2026-10-06T17:39:46Z https://api.figshare.com/v2/oai

oai:figshare.com:article/32326584 2026-09-28T09:23:49Z category_24208 category_24184 category_24199 category_24205 category_24352 category_24355 category_24361 category_24691 category_24694 category_24508 category_27046 category_27052 category_27205 category_29869 category_29902 category_29755 item_type_3 month_year_09_2026

How much is enough? Optimising sampling frames for genomic surveillance of Escherichia coli and Klebsiella spp. bloodstream infections – a retrospective study - Supplementary data files. Dorottya Nagy (21583646) Bioinformatics and computational biology not elsewhere classified Bioinformatic methods development Sequence analysis Translational and applied bioinformatics Bacteriology Infectious agents Microbial genetics Medical bacteriology Medical infection agents (incl. prions) Infectious diseases Disease surveillance Epidemiological methods Public health not elsewhere classified Applied statistics Statistics not elsewhere classified Biological mathematics Bacterial genomes - Analysis whole genome sequencing of Enterobacteriaceae Long-read sequences sample size calculation methods Bayes Theorem Background: Optimising sampling frames for genomic surveillance of E. coli and Klebsiella may support interventions to mitigate bloodstream infections (BSIs), but approaches to estimating sample size and how these relate to bacterial population diversity at multiple genetic levels (strain/plasmid/antimicrobial resistance genes[ARGs]) are lacking.Methods: Using systematically collected, regionally-stratified, whole genome sequencing data from a 6-month genomic survey of English E. coli/Klebsiella BSI isolates (n=1,939; NEKSUS), we used Bayesian approaches to estimate the sample sizes required to capture genetic diversity at strain- (MLST, fastBAPS clusters), plasmid- and ARG-levels, using two diversity measures: ‘coverage’ (i.e. proportion of the bacterial population/plasmids/ARGs represented by features observed in the sample), and the number/proportion of unique features observed at varying surveillance sample sizes.Findings: Randomly sampling 1,400 E. coli/Klebsiella BSI isolates each achieved ≥80% coverage of bacterial lineages and ARGs (i.e. capture features constituting ≥80% of the population) at 95% certainty, but captured lower proportions of unique features (28% MLSTs, 59% fastBAPS clusters, 19% plasmid subcommunities, and 57% ARGs for E. coli; 49%, 87%, 50% and 83% for Klebsiella, respectively). Sample sizes required for 80% coverage of E. coli plasmid populations were higher than MLSTs (1,928[95% CrI:1,837–2,025] vs 1,351[1,230–1,472]), while for Klebsiella, estimates were lower for plasmids (1,115[1,052–1,181] vs 1,422[1,331–1,515] for MLSTs). Lower sample sizes adequately captured 80% coverage of fastBAPS clusters and ARGs (649[575 – 727] and 27[23–30], respectively, for E. coli; 113[84–145] and 83[72-96] for Klebsiella), due to feature-specific frequency distributions. Klebsiella BSIs were more diverse than E. coli, with sampling 10.9% vs 3.2% of total annual BSIs in England needed to reach 80% MLST coverage. Plasmid populations and Klebsiella MLSTs were region-specific, emphasising the need for regionally-representative sampling.Interpretation: Bayesian analysis facilitates estimates of context-specific genomic surveillance sample sizes. Cost-effective targets for coverage require further optimisation.Supplementary data files:<ul><li>neksus_ecoli_bsi_samples_metadata.csv - ENA accessions, assembly stats, metadata, and MLST data for E. coli blood culture isolates from NEKSUS study</li><li>neksus_kleb_bsi_samples_metadata.csv - as above but for Klebsiella spp. isolates</li><li>neksus_ecoli_bsi_amrfinder_metadata.csv - AMRFinderPlus and plasmid annotations for E. coli blood culture isolates from NEKSUS study</li><li>neksus_kleb_bsi_amrfinder_metadata.csv - as above but for Klebsiella spp. isolates.</li><li>BSAC_Supplemental_Data_S1.csv - data from the publicly available BSAC study, used for external validation</li><li>NORM_supplementary.csv - data from the publicly available NORM datasrt, used for external validation</li></ul> 2026-09-28T09:23:49Z Dataset Dataset 10.6084/m9.figshare.32326584.v2 https://figshare.com/articles/dataset/How_much_is_enough_for_genomic_surveillance_of_i_E_coli_i_and_i_Klebsiella_i_bloodstream_infection_isolates_in_England_-_Supplementary_data_files_/32326584 CC BY 4.0