Anna Kaarina Pöntinen

PAN-GWES: Pangenome-spanning epistasis and co-selection analysis via de Bruijn graphs

Publisher: Cold Spring Harbor Laboratory

Date: 08-09-2023

DOI: 10.1101/2023.09.07.556769

Consistent typing of plasmids with the mge-cluster pipeline

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.

Detecting co-selection through excess linkage disequilibrium in bacterial genomes

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.

Robust analysis of prokaryotic pangenome gene gain and loss rates with Panstripe

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 .

Apparent nosocomial adaptation of Enterococcus faecalis predates the modern hospital era

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.

University Hospital Of North Norway

Location: Norway

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University Of Oslo

Location: Norway

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University Of Helsinki

Location: Finland

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