The calcium goes meow : effects of ions and glycosylation on Fel d 1, the major cat allergen

The major cat allergen, Fel d 1, is a structurally complex protein with two N-glycosylation sites that may be filled by different glycoforms. In addition, the protein contains three putative Ca2+ binding sites. Since the impact of these Fel d 1 structure modifications on the protein dynamics, physiology and pathology are not well established, the present work employed computational biology techniques to tackle these issues. While conformational effects brought upon by glycosylation were identified, potentially involved in cavity volume regulation, our results indicate that only the central Ca2+ion remains coordinated to Fel d 1 in biological solutions, impairing its proposed role in modulating phospholipase A2 activity. As these results increase our understanding of Fel d 1 structural biology, they may offer new support for understanding its physiological role and impact into cat-promoted allergy

Variant predictions in congenital adrenal hyperplasia caused by mutations in CYP21A2

CYP21A2 deficiency represents 95% of congenital adrenal hyperplasia (CAH) cases, a group of genetic disorders that affect steroid biosynthesis. The genetic and functional analysis provide critical tools to elucidate complex CAH cases. One of the most accessible tools to infer the pathogenicity of new variants is in silico prediction. Here, we analyzed the performance of in silico prediction tools to categorize missense single nucleotide variants (SNVs) of CYP21A2. SNVs of CYP21A2 characterized in vitro by functional assays were selected to assess the performance of online single and meta predictors. SNVs were tested separately or in combination with the related phenotype (severe or mild CAH form). In total, 103 SNVs of CYP21A2 (90 pathogenic and 13 neutral) were used to test the performance of 13 single-predictors and four meta-predictors. All SNVs associated with the severe phenotypes were well categorized by all tools, with an accuracy of between 0.69 (PredictSNP2) and 0.97 (CADD), and Matthews’ correlation coefficient (MCC) between 0.49 (PoredicSNP2) and 0.90 (CADD). However, SNVs related to the mild phenotype had more variation, with the accuracy between 0.47 (S3Ds&GO and MAPP) and 0.88 (CADD), and MCC between 0.18 (MAPP) and 0.71 (CADD). From our analysis, we identified four predictors of CYP21A2 variant pathogenicity with good performance, CADD, ConSurf, DANN, and PolyPhen2. These results can be used for future analysis to infer the impact of uncharacterized SNVs in CYP21A2

The fast and the furriest: Investigating the rate of selection on mammalian toxins

The evolution of venom and the selection pressures that act on toxins have been increasingly researched within toxinology in the last two decades, in part due to the exceptionally high rates of diversifying selection observed in animal toxins. In 2015, Sungar and Moran proposed the ‘two-speed’ model of toxin evolution linking evolutionary age of a group to the rates of selection acting on toxins but due to a lack of data, mammals were not included as less than 30 species of venomous mammal have been recorded, represented by elusive species which produce small amounts of venom. Due to advances in genomics and transcriptomics, the availability of toxin sequences from venomous mammals has been increasing. Using branch- and site-specific selection models, we present the rates of both episodic and pervasive selection acting upon venomous mammal toxins as a group for the first time. We identified seven toxin groups present within venomous mammals, representing Chiroptera, Eulipotyphla and Monotremata: KLK1, Plasminogen Activator, Desmallipins, PACAP, CRiSP, Kunitz Domain One and Kunitz Domain Two. All but one group (KLK1) was identified by our results to be evolving under both episodic and pervasive diversifying selection with four toxin groups having sites that were implicated in the fitness of the animal by TreeSAAP (Selection on Amino Acid Properties). Our results suggest that venomous mammal ecology, behaviour or genomic evolution are the main drivers of selection, although evolutionary age may still be a factor. Our conclusion from these results indicates that mammalian toxins are following the two-speed model of selection, evolving predominately under diversifying selection, fitting in with other younger venomous taxa like snakes and cone snails—with high amounts of accumulating mutations, leading to more novel adaptions in their toxins

DmCatD, a cathepsin D-like peptidase of the hematophagous insect Dipetalogaster maxima (Hemiptera: Reduviidae): Purification, bioinformatic analyses and the significance of its interaction with lipophorin in the internalization by developing oocytes

