RESUMEN
Studies of bacterial adaptation and evolution are hampered by the difficulty of measuring traits such as virulence, drug resistance, and transmissibility in large populations. In contrast, it is now feasible to obtain high-quality complete assemblies of many bacterial genomes thanks to scalable high-accuracy long-read sequencing technologies. To exploit this opportunity, we introduce a phenotype- and alignment-free method for discovering coselected and epistatically interacting genomic variation from genome assemblies covering both core and accessory parts of genomes. Our approach uses a compact colored de Bruijn graph to approximate the intragenome distances between pairs of loci for a collection of bacterial genomes to account for the impacts of linkage disequilibrium (LD). We demonstrate the versatility of our approach to efficiently identify associations between loci linked with drug resistance and adaptation to the hospital niche in the major human bacterial pathogens Streptococcus pneumoniae and Enterococcus faecalis.
Asunto(s)
Enterococcus faecalis , Epistasis Genética , Genoma Bacteriano , Streptococcus pneumoniae , Streptococcus pneumoniae/genética , Enterococcus faecalis/genética , Desequilibrio de Ligamiento , Humanos , Genómica/métodosRESUMEN
Bacterial genomes differ in both gene content and sequence mutations, which underlie extensive phenotypic diversity, including variation in susceptibility to antimicrobials or vaccine-induced immunity. To identify and quantify important variants, all genes within a population must be predicted, functionally annotated, and clustered, representing the "pangenome." Despite the volume of genome data available, gene prediction and annotation are currently conducted in isolation on individual genomes, which is computationally inefficient and frequently inconsistent across genomes. Here, we introduce the open-source software graph-gene-caller (ggCaller). ggCaller combines gene prediction, functional annotation, and clustering into a single workflow using population-wide de Bruijn graphs, removing redundancy in gene annotation and resulting in more accurate gene predictions and orthologue clustering. We applied ggCaller to simulated and real-world bacterial data sets containing hundreds or thousands of genomes, comparing it to current state-of-the-art tools. ggCaller has considerable speed-ups with equivalent or greater accuracy, particularly with data sets containing complex sources of error, such as assembly contamination or fragmentation. ggCaller is also an important extension to bacterial genome-wide association studies, enabling querying of annotated graphs for functional analyses. We highlight this application by functionally annotating DNA sequences with significant associations to tetracycline and macrolide resistance in Streptococcus pneumoniae, identifying key resistance determinants that were missed when using only a single reference genome. ggCaller is a novel bacterial genome analysis tool with applications in bacterial evolution and epidemiology.
Asunto(s)
Antibacterianos , Estudio de Asociación del Genoma Completo , Farmacorresistencia Bacteriana , Macrólidos , Programas Informáticos , Anotación de Secuencia Molecular , Genoma Bacteriano , Análisis por Conglomerados , AlgoritmosRESUMEN
Bacterial genome data are accumulating at an unprecedented speed due to the routine use of sequencing in clinical diagnoses, public health surveillance, and population genetics studies. Genealogical reconstruction is fundamental to many of these uses; however, inferring genealogy from large-scale genome data sets quickly, accurately, and flexibly is still a challenge. Here, we extend an alignment- and annotation-free method, PopPUNK, to increase its flexibility and interpretability across data sets. Our method, iterative-PopPUNK, rapidly produces multiple consistent cluster assignments across a range of sequence identities. By constructing a partially resolved genealogical tree with respect to these clusters, users can select a resolution most appropriate for their needs. We showed the accuracy of clusters at all levels of similarity and genealogical inference of iterative-PopPUNK based on simulated data and obtained phylogenetically concordant results in real data sets from seven bacterial species. Using two example sets of Escherichia/Shigella and Vibrio parahaemolyticus genomes, we show that iterative-PopPUNK can achieve cluster resolutions ranging from phylogroup down to sequence typing (ST). The iterative-PopPUNK algorithm is implemented in the "PopPUNK_iterate" program, available as part of the PopPUNK package.
Asunto(s)
Algoritmos , Genoma Bacteriano , Bacterias/genética , Análisis por ConglomeradosRESUMEN
SUMMARY: Fastlin is a bioinformatics tool designed for rapid Mycobacterium tuberculosis complex (MTBC) lineage typing. It utilizes an ultra-fast alignment-free approach to detect previously identified barcode single nucleotide polymorphisms associated with specific MTBC lineages. In a comprehensive benchmarking against existing tools, fastlin demonstrated high accuracy and significantly faster running times. AVAILABILITY AND IMPLEMENTATION: fastlin is freely available at https://github.com/rderelle/fastlin and can easily be installed using Conda.
