High-confidence 3D template matching for cryo-electron tomography.

Visual proteomics attempts to build atlases of the molecular content of cells but the automated annotation of cryo electron tomograms remains challenging. Template matching (TM) and methods based on machine learning detect structural signatures of macromolecules. However, their applicability remains limited in terms of both the abundance and size of the molecular targets. Here we show that the performance of TM is greatly improved by using template-specific search parameter optimization and by including higher-resolution information. We establish a TM pipeline with systematically tuned parameters for the automated, objective and comprehensive identification of structures with confidence 10 to 100-fold above the noise level. We demonstrate high-fidelity and high-confidence localizations of nuclear pore complexes, vaults, ribosomes, proteasomes, fatty acid synthases, lipid membranes and microtubules, and individual subunits inside crowded eukaryotic cells. We provide software tools for the generic implementation of our method that is broadly applicable towards realizing visual proteomics.

Modeling potential risk areas of Orthohantavirus transmission in Northwestern Argentina using an ecological niche approach.

BACKGROUND: Hantavirus Pulmonary Syndrome (HPS) is a rodent-borne zoonosis in the Americas, with up to 50% mortality rates. In Argentina, the Northwestern endemic area presents half of the annually notified HPS cases in the country, transmitted by at least three rodent species recognized as reservoirs of Orthohantavirus. The potential distribution of reservoir species based on ecological niche models (ENM) can be a useful tool to establish risk areas for zoonotic diseases. Our main aim was to generate an Orthohantavirus risk transmission map based on ENM of the reservoir species in northwest Argentina (NWA), to compare this map with the distribution of HPS cases; and to explore the possible effect of climatic and environmental variables on the spatial variation of the infection risk. METHODS: Using the reservoir geographic occurrence data, climatic/environmental variables, and the maximum entropy method, we created models of potential geographic distribution for each reservoir in NWA. We explored the overlap of the HPS cases with the reservoir-based risk map and a deforestation map. Then, we calculated the human population at risk using a census radius layer and a comparison of the environmental variables' latitudinal variation with the distribution of HPS risk. RESULTS: We obtained a single best model for each reservoir. The temperature, rainfall, and vegetation cover contributed the most to the models. In total, 945 HPS cases were recorded, of which 97,85% were in the highest risk areas. We estimated that 18% of the NWA population was at risk and 78% of the cases occurred less than 10 km from deforestation. The highest niche overlap was between Calomys fecundus and Oligoryzomys chacoensis. CONCLUSIONS: This study identifies potential risk areas for HPS transmission based on climatic and environmental factors that determine the distribution of the reservoirs and Orthohantavirus transmission in NWA. This can be used by public health authorities as a tool to generate preventive and control measures for HPS in NWA.

Andes Virus Genome Mutations That Are Likely Associated with Animal Model Attenuation and Human Person-to-Person Transmission.

We performed whole-genome sequencing with bait enrichment techniques to analyze Andes virus (ANDV), a cause of human hantavirus pulmonary syndrome. We used cryopreserved lung tissues from a naturally infected long-tailed colilargo, including early, intermediate, and late cell culture, passages of an ANDV isolate from that animal, and lung tissues from golden hamsters experimentally exposed to that ANDV isolate. The resulting complete genome sequences were subjected to detailed comparative genomic analysis against American orthohantaviruses. We identified four amino acid substitutions related to cell culture adaptation that resulted in attenuation of ANDV in the typically lethal golden hamster animal model of hantavirus pulmonary syndrome. Changes in the ANDV nucleocapsid protein, glycoprotein, and small nonstructural protein open reading frames correlated with mutations typical for ANDV strains associated with increased virulence in the small-animal model. Finally, we identified three amino acid substitutions, two in the small nonstructural protein and one in the glycoprotein, that were only present in the clade of viruses associated with efficient person-to-person transmission. Our results indicate that there are single-nucleotide polymorphisms that could be used to predict strain-specific ANDV virulence and/or transmissibility. IMPORTANCE Several orthohantaviruses cause the zoonotic disease hantavirus pulmonary syndrome (HPS) in the Americas. Among them, HPS caused by Andes virus (ANDV) is of great public health concern because it is associated with the highest case fatality rate (up to 50%). ANDV is also the only orthohantavirus associated with relatively robust evidence of person-to-person transmission. This work reveals nucleotide changes in the ANDV genome that are associated with virulence attenuation in an animal model and increased transmissibility in humans. These findings may pave the way to early severity predictions in future ANDV-caused HPS outbreaks.

