ORCID Profile
0000-0003-4397-2224
Current Organisation
University of Oslo
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Microbial genetics | Microbiology | Bioinformatic methods development | Phylogeny and comparative analysis |
Publisher: CSIRO Publishing
Date: 2017
DOI: 10.1071/CH17228
Publisher: eLife Sciences Publications, Ltd
Date: 02-03-2021
DOI: 10.7554/ELIFE.64618
Abstract: COVID-19 poses a major challenge to care homes, as SARS-CoV-2 is readily transmitted and causes disproportionately severe disease in older people. Here, 1167 residents from 337 care homes were identified from a dataset of 6600 COVID-19 cases from the East of England. Older age and being a care home resident were associated with increased mortality. SARS-CoV-2 genomes were available for 700 residents from 292 care homes. By integrating genomic and temporal data, 409 viral clusters within the 292 homes were identified, indicating two different patterns – outbreaks among care home residents and independent introductions with limited onward transmission. Approximately 70% of residents in the genomic analysis were admitted to hospital during the study, providing extensive opportunities for transmission between care homes and hospitals. Limiting viral transmission within care homes should be a key target for infection control to reduce COVID-19 mortality in this population.
Publisher: Microbiology Society
Date: 02-2021
Abstract: Escherichia coli is a highly erse organism that includes a range of commensal and pathogenic variants found across a range of niches and worldwide. In addition to causing severe intestinal and extraintestinal disease, E. coli is considered a priority pathogen due to high levels of observed drug resistance. The ersity in the E. coli population is driven by high genome plasticity and a very large gene pool. All these have made E. coli one of the most well-studied organisms, as well as a commonly used laboratory strain. Today, there are thousands of sequenced E. coli genomes stored in public databases. While data is widely available, accessing the information in order to perform analyses can still be a challenge. Collecting relevant available data requires accessing different sources, where data may be stored in a range of formats, and often requires further manipulation and processing to apply various analyses and extract useful information. In this study, we collated and intensely curated a collection of over 10 000 E. coli and Shigella genomes to provide a single, uniform, high-quality dataset. Shigella were included as they are considered specialized pathovars of E. coli . We provide these data in a number of easily accessible formats that can be used as the foundation for future studies addressing the biological differences between E. coli lineages and the distribution and flow of genes in the E. coli population at a high resolution. The analysis we present emphasizes our lack of understanding of the true ersity of the E. coli species, and the biased nature of our current understanding of the genetic ersity of such a key pathogen.
Publisher: Cold Spring Harbor Laboratory
Date: 06-08-2023
DOI: 10.1101/2023.08.04.551407
Abstract: Population genomics has revolutionised our ability to study bacterial evolution by enabling data-driven discovery of the genetic architecture of trait variation. Genome-wide association studies (GWAS) have more recently become accompanied by genome-wide epistasis and co-selection (GWES) analysis, which offers a phenotype-free approach to generating hypotheses about selective processes that simultaneously impact multiple loci across the genome. However, existing GWES methods only consider associations between distant pairs of loci within the genome due to the strong impact of linkage-disequilibrium (LD) over short distances. Based on the general functional organisation of genomes it is nevertheless expected that the majority of co-selection and epistasis will act within relatively short genomic proximity, on co-variation occurring within genes and their promoter regions, and within operons. Here we introduce LDWeaver, which enables an exhaustive GWES across both short- and long-range LD, to disentangle likely neutral co-variation from selection. We demonstrate the ability of LDWeaver to efficiently generate hypotheses about co-selection using large genomic surveys of multiple major human bacterial pathogen species and validate several findings using functional annotation and phenotypic measurements. Our approach will facilitate the study of bacterial evolution in the light of rapidly expanding population genomic data.
Publisher: Cold Spring Harbor Laboratory
Date: 14-10-2023
Publisher: eLife Sciences Publications, Ltd
Date: 13-08-2021
DOI: 10.7554/ELIFE.66857
Abstract: Monitoring the spread of SARS-CoV-2 and reconstructing transmission chains has become a major public health focus for many governments around the world. The modest mutation rate and rapid transmission of SARS-CoV-2 prevents the reconstruction of transmission chains from consensus genome sequences, but within-host genetic ersity could theoretically help identify close contacts. Here we describe the patterns of within-host ersity in 1181 SARS-CoV-2 s les sequenced to high depth in duplicate. 95.1% of s les show within-host mutations at detectable allele frequencies. Analyses of the mutational spectra revealed strong strand asymmetries suggestive of damage or RNA editing of the plus strand, rather than replication errors, dominating the accumulation of mutations during the SARS-CoV-2 pandemic. Within- and between-host ersity show strong purifying selection, particularly against nonsense mutations. Recurrent within-host mutations, many of which coincide with known phylogenetic homoplasies, display a spectrum and patterns of purifying selection more suggestive of mutational hotspots than recombination or convergent evolution. While allele frequencies suggest that most s les result from infection by a single lineage, we identify multiple putative ex les of co-infection. Integrating these results into an epidemiological inference framework, we find that while sharing of within-host variants between s les could help the reconstruction of transmission chains, mutational hotspots and rare cases of superinfection can confound these analyses.
