DOI: 10.5061/dryad.2280gb5vj
title: Genetic anaylsis of pediatric osteoarticular infections

description: Background: Pediatric osteoarticular infections are commonly caused by
 Staphylococcus aureus. The contribution of S. aureus genomic variability
 to pathogenesis of these infections is poorly described. 
 Methods: We prospectively enrolled 47 children over 3 1/2 years from whom
 S. aureus was isolated on culture---12 uninfected with skin colonization,
 16 with skin abscesses, 19 with osteoarticular infections (four with
 septic arthritis, three with acute osteomyelitis, six with acute
 osteomyelitis and septic arthritis and six with chronic osteomyelitis).
 Isolates underwent whole genome sequencing, with assessment for 254
 virulence genes and any mutations as well as the creation of a
 phylogenetic tree. Finally, isolates were compared for their ability to
 form static biofilms and compared to the genetic analysis. Results: No
 sequence types predominated amongst osteoarticular infections. Only genes
 involved in the evasion of host immune defenses were more frequently
 carried by isolates from osteoarticular infections than from skin
 colonization (p=.02). Virulence gene mutations were only noted in 14 genes
 (three regulating biofilm formation) when comparing isolates from subjects
 with osteoarticular infections and those with skin colonization. Biofilm
 results demonstrated large heterogeneity in the isolates’ capacity to form
 static biofilms, with healthy control isolates producing more robust
 biofilm formation. Conclusions: S. aureus causing osteoarticular
 infections are genetically heterogeneous, and more frequently harbor genes
 involved in immune evasion than less invasive isolates. However, virulence
 gene carriage overall is similar with infrequent mutations, suggesting
 that pathogenesis of S. aureus osteoarticular infections may be primarily
 regulated at transcriptional and/or translational levels.
description: <strong>Construction of the Study Cohort</strong>:
 Subjects were prospectively enrolled between June
 12<sup>th</sup>, 2016, and December
 2<sup>nd</sup>, 2019. Subjects admitted to our hospital or
 Pediatric Emergency Department who were under 18 years of age and without
 known immune deficiencies or post-operative or orthopedic
 implant-associated infections were eligible for enrollment. Subjects were
 enrolled from the following four groups of osteoarticular infections: 1.)
 acute osteomyelitis (symptoms &lt;14 days, normal orthopedic plain
 films at admission and elevated inflammatory markers, as previously
 described) 2.) acute septic arthritis (any subject requiring an arthrotomy
 for suspected septic arthritis with the growth of <em>S.
 aureus</em> on a culture of blood and/or synovial fluid) 3.) chronic
 osteomyelitis (symptoms &gt;14 days at admission, abnormal orthopedic
 plain films at admission and histopathology supporting the diagnosis if
 available, with normal or mildly elevated inflammatory markers) 4.)
 concurrent acute septic arthritis and acute osteomyelitis. To better
 evaluate genomic composition across a spectrum of invasion, <em>S.
 aureus</em> isolates collected from two groups of controls were
 utilized: 1.) children with skin and soft tissue abscesses (with sterile
 blood cultures, if obtained, and no evidence of systemic invasions such as
 pneumonia or osteoarticular infections) and 2.) uninfected children with
 asymptomatic skin colonization who were admitted for non-infectious
 conditions (e.g. febrile seizures, asthma exacerbations). Demographic and
 clinical information were obtained for all subjects from the electronic
 medical record, save for healthy, uninfected controls who were promised
 anonymity. <strong>Microbiological
 Methodology</strong>: For subjects with infection, bacterial
 isolates from clinical cultures were confirmed as <em>S.
 aureus</em> via matrix-assisted laser desorption time-of-flight
 (MALDI-TOF) analysis, and then collected from sub-cultures for sequencing.
 Multiple isolates may have been collected from the same subject (e.g. if
 cultures isolated <em>S. aureus</em> from multiple time points
 during admission), though genomic comparisons unless stated otherwise were
 based on the initial isolate. For uninfected control subjects, axillary or
 nasal swabs were collected and plated on mannitol salt agar.
 Coagulase-positive isolates fermenting mannitol underwent confirmatory
 MALDI-TOF analysis and confirmed <em>S. aureus</em> isolates
 were saved for sequencing. All <em>S. aureus</em> isolates
 were frozen in 10% glycerol stock at -80 degrees until batched analysis.
 Susceptibility testing (to differentiate methicillin-resistant
 <em>S. aureus</em>, MRSA, from methicillin-susceptible
 <em>S. aureus</em>, MSSA) was performed with disk diffusion
 prior to freezing and confirmed with molecular analysis for the
 <em>mecA</em> gene. 
