Molecular Epidemiology of Staphylococcus Epidermidis in Prosthetic Joint Infections

Molecular epidemiology of Staphylococcus epidermidis in prosthetic joint infections

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Örebro Studies in Medicine 203

EMELI MÅNSSON

Molecular epidemiology of Staphylococcus epidermidis in prosthetic joint infections

Title: Molecular epidemiology of Staphylococcus epidermidis in prosthetic joint infections Publisher: Örebro University 2019 www.oru.se/publikationer

Print: Örebro University, Repro 10/2019

ISSN 1652-4063 ISBN 978-91-7529-309-7 Abstract

Emeli Månsson (2019): Molecular epidemiology of Staphylococcus epidermidis in prosthetic joint infections. Örebro Studies in Medicine 203.

Staphylococcus epidermidis is ubiquitous in the human microbiota, but also an important pathogen in healthcare-associated infections, such as prosthetic joint infections (PJIs). In this thesis, aspects of the molecular epidemiology of S. epidermidis in PJIs were investigated with the aim of improving our understanding of the pre- and perioperative measures required to reduce the incidence of S. epidermidis PJIs. In Paper I, S. epidermidis retrieved from air sampling in the operating field during arthroplasty was characterized by multilocus sequence typing and antibiotic susceptibility testing. No isolates belonging to sequence types (STs) 2 and 215, previously associated with PJIs, were found in the air of the operating field. During air sampling, several Staphylococcus pettenkoferi isolates were identified, and as a spin-off of Paper I, the genomic relatedness of these isolates to S. pettenkoferi isolates from blood cultures was described in Paper II. In Paper III, genetic traits distinguishing S. epidermidis isolated from PJIs were determined using genome-wide association study accounting for population effects after whole-genome sequencing (WGS) of a population-based 10-year collection of S. epidermidis isolates from PJIs and of nasal isolates retrieved from patients scheduled for arthroplasty. Genes associated with antimicrobial agents used for prophylaxis in arthroplasty, i.e., beta-lactam antibiotics, aminoglycosides, and chlorhexidine, were associated with PJI origin. S. epidermidis from PJIs were dominated by the ST2a, ST2b, ST5, and ST215 lineages. In Paper IV, selective agar plates were used to investigate colonization with methicillin resistant S. epidermidis (MRSE) in patients scheduled for arthroplasty. MRSE were further characterized by WGS. A subset of patients was found to harbour PJI-associated S. epidermidis lineages in their microbiota before hospitalization, but no isolates belonging to the ST2a lineage nor any rifampicin-resistant isolates were retrieved.

Keywords: Staphylococcus epidermidis, molecular epidemiology, prosthetic joint infections, whole genome sequencing, Staphylococcus pettenkoferi

Emeli Månsson, School of Medical Sciences, Örebro University, SE-70182 Örebro, Sweden, [email protected]

Table of Contents

LIST OF ORIGINAL PAPERS ...... 9

LIST OF ABBREVIATIONS ...... 11

INTRODUCTION ...... 13 Coagulase negative staphylococci ...... 15 Staphylococcus pettenkoferi ...... 16 Introduction to genomic analyses in molecular epidemidology studies 17 Whole genome sequencing (WGS) ...... 18 Analysis of WGS data – bioinformatics ...... 20 Staphylococcal Casette Chromosome mec (SCCmec) ...... 22 Staphylococcus epidermidis – a friend and a foe ...... 22 S. epidermidis in the human microbiota ...... 23 S. epidermidis in clinical infections...... 24 Molecular epidemiology of S. epidermidis ...... 25 Molecular typing of S. epidermidis from PJIs ...... 25 Biofilm formation by S. epidermidis ...... 26 Quorum sensing - molecular crosstalk within the biofilm ...... 27 Attenuated host immune response in biofilms ...... 28 Recalcitrance towards antimicrobial treatment ...... 28 Antibiotic susceptibility testing (AST) of S. epidermidis ...... 28 WGS in AST...... 29 What discriminates clinical S. epidermidis from commensal S. epidermidis isolates? ...... 30 Biofilm formation ...... 30 Antimicrobial resistance, IS256 and sesI ...... 30 fdh and ACME - markers of commensalism? ...... 31 Hip- and knee prosthetic joint infections with S. epidermidis ...... 32 Diagnostic criteria for S. epidermidis PJI ...... 32 Classification of PJIs ...... 35 Incidence of hip and knee S. epidermidis PJIs ...... 35 Pathogenesis of S. epidermidis PJIs...... 36 Treatment of S. epidermidis PJIs ...... 38 Morbidity and mortality in PJIs ...... 41 Preventive strategies in prosthetic joint surgery in Sweden ...... 42 Summary of introduction ...... 43 AIMS ...... 44 MATERIALS AND METHODS ...... 45 Sampling of patients (Paper III-IV) ...... 45 Intraoperative air sampling (Paper I) ...... 47 Bacterial isolates (Paper I-IV) ...... 47 Paper I ...... 47 Paper II ...... 47 Paper III ...... 48 Paper IV ...... 48 Species identification (Paper I-IV) ...... 49 MALDI-TOF MS (Paper I-IV) ...... 49 rpoB gene sequencing (Paper II) ...... 49 16S rRNA gene sequencing (Paper I) ...... 50 Antimicrobial susceptibility testing (Paper I-III) ...... 50 Genotyping methods ...... 50 MLST (Paper I,III-IV) ...... 50 Rep-PCR typing (Paper II) ...... 51 WGS and analysis of WGS data (Paper II-IV) ...... 51 DNA extraction and library preparation ...... 51 Genome sequencing and quality control ...... 52 Publically available genome sequences used in this thesis (Paper II-IV) 52 Phylogenetic relationships ...... 52 Genome-wide analysis study (GWAS) (Paper III) ...... 53 Genotypic antimicrobial resistance (Paper II-IV) ...... 54 SCCmec diversity (Paper III) ...... 54 Genes associated with biofilm, virulence and commensalism (Paper III, IV, additional data) ...... 54 Digital DNA:DNA hybridization (additional data) ...... 55 Phenotypic biofilm production (study II) ...... 55 Ethical considerations ...... 56 Statistics ...... 57 RESULTS AND DISCUSSION ...... 58 Molecular epidemiology of S. epidermidis in relation to PJIs (I, III, IV) .. 58 Clonal relatedness of S. epidermidis isolated from PJIs ...... 58 Swedish PJI isolates ...... 58 International data ...... 61 Genetic diversity of S. epidermidis retrieved from the microbiota of patients scheduled for prosthetic joint surgery (Paper III, IV) ...... 65 Nasal S. epidermidis retrieved from standard culture medium ...... 65 Nasal and skin S. epidermidis retrieved from media selecting for methicillin resistance ...... 65 S. epidermidis in the air of the operating field during prosthetic joint surgery (Paper I) ...... 70 Genetic traits in S. epidermidis in relation to isolate origin (Paper III, IV) ...... 74 GWAS adjusting for lineage effect (Paper III, IV) ...... 74 Genes associated with biofilm formation (Paper III) ...... 77 IS256 and sesI (Paper III) ...... 79 ACME-arcA and fdh (Paper III) ...... 79 Genes and gene variants associated with antimicrobial resistance (Paper III, IV) ...... 80 SCCmec diversity (Paper III) ...... 81 Clinical aspects (Paper I, III-IV) ...... 83 Is there a marker able to distinguish S. epidermidis isolates with a higher capacity to cause PJI? ...... 83 Or are all S. epidermidis equally fit to cause PJIs?...... 85 Can a centres proportion of MDRSE in S. epidermidis PJIs reflect adherence to prophylaxis regimens? ...... 86 Is preoperative whole-body cleansing with chlorhexidine driving the rate of MDRSE PJIs? ...... 86 Should the current antimicrobial prophylaxis regimens in total joint arthroplasty (TJA) be adapted to cover for MDRSE?...... 88 What is the origin of S. epidermidis causing PJIs – selection from patients’ pre-hospital admission microbiota or nosocomial transmission? ...... 90 Limitations ...... 92 Paper I...... 92 Paper III ...... 92 Paper IV ...... 92 Genomic relatedness of S. pettenkoferi isolates of different origin ...... 93 Study collection ...... 93 Repetitive sequenced-based PCR typing ...... 93 Phylogenetic relationships ...... 94 Methicillin resistance and presence of mecA ...... 95 Prediction of pathogenicty ...... 97 Digital DNA:DNA hybridization ...... 98 BLAST of the rpoB sequence of the proposed species “S. pseudolugdunensis” ...... 99 Clinical aspects ...... 101 Limitations (Paper II) ...... 101 CONCLUSIONS ...... 103 FUTURE PERSPECTIVES ...... 105

POPULÄRVETENSKAPLIG SAMMANFATTNING ...... 107

ACKNOWLEDGMENTS ...... 110

REFERENCES ...... 113 List of original Papers This thesis is based on the following original Papers and manuscripts, referred to in the text by their Roman numericals:

I. Månsson E, Hellmark B, Sundqvist M, Söderquist B. Sequence types of Staphylococcus epidermidis associated with prosthetic joint infections are not present in the laminar airflow during prosthetic joint surgery. APMIS. 2015 Jul;123(7):589-95.

II. Månsson E, Hellmark B, Stegger M, Skytt Andersen P, Sundqvist M, Söderquist B. Genomic relatedness of Staphylococcus pettenkoferi isolates of different origins. J Med Microbiol. 2017 May;66(5):601-608.

III. Månsson E, Bech Johannesen T, Nilsdotter-Augustinsson Å, Söderquist B, Stegger M. Genomic traits in Staphylococcus epidermidis associated with prosthetic joint infections. (submitted)

IV. Månsson E, Tevell S, Nilsdotter-Augustinsson Å, Bech Johannesen T, Sundqvist M, Stegger M, Söderquist B. Methicillin resistant Staphylococcus epidermidis lineages in the nasal and skin microbiota of patients scheduled for arthroplasty surgery. (in manuscript)

EMELI MÅNSSON Molecular epidemiology of S. epidermidis in PJIs 9

The following Papers were written and published during the author’s PhD- studies but are not included in the thesis:

Månsson E, Sahdo B, Nilsdotter-Augustinsson Å, Särndahl E, Söderquist B. Lower activation of caspase-1 by Staphylococcus epidermidis isolated from prosthetic joint infections compared to commensals. J Bone Jt Infect. 2018 Jan 13;3(1):10–14.

Månsson E, Söderquist B, Nilsdotter-Augustinsson Å, Särndahl E, Demirel I. Staphylococcus epidermidis from prosthetic joint infections induces lower IL-1 release from human neutrophils than isolates from normal flora. APMIS. 2018 Aug;126(8):678–684. β

10 EMELI MÅNSSON Molecular epidemiology of S. epidermidis in PJIs

List of abbreviations ACME arginine catabolic mobile element AIP autoinducing peptide AMP antimicrobial peptide AMR antimicrobial resistance ANI average nucleotide identity AST antibiotic susceptibility testing BLAST basic local alignment search tool bp base pair CFU colony forming units CHG chlorhexidine gluconate COMER copper and mercury resistance mobile element CoNS coagulase-negative staphylococci EUCAST European Committee on Antimicrobial Susceptibility Testing dDDH digital DNA-DNA hybridization DDH DNA-DNA hybridization GWAS genome-wide association study HGT horizontal gene transfer IL interleukin IS insertion sequence MALDI-TOF MS matrix-assisted laser desorption/ionization time-of- flight mass spectrometry MDR multidrug-resistant MDRSE multidrug-resistant Staphylococcus epidermidis MGE mobile genetic element MIC minimum inhibitory concentration

EMELI MÅNSSON Molecular epidemiology of S. epidermidis in PJIs 11

MLAF mobile laminar air flow MLST multilocus sequence typing MRCoNS methicillin-resistant coagulase-negative staphylococci MRSA methicillin-resistant Staphylococcus aureus MRSE methicillin-resistant Staphylococcus epidermidis MSSE methicillin-sensitive Staphylococcus epidermidis ODRI orthopaedic-device–related infection ORFs open reading frames OT operating theatre PCR polymerase chain reaction PJI prosthetic joint infection PMMA polymethyl methacrylate PRISS ProtesRelaterade Infektioner Ska Stopppas PSM phenol soluble modulins SCCmec Staphylococcal Cassette Chromosome mec SNP single nucleotide polymorphism SNV single nucleotide variant ST sequence type THA total hip arthroplasty TJA total joint arthroplasty TKA total knee arthroplasty WGS whole-genome sequencing

12 EMELI MÅNSSON Molecular epidemiology of S. epidermidis in PJIs

Introduction Staphylococcus epidermidis are coagulase-negative staphylococci (CoNS) that colonize human skin and mucous membranes soon after birth (1, 2). Due to the ubiquitous presence of S. epidermidis in the human microbiota, contamination of clinical cultures is common, and it can be difficult to assess whether growth of S. epidermidis should be regarded as contamination or as a true infection. Colonization with S. epidermidis is beneficial to the host in several ways (3), but in modern medicine S. epidermidis is also a major causative microorganism in healthcare-associated infections, such as foreign body- related infections, and infections in immunocompromised patients, including preterm infants (4). In recent years, there have been alarming reports of the world-wide spread of multidrug-resistant (MDR) lineages of S. epidermidis (MDRSE) causing clinical infections (5, 6). Total joint arthroplasty (TJA) has had a tremendous beneficial effect of on the quality of life (7) of millions of people since its introduction in clinical practice in the 1960s (8). The rate of deep infection is low, about 1% (according to data from the Swedish Hip Arthroplasty Register [SHAR, www.shpr.se] and the Swedish Knee Arthroplasty Register [SKAR, www.myknee.se], but the consequences of prosthetic joint infections (PJIs) are often devastating for patients: need for repeated surgery, long-term antibiotic treatment associated with potential side-effects, and risk of reduced functional outcome compared with patients with uncomplicated arthroplasties (9, 10). Additionally, PJIs are also associated with increased mortality (11, 12). The treatment cost of a PJI is estimated at EUR 18,900 - 44,600 (data from Finland) (13), and the total amount spent by health care systems on PJI treatment is estimated to have doubled in the last decade (14). S. epidermidis is a major pathogen in PJIs (15). Molecular epidemiological studies have found that a limited number of sequence types (STs) are over-represented in clincal infections with S. epidermidis (6, 16- 19). Sparse data are available for PJIs, but a previous study using multilocus sequence typing (MLST) found S. epidermidis from PJIs (n = 61) to be distinct from S. epidermidis from normal skin flora (n = 24) and to be dominated by ST2 and ST215 (20). This thesis project started with a desire to understand the underlying explanation for the predominance of these lineages in hip and knee S. epidermidis PJIs, with the intention to, by extension, understand what pre- and perioperative measures are called for to reduce the incidence of S. epidermidis PJIs.

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This thesis is a compilation thesis comprising four Papers. In the first Paper, we investigated whether the STs of S. epidermidis associated with PJIs were found in the air of the operating field during arthroplasty surgery, speaking in favour of intraoperative air-borne transmission. As a spin-off, we described relatedness of a relatively unknown CoNS species - Staphylococcus pettenkoferi – of different origins in Paper II. Using whole- genome sequencing (WGS), high-resolution information on the phylogenetic relationships between S. epidermidis from hip and knee PJIs and isolates from nasal mucosa, as well as insights into the genetic traits that distinguish S. epidermidis that cause PJIs were gained in the third Paper. In Paper IV, we cultured samples from the nares, inguinal crease and skin over the hip/knee on media selective for methicillin resistance to investigate the colonization rate and diversity of methicillin-resistant S. epidermidis (MRSE) before hospitalization for total joint arthoplasty (TJA).

14 EMELI MÅNSSON Molecular epidemiology of S. epidermidis in PJIs

Coagulase negative staphylococci Staphylococci, from the greek words “staphyle” meaning grape and “kokkos” meaning granule, are round Gram-positive bacteria that often appear in clusters resembling grape bunches under the microscope (21). The genus Staphylococcus, as of August 2019 comprising 54 species and 26 subspecies (https://www.dsmz.de/bacterial-diversity/prokaryotic- nomenclature-up-to-date), belongs to the family Staphylococcaceae, the order Bacillales, the class Bacilli, and the phylum Firmicutes (4). Coagulase- negative staphylococci (CoNS) can be distinguished biochemically from the major human pathogen among staphylococci, Staphylococcus aureus, by testing for coagulase (Figure 1) (4).

Figure 1. Clinical and epidemiological schema of the genus Staphylococcus based on the categorisation of coagulase as a major virulence factor. Reprinted from Becker et al. (4) with permission.

Due to the need for labour intensive techniques, CoNS were rarely identified to the species levels before the introduction of matrix assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) in clinical practice (22). Today, species identification of staphylococci is however inexpensive, rapid, and accurate, largely due to this method (23), and there is a growing understanding that CoNS is a heterogenous group of species with a range of pathogenic capacities, potentially also at the strain level (4, 24).

