PENCALC: A program for penetrance estimation in autosomal dominant diseases

We present a computer program developed for estimating penetrance rates in autosomal dominant diseases by means of family kinship and phenotype information contained within the pedigrees. The program also determines the exact 95% credibility interval for the penetrance estimate. Both executable (PenCalc for Windows) and web versions (PenCalcWeb) of the software are available. The web version enables further calculations, such as heterozygosity probabilities and assessment of offspring risks for all individuals in the pedigrees. Both programs can be accessed and down-loaded freely at the home-page address http://www.ib.usp.br/~otto/software.htm

Influenza d virus infection in herd of cattle, Japan

Citation: Murakami, S., Endoh, M., Kobayashi, T., Takenaka-Uema, A., Chambers, J. K., Uchida, K., . . . Horimoto, T. (2016). Influenza d virus infection in herd of cattle, Japan. Emerging Infectious Diseases, 22(8), 1517-1519. doi:10.3201/eid2208.160362Although the provisionally named influenza D virus was first isolated as an influenza C–like virus from pigs with respiratory illness in Oklahoma in 2011 (1,2), epidemiologic analyses suggested that cattle are major reservoirs of this virus (3) and the virus is potentially involved in the bovine respiratory disease complex. The high rates of illness and death related to this disease in feedlot cattle are caused by multiple factors, including several viral and bacterial co-infections. Influenza D viruses were detected in cattle and pigs with respiratory diseases (and in some healthy cattle) in China (4), France (5), Italy (6), among other countries, indicating their wide global geographic distribution. Although the influenza D virus, like the human influenza C virus, is known to use 9-O-acetylated sialic acids as the cell receptor (2,7), its zoonotic potential is undefined because of limited research (1,8). We report influenza D virus infection in a herd of cattle in Japan

Predicting Secondary Structures, Contact Numbers, and Residue-wise Contact Orders of Native Protein Structure from Amino Acid Sequence by Critical Random Networks

Prediction of one-dimensional protein structures such as secondary structures and contact numbers is useful for the three-dimensional structure prediction and important for the understanding of sequence-structure relationship. Here we present a new machine-learning method, critical random networks (CRNs), for predicting one-dimensional structures, and apply it, with position-specific scoring matrices, to the prediction of secondary structures (SS), contact numbers (CN), and residue-wise contact orders (RWCO). The present method achieves, on average, $Q_3$ accuracy of 77.8% for SS, correlation coefficients of 0.726 and 0.601 for CN and RWCO, respectively. The accuracy of the SS prediction is comparable to other state-of-the-art methods, and that of the CN prediction is a significant improvement over previous methods. We give a detailed formulation of critical random networks-based prediction scheme, and examine the context-dependence of prediction accuracies. In order to study the nonlinear and multi-body effects, we compare the CRNs-based method with a purely linear method based on position-specific scoring matrices. Although not superior to the CRNs-based method, the surprisingly good accuracy achieved by the linear method highlights the difficulty in extracting structural features of higher order from amino acid sequence beyond that provided by the position-specific scoring matrices.Comment: 20 pages, 1 figure, 5 tables; minor revision; accepted for publication in BIOPHYSIC

A single residue substitution in the receptor-binding domain of H5N1 hemagglutinin is critical for packaging into pseudotyped lentiviral particles

© 2012 Tang et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.Background: Serological studies for influenza infection and vaccine response often involve microneutralization and hemagglutination inhibition assays to evaluate neutralizing antibodies against human and avian influenza viruses, including H5N1. We have previously characterized lentiviral particles pseudotyped with H5-HA (H5pp) and validated an H5pp-based assay as a safe alternative for high-throughput serological studies in BSL-2 facilities. Here we show that H5-HAs from different clades do not always give rise to efficient production of H5pp and the underlying mechanisms are addressed. Methodology/Findings: We have carried out mutational analysis to delineate the molecular determinants responsible for efficient packaging of HA from A/Cambodia/40808/2005 (H5Cam) and A/Anhui/1/2005 (H5Anh) into H5pp. Our results demonstrate that a single A134V mutation in the 130-loop of the receptor binding domain is sufficient to render H5Anh the ability to generate H5Anh-pp efficiently, whereas the reverse V134A mutation greatly hampers production of H5Cam-pp. Although protein expression in total cell lysates is similar for H5Anh and H5Cam, cell surface expression of H5Cam is detected at a significantly higher level than that of H5Anh. We further demonstrate by several independent lines of evidence that the behaviour of H5Anh can be explained by a stronger binding to sialic acid receptors implicating residue 134. Conclusions: We have identified a single A134V mutation as the molecular determinant in H5-HA for efficient incorporation into H5pp envelope and delineated the underlying mechanism. The reduced binding to sialic acid receptors as a result of the A134V mutation not only exerts a critical influence in pseudotyping efficiency of H5-HA, but has also an impact at the whole virus level. Because A134V substitution has been reported as a naturally occurring mutation in human host, our results may have implications for the understanding of human host adaptation of avian influenza H5N1 virusesThis work was supported by grants from the Research Fund for the Control of Infectious Diseases of Hong Kong (RFCID#08070972), the Area of Excellence Scheme of the University Grants Committee (grant AoE/M-12/-06 of the Hong Kong Special Administrative Region, China), the French Ministry of Health, and the RESPARI project of the Institut Pasteur International Network