 <strong>Sequencing Methodology</strong>: Prior to
 sequencing, isolates were re-cultivated in tryptic soy broth, mixed in
 DNA/RNA Shield lysis tubes™ (Zymo Research™), and centrifuged at 10,000 x
 g for 1 minute. DNA was isolated using the ZymoBIOMICS DNA isolation kit
 following the manufacturer’s recommended protocol (Zymo Research™). More
 specifically, the resulting supernatant was added to a Zymospin™ filter,
 centrifuged at 8000 x g for 1 minute followed by the addition of DNA
 binding buffer. The resulting mixture was added to a Zymospin™ column,
 centrifuged at 10,000 x g for 1 minute followed by rinses with DNA wash
 buffer. This was added to DNAse/RNAse free water and centrifuged at 10,000
 x g for 1 minute. DNA was eluted from this using a Zymospin™ filter via
 centrifugation. The resulting DNA was prepared for Illumina
 next-generation sequencing using the Illumina Nextera XT DNA library prep
 kit, per recommended instructions. Completed sequencing libraries were
 assessed for quality and concentration by gel electrophoresis (Agilent™)
 and Qubit fluorometric quantitation (Thermo Fisher Scientific™),
 respectively. Completed libraries were pooled in equimolar ratios and
 underwent whole genome sequencing via 2x250 bp sequencing using v3
 sequencing reagents on an Illumina MiSeq (see supplementary table for the
 number of sequencing reads).
 <strong>Supplementary Table</strong>: Summary
 statistics for <em>S. aureus</em> genome assemblies.
 Assemblies were generated with short read data in Unicycler.
 <strong> </strong> <strong> </strong> <strong>Isolate</strong> <strong> </strong> <strong> </strong> <strong>Total Length</strong> <strong> </strong> <strong> </strong> <strong>N50</strong> <strong> </strong> <strong> </strong> <strong>Node Count </strong> <strong>Total sequencing Reads</strong> BJ01 2,901,610 bp 345,300 bp 78 2,493,902 BJ02 2,715,651 bp 324,653 bp 44 2,573,422 BJ04 2,883,664 bp 141,830 bp 93 2,681,288 BJ05 2,865,130 bp 150,065 bp 100 2,749,802 BJ08 2,796,476 bp 684,080 bp 70 3,602,990 BJ09 2,781,240 bp 842,798 bp 67 2,833,918 BJ11 2,874,312 bp 493,515 bp 67 1,580,456 BJ12 2,858,770 bp 381,724 bp 62 2,730,932 BJ14 2,838,579 bp 150,667 bp 91 3,374,678 BJ16 2,836,748 bp 150,664 bp 108 2,628,512 BJ17 2,742,652 bp 324,699 bp 49 2,993,488 BJ18 2,824,929 bp 145,010 bp 89 3,035,276 BJ20 2,859,966 bp 379,768 bp 73 2,763,582 BJ22 2,779,014 bp 511,094 bp 84 2,970,612 BJ23 2,677,006 bp 410,206 bp 65 3,289,726 BJ26 2,815,461 bp 114,527 bp 83 4,828,216 BJ27 2,716,312 bp 122,975 bp 108 3,037,438 BJ30 2,696,579 bp 127,949 bp 100 2,847,488 BJ31 2,799,975 bp 150,665 bp 76 2,986,212 HC01 2,776,425 bp 193,291 bp 69 2,125,306 HC02 2,760,837 bp 285,743 bp 58 4,037,150 HC03 2,820,835 bp 104,463 bp 103 2,796,428 HC04 2,820,879 bp 128,014 bp 102 2,702,478 HC05 2,877,095 bp 134,327 bp 116 3,598,540 HC06 2,880,941 bp 154,342 bp 74 3,488,542 HC07 2,808,650 bp 157,169 bp 68 2,603,822 HC08 2,823,380 bp 621,812 bp 53 2,887,710 HC09 2,803,283 bp 149,999 bp 87 3,237,888 HC10 2,715,641 bp 243,762 bp 88 2,884,042 HC11 2,716,677 bp 118,887 bp 79 2,543,440 HC12 3,392,452 bp 105,910 bp 125 2,331,754 SSTI01 2,871,429 bp 894,766 bp 63 2,580,842 SSTI02 2,846,042 bp 345,301 bp 67 1,969,730 SSTI03 2,831,934 bp 206,477 bp 57 2,775,570 SSTI04 2,834,658 bp 681,695 bp 72 2,803,116 SSTI05 2,845,265 bp 590,828 bp 73 3,392,124 SSTI06 2,912,114 bp 345,300 bp 80 3,087,318 SSTI07 2,803,283 bp 149,999 bp 87 3,189,308 SSTI08 2,802,181 bp 150,668 bp 85 2,726,460 SSTI09 2,808,063 bp 134,927 bp 90 3,306,610 SSTI10 2,851,911 bp 345,300 bp 83 2,358,188 SSTI11 2,711,189 bp 314,039 bp 77 4,099,420 SSTI12 2,792,046 bp 195,369 bp 75 2,994,698 SSTI13 2,780,063 bp 653,640 bp 51 3,644,138 SSTI14 2,846,853 bp 141,745 bp 102 1,860,656 SSTI15 2,825,361 bp 867,024 bp 61 3,059,198 SSTI16 2,897,283 bp 345,301 bp 80 4,805,946   <strong>Bioinformatic and Phylogenetic Methodology</strong>: For analysis of virulence genes, FASTA sequences were identified for 254 virulence genes (genes taken from a published compilation and a supplementary literature search). Sequencing data of <em>S. aureus </em>were aligned using BWA 0.7.17 using <em>S. aureus</em> reference genome NCT8325 downloaded from NCBI. Binary alignment map (BAM) files were sorted and indexed using Samtools 1.9. BCFTools 1.9 was used to count allele frequency from the BAM files. Transcriptome information of <em>S. aureus </em>was downloaded from GenBank as CP000253.1 general feature file and converted to gene transfer format (GTF) using GFF Utilities. Then FeatureCounts was used to count reads aligned to genes. Proportion tests were used to assess for a proportional difference of variants between case and control groups. Adjusted p &lt; 0.05 was considered statistically significant. For phylogenetic analysis, raw sequencing reads were trimmed