Publisher: Wiley
Date: 11-01-2018
DOI: 10.1111/FEBS.14370
Abstract: Transient regulation of Plasmodium numbers below the density that induces fever has been observed in chronic malaria infections in humans. This species transcending control cannot be explained by immunity alone. Using an in vitro system we have observed density dependent regulation of malaria population size as a mechanism to possibly explain these in vivo observations. Specifically, Plasmodium falciparum blood stages from a high but not low-density environment exhibited unique phenotypic changes during the late trophozoite (LT) and schizont stages of the intraerythrocytic cycle. These included in order of appearance: failure of schizonts to mature and merozoites to replicate, apoptotic-like morphological changes including shrinking, loss of mitochondrial membrane potential, and blebbing with eventual release of aberrant parasites from infected erythrocytes. This unique death phenotype was triggered in a stage-specific manner by sensing of a high-density culture environment. Conditions of glucose starvation, nutrient depletion, and high lactate could not induce the phenotype. A high-density culture environment induced rapid global changes in the parasite transcriptome including differential expression of genes involved in cell remodeling, clonal antigenic variation, metabolism, and cell death pathways including an apoptosis-associated metacaspase gene. This transcriptional profile was also characterized by concomitant expression of asexual and sexual stage-specific genes. The data show strong evidence to support our hypothesis that density sensing exists in P. falciparum. They indicate that an apoptotic-like mechanism may play a role in P. falciparum density regulation, which, as in yeast, has features quite distinguishable from mammalian apoptosis. Gene expression data are available in the GEO databases under the accession number GSE91188.
Publisher: Cold Spring Harbor Laboratory
Date: 26-10-2018
DOI: 10.1101/454355
Abstract: 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 analysing 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 maximise 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 erse set of real bacterial and viral datasets show that fastbaps provides comparable or improved solutions to previous model-based methods, while generally being significantly faster. The method is made freely available under an open source MIT licence as an easy to use R package at tonkinhill/fastbaps .
Publisher: Cold Spring Harbor Laboratory
Date: 14-11-2020
DOI: 10.1101/2020.11.13.381137
Abstract: Sequestration of Plasmodium falciparum -infected erythrocytes to host endothelium through the parasite-derived Pf EMP1 adhesion proteins is central to the development of malaria pathogenesis. Pf EMP1 proteins have ersified and expanded to encompass many sequence variants conferring each parasite a similar array of human endothelial receptor binding phenotypes. Here, we analyzed RNA-seq profiles of parasites isolated from 32 P. falciparum infected adult travelers returning to Germany. Patients were categorized into either malaria naïve (n=15) or pre-exposed (n=17), and into severe (n=8) or non-severe (n=24) cases. For differential expression analysis of Pf EMP1-encoding var gene transcripts were de novo assembled from RNA-seq data and, in parallel, var expressed sequence tags were analyzed and used to predict the encoded domain composition of the transcripts. Both approaches showed in concordance that severe malaria was associated with Pf EMP1 containing the endothelial protein C receptor (EPCR)-binding CIDRα1 domain, whereas CD36-binding Pf EMP1 was linked to non-severe malaria outcomes. First-time infected adults were more likely to develop severe symptoms and tended to be infected for a longer period. Thus, parasites with more pathogenic Pf EMP1 variants are more common in patients with a naïve immune status and/or adverse inflammatory host responses to first infections favors growth of EPCR-binding parasites.
Publisher: Oxford University Press (OUP)
Date: 30-07-2019
DOI: 10.1093/NAR/GKZ656
Abstract: 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.
Publisher: Springer Science and Business Media LLC
Date: 08-10-2020
DOI: 10.1038/S42003-020-01290-9
Abstract: Hyper-virulent Streptococcus pneumoniae serotype 1 strains are endemic in Sub-Saharan Africa and frequently cause lethal meningitis outbreaks. It remains unknown whether genetic variation in serotype 1 strains modulates tropism into cerebrospinal fluid to cause central nervous system (CNS) infections, particularly meningitis. Here, we address this question through a large-scale linear mixed model genome-wide association study of 909 African pneumococcal serotype 1 isolates collected from CNS and non-CNS human s les. By controlling for host age, geography, and strain population structure, we identify genome-wide statistically significant genotype-phenotype associations in surface-exposed choline-binding ( P = 5.00 × 10 −08 ) and helicase proteins ( P = 1.32 × 10 −06 ) important for invasion, immune evasion and pneumococcal tropism to CNS. The small effect sizes and negligible heritability indicated that causation of CNS infection requires multiple genetic and other factors reflecting a complex and polygenic aetiology. Our findings suggest that certain pathogen genetic variation modulate pneumococcal survival and tropism to CNS tissue, and therefore, virulence for meningitis.