Asunto(s)
Mycobacterium tuberculosis , Mycobacterium tuberculosis/genética , Biología Computacional , Polimorfismo de Nucleótido Simple , Programas InformáticosRESUMEN
The mitochondria are central in the cellular response to changing environmental conditions resulting from disease states, environmental exposures or normal physiological processes. Although the influences of environmental stressors upon the nuclear epigenome are well characterized, the existence and role of the mitochondrial epigenome remains contentious. Here, by quantifying the mitochondrial epigenomic response of pineal gland cells to circadian stress, we confirm the presence of extensive cytosine methylation within the mitochondrial genome. Furthermore, we identify distinct epigenetically plastic regions (mtDMRs) which vary in cytosinic methylation, primarily in a non CpG context, in response to stress and in a sex-specific manner. Motifs enriched in mtDMRs contain recognition sites for nuclear-derived DNA-binding factors (ATF4, HNF4A) important in the cellular metabolic stress response, which we found to be conserved across diverse vertebrate taxa. Together, these findings suggest a new layer of mito-nuclear interaction in which the nuclear metabolic stress response could alter mitochondrial transcriptional dynamics through the binding of nuclear-derived transcription factors in a methylation-dependent context.
Asunto(s)
Genoma Mitocondrial , Vertebrados , Femenino , Masculino , Animales , Vertebrados/genética , Mitocondrias/genética , Epigenoma , Epigenómica , MitomicinaRESUMEN
Streptococcus mitis is a common oral commensal and an opportunistic pathogen that causes bacteremia and infective endocarditis; however, the species has received little attention compared to other pathogenic streptococcal species. Effective and easy-to-use molecular typing tools are essential for understanding bacterial population diversity and biology, but schemes specific for S. mitis are not currently available. We therefore developed a multilocus sequence typing (MLST) scheme and defined sequence clusters or lineages of S. mitis using a comprehensive global data set of 322 genomes (148 publicly available and 174 newly sequenced). We used internal 450-bp sequence fragments of seven housekeeping genes (accA, gki, hom, oppC, patB, rlmN, and tsf) to define the MLST scheme and derived the global S. mitis sequence clusters using the PopPUNK clustering algorithm. We identified an initial set of 259 sequence types (STs) and 258 global sequence clusters. The schemes showed high concordance (100%), capturing extensive S. mitis diversity with strains assigned to multiple unique STs and global sequence clusters. The tools also identified extensive within- and between-host S. mitis genetic diversity among isolates sampled from a cohort of healthy individuals, together with potential transmission events, supported by both phylogeny and pairwise single nucleotide polymorphism (SNP) distances. Our novel molecular typing and strain clustering schemes for S. mitis allow for the integration of new strain data, are electronically portable at the PubMLST database (https://pubmlst.org/smitis), and offer a standardized approach to understanding the population structure of S. mitis. These robust tools will enable new insights into the epidemiology of S. mitis colonization, disease and transmission.