EMELI MÅNSSON Molecular epidemiology of S. epidermidis in PJIs 15 In the past, species definition was based on morphology and biochemistry, later moving on to DNA G+C content, DNA:DNA hybridization (DDH), DNA:rRNA hybridization, and sequencing of the 16SrRNA gene as technology advanced, but today species definition is increasingly based on WGS (25). The proposed and generally accepted species boundaries are <98.7% for 16S rRNA sequence identity, <70% for digital DDH (dDDH [Genome-to-Genome Distance Calculator]) similarity, and <95–96% for average nucleotide identity (ANI) (26). For the subspecies level, a value of 79-80% dDDH similarity has been proposed as the threshold (27). The ability to cause clinical infection differs between CoNS species. Overall, S. epidermidis and Staphylococcus hemolyticus have the largest clinical impact, but there are case reports of clinical infections with all CoNS species retrieved from human skin or mucous membranes (4). Several algorithms, based on a combination of number of positive cultures and clinical data, for determining the clinical significance of CoNS in blood cultures have been proposed, with reasonable specificity (91–93%) but lower sensitivity (62%) (28, 29). The European Manual of Clinical Microbiology state that for CoNS the significance of blood cultures should be interpreted based on the number of positive bottles, the total number of blood cultures performed, and relevant clinical information. (30). The clinical significance of non-S. epidermidis CoNS was investigated in a German study of 252 patients with positive blood cultures (31). Here, S. haemolyticus (n = 28), Staphylococcus hominis (n = 13), Staphylococcus capitis (n = 12), and Staphylococcus lugdunensis (n = 3) contributed to 96.6% of all relevant infections, whereas S. pettenkoferi (n = 7), Staphylococcus saccharolyticus (n = 3), Staphylococcus caprae (n = 2), Staphylococcus auricularis (n = 1), Staphylococcus schleiferi (n = 1), and Staphylococcus simulans (n = 1) were consistently categorized as contaminants (31). The authors defined clinical significance from a combination of microbiology results and clinical data in discharge letters.

Staphylococcus pettenkoferi S. pettenkoferi was first described in 2002 (32). Based on 16SrRNA, dnaJ, rpoB, and tuf sequencing S. pettenkoferi is most closely related to Staphylococcus massiliensis and belongs to the Saprophyticus species group (33), but the biochemical profile is most similar to S. capitis and S. auricularis (34). S. pettenkoferi displays 98% 16SrRNA sequence similarity to Staphylococcus argensis (isolated from water), but the species are

16 EMELI MÅNSSON Molecular epidemiology of S. epidermidis in PJIs distinguished by phenotypical and physiological markers (35). By 2013, S. pettenkoferi had been isolated from human blood cultures (32, 34, 36-41), diabetic foot osteomyelitis (42), nasal carriage (43), and a cat cage (44).

Introduction to genomic analyses in molecular epidemiology studies Molecular epidemiology is “the use of molecular typing methods for infectious agents in the study of the distribution, dynamics, and determinants of health and disease in human populations” (45), and thus includes studies of strain-specific pathogenicity, i.e the capacity of a microbe to cause damage in a host (46), and on molecular determinants and/or genomic traits that are associated with increased virulence within a species, i.e virulence factors (47). Virulence can be defined as “the relative capacity of a microbe to cause damage in a host” (46). There are four broad types of genotyping methods that can be used in molecular epidemiology studies: fingerprint based, hybridization based, PCR based, and sequence-based (45) methods: 1. Pulse field gel electrophoresis (PFGE) and repetitive-sequence-based PCR typing (rep-PCR) are examples of fingerprint-based methods. These methods compare genome fragment patterns: in PFGE, restriction endonuclease enzymes cut DNA at specific recognition sequences, and the fragments are then separated according to size in a gel electrophoresis; in rep-PCR, pathogen-specific PCR primers binds to repetitive DNA sequences and the pattern of amplicons is analysed (48). 2. DNA microarray is an example of a hybridization method. In this method, short nucleic-acid recognition sequences (probes) complementary to target sequences are fixed to a surface upon which purified and labelled DNA can hybridize for the visualization of genetic content (48). 3. In PCR-based methods, PCR products are characterized, for example by size using agarose electrophoresis, as in multiple-locus variable number of tandem repeat analysis (48), or by the percentage of GC content, using high-resolution melting analysis (49). 4. Sequence-based genotyping methods includes single-locus sequence typing (SLST) (e.g., of the spa gene in S. aureus), MLST, and the analysis of WGS data (e.g., SNPs in the core genome [i.e., the part

EMELI MÅNSSON Molecular epidemiology of S. epidermidis in PJIs 17

om the genome that is shared between all isolates of a species within a collection] or allel profiles of predefined core genes). In S. epidermidis MLST, allelic profiles of seven housekeeping genes are first determined by sequencing 412–465 base pair (bp)-long amplicons, and STs are then assigned based on the combination of allelic profiles (50).

Whole genome sequencing (WGS) Sanger sequencing (also referred to as first-generation sequencing) was used to sequence the first complete bacterial genome, published in 1995 (51). Improvements of the original Sanger sequencing method (primarily by replacement of radiolabelling with detection based on fluorescence, and by improved detection by capillary electrophoresis) enabled commercial DNA sequencing machines that produces high-quality and relatively long sequences (500-1000 bp), but the throughput is limited (0.0003 GB) (52, 53). Next-generation sequencing (NGS), or massively parallel sequencing (also referred to as second-generation sequencing, or short read sequencing), is the prevlent technology used today. NGS technology produces a large number of short reads of random pieces of each genome and permits the sequencing of multiple genomes in each run. Third- generation sequencing (long-read sequencing) technology directly sequences single DNA molecules. Read lengths of up to 100 kbp can be obtained, but with a higher inherent error profile (54). In NGS, the different sequencing platforms use different technologies for short-read sequencing but the workflow is similar (Figure 2): 1) discrete pure bacterial colonies are obtained from bacterial cultures of clinical specimens; 2) bacterial DNA is extracted, using either a commercial kit or in- house protocol, through cell lysis, DNA precipitation, and purification (i.e., removal of salts and other impurities); 3) DNA quality control (including measurement of DNA concentration); 4) DNA fragment libraries are pre- pared by randomly cleaving the high-molecular-weight DNA into fragments, and tagging them with sequencing primers, and barcodes, to enable the sorting of reads in a later stage (52).

18 EMELI MÅNSSON Molecular epidemiology of S. epidermidis in PJIs

Figure 2. Schematic overview of whole genome sequencing (WGS) workflow. Re- printed with minor modification from Besser et al. (52) with permission.

The technique for template generation and sequencing (5) differs between platforms. The Illumina platform, used to perform WGS in this thesis, uses a flow cell coated with primers complementary to the adaptor sequences. Fragment ends bind to the primers, and are amplified by bridge amplification by PCR into clusters. Fluorescently labelled nucleotides (A, C, G, and T) are added and incorporated into the complementary strand of the amplified template. After each “round” of incorporation the fluorescence of the incorporated nucleotides is imaged and the corresponding nucleotide at each position recorded. The results can be analysed as single-end reads, or a second strand can be synthesized, resulting in paired-end reads (54). The output – raw reads – is stored in the FASTQ format containing the sequence and the associated quality scores (Phred scores) for each base call (predicted nucleotide) (55). The Illumina MiSeq instrument produces read lenghts of up to 300 bp, has a user friendly workflow, and has a maximum output of 15 GB. In comparison, the NextSeq instrument produces read lengths to up to 150 bp and is designed for much higher sample throughput (up to 120 GB, reducing the per sample cost), but requires additional automation for library preparation (52).

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Amplicon-based sequencing (i.e., targeted sequencing of a particular region of interest, such as the 16S rRNA gene) and shotgun metagenomic sequencing are examples of culture-independent applications of WGS that are useful in microbiome studies (56, 57).

Analysis of WGS data: bioinformatics Bioinformatics is “an interdisciplinary research field that applies methodologies from computer science, applied mathematics and statistics to the study of biological phenomena” (55). The first step of the bioinformatic workflow after sequencing is quality assessment; reads or nucleotides of low quality are removed (trimmed), as are the sequences inserted during library preparation, and contamination is checked for. After quality control, the sequencing depth (i.e., the number of reads covering a particular nucleotide in the genome) and coverage (i.e., the average number of reads covering any given position in the sequenced genome) is determined (55). The coverage can also be expressed as the percentage of a reference genome covered to a certain depth; for example, a 80% coverage of 10x means that 80% of the genome has been sequenced to a minimum depth of 10 reads per base call (58). To infer phylogenetic relatedness between isolates, single-nucleotide polymorphisms (SNPs) in the core genome are usually used. These can be identified from the alignment of reads to a closely related reference sequence, a process referred to as SNP calling (54). A SNP is by definition a position in the genome where the least frequent variant is present at a given frequency, usually in at least 1% of the population (59). However, the term SNP is commonly used to define a nucleotide variant at a single nucleotide position (i.e., a single-nucleotide variant, SNV) in relation to the reference, without the requisite of a given frequency (https://www.ensembl.org/info/genome/variation/prediction/classification.h tml), and in this thesis the term SNP will be used interchangeably with the term SNV. Phylogenies are estimated from SNPs by substitution models that describe the rate of change of fixed mutations among sequences (60). Horizontal gene transfer (HGT) may mask the “true phylogeny” (55), and to circumvent this, specific programs such as Gubbins (61) can be used to identify recombinations by identifiying regions with high SNP density and removing them from the SNP alignments. The approximate of phylogenetic relatedness of isolates is commonly depicted as a phylogenetic tree. In the phylogeny, isolates having a common

20 EMELI MÅNSSON Molecular epidemiology of S. epidermidis in PJIs ancesteor can be referred to as forming a clade or a lineage (Merriam- Webster Medical Dictionary, www.merriam-webster.com/medical), without any commonly used distinction between the terms, and no inherent limit on intra-clade or intra-lineage pair-wise SNP distances. Within a clade or a lineage, bacterial strains can be defined. A suggested broad definition of strain is “a group of pathogens that share an indistinguishable genome sequence by descent, but which, by the molecular technique or techniques used, are measurably distinct from other pathogens of the same species” (45), but the applied definition of strain can vary between studies, and strain is sometimes not defined at all. The demand for an indistinguishable genome sequence between isolates within a strain has been questioned as SNVs accumulate over generations, and as technical replicate sequencing errors could interfere with conclusions about strain identity (62, 63). At present, isolates separated by 0–3 SNVs (sequenced using Illumina technology) have been proposed to be regarded as “genomically indistinguishable” based on the average technical replicate error frequency plus 4.15 standard deviations (63, 64). During the course of an outbreak, the accumulation of SNVs in a bacterial strain is to be expected at a species-specific rate (63). Thus, the threshold set for pair-wise SNVs distances to define isolates as related will vary from species-to-species, and from case-to-case depending on the time frame (65). For methicillin- resistant S. aureus (MRSA), an example of a relatedness threshold is ≤15 SNPs (65), but a community transmission chain has been hypothesized to exist between isolates differing by up to 36 SNPs (66). To investigate not only the core genome but also the accessory genome, reads are assembled into draft genomes (de novo assemblies) (55). In de novo assembly, software identifies overlapping reads and merges them into longer contiguous sequences (contigs) without the use of a reference genome. The output of the assembler is in FASTA format, containing the nucleotide sequence of each contig and an identifier. The quality of the assembly can be assessed by the number of contigs (lower is generally better), the size of the assembled genome (versus to what is expected based on reference genomes), and the N50 value (higher is better). N50 is determined by ordering all contigs by size, from the largest to the smallest, and determining the combined assembly size after each additional contig. N50 is the length of the contig that results in reaching 50% of the total assembly size (55). Following assembly, gene annotation, i.e., “the process of identifying the location and biological role of genetic features present in a DNA sequence”

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(55), can be performed by softwares such as RAST or Prokka (54). Next, core genes (i.e., genes present in all genomes) and accessory genes (i.e., all other genes) can be determined in a collection of annotated genomes from the same species by softwares such as Roary (54). The core genes and the accessory genes together comprise the pan-genome of a species, which can be analysed and associated with phenotypic traits in microbial genome-wide association studies (GWAS) (54, 55). Classical MLST profiles can be assigned from draft genomes, and provided a scheme is available for the species, the discriminatory power can be enhanced by assessing allel profiles for all core genes (cgMLST) or the whole genome (wgMLST) (55).

Staphylococcal Cassette Chromosome mec (SCCmec) SCCmec is the mobile genetic element (MGE) responsible for conferring broad-spectrum beta-lactam resistance in staphylococci. SCCmec is composed of three major elements: the mec gene complex, the ccr gene complex, and the junkyard regions (J-regions, also referred to as joining regions). The mec gene complex is further composed of: the mec gene, encoding penicillin-binding protein 2a (PBP2a), which confers beta-lactam resistance, the regulatory elements mecR1 and mecI, and associated insertion sequences (ISs). The ccr gene complex is composed of cassette chromosome recombinase (ccr) genes (ccrA, ccrB, and ccrC), which encode site-specific recombinases responsible for the accurate integration and/or excision of SCCmec into/from the chromosome, and open reading frames (ORFs) of unknown functions. The J-regions are nonessential cassette components that may contain determinants of additional antimicrobial resistance (AMR) (67). SCCmec typing is based on the types of mec and ccr gene complexes, with subtyping based on polymorphism in the J-regions. Composite SCC elements are SCC elements carrying two or more ccr gene complexes (67).

Staphylococcus epidermidis: a friend and a foe S. epidermidis belong to the “Epidermidis” cluster group together with S. capitis, S. caprae and S. saccharolyticus (33). The first valid taxonomic description of the species S. epidermidis (at that time called Albococcus epidermidis) is from the beginning of the 20th century (4, 68). The median size of complete S. epidermidis genomes submitted to the National Center for Biotechnology Information (NCBI) Reference Sequence (RefSeq)

22 EMELI MÅNSSON Molecular epidemiology of S. epidermidis in PJIs database (n = 19) is 2.6 Mbp, comprising approximately 2550 genes and with a GC content of ≈32% (https://www.ncbi.nlm.nih.gov/genome/genomes/ 155#, accessed September 2019). S. epidermidis has an open pan-genome (64, 69), with approximately 20% of the genome comprising variable genes shared only by a few strains (69).

S. epidermidis in the human microbiota S. epidermidis are symbionts – commensal bacteria with beneficial effects for the host (70) – that promotes wound healing, host immunity, and defense against pathogens by interaction with keratinocytes, T lymphocytes, and other bacterial species in the microbiota (Table 1) (3).

Type of interaction Mechanism (example(s)) Reference Control of inflammation Regulation of T-lymphocyte (71) response (effector vs. suppressive) Control of infection Regulation of keratinocytes’ (71) antimicrobial peptide production (72) Production of bacteriocins Control of atopic dermatitis Reducing S. aureus colonization (73) Control of skin cancer Production of 6-HAP (74) Wound repair Inhibition of proinflammatory TLR3 (75) signalling

Table 1. Examples of S. epidermidis interactions that are beneficial to the human host (3). 6-HAP = 6-N-hydroxyaminopurin. TLR = toll-like receptor.

Interactions between S. epidermidis and the host can be strain-specific, and can vary depending on the local environment (e.g., intact or inflamed skin) (3). An exciting example of a strain-specific beneficial effect of S. epidermidis is the reported local control of skin cancer by the antimicrobial substance 6-N-hydroxyaminopurin (6-HAP) produced by some S. epidermidis strains present in the human microbiome (74). Application of 6-HAP producing strains of S. epidermidis protected mice against ultraviolet-induced skin neoplasia, presumably by competing with adenine to inhibit DNA synthesis (74). S. epidermidis colonizes the human skin and gastro-intestinal tract rapidly after birth (1, 2). The relative abundance of S. epidermidis is highest in moist areas of the skin (e.g., the nares, inguinal crease, foot, and popliteal fossa), but S. epidermidis is also found in sebaceous and dry areas (76). Shotgun metagenomic sequencing has demonstrated that several strains of

EMELI MÅNSSON Molecular epidemiology of S. epidermidis in PJIs 23

S. epidermidis are present simultaneously on a single body area, and that there is a greater difference in the relative abundance of each strain between type of area (i.e., moist vs. sebaceous) than between individuals (76). Inter- individual variation in the human skin microbiome is likely dependent on a various host factors, such as the immune system, the host genotype, host lifestyle, and chronic conditions such as diabetes, as well as on the environmental (e.g., climate and geographical location) factors (77). In healthy humans, the individual profile of S. epidermidis strains per site seems to remain stable over both the short (weeks) and long term (months) (78). This is in contrast to the changes in the strain profile of CoNS in the skin microbiota noted during hospitalization for orthopaedic surgery, with rates of methicillin-resistant CoNS (MRCoNS) retrieved from the microbiota increasing from 4–25% to 31–81% during hospitalization (79- 81). Furthermore, nearly double carriage rates of MRCoNS (46%) was found in patients undergoing revision total hip arthroplasty (THA) compared with primary THA (24%) (82). In these studies, CoNS were generally not determined to the species level, but as S. epidermidis is the major CoNS species retrieved from human skin, these findings likely reflect changes in the S. epidermidis strain profile. The carriage rates of MRCoNS among orthopaedic ward staff and orthopaedic surgeons have also been investigated. MRCoNS were retrieved from 33–50 % of orthopaedic ward staff in two Swedish studies (79, 80), as compared with a 6% nasal carriage rate of MRCoNS among orthopaedic surgeons from Northern Europe (83).