Publisher: Cold Spring Harbor Laboratory
Date: 24-08-2023
Abstract: Bacterial genomes differ in both gene content and sequence mutations, which underlies extensive phenotypic ersity, 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 in idual 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 datasets 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 datasets 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.
Publisher: Microbiology Society
Date: 25-05-2023
Abstract: Horizontal gene transfer (HGT) and the resulting patterns of gene gain and loss are a fundamental part of bacterial evolution. Investigating these patterns can help us to understand the role of selection in the evolution of bacterial pangenomes and how bacteria adapt to a new niche. Predicting the presence or absence of genes can be a highly error-prone process that can confound efforts to understand the dynamics of horizontal gene transfer. This review discusses both the challenges in accurately constructing a pangenome and the potential consequences errors can have on downstream analyses. We hope that by summarizing these issues researchers will be able to avoid potential pitfalls, leading to improved bacterial pangenome analyses.
Publisher: Springer Science and Business Media LLC
Date: 10-10-2022
DOI: 10.1038/S41564-022-01238-1
Abstract: Characterizing the genetic ersity of pathogens within the host promises to greatly improve surveillance and reconstruction of transmission chains. For bacteria, it also informs our understanding of inter-strain competition and how this shapes the distribution of resistant and sensitive bacteria. Here we study the genetic ersity of Streptococcus pneumoniae within 468 infants and 145 of their mothers by deep sequencing whole pneumococcal populations from 3,761 longitudinal nasopharyngeal s les. We demonstrate that deep sequencing has unsurpassed sensitivity for detecting multiple colonization, doubling the rate at which highly invasive serotype 1 bacteria were detected in carriage compared with gold-standard methods. The greater resolution identified an elevated rate of transmission from mothers to their children in the first year of the child’s life. Comprehensive treatment data demonstrated that infants were at an elevated risk of both the acquisition and persistent colonization of a multidrug-resistant bacterium following antimicrobial treatment. Some alleles were enriched after antimicrobial treatment, suggesting that they aided persistence, but generally purifying selection dominated within-host evolution. Rates of co-colonization imply that in the absence of treatment, susceptible lineages outcompeted resistant lineages within the host. These results demonstrate the many benefits of deep sequencing for the genomic surveillance of bacterial pathogens.
Publisher: Cold Spring Harbor Laboratory
Date: 2023
Abstract: Horizontal gene transfer (HGT) plays a critical role in the evolution and ersification of many microbial species. The resulting dynamics of gene gain and loss can have important implications for the development of antibiotic resistance and the design of vaccine and drug interventions. Methods for the analysis of gene presence/absence patterns typically do not account for errors introduced in the automated annotation and clustering of gene sequences. In particular, methods adapted from ecological studies, including the pangenome gene accumulation curve, can be misleading as they may reflect the underlying ersity in the temporal s ling of genomes rather than a difference in the dynamics of HGT. Here, we introduce Panstripe, a method based on generalized linear regression that is robust to population structure, s ling bias, and errors in the predicted presence/absence of genes. We show using simulations that Panstripe can effectively identify differences in the rate and number of genes involved in HGT events, and illustrate its capability by analyzing several erse bacterial genome data sets representing major human pathogens.
Publisher: eLife Sciences Publications, Ltd
Date: 04-01-2021
Publisher: Wiley
Date: 21-12-2018
DOI: 10.1111/FEBS.14715
Abstract: The mechanisms that underpin the formation, growth and composition of otoliths, the biomineralized stones in the inner ear of fish, are largely unknown, as only a few fish inner ear proteins have been reported. Using a partial transcriptome for the inner ear of black bream (Acanthopagrus butcheri), in conjunction with proteomic data, we discovered hundreds of previously unknown proteins in the otolith. This allowed us to develop hypotheses to explain the mechanisms of inorganic material supply and daily formation of growth bands. We further identified a likely protein mediator of crystal nucleation and an explanation for the apparent metabolic inertness of the otolith. Due to the formation of both daily and annual increments, otoliths are routinely employed as natural chronometers, being used for age and growth estimation, fisheries stock assessments, and the reconstruction of habitat use, movement, diet and the impacts of climate change. Our findings provide an unprecedented view of otolith molecular machinery, aiding in the interpretation of these essential archived data.
Publisher: Oxford University Press (OUP)
Date: 05-07-2023
Abstract: Extrachromosomal elements of bacterial cells such as plasmids are notorious for their importance in evolution and adaptation to changing ecology. However, high-resolution population-wide analysis of plasmids has only become accessible recently with the advent of scalable long-read sequencing technology. Current typing methods for the classification of plasmids remain limited in their scope which motivated us to develop a computationally efficient approach to simultaneously recognize novel types and classify plasmids into previously identified groups. Here, we introduce mge-cluster that can easily handle thousands of input sequences which are compressed using a unitig representation in a de Bruijn graph. Our approach offers a faster runtime than existing algorithms, with moderate memory usage, and enables an intuitive visualization, classification and clustering scheme that users can explore interactively within a single framework. Mge-cluster platform for plasmid analysis can be easily distributed and replicated, enabling a consistent labelling of plasmids across past, present, and future sequence collections. We underscore the advantages of our approach by analysing a population-wide plasmid data set obtained from the opportunistic pathogen Escherichia coli, studying the prevalence of the colistin resistance gene mcr-1.1 within the plasmid population, and describing an instance of resistance plasmid transmission within a hospital environment.