DmCatD, a cathepsin D-like peptidase of the hematophagous insect Dipetalogaster maxima, is synthesized by the fat body and the ovary and functions as yolk protein precursor. Functionally, DmCatD is involved in vitellin proteolysis. In this work, we purified and sequenced DmCatD, performed bioinformatic analyses and investigated the events involved in its targeting and storage in developing oocytes. By ion exchange and gel filtration chromatography, DmCatD was purified from egg homogenates and its identity was confirmed by mass spectrometry. Approximately 73% of the full-length transcript was sequenced. The phylogeny indicated that DmCatD has features which suggest its distancing from “classical” cathepsins D. Bioinformatic analyses using a chimeric construct were employed to predict post-translational modifications. Structural modeling showed that DmCatD exhibited the expected folding for this type of enzyme, and an active site with conserved architecture. The interaction between DmCatD and lipophorin in the hemolymph was demonstrated by co-immunoprecipitation. Colocalization of both proteins in developing oocyte membranes and yolk bodies was detected by immunofluorescence. Docking assays favoring the interaction DmCatD-lipophorin were carried out after modeling lipophorin of a related triatomine species. Our results suggest that lipophorin acts as a carrier for DmCatD to facilitate its further internalization by the oocytes. The mechanisms involved in the uptake of peptidases within the oocytes of insects have not been reported. This is the first experimental work supporting the interaction between cathepsin D and lipophorin in an insect species, enabling us to propose a pathway for its targeting and storage in developing oocytes.Fil: Leyria, Jimena. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Córdoba. Centro de Investigaciones en Bioquímica Clínica e Inmunología; Argentina. Universidad Nacional de Córdoba. Facultad de Ciencias Químicas. Departamento de Bioquímica Clínica; ArgentinaFil: Fruttero, Leonardo Luis. Universidad Nacional de Córdoba. Facultad de Ciencias Químicas. Departamento de Bioquímica Clínica; Argentina. Pontificia Universidade Católica do Rio Grande do Sul; Brasil. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Córdoba. Centro de Investigaciones en Bioquímica Clínica e Inmunología; ArgentinaFil: Ligabue Braun, Rodrigo. Universidade Federal do Rio Grande do Sul; BrasilFil: Defferrari, Marina S.. University of Toronto; CanadáFil: Arrese, Estela L.. Oklahoma State University; Estados UnidosFil: Soulages, José L.. Oklahoma State University; Estados UnidosFil: Settembrini, Beatriz Patricia. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Museo Argentino de Ciencias Naturales “Bernardino Rivadavia”; ArgentinaFil: Carlini, Célia Regina R S. Pontificia Universidade Católica do Rio Grande do Sul; BrasilFil: Canavoso, Lilian Etelvina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Córdoba. Centro de Investigaciones en Bioquímica Clínica e Inmunología; Argentina. Universidad Nacional de Córdoba. Facultad de Ciencias Químicas. Departamento de Bioquímica Clínica; Argentin

Determining the pathogenicity of CFTR missense variants : multiple comparisons of in silico predictors and variant annotation databases

Pathogenic variants in the Cystic Fibrosis Transmembrane Conductance Regulator gene (CFTR) are responsible for cystic fibrosis (CF), the commonest monogenic autosomal recessive disease, and CFTR-related disorders in infants and youth. Diagnosis of such diseases relies on clinical, functional, and molecular studies. To date, over 2,000 variants have been described on CFTR (~40% missense). Since few of them have confirmed pathogenicity, in silico analysis could help molecular diagnosis and genetic counseling. Here, the pathogenicity of 779 CFTR missense variants was predicted by consensus predictor PredictSNP and compared to annotations on CFTR2 and ClinVar. Sensitivity and specificity analysis was divided into modeling and validation phases using just variants annotated on CFTR2 and/or ClinVar that were not in the validation datasets of the analyzed predictors. After validation phase, MAPP and PhDSNP achieved maximum specificity but low sensitivity. Otherwise, SNAP had maximum sensitivity but null specificity. PredictSNP, PolyPhen-1, PolyPhen-2, SIFT, nsSNPAnalyzer had either low sensitivity or specificity, or both. Results showed that most predictors were not reliable when analyzing CFTR missense variants, ratifying the importance of clinical information when asserting the pathogenicity of CFTR missense variants. Our results should contribute to clarify decision making when classifying the pathogenicity of CFTR missense variants