S. epidermidis in clinical infections S. epidermidis are not merely beneficial to humans but also significant pathobionts – commensal bacteria with pathogenic potential (70), and could also be referred to as colonising opportunistic patghogens (COP) – bacteria able to cause disease when they are introduced into a susceptible body site or an immunologically compromised host (84). S. epidermidis is a major pathogen in PJIs (9, 85), as well as in clinical infections associated with other medical devices such as intravascular catheters, vascular grafts, prosthetic heart valves, cardiac devices, cerebrospinal fluid shunts, and continuous ambulatory peritoneal dialysis catheters (4). S. epidermidis can also cause bacteremia/septicaemia in neonates and immunocompromised (neutropenic) patients, as well as native-valve endocarditis, predominantly in association with health-care or among people who inject drugs (4).

24 EMELI MÅNSSON Molecular epidemiology of S. epidermidis in PJIs

Molecular epidemiology of S. epidermidis The first study of the molecular epidemiology of S. epidermidis (86), indexed in MEDLINE in 1988, suggested that patients acquire multidrug- resistant S. epidermidis strains from the hospital environment when their normal flora is disrupted by antimicrobial administration or antiseptics used in preparation for surgery, and that these strains are then disseminated to hospital staff, who convey them to the operating room where the strains gain access to prosthetic devices during implantation. ST2 is the predominant ST in S. epidermidis clinical infections world- wide, reported to constitute 18–65% of isolates (16, 17, 19, 87-89). In studies including only MRSE, MDRSE, or rifampicin-resistant S. epidermidis, the proportion of ST2 is even higher at 40-100% (6, 90-92). ST5, ST22, and ST23 are other major STs in invasive S. epidermidis infections globally (6, 16-18, 93), whereas ST215, first reported in 2009 from eight Swedish hospitals (including Västerås) and one Norweigan hospital (90), as of October 2019 still has not been reported from any other country (https://pubmlst.org/bigsdb?db=pubmlst_sepidermidis_isolates). After ST2, ST215 was the second most prevalent ST found in a long-term molecular epidemiology study of blood culture isolates of S. epidermidis retrieved from a Swedish haematological ward (Örebro), being retrieved from blood cultures throughout the study period (1980–2009) (19). As of June 2019, 875 MLST profiles (STs) were recognized in the S. epidermidis pubMLST database (https://pubmlst.org/sepidermidis/).

Molecular typing of S. epidermidis from PJIs Limited molecular typing data for S. epidermidis isolated from PJIs were available when this thesis project started in 2013. In a single-centre study from Paris, France, including 101 S. epidermidis isolates from 70 patients with bone and joint infections (proportion of PJI not presented), MLST was performed on 97 isolates (94). The most prevalent STs were ST5 (20/97), ST2 (18/97), and ST23 (17/97). The remaining 42 isolates belonged to 30 different STs. Hellmark et al. (20) compared S. epidermidis isolates from PJIs from two Swedish counties with isolates representing colonization, and found a predominance of ST2 (28/61 isolates) and ST215 (19/61 isolates) in PJIs, whereas the distribution of STs among isolates from nares (n = 13) and wrists (n = 11) from healthy individuals was more diverse (20). PFGE was used to characterize S. epidermidis from hip and knee PJIs (n = 11) and intramedullary osteosynthesis device infections (n = 4) in a study from Lyon, France (95), but apart from the small number of included isolates, this study

EMELI MÅNSSON Molecular epidemiology of S. epidermidis in PJIs 25 excluded gentamicin-resistant strains (n = 9), so conclusions are difficult to draw from the pattern analysis demonstrating partial clustering of isolates from bone and joint infections.

Biofilm formation by S. epidermidis William Costerton, “the father of biofilms”, described in 1978 how bacteria adhere to surfaces in most natural environments, as well as in clinical diseases such as dental caries and pneumonia, through “glycocalyx” comprising branching sugar molecules (96). Biofilm, defined as a “community of microorganisms in a structural matrix usually adherent to an underlying substratum” (97), is formed in a complex and dynamic process involving adherence, attachment, accumulation, maturation, and detachment (Figure 3) (98).

2 3 4

Figure 3. S. epidermidis biofilm formation. Reprinted with minor modifications from Otto (98).

Adherence to the surface is achieved largely by bacterial cell surface hydrophobicity. Bacterial proteins that contribute to the hydrophobic character of the S. epidermidis cell surface, such as autolysin of S. epidermidis (AtlE) and the biofilm-associated protein (Bap)/bap-homologue protein (Bhp), are involved in this step, as is wall teichoic acid. Extracellular DNA (eDNA) released from autolysis by hydrolysis mediated by AtlE is probably also important at this early stage of biofilm formation (4). Attachment to host matrix proteins that rapidly cover foreign material after implantation is mediated by S. epidermidis surface molecules. These

26 EMELI MÅNSSON Molecular epidemiology of S. epidermidis in PJIs surface molecules includes cell-wall-anchored (CWA) proteins, including microbial surface components recognizing adhesive matrix molecules (MSCRAMMs), such as serine-aspartate repeat protein G (SdrG), serine- aspartate repeat protein F (SdrF), and serine-asparate repeat protein H (SdrH), and S. epidermidis surface (Ses) proteins; non-covalently linked surface-associated proteins, such as AtlE, S. epidermidis autolysin/adhesin (Aae), and extracellular maxtrix-binding protein (Embp); and cell wall teichoic acids (4). The molecules involved in the steps of accumulation and maturation, may differ between strains of S. epidermidis. An important adhesin that encloses and connects S. epidermidis cells in biofilms is the polysaccharide intercellular adhesin (PIA), or poly-N-acetyl-glucosamine (PNAG), synthezied by the icaADBC genes (99). In S. epidermidis lacking the ica operon, adhesion may be accomplished by the accumulation associated protein (Aap), Bhp, or Embp (99). Ses proteins (SesC and SesE) have also been associated with PIA-independent biofilm formation (100, 101). The morphological properties of PIA-dependent biofilms may differ significantly from biofilms dependent on, for example Aap or Embp, which could explain why ica-positive S. epidermidis isolates are more prevalent in catheter-related infections (with high mechanical stress) than in PJIs (characterized by a static condition at the implant-tissue interface) (101). The final step is detachment or the release of bacterial cells from the biofilm. This is controlled by the quorum-sensing system accessory gene regulator (agr) (98), possibly by regulating S. epidermidis phenol-soluble modulins (PSMs) (99).

Quorum sensing - molecular crosstalk within the biofilm S. epidermidis in biofilms “communicate” by secreting an autoinducing peptide (AIP) (whose precursor is coded for by the agrD gene, whearas modification/cleavage/export is coded for by the agrB gene) that enables the community to regulate cell transcription based on cell density (102). When extracellular levels of AIP reach a threshold concentration (due to increased cell density), AIP binds to a membrane sensor protein (coded for by agrC). This initiates a series of intracellular events (involving agrA) that results in the expression of regulatory RNA (RNAII and RNAIII), which in turn regulates the translation of adhesions (inhibition) and exoenzymes/toxins (derepression). Sequence variants of agrB, agrC and agrD lead to AIPs with varied signalling specificities that allow AIP to inhibit agr activity in strains belonging to other agr specificity groups and/or other staphylococcal species

EMELI MÅNSSON Molecular epidemiology of S. epidermidis in PJIs 27

(102). S. epidermidis are classified as agr type I-III based on the sequence of the agrD gene (103).

Attenuated host immune response in biofilms Host immune response against S. epidermidis in biofilms is attenuated due to functionally impaired granulocytes and evasion of phagocytosis (104). Lower levels of pro-inflammatory cytokines and elevated levels of anti- inflammatory cytokines have been reported from biofilm-grown S. epidermidis compared with planktonic cells (105). However, the precise mechanisms of how S. epidermidis biofilms attenuate polymorphonuclear cell and macrophage killing, and whether this ability of S. epidermidis differ between different lineages of S. epidermidis, remains to be clarified (106).

Recalcitrance towards antimicrobial treatment Bacteria within biofilms are difficult to eradicate with antibiotic treatment. There are multiple reasons for this: restricted antibiotic penetration, altered microelement leading to the reduced efficacy of e.g. beta-lactams or aminoglycosides, altered expression of genes coding for, for example, efflux pumps, and the presence of persister cells (i.e., genetically susceptible growth arrested bacteria that survive treatment with antibiotics (107)) (108). Furthermore, biofilms facilitate the horizontal gene transfer of genes encoding AMR, and the selection of resistant mutants due to subinhibitory concentrations of antibiotics. Last, hypermutability within biofilms also contributes to antibiotic tolerance (108).

Antibiotic susceptibility testing (AST) of S. epidermidis The Swedish national recommended antibiotic panel for the susceptibility testing of staphylococci (including S. epidermidis) from PJIs, issued by Ref- erensgruppen för antibiotikafrågor (RAF) (https://www.sls.se/RAF/Re- sistensbestamning/Minimiurval-for-resistensbesked/, accessed September 2019) lists aminoglycoside, isoxazolyl penicillin, clindamycin, fusidic aid, ciprofloxacin, and rifampicin. In the extended AST of clinically relevant CoNS linezolid, rifampicin, teicoplanin, trimethoprim/sulfamethoxazole, and vancomycin are suggested. AST is generally performed using the European Committee on Antimi- crobial Susceptibility Testing (EUCAST) disk diffusion test methodology (109), with the exception of teicoplanin and vancomycin testing, performed using gradient minimum inhibitory concentration (MIC) strip tests or, preferably, by broth microdilution. Briefly, disk diffusion testing is performed

28 EMELI MÅNSSON Molecular epidemiology of S. epidermidis in PJIs by preparing an inoculum suspension of a specified turbidity (equivalent to 0.5 McFarland, measured by a photometric device) by suspending well-isolated colonies from overnight growth on non-selective medium in saline. The suspension is inoculated evenly on Mueller–Hinton (MH) agar plates, after which antibiotic disks are applied and the plates subsequently incubated at 35±1°C in air over night. After incubation, a confluent lawn of growth, evenly distributed over the agar, should be verified. The inhibitory zones are measured to the nearest millimetre with a ruler or calliper. Zone diameters are interpreted as susceptibility categories according to the current EUCAST Breakpoint Table. MDR isolates are in literal terms resistant to more than one drug, but the definition most frequently used for Gram-positive bacteria is “resistant to three or more antimicrobial classes” (110). However, there has not been consensus on the types, classes, or groups of antimicrobial agents to be used when defining MDR. A expert group proposal initiated jointly by the Euro- pean Centre for Disease Prevention and Control (ECDC) and the Centers for Disease Control and Prevention (CDC) has suggested that an MDR S. aureus is an isolate that is i) an MRSA and/or ii) non-susceptible to at least one agent in ≥3 antimicrobial categories out of 17 listed therapeutically relevant groups (110), but there is no suggested definition for MDR S. epidermidis.

WGS in AST For most bacteria, the evidence for using WGS to predict antimicrobial resistance in clinical microbiology is currently either poor or non-existent (111). For S. aureus, however, the use of WGS to infer AST has been found to be effective for most clinically relevant agents, with sensitivity of 0.97– 0.99, and specificity of 0.99–0.996 reported for genotypic predictions in the largest studies, but several problems have been identified: genetic instability with loss of the plasmid carrying ermC (encoding erythromycin resistance) and of the SCCmec element from the chromosome during passage; knowledge gaps regarding the genetic basis of resistance (e.g. vancomycin); and laboratory variation in phenotypic testing. Standardization of quality- control metrics, bioinformatic tools, and the establishment of a single database of all known resistance genes and gene variants have been called for (111). No data for S. epidermidis are reported in the review article cited above.

EMELI MÅNSSON Molecular epidemiology of S. epidermidis in PJIs 29

What distinguishes clinical S. epidermidis from commensal S. epidermidis isolates?

Biofilm formation Increased capacity to form biofilm, and the presence of the icaA gene has been associated with S. epidermidis isolates of clinical origin (112). However, contradictory results have been found; icaA was unable to discriminate commensal strains from invasive strains in patients undergoing stem cell transplantation (113), and no statistically significant difference was found between isolates from PJIs and colonizing isolates in terms of prevalence of icaADB genes, nor phenotypic biofilm formation (20). Biofilm formation on foreign material is a key factor in establishing infection and evading host immune response (114), but is also important for survival in the skin microbiota, especially on moist skin (69), and it is likely that factors (i.e., genes and proteins) that facilitate the establishment of S. epidermidis infection and persistence are also important for colonization (99).

Antimicrobial resistance, IS256 and sesI Clinical S. epidermidis isolates are often methicillin resistant (≈70-90%) and MDR, compared to colonising S. epidermidis retrieved from sampling of healthy individuals, from whom the reported rate of methicillin-resistance is 3-7% (20, 87, 113, 115). However, 24/25 of colonising S. epidermidis retrieved from sampling of patients undergoing stem cell transplantation were found to be mecA-positive, but still clonally unrelated, and mecA thus not able to discriminate invasive from colonising strains within this patient population (113). The IS element IS256 has more frequently been identified in clinical rather than colonizing S. epidermidis strains (115-117). IS256 was first described as part of the transposon Tn4001, which confers resistance towards aminoglycosides, but IS256 can be found in multiple copies in staphylococcal genomes (118). IS256 can modify expression of genes encoding antimicrobial resistance through the insertion into regulators, or by formation of hybrid promoters, and can also modulate biofilm formation by transposition into the ica genes (112). In addition, IS256 contributes to genome flexibility by serving as a cross-over point for homologous recombination events (118).

30 EMELI MÅNSSON Molecular epidemiology of S. epidermidis in PJIs

The cell-wall-associated surface protein SesI has been suggested as a marker of invasive S. epidermidis isolates, and found to be rare among colonising isolates retrieved from healthy individuals (119, 120), but the prevalence of SesI in colonising isolates retrieved from hospitalised patients is not known. fdh and ACME: markers of commensalism? In a comparative genomic study, ten genes were found to differentiate S. epidermidis isolates of commensal origin from a phylogenetically distinct group of S. epidermidis isolates of mixed origin (69). The only gene of known function – the formate dehydrogenase (fdh) gene (present in 16/71 commensal strains) – was suggested as a marker of commensalism, and reported to have higher discriminative capacity than IS256 (69). The arginine catabolic mobile element (ACME) function in S. epidermidis remains to be clarified, but in MRSA USA300 (where it was first described), allotype I, harbouring arcA (encoding an arginine deaminase pathway), and opp3 (encoding an oligopeptide permease ABC transporter), have been linked to increased fitness and colonization capability (121). Colonising S. epidermidis isolates reportedly harbour ACME to a greater extent than do isolates from clinical infections (122, 123).

To summarize, present data suggest an association between antimicrobial resistance and IS256 and clinical infections with S. epidermidis, whereas divergent results concerning the association between biofilm formation and clinical infections have been reported. There is a possible relationship between fdh and ACME and colonising isolates of S. epidermidis. However, S. epidermidis has been argued to be “an accidental pathogen” causing infections not because of specific virulence traits, but because of frequent introductions into susceptible hosts due to its ubiquitous presence on human skin and mucous membranes, and its ability to adhere and avoid host immune defence (98).

EMELI MÅNSSON Molecular epidemiology of S. epidermidis in PJIs 31

Hip- and knee prosthetic joint infections with S. epidermidis Professor Themistocles Glück, surgical chief physician at the Emperor and Empress Friedrich Paediatric Hospital in Berlin, implanted the first hinged knee joint in 1890, followed by hip, wrist and elbow arthroplasties all made from ivory. However, he was later forced by his chief to publish a repentant declaration where he concluding that replacing joints affected by active tuberculosis was erroneous because the infection recurred (124). The first prosthetic total hip (i.e., replacement of both the head of the femur and the acetabulum) was developed in the late 1930s, but the major step forward was the introduction of cemented low-friction arthroplasty by UK orthopaedic surgeon Sir John Charnley in the late 1950s (125). The prosthesis’ design, component materials, fixation methods, and surgical techniques have developed over the years, and total joint replacement is today restoring quality of life for millions of patients suffering from arthritis world-wide (126, 127). The number of patients affected by hip- and knee PJIs is projected to increase in coming decades because of the increased number of hip and knee replacements performed (128-131). In Sweden, ≈15,000 primary knee joint replacements and ≈18,000 primary hip joint replacements are performed annually (data from SKAR and SHAR).

Diagnostic criteria for S. epidermidis PJI The Swedish Society of Infectious Diseases (SILF) 2018 guidelines on the management of joint- and skeletal infections (132) have adopted the Infectious Disease Society of America criteria for defining PJI (133), with modifications according to Zimmerli (134) (Table 2).

