Bacterial genomic epidemiology with mixed samples

Mäklin, Tommi; Kallonen, Teemu; Alanko, Jarno; Samuelsen, Ørjan; Hegstad, Kristin; Mäkinen, Veli; Corander, Jukka; Heinz, Eva; Honkela, Antti

doi:10.1099/mgen.0.000691

Cited by 24 publications

(43 citation statements)

References 88 publications

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“…Lineage deconvolution was performed via the mSWEEP and mGEMS algorithms (87, 88) using a reference database consisting of a high quality subset of 20,047 genomes from the Global Pneumococcal Sequencing Project database (9). Included in this subset were 2,663 genome assemblies from the original genome sequencing study of the Maela camp that relied on single colony picks (24).…”

Section: Methodsmentioning

confidence: 99%

“…The PopPUNK algorithm was used to assign each of these genomes to their respective Global Pneumococcal Sequencing Cluster (89). The mSWEEP and mGEMS pipelines were then run using the fastq files for each deep sequencing sample with the exact commands used given in the Rmarkdown provided as part of the accompanying GitHub repository (87, 88). To reduce the possibility of false positives lineages were only called if they were present at a frequency of at least 1%.…”

Section: Methodsmentioning

confidence: 99%

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Pneumococcal within-host diversity during colonisation, transmission and treatment

Tonkin‐Hill

Ling

Chaguza

et al. 2022

Preprint

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Characterising the genetic diversity 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 diversity of Streptococcus pneumoniae within individual infants and their mothers by deep sequencing whole pneumococcal populations from longitudinal nasopharyngeal samples. 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.

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Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Pneumococcal within-host diversity during colonisation, transmission and treatment

Tonkin‐Hill

Ling

Chaguza

et al. 2022

Preprint

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“…Our study extends the previous analysis by providing lineage-level characterization and subsequent genome assembly from these samples for several important pathogen species (Supplementary Table 1) as well as a more detailed exploration of the diversity within the Klebsiella genus. In both the lineage-level characterization and the Klebsiella species analysis we applied the recent mSWEEP and mGEMS methods [15], [16] with a bespoke set of reference sequences (Methods section). The analysis pipeline is described in more detail in Supplementary Figure 1 and in the Methods section.…”

Section: Resultsmentioning

confidence: 99%

“…Here, we were able to advance this understanding thanks to the deep sequencing of neonatal stool samples in a previous landmark study [14]. Combined with novel methodology [15], [16] and high-precision genomic reference libraries, these results allowed us to identify and assemble single genomes from metagenomic sequencing data at the level of resolution for standard bacterial genomic epidemiology.…”

Section: Discussionmentioning

confidence: 99%

Strong pathogen competition in neonatal gut colonisation

Mäklin

Thorpe

Pöntinen

et al. 2022

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Bacterial pathogen species and their strains that colonise the human gut are generally understood to compete against both each other and the commensal species colonising this ecosystem. However, currently we are lacking a population-wide quantification of strain-level colonisation dynamics for many common bacterial pathogens and the relationship of colonisation potential to prevalence in disease is unknown. In addition, it is unclear how ecological factors might be modulating the dynamics. Here, using a combination of latest high-resolution metagenomics and strain-level genomic epidemiology methods leveraging large genomic reference libraries of key pathogens, we performed a quantification of the competition and colonisation dynamics for a longitudinal cohort of neonatal gut microbiomes. We found a strong inter- and intra-species competition dynamic in the gut colonisation process, but also a number of synergistic relationships among several species belonging to genus Klebsiella, which includes the prominent human pathogen Klebsiella pneumoniae. Additionally, we find no evidence of preferential colonisation by hospital-adapted pathogen lineages in either vaginal or caesarean section birth groups. Our analysis also enables the first unbiased assessment of the strain-level colonisation potential of extra-intestinal pathogenic Escherichia coli (ExPEC) in comparison with their potential to cause bloodstream infections. We determined that the established common ExPEC clones ST73 and ST95 are overall significantly more pathogenic than the more recent, globally circulating multi-drug resistant clone ST131, where only a single subclone (ST131-C2) exhibited excess pathogenic potential. Our study highlights the importance of systematic surveillance of bacterial gut pathogens, not only from disease but also from carriage state, to better inform therapies and preventive medicine in the future.

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“…We then construct the multi-string variant of the SBWT defined in Section 3.1 for each of the datasets. For all new index variants, we extract the data structure from the Wheeler BOSS index constructed using the tool Themisto [20]. This is straightforward as the Wheeler BOSS index gives access to the outgoing edge labels from each k -mer of the data in colexicographic order.…”

Section: Methodsmentioning

confidence: 99%

Succinct k-mer Sets Using Subset Rank Queries on the Spectral Burrows-Wheeler Transform ^*

Alanko

Puglisi

Vuohtoniemi

2022

Preprint

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The k-spectrum of a string is the set of all distinct substrings of length k occurring in the string. This is a lossy but computationally convenient representation of the information in the string, with many applications in high-throughput bioinformatics. In this work, we define the notion of the Spectral Burrows-Wheeler Transform (SBWT), which is a sequence of subsets of the alphabet of the string encoding the k-spectrum of the string. The SBWT is a distillation of the ideas found in the BOSS and Wheeler graph data structures. We explore multiple different approaches to index the SBWT for membership queries on the underlying k-spectrum. We identify subset rank queries as the essential subproblem, and propose four succinct index structures to solve it. One of the approaches essentially leads to the known BOSS data structure, while the other three offer attractive time-space trade-offs and support simpler query algorithms that rely only on fast rank queries. The most general approach involves a novel data structure we dub the subset wavelet tree, which we find to be of independent interest. All of the approaches are also amendable to entropy compression, which leads to good space bounds on the sizes of the data structures. Using entropy compression, we show that the SBWT can support membership queries on the k-spectrum of a single string in O(k) time and (n + k)(log σ + 1/ln 2) + o((n + k)σ) bits of space, where n is the number of distinct substrings of length k in the input and σ is the size of the alphabet. This improves from the time O(k log σ) achieved by the BOSS data structure, while maintaining the same asymptotic space complexity of O(n log σ), albeit with smaller constant factors. We show, via experiments on a range of genomic data sets, that the simplicity of our new indexes translates into large performance gains in practice over prior art.

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Bacterial genomic epidemiology with mixed samples

Cited by 24 publications

References 88 publications

Pneumococcal within-host diversity during colonisation, transmission and treatment

Pneumococcal within-host diversity during colonisation, transmission and treatment

Strong pathogen competition in neonatal gut colonisation

Succinct k-mer Sets Using Subset Rank Queries on the Spectral Burrows-Wheeler Transform ^*

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Bacterial genomic epidemiology with mixed samples

Cited by 24 publications

References 88 publications

Pneumococcal within-host diversity during colonisation, transmission and treatment

Pneumococcal within-host diversity during colonisation, transmission and treatment

Strong pathogen competition in neonatal gut colonisation

Succinct k-mer Sets Using Subset Rank Queries on the Spectral Burrows-Wheeler Transform *

Contact Info

Product

Resources

About

Succinct k-mer Sets Using Subset Rank Queries on the Spectral Burrows-Wheeler Transform ^*