TriMem: A parallelized hybrid Monte Carlo software for efficient simulations of lipid membranes.

Lipid membranes are integral building blocks of living cells and perform a multitude of biological functions. Currently, molecular simulations of cellular-scale membrane remodeling processes at atomic resolution are extremely difficult, due to their size, complexity, and the large times-scales on which these processes occur. Instead, elastic membrane models are used to simulate membrane shapes and transitions between them and to infer their properties and functions. Unfortunately, an efficiently parallelized open-source simulation code to do so has been lacking. Here, we present TriMem, a parallel hybrid Monte Carlo simulation engine for triangulated lipid membranes. The kernels are efficiently coded in C++ and wrapped with Python for ease-of-use. The parallel implementation of the energy and gradient calculations and of Monte Carlo flip moves of edges in the triangulated membrane enable us to simulate large and highly curved membrane structures. For validation, we reproduce phase diagrams of vesicles with varying surface-to-volume ratios and area difference. We also compute the density of states to verify correct Boltzmann sampling. The software can be used to tackle a range of large-scale membrane remodeling processes as a step toward cell-scale simulations. Additionally, extensive documentation make the software accessible to the broad biophysics and computational cell biology communities.

Mapping the global distribution of Strongyloides stercoralis and hookworms by ecological niche modeling.

BACKGROUND: The WHO has established a control strategy for Strongyloides stercoralis in school-aged children as well as targets and to maintain control programs for Ascaris lumbricoides, Trichuris trichiura and hookworms. For an efficient development of control programs, it is necessary to know the target countries around the world, as well as the areas within each country where efforts should be focused. Therefore, maps that provide information on the areas at risk for soil-transmitted helminth (STH) infections on a national and sub-national scale would allow for a better allocation of resources. METHODS: We used the ecological niche models MaxEnt and Kuenm R library to estimate the global distribution of S. stercoralis and hookworms. We used occurrence points of both species extracted from surveys of two literature reviews and from the Global Atlas of Helminth Infection database, together with 14 raster maps of environmental variables. RESULTS: We obtained two raster maps with the presence probability of S. stercoralis and hookworm infections at a global level and then estimated the global population at risk to be 2.6 and 3.4 billion, respectively. The population at risk was also estimated at the country level using estimations for areas as small as 25 km2. A relationship was found between the probability of the presence of S. stercoralis and its prevalence, and a raster map was generated. Annual precipitation, annual temperature, soil carbon content and land cover were the main associated environmental variables. The ecological niches of Strongyloides stercoralis and hookworms had an overlap of 68%. CONCLUSIONS: Here we provide information that can be used for developing more efficient and integrated control strategies for S. stercoralis and hookworm infections. This information can be annexed to the study of other risk factors or even other diseases to assess the health status of a community. GRAPHICAL ABSTARCT.

Emerging hantaviruses in Central Argentina: First case of Hantavirus Pulmonary Syndrome caused by Alto Paraguay virus, and a novel orthohantavirus in Scapteromys aquaticus rodent.

Orthohantaviruses are emerging rodent-borne pathogens that cause Hantavirus Pulmonary Syndrome in humans. They have a wide range of rodent reservoir hosts and are transmitted to humans through aerosolized viral particles generated by the excretions of infected individuals. Since the first description of HPS in Argentina, new hantaviruses have been reported throughout the country, most of which are pathogenic to humans. We present here the first HPS case infected with Alto Paraguay virus reported in Argentina. Until now, Alto Paraguay virus was considered a non-pathogenic orthohantavirus since it was identified in a rodent, Holochilus chacarius. In addition to this, with the goal of identifying potential hantavirus host species in the province of Santa Fe, we finally describe a novel orthohantavirus found in the native rodent Scapteromys aquaticus, which differed from other hantaviruses described in the country so far. Our findings implicate an epidemiological warning regarding these new orthohantaviruses circulating in Central Argentina as well as new rodent species that must be considered as hosts from now on.