32 EMELI MÅNSSON Molecular epidemiology of S. epidermidis in PJIs

SILF PJI criteria (one of five is required for diagnosis) • A sinus tract communicating with the prosthesis • Purulence surrounding the prosthesis, without another known etiology • Two or more intraoperative cultures (or a combination of preoperative as- piration and intraoperative cultures) that yield the same microorganism (indistinguishable by clinical routine laboratory methods, including species identification and common antibiogram). • Histopathological evidence of acute inflammation in periprosthetic tissue • Elevated leukocyte count in the synovial fluid and/or predominance of neutrophils

Table 2. SILF criteria for the diagnosis of PJI

To improve culture results, antimicrobial treatment should preferable be withheld ≥2 weeks before sampling, and five tissue samples should be obtained from different aspects of the periprosthetic tissue in the operating field (with a new set of sterile instruments for each sample), and placed in separate sterile containers (or directly in broth) (132). A 2018 survey of 19/25 clinical microbiology departments in Sweden revealed great diversity in the of use of transportation media, culture media, whether AST is performed on all samples or only one, and how the results are presented to the referring physician (personal communication, Martin Sundqvist). Soni- cation of the removed prosthetic device (i.e., application of ultrasound waves to release bacteria imbedded in biofilm) was performed by four laboratories. This reportedly increases the culture positivity (135), but experiences differ, and in a retrospective review from a centre specializing in bone and joint infections, sonication did not improve sensitivity, but was associated with lower specificity than was tissue culture (136). The present study also found similar sensitivities between culture and sonication within the subgroup of low-virulent microorganisms such as CoNS, and in the subgroups of patients undergoing surgery while on antibiotics, or under recent antibiotic exposure (136). S. epidermidis is a ubiquitous skin commensal and the possibility of contamination (either intraoperatively or at the microbiology laboratory) must be considered. According to Swedish guidelines, a single positive intraoperative culture of S. epidermidis should be interpreted as a probable contamination, but with consideration of the clinical context (132). The significance of a single positive intraoperative culture was investigated in a registry-based retrospective study of 2305 revisions of presumed aseptic loosening (137). In revisions with a single positive culture (likely to have been

EMELI MÅNSSON Molecular epidemiology of S. epidermidis in PJIs 33 dismissed as probable contamination), the relative risk (RR) of subsequent overall revision surgery within a year was 1.7 (95% confidence interval [C.I] 1.1-2.8), and the RR of revision due to PJI 2.6 (95% C.I 1.6-2.0), compared with culture-negative cases, whereas no increased risk of revision was noted for surgeries with ≥2 positive intraoperative cultures. Out of the 100 revisions of presumed aseptic revision with a single positive culture, CoNS was retrieved from 71, and out of the 43 revisions that were re-revised within a year due to PJI, all grew CoNS. No data on the correlation of CoNS species nor antibiogram between the initial revision and the re-revisions was presented in the study, but the authors concluded that some cases of unex- pected growth in a single culture is likely to represent true infection (137). The 2013 International Consensus Meeting (ICM) criteria for PJI was established by the joint meeting of the Musculoskeletal Infection Society (MSIS, US) and the European Bone and Joint Infection Society (EBJIS) in 2013 and differ somewhat from the modified IDSA criteria endorsed by SILF. According to these criteria, a single positive culture is a minor criterion. A PJI is defined either by fulfilling one major criterion (i.e., two positive periprosthetic cultures with phenotypically identical organisms or a sinus tract communicating with the joint) or three minor criteria (138). The specificity of the ICM criteria is reportedly excellent (99.5%), but the sensitivity is somewhat lower (86.9%) (139). To address this, and to ease preoperative diagnosis of infection, a scoring system for the minor criteria, which also includes the synovial marker alpha-defensin and serum d-dimer, has recently been developed and validated (139), and the revised 2018 ICM criteria for hip- and knee PJIs were endorsed in July 2018 (140) (Table 3) by the 2018 ICM on Musculoskeletal Infection.

34 EMELI MÅNSSON Molecular epidemiology of S. epidermidis in PJIs

The 2018 ICM criteria for PJI diagnosis Major criteria • two positive growths of the same organism using standard culture methods • sinus tract communicating with the joint or visualization of the prosthesis Minor criteria • elevated CRP or D-dimer (2p) • elevated ESR (1p) • elevated synovial WBC or leukocyte esterase or positive alpha-defensin (3p) • elevated synovial PMN (%) (2p) • a single positive culture (2p) • positive histology (3p) • positive intraoperative purulence (3p) Table 3. The 2018 International Consensus Meeting (ICM) criteria for hip- and knee PJIs. For minor criteria, a combined preoperative and postoperative score of ≥6 points is interpreted as PJI, 3–5 points as inconclusive, and <3 points as no PJI. ESR = erythrocyte sedimentation rate. WBC = white blood cell count. PMN = poly- morphnuclear leukocytes.

Classification of PJIs PJIs are classified as (134): • acute haematogenous PJIs (duration of symptoms less than 3 weeks in a previously uncomplicated prosthetic joint) • early postoperative PJIs (manifest infection within 1 month ofarthroplasty surgery), and • chronic PJIs (duration of symptoms for more than 3 weeks debuting >1 month after arthroplasty surgery)

Incidence of hip and knee S. epidermidis PJIs The reported two-year cumulative incidence of reoperation/revision surgery due to PJI (all species) in Sweden during the years 2014–2017 and 2006– 2015 are 1.2% for THA and 0.7% (with osteoarthritis as primary indication) for total knee arthroplasty (TKA), respectively (data from SKAR and SHAR). However, the true rate of PJIs is higher, as not all patients with a clinical diagnosis of PJI are deemed fit for revision surgery, and hence are treated conservatively with suppressive antibiotic treatment. This was illustrated by a Swedish study combining data from the SHAR and the

EMELI MÅNSSON Molecular epidemiology of S. epidermidis in PJIs 35

Swedish Prescribed Drug Register that included primary THA performed from July 2005 to December 2008 and defined PJI according to modified MSIS criteria (141). Out of 443 patients identified with PJIs, 38 patients (8.5%) were not reoperated. The two-year cumulative incidence of PJI was found to be 0.9% (95% C.I 0.85–1.02), and thus higher than the SHAR reported two-year cumulative incidence of reoperation due to PJI 2005– 2008 of 0.7%. Furthermore, a study from Denmark found that only two thirds of all revisions due to PJIs were captured by the Danish Hip Arthroplasty Registry (DHR), and of those reported as PJIs, more than 1/5 were misclassified as infections (142). In this Danish study, data on >37,000 primary THAs were matched with data from the microbiology databases, the national prescription database, the clinical biochemistry databases, and data from the National Register of Patients. When DHR data were combined with data from the microbiology databases, 9/10 of PJIs were identified, and the specificity increased to 100% (the microbiology criterion in the study was three or more intraoperative samples yielding the same microorganism). The cumulative incidence of revision surgery due to PJI has increased in recent years, as outlined above. This is believed to be partly due to a change in surgical strategy due to increased awareness of the importance of debridement and of replacing prosthetic components when treating PJIs (141). Incidence data on S. epidermidis hip- and knee PJIs are lacking as species determination of CoNS was uncommon until recently. Together with S. aureus, CoNS are the most frequently identified microorganisms in PJIs, reported in 25–29% of infections (9, 85, 141, 143, 144). This percentage is even higher (55%) in infections presenting more than a year after primary surgery (i.e., late chronic infections) (85). In studies identifying CoNS to the species level, S. epidermis reportedly represents 61-85% of all CoNS isolates (15, 145). Taken together, this means that the two-year cumulative incidence of revision surgery for S. epidermidis PJIs could be roughly estimated to be in the range of 0.18–0.30% in THA and 0.11–0.17% in TKA, and the number of patients undergoing revision surgery/reoperation due to a hip- or knee S. epidermidis PJI after THA and TKA in Sweden thus to be between 50 to 90, annually.

Pathogenesis of S. epidermidis PJIs Bacteria can be introduced to the prosthetic joint: i) directly to the prosthetic joint during surgery; ii) in the immediate postoperative period via the

36 EMELI MÅNSSON Molecular epidemiology of S. epidermidis in PJIs wound before the superficial and deep facial planes have healed; or iii) by haemotogenous seeding. (9). Haematogenous seeding is probably the route of infection in a very small proportion of all S. epidermidis PJIs (85), but the relative importance of the other two possible routes is unknown. Prolonged wound leakage may be both a symptom and a risk factor of PJI, and in an ongoing Dutch study the optimal way to handle patients exhibiting prolonged wound leakage is investigated by randomisation to either early debridement, antibiotics, and implant retention (DAIR) (at day 9–10 after index surgery) or non-surgical treatment (146). The origin of S. epidermidis causing PJIs is likely the patients’ perioperative microbiota; ≈70–95% of all surgical site infections has been estimated to arise from the patients’ nasal and skin microbiota (147). Once S. epidermidis has gained access to the prosthetic joint, the ability to attach, adhere, and form biofilm on the implant is a key factor for the successful establishment of an infection (148, 149). Bacteria in PJIs can be found both as planktonic (i.e., single cell) bacteria in the joint fluid, embedded in biofilm both on the implant and in the periprosthetic tissue, and in host cells (Figure 4) (97). Recently S. epidermidis was shown to persist in phagolysosomes in fibroblasts and osteoblasts in vitro, and viable bacteria to be released upon cell death (150). Formation of small colony variants (SCV) were promoted in intracellular persistence, and the authors speculated that this could be important for the suppression of proinflammatory cytokine response.

EMELI MÅNSSON Molecular epidemiology of S. epidermidis in PJIs 37

Figure 4. Biofilm formation in a prosthetic knee joint. Bacteria in biofilm can be found on the implant and in the periprosthetic tissue. Bacteria may also reside inside host cells (150) and in planktonic form in the joint fluid. Reprinted from McCo- noughey et al. (97) with permission.

Treatment of S. epidermidis PJIs Revision surgery, with meticulous debridement of infected tissue and exchange of parts of or the entire prosthesis, is crucial in treatment of all PJIs, including S. epidermidis PJIs. Antibiotic treatment without surgery will not achieve cure and is regarded as suppressive treatment, usually continued lifelong (10). The SILF guidelines on the management of joint- and skeletal infections management were recently updated and the recommendations for treatment of PJIs will be summarized below (132). In hip and knee PJIs manifesting within 4 weeks of primary surgery, or with a maximum of three weeks of symptoms (acute haematogenous), DAIR is the recommended procedure, provided that the prosthetic joint is

38 EMELI MÅNSSON Molecular epidemiology of S. epidermidis in PJIs stable (Figure 5). During this procedure, modular components (i.e., the fem- oral head and polyethylene liner) are exchanged, but the bone–prosthesis interface is left intact. Treatment outcomes in terms of infection cure are similar for DAIR and two-staged revision, but the functional outcome may be better for DAIR (151). In chronic PJIs, a one- or two-stage procedure with exchange of the implant is recommended (Figure 5). One-stage revision surgery is potentially associated with decreased surgical morbidity and mortality, earlier functional return, lower costs, and increased health-related quality-adjusted life years compared with the two-stage protocol, but randomized, adequately powered multicentre studies are currently lacking (152). Two-stage exchange is preferred to one-stage exchange in cases of difficult-to-treat microorganisms: rifampicin resistant staphylococci, enterococci, quinolone-resistant gram-negatives, and fungi). A cement spacer with antibiotic(s) effective against the causative microorganism is introduced at the first stage of a two-stage procedure with the aim of achieving high local concentrations of antibiotics (153).

EMELI MÅNSSON Molecular epidemiology of S. epidermidis in PJIs 39

Acute infection (≤3 wks of symptoms)? Yes Debridement, Antibiotics, Implant stable? and Implant Retention Good quality soft tissue? (DAIR) No DTT microorganism?

No 2 wks iv 10 wks rifampicin based combination therapy

One-stage exchange revision surgery (not for DTT microorganisms)

2 wks iv 10 wks po rifampicin based combination therapy

Two-stage exchange revision surgery

Two-stage with short interval (not for DTT microorganisms)

2-3 wks iv 10 wks po rifampicin based combination therapy

Two-stage with long interval (including DTT microorganisms)

6 wks iv/po antibiotics (no rif)) 2 wks no ab +/- ab

antibiotic impregnated spacer

Figure 5. Treatment algorithms for revision surgery in PJIs. Modified from (132). DTT= difficult to treat; i.e rifampicin resistant staphylococci, enterococci, quinolone resistant gram-negatives, and fungi. → = prosthesis retention, ↑ = prosthesis removal, and ↓ = prosthesis implanted. wks = weeks (duration of treatment).

Intravenous antimicrobial treatment is started at the time of revision surgery based on AST (e.g., cloxacillin for methicillin-sensitive S. epidermidis [MSSE] and vancomycin or daptomycin for MRSE). Intravenous treatment is continued for 1–2 weeks until the wound is dry, and then followed by oral treatment with rifampicin, preferably in combination with ciprofloxacin or levofloxacin (or according to AST result if fluoroquinolone resistant)

40 EMELI MÅNSSON Molecular epidemiology of S. epidermidis in PJIs for a total treatment period of three months in all patients undergoing revision surgery, except for two-staged exchange with a long interval, in which standard osteomyelitis treatment without rifampicin is preferred (Figure 5). Side-effects of rifampicin includes anorexia, nausea, and vomiting, and patients must be monitored for liver toxicity and bone marrow suppression (154). A recent systematic review found that shorter treatment (8 weeks after DAIR for hip PJI and 75 days for knee PJIs) is not associated with increased risk of treatment failure, and that shorter treatment (less than 4– 6 weeks) also appear safe for staged exchange arthroplasty (155). In multivariate analysis, increasing age was associated with greater advantage of short-course antibiotics (155).

Morbidity and mortality in PJI PJI is associated with substantial morbidity and mortality. Patients treated for PJI have an overall lower health-related quality of life, and report more pain, more stiffness and poorer function scores, as well as poorer mental health, than do patients with uncomplicated arthroplasties (156). One out of eight patients treated for PJI rated their health status as equivalent to, or worse than, death (156). PJI patients express an absence of, and need for, psychological support during the process of diagnosis, treatment and protracted recovery (157). The profoundly negative impact of PJIs on patients’ quality of life is well recognized by the treating orthopaedic surgeons, as determined by a qualitative study of how PJIs affect orthopaedic surgeons professionally and personally (158). “The worst thing to happen … beyond dying” and “a catastrophe, absolute disaster” are two representative quotations from participating surgeons, and feelings of some level of personal responsibility were found to be common, especially when the source of the infection was unknown, despite the understanding that risk and complications are inherent in surgery. Support from colleagues in multidisciplinary teams with regular, open discussions of complications and treatment choices were found to be important. The authors suggested that orthopaedic surgeons who treat patients with PJIs are at an increased risk of burnout, and that the uncertainty about the cause of PJIs may significantly contribute to the negative stress. A five-fold increased risk of death (multivariate adjusted odds ratio 5.9 [95% C.I 3.5–10.2]) one year after revision surgery was found for patients treated for PJI compared with patients undergoing revision surgery for aseptic failure in a single-centre study from the USA (11). Five years after

EMELI MÅNSSON Molecular epidemiology of S. epidermidis in PJIs 41 revision surgery for PJI, 25% of patients were deceased. In a population- based cohort study from Denmark, including all patients reported to the Danish Hip Arthroplasty Registry for 10 years, linking data to the microbiology databases, the National Register of Patients, and the Civil Registration System, the relative mortality risk, adjusted for age, sex, and comorbidity, for patients undergoing revision for PJI compared with patients with uncomplicated primary THA was 2.18 (95% C.I 1.54–3.08) (12). Mortality risk was not statistically significicantly different between S. aureus (RR 1.0) and CoNS PJIs (RR 1.08 [95% C.I 0.42–2.73]).

Preventive strategies in arthroplasty surgery in Sweden ProtesRelaterade Infektioner Ska Stoppas (PRISS) (in English, “Prosthetic related infections shall be stopped”) was a joint project between Landstingens Ömsesidiga Försäkringsbolag (LÖF) (a Swedish insurance company that insures publicly financed health care providers), and the Swedish associations of orthopaedic surgeons, orthopaedic nurses, perioperative nurses, physiotherapists, infectious diseases physicians, anesthesia and intensive care physicians, and infection control specialists from 2009 to 2013. The final recommendations of the expert group (https://lof.se/patientsakerhet/vara-projekt/rekommendationer/), includes statements on PJI risk factors, patient optimization before surgery, and antimicrobial prophylaxis as well as recommendations for the follow-up and registration of infections, and for the optimization of the operative environment. In the section on preoperative optimization, the expert group states that preoperative whole-body cleansing with chlorhexidine gluconate (CHG)- containing soap should be performed twice before surgery. Patient skin microbiota is noted to change rapidly after hospitalization, so it is suggested that preoperative stay in the hospital be minimized. In terms of antimicrobial prophylaxis, the expert group states that 2g of anti-staphylococcal penicillin (cloxacillin) should be given in three doses (at 0, 2, and 6 h), with the first dose given 30–45 minutes before incision. This is in contrast to the 2018 ICM, which advocates a broader spectrum of ac- tion, including against gram-negatives, and recommends a first- (cefazolin) or second-generation cephalosporin (cefuroxime) in a single- and weight- adjusted dose (159). As for the operative environment, the expert group states that ultra-clean air with fewer than 5 colony forming units (CFU) per m3 should be achieved, and that CFU/m3 levels should be monitored.

