Investigating Homology between Proteins using Energetic Profiles

Accumulated experimental observations demonstrate that protein stability is often preserved upon conservative point mutation. In contrast, less is known about the effects of large sequence or structure changes on the stability of a particular fold. Almost completely unknown is the degree to which stability of different regions of a protein is generally preserved throughout evolution. In this work, these questions are addressed through thermodynamic analysis of a large representative sample of protein fold space based on remote, yet accepted, homology. More than 3,000 proteins were computationally analyzed using the structural-thermodynamic algorithm COREX/BEST. Estimated position-specific stability (i.e., local Gibbs free energy of folding) and its component enthalpy and entropy were quantitatively compared between all proteins in the sample according to all-vs.-all pairwise structural alignment. It was discovered that the local stabilities of homologous pairs were significantly more correlated than those of non-homologous pairs, indicating that local stability was indeed generally conserved throughout evolution. However, the position-specific enthalpy and entropy underlying stability were less correlated, suggesting that the overall regional stability of a protein was more important than the thermodynamic mechanism utilized to achieve that stability. Finally, two different types of statistically exceptional evolutionary structure-thermodynamic relationships were noted. First, many homologous proteins contained regions of similar thermodynamics despite localized structure change, suggesting a thermodynamic mechanism enabling evolutionary fold change. Second, some homologous proteins with extremely similar structures nonetheless exhibited different local stabilities, a phenomenon previously observed experimentally in this laboratory. These two observations, in conjunction with the principal conclusion that homologous proteins generally conserved local stability, may provide guidance for a future thermodynamically informed classification of protein homology

Biogenesis and functions of bacterial S-layers.

The outer surface of many archaea and bacteria is coated with a proteinaceous surface layer (known as an S-layer), which is formed by the self-assembly of monomeric proteins into a regularly spaced, two-dimensional array. Bacteria possess dedicated pathways for the secretion and anchoring of the S-layer to the cell wall, and some Gram-positive species have large S-layer-associated gene families. S-layers have important roles in growth and survival, and their many functions include the maintenance of cell integrity, enzyme display and, in pathogens and commensals, interaction with the host and its immune system. In this Review, we discuss our current knowledge of S-layer and related proteins, including their structures, mechanisms of secretion and anchoring and their diverse functions

Mild gestational diabetes in pregnancy and the adipoinsular axis in babies born to mothers in the ACHOIS randomised controlled trial

BACKGROUND: Mild gestational diabetes is a common complication of pregnancy, affecting up to 9% of pregnant women. Treatment of mild GDM is known to reduce adverse perinatal outcomes such as macrosomia and associated birth injuries, such as shoulder dystocia, bone fractures and nerve palsies. This study aimed to compare the plasma glucose concentrations and serum insulin, leptin and adiponectin in cord blood of babies of women (a) without gestational diabetes mellitus (GDM), (b) with mild GDM under routine care, or (c) mild GDM with treatment. METHODS: 95 women with mild GDM on oral glucose tolerance testing (OGTT) at one tertiary level maternity hospital who had been recruited to the ACHOIS trial at one of the collaborating hospitals and randomised to either Treatment (n = 46) or Routine Care (n = 49) and Control women with a normal OGTT (n = 133) were included in the study. Women with mild GDM (treatment or routine care group) and OGTT normal women received routine pregnancy care. In addition, women with treated mild GDM received dietary advice, blood glucose monitoring and insulin if necessary. The primary outcome measures were cord blood concentrations of glucose, insulin, adiponectin and leptin. RESULTS: Cord plasma glucose was higher in women receiving routine care compared with control, but was normalized by treatment for mild GDM (p = 0.01). Cord serum insulin and insulin to glucose ratio were similar between the three groups. Leptin concentration in cord serum was lower in GDM treated women compared with routine care (p = 0.02) and not different to control (p = 0.11). Adiponectin was lower in both mild GDM groups compared with control (Treatment p = 0.02 and Routine Care p = 0.07), while the adiponectin to leptin ratio was lower for women receiving routine care compared with treatment (p = 0.08) and control (p = 0.05). CONCLUSION: Treatment of women with mild GDM using diet, blood glucose monitoring and insulin if necessary, influences the altered fetal adipoinsular axis characteristic of mild GDM in pregnancy

Genetic diversity of the African malaria vector Anopheles gambiae

The sustainability of malaria control in Africa is threatened by the rise of insecticide resistance in Anopheles mosquitoes, which transmit the disease1. To gain a deeper understanding of how mosquito populations are evolving, here we sequenced the genomes of 765 specimens of Anopheles gambiae and Anopheles coluzzii sampled from 15 locations across Africa, and identified over 50 million single nucleotide polymorphisms within the accessible genome. These data revealed complex population structure and patterns of gene flow, with evidence of ancient expansions, recent bottlenecks, and local variation in effective population size. Strong signals of recent selection were observed in insecticide-resistance genes, with several sweeps spreading over large geographical distances and between species. The design of new tools for mosquito control using gene-drive systems will need to take account of high levels of genetic diversity in natural mosquito populations

Change in Allosteric Network Affects Binding Affinities of PDZ Domains: Analysis through Perturbation Response Scanning