Asunto(s)
Streptococcus mitis , Streptococcus , Humanos , Tipificación de Secuencias Multilocus , Streptococcus mitis/genética , Streptococcus/genética , Análisis por Conglomerados , FilogeniaRESUMEN
BACKGROUND: Intermittent fasting (IF), the implementation of fasting periods of at least 12 consecutive hours on a daily to weekly basis, has received a lot of attention in recent years for imparting the life-prolonging and health-promoting effects of caloric restriction with no or only moderate actual restriction of caloric intake. IF is also widely practiced in the rearing of broiler breeders, the parent stock of meat-type chickens, who require strict feed restriction regimens to prevent the serious health problems associated with their intense appetites. Although intermittent fasting has been extensively used in this context to reduce feed competition and its resulting stress, the potential of IF in chickens as an alternative and complementary model to rodents has received less investigation. In both mammals and birds, the liver is a key component of the metabolic response to IF, responding to variations in energy balance. Here we use a microarray analysis to examine the liver transcriptomics of wild-type Red Jungle Fowl chickens fed either ad libitum, chronically restricted to around 70% of ad libitum daily or intermittently fasted (IF) on a 2:1 (2 days fed, 1 day fasted) schedule without actual caloric restriction. As red junglefowl are ancestral to domestic chicken breeds, these data serve as a baseline to which existing and future transcriptomic results from farmed birds such as broiler breeders can be compared. RESULTS: We find large effects of feeding regimen on liver transcriptomics, with most of the affected genes relating to energy metabolism. A cluster analysis shows that IF is associated with large and reciprocal changes in genes related to lipid and carbohydrate metabolism, but also chronic changes in genes related to amino acid metabolism (generally down-regulated) and cell cycle progression (generally up-regulated). The overall transcription pattern appears to be one of promoting high proliferative plasticity in response to fluctuations in available energy substrates. A small number of inflammation-related genes also show chronically changed expression profiles, as does one circadian rhythm gene. CONCLUSIONS: The increase in proliferative potential suggested by the gene expression changes reported here indicates that birds and mammals respond similarly to intermittent fasting practices. Our findings therefore suggest that the health benefits of periodic caloric restriction are ubiquitous and not restricted to mammals alone. Whether a common fundamental mechanism, for example involving leptin, underpins these benefits remains to be elucidated.
Asunto(s)
Pollos , Ayuno , Animales , Restricción Calórica , Pollos/genética , Expresión Génica , Hígado , MamíferosRESUMEN
BACKGROUND: England's COVID-19 roadmap out of lockdown policy set out the timeline and conditions for the stepwise lifting of non-pharmaceutical interventions (NPIs) as vaccination roll-out continued, with step one starting on March 8, 2021. In this study, we assess the roadmap, the impact of the delta (B.1.617.2) variant of SARS-CoV-2, and potential future epidemic trajectories. METHODS: This mathematical modelling study was done to assess the UK Government's four-step process to easing lockdown restrictions in England, UK. We extended a previously described model of SARS-CoV-2 transmission to incorporate vaccination and multi-strain dynamics to explicitly capture the emergence of the delta variant. We calibrated the model to English surveillance data, including hospital admissions, hospital occupancy, seroprevalence data, and population-level PCR testing data using a Bayesian evidence synthesis framework, then modelled the potential trajectory of the epidemic for a range of different schedules for relaxing NPIs. We estimated the resulting number of daily infections and hospital admissions, and daily and cumulative deaths. Three scenarios spanning a range of optimistic to pessimistic vaccine effectiveness, waning natural immunity, and cross-protection from previous infections were investigated. We also considered three levels of mixing after the lifting of restrictions. FINDINGS: The roadmap policy was successful in offsetting the increased transmission resulting from lifting NPIs starting on March 8, 2021, with increasing population immunity through vaccination. However, because of the emergence of the delta variant, with an estimated transmission advantage of 76% (95% credible interval [95% CrI] 69-83) over alpha, fully lifting NPIs on June 21, 2021, as originally planned might have led to 3900 (95% CrI 1500-5700) peak daily hospital admissions under our central parameter scenario. Delaying until July 19, 2021, reduced peak hospital admissions by three fold to 1400 (95% CrI 700-1700) per day. There was substantial uncertainty in the epidemic trajectory, with particular sensitivity to the transmissibility of delta, level of mixing, and estimates of vaccine effectiveness. INTERPRETATION: Our findings show that the risk of a large wave of COVID-19 hospital admissions resulting from lifting NPIs can be substantially mitigated if the timing of NPI relaxation is carefully balanced against vaccination coverage. However, with the delta variant, it might not be possible to fully lift NPIs without a third wave of hospital admissions and deaths, even if vaccination coverage is high. Variants of concern, their transmissibility, vaccine uptake, and vaccine effectiveness must be carefully monitored as countries relax pandemic control measures. FUNDING: National Institute for Health Research, UK Medical Research Council, Wellcome Trust, and UK Foreign, Commonwealth and Development Office.
