Inferring the heritability of bacterial traits in the era of machine learning

Quantification of heritability is a fundamental desideratum in genetics, which allows an assessment of the contribution of additive genetic variation to the variability of a trait of interest. The traditional computational approaches for assessing the heritability of a trait have been developed in the field of quantitative genetics. However, the rise of modern population genomics with large sample sizes has led to the development of several new machine learning based approaches to inferring heritability. In this paper, we systematically summarize recent advances in machine learning which can be used to infer heritability. We focus on an application of these methods to bacterial genomes, where heritability plays a key role in understanding phenotypes such as antibiotic resistance and virulence, which are particularly important due to the rising frequency of antimicrobial resistance. By designing a heritability model incorporating realistic patterns of genome-wide linkage disequilibrium for a frequently recombining bacterial pathogen, we test the performance of a wide spectrum of different inference methods, including also GCTA. In addition to the synthetic data benchmark, we present a comparison of the methods for antibiotic resistance traits for multiple bacterial pathogens. Insights from the benchmarking and real data analyses indicate a highly variable performance of the different methods and suggest that heritability inference would likely benefit from tailoring of the methods to the specific genetic architecture of the target organism

Mandrake : visualizing microbial population structure by embedding millions of genomes into a low-dimensional representation

In less than a decade, population genomics of microbes has progressed from the effort of sequencing dozens of strains to thousands, or even tens of thousands of strains in a single study. There are now hundreds of thousands of genomes available even for a single bacterial species, and the number of genomes is expected to continue to increase at an accelerated pace given the advances in sequencing technology and widespread genomic surveillance initiatives. This explosion of data calls for innovative methods to enable rapid exploration of the structure of a population based on different data modalities, such as multiple sequence alignments, assemblies and estimates of gene content across different genomes. Here, we present Mandrake, an efficient implementation of a dimensional reduction method tailored for the needs of large-scale population genomics. Mandrake is capable of visualizing population structure from millions of whole genomes, and we illustrate its usefulness with several datasets representing major pathogens. Our method is freely available both as an analysis pipeline (https://github.com/johnlees/mandrake) and as a browser-based interactive application (https://gtonkinhill.github.io/mandrake-web/).This article is part of a discussion meeting issue 'Genomic population structures of microbial pathogens'.Peer reviewe

Recent approaches in computational modelling for controlling pathogen threats.

In this review, we assess the status of computational modelling of pathogens. We focus on three disparate but interlinked research areas that produce models with very different spatial and temporal scope. First, we examine antimicrobial resistance (AMR). Many mechanisms of AMR are not well understood. As a result, it is hard to measure the current incidence of AMR, predict the future incidence, and design strategies to preserve existing antibiotic effectiveness. Next, we look at how to choose the finite number of bacterial strains that can be included in a vaccine. To do this, we need to understand what happens to vaccine and non-vaccine strains after vaccination programmes. Finally, we look at within-host modelling of antibody dynamics. The SARS-CoV-2 pandemic produced huge amounts of antibody data, prompting improvements in this area of modelling. We finish by discussing the challenges that persist in understanding these complex biological systems

Reviews

The following publications have been reviewed by the mentioned authors;Beginning Graphical Communication by M. Jordan, B. Hawtin and A. Neil, reviewed by John LeesArt Related Topics by Bob Nunn and Chris Locke, reviewed by A. CharltonHandbook for Art and Design Students by Robin Jesson, reviewed by John LancasterDrawing and Cognition Descriptive and Experimental Studies of Graphic Production Processes by Peter Van Sommers, reviewed by Pamela M. SchenkThe Student's Guide to Western Calligraphy an Illustrated Survey by Joyce Irene Whalley, reviewed by John LancasterSource Directory for Authentic Indian, Eskimo and Aleut Arts and Crafts by the Indian Arts and Crafts BoardMarianne Straub by Mary Schoeser, reviewed by Kim GreerMisha Black by Avril Blake, reviewed by Kim Greer'Working in Crafts' - A National Survey by the Crafts Council, reviewed by L. SayerDirectory of Design Expertise by the Design Council, reviewed by R. Smit

