temporal Expression of Bacterial Proteins Instructs Host CD4 T Cell Expansion and Th17 Development

Pathogens can substantially alter gene expression within an infected host depending on metabolic or virulence requirements in different tissues, however, the effect of these alterations on host immunity are unclear. Here we visualized multiple CD4 T cell responses to temporally expressed proteins in Salmonella-infected mice. Flagellin-specific CD4 T cells expanded and contracted early, differentiated into Th1 and Th17 lineages, and were enriched in mucosal tissues after oral infection. In contrast, CD4 T cells responding to Salmonella Type-III Secretion System (TTSS) effectors steadily accumulated until bacterial clearance was achieved, primarily differentiated into Th1 cells, and were predominantly detected in systemic tissues. Thus, pathogen regulation of antigen expression plays a major role in orchestrating the expansion, differentiation, and location of antigen-specific CD4 T cells in vivo.     

Does prey size matter? Novel observations of feeding in the leatherback turtle (Dermochelys coriacea) allow a test of predator–prey size relationships

Optimal foraging models predict that large predators should concentrate on large prey in order to maximize their net gain of energy intake. Here, we show that the largest species of sea turtle, Dermochelys coriacea, does not strictly adhere to this general pattern. Field observations combined with a theoretical model suggest that a 300 kg leatherback turtle would meet its energetic requirements by feeding for 3-4 h a day on 4 g jellyfish, but only if prey were aggregated in high-density patches. Therefore, prey abundance rather than prey size may, in some cases, be the overriding parameter for foraging leatherbacks. This is a classic example where the presence of small prey in the diet of a large marine predator may reflect profitable foraging decisions if the relatively low energy intake per small individual prey is offset by high encounter rates and minimal capture and handling costs. This study provides, to our knowledge, the first quantitative estimates of intake rate for this species.     

A program for annotating and predicting the effects of single nucleotide polymorphisms, SnpEff: SNPs in the genome of Drosophila melanogaster strain w1118; iso-2; iso-3

We describe a new computer program, SnpEff, for rapidly categorizing the effects of variants in genome sequences. Once a genome is sequenced, SnpEff annotates variants based on their genomic locations and predicts coding effects. Annotated genomic locations include intronic, untranslated region, upstream, downstream, splice site, or intergenic regions. Coding effects such as synonymous or non-synonymous amino acid replacement, start codon gains or losses, stop codon gains or losses, or frame shifts can be predicted. Here the use of SnpEff is illustrated by annotating ~356,660 candidate SNPs in ~117 Mb unique sequences, representing a substitution rate of ~1/305 nucleotides, between the Drosophila melanogaster w(1118); iso-2; iso-3 strain and the reference y(1); cn(1) bw(1) sp(1) strain. We show that ~15,842 SNPs are synonymous and ~4,467 SNPs are non-synonymous (N/S ~0.28). The remaining SNPs are in other categories, such as stop codon gains (38 SNPs), stop codon losses (8 SNPs), and start codon gains (297 SNPs) in the 5'UTR. We found, as expected, that the SNP frequency is proportional to the recombination frequency (i.e., highest in the middle of chromosome arms). We also found that start-gain or stop-lost SNPs in Drosophila melanogaster often result in additions of N-terminal or C-terminal amino acids that are conserved in other Drosophila species. It appears that the 5' and 3' UTRs are reservoirs for genetic variations that changes the termini of proteins during evolution of the Drosophila genus. As genome sequencing is becoming inexpensive and routine, SnpEff enables rapid analyses of whole-genome sequencing data to be performed by an individual laboratory.     

Proliferating CD4+ T cells undergo immediate growth arrest upon cessation of TCR signaling in vivo

To investigate the role of TCR signaling in the exit of CD4+ T cells from cell cycle, we took advantage of a low frequency TEa T cell adoptive transfer technique as well as the Y-Ae mAb to interrupt Ag/MHC recognition before the completion of clonal expansion. Termination of TCR signaling after 36 h of Ag exposure caused an immediate reduction in cell size and deceleration of G1->SG2M phase cell cycle progression. As a consequence, clonal expansion in the absence of durable TCR signaling decreased by two-thirds. Thus, CD4+ T cells scan for the presence Ag throughout their clonal expansion response, and continuously adjust their rate of cell growth and G1->S phase transition to match their intensity of TCR signaling.     

Computational studies reveal phosphorylation-dependent changes in the unstructured R domain of CFTR

The cystic fibrosis transmembrane conductance regulator (CFTR) is a cAMP-dependent chloride channel that is mutated in cystic fibrosis, an inherited disease of high morbidity and mortality. The phosphorylation of its ∼ 200 amino acid R domain by protein kinase A is obligatory for channel gating under normal conditions. The R domain contains more than ten PKA phosphorylation sites. No individual site is essential but phosphorylation of increasing numbers of sites enables progressively greater channel activity. In spite of numerous studies of the role of the R domain in CFTR regulation, its mechanism of action remains largely unknown. This is because neither its structure nor its interactions with other parts of CFTR have been completely elucidated. Studies have shown that the R domain lacks well-defined secondary structural elements and is an intrinsically disordered region of the channel protein. Here, we have analyzed the disorder pattern and employed computational methods to explore low-energy conformations of the R domain. The specific disorder and secondary structure patterns detected suggest the presence of molecular recognition elements (MoREs) that may mediate phosphorylation-regulated intra- and inter-domain interactions. Simulations were performed to generate an ensemble of accessible R domain conformations. Although the calculated structures may represent more compact conformers than occur in vivo, their secondary structure propensities are consistent with predictions and published experimental data. Equilibrium simulations of a mimic of a phosphorylated R domain showed that it exhibited an increased radius of gyration. In one possible interpretation of these findings, by changing its size, the globally unstructured R domain may act as an entropic spring to perturb the packing of membrane-spanning sequences that constitute the ion permeability pathway and thereby activate channel gating.