Asunto(s)
Vacunas contra la COVID-19/administración & dosificación , COVID-19/prevención & control , COVID-19/transmisión , Control de Enfermedades Transmisibles/organización & administración , SARS-CoV-2 , Cobertura de Vacunación/organización & administración , COVID-19/epidemiología , COVID-19/mortalidad , Inglaterra/epidemiología , Mortalidad Hospitalaria/tendencias , Hospitalización/estadística & datos numéricos , Humanos , Modelos Teóricos , Admisión del Paciente/estadística & datos numéricosRESUMEN
The routine use of genomics for disease surveillance provides the opportunity for high-resolution bacterial epidemiology. Current whole-genome clustering and multilocus typing approaches do not fully exploit core and accessory genomic variation, and they cannot both automatically identify, and subsequently expand, clusters of significantly similar isolates in large data sets spanning entire species. Here, we describe PopPUNK (Population Partitioning Using Nucleotide K -mers), a software implementing scalable and expandable annotation- and alignment-free methods for population analysis and clustering. Variable-length k-mer comparisons are used to distinguish isolates' divergence in shared sequence and gene content, which we demonstrate to be accurate over multiple orders of magnitude using data from both simulations and genomic collections representing 10 taxonomically widespread species. Connections between closely related isolates of the same strain are robustly identified, despite interspecies variation in the pairwise distance distributions that reflects species' diverse evolutionary patterns. PopPUNK can process 103-104 genomes in a single batch, with minimal memory use and runtimes up to 200-fold faster than existing model-based methods. Clusters of strains remain consistent as new batches of genomes are added, which is achieved without needing to reanalyze all genomes de novo. This facilitates real-time surveillance with consistent cluster naming between studies and allows for outbreak detection using hundreds of genomes in minutes. Interactive visualization and online publication is streamlined through the automatic output of results to multiple platforms. PopPUNK has been designed as a flexible platform that addresses important issues with currently used whole-genome clustering and typing methods, and has potential uses across bacterial genetics and public health research.
Asunto(s)
Técnicas de Tipificación Bacteriana/métodos , Genoma Bacteriano , Programas Informáticos , Bacterias/clasificación , Infecciones Bacterianas/epidemiología , Variación Genética , Genómica/métodosRESUMEN
The past two decades have witnessed an alarming expansion of staphylococcal disease caused by community-acquired methicillin-resistant Staphylococcus aureus (CA-MRSA). The factors underlying the epidemic expansion of CA-MRSA lineages such as USA300, the predominant CA-MRSA clone in the United States, are largely unknown. Previously described virulence and antimicrobial resistance genes that promote the dissemination of CA-MRSA are carried by mobile genetic elements, including phages and plasmids. Here, we used high-resolution genomics and experimental infections to characterize the evolution of a USA300 variant plaguing a patient population at increased risk of infection to understand the mechanisms underlying the emergence of genetic elements that facilitate clonal spread of the pathogen. Genetic analyses provided conclusive evidence that fitness (manifest as emergence of a dominant clone) changed coincidently with the stepwise emergence of (i) a unique prophage and mutation of the regulator of the pyrimidine nucleotide biosynthetic operon that promoted abscess formation and colonization, respectively, thereby priming the clone for success; and (ii) a unique plasmid that conferred resistance to two topical microbiocides, mupirocin and chlorhexidine, frequently used for decolonization and infection prevention. The resistance plasmid evolved through successive incorporation of DNA elements from non-S. aureus spp. into an indigenous cryptic plasmid, suggesting a mechanism for interspecies genetic exchange that promotes antimicrobial resistance. Collectively, the data suggest that clonal spread in a vulnerable population resulted from extensive clinical intervention and intense selection pressure toward a pathogen lifestyle that involved the evolution of consequential mutations and mobile genetic elements.
Asunto(s)
Infecciones Comunitarias Adquiridas/microbiología , Staphylococcus aureus Resistente a Meticilina/genética , Virulencia/genética , Animales , Antibacterianos/farmacología , Niño , Clorhexidina/farmacología , Infecciones Comunitarias Adquiridas/tratamiento farmacológico , Genoma Bacteriano/genética , Humanos , Staphylococcus aureus Resistente a Meticilina/efectos de los fármacos , Ratones , Pruebas de Sensibilidad Microbiana/métodos , Mupirocina/farmacología , Filogenia , Plásmidos/genética , Infecciones Estafilocócicas/tratamiento farmacológico , Infecciones Estafilocócicas/microbiologíaRESUMEN
We present fastbaps, a fast solution to the genetic clustering problem. Fastbaps rapidly identifies an approximate fit to a Dirichlet process mixture model (DPM) for clustering multilocus genotype data. Our efficient model-based clustering approach is able to cluster datasets 10-100 times larger than the existing model-based methods, which we demonstrate by analyzing an alignment of over 110 000 sequences of HIV-1 pol genes. We also provide a method for rapidly partitioning an existing hierarchy in order to maximize the DPM model marginal likelihood, allowing us to split phylogenetic trees into clades and subclades using a population genomic model. Extensive tests on simulated data as well as a diverse set of real bacterial and viral datasets show that fastbaps provides comparable or improved solutions to previous model-based methods, while being significantly faster. The method is made freely available under an open source MIT licence as an easy to use R package at https://github.com/gtonkinhill/fastbaps.
