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Enregistrement W6921160756 · doi:10.6084/m9.figshare.24465139

Additional file 1 of Bacterial genome-wide association study substantiates papGII of Escherichia coli as a major risk factor for urosepsis

2023· article· en· W6921160756 sur OpenAlexaff

Notice bibliographique

RevueFigshare · 2023
Typearticle
Langueen
DomaineArts and Humanities
ThématiqueLibraries and Information Services
Établissements canadiensMcGill University
Organismes subventionnairesnon disponible
Mots-clésEscherichia coliPhylogeneticsStrain (injury)Nucleic acid sequenceGenotypeWhole genome sequencingNitrofurantoinGenomeGenetic diversity

Résumé

récupéré en direct d'OpenAlex

Additional file 1: Fig. S1. Distribution of E. coli phylogroups (left) and Sequence Types (ST) (right) in male (n=251) (upper row) and female (n=574) (lower row) patients. Fig. S2. Distribution of E. coli phylogroups (left) and Sequence Types (ST) (right) in in female patients (n=574) younger than 40 years (n=52) (upper row) and older than 40 years (n=522) (lower row) patients. Fig. S3. Distribution of E. coli phylogroups (left) and Sequence Types (ST) (right) in invasive infections (n=261) (upper row) and non-invasive infections (n=574) (lower row) patients. Fig. S4. Core genome phylogeny of 825 E. coli strains. Columns represent (from left to right): the assigned phylogroup, the sequence type, phenotypic resistance against ceftriaxone, meropenem, fosfomycin, nitrofurantoin and ciprofloxacin. Fig. S5. Within host genetic diversity of E. coli strains isolated from the same clinical cases. a: core genome phylogeny of E. coli strains (n=225), isolated from the same clinical case (n=106), coloured by phylogroup. The numbers correspond to the case identifier and strains were only labelled, if they exhibited < 99.9% Average Nucleotide Identity to the strain isolated from the same clinical case. b: papG variant encoded by isolates which exhibited < 99.9% Average Nucleotide Identity to the strain isolated from the same clinical case. c: Average Nucleotide Identity of strains isolated from case 3. d: SNV of 10 picked isolates from three cases, either from urine or blood culture samples. Fig. S6. Average Nucleotide Identity values for unitigs identified in our bGWAS and mapping to papG (X-axis) and the reference sequences for the five papG variants (Y-axis). Fig. S7. a: Significance level and average effect size of genes with mapping unitigs identified as significant in a bGWAS including all clinical cases (n=751 complete observations) (right) and including cases for which the port of entry for bacteraemia could be assigned to the urinary tract (n=612 complete observations) (right). In the right figure only genes with a maximum -log10(p-value) > 11 are labelled. Genes with locus tags 100888-20_01189, 100033-19_04615 and 100033-19_04621 are labelled as papJ_2, papJ_3 and papI_2, respectively, as they were identified as such. The gene with the locus tags 100033-19_03452 are labelled as ‘hp’ (= hypothetical protein); Odds ratio estimates with 95% confidence intervals for b: Typical urinary tract infection symptoms (n = 717 complete observations with 213 events); c: Admission to the intensive care unit (n = 751 complete observations with 172 events); d: 30-day all cause mortality (n = 749 complete observations with 45 events); using the generalised linear model (GLM). e: Performance of GLM classifiers using ‘Invasive disease’ as outcome variable and the same dataset as and variables as in the GLM as input (751 complete observations with 210 events), either including the presence of papGII as a predictor or not. Error bars indicate the standard deviation and the means were compared using paired Wilcoxon tests. OR = odds ratio; CI = confidence interval; CCI = Charlson Comorbidity Index; ‘AUROC’: area under the receiver operating curve; ‘NPV’: negative predictive value; ‘PPV’: positive predictive value; ‘ns’ = not significant; ‘*’ = p-value < 0.05; ‘**’ = p-value < 0.01; ‘***’ = p-value < 0.001. Fig. S8. C-reactive protein concentration (a) and leucocyte count (b) measured in blood samples of cases, for which a papGII positive or a papGII negative E. coli strain was isolated from a urine or a blood culture samples. Leucocyte counts were measured on the day the urine / blood culture samples were taken. Fig. S9. (a) Bacterial cell count, (b), leucocyte count divided by bacterial cell count (c) nitrite status and (d) erythrocyte count divided by bacterial cell count measured in urine samples of cases, for which a papGII positive or a papGII negative E. coli strain was isolated from a urine or a blood culture samples. Fig. S10. Relative occurrence of papGII in isolates from patients younger vs. older than 40 years, in isolates from male vs. female patients and in isolates from patients which were immunosuppressed vs. patients which were not immunosuppressed. Fig. S11. Occurrence of MALDI-TOF mass peaks in spectra acquired from E. coli strains encoding no papG gene, encoding a papG variant other than papGII and encoding papGII. ‘Occurrence’ refers to the percentage of spectra per group in which a peak was detected. Each strain was measured in quadruplicate either on a Microflex Biotyper device, or an Axmina Confidence device. Masses are only depicted if detected in > 30% or < 25% of spectra for one or more of the groups. Fig. S12. Occurrence of MALDI-TOF mass peaks in spectra acquired from E. coli strains of different phylogroups. ‘Occurrence’ refers to the percentage of spectra per group in which a peak was detected. Each strain was measured in quadruplicate either on a Microflex Biotyper device, or an Axmina Confidence device. Phylogroups for which less than five strains were available (E1, E2 and G) were excluded from the plot. Masses are only depicted if detected in > 50% or < 25% of spectra for one or more of the groups. Fig. S13. Core genome phylogeny of the E. coli strains collected for this study (one strain per clinical case, n=825). Phylogroup assignment, Sequence Type (ST) (eight most frequent ones coloured, more rare STs in grey), papG variant, mass of HdeA, predicted from the amino acid sequence. Fig. S14. Results of the endpoint PCR assay (a) to test the functionality of the primers designed at centre 1. This also includes tests for the cross reactivity between papGII and papGIII primers. (b) to test the functionality of the rpoD primers designed at centre 2. Fig. S15. Evaluating the efficiency of primers and probes used in our qPCR assay (a) qPCR standard curves and values for the primer pairs gapC_2, papC_1, uidA and papGII_2 tested at centre 1. Each measurement was performed in triplicate. (b) Amplification plots for the two rpoD probes designed at centre 2. Measurements performed in quadruplicate. Fig. S16. Variants of primer and probe sequences detected in our genome collection (n=1,076). Sequences used in the qPCR assay are indicated in blue and alternative variants detected in the genomes are depicted in black. Variants were called using the variantcaller Freebayes via snippy and using a minimum coverage of 20x. Fig. S17. (a) Efficiency of the primer pairs in the single reaction (blue) and in a triplex reaction (orange) for the primers used at center 1 (gapC, papC and papGII). (b) Amplification curves of primers used at center 2: rpoD and papGII in duplex reactions and of papGII in a triplex reaction with rpoD and papC. Fig. S18. Comparison of the Ct-value yielded when processing urine pellets (n=24) using the QIAamp DNA Mini Kit and after boiling for 10 minutes. Supplementary Methods. Endpoint PCR, Quantitative PCR, Multiplexing the qPCR, Applying qPCR assay directly to urine samples, Screening of patient samples. Supplementary PCR Data: Evaluation of primer functionality.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,002
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesCharge utile insuffisante (le modèle a refusé de juger)
Catégories consensuellesCharge utile insuffisante (le modèle a refusé de juger)
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: Sans objet
GenreSignal candidat: Jeu de données · Signal consensuel: Jeu de données
Score de désaccord entre enseignants0,994
Score d'incertitude au seuil0,999

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0000,002
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,000
Communication savante0,0000,001
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,9960,001

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,042
Tête enseignante GPT0,225
Écart entre enseignants0,183 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; les deux têtes enseignantes s’accordent sur ce qui est montré ici.

Devis d'étudeSans objet
Domainenon disponible
GenreJeu de données

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2023
Routes d'admission1
Résumé présentoui

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