Publisher: Oxford University Press (OUP)
Date: 13-01-2022
Abstract: Whole-genome sequencing has facilitated genome-wide analyses of association, prediction and heritability in many organisms. However, such analyses in bacteria are still in their infancy, being limited by difficulties including genome plasticity and strong population structure. Here we propose a suite of methods including linear mixed models, elastic net and LD-score regression, adapted to bacterial traits using innovations such as frequency-based allele coding, both insertion/deletion and nucleotide testing and heritability partitioning. We compare and validate our methods against the current state-of-art using simulations, and analyse three phenotypes of the major human pathogen Streptococcus pneumoniae, including the first analyses of minimum inhibitory concentrations (MIC) for penicillin and ceftriaxone. We show that the MIC traits are highly heritable with high prediction accuracy, explained by many genetic associations under good population structure control. In ceftriaxone MIC, this is surprising because none of the isolates are resistant as per the inhibition zone criteria. We estimate that half of the heritability of penicillin MIC is explained by a known drug-resistance region, which also contributes a quarter of the ceftriaxone MIC heritability. For the within-host carriage duration phenotype, no associations were observed, but the moderate heritability and prediction accuracy indicate a moderately polygenic trait.
Publisher: Springer Science and Business Media LLC
Date: 22-07-2020
Publisher: Elsevier BV
Date: 07-2021
Publisher: Springer Science and Business Media LLC
Date: 18-09-2017
DOI: 10.1038/S41598-017-11814-9
Abstract: Plasmodium falciparum causes a spectrum of malarial disease from asymptomatic to uncomplicated through to severe. Investigations of parasite virulence have associated the expression of distinct variants of the major surface antigen of the blood stages known as Pf EMP1 encoded by up to 60 var genes per genome. Looking at the population genomics of var genes in cases of uncomplicated malaria, we set out to determine if there was any evidence of a selective sweep of specific var genes or clonal epidemic structure related to the incidence of uncomplicated disease in children. By sequencing the conserved DBLα domain of var genes from six sentinel sites in Uganda we found that the parasites causing uncomplicated P. falciparum disease in children were highly erse and that every child had a unique var DBLα repertoire. Despite extensive var DBLα ersity and minimal overlap between repertoires, specific DBLα types and groups were conserved at the population level across Uganda. This pattern was the same regardless of the geographic distance or malaria transmission intensity. These data lead us to propose that any parasite can cause uncomplicated malarial disease and that these erse parasite repertoires are composed of both upsA and non-upsA var gene groups.
Publisher: eLife Sciences Publications, Ltd
Date: 18-04-2021
Publisher: Cold Spring Harbor Laboratory
Date: 19-12-2022
DOI: 10.1101/2022.12.16.520696
Abstract: Extrachromosomal elements of bacterial cells such as plasmids are notorious for their importance in evolution and adaptation to changing ecology. However, high-resolution population-wide analysis of plasmids has only become accessible recently with the advent of scalable long-read sequencing technology. Current typing methods for the classification of plasmids remain limited in their scope which motivated us to develop a computationally efficient approach to simultaneously recognize novel types and classify plasmids into previously identified groups. Our method can easily handle thousands of input sequences which are compressed using a unitig representation in a de Bruijn graph. We provide an intuitive visualization, classification and clustering scheme that users can explore interactively. This provides a framework that can be easily distributed and replicated, enabling a consistent labelling of plasmids across past, present, and future sequence collections. We illustrate the attractive features of our approach by the analysis of population-wide plasmid data from the opportunistic pathogen Escherichia coli and the distribution of the colistin resistance gene mcr-1 . 1 in the plasmid population.
Publisher: Cold Spring Harbor Laboratory
Date: 25-12-2020
DOI: 10.1101/2020.12.23.424229
Abstract: Monitoring the spread of SARS-CoV-2 and reconstructing transmission chains has become a major public health focus for many governments around the world. The modest mutation rate and rapid transmission of SARS-CoV-2 prevents the reconstruction of transmission chains from consensus genome sequences, but within-host genetic ersity could theoretically help identify close contacts. Here we describe the patterns of within-host ersity in 1,181 SARS-CoV-2 s les sequenced to high depth in duplicate. 95% of s les show within-host mutations at detectable allele frequencies. Analyses of the mutational spectra revealed strong strand asymmetries suggestive of damage or RNA editing of the plus strand, rather than replication errors, dominating the accumulation of mutations during the SARS-CoV-2 pandemic. Within and between host ersity show strong purifying selection, particularly against nonsense mutations. Recurrent within-host mutations, many of which coincide with known phylogenetic homoplasies, display a spectrum and patterns of purifying selection more suggestive of mutational hotspots than recombination or convergent evolution. While allele frequencies suggest that most s les result from infection by a single lineage, we identify multiple putative ex les of co-infection. Integrating these results into an epidemiological inference framework, we find that while sharing of within-host variants between s les could help the reconstruction of transmission chains, mutational hotspots and rare cases of superinfection can confound these analyses.