Asunto(s)
Algoritmos , Proteínas Bacterianas/clasificación , Teorema de Bayes , Análisis por Conglomerados , Bases de Datos de Proteínas , Proteínas del Virus de la Inmunodeficiencia Humana/clasificación , Modelos Teóricos , Proteínas Bacterianas/genética , Biología Computacional/métodos , Proteínas del Virus de la Inmunodeficiencia Humana/genética , Filogenia , Reproducibilidad de los ResultadosRESUMEN
Covariance-based discovery of polymorphisms under co-selective pressure or epistasis has received considerable recent attention in population genomics. Both statistical modeling of the population level covariation of alleles across the chromosome and model-free testing of dependencies between pairs of polymorphisms have been shown to successfully uncover patterns of selection in bacterial populations. Here we introduce a model-free method, SpydrPick, whose computational efficiency enables analysis at the scale of pan-genomes of many bacteria. SpydrPick incorporates an efficient correction for population structure, which adjusts for the phylogenetic signal in the data without requiring an explicit phylogenetic tree. We also introduce a new type of visualization of the results similar to the Manhattan plots used in genome-wide association studies, which enables rapid exploration of the identified signals of co-evolution. Simulations demonstrate the usefulness of our method and give some insight to when this type of analysis is most likely to be successful. Application of the method to large population genomic datasets of two major human pathogens, Streptococcus pneumoniae and Neisseria meningitidis, revealed both previously identified and novel putative targets of co-selection related to virulence and antibiotic resistance, highlighting the potential of this approach to drive molecular discoveries, even in the absence of phenotypic data.
Asunto(s)
Biología Computacional/métodos , Epistasis Genética , Genoma Bacteriano/genética , Genómica , Farmacorresistencia Microbiana/genética , Humanos , Metagenómica/métodos , Neisseria meningitidis/genética , Neisseria meningitidis/patogenicidad , Streptococcus pneumoniae/genética , Virulencia/genéticaRESUMEN
Cadmium zinc telluride (CdZnTe) detectors are known to suffer from polarization effects under high photon flux due to poor hole transport in the crystal material. This has led to the development of a high-flux capable CdZnTe material (HF-CdZnTe). Detectors with the HF-CdZnTe material have shown promising results at mitigating the onset of the polarization phenomenon, likely linked to improved crystal quality and hole carrier transport. Better hole transport will have an impact on charge collection, particularly in pixelated detector designs and thick sensors (>1 mm). In this paper, the presence of charge sharing and the magnitude of charge loss were calculated for a 2 mm thick pixelated HF-CdZnTe detector with 250 µm pixel pitch and 25 µm pixel gaps, bonded to the STFC HEXITEC ASIC. Results are compared with a CdTe detector as a reference point and supported with simulations from a Monte-Carlo detector model. Charge sharing events showed minimal charge loss in the HF-CdZnTe, resulting in a spectral resolution of 1.63 ± 0.08 keV Full Width at Half Maximum (FWHM) for bipixel charge sharing events at 59.5 keV. Depth of interaction effects were shown to influence charge loss in shared events. The performance is discussed in relation to the improved hole transport of HF-CdZnTe and comparison with simulated results provided evidence of a uniform electric field.