Co-administration of Favipiravir and the Remdesivir Metabolite GS-441524 Effectively Reduces SARS-CoV-2 Replication in the Lungs of the Syrian Hamster Model

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has spread worldwide since December 2019, causing coronavirus disease 2019 (COVID-19). Although vaccines for this virus have been developed rapidly, repurposing drugs approved to treat other diseases remains an invaluable treatment strategy. Here, we evaluated the inhibitory effects of drugs on SARS-CoV-2 replication in a hamster infection model and in in vitro assays. Favipiravir significantly suppressed virus replication in hamster lungs. Remdesivir inhibited virus replication in vitro, but was not effective in the hamster model. However, GS-441524, a metabolite of remdesivir, effectively suppressed virus replication in hamsters. Co-administration of favipiravir and GS-441524 more efficiently reduced virus load in hamster lungs than did single administration of either drug for both the prophylactic and therapeutic regimens; prophylactic co-administration also efficiently inhibited lung inflammation in the infected animals. Furthermore, pretreatment of hamsters with favipiravir and GS-441524 effectively protected them from virus transmission via respiratory droplets upon exposure to infected hamsters. Repurposing and co-administration of antiviral drugs may help combat COVID-19. IMPORTANCE During a pandemic, repurposing drugs that are approved for other diseases is a quick and realistic treatment option. In this study, we found that co-administration of favipiravir and the remdesivir metabolite GS-441524 more effectively blocked SARS-CoV-2 replication in the lungs of Syrian hamsters than either favipiravir or GS-441524 alone as part of a prophylactic or therapeutic regimen. Prophylactic co-administration also reduced the severity of lung inflammation. Moreover, co-administration of these drugs to naive hamsters efficiently protected them from airborne transmission of the virus from infected animals. Since both drugs are nucleotide analogs that interfere with the RNA-dependent RNA polymerases of many RNA viruses, these findings may also help encourage co-administration of antivirals to combat future pandemics

Multi-ancestry study of blood lipid levels identifies four loci interacting with physical activity.

Many genetic loci affect circulating lipid levels, but it remains unknown whether lifestyle factors, such as physical activity, modify these genetic effects. To identify lipid loci interacting with physical activity, we performed genome-wide analyses of circulating HDL cholesterol, LDL cholesterol, and triglyceride levels in up to 120,979 individuals of European, African, Asian, Hispanic, and Brazilian ancestry, with follow-up of suggestive associations in an additional 131,012 individuals. We find four loci, in/near CLASP1, LHX1, SNTA1, and CNTNAP2, that are associated with circulating lipid levels through interaction with physical activity; higher levels of physical activity enhance the HDL cholesterol-increasing effects of the CLASP1, LHX1, and SNTA1 loci and attenuate the LDL cholesterol-increasing effect of the CNTNAP2 locus. The CLASP1, LHX1, and SNTA1 regions harbor genes linked to muscle function and lipid metabolism. Our results elucidate the role of physical activity interactions in the genetic contribution to blood lipid levels

Identifying Influenza Viruses with Resequencing Microarrays

Resequencing microarrays rapidly identify influenza viruses

Evolutionary Repercussions of Avian Culling on Host Resistance and Influenza Virulence

Keeping pandemic influenza at bay is a global health priority. Of particular concern is the continued spread of the influenza subtype H5N1 in avian populations and the increasing frequency of transmission to humans. To decrease this threat, mass culling is the principal strategy for eradicating influenza in avian populations. Although culling has a crucial short-term epidemiological benefit, evolutionary repercussions on reservoir hosts and on the viral population have not been considered.To explore the epidemiological and evolutionary repercussions of mass avian culling, we combine population genetics and epidemiological influenza dynamics in a mathematical model parameterized by clinical, epidemiological, and poultry data. We model the virulence level of influenza and the selection on a dominant allele that confers resistance against influenza [1, 2] in a poultry population. Our findings indicate that culling impedes the evolution of avian host resistance against influenza. On the pathogen side of the coevolutionary race between pathogen and host, culling selects for heightened virulence and transmissibility of influenza.Mass culling achieves a short-term benefit at the expense of long-term detriments: a more genetically susceptible host population, ultimately greater mortality, and elevated influenza virulence