Publisher: Cold Spring Harbor Laboratory
Date: 15-06-2023
DOI: 10.1101/2023.06.15.545111
Abstract: Mutational spectra describe the pattern of mutations acquired during evolution and are driven by factors including mutagens, repair processes and selection. Calculating mutational spectra of pathogen genomic datasets may enable analysis of factors that influence these mutational processes, including replication niches, transmission routes and pathogen biology. Here, we introduce MutTui, which can leverage multiple types of sequence data to calculate and compare mutational spectra of DNA and RNA pathogens. MutTui is available at hrisruis/MutTui .
Publisher: Springer Science and Business Media LLC
Date: 09-03-2021
DOI: 10.1038/S41467-021-21749-5
Abstract: Enterococcus faecalis is a commensal and nosocomial pathogen, which is also ubiquitous in animals and insects, representing a classical generalist microorganism. Here, we study E. faecalis isolates ranging from the pre-antibiotic era in 1936 up to 2018, covering a large set of host species including wild birds, mammals, healthy humans, and hospitalised patients. We sequence the bacterial genomes using short- and long-read techniques, and identify multiple extant hospital-associated lineages, with last common ancestors dating back as far as the 19th century. We find a population cohesively connected through homologous recombination, a metabolic flexibility despite a small genome size, and a stable large core genome. Our findings indicate that the apparent hospital adaptations found in hospital-associated E. faecalis lineages likely predate the “modern hospital” era, suggesting selection in another niche, and underlining the generalist nature of this nosocomial pathogen.
Publisher: Cold Spring Harbor Laboratory
Date: 21-02-2022
DOI: 10.1101/2022.02.20.480002
Abstract: Characterising the genetic ersity of pathogens within the host promises to greatly improve surveillance and reconstruction of transmission chains. For bacteria, it also informs our understanding of inter-strain competition, and how this shapes the distribution of resistant and sensitive bacteria. Here we study the genetic ersity of Streptococcus pneumoniae within in idual infants and their mothers by deep sequencing whole pneumococcal populations from longitudinal nasopharyngeal s les. We demonstrate deep sequencing has unsurpassed sensitivity for detecting multiple colonisation, doubling the rate at which highly invasive serotype 1 bacteria were detected in carriage compared to gold-standard methods. The greater resolution identified an elevated rate of transmission from mothers to their children in the first year of the child’s life. Comprehensive treatment data demonstrated infants were at an elevated risk of both the acquisition, and persistent colonisation, of a multidrug resistant bacterium following antimicrobial treatment. Some alleles were enriched after antimicrobial treatment, suggesting they aided persistence, but generally purifying selection dominated within-host evolution. Rates of co-colonisation imply that in the absence of treatment, susceptible lineages outcompeted resistant lineages within the host. These results demonstrate the many benefits of deep sequencing for the genomic surveillance of bacterial pathogens.
Publisher: Springer Science and Business Media LLC
Date: 24-01-2020
DOI: 10.1007/S10126-020-09945-8
Abstract: Cnidarians are one of the oldest known animal lineages (ca. 700 million years), with a unique envenomation apparatus to deliver a potent mixture of peptides and proteins. Some peptide toxins from cnidarian venom have proven therapeutic potential. Here, we use a transcriptomic roteomic strategy to identify sequences with similarity to known venom protein families in the tentacles of the endemic Australian 'speckled anemone' (Oulactis sp.). Illumina RNASeq data were assembled de novo. Annotated sequences in the library were verified by cross-referencing in iduals' transcriptomes or protein expression evidence from LC-MS/MS data. Sequences include pore-forming toxins, phospholipases, peptidases, neurotoxins (sodium and potassium channel modulators), cysteine-rich secretory proteins and defensins (antimicrobial peptides). Fewer than 4% of the sequences in the library occurred across the three in iduals examined, demonstrating high sequence variability of an in idual's arsenal. We searched for actinoporins in Oulactis sp. to assess sequence similarity to the only described toxins (OR-A and -G) for this genus and examined the domain architecture of venom-related peptides and proteins. The novel putative actinoporin of Oulactis sp. has a greater similarity to other species in the Actiniidae family than to O. orientalis. Venom-related sequences have an architecture that occurs in single, repeat or multi-domain combinations of venom-related (e.g. ShK-like) and non-venom (e.g. whey acid protein) domains. This study has produced the first transcriptomes for an endemic Australian sea anemone species and the genus Oulactis, while identifying nearly 400 novel venom-related peptides and proteins for future structural and functional analyses and venom evolution studies.
