Improved Prediction of Bacterial Genotype-Phenotype Associations Using Interpretable Pangenome-Spanning Regressions

Discovery of genetic variants underlying bacterial phenotypes and the prediction of phenotypes such as antibiotic resistance are fundamental tasks in bacterial genomics. Genome-wide association study (GWAS) methods have been applied to study these relations, but the plastic nature of bacterial genomes and the clonal structure of bacterial populations creates challenges. We introduce an alignment-free method which finds sets of loci associated with bacterial phenotypes, quantifies the total effect of genetics on the phenotype, and allows accurate phenotype prediction, all within a single computationally scalable joint modeling framework. Genetic variants covering the entire pangenome are compactly represented by extended DNA sequence words known as unitigs, and model fitting is achieved using elastic net penalization, an extension of standard multiple regression. Using an extensive set of state-of-the-art bacterial population genomic data sets, we demonstrate that our approach performs accurate phenotype prediction, comparable to popular machine learning methods, while retaining both interpretability and computational efficiency. Compared to those of previous approaches, which test each genotype-phenotype association separately for each variant and apply a significance threshold, the variants selected by our joint modeling approach overlap substantially. IMPORTANCE Being able to identify the genetic variants responsible for specific bacterial phenotypes has been the goal of bacterial genetics since its inception and is fundamental to our current level of understanding of bacteria. This identification has been based primarily on painstaking experimentation, but the availability of large data sets of whole genomes with associated phenotype metadata promises to revolutionize this approach, not least for important clinical phenotypes that are not amenable to laboratory analysis. These models of phenotype-genotype association can in the future be used for rapid prediction of clinically important phenotypes such as antibiotic resistance and virulence by rapid-turnaround or point-of-care tests. However, despite much effort being put into adapting genome-wide association study (GWAS) approaches to cope with bacterium-specific problems, such as strong population structure and horizontal gene exchange, current approaches are not yet optimal. We describe a method that advances methodology for both association and generation of portable prediction models.Peer reviewe

A numerical study of compact approximations based on flat integrated radial basis functions for second-order differential equations

In this paper, we propose a simple but effective preconditioning technique to improve the numerical stability of Integrated Radial Basis Function (IRBF) methods. The proposed preconditioner is simply the inverse of a well-conditioned matrix that is constructed using non-flat IRBFs. Much larger values of the free shape parameter of IRBFs can thus be employed and better accuracy for smooth solution problems can be achieved. Furthermore, to improve the accuracy of local IRBF methods, we propose a new stencil, namely Combined Compact IRBF (CCIRBF), in which (i) the starting point is the fourth-order derivative; and (ii) nodal values of first- and second-order derivatives at side nodes of the stencil are included in the computation of first- and second-order derivatives at the middle node in a natural way. The proposed stencil can be employed in uniform/nonuniform Cartesian grids. The preconditioning technique in combination with the CCIRBF scheme employed with large values of the shape parameter are tested with elliptic equations and then applied to simulate several fluid flow problems governed by Poisson, Burgers, convection-diffusion, and Navier-Stokes equations. Highly accurate and stable solutions are obtained. In some cases, the preconditioned schemes are shown to be several orders of magnitude more accurate than those without preconditioning

Compact approximation stencils based on integrated flat radial basis functions

This paper presents improved ways of constructing compact integrated radial basis function (CIRBF) stencils, based on extended precision, definite integrals, higher-order IRBFs and minimum number of derivative equations, to enhance their performance over large values of the RBF width. The proposed approaches are numerically verified through second-order linear differential equations in one and two variables. Significant improvements in the matrix condition number, solution accuracy and convergence rate with grid refinement over the usual approaches are achieved

High-order fluid solver based on a combined compact integrated RBF approximation and its fluid structure interaction applications

In this study, we present a high-order numerical method based on a combined compact integrated RBF (IRBF) approximation for viscous flow and fluid structure interaction (FSI) problems. In the method, the fluid variables are locally approximated by using the combined compact IRBF, and the incompressible Navier-Stokes equations are solved by using the velocity-pressure formulation in a direct fully coupled approach. The fluid solver is verified through various problems including heat, Burgers, convection-diffusion equations, Taylor-Green vortex and lid driven cavity flows. It is then applied to simulate some FSI prob- lems in which an elastic structure is immersed in a viscous incompressible fluid. For FSI simulations, we employ the immersed boundary framework using a regular Eulerian computational grid for the fluid mechanics together with a Lagrangian representation of the immersed boundary. For the immersed fibre/membrane FSI problems, although the order of accuracy of the present scheme is generally similar to FDM approaches reported in the literature, the present approach is nonetheless more accurate than FDM approaches at comparable grid spacings. The numerical results obtained by the present scheme are highly accurate or in good agreement with those reported in earlier studies of the same problems

Statistical Analsysis to Evaluate Heavy Metal Pollution in the Air Obatained by Moss Technique in Hanoi and its Surrounding Region