with Trim Galore using default settings. Assemblies were created with Unicycler (Supplementary table). Sequence types were determined using ARIBA. Forty-seven isolates (one from each patient) were included for phylogenetic analysis. For these 47 isolates, a core genome alignment was created with Roary. A maximum likelihood phylogeny was built from the core genome alignment with IQ-TREE using 5000 ultrafast bootstraps and a GTR+G model of nucleotide substitution. Phylogenies were visualized using GGTREE. Branches were analyzed by year, source of the sequenced isolate, the presence of the mecA gene, and the type of infection. Given that the traditional classification of the types of osteoarticular infection as either septic arthritis, acute osteomyelitis, or chronic osteomyelitis may be somewhat arbitrary and not reflective of a continuum of infection (e.g. both septic arthritis and chronic osteomyelitis may arise as complications of acute osteomyelitis), a severity of illness score was calculated for subjects with acute osteomyelitis as previously described for assessment of phylogenetic relatedness and disease severity.  <strong>Static Biofilm Assay</strong>: Static biofilm assays were conducted using a modified method of Cassat et al. that we recently described. Briefly, 96-well plates were coated overnight at 4 °C with pooled human plasma (IPLANAC; Innovative Research, Novi, MI). Overnight cultures in duplicate for each strain were grown in TNB [trypticase soy broth (Becton, Dickinson and Company, Sparks, MD) with 0.5% w/v dextrose (VWR Analytical, Radnor, PA) and 3% w/v NaCl (Fisher Scientific, Waltham, MA)] at 37 °C with 220 rpm. Overnight cultures were OD<sub>600nm</sub> matched to within 0.05 and then diluted 1:200 %v/v in fresh media. Coated wells were gently washed with phosphate-buffered saline (PBS) and then inoculated with six technical replicates per biological replicate. PBS in coated wells served as a negative stain control. Plates were then incubated statically for 24 h at 37 °C. The non-adherent culture was aspirated, washed twice with PBS, and then and the wells were fixed with 100 % v/v ethanol. Ethanol was removed and the plate was allowed to dry for 10 min. Biofilm was stained with 0.1 % w/v crystal violet (Sigma-Aldrich) for 2 minutes and then aspirated and washed twice with PBS. The stain was eluted with 100 % v/v ethanol by shaking for 10min and then diluted 1:10 in 100 % v/v ethanol for OD<sub>595nm</sub> measurement. A USA300 <em>S. aureus</em> MRSA isolate (AH1263) and its isogenic <em>agr</em>-deletion mutant (AH1292) were included on each plate as internal controls and biofilm comparators. <strong>Statistical Methodology</strong>:<strong> </strong>Descriptive statistics including counts and frequencies were used to profile participant characteristics, including the type of osteoarticular infection. For categorical variables, chi-square tests were calculated using Fisher’s exact test for cell sizes less than five. For continuous variables, means, medians, and interquartile range (IQR) were assessed. In addition to analysis of the distribution of individual genes between types of infection and controls, genes were also grouped into families according to putative function (toxin, adhesins, antibiotic resistance, immune evasion, proteases, hemolysins/leukocidins/hyaluronidases) as described in the literature, and the mean proportion positive for each family was calculated. Assignment of genes to a family was based upon putative functions listed on the website www.uniprot.org, a recently published review on the topic and supplementary literature review. Differences in mean distribution between osteoarticular infections vs. healthy controls and vs. skin abscess controls were calculated using a t-test. Descriptive statistics were also employed to evaluate gene carriage in isolates from separate sources in the same patient (e.g. bone and blood cultures) and isolates from the same patient serially over time. All statistical tests were two-sided. To decrease the likelihood of false positive findings given the large number of statistical comparisons undertaken, the Benjamini and Hochberg correction was used and reported as the final p-value. The quantity of biofilm production for each included bacterial isolate was compared between skin soft tissue infections, bone and joint infections and healthy controls, and to the biofilm comparators and internal controls AH1263 and to AH1292. Biofilm quantities were evaluated on a log scale to accommodate non-normal distributions. Mixed models were estimated by accounting for repeated measures. All statistical tests used a two-side alpha value of .05. Analyses were conducted using Statistical Analysis Systems (SAS) software, v. 9.4 (Cary, N.C.).
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