Publisher: Springer Science and Business Media LLC
Date: 07-08-2017
Publisher: Cold Spring Harbor Laboratory
Date: 31-08-2018
DOI: 10.1101/404624
Abstract: The ability to distinguish between pathogens is a fundamental requirement to understand the epidemiology of infectious diseases. Phylogenetic analysis of genomic data can provide a powerful platform to identify lineages within bacterial populations, and thus inform outbreak investigation and transmission dynamics. However, resolving differences between pathogens associated with low variant (LV) populations carrying low median pairwise single nucleotide variant (SNV) distances, remains a major challenge. Here we present rPinecone, an R package designed to define sub-lineages within closely related LV populations. rPinecone uses a root-to-tip directional approach to define sub-lineages within a phylogenetic tree according to SNV distance from the ancestral node. The utility of this program was demonstrated using genomic data of two LV populations: a hospital outbreak of methicillin-resistant Staphylococcus aureus and endemic Salmonella Typhi from rural Cambodia. rPinecone identified the transmission branches of the hospital outbreak and geographically-confined lineages in Cambodia. Sub-lineages identified by rPinecone in both analyses were phylogenetically robust. It is anticipated that rPinecone can be used to discriminate between lineages of bacteria from LV populations where other methods fail, enabling a deeper understanding of infectious disease epidemiology for public health purposes. Source code for rPinecone is available on GitHub under the open source licence GNU GPL 3 (url: lexwailan/rpinecone ). Newick format files for both phylogenetic trees have been deposited in Figshare (url: 0.6084/m9.figshare.7022558 ) Geographical analysis of the S . Typhi Dataset using Microreact is available at roject/r1IqkrN1X . Accession numbers, meta data and s le lineage results of both datasets used in this paper are listed in the supplementary tables. I/We confirm all supporting data, code and protocols have been provided within the article or through supplementary data files. ⊠ Whole genome sequence data from bacterial pathogens is increasingly used in the epidemiological investigation of infectious disease, both in outbreak and endemic situations. However, distinguishing bacterial species which are both very similar and which are likely to come from a small geographical and temporal range presents a major technical challenge for epidemiologists. rPinecone was designed to address this challenge and utilises phylogenetic data to define lineages within bacterial populations that have limited variation. This approach is therefore of great interest to epidemiologists as it adds a further level of clarity above and beyond that which is offered by existing approaches which have not been designed to consider bacterial isolates containing variation that only transiently exist, but which is epidemiologically informative. rPinecone has the flexibility to be applied to multiple pathogens and has direct application for investigations of clinical outbreaks and endemic disease to understand transmission dynamics or geographical hotspots of disease.
Publisher: F1000 Research Ltd
Date: 30-07-2018
DOI: 10.12688/WELLCOMEOPENRES.14694.1
Abstract: Identifying structure in collections of sequence data sets remains a common problem in genomics. hierBAPS, a popular algorithm for identifying population structure in haploid genomes, has previously only been available as a MATLAB binary. We provide an R implementation which is both easier to install and use, automating the entire pipeline. Additionally, we allow for the use of multiple processors, improve on the default settings of the algorithm, and provide an interface with the ggtree library to enable informative illustration of the clustering results. Our aim is that this package aids in the understanding and dissemination of the method, as well as enhancing the reproducibility of population structure analyses.
Publisher: eLife Sciences Publications, Ltd
Date: 19-07-2021
Publisher: Cold Spring Harbor Laboratory
Date: 24-01-2019
Abstract: 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 ( Pop ulation P artitioning U sing N ucleotide 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’ ergence 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’ erse evolutionary patterns. PopPUNK can process 10 3 –10 4 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.
