Evidence map›Paper›PMID 37460975›Full record

ArticleBMC genomics2023

A high fidelity approach to assembling the complex Borrelia genome.

Sabrina Hepner, Konstantin Kuleshov, Ave Tooming-Kunderud, Nikolas Alig, Alexander Gofton, Sherwood Casjens, Robert E Rollins, Alexandra Dangel, Evangelos Mourkas, Samuel K Sheppard and 5 more

Open access · goldAbstract read
In one paragraph

Article in BMC genomics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.

0numbers the graph read from it
0cells of the map it votes in
18citing papers in PubMed
7.0field-weighted citation impact, top 2% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

18 citing papers in PubMed, 25 citations in OpenAlex.

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  18. Microorganisms · 2023
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

15 authors at 9 institutions in 7 countries.

Sabrina HepnerGerman National Reference Centre for Borrelia, Oberschleissheim, Germany. sabrina.hepner@lgl.bayern.de.
Konstantin KuleshovCentral Research Institute of Epidemiology, Moscow, Russia.
Ave Tooming-KunderudDepartment of Biosciences, Norwegian Sequencing Centre at Centre for Ecological and Evolutionary Synthesis, University of Oslo, Oslo, Norway.
Nikolas AligGerman National Reference Centre for Borrelia, Oberschleissheim, Germany.
Alexander GoftonCSIRO, Health and Biosecurity, Canberra, ATC, Australia.
Sherwood CasjensDivision of Microbiology and Immunology, Pathology Department, University of Utah School of Medicine, Salt Lake City, UT, USA.
Robert E RollinsInstitute of Avian Research "Vogelwarte Helgoland", Wilhelmshaven, Germany.
Alexandra DangelBavarian Health and Food Safety Authority, Oberschleissheim, Germany.
Evangelos MourkasDepartment of Biology, University of Oxford, Oxford, UK.
Samuel K SheppardDepartment of Biology, University of Oxford, Oxford, UK.
Andreas WieserMedical Microbiology and Hospital Epidemiology, Max von Pettenkofer Institute, Faculty of Medicine, LMU Munich, Munich, Germany.
Johannes HübnerDr. Von Hauner Children's Hospital, LMU Munich, Munich, Germany.
Andreas SingGerman National Reference Centre for Borrelia, Oberschleissheim, Germany.
Volker FingerleGerman National Reference Centre for Borrelia, Oberschleissheim, Germany.
Gabriele MargosGerman National Reference Centre for Borrelia, Oberschleissheim, Germany.
Institute of Bioinformatics and Systems Biology · DEUniversity of Oxford · GBCentral Research Institute of Epidemiology · RUCSIRO Health and Biosecurity · AUFraunhofer Institute for Translational Medicine and Pharmacology · DEInstitute of Avian Research · DELudwig-Maximilians-Universität München · DEUniversity of Oslo · NOUniversity of Utah · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundBacteria of the Borrelia burgdorferi sensu lato (s.l.) complex can cause Lyme borreliosis. Different B. burgdorferi s.l. genospecies vary in their host and vector associations and human pathogenicity but the genetic basis for these adaptations is unresolved and requires completed and reliable genomes for comparative analyses. The de novo assembly of a complete Borrelia genome is challenging due to the high levels of complexity, represented by a high number of circular and linear plasmids that are dynamic, showing mosaic structure and sequence homology. Previous work demonstrated that even advanced approaches, such as a combination of short-read and long-read data, might lead to incomplete plasmid reconstruction. Here, using recently developed high-fidelity (HiFi) PacBio sequencing, we explored strategies to obtain gap-free, complete and high quality Borrelia genome assemblies. Optimizing genome assembly, quality control and refinement steps, we critically appraised existing techniques to create a workflow that lead to improved genome reconstruction.

resultsDespite the latest available technologies, stand-alone sequencing and assembly methods are insufficient for the generation of complete and high quality Borrelia genome assemblies. We developed a workflow pipeline for the de novo genome assembly for Borrelia using several types of sequence data and incorporating multiple assemblers to recover the complete genome including both circular and linear plasmid sequences.

conclusionOur study demonstrates that, with HiFi data and an ensemble reconstruction pipeline with refinement steps, chromosomal and plasmid sequences can be fully resolved, even for complex genomes such as Borrelia. The presented pipeline may be of interest for the assembly of further complex microbial genomes.

Indexed as

BorreliaBorrelia burgdorferiBorrelia burgdorferi GroupLyme DiseaseGenome, BacterialHumansPhylogenyBorrelia burgdorferiDe novo assemblyGenome reconstruction pipelineGenomicsHiFi sequencingPlasmids

Identifiers

PMID37460975
PMCPMC10353223
OpenAlexW4384559950

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LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.