RESUMEN
Legionella pneumophila is an environmental bacterium and the leading cause of Legionnaires' disease. Just five sequence types (ST), from more than 2000 currently described, cause nearly half of disease cases in northwest Europe. Here, we report the sequence and analyses of 364 L. pneumophila genomes, including 337 from the five disease-associated STs and 27 representative of the species diversity. Phylogenetic analyses revealed that the five STs have independent origins within a highly diverse species. The number of de novo mutations is extremely low with maximum pairwise single-nucleotide polymorphisms (SNPs) ranging from 19 (ST47) to 127 (ST1), which suggests emergences within the last century. Isolates sampled geographically far apart differ by only a few SNPs, demonstrating rapid dissemination. These five STs have been recombining recently, leading to a shared pool of allelic variants potentially contributing to their increased disease propensity. The oldest clone, ST1, has spread globally; between 1940 and 2000, four new clones have emerged in Europe, which show long-distance, rapid dispersal. That a large proportion of clinical cases is caused by recently emerged and internationally dispersed clones, linked by convergent evolution, is surprising for an environmental bacterium traditionally considered to be an opportunistic pathogen. To simultaneously explain recent emergence, rapid spread and increased disease association, we hypothesize that these STs have adapted to new man-made environmental niches, which may be linked by human infection and transmission.
Asunto(s)
Evolución Molecular , Legionella pneumophila/genética , Enfermedad de los Legionarios/microbiología , Humanos , Legionella pneumophila/clasificación , Legionella pneumophila/aislamiento & purificación , Legionella pneumophila/patogenicidad , Mutación , Filogenia , Polimorfismo de Nucleótido Simple , Selección Genética , Virulencia/genéticaRESUMEN
Summary: 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. Availability and implementation: pyseer is written in python and is freely available at https://github.com/mgalardini/pyseer, or can be installed through pip. Documentation and a tutorial are available at http://pyseer.readthedocs.io. Supplementary information: Supplementary data are available at Bioinformatics online.
Asunto(s)
Bacterias/crecimiento & desarrollo , Estudios de Asociación Genética , Programas Informáticos , Biología Computacional , Modelos EstadísticosRESUMEN
The development of low profile gamma-ray detectors has encouraged the production of small field of view (SFOV) hand-held imaging devices for use at the patient bedside and in operating theatres. Early development of these SFOV cameras was focussed on a single modality-gamma ray imaging. Recently, a hybrid system-gamma plus optical imaging-has been developed. This combination of optical and gamma cameras enables high spatial resolution multi-modal imaging, giving a superimposed scintigraphic and optical image. Hybrid imaging offers new possibilities for assisting clinicians and surgeons in localising the site of uptake in procedures such as sentinel node detection. The hybrid camera concept can be extended to a multimodal detector design which can offer stereoscopic images, depth estimation of gamma-emitting sources, and simultaneous gamma and fluorescence imaging. Recent improvements to the hybrid camera have been used to produce dual-modality images in both laboratory simulations and in the clinic. Hybrid imaging of a patient who underwent thyroid scintigraphy is reported. In addition, we present data which shows that the hybrid camera concept can be extended to estimate the position and depth of radionuclide distribution within an object and also report the first combined gamma and Near-Infrared (NIR) fluorescence images.
Asunto(s)
Cámaras gamma , Rayos gamma , Imagen Óptica , CintigrafíaRESUMEN
The material properties and morphologies of the modified integumentary organs of birds (the keratinous bills, claws and feathers) have evolved to withstand the variety of mechanical stresses imposed by their interaction with the environment. These stresses are likely to vary temporally in seasonal environments and may also differ between the sexes as a result of behavioural dimorphism. Here we investigate the morphology and material properties of the claws of male and female Svalbard ptarmigan (Lagopus muta hyperborea) during the summer and winter using nanoindentation. Despite differences in locomotor demands between the sexes and pronounced seasonal differences in environmental conditions, like ground substrate, ambient temperature and day length, there was no significant difference in Young׳s modulus or hardness between the seasons for each sex. However, when comparing males and females, female claws were significantly harder than those of males and both sexes had significantly wider claws during winter. We propose that wider claws may follow winter claw moulting as the claws are regrown and form an important part of the ptarmigan׳s snowshoe-like foot that is an adaptation to locomotion on snow. Future work focusing on growth rates and more broad measures of material properties in both captive and wild birds is required to determine the extent of seasonal and sex differences in the material properties of their keratinous structures.
Asunto(s)
Aclimatación , Galliformes/fisiología , Queratinas/metabolismo , Estaciones del Año , Animales , Femenino , Galliformes/anatomía & histología , Galliformes/metabolismo , Pezuñas y Garras/anatomía & histología , Pezuñas y Garras/metabolismo , Masculino , Factores SexualesRESUMEN
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.