Publisher: Cold Spring Harbor Laboratory
Date: 04-10-2021
DOI: 10.1101/2021.10.04.462983
Abstract: Advances in whole-genome genotyping and sequencing have allowed genome-wide analyses of association, prediction and heritability in many organisms. However, the application of such analyses to bacteria is still in its infancy, being limited by difficulties including the plasticity of bacterial genomes and their strong population structure. Here we propose, and validate using simulations, a suite of genome-wide analyses for bacteria. We combine methods from human genetics and previous bacterial studies, including linear mixed models, elastic net and LD-score regression, and introduce innovations such as frequency-based allele coding, testing for both insertion/deletion and nucleotide effects and partitioning heritability by genome region. We then analyse three phenotypes of a major human pathogen Streptococcus pneumoniae , including the first analyses of minimum inhibitory concentrations (MIC) for each of two antibiotics, penicillin and ceftriaxone. We show that these are highly heritable leading to high prediction accuracy, which is explained by many genetic associations identified under good control of population structure effects. In the case of ceftriaxone MIC, these results are surprising because none of the isolates was resistant according to the inhibition zone diameter threshold. We estimate that just over half of the heritability of penicillin MIC is explained by a known drug-resistance region, which also contributes around a quarter of the heritability of ceftriaxone MIC. For the within-host survival phenotype carriage duration, no reliable associations were found but we observed moderate heritability and prediction accuracy, indicating a polygenic trait. While generating important new results for S. pneumoniae , we have critically assessed existing methods and introduced innovations that will be useful for future large-scale population genomics studies to help decipher the genetic architecture of bacterial traits. Genome-wide association, prediction and heritability analyses in bacteria are beginning to help unravel the genetic underpinnings of traits such as antimicrobial resistance, virulence, within-host survival and transmissibility. Progress to date is limited by challenges including the effects of strong population structure and variable recombination, and the many gaps in sequence alignments including the absence of entire genes in many isolates. More work is required to critically asses and develop methods for bacterial genomics. We address this task here, using a range of existing methods from bacterial and human genetics, such as linear mixed models, elastic net and LD-score regression. Using simulations, we first validate and then adapt these methods to introduce new analyses, including separate assessment of gap and nucleotide effects, a new allele coding for association analyses and a method to partition heritability into genome regions. We analyse within-host survival and two antimicrobial response traits of Streptococcus pneumoniae , identifying many novel associations while demonstrating good control of population structure and accurate prediction. We present both new results for an important pathogen and methodological advances that will be useful in guiding future studies in bacterial population genomics.
Publisher: Cold Spring Harbor Laboratory
Date: 13-07-2022
DOI: 10.1101/2022.07.13.499881
Abstract: As observed in cancers, in idual mutagens and defects in DNA repair create distinctive mutational signatures that combine to form context-specific spectra within cells. We reasoned that similar processes must occur in bacterial lineages, potentially allowing decomposition analysis to identify disrupted DNA repair processes and niche-specific mutagen exposure. Here we reconstructed mutational spectra for 84 clades from 31 erse bacterial species, assigned signatures to specific DNA repair pathways using hypermutator lineages, and, by comparing mutational spectra of clades from different environmental and biological locations, extracted reproducible niche-associated mutational signatures. We show that mutational spectra can predict general and specific bacterial niches and therefore reveal the site of infection and types of transmission routes for established and emergent human bacterial pathogens. Variable mutagen exposure and DNA repair drive differential mutational spectra between bacteria and enable niche inference
Publisher: Cold Spring Harbor Laboratory
Date: 08-09-2023
Publisher: Public Library of Science (PLoS)
Date: 25-02-2021
DOI: 10.1371/JOURNAL.PGEN.1009269
Abstract: Malaria remains a major public health problem in many countries. Unlike influenza and HIV, where ersity in immunodominant surface antigens is understood geographically to inform disease surveillance, relatively little is known about the global population structure of PfEMP1, the major variant surface antigen of the malaria parasite Plasmodium falciparum . The complexity of the var multigene family that encodes PfEMP1 and that ersifies by recombination, has so far precluded its use in malaria surveillance. Recent studies have demonstrated that cost-effective deep sequencing of the region of var genes encoding the PfEMP1 DBLα domain and subsequent classification of within host sequences at 96% identity to define unique DBLα types, can reveal structure and strain dynamics within countries. However, to date there has not been a comprehensive comparison of these DBLα types between countries. By leveraging a bioinformatic approach (jumping hidden Markov model) designed specifically for the analysis of recombination within var genes and applying it to a dataset of DBLα types from 10 countries, we are able to describe population structure of DBLα types at the global scale. The sensitivity of the approach allows for the comparison of the global dataset to ape s les of Plasmodium Laverania species. Our analyses show that the evolution of the parasite population emerging out of Africa underlies current patterns of DBLα type ersity. Most importantly, we can distinguish geographic population structure within Africa between Gabon and Ghana in West Africa and Uganda in East Africa. Our evolutionary findings have translational implications in the context of globalization. Firstly, DBLα type ersity can provide a simple diagnostic framework for geographic surveillance of the rapidly evolving transmission dynamics of P . falciparum . It can also inform efforts to understand the presence or absence of global, regional and local population immunity to major surface antigen variants. Additionally, we identify a number of highly conserved DBLα types that are present globally that may be of biological significance and warrant further characterization.