The aim of this paper was the application of statistical analysis including principal component analysis to evaluate heavy metal pollution obtained by moss technique in the air of Ha Noi and its surrounding areas and to evaluate potential pollution sources. The concentrations of 33 heavy metal elements in 27 samples of Barbula Indica moss in the investigated region collected in December of 2016 in the investigated area have been examined using multivariate statistical analysis. Five factors explaining 80% of the total variance were identified and their potential sources have been discussed

Prevalence and correlates of zinc deficiency in pregnant Vietnamese women in Ho Chi Minh City

Background: Although Vietnam is a region with a plant-based diet that has a high zinc deficiency, epidemiological data showing how this affects pregnant women are limited. This study explores the prevalence of zinc deficiency and possible correlates in pregnant Vietnamese women in Ho Chi Minh City. Methods: This was a crosssectional study conducted at a general hospital in Ho Chi Minh City, Vietnam. All pregnant women who came to their first antenatal care visit from November 2011 to June 2012 were recruited. Those taking a vitamin and/or mineral supplement were excluded. Serum zinc concentrations, determined by a standard colorimetric method, of 10.7 mol/L-17.5 mol/L (70.0 g/dL-114 g/dL) were classified as normal and under 10.7 mol/L (70.0 g/dL) as zinc deficient. Results: In total, 254 pregnant women were invited and 107 (42%) participated. The mean age of participants was 29 years, and mean gestational age was 10 weeks. Median zinc concentration in serum was 13.6 mol/L, and the prevalence of zinc deficiency was 29% (95% CI=21%-39%). The daily intake of a milk product supplement was the only significant correlate of zinc deficiency of the items investigated (adjusted OR=0.40, p=0.049). Discussion: This is the first study reporting that more than 25% of pregnant Vietnamese women in Ho Chi Minh City are zinc deficient. Further academic and clinical input is needed to confirm the scale of this neglected issue and to investigate the potential of milk product supplementation in this population

In silico-designed lignin peroxidase from Phanerochaete chrysosporium shows enhanced acid stability for depolymerization of lignin

Background: The lignin peroxidase isozyme H8 from the white-rot fungus Phanerochaete chrysosporium (LiPH8) demonstrates a high redox potential and can efficiently catalyze the oxidation of veratryl alcohol, as well as the degradation of recalcitrant lignin. However, native LiPH8 is unstable under acidic pH conditions. This characteristic is a barrier to lignin depolymerization, as repolymerization of phenolic products occurs simultaneously at neutral pH. Because repolymerization of phenolics is repressed at acidic pH, a highly acid-stable LiPH8 could accelerate the selective depolymerization of recalcitrant lignin. Results: The engineered LiPH8 was in silico designed through the structural superimposition of surface-active site-harboring LiPH8 from Phanerochaete chrysosporium and acid-stable manganese peroxidase isozyme 6 (MnP6) from Ceriporiopsis subvermispora. Effective salt bridges were probed by molecular dynamics simulation and changes to Gibbs free energy following mutagenesis were predicted, suggesting promising variants with higher stability under extremely acidic conditions. The rationally designed variant, A55R/N156E-H239E, demonstrated a 12.5-fold increased half-life under extremely acidic conditions, 9.9-fold increased catalytic efficiency toward veratryl alcohol, and a 7.8-fold enhanced lignin model dimer conversion efficiency compared to those of native LiPH8. Furthermore, the two constructed salt bridges in the variant A55R/N156E-H239E were experimentally confirmed to be identical to the intentionally designed LiPH8 variant using X-ray crystallography (PDB ID: 6A6Q). Conclusion: Introduction of strong ionic salt bridges based on computational design resulted in a LiPH8 variant with markedly improved stability, as well as higher activity under acidic pH conditions. Thus, LiPH8, showing high acid stability, will be a crucial player in biomass valorization using selective depolymerization of lignin

Associations of Underlying Health Conditions With Anxiety and Depression Among Outpatients: Modification Effects of Suspected COVID-19 Symptoms, Health-Related and Preventive Behaviors

Objectives: We explored the association of underlying health conditions (UHC) with depression and anxiety, and examined the modification effects of suspected COVID-19 symptoms (S-COVID-19-S), health-related behaviors (HB), and preventive behaviors (PB).Methods: A cross-sectional study was conducted on 8,291 outpatients aged 18–85 years, in 18 hospitals and health centers across Vietnam from 14th February to May 31, 2020. We collected the data regarding participant's characteristics, UHC, HB, PB, depression, and anxiety.Results: People with UHC had higher odds of depression (OR = 2.11; p < 0.001) and anxiety (OR = 2.86; p < 0.001) than those without UHC. The odds of depression and anxiety were significantly higher for those with UHC and S-COVID-19-S (p < 0.001); and were significantly lower for those had UHC and interacted with “unchanged/more” physical activity (p < 0.001), or “unchanged/more” drinking (p < 0.001 for only anxiety), or “unchanged/healthier” eating (p < 0.001), and high PB score (p < 0.001), as compared to those without UHC and without S-COVID-19-S, “never/stopped/less” physical activity, drinking, “less healthy” eating, and low PB score, respectively.Conclusion: S-COVID-19-S worsen psychological health in patients with UHC. Physical activity, drinking, healthier eating, and high PB score were protective factors