Asunto(s)
COVID-19 , Simulación por Computador , SARS-CoV-2 , Humanos , COVID-19/prevención & control , COVID-19/epidemiología , COVID-19/inmunología , COVID-19/virología , SARS-CoV-2/inmunología , Antibacterianos/farmacología , Pandemias/prevención & control , Farmacorresistencia MicrobianaRESUMEN
Minimum Inhibitory Concentrations (MICs) are the gold standard for quantitatively measuring antibiotic resistance. However, lab-based MIC determination can be time-consuming and suffers from low reproducibility, and interpretation as sensitive or resistant relies on guidelines which change over time. Genome sequencing and machine learning promise to allow in silico MIC prediction as an alternative approach which overcomes some of these difficulties, albeit the interpretation of MIC is still needed. Nevertheless, precisely how we should handle MIC data when dealing with predictive models remains unclear, since they are measured semi-quantitatively, with varying resolution, and are typically also left- and right-censored within varying ranges. We therefore investigated genome-based prediction of MICs in the pathogen Klebsiella pneumoniae using 4367 genomes with both simulated semi-quantitative traits and real MICs. As we were focused on clinical interpretation, we used interpretable rather than black-box machine learning models, namely, Elastic Net, Random Forests, and linear mixed models. Simulated traits were generated accounting for oligogenic, polygenic, and homoplastic genetic effects with different levels of heritability. Then we assessed how model prediction accuracy was affected when MICs were framed as regression and classification. Our results showed that treating the MICs differently depending on the number of concentration levels of antibiotic available was the most promising learning strategy. Specifically, to optimise both prediction accuracy and inference of the correct causal variants, we recommend considering the MICs as continuous and framing the learning problem as a regression when the number of observed antibiotic concentration levels is large, whereas with a smaller number of concentration levels they should be treated as a categorical variable and the learning problem should be framed as a classification. Our findings also underline how predictive models can be improved when prior biological knowledge is taken into account, due to the varying genetic architecture of each antibiotic resistance trait. Finally, we emphasise that incrementing the population database is pivotal for the future clinical implementation of these models to support routine machine-learning based diagnostics.
Asunto(s)
Antibacterianos , Klebsiella pneumoniae , Klebsiella pneumoniae/genética , Reproducibilidad de los Resultados , Antibacterianos/farmacología , Aprendizaje Automático , Pruebas de Sensibilidad MicrobianaRESUMEN
Defining the population structure of a pathogen is a key part of epidemiology, as genomically related isolates are likely to share key clinical features such as antimicrobial resistance profiles and invasiveness. Multiple different methods are currently used to cluster together closely related genomes, potentially leading to inconsistency between studies. Here, we use a global dataset of 26 306 Streptococcus pneumoniae genomes to compare four clustering methods: gene-by-gene seven-locus MLST, core genome MLST (cgMLST)-based hierarchical clustering (HierCC) assignments, life identification number (LIN) barcoding and k-mer-based PopPUNK clustering (known as GPSCs in this species). We compare the clustering results with phylogenetic and pan-genome analyses to assess their relationship with genome diversity and evolution, as we would expect a good clustering method to form a single monophyletic cluster that has high within-cluster similarity of genomic content. We show that the four methods are generally able to accurately reflect the population structure based on these metrics and that the methods were broadly consistent with each other. We investigated further to study the discrepancies in clusters. The greatest concordance was seen between LIN barcoding and HierCC (adjusted mutual information score=0.950), which was expected given that both methods utilize cgMLST, but have different methods for defining an individual cluster and different core genome schema. However, the existence of differences between the two methods shows that the selection of a core genome schema can introduce inconsistencies between studies. GPSC and HierCC assignments were also highly concordant (AMI=0.946), showing that k-mer-based methods which use the whole genome and do not require the careful selection of a core genome schema are just as effective at representing the population structure. Additionally, where there were differences in clustering between these methods, this could be explained by differences in the accessory genome that were not identified in cgMLST. We conclude that for S. pneumoniae, standardized and stable nomenclature is important as the number of genomes available expands. Furthermore, the research community should transition away from seven-locus MLST, whilst cgMLST, GPSC and LIN assignments should be used more widely. However, to allow for easy comparison between studies and to make previous literature relevant, the reporting of multiple clustering names should be standardized within the research.