Probabilistic noninvasive prediction of wall properties of abdominal aortic aneurysms using Bayesian regression.

Multiple patient-specific parameters, such as wall thickness, wall strength, and constitutive properties, are required for the computational assessment of abdominal aortic aneurysm (AAA) rupture risk. Unfortunately, many of these quantities are not easily accessible and could only be determined by invasive procedures, rendering a computational rupture risk assessment obsolete. This study investigates two different approaches to predict these quantities using regression models in combination with a multitude of noninvasively accessible, explanatory variables. We have gathered a large dataset comprising tensile tests performed with AAA specimens and supplementary patient information based on blood analysis, the patients medical history, and geometric features of the AAAs. Using this unique database, we harness the capability of state-of-the-art Bayesian regression techniques to infer probabilistic models for multiple quantities of interest. After a brief presentation of our experimental results, we show that we can effectively reduce the predictive uncertainty in the assessment of several patient-specific parameters, most importantly in thickness and failure strength of the AAA wall. Thereby, the more elaborate Bayesian regression approach based on Gaussian processes consistently outperforms standard linear regression. Moreover, our study contains a comparison to a previously proposed model for the wall strength.

Calibration of parameters for cardiovascular models with application to arterial growth.

We present a computational framework for the calibration of parameters describing cardiovascular models with a focus on the application of growth of abdominal aortic aneurysms (AAA). The growth rate in this sort of pathology is considered a critical parameter in the risk management and is an essential indicator for the assessment of surveillance intervals. Parameters describing growth of AAAs are not measurable directly and need to be estimated from available data often given by medical imaging technologies. Registration procedures often applied in standard workflows of parameter identification to extract the image encoded information are a source of significant systematic error. The concept of surface currents provides means to effectively avoid this source of errors by establishing a mathematical framework to compare surface information, directly accessible from image data. By utilizing this concept it is possible to inversely estimate growth parameters using sophisticated numerical models of AAAs from measurements available as surface information. In this work we present a framework to obtain spatial distributions of parameters governing growth of arterial tissue, and we show how the use of surface currents can significantly improve the results. We further present the application to patient specific follow-up data resulting in a spatial map of volumetric growth rates enabling, for the first time, prediction of further AAA expansion.

Biomechanics and gene expression in abdominal aortic aneurysm.

OBJECTIVE: The aim of the study was to detect inter-relations between the mechanical conditions and material properties of abdominal aortic aneurysm (AAA) wall and the underlying local gene expression of destabilizing inflammatory, proteolytic, and structural factors. METHODS: During open surgery, 51 tissue samples from 31 AAA patients were harvested. Gene expression of collagen types I and III, inflammatory factors CD45 and MSR1, proteolytic enzymes matrix metalloproteinases 2 and 9, and tissue inhibitor of matrix metalloproteinase 1 was analyzed by reverse transcription-polymerase chain reaction. Material properties of corresponding AAA tissue samples were assessed by cyclic sinusoidal and destructive testing. Local mechanical conditions of stress and strain were determined by advanced nonlinear finite element analysis based on patient-specific three-dimensional AAA models derived from preoperative computed tomography data. RESULTS: In the AAA wall, all parameters analyzed were significantly expressed at the messenger RNA level. With respect to mechanical properties of the aneurysmatic wall, expression of collagen III correlated with the stiffness parameter α (r = -0.348; P = .017), and matrix metalloprotease 2 correlated with the stiffness parameter ß and wall strength (r = -0.438 and -0.593; P = .005 and P < .001). Furthermore, significant relationships were observed between local AAA diameter and the expression of CD45, MSR1, and tissue inhibitor of matrix metalloproteinase 1 (r = 0.285, 0.551, 0.328; P < .05). However, we found no inter-relation of local calculated wall stresses and strains with gene expression. CONCLUSIONS: Our results show for the first time that gene expressions of destabilizing factors within AAA tissue might be correlated to geometric and mechanical properties of the AAA wall. However, we found no influence of local mechanical conditions on gene expression of these factors. Therefore, these preliminary results are still ambiguous.