Antimicrobial resistance among migrants in Europe: a systematic review and meta-analysis

BACKGROUND: Rates of antimicrobial resistance (AMR) are rising globally and there is concern that increased migration is contributing to the burden of antibiotic resistance in Europe. However, the effect of migration on the burden of AMR in Europe has not yet been comprehensively examined. Therefore, we did a systematic review and meta-analysis to identify and synthesise data for AMR carriage or infection in migrants to Europe to examine differences in patterns of AMR across migrant groups and in different settings. METHODS: For this systematic review and meta-analysis, we searched MEDLINE, Embase, PubMed, and Scopus with no language restrictions from Jan 1, 2000, to Jan 18, 2017, for primary data from observational studies reporting antibacterial resistance in common bacterial pathogens among migrants to 21 European Union-15 and European Economic Area countries. To be eligible for inclusion, studies had to report data on carriage or infection with laboratory-confirmed antibiotic-resistant organisms in migrant populations. We extracted data from eligible studies and assessed quality using piloted, standardised forms. We did not examine drug resistance in tuberculosis and excluded articles solely reporting on this parameter. We also excluded articles in which migrant status was determined by ethnicity, country of birth of participants' parents, or was not defined, and articles in which data were not disaggregated by migrant status. Outcomes were carriage of or infection with antibiotic-resistant organisms. We used random-effects models to calculate the pooled prevalence of each outcome. The study protocol is registered with PROSPERO, number CRD42016043681. FINDINGS: We identified 2274 articles, of which 23 observational studies reporting on antibiotic resistance in 2319 migrants were included. The pooled prevalence of any AMR carriage or AMR infection in migrants was 25·4% (95% CI 19·1-31·8; I2 =98%), including meticillin-resistant Staphylococcus aureus (7·8%, 4·8-10·7; I2 =92%) and antibiotic-resistant Gram-negative bacteria (27·2%, 17·6-36·8; I2 =94%). The pooled prevalence of any AMR carriage or infection was higher in refugees and asylum seekers (33·0%, 18·3-47·6; I2 =98%) than in other migrant groups (6·6%, 1·8-11·3; I2 =92%). The pooled prevalence of antibiotic-resistant organisms was slightly higher in high-migrant community settings (33·1%, 11·1-55·1; I2 =96%) than in migrants in hospitals (24·3%, 16·1-32·6; I2 =98%). We did not find evidence of high rates of transmission of AMR from migrant to host populations. INTERPRETATION: Migrants are exposed to conditions favouring the emergence of drug resistance during transit and in host countries in Europe. Increased antibiotic resistance among refugees and asylum seekers and in high-migrant community settings (such as refugee camps and detention facilities) highlights the need for improved living conditions, access to health care, and initiatives to facilitate detection of and appropriate high-quality treatment for antibiotic-resistant infections during transit and in host countries. Protocols for the prevention and control of infection and for antibiotic surveillance need to be integrated in all aspects of health care, which should be accessible for all migrant groups, and should target determinants of AMR before, during, and after migration. FUNDING: UK National Institute for Health Research Imperial Biomedical Research Centre, Imperial College Healthcare Charity, the Wellcome Trust, and UK National Institute for Health Research Health Protection Research Unit in Healthcare-associated Infections and Antimictobial Resistance at Imperial College London

Genome-wide association meta-analyses and fine-mapping elucidate pathways influencing albuminuria

Abstract: Increased levels of the urinary albumin-to-creatinine ratio (UACR) are associated with higher risk of kidney disease progression and cardiovascular events, but underlying mechanisms are incompletely understood. Here, we conduct trans-ethnic (n = 564,257) and European-ancestry specific meta-analyses of genome-wide association studies of UACR, including ancestry- and diabetes-specific analyses, and identify 68 UACR-associated loci. Genetic correlation analyses and risk score associations in an independent electronic medical records database (n = 192,868) reveal connections with proteinuria, hyperlipidemia, gout, and hypertension. Fine-mapping and trans-Omics analyses with gene expression in 47 tissues and plasma protein levels implicate genes potentially operating through differential expression in kidney (including TGFB1, MUC1, PRKCI, and OAF), and allow coupling of UACR associations to altered plasma OAF concentrations. Knockdown of OAF and PRKCI orthologs in Drosophila nephrocytes reduces albumin endocytosis. Silencing fly PRKCI further impairs slit diaphragm formation. These results generate a priority list of genes and pathways for translational research to reduce albuminuria