The allosteric mechanism plays a key role in cellular functions of several PDZ domain proteins (PDZs) and is directly linked to pharmaceutical applications; however, it is a challenge to elaborate the nature and extent of these allosteric interactions. One solution to this problem is to explore the dynamics of PDZs, which may provide insights about how intramolecular communication occurs within a single domain. Here, we develop an advancement of perturbation response scanning (PRS) that couples elastic network models with linear response theory (LRT) to predict key residues in allosteric transitions of the two most studied PDZs (PSD-95 PDZ3 domain and hPTP1E PDZ2 domain). With PRS, we first identify the residues that give the highest mean square fluctuation response upon perturbing the binding sites. Strikingly, we observe that the residues with the highest mean square fluctuation response agree with experimentally determined residues involved in allosteric transitions. Second, we construct the allosteric pathways by linking the residues giving the same directional response upon perturbation of the binding sites. The predicted intramolecular communication pathways reveal that PSD-95 and hPTP1E have different pathways through the dynamic coupling of different residue pairs. Moreover, our analysis provides a molecular understanding of experimentally observed hidden allostery of PSD-95. We show that removing the distal third alpha helix from the binding site alters the allosteric pathway and decreases the binding affinity. Overall, these results indicate that (i) dynamics plays a key role in allosteric regulations of PDZs, (ii) the local changes in the residue interactions can lead to significant changes in the dynamics of allosteric regulations, and (iii) this might be the mechanism that each PDZ uses to tailor their binding specificities regulation

Structure-Based Predictive Models for Allosteric Hot Spots

In allostery, a binding event at one site in a protein modulates the behavior of a distant site. Identifying residues that relay the signal between sites remains a challenge. We have developed predictive models using support-vector machines, a widely used machine-learning method. The training data set consisted of residues classified as either hotspots or non-hotspots based on experimental characterization of point mutations from a diverse set of allosteric proteins. Each residue had an associated set of calculated features. Two sets of features were used, one consisting of dynamical, structural, network, and informatic measures, and another of structural measures defined by Daily and Gray [1]. The resulting models performed well on an independent data set consisting of hotspots and non-hotspots from five allosteric proteins. For the independent data set, our top 10 models using Feature Set 1 recalled 68–81% of known hotspots, and among total hotspot predictions, 58–67% were actual hotspots. Hence, these models have precision P = 58–67% and recall R = 68–81%. The corresponding models for Feature Set 2 had P = 55–59% and R = 81–92%. We combined the features from each set that produced models with optimal predictive performance. The top 10 models using this hybrid feature set had R = 73–81% and P = 64–71%, the best overall performance of any of the sets of models. Our methods identified hotspots in structural regions of known allosteric significance. Moreover, our predicted hotspots form a network of contiguous residues in the interior of the structures, in agreement with previous work. In conclusion, we have developed models that discriminate between known allosteric hotspots and non-hotspots with high accuracy and sensitivity. Moreover, the pattern of predicted hotspots corresponds to known functional motifs implicated in allostery, and is consistent with previous work describing sparse networks of allosterically important residues

Positioning the principles of precision medicine in care pathways for allergic rhinitis and chronic rhinosinusitis - A EUFOREA-ARIA-EPOS-AIRWAYS ICP statement.

Precision medicine (PM) is increasingly recognized as the way forward for optimizing patient care. Introduced in the field of oncology, it is now considered of major interest in other medical domains like allergy and chronic airway diseases, which face an urgent need to improve the level of disease control, enhance patient satisfaction and increase effectiveness of preventive interventions. The combination of personalized care, prediction of treatment success, prevention of disease and patient participation in the elaboration of the treatment plan is expected to substantially improve the therapeutic approach for individuals suffering from chronic disabling conditions. Given the emerging data on the impact of patient stratification on treatment outcomes, European and American regulatory bodies support the principles of PM and its potential advantage over current treatment strategies. The aim of the current document was to propose a consensus on the position and gradual implementation of the principles of PM within existing adult treatment algorithms for allergic rhinitis (AR) and chronic rhinosinusitis (CRS). At the time of diagnosis, prediction of success of the initiated treatment and patient participation in the decision of the treatment plan can be implemented. The second-level approach ideally involves strategies to prevent progression of disease, in addition to prediction of success of therapy, and patient participation in the long-term therapeutic strategy. Endotype-driven treatment is part of a personalized approach and should be positioned at the tertiary level of care, given the efforts needed for its implementation and the high cost of molecular diagnosis and biological treatment

ICAR: endoscopic skull‐base surgery

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Guidelines for the use and interpretation of assays for monitoring autophagy (4th edition)1.

In 2008, we published the first set of guidelines for standardizing research in autophagy. Since then, this topic has received increasing attention, and many scientists have entered the field. Our knowledge base and relevant new technologies have also been expanding. Thus, it is important to formulate on a regular basis updated guidelines for monitoring autophagy in different organisms. Despite numerous reviews, there continues to be confusion regarding acceptable methods to evaluate autophagy, especially in multicellular eukaryotes. Here, we present a set of guidelines for investigators to select and interpret methods to examine autophagy and related processes, and for reviewers to provide realistic and reasonable critiques of reports that are focused on these processes. These guidelines are not meant to be a dogmatic set of rules, because the appropriateness of any assay largely depends on the question being asked and the system being used. Moreover, no individual assay is perfect for every situation, calling for the use of multiple techniques to properly monitor autophagy in each experimental setting. Finally, several core components of the autophagy machinery have been implicated in distinct autophagic processes (canonical and noncanonical autophagy), implying that genetic approaches to block autophagy should rely on targeting two or more autophagy-related genes that ideally participate in distinct steps of the pathway. Along similar lines, because multiple proteins involved in autophagy also regulate other cellular pathways including apoptosis, not all of them can be used as a specific marker for bona fide autophagic responses. Here, we critically discuss current methods of assessing autophagy and the information they can, or cannot, provide. Our ultimate goal is to encourage intellectual and technical innovation in the field