Symmetry violations at BABAR

Content from this work may be used under the terms of the Creative Commons Attribution 3.0 licence. Any further distribution of this work must maintain attribution to the author(s) and the title of the work, journal citation and DOI. Published under licence by IOP Publishing Ltd.2014 J. Phys.: Conf. Ser. 556 012042 (http://iopscience.iop.org/1742-6596/556/1/012042

pyseer : a comprehensive tool for microbial pangenome-wide association studies

Genome-wide association studies (GWAS) in microbes have different challenges to GWAS in eukaryotes. These have been addressed by a number of different methods. pyseer brings these techniques together in one package tailored to microbial GWAS, allows greater flexibility of the input data used, and adds new methods to interpret the association results.Peer reviewe

Direct evidence from high-field magnetotransport for a dramatic change of quasiparticle character in van der Waals ferromagnet Fe_3−⁢GeTe₂

Magnetometry and magnetoresistance (MR) data taken on the van der Waals ferromagnet Fe3−⁢GeTe2 (FGT) reveal three distinct contributions to the MR: a linear negative component, a contribution from closed Fermi-surface orbits, and an enhancement proportional to the square of the applied magnetic field which is linked to a noncoplanar spin arrangement. Contrary to earlier studies on FGT, by accounting for the field dependence of the anomalous Hall effect, we find that the ordinary Hall coefficient decreases markedly below 80 K, indicating a significant change in character of the electrons and holes on the Fermi-surface at this temperature. The resulting altered ground state eventually causes the Hall coefficient to reverse sign at 35 K. Our Hall data support the proposal that Kondo-lattice behavior develops in this -electron material below 80 K. Additional evidence comes from the negative linear component of the MR, which arises from electron-magnon scattering with an atypical temperature dependence attributable to the onset of Kondo screening

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

Genome-wide identification of lineage and locus specific variation associated with pneumococcal carriage duration.

Streptococcus pneumoniae is a leading cause of invasive disease in infants, especially in low-income settings. Asymptomatic carriage in the nasopharynx is a prerequisite for disease, but variability in its duration is currently only understood at the serotype level. Here we developed a model to calculate the duration of carriage episodes from longitudinal swab data, and combined these results with whole genome sequence data. We estimated that pneumococcal genomic variation accounted for 63% of the phenotype variation, whereas the host traits considered here (age and previous carriage) accounted for less than 5%. We further partitioned this heritability into both lineage and locus effects, and quantified the amount attributable to the largest sources of variation in carriage duration: serotype (17%), drug-resistance (9%) and other significant locus effects (7%). A pan-genome-wide association study identified prophage sequences as being associated with decreased carriage duration independent of serotype, potentially by disruption of the competence mechanism. These findings support theoretical models of pneumococcal competition and antibiotic resistance

Trans-abdominal in vivo placental vessel occlusion using High Intensity Focused Ultrasound.

Pre-clinically, High Intensity Focused Ultrasound (HIFU) has been shown to safely and effectively occlude placental blood vessels in the acute setting, when applied through the uterus. However, further development of the technique to overcome the technical challenges of targeting and occluding blood vessels through intact skin remains essential to translation into human studies. So too does the assessment of fetal wellbeing following this procedure, and demonstration of the persistence of vascular occlusion. At 115 ± 10 d gestational age (term~147 days) 12 pregnant sheep were exposed to HIFU (n = 6), or to a sham (n = 6) therapy through intact abdominal skin (1.66 MHz, 5 s duration, in situ ISPTA 1.3-4.4 kW.cm-2). Treatment success was defined as undetectable colour Doppler signal in the target placental vessel following HIFU exposures. Pregnancies were monitored for 21 days using diagnostic ultrasound from one day before HIFU exposure until term, when post-mortem examination was performed. Placental vessels were examined histologically for evidence of persistent vascular occlusion. HIFU occluded 31/34 (91%) of placental vessels targeted, with persistent vascular occlusion evident on histological examination 20 days after treatment. The mean diameter of occluded vessels was 1.4 mm (range 0.3-3.3 mm). All pregnancies survived until post mortem without evidence of significant maternal or fetal iatrogenic harm, preterm labour, maternal or fetal haemorrhage or infection. Three of six ewes exposed to HIFU experienced abdominal skin burns, which healed without intervention within 21 days. Mean fetal weight, fetal growth velocity and other measures of fetal biometry were not affected by exposure to HIFU. Fetal Doppler studies indicated a transient increase in the umbilical artery pulsatility index (PI) and a decrease in middle cerebral artery PI as a result of general anaesthesia, which was not different between sham and treatment groups. We report the first successful application of fully non-invasive HIFU for occlusion of placental blood flow in a pregnant sheep model, with a low risk of significant complications. This proof of concept study demonstrates the potential of this technique for clinical translation