Publisher: eLife Sciences Publications, Ltd
Date: 28-04-2021
DOI: 10.7554/ELIFE.69040
Abstract: Sequestration of Plasmodium falciparum ( P. falciparum )-infected erythrocytes to host endothelium through the parasite-derived P. falciparum erythrocyte membrane protein 1 ( Pf EMP1) adhesion proteins is central to the development of malaria pathogenesis. Pf EMP1 proteins have ersified and expanded to encompass many sequence variants, conferring each parasite a similar array of human endothelial receptor-binding phenotypes. Here, we analyzed RNA-seq profiles of parasites isolated from 32 P. falciparum- infected adult travellers returning to Germany. Patients were categorized into either malaria naive (n = 15) or pre-exposed (n = 17), and into severe (n = 8) or non-severe (n = 24) cases. For differential expression analysis, Pf EMP1-encoding var gene transcripts were de novo assembled from RNA-seq data and, in parallel, var- expressed sequence tags were analyzed and used to predict the encoded domain composition of the transcripts. Both approaches showed in concordance that severe malaria was associated with Pf EMP1 containing the endothelial protein C receptor (EPCR)-binding CIDRα1 domain, whereas CD36-binding Pf EMP1 was linked to non-severe malaria outcomes. First-time infected adults were more likely to develop severe symptoms and tended to be infected for a longer period. Thus, parasites with more pathogenic Pf EMP1 variants are more common in patients with a naive immune status, and/or adverse inflammatory host responses to first infections favor the growth of EPCR-binding parasites.
Publisher: Cold Spring Harbor Laboratory
Date: 25-04-2022
DOI: 10.1101/2022.04.23.489244
Abstract: Horizontal gene transfer (HGT) plays a critical role in the evolution and ersification of many microbial species. The resulting dynamics of gene gain and loss can have important implications for the development of antibiotic resistance and the design of vaccine and drug interventions. Methods for the analysis of gene presence/absence patterns typically do not account for errors introduced in the automated annotation and clustering of gene sequences. In particular, methods adapted from ecological studies, including the pangenome gene accumulation curve, can be misleading as they may reflect the underlying ersity in the temporal s ling of genomes rather than a difference in the dynamics of HGT. Here, we introduce Panstripe, a method based on Generalised Linear Regression that is robust to population structure, s ling bias and errors in the predicted presence/absence of genes. We demonstrate using simulations that Panstripe can effectively identify differences in the rate and number of genes involved in HGT events, and illustrate its capability by analysing several erse bacterial genome datasets representing major human pathogens. Panstripe is freely available as an R package at tonkinhill anstripe .
Publisher: Oxford University Press (OUP)
Date: 11-05-2019
DOI: 10.1093/NAR/GKZ361
Publisher: Cold Spring Harbor Laboratory
Date: 28-01-2020
DOI: 10.1101/2020.01.28.922989
Abstract: Population-level comparisons of prokaryotic genomes must take into account the substantial differences in gene content, resulting from frequent horizontal gene transfer, gene duplication and gene loss. However, the automated annotation of prokaryotic genomes is imperfect, and errors due to fragmented assemblies, contamination, erse gene families and mis-assemblies accumulate over the population, leading to profound consequences when analysing the set of all genes found in a species. Here we introduce Panaroo, a graph based pangenome clustering tool that is able to account for many of the sources of error introduced during the annotation of prokaryotic genome assemblies. We verified our approach through extensive simulations of de novo assemblies using the infinitely many genes model and by analysing a number of publicly available large bacterial genome datasets. Using a highly clonal Mycobacterium tuberculosis dataset as a negative control case, we show that failing to account for annotation errors can lead to pangenome estimates that are dominated by error. We additionally demonstrate the utility of the improved graphical output provided by Panaroo by performing a pan-genome wide association study in Neisseria gonorrhoeae and by analysing gene gain and loss rates across 51 of the major global pneumococcal sequence clusters. Panaroo is freely available under an open source MIT licence at tonkinhill anaroo .
Publisher: Cold Spring Harbor Laboratory
Date: 06-07-2018
DOI: 10.1101/360917
Abstract: The routine use of genomics for disease surveillance provides the opportunity for high-resolution bacterial epidemiology. However, current whole-genome clustering and multi-locus typing approaches do not fully exploit core and accessory genomic variation, and cannot both automatically identify, and subsequently expand, clusters of significantly-similar isolates in large datasets and across species. Here we describe PopPUNK (Population Partitioning Using Nucleotide K-mers poppunk.readthedocs.io/en/latest/ ). 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’ ergence in shared sequence and gene content, which we demonstrate to be accurate over multiple orders of magnitude using both simulated data and real datasets from ten taxonomically-widespread species. Connections between closely-related isolates of the same strain are robustly identified, despite variation in the discontinuous pairwise distance distributions that reflects species’ erse evolutionary patterns. PopPUNK can process 10 3 -10 4 genomes as single batch, with minimal memory use and runtimes up to 200-fold faster than existing methods. Clusters of strains remain consistent as new batches of genomes are added, which is achieved without needing to re-analyse all genomes de novo. This facilitates real-time surveillance with stable cluster naming and allows for outbreak detection using hundreds of genomes in minutes. Interactive visualisation and online publication is streamlined through 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.
Publisher: Public Library of Science (PLoS)
Date: 12-03-2018
Location: United Kingdom of Great Britain and Northern Ireland
Start Date: 2016
End Date: 2020
Funder: Wellcome Trust
View Funded ActivityStart Date: 2024
End Date: 12-2026
Amount: $435,431.00
Funder: Australian Research Council
View Funded Activity