42 EMELI MÅNSSON Molecular epidemiology of S. epidermidis in PJIs

The PRISS statement does not discuss locally administered antimicrobial prophylaxis in bone cement. However, fixation of both the cup and the stem with bone cement in primary hip arthroplasty is recommended in Sweden for most patients aged over 75 years, and was used in 60% of all total hip replacements in Sweden in 2017 (160). Out of all more than 10,000 cemented hip arthroplasties performed that year, bone cement containing gentamicin was used in all but 58 procedures, and the historic use of antibiotics in bone cement may explain why (in Sweden) the reported adjusted relative risk of reoperation due to infection is 1.29 (95% C.I 1.13–1.47) higher in uncemented than cemented THA (160). The 2018 ICM recommendation is that antibiotic-impregnated cement may be used in primary TJA to reduce the risk of PJIs, but acknowledges that the cost-benefit analysis may be most favourable for patients at high risk of infection (161).

Summary of introduction S. epidermidis PJIs are rare but devastating to the patients affected. The limited data available on the molecular epidemiology of S. epidermidis in PJIs suggest that, as in other clinical infections with S. epidermidis, a limited number of hospital-associated STs predominate. During hospitalization, the proportion of patients colonized with MRCoNS increases, but whether this is due to the selection of MRCoNS already present in the pre-admission microbiota but in low relative abundance, or due to intra-hospital transmission of hospital-associated MDRSE is not known. Furthermore, the underlying reason for the success of certain S. epidermidis STs in PJIs remains to be elucidated, and last, if a genetic trait or traits could be identified that could distinguish S. epidermidis isolates representing true infection from isolates representing contamination this would be useful in clinical practice.

EMELI MÅNSSON Molecular epidemiology of S. epidermidis in PJIs 43

Aims The main aim of this thesis was to study the molecular epidemiology of S. epidermidis in PJIs, in order, by extension, to contribute to improved perioperative care of patients undergoing hip and knee arthroplasty.

Accordingly, the thesis objectives were:

• To characterize S. epidermidis isolates from PJIs and nasal mucosa by WGS, and determine what genomic traits differentiate PJI isolates from nasal isolates, to understand the underlying factors explaining the success of predominant MDRSE lineages.

• To investigate whether patients are colonized with MDRSE lineages associated with PJIs before hospitalization for TJA.

• To investigate whether STs of S. epidermidis associated with PJIs are found in the air of the operating field during arthroplasty surgery.

During the thesis work a separate aim – to study the genomic relatedness of S. pettenkoferi isolates of different origins – was defined.

44 EMELI MÅNSSON Molecular epidemiology of S. epidermidis in PJIs

Materials and Methods

Sampling of patients (Papers III–IV) After informed consent, and according to a protocol approved by the Regional Ethical Vetting Board, patients scheduled for hip- or knee arthroplasty in Region Örebro County (Lindesberg hospital, n = 29, November 2015 to December 2015), Region Östergötland (Linköping university hospital, n = 23, March 2013 to January 2015), Region Värmland (Karlstad hospital, n = 40, January 2013 to January 2014) and Region Västmanland (Västerås hospital, n = 37, December 2012 to May 2014) were sampled from their nares, inguinal crease, and either skin over hip/knee (depending on planned surgery) at the orthopaedic outpatient clinics 11 days (median, interquartile range [IQR] 8-19 days) before hospitalization. Sampling was performed using flocked swabs (ESwab, Copan Italia Spa, Brescia, Italy). All samples were sent to the Department of Clinical Microbiology, Örebro University Hospital, and subsequently plated on blood agar (Columbia Blood Agar Base 3.9% w/v [Oxoid, Basingstoke, Hampshire, UK] supplemented with 6% defibrinated horse blood [Håtunalab AB, Bro, Sweden]). All growth on the plates was harvested and stored frozen (–80°C) in preservation medium (Trypticase Soy Broth, BD Diagnostic Systems, Sparks, MD, USA), supplemented with 0.3% w/v yeast extract (BD Diagnostic Systems), and 29% horse serum (Håtunalab AB). Sampling was repeated after the first whole-body cleansing with CHG- containing soap for patients in regions Örebro County, Östergötland, and Värmland (after admission to hospital), and after the second whole-body cleansing with CHG containing soap for patients from all regions (patients in Västmanland performed their whole-body cleansing with CHG containing soap at home). A final set of samples was taken at discharge. Additional sampling of the nares of patients scheduled for hip and knee joint replacement surgery was performed in Region Örebro County (Lindesberg hospital, n = 262 September 2017 to May 2018). In Paper III, S. epidermidis from 150 nasal samples taken before hospitalization (Figure 6) were included for comparison with S. epidermidis isolates from PJIs. In Paper IV, pre-admission samples from the nares, inguinal crease and skin over hip/knee of patients from Östergötland, Värmland and Västmanland who contributed with nasal S. epidermidis in Paper III were included (Figure 6).

EMELI MÅNSSON Molecular epidemiology of S. epidermidis in PJIs 45

isolates samples 84 18 29 19 54 87 57 150 198 S. epidermidisS. isolates x3 x3 x3 A singleA random colony of patients 23 40 37 18 29 19 66 S. epidermidis S. 29+82 Örebro 262 Värmland Värmland Örebro Östergötland Västmanland Östergötland Västmanland Nare Paper III - included nasal nares fromSamples Paper IV - included samples (orthopaedic outpatient clinic)

ORTHOPAEDIC OUTPATIENT CLINIC

Preop sample

Västmanland) ( hospitalization of Period

Östergötland, Värmland) Östergötland, (Örebro, hospitalization of Period 87 87 87 85 85 85 129 129 129 106 106 106 total: total: total: total: 0 0 0 37 37 37 22 22 22 17 17 17 Västmanland Västmanland Västmanland Västmanland 40 40 40 37 37 37 36 36 36 22 22 22 Värmland Värmland Värmland Värmland 23 23 23 22 22 22 22 22 22 23 23 23 19) 19) - 5) - Östergötland Östergötland Östergötland Östergötland - 29 29 29 28 28 28 26 26 26 23 23 23 Örebro Örebro Örebro Örebro (median, IQR 8 IQR(median, (median, IQR 3 IQR(median, days (median, IQR 8 days IQR(median, 4 days 11 days 11 Nare crease Inguinal Hip/knee Nare crease Inguinal Hip/knee Nare crease Inguinal Hip/knee Nare crease Inguinal Hip/knee 1st PREOPERATIVE SHOWER with CHG SOAP PREOPERATIVE2nd SHOWER with CHG SOAP PROSTHETIC JOINT SURGERY ORTHOPAEDIC OUTPATIENT CLINIC Preop sample 1 Preop sample 2 Preop sample 3 sample,Postop discharge at

Figure 6. Overview of sampling of patients, and origin of nasal S. epidermidis isolates included in Paper III and pre-admission samples from nares, inguinal crease and skin over hip/knee included in Paper IV.

46 EMELI MÅNSSON Molecular epidemiology of S. epidermidis in PJIs Intraoperative air sampling (Paper I) Air sampling in the operating field was performed at Hospital of Västmanland, Västerås, Sweden, during 17 hip or kne arthroplasties between November 2011 and January 2012. The operating theatres (OTs) were equipped with mobile laminar air flow (MLAF) units. A Sartorius MD-8 air scanner (Sartorius Mechatronics, Göttingen, Germany) operating at a flow rate of 6 m3/h was used by an experienced infection control nurse according to local guidelines for air quality monitoring. The sterile filter holder was placed approximately 20 cm from the skin incision, directed in line with the laminar flow. Sterile gelatine filters (3 µm pore size, 80 mm diameter) were exchanged every 10 minutes by the scrub nurse and given to the infection control nurse who placed the filters on blood agar plates (Columbia II agar [BD Diagnostics Systems, Sparks, MD, USA] 4.25% w/v; horse blood, defibrinated, [Håtunalab AB] 6% w/v). A negative control (i.e., an unused filter) was analysed from all operations. The infection control nurse responsible for air sampling did not intervene with the positioning of MLAF units before or during surgery, but the results of the air quality measurements were conveyed to the perioperative team continuously during the study period.

Bacterial isolates (Papers I–IV)

Paper I The blood agar plates (with filters) from the 17 joint replacement surgeries during which air sampling was performed were incubated in an aerobic atmosphere at 36°C for 48 h at the Department of Clinical Microbiology laboratory, Hospital of Västmanland, Västerås, Sweden. The total numbers of colonies per plate were counted, and the plates were sent to the Department of Clinical Microbiology, Örebro University Hospital, Örebro, Sweden, where 743 colonies were sub-cultured and stored in preservation medium (Trypticase Soy Broth, BD Diagnostic Systems, Sparks, MD, USA), supplemented with 0.3% yeast extract (BD Diagnostic Systems), and 29% horse serum (Håtunalab AB) at –80°C pending further analysis.

Paper II S. pettenkoferi isolates retrieved from air-sampling in Paper I (n = 9) were analysed together with S. pettenkoferi isolates from blood cultures identified at the departments of Clinical Microbiology in Örebro (n = 1) and

EMELI MÅNSSON Molecular epidemiology of S. epidermidis in PJIs 47

Växjö (n = 13), as well as two S. pettenkoferi isolates from the European arm of the SENTRY Antimicrobial Surveillance Program (provided by JMI Laboratories, North Liberty, IA, USA), and the type strain CCUG 51270T for a total of 26 isolates of S. pettenkoferi.

Paper III S. epidermidis isolates from tissue cultures obtained during debridement or revision surgery due to presumed hip or knee PJI between 2007 and 2016 in two Swedish regions (n = 139) were included. Only isolates from surgeries with a minimum of two positive tissue cultures displaying identical antibiograms were included, and only one isolate per patient was included (isolates from repeated surgeries were excluded). The isolates were prospectively collected and preserved at –80°C in preservation medium Trypticase Soy Broth (BD Diagnostic Systems), supplemented with 0.3% yeast extract (BD Diagnostic Systems), and 29% horse serum (Håtunalab AB), at the departments of Clinical Microbiology at Örebro University Hospital, Örebro, Sweden and Linköping University Hospital, Linköping, Sweden, as per clinical routine.

The PJI isolates were compared with S. epidermidis isolates retrieved from nasal swabs of patients scheduled for hip- or knee arthroplasty surgery in four Swedish regions, i.e., Örebro, Östergötland, Värmland and Västmanland, between 2012 and 2017. The 150 nasal S. epidermidis isolates were identified from stored samples from which 10 µL of preservation medium was plated on blood agar plates (n = 129), and in primary streaks of nasal swabs plated on Mueller-Hinton (MH) II agar 3.8% w/v (BD Diagnostic Systems) plates (n = 82) (Figure 6). Staphylococci were identified by colony morphology after overnight culture in an aerobic atmosphere at 36°C followed by species identification with MALDI-TOF MS. A single S. epidermidis isolate per nasal sample was randomly chosen for further analysis.

Paper IV Ten µL of the stored preservation medium of samples from the nares, inguinal crease, and skin over hip/ knee of 66 patients sampled before hospitalization for arthroplasty surgery was dispensed and subcultured on MH agar plates supplemented with 5 mg/L cefoxitin (Sigma Aldrich, Darmstadt, Ger- many), and on a chromogenic medium primarily used for the detection of MRSA (CHROMID MRSA, bioMérieux). After 48 h of incubation in an

48 EMELI MÅNSSON Molecular epidemiology of S. epidermidis in PJIs aerobic atmosphere at 36°C, five colonies (in total from the two plates, when available) with macroscopic colony morphology consistent with staphylococci were randomly chosen and determined to species level by MALDI-TOF MS. Isolates identified as S. epidermidis were further characterized by mecA PCR (162) or loop-mediated isothermal amplification (LAMP, Genie II, Amplex Diagnostics GmbH, München, Germany and easyplex MRSAplus, Amplex). In total, 163 MRSE isolates were identified in the 198 patient samples and further characterized by WGS.

Species identification (Papers I–IV)

MALDI-TOF MS (Papers I–IV) MALDI-TOF MS was performed using Microflex LT and Biotyper software (Bruker Daltonik, Bremen, Germany; software versions and databases continuosly updated during the study period). The score cut-off score for species identification was ≥2.0 (Papers I–IV). In Paper I, extraction using a formic acid was used when a score value <2.0 was obtained. Furtermore, isolates with no reliable identification (score <1.7), despite extraction, but with good quality spectra, were clustered in Flex Analysis (these isolates were interpreted as likely to be species that were not represented in the database). A centrally placed isolate in each cluster was chosen for species identification by 16S rRNA gene sequencing. The MS spectra of isolates identified to species level by 16S rRNA gene sequencing were added to the MALDI-TOF MS database and a new matching of isolate spectra that previously had no reliable identification was performed. rpoB gene sequencing (Paper II) rpoB gene sequencing was performed as previously described (163) to verify species identification (S. pettenkoferi) in Paper II. Briefly, a 485 bp segment of the rpoB gene was amplified and the nucleotide sequence determined by fluorescence-based cycle sequencing, a modification of Sanger sequencing (ABI PRISM 3100 Genetic Analyzer, Applied Biosystems, Carlsbad, CA, USA). For species verification, a 485 bp segment was analysed by basic local alignment search tool (BLAST) (164) searching against staphylococcal rpoB sequences deposited in GenBank (165) using ≥94% sequence similarity as cut-off for species level (166).

EMELI MÅNSSON Molecular epidemiology of S. epidermidis in PJIs 49

16S rRNA gene sequencing (Paper I) 16S rRNA gene sequencing was performed as previously described (167). The nucleotide sequence was determined by fluorescence-based cycle sequencing using capillary electrophoresis (ABI PRISM 3100 Genetic Ana- lyzer, Applied Biosystems). Species identification was performed by BLAST searching against sequences deposited in GenBank (165) using ≥99% similarity as the cut-off for species level.

Antimicrobial susceptibility testing (Papers I–III) AST was performed by disc diffusion testing according to EUCAST guidelines (http://www.eucast.org). The antibiotics tested were cefoxitin 30 µg, fusidic acid 10 µg, clindamycin 2 µg, erythromycin 15 µg, gentamicin 10 µg, rifampicin 5 µg, trimethoprim/sulfamethoxazole 25 µg, and norfloxacin 10 µg (all discs from Oxoid, Basingstoke, Hampshire, UK). The clinical breakpoints were according to the recommendations of EUCAST at the time of the study. Gradient minimum inhibitory concentration (MIC) strip tests (ETEST, bioMérieux) were used for the determination of vancomycin MIC for PJI isolates in Paper III.

Genotyping methods

MLST (Papers I,III-IV) In Paper I, MLST of S. epidermidis was performed by the amplification of fragments of seven house keeping genes; carbamate kinase (arcC), shikimate dehydrogenase (aroE), ABC transporter (gtr), DNA mismatch repair protein (mutS), pyrimidine operon regulatory protein (pyrR), triosephosphate isomerase (tpiA), and acetyl coenzyme A acetyltransferase (yqiL) according to Thomas et al (50). Primers described by Wang et al (168) were used for the aroE gene, and primers described by Wisplinghoff et al. (169) for the tpiA gene for a few isolates for which no PCR products of the aroE and tpiA genes could be detected. The nucleotide sequences were determined by fluorescence-based cycle sequencing using capillary electrophoresis (ABI PRISM 3100 Genetic Analyzer, Applied Biosystems). Allelic profiles and STs were assigned using the S. epidermidis MLST database (http://eburst.mlst.net).

50 EMELI MÅNSSON Molecular epidemiology of S. epidermidis in PJIs

In Papers III and IV , allelic profiles and STs were assigned from sequencing data using mlst (https://github.com/tseemann/mlst) based on the S. epidermidis MLST typing scheme (https://pubmlst.org/sepidermidis/) sited at the University of Oxford (170).

Rep-PCR typing (Paper II) DNA was extracted using the UltraClean Microbial DNA isolation kit (bio- Mérieux) following the manufacturer’s instructions. Amplification of DNA was performed using the DiversiLab Staphylococcus DNA fingerprinting kit (bioMérieux) and the amplified rep-PCR products were then separated by electrophoresis in a microfluidics DNA LabChip (bioMérieux) and detected with an Agilent 2100 Bioanalyzer (Agilent Technologies, Palo Alto, CA, USA). The DiversiLab software package (bioMérieux) calculates the similarity between samples using the Pearson’s Correlation, the modified Kullback- Leibler (KL) divergence, and the extended Jaccard similarity. All methods calculate similarity based on the relative intensities of the sample pair at each datapoint, but they each place a different emphasis on peak intensity and presence. The KL divergence was chosen to present similarity, as it is recommended in the user manual when there are only one or two high-intensity peaks at the same molecular weight, but similar dendrograms/scatter plots were obtained with the other methods.

