Genetic anaylsis of pediatric osteoarticular infections

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.

Methods
Construction of the Study Cohort: Subjects were prospectively enrolled between June 12th, 2016, and December 2nd, 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 <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 S. aureus on a culture of blood and/or synovial fluid) 3.) chronic osteomyelitis (symptoms >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, S. aureus 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.

Microbiological Methodology: For subjects with infection, bacterial isolates from clinical cultures were confirmed as S. aureus 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 S. aureus 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 S. aureus isolates were saved for sequencing. All S. aureus isolates were frozen in 10% glycerol stock at -80 degrees until batched analysis. Susceptibility testing (to differentiate methicillin-resistant S. aureus, MRSA, from methicillin-susceptible S. aureus, MSSA) was performed with disk diffusion prior to freezing and confirmed with molecular analysis for the mecA gene. 

Sequencing Methodology: 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).

Supplementary Table: Summary statistics for S. aureus genome assemblies. Assemblies were generated with short read data in Unicycler.

Isolate

Total Length

N50

Node Count

Total sequencing Reads

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

Bioinformatic and Phylogenetic Methodology: 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 S. aureus were aligned using BWA 0.7.17 using S. aureus 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 S. aureus 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 < 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. 

Static Biofilm Assay: 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 OD600nm 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 OD595nm measurement. A USA300 S. aureus MRSA isolate (AH1263) and its isogenic agr-deletion mutant (AH1292) were included on each plate as internal controls and biofilm comparators.

Statistical Methodology: 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.).