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In vitro and in silico parameters for precise cgMLST typing of Listeria monocytogenes
by
Brisse, Sylvain
, Palma, Federica
, Garofolo, Giuliano
, Mangone, Iolanda
, Chiaverini, Alexandra
, Torresi, Marina
, Di Pasquale, Adriano
, Moura, Alexandra
, Radomski, Nicolas
, Janowicz, Anna
, Criscuolo, Alexis
, Cammà, Cesare
in
Alleles
/ Analysis
/ Animal Genetics and Genomics
/ Assembly
/ Bioinformatics
/ Biomedical and Life Sciences
/ cgMLST
/ Comparability of workflows
/ Completeness
/ Control
/ Datasets
/ DNA sequencing
/ Gene loci
/ Generalized linear model
/ Generalized linear models
/ Genome, Bacterial
/ Genomes
/ Genomics
/ Heterogeneity
/ Identification and classification
/ Life Sciences
/ Listeria
/ Listeria monocytogenes
/ Listeria monocytogenes - genetics
/ Methods
/ Microarrays
/ Microbial Genetics and Genomics
/ Multilocus Sequence Typing
/ Nucleotide sequence
/ Nucleotide sequencing
/ Parameter identification
/ Pathogens
/ Phylogeny
/ Plant Genetics and Genomics
/ Principal component analysis
/ Principal components analysis
/ Proteomics
/ Reproducibility
/ Statistical models
/ Whole Genome Sequencing
2022
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In vitro and in silico parameters for precise cgMLST typing of Listeria monocytogenes
by
Brisse, Sylvain
, Palma, Federica
, Garofolo, Giuliano
, Mangone, Iolanda
, Chiaverini, Alexandra
, Torresi, Marina
, Di Pasquale, Adriano
, Moura, Alexandra
, Radomski, Nicolas
, Janowicz, Anna
, Criscuolo, Alexis
, Cammà, Cesare
in
Alleles
/ Analysis
/ Animal Genetics and Genomics
/ Assembly
/ Bioinformatics
/ Biomedical and Life Sciences
/ cgMLST
/ Comparability of workflows
/ Completeness
/ Control
/ Datasets
/ DNA sequencing
/ Gene loci
/ Generalized linear model
/ Generalized linear models
/ Genome, Bacterial
/ Genomes
/ Genomics
/ Heterogeneity
/ Identification and classification
/ Life Sciences
/ Listeria
/ Listeria monocytogenes
/ Listeria monocytogenes - genetics
/ Methods
/ Microarrays
/ Microbial Genetics and Genomics
/ Multilocus Sequence Typing
/ Nucleotide sequence
/ Nucleotide sequencing
/ Parameter identification
/ Pathogens
/ Phylogeny
/ Plant Genetics and Genomics
/ Principal component analysis
/ Principal components analysis
/ Proteomics
/ Reproducibility
/ Statistical models
/ Whole Genome Sequencing
2022
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In vitro and in silico parameters for precise cgMLST typing of Listeria monocytogenes
by
Brisse, Sylvain
, Palma, Federica
, Garofolo, Giuliano
, Mangone, Iolanda
, Chiaverini, Alexandra
, Torresi, Marina
, Di Pasquale, Adriano
, Moura, Alexandra
, Radomski, Nicolas
, Janowicz, Anna
, Criscuolo, Alexis
, Cammà, Cesare
in
Alleles
/ Analysis
/ Animal Genetics and Genomics
/ Assembly
/ Bioinformatics
/ Biomedical and Life Sciences
/ cgMLST
/ Comparability of workflows
/ Completeness
/ Control
/ Datasets
/ DNA sequencing
/ Gene loci
/ Generalized linear model
/ Generalized linear models
/ Genome, Bacterial
/ Genomes
/ Genomics
/ Heterogeneity
/ Identification and classification
/ Life Sciences
/ Listeria
/ Listeria monocytogenes
/ Listeria monocytogenes - genetics
/ Methods
/ Microarrays
/ Microbial Genetics and Genomics
/ Multilocus Sequence Typing
/ Nucleotide sequence
/ Nucleotide sequencing
/ Parameter identification
/ Pathogens
/ Phylogeny
/ Plant Genetics and Genomics
/ Principal component analysis
/ Principal components analysis
/ Proteomics
/ Reproducibility
/ Statistical models
/ Whole Genome Sequencing
2022
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In vitro and in silico parameters for precise cgMLST typing of Listeria monocytogenes
Journal Article
In vitro and in silico parameters for precise cgMLST typing of Listeria monocytogenes
2022
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Overview
Background
Whole genome sequencing analyzed by core genome multi-locus sequence typing (cgMLST) is widely used in surveillance of the pathogenic bacteria
Listeria monocytogenes
. Given the heterogeneity of available bioinformatics tools to define cgMLST alleles, our aim was to identify parameters influencing the precision of cgMLST profiles.
Methods
We used three
L. monocytogenes
reference genomes from different phylogenetic lineages and assessed the impact of in vitro (i.e. tested genomes, successive platings, replicates of DNA extraction and sequencing) and in silico parameters (i.e. targeted depth of coverage, depth of coverage, breadth of coverage, assembly metrics, cgMLST workflows, cgMLST completeness) on cgMLST precision made of 1748 core loci. Six cgMLST workflows were tested, comprising assembly-based (BIGSdb, INNUENDO, GENPAT, SeqSphere and BioNumerics) and assembly-free (i.e. kmer-based MentaLiST) allele callers. Principal component analyses and generalized linear models were used to identify the most impactful parameters on cgMLST precision.
Results
The isolate’s genetic background, cgMLST workflows, cgMLST completeness, as well as depth and breadth of coverage were the parameters that impacted most on cgMLST precision (i.e. identical alleles against reference circular genomes). All workflows performed well at ≥40X of depth of coverage, with high loci detection (> 99.54% for all, except for BioNumerics with 97.78%) and showed consistent cluster definitions using the reference cut-off of ≤7 allele differences.
Conclusions
This highlights that bioinformatics workflows dedicated to cgMLST allele calling are largely robust when paired-end reads are of high quality and when the sequencing depth is ≥40X.
Publisher
BioMed Central,BioMed Central Ltd,Springer Nature B.V,BMC
Subject
/ Analysis
/ Animal Genetics and Genomics
/ Assembly
/ Biomedical and Life Sciences
/ cgMLST
/ Control
/ Datasets
/ Genomes
/ Genomics
/ Identification and classification
/ Listeria
/ Listeria monocytogenes - genetics
/ Methods
/ Microbial Genetics and Genomics
/ Principal component analysis
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