WGS and analysis of WGS data (Paper II-IV)

DNA extraction and library preparation In Paper II, DNA was extracted using the DNeasy Blood and Tissue Kit (Qiagen, Valencia, CA, USA) following the manufacturer’s instructions. Fragment libraries were constructed using the Nextera XT Kit (Illumina Inc., San Diego, CA, USA). In Paper III, DNA was extracted using the QIAsymphony DSP Vi- rus/Pathogen Kit (Qiagen, Hilden, Germany). Extracted DNA was quanti- fied using a Qubit fluorometer (Invitrogen, Waltham, MA, USA), followed by library preparation using the Nextera XT DNA Library Prep Kit (Illu- mina Inc.) following the manufacturer’s protocol. In Paper IV, DNA was purified using the Roche MagNA Pure 96 System (F. Hoffman-La Roche Ltd, Basel, Switzerland). Quantification of DNA and library preparation were performed as in Paper III.

EMELI MÅNSSON Molecular epidemiology of S. epidermidis in PJIs 51

Genome sequencing and quality control In Paper II, 251 bp paired-end sequencing was performed on a MiSeq platform (Illumina Inc.). In Paper III-IV, the libraries were sequenced on a NextSeq 550 platform (Illumina Inc.,) to obtain paired-end 151 bp reads. The generated sequencing data were subjected to quality control using bifrost (https://github.com/ssi-dk/bifrost) to ensure adequate sequencing depth of all isolates. Interspecies contamination was checked for using Kra- ken v1.0 (171), whereas intraspecies contamination was investigated using NASP v.1.0.0 (172). All genome sequences were archived at the European Nucleotide Archive under study IDs ERS1751294-ERS1751319 (Paper II), BioProject ID PRJEB32707 (Paper III), and BioProject ID PRJEB34788 (Paper IV).

Publicly available genome sequences used in this thesis (Papers II–IV) In Paper II, a draft genome of S. pettenkoferi NZ_JVVL00000000.1 (strain 1286_SHAE) from the NCBI Reference Sequence Database (RefSeq, https://www.ncbi.nlm.nih.gov/refseq) was used as the reference for read mapping and subsequent SNP analysis. S. pettenkoferi draft genomes NZ_JVAY00000000.1 (strain 589_SHAE) and NZ_AGUA0000000.1 (strain VCU012) were included in the analysis of phylogenetic relationships. In Paper III, ATCC 12228 chromosome (173) (GenBank accession number CP022247) was used as reference for SNP calling, and for international validation and extrapolation sequence data from two recently published S. epidermidis papers (6, 174) as well as all additional sequence data from S. epidermidis of human origin present in RefSeq as of 13 March 2019 (with metadata on country of isolation) were used, after removing isolates with low sequencing depth or signs of contamination using NASP v1.0.0 (172).

Phylogenetic relationships In Paper II, the NASP v1.0.0 (172) pipeline was used to align raw reads to the draft genome of S. pettenkoferi NZ_JVVL00000000.1 obtained from RefSeq, using the short-read alignment component of the Burrows-Wheeler aligner (BWA-MEM) (175) after removing duplicated regions of the reference genome as identified using NUCmer (176). Two other available S. pettenkoferi draft genomes; i.e.; NZ_JVAY00000000.1 and NZ_AGUA0000000.1, were also aligned to the reference draft genome. Each alignment was analysed for SNPs identified using GATK (177). Sites that did not meet a minimum sequencing depth of 10, or if the variant was

52 EMELI MÅNSSON Molecular epidemiology of S. epidermidis in PJIs present in <90% of the base calls (i.e., failed proportion filter), were excluded across the collection. Phylogenetic relationships were reconstructed using the maximum-likelihood method implemented in PhyML using Smart Model Selection with 100 replicates of all included isolates (178). In Paper III, the NASP v.1.0.0 pipeline was used with the same programs as in Paper II to align raw reads (and assembled genomes in selected cases) to the S. epidermidis ATCC 12228 reference chromosome (173)(GenBank accession number CP022247), and for SNP calling. Phylogenetic recon- struction was carried out using different approaches in Paper III due to com- putational limitations in calculations on the larger dataset. For the complete set of Swedish and international human isolates of S. epidermidis (n = 1,161), the phylogeny was obtained using the approximately-maximum- likelihood implementation in FastTree v2.1.10 (179) using the generalized time-reversible (GTR) substitution model as well as nearest-neighbor inter- changes (NNI) and subtree-pruning-regrafting (SPR) rearrangements for tree optimization. Phylogenies for the ST2 clade (n = 353), the ST5-clade (n = 93), and the Sweden-only collection (n = 289) were obtained with RAxML v8.2.1 (180) using the GTRCAT model and 100 replicates for bootstrapping. Visualization and annotation of midpoint-rooted phylogenies were performed in iTol v4.3 (181) (https://itol.embl.de) with subsequent editing in Adobe Illustrator (Adobe Inc., San Jose, CA, USA).

Genome-wide analysis study (GWAS) (Paper III) The open-source R package treeWAS (182), designed to minimize the con- founding effects of population structure and recombination, was used to perform GWAS of genes, SNPs, and k-mers associated with PJI origin in Paper III. SPAdes v3.11.1(183) using default settings was used to assemble reads. Genes and their locations in the assemblies were identified (annotated) using Prokka (184), followed by identification of the core, pan-, and accessory genome using Roary (185). To mitigate inaccuracies in gene presence/absence data due to difficulties in gene assembly in certain regions we used Mykrobe (186) on sequence data (reads) to identify genes in the accessory genome (identified by Roary), with 80% coverage and a minimum sequencing depth of five as cut-offs. K-mers (31 bp) were obtained using pyseer (187). To mitigate the effects of homologue recombination on the phylogenetic relationships, Gubbins (61) was used with default settings on the SNP-only alignments obtained from NASP before treeWAS was applied.

EMELI MÅNSSON Molecular epidemiology of S. epidermidis in PJIs 53

Genotypic antimicrobial resistance (AMR) (Papers II-IV, additional data) In paper II–IV, ABRicate (https://github.com/tseemann/abricate) was used to search the assembled genomes for acquired AMR genes in the ResFinder (188) database. Gene presence was determined based on a >80% hit length and >90% sequence identity. Point mutations associated with AMR and tolerance of biocides were investigated in Papers III-IV; Geneious Prime v2019.1 (Biomatters Ltd, Auck- land, New Zealand) was used for the BLASTN search for positions in genes where SNPs associated with AMR have been described. Genes and positions are presented in a Supplementary Table in Paper III. Genes and gene variants associated with AMR were determined in S. epidermidis from PJIs in Västmanland (this thesis) using ResFinder (https://cge.cbs.dtu.dk/services/ResFinder/).

SCCmec diversity (Paper III) SCCmecFinder v1.2 (189) was used for initial typing. Elements were classified as known types, including composites when previously described and acknowledged by the International Working Group on the Classification of Staphylococcal Cassette Chromosome Elements (IWG-SCC, www.sccmec.org) (190), whereas other types were presented as composites. If divergent results were obtained using the BLAST and the k-mer-based approaches, the elements in question were manually investigated for mec and ccr gene complexes for validation.

Genes associated with biofilm, virulence, and commensalism (Papers III, and IV, additional data) Geneious was used for the BLASTN search of reference sequences of aap, bhp, embp, icaA, ses I, fdh, and ACME-arcA (Paper III). The IS256 gene was detected using Mykrobe to map reads to reference (CP018629.1, positions 533,639-534,811) (Paper III). Genes associated with PJIs as determined by GWAS in Paper III were identified in MRSE sequenced in Paper IV using Mykrobe on raw sequencing data. Genes were identified using a 90% proportion of gene length covered and a minimum coverage of five as cut-offs. PathogenFinder (191) – an online tool developed to estimate the pathogenic potential of an isolate based on its sequence – was used on S. pettenkoferi genomes (this thesis).

54 EMELI MÅNSSON Molecular epidemiology of S. epidermidis in PJIs

Digital DNA:DNA hybridization (additional data) The genomic relatedness of twenty S. pettenkoferi isolates included in Paper II was investigated by uploading genome sequence data to the Type (Strain) Genome Server (TYGS) (25), a free online tool for whole genome-based taxonomic analysis available at https://tygs.dsmz.de. TYGS analysis extract 16S rDNA gene sequences from the user genomes using RNAmmer (192). Each 16S rDNA sequence is then analysed using BLAST against the 16S rDNA gene sequence of each of the type strains available in the TYGS database. This is used as a proxy to find the best 50 matching type strains for each uploaded genome. Precise distances using the Genome BLAST Dis- tance Phylogeny (GBDP) approach under the “coverage” algorithm and distance formula d5 (193) are subsequently calculated and the 10 closest type strain genomes for each of the user genomes is determined. Pairwise com- parisons among the set of genomes are conducted using GBDP and intergenomic distances are inferred under the “trimming” algorithm and distance formula d5 (193). One hundred distance replicates are calculated. Digital DNA:DNA hybridization (dDDH) values and confidence intervals are calculated using the recommended settings of the genome-to-genome distance calculator (193). The resulting intergenomic distances were used to infer a balanced minimum evolution tree with branch support via FASTME v2.1.4 including SPR postprocessing (194). Branch support was inferred from 100 pseudo-bootstrap replicates each. The trees were rooted at the midpoint and visualized with PhyD3 (195). Type-based species clustering was done as previously applied using a 70% dDDH radius around each of the 15 type strains (196), and subspecies clustering was done using a 79% dDDH threshold as previously suggested (27).

Phenotypic biofilm production (Paper II) A microtiter plate assay was used to detect biofilm formation, as described previously (117).

EMELI MÅNSSON Molecular epidemiology of S. epidermidis in PJIs 55

Ethical considerations Paper I Air sampling was undertaken as part of the Department of Infection Control’s routine surveillance of air quality in the OT. No data that could be traced back to an individual patient were recorded.

Paper II Subcultured S. pettenkoferi isolates were included. Bacterial isolates were obtained from air sampling (study I) and clinical infections. No personal data that could be traced back to an individual patient were obtained.

Paper III Subcultured S. epidermidis isolates from PJIs were prospectively stored without clinical data. Limited clinical data from the original microbiology request form (joint, sex, year of birth, and date of sampling) were provided with the isolates. No personal data that could be traced back to an individual patient were obtained.

S. epidermidis isolates from nasal swabs were obtained from patients scheduled for arthroplasty surgery after informed consent (protocol approved by the Regional Ethics Review Board [Uppsala, Dnr 2012/092; Uppsala, Dnr 2016/151/2], for further details please see below under Paper IV).

Paper IV After informed consent, the normal skin and mucosal flora of patients scheduled for arthroplasty surgery were sampled by rubbing a soft swab against the skin in the inguinal crease, the skin over the affected joint, and the sides of one nostril. Swabbing was pain free, and the participants were subject to no harm nor risk. As the sampling procedure was repeated after pre-operative cleansing with CHG-containing soap, and at discharge from hospital, samples were marked with patient identification numbers to facilitate pairing of samples, but after finalization of the collection, further analyses were undertaken using serial numbers. The study protocol was approved by the Regional Ethics Review Board (Uppsala, Dnr 2012/092).

56 EMELI MÅNSSON Molecular epidemiology of S. epidermidis in PJIs

Statistics In Paper I, median, interquartile range (IQR), and range were used to describe the number of CFU/m3 air per operation in Paper I (the data was not normally distributed). Chi-square testing was used to test the frequency of Micrococcus and CoNS, respectively, between operations during which ultra-clean air was and was not obtained. In Paper II, the modified Kullback–Leibler method was chosen to calculate percent similarities between samples in the DiversiLab software. In Paper III, Simpson’s Diversity Index (DI) with 95% confidence intervals (197) was used to compare ST diversity between PJI isolates and colonizing isolates. The value of the DI ranges from 0 to 1; with 0 representing no diversity and 1 infinitive diversity. Median and IQR were used to present the age of patients contributing with PJI and nasal isolates, respectively, after using Shapiro-Wilk to determine normality. The association between between gene of interest and isolate origin was tested using Binary Logistic Regression and Fisher’s exact test. The association between PJI lineage and administrative region of isolation was tested using Chi-square testing, as were differences in the frequency of PJI associated genes (as determined by treewas) between PJI-isolates obtained within this study and in internationally available PJI sequences. Bonferroni adjustment was not performed, and a p-value < 0.05 (two-sided) was considered statistically significant. For the GWAS analyses, any trait with p-value <0.05 after correction for multiple testing using Bonferroni adjustment was considered significant. In Paper IV, mean and SD were used to describe patient age (after determining normality using Shapiro-Wilk testing). Chi-square testing and t-testing were used to test differences in MRSE colonization rates and in mean age between patients recruited between the three administrative regions, respectively. Fisher’s exact test was used to test differences in the frequency of co-existing genotypic AMR in MRSE from different body areas. A p- value (two-sided) <0.05 was considered statistically significant. Statistical analysis was performed using SPSS v25 (IBM Corp., Armonk, N.Y, USA), R v3.5.1 (https://www.R-project.org), or using online tools at www.openepi.com (i.e., confidence interval for normal approximation confidence interval for a given percentage) and www.comparingpartitions.info/ (i.e., Simpson’s DI with confidence intervals).

EMELI MÅNSSON Molecular epidemiology of S. epidermidis in PJIs 57

Results and Discussion

Molecular epidemiology of S. epidermidis in relation to PJIs (Pa- pers I, III, and IV)

Clonal relatedness of S. epidermidis isolated from PJIs

Swedish PJI isolates S. epidermidis isolates prospectively collected from hip- and knee- PJIs over a ten-year period (2007–2016) in Region Örebro County and Region Östergötland, (n = 139) were sequenced in Paper III. Phylogenetic relatedness was inferred from SNPs in the core genome after inclusion of 150 nasal S. epidermidis for comparison. Four major PJI-lineages, hereafter referred to as ST2a (n = 16), ST2b (n = 43), ST5 (n = 16, 13 of PJI origin), and ST215 (n = 34) lineages based on the dominant ST as determined by MLST (Figure 7), were identified. The four lineages together comprised 76% of all PJI isolates.

Tree scale 0.1

218 ST

S T 5

5 1 2 T S

S T a 7 2 3 T S

2b ST

Figure 7. Phylogenetic relatedness of S. epidermidis from PJIs (n = 139, green) and nasal microbiota (n = 150, red). The midpoint-rooted phylogeny was based on 95,245 SNPs and the scale-bar indicates substitutions per site.

58 EMELI MÅNSSON Molecular epidemiology of S. epidermidis in PJIs The ST2a and ST2b represent two distinct lineages of ST2, primarily distinguished by a single recombination event. The ST2a lineage comprised only ST2 isolates, whereas the in the other lineages single locus variants (SLVs) of the founder ST were found (i.e.: in the ST2b-lineage ST2, ST731, and ST735; in the ST5-lineage ST5, ST87, and ST713; and in the ST215- lineage ST215, ST434, and ST730). ST434 is an SLV of ST215 not found in the previous PJI study by Hellmark et al.(20), or in a long-term molecular epidemiology study of 373 bacteremia isolates from a haematological ward in Örebro, 1980–2009 (19). In the pubMLST database (pubmlst.org), however, ST434 is represented by three isolates, reported from three PJIs from Umeå and Östersund, Sweden, 2010–2011. Looking into details of the ST215-lineage of isolates from Paper III, 4/34 were ST434 and these were isolated in the later study period (2012–2014, two isolates from each region), suggesting the spread of ST434 between hospitals in Sweden over the last decade. Isolates within each major PJI lineage were closely related (Figure 8). The median (interquartile range, IQR) pair-wise SNP distances within each major PJI lineage were: ST2a, 69 (42-81 SNPs); ST2b, 135 (96-164); ST5 97 (86-113); and ST215, 46 (38-53).

Figure 8. Intra-lineage (red) and inter-lineages (orange) diversity (pairwise SNP distances) among the major S. epidermidis lineages identified in Paper III. Three nasal S. epidermidis isolates clustered with PJI isolates within the ST5 lineage. For comparison two major lineages with predominantly nasal isolates (ST73 and ST218) are included. Boxes represent the interquartile range (IQR) with median outlined as a horizontal line, whereas whiskers present lowest/highest value within 1.5 IQR.

EMELI MÅNSSON Molecular epidemiology of S. epidermidis in PJIs 59

The four major PJI-lineages were all identified and present, but with variation in relative abundance, over the ten-year period in both regions (Figure 9, Table 4).

Figure 9. PJI isolates sequenced in Paper III (n = 139); number of isolates per lineage per year of isolation.

Lineage Örebro Östergötland total ST2a 8 (15%) 8 (10%) 16 (12%) ST2b 21 (38%) 22 (26%) 43 (31%) ST5 6 (11%) 7 (8%) 13 (9%) ST215 11 (20%) 23 (27%) 34 (24%) other STs 9 (16%) 24 (29%) 33 (24%) Total 55 (100%) 84 (100%) 139

Table 4. PJI isolates sequenced in Paper III; number of PJI isolates per lineage per administrative region. Chi-square=5.53, df=4, p=0.2546 (two-sided).

The findings in Paper III thus confirmed the results of Hellmark et al (20) in a larger collection of isolates – that S. epidermidis PJIs were dominated by a few lineages. The higher discriminatory ability of SNP-based analysis in relation to MLST was illustrated by the presence of two distinct lineages of ST2, as was the sensitivity of MLST to SNPs (leading to the assignment of new STs within a lineage). MLST profiles of S. epidermidis isolates from hip- and knee PJIs in Väst- manland (n = 18), prospectively collected over a two-year period (2012–

60 EMELI MÅNSSON Molecular epidemiology of S. epidermidis in PJIs

2013, two years after intraoperative air sampling was performed in Paper I), were determined by WGS (this thesis). Only isolates retrieved from tissue cultures from revision surgeries for suspected of hip- or knee PJIs from which a minimum of two intraoperative cultures grew S. epidermidis with identical antibiograms were sequenced, and only one isolate per patient was included. The most common STs were ST2 (n = 7) and ST434 (n = 3), together comprising 55% of all isolates. No ST215, nor ST5 (or STs clustering with ST5 in Paper III) was found. Reference-based SNP calling and estimation of phylogenies have not been performed for these isolates, so the ST2a- and ST2b-lineages could not be distinguished, but, in one ST2 isolate the dual rpoB mutations D471Y/H481N were identified which only were found among ST2a isolates in Paper III. One SLV of ST5 (ST17) was identified, but ST17-isolates in Paper III did not cluster with the ST5-lineage (Supplementary data in Paper III). The remaining isolates belonged to ST19, ST35, ST73 (n=2), ST203, ST218, and ST307.

International data Phylogenetic relationships of isolates sequenced in Paper III to publicly available S. epidermidis sequences of human origin (n = 872) was determined in Paper III (Figure 10). The Swedish PJI isolates were found to con- sist of several subgroups within S. epidermidis lineages ST2a, ST2b, and ST5 isolated from hospitals world-wide (Figure 10). Only three isolates belonging to the ST215 lineage were found among publicly available international S. epidermidis sequences, two clinical isolates from Denmark (none with metadata “PJI”) and one colonising isolate from Iceland. International S. epidermidis sequences with metadata indicating “prosthetic joint infection” (n = 122) were found within the ST2b and ST5 lineages, but also in a third ST2 lineage (ST2c), in the ST59 lineage, and in the globally distributed hospital-associated ST23.

EMELI MÅNSSON Molecular epidemiology of S. epidermidis in PJIs 61

PJI Source

Continent

is ST5 III) in light ST23 - ST59 and ST23 Paper bar indicates sub- indicates - bar C 0.002 (~90 SNPs) PJI are the Source Swedish ( Swedish Continent ST5 of phylogeny Detailed , . . C) ST2b ST2a le: PJI isolates PJI le: 52,690 SNPs and the scale the and SNPs 52,690 III (n=289) and publicly available S. epidermid available publicly and (n=289) III

B 0.01 (~300 SNPs) Paper and ST215) are coloured ST215) and ingreyas ST59 , ST23 phylogeny based on 29,843 SNPs) 29,843 on based phylogeny ST2c ST215 ST5 T2b, ST2c,T2b, ST5 rooted phylogeny was based on based was phylogeny - rooted continent of isolation. Outermost circ Outermost isolation. of continent s s 0.05 T2a, S (~2600 SNPs) S ST2a i.e., i.e., Ps). Ps). - lineages (

ST2b

Continent PJI A . Phylogenetic relationships of S. epidermidis sequenced in sequenced S. epidermidis of relationships Phylogenetic . d and international in black. The The midpoint black. in d and international Africa Asia South America Clinical infection skin/mucosa Missing data Sweden International Australia Europe North America 4,284 SN on 4 4,284 based (phylogeny re Figure 10 Figure sequences. A) Major PJI lineages. Innermost circle: colour represent ( ST2a/ST2b phylogeny of B) Detailed site. per stitutions Continent PJI Source

62 EMELI MÅNSSON Molecular epidemiology of S. epidermidis in PJIs

To further relate the present findings to international data, PubMed was searched using the search terms (“molecular epidemiology” OR “MLST”) AND (“Staphylococcus epidermidis”) AND (Humans[Mesh])) on 22 July 2019. The titles and abstracts of all 85 Papers retrieved were reviewed to identify studies reporting MLST typing data from S. epidermidis PJIs, but no study of the molecular epidemiology of PJIs presenting MLST data was found other than that of Hellmark et al (20). Next, the ESCMID eLibrary was searched for ECCMID abstracts using the broad search term “epidermidis”; 103 abstracts were reviewed and three abstracts on the molecular epidemiology of S. epidermidis in PJIs were identified. Data from these presentations (198-200) (including material presented during oral presentation at 29th ECCMID, Amsterdam, the Netherlands, 2019) are presented in Table 5, together with MLST data for the 122 publicly available S. epidermidis genomes with metadata indicating PJI origin (accessed in Paper III). STs were assigned to lineages based on the phylogenetic analysis in Paper III. As shown in Table 5, available data from Europe and the USA indicate a similar predominance of ST2- and ST5-lineages in S. epidermidis PJIs, whereas the ST215 lineage has not been isolated from PJIs outside Sweden.

EMELI MÅNSSON Molecular epidemiology of S. epidermidis in PJIs 63

Table 5. MLST of S. epidermidis in PJIs in accessible study collections.

64 EMELI MÅNSSON Molecular epidemiology of S. epidermidis in PJIs

Genetic diversity of S. epidermidis retrieved from the microbiota of patients scheduled for arthroplasty surgery (Paper III and IV)

Nasal S. epidermidis retrieved from standard culture medium In Paper III, a single random colony of S. epidermidis from 150 nasal samples taken a median of 2 weeks before admission to hospital for arthroplasty surgery and cultured on standard medium (MH agar plates) was selected for further characterization by WGS. Phylogenetic analysis based on core genome analysis demonstrated considerable diversity of the nasal isolates (Figure 7, Simpson Diversity Index 0.964 [95% C.I 0.950-0.978] vs. 0.798 [95% C.I 0.742-0.855] for PJI isolates). However, discrete lineages were also evident, including two lineages with more than 10 isolates each: ST218 (n = 21) and ST73 (n = 18) (Figure 7). Three nasal isolates clustered within the PJI-associated ST5 lineage (Figure 7), but no nasal isolate clustered with the PJI-associated lineages ST2a, ST2b, and ST215. Seven nasal isolates were closely related to ST59 isolates from PJIs.

Nasal and skin S. epidermidis retrieved from media selective for methicillin resistance In Paper IV, selective culture media were used to investigate whether MRSE were present, but at low abundance, in the microbiota before hospitalization, and thus potentially missed by random selection of a single colony from non-selective medium (as was done in Paper III). Samples from the nares, inguinal crease and skin over the hip/knee of 66 patients were plated on MH agar plates supplemented with cefoxitin and on MRSA chromogenic plates. In total, 409 CoNS colonies (presumably methicillin-resistant due to their growth on selective media) were found in samples from the vast majority of patients, i.e., 52/66. The most frequently identified CoNS species was S. epidermidis (n = 167, 32 patients), followed by S. haemolyticus (n = 76, 18 patients), S. pettenkoferi (n = 54, 10 patients), S. hominis (n = 31, 6 patients), Staphylococcus cohnii (n = 21, 4 patients), S. capitis (n = 11, 4 patients), and S. lugdunensis (n = 10, 3 patients). Identification to species level with MALDI-TOF was impossible for 34 staphylococcal isolates (“Staphylococcus species”) from ten patients. Four S. aureus isolates (all mecA/mecC negative) were retrieved from two patients. A total of 163 S. epidermidis isolates from 30 patients (30/66, 45% of sampled patients, 95% C.I. 34–57%) were verified as mecA positive (hereafter referred to as MRSE). Colonization rates with MRSE varied between

EMELI MÅNSSON Molecular epidemiology of S. epidermidis in PJIs 65 hospitals: Karlstad (A) 20/29 (69%), Västerås (B) 6/19 (32%), and Linkö- ping (C) 4/18 (22%) (p=0.003, df=2) (Table 6). In more than half of the MRSE-colonized patients (17/30), MRSE was retrieved from a single body site (nares, n = 7; inguinal crease, n = 6; hip/ knee, n = 4) (Table 6). In samples from eleven patients, MRSE was retrieved from the nasal mucosa and either the inguinal crease or site of planned surgery, and in one patient MRSE was retrieved from all three sampled body areas.

66 EMELI MÅNSSON Molecular epidemiology of S. epidermidis in PJIs

STs of MRSE strains SNVs (number in bold = multidrug-re- distance sistant) (range) ST of ID Nasal Inguinal Hip/ between MRSE in nr. Age Sex Hospital mucosa crease knee samples paper III

1 84 M A 5 5 5 6-40 - 2 83 M A 87 87 - 2 87 3 80 F A 54 54 - 12 54 4 79 F A - 230 - - 7 76 F A 5 5 - 1 - 8 75 M A - 5 22 3917 - 10 75 F A 22 - 22, 22 13-20 - 13 73 F A - 22 - 14 71 M A 54 35 - 3917 - 15 71 F A 290 - - - 16 70 F A 2,2,2 - 2 9-10 - 19 61 M A 22 - - 22 24 54 F A 48,38,59 48 - 3-8466 - 29 43 F A 22 - 22 19 - 30 73 F A 173 - 5 5842 - 33 78 F A 882 - - - 35 73 F A - - 22 - 36 60 F A 22 - - - 37 83 F A 5 - - - 39 74 F A 21,21,21,46 22, 22 - 5641-6381 - 42 77 M B - 2 - - 46 70 M B - - 210, 210 - 51 61 F B - 2 - - 55 60 M B - - 2 - 58 81 M B - 81 - - 61 57 F B 17 46, 46 - 5411-5414 54 88 46 M C 881 - - - 89 64 M C - - 215 - 91 49 M C 38 - - - 98 53 F C - 487 - - 57 85 F B - - - 713

Table 6. Methicillin-resistant S. epidermidis (MRSE) strains per patient sample (Pa- per IV). ID nr. = patient identification number, STs = sequence types, SNVs = single nucleotide variants.

EMELI MÅNSSON Molecular epidemiology of S. epidermidis in PJIs 67

Following quality control of sequence data, sequences from six isolates were excluded: four due to signs of intraspecies contamination based on the failed proportion filter (SNPs were not found in >90% of base calls per nucleotide), and two due to contamination with other species. In total, high quality sequence data were available for 157 MRSE that were included in the first phylogenetic analysis. Based on a conserved core genome of 1.8 Mbp (69.7% of the chromosome of reference RP62a), 52 MRSE strains (isolates separated by 0-3 SNVs) were identified in 44 samples. Most patients who were colonized with MRSE at multiple sites (10/13) were colonized with multiple strains (i.e., strains that differing more than three SNVs between samples). In 3/13 patients, isolates from the same strain were identified in samples from two locations. The maximum SNV distance displayed between MRSE strains with identical STs, retrieved from the same patient, was 40 SNVs. Overall, 23 STs were identified, including two novel, but unrelated, STs: ST881 and ST882. To simplify the presentation of the clonal relatedness of MRSE strains retrieved from pre-admission sampling, a second phylogeny with a single isolate per MRSE strain per sample (n = 55, three MRSE strains were identified in two samples from three patients) was generated (Figure 11). Strains belonging to lineages associated with PJIs in Sweden were identified in samples from ten patients. ST2b, n = 3; ST5, n = 6; ST215, n = 1. No ST2a isolate was retrieved from the 198 (66 x 3) samples. Nine patients were colonized with MRSE strains belonging to the ST22 lineage, and one patient with an ST2 strain (non-ST2a/2b) closely related to the ST22 lineage.

68 EMELI MÅNSSON Molecular epidemiology of S. epidermidis in PJIs

Figure 11. Phylogenetic relatedness of n = 55 mecA-positive S. epidermidis isolates retrieved from sampling of 66 patients before hospitalization for arthroplasty surgery. Lineages previously associated with PJIs in Sweden are marked in grey. Col- umns from left to right: ST (sequence type)/lineage, genes previously associated with PJI origin (genes associated with SCCmec [dark blue], aminoglycoside resistance [medium blue], macrolide-lincosamide resistance [light blue], chlorhexidine tolerance [purple], IS256 [orange], gene coding for proteins of unknown function [dark red]), patient identification number, sample origin (body area), hospital of isolation. The midpoint-rooted phylogeny was based on 66,152 SNPs and the scale bar indicates substitutions per site.

By use of selective plating of samples from three body sites, we were able to demonstrate that a great proportion of patients scheduled for arthroplasty surgery harbour presumably MRCoNS in their microbiota before hospitalization (52/66, 79%), and that a subset are colonized with MRSE belonging to lineages associated with PJIs (up to 30% of patients, if including ST22 which was found among international S. epidermidis sequences

EMELI MÅNSSON Molecular epidemiology of S. epidermidis in PJIs 69 from PJIs [Table 5]), but plausibly in low relative abundance. MRSE was most often retrieved from nasal samples, but one third of MRSE-colonized patients would have been missed by mere nasal sampling (10/30, including 4/10 patients colonized with PJI-associated lineages). The colonization rate with MRSE was higher in Paper IV than in two previous studies using selective medium (80, 201) (p=0.01, Chi square), in which MRCoNS were retrieved from 2/14 patients (14%, 95% C.I 0–33%) (80) and MRSE from 25/100 (25%, 95% C.I 18–34%) (201) at admission. In the previous studies agar plates supplemented with 10mg/L methicillin were used, and the different choices of selective media might have influenced the results, but it is also possible that colonization with MRSE has increased in the population in recent decades.

S. epidermidis in the air of the operating field during arthroplasty surgery (Paper I) To study whether STs of S. epidermidis associated with PJIs are found in the operating field air during arthroplasty surgery, air sampling was performed during 14 THAs, 2 TKAs, and one unicompartemental knee arthroplasty (UKA) in Hospital of Västmanland, Västerås, Sweden, from Novem- ber 2011 to January 2012 by an experienced infection control nurse (Figure 12). The ORs were equipped with mobile laminar airflow elements, but ultra-clean air (<10 CFU/m3) was not achieved during 4/17 (24%) prosthetic joint surgeries, and during 2/13 surgeries with a median CFU/m3 ≤10, this was not obtained consistently throughout the operation. The intention was to perform species identification of all colonies that were retrieved from air sampling, but as the air quality was unexpectedly poor during the first procedure, this was limited to 20 colonies per plate (specifically selecting colonies with macroscopic appearance of CoNS) for the first operation (totalling 100 colonies retrieved from the first procedure). From the remaining 16 operations, all colonies (n = 643) were subcultured and frozen pending species identification. Eight colonies did not grow after thawing, so in total 735 colonies were available for species identification.

70 EMELI MÅNSSON Molecular epidemiology of S. epidermidis in PJIs

Figure 12. Positioning of the air sampling device in the proximity of the operating field. Photo by Christer Häggström.

Species identification demonstrated that isolates retrieved from air sampling were predominantly either Micrococcus sp. (n = 303) or Staphylococ- cus sp. (n = 247), followed by Corynebacterium sp. (n = 37), Kocuria sp. (n = 17), Dietzia sp. (n = 9) and Stenotrophomonas sp. (n = 7). MALDI-TOF did not result in species identification of 68 isolates (presumably due to the absence of species-specific spectra in the Biotyper database). These 68 isolates had unique spectra when investigated with Flex Analysis and were not subjected to 16S rRNA gene sequencing (as the aim of the study was to characterize S. epidermidis). S. epidermidis (n = 32) was retrieved in air samples from 11/17 operations (Table 7). In four of the eleven operations, the air quality was below the threshold of <5 CFU/m3 set by the PRISS project. MLST demonstrated 18 different S. epidermidis STs (1-4 STs per operation). All but one of the S. epidermidis isolates were susceptible to cloxacillin (cefoxitin) used for systemic prophylaxis in arthroplasty surgery, and all isolates were susceptible to gentamicin (used in bone fixation cement). One ST204 isolate was resistant to fusidic acid, clindamycin and erythromycin and thus was categorized as MDR. Of S. epidermidis isolates retrieved from air sampling, 10/32 belonged to STs that were later found among S. epidermidis isolates from nasal samples

EMELI MÅNSSON Molecular epidemiology of S. epidermidis in PJIs 71 taken from patients before hospitalization for TJA (Paper III) (Table 7). Most remaining isolates (15/22) belonged to new STs and had thus so far not been reported from any clinical infections (nor as isolates representing colonization). STs previously associated with PJIs (20) were not found in the air of the operating field during arthroplasty surgery, and neither were any other STs associated with PJIs (Table 5), with the exception of two PJI isolates from Västerås collected during 2012–2013, which were ST73. The STs found in the air were mostly associated with carriage in the PubMSLT S. epidermidis database, with the exception of ST86, ST130, and ST54 which had been isolated from clinical infections (Table 7). The only isolate reported in Paper I as non-susceptible (intermediate) to cefoxitin was a ST54 isolate with a zone diameter of 26 mm. This isolate was tested and found to be mecA positive. The current EUCAST breakpoint table (v9.0) cut off for cefoxitin sensitivity is ≥ 25 mm for S. epidermidis, but zone diameters 25–27 mm are highlighted as area of technical uncertainty (ATU). Isolates with zone diameters within the ATU can either be retested, have AST complemented with a genotypic test, be downgraded in terms of susceptibility category, or be reported to the clinician with information about the uncertainty (EUCAST breakpoint tables version 9.0). It can be noted that two out of three ST54 isolates retrieved from nasal samples in Paper III were mecA positive, and that 2/66 patients in Paper IV were colonized with a mecA positive ST54 isolate. To summarize, in more than half of the surgeries, S. epidermidis was retrieved from air sampling in the operating field. MLST of these isolates demonstrated heterogenous STs, but most isolates belonged to STs associated with colonization, and no isolate associated with the ST2a, ST2b, ST5, or ST215 lineage was retrieved from intraoperative air sampling.

72 EMELI MÅNSSON Molecular epidemiology of S. epidermidis in PJIs

tes

ring isolates IDs, IDs, isolates clindamycin,

e arthroplasty; Bilat, dermidis ether theST wasfound among S. epidermidis database are indicated in the lastfour columnsthe toright. count during the operation, durationsurgery, of S. epi

3 retrieved from intraoperative airsampling during arthroplastysurgery (Paper I). From leftright: to operation

S. epidermidis Table 7. (running number),type procedure of performed (UKA, unicompartementalarthroplasty; knee TKA, total kne bilateral; THA, totalarthroplasty), hip operatingtheatre (OT) identification number, numberpersons of present the in du OR surgery, number of door openings, median CFU/m sequencetypes (STs), andAST results (i.e., zone diameters [mm] diskby diffusion testing forcefoxitin, fusidic acid [FA], erythromycin,gentamicin, rifampicin, folate pathway inhibitors [TMP/SMX], and norfloxacin).Wh nasal samplesin Paper III, among PJI sequences(Table 5), among MRSE isolates retrieved in PaperIV,and the number of isola and predominant sourceas reported the in pubMLST

EMELI MÅNSSON Molecular epidemiology of S. epidermidis in PJIs 73

Genetic traits in S. epidermidis in relation to isolate origin (Papers III and IV)

GWAS adjusting for lineage effect (Papers III and IV) In Paper III, we identified 13 genes, four SNPs, and 47 k-mers to be significantly associated with PJI origin (p-value <0.05 after Bonferroni-adjustment). Most of the genes (12/13, 92%) are associated with AMR (i.e., methicillin, aminoglycosides, and macrolide-lincosamides resistance) or decreased susceptibility to chlorhexidine, or are genes present on the MGE harbouring these genes (Table 8, Figure 13). Two genes, group_596 and group_3224, encoded hypothetical proteins of unknown function.

Length PJI Nares Gene Gene ID Protein AMR (bp) MGE n (%) n (%) Penicillin - 113 8 binding mecA pbp protein 2a beta-lactam 2007 SCCmec (81%) (5%) HMG-CoA 108 8 mvaS mvaS_1 synthase 168 SCCmec (78%) (5%) acyl dehy- dratase 113 8 maoC paaZ MaoC 429 SCCmec (81%) (5%) glycerophos- phoryl diester 112 8 phos- ugpQ ugpQ phodiesterase 744 SCCmec (81%) (5%) 98 3 Hypothetical group_3224 protein 1257 SCCmec (71%) (2%) aac(6')- AAC(6')- aminoglyco- 99 1 aph(2'') aacA-aphD APH(2'') side 1440 transposon (71%) (1%) GNAT family 99 1 N-acetyltrans- group_4693 group_4693 ferase 405 transposon (71%) (1%) aminoglyco- 99 1 IS256 group_3861 side 1173 IS (71%) (1%) 76 1 ermC_2 ermC ErmC MLS 735 plasmid (55%) (1%) 76 1 repL group_1688 RepL 477 plasmid (55%) (1%) 97 14 qacA qacA QacA antiseptics 1530 plasmid (70%) (9%) 99 14 qacR qacR QacR 561 plasmid (71%) (9%) 104 1 Hypothetical group_596 protein 456 undetermined (75%) (1%) Table 8. Genes associated with PJI origin in Paper III (GWAS). AMR; antimicrobial resistance (gene associated with), MGE; mobile genetic element.

74 EMELI MÅNSSON Molecular epidemiology of S. epidermidis in PJIs

Figure 13. Phylogenetic relatedness and genomic traits identified in S. epidermidis from PJIs and nasal microbiota in Paper III. S. epidermidis isolates from PJIs (n = 139; light red) and S. epidermidis isolates from nasal swabs from patients scheduled for arthroplasty surgery (n = 150; green). Major PJI lineages (ST2a, ST2b, ST5, and ST215) are coloured in grey. GWAS results are presented in purple (colour intensity indicates the numbers of genes, k-mers, and SNPs present). Genes associated with biofilm formation are presented in blue, from centre and outwards; icaA, aap, bhp, and embp. Genes previously associated with clinical infections are presented in dark red, from centre and outwards: IS256 and sesI. Genes previously associated with colonization are presented in dark green, from centre and outwards: IS256, and sesI. The mid-point rooted phylogeny was based on 95,245 SNPs and the scale-bar indicates substitutions per site.

Three out of four core genome SNPs identified with treeWAS were non- synoymous (altered the amino acid sequence of the protein), and two of these two, i.e., gyrA::S84F/Y and grlB::S80F/Y, have been associated with

EMELI MÅNSSON Molecular epidemiology of S. epidermidis in PJIs 75 decreased susceptibility to fluoroquinolones in S. epidermidis (202). All k- mers were associated with IS256. To validate the GWAS results, the presence of the 13 genes associated with PJI origin were investigated in international S. epidermidis sequences from PJIs (n = 122). Genes associated with SCCmec (mecA, mvaS, maoC, ugpQ, and group_3224) were found to a similar degree in international sequences and in PJI isolates from Örebro/Östergötland, while the proportion of isolates harbouring genes related to aminoglycoside and macrolide-lincosamide resistance and reduced susceptibility towards chlorhexidine was somewhat lower, though the prevalence still significantly higher compared to nasal isolates in Paper III (Table 9, Table 8). It can be speculated that less usage of bone fixation cement (loaded with gentamicin) and less usage of preoperative cleansing with CHG have exerted less selection pressure in internationally for these agents (203), partly explaining the lower proportion of S. epidermidis harbouring genes associated with resistance to/tolerance of these agents.

PJI isolates International PJI in Paper III sequences Gene (n = 139) (n = 122) Pearson Chi-square mecA 113 (81%) 88 (72%) p = 0.0792 mvaS 108 (78%) 75 (62%) p = 0.0043 maoC 113 (81%) 88 (72%) p = 0.0792 ugpQ 112 (81%) 88 (72%) p = 0.1077 group_3224 98 (71%) 80 (66%) p = 0.3935 aac(6')-aph(2'') 99 (71%) 69 (57%) p = 0.0136 group_4693 99 (71%) 69 (57%) p = 0.0136 IS256 99 (71%) 69 (57%) p = 0.0136 ermC 76 (55%) 45 (37%) p = 0.0040 repL 76 (55%) 42 (34%) p = 0.0010 qacA 97 (70%) 60 (49%) p = 0.0007 qacR 99 (71%) 59 (48%) p = 0.0002 group_596 104 (75%) 113 (93%) p = 0.0001

Table 9. Prevalence of genes associated with PJI origin (by GWAS) in S. epidermidis isolates from Örebro/Östergötland and in international S. epidermidis PJI sequences.

76 EMELI MÅNSSON Molecular epidemiology of S. epidermidis in PJIs

In Paper III, AMR was found to be the common trait shared by S. epidermidis that cause PJIs, and no previously described or putative virulence factor was identified by GWAS. However, lineage-specific (virulence) factors important in the pathogenesis of PJI will not be captured by this method. The genes associated with PJIs in Paper III were investigated in MRSE isolates retrieved from sampling of patients before hospitalization for TJA in Paper IV. Genes associated with the SCCmec element were, as expected, identified in all isolates, but genes associated with aminoglycoside resistance were rare among MRSE that did not belong to ST2b, ST5, ST22, and ST215 lineages (Figure 11). The aac(6’)-aph(2’’) gene was only present in 12/52 MRSE strains in samples from 11/30 MRSE-colonized patients, suggesting that gentamicin in bone cement is effective for most MRSE strains that patients harbour in their microbiota before hospitalization, and thus provides supplementary coverage for systemic antimicrobial prophylaxis. IS256 and ermC were also rare among MRSE strains retrieved from selective plating and found in 14/52 MRSE strains. However, the genes encoding two hypothetical proteins, group_596 and group_3224, were strikingly present in 50/52 and 43/52 MRSE strains, but only group_3224 could be associated with the SCCmec element. qacA was present in 28/52 MRSE strains from 19/66 patients.

Genes associated with biofilm formation (Paper III) Gene presence/absence data for icaA, aap, bhp, and embp were analysed across the collection in Paper III. Individual biofilm-associated genes were found to be over-represented in specific PJI-lineages (e.g. all ST2a isolates harboured icaA, and all ST215 isolates harboured embp, Table 10a). icaA was associated with PJI origin (OR 2.9 [1.7–4.7)]) (Table 10b) when gene absence/presence data was analysed without consideration to population effects, but, as presented above, no statistically significant association was found between any biofilm-formation–associated gene and PJI origin in GWAS accounting for population structure. The association between icaA and PJIs was thus confounded by the predominance of ST2 isolates among isolates from PJIs.

EMELI MÅNSSON Molecular epidemiology of S. epidermidis in PJIs 77

PJI isolates Nasal (N = 139) isolates (N = 150)

ST2a ST2b ST5 ST215 other STs (n = 16) (n = 43) (n = 13) (n = 34) (n = 33) icaA, 16 42 0 0 8 36 n (%) (100%) (98%) (24%) (24%) aap/sesF, 15 42 12 0 23 104 n (%) (94% (98%) (92%) (70%) (69%) bhp/sesD, 0 0 13 0 10 27 n (%) (100%) (30%) (18%)

Biofilm formation Biofilm embp, 16 37 13 34 33 149 n (%) (100%) (86%) (100%) (100%) (100%) (99%)

IS256, 16 43 2 34 5 1 n (%) (100%) (100%) (15%) (100%) (15%) (1%) infections

sesI, 16 13 0 34 0 0 Clinical n (%) (100%) (30%) (100%)

fdh, 0 0 0 0 2 14 n (%) (6%) (9%)

ACME-arcA, 0 5 12 0 24 114 Colonization n (%) (12%) (92%) (73%) (76%) Table 10a. Data from Paper III. Genes associated with S. epidermidis biofilm formation, clinical infections, and colonization by origin and major PJI lineages.

78 EMELI MÅNSSON Molecular epidemiology of S. epidermidis in PJIs PJIs Nasal isolates OR* (N = 139) (N = 150) (95% C.I.) Biofilm icaA, n (%) 66 (48%) 36 (24%) 2.9 (1.7–4.7) formation aap/sesF, n (%) 92 (66%) 104 (69%) 0.9 (0.5–1.4) ns bhp/sesD, n (%) 23 (17%) 27 (18%) 0.9 (0.5–1.7) ns embp, n (%) 133 (96%) 149 (99%) 0.1 (0.02–1.3) ns Clinical IS256, n (%) 100 (72%) 1 (1%) 382.1 (51.7–2825.9) infections sesI, n (%) 63 (45%) 0 p < 0.0000** Colonization fdh, n (%) 2 (1%) 14 (9%) 0.1 (0.0–0.6) ACME-arcA, n (%) 41 (30%) 114 (76%) 0.1 (0.1–0.2)

Table 10b. Data from Paper III. Genes associated with S. epidermidis biofilm formation, clinical infection, and colonization presented by origin of isolates. CI, confidence interval; N, total number of isolates within each isolate group; n, number of isolates with gene present; ns, non-significant. * OR for S. epidermidis isolates from PJIs. **Fisher's exact test.

IS256 and sesI (Paper III) In GWAS, IS256 was found to be statistically significantly associated with PJI origin (Table 8), and also without corrections for lineage effects an association between IS256 and PJI origin was found (Table 10b), but as shown in Table 10a, IS256 was rare in isolates in the ST5 lineage. SesI was not identified in GWAS, but found to be highly prevalent in the ST2a and ST215 lineages (Table 10a and 10b).

ACME-arcA and fdh (Paper III) ACME-arcA and fdh have previously been suggested as markers of commensalism in S. epidermidis (69, 123). In Paper III, both were negatively associated with PJI origin (OR 0.1 [0.0–0.6] and OR 0.1 [0.1–0.2] (Table 10b) but the results were found to be highly lineage dependent (Table 10a) and failed to reach statistically significance when the population structure was corrected for in GWAS.

EMELI MÅNSSON Molecular epidemiology of S. epidermidis in PJIs 79 Genes and gene variants associated with antimicrobial resistance (Papers III and IV) As demonstrated by GWAS, S. epidermidis isolates from PJIs harboured genes and gene variants associated with AMR to a significantly greater extent than isolates retrieved from nasal sampling in Paper III (Table 11).

PJI isolates Nasal isolates Antimicrobial category, n (%) (N = 139) (N = 150) OR* (95% CI)

Beta-lactam antibiotics a 113 (81%) 8 (5%) 77.1 (33.6–177.0)

Fusidic acidb 57 (41%) 18 (12%) 5.1 (2.8–9.3)

Macrolides-Lincosamidesc 87 (63%) 22 (15%) 9.7 (5.5–17.2)

Rifampicind 30 (22%) 0 **p < 0.0001

Aminoglycosidese 101 (73%) 2 (1%) 196.7 (46.4–833.7)

Fluoroquinolonesf 114 (82%) 16 (11%) 38.2 (19.4–75.0)

Folate-pathway inhibitorsg 68 (49%) 8 (5%) 17.0 (7.7–37.3)

Multidrug resistant, n (%) 115 (83%) 7 (5%) 97.9 (40.7–235.3)

Table 11. Data from Paper III. Gene and gene variants associated with antimicrobial resistance per antimicrobial category and isolate origin. CI, confidence interval; N, total number of isolates within each isolate group; n, total number of isolates with gene(s) and/or point mutation(s) associated with resistance. * OR for S. epidermidis isolates from PJIs. ** Fisher's exact test. a mecA. b fusA (variant), fusB, fusC. c erm(A), erm(C), lnu(A), mph(C), msr(A), vat(B), vga(A), vga(B). d rpob (variant). e aac(6')-aph(2''), aadD. f gyrA (variant), grlA (variant), grlB (variant). g dfrG, folA (variant). Multidrug resistant defined as presence of genes and/or mutations associated with resistance towards ≥3 antimicrobial categories.

In particular, we noted high rates of genotypic resistance to compounds used for systemic (beta-lactam antibiotics; OR 77.1 [33.6–177.0]) and local (aminoglycosides; OR 196.7 [46.4–833.7]) antimicrobial prophylaxis in PJIs. The qacA gene that encodes an efflux pump that causes decreased susceptibility to quaternary ammonium compounds such as chlorhexidine was identified in 70% (97/139) of isolates from PJIs, versus in 9% (14/150) of isolates from anterior nares (OR 22, 95% C.I. 11.6–43.3). Recently described point mutations in qacA associated with increased tolerance of

80 EMELI MÅNSSON Molecular epidemiology of S. epidermidis in PJIs chlorhexidine (204) were identified in 12/16 ST2a isolates and 14/43 ST2b isolates. Higher rates of resistance towards antimicrobial categories used for treating PJIs were noted among PJI isolates than among isolates from anterior nares in Paper III: rifampicin 30/150 versus 0/150, fluoroquinolones 114/139 versus 16/150, and macrolides-lincosamides 87/139 versus 22/150. The specific dual mutations in rpoB::D471E/I527M, associated not only with rifampicin resistance but also with vancomycin heteroresistance (6) were identified in all 16 ST2a isolates, whereas additional rpoB-associated resistance towards rifampicin was exclusive to other major PJI lineages (i.e., ST2b 4/43, ST5 3/13, and ST215 7/34). No point mutations associated with daptomycin or linezolid resistance were identified in the collection. Among PJI isolates from Västmanland, methicillin resistance (as determined by the presence of mecA) was less common (9/18, 50%) than among PJI isolates in Paper III (p = 0.01, Fisher’s exact test, two-sided). All mecA- positive isolates belonged to the ST2- or ST215-lineages and were also found to be genotypic MDR. Genes encoding aminoglycoside resistance and gene variants associated with fluoroquinolone resistance were only found within isolates belonging to ST2 and ST215 lineages. In MRSE retrieved from nasal and skin microbiota in Paper IV, no mutations associated with rifampicin resistance were found. MDRSE was found in 26 samples from 19/66 patients.

SCCmec diversity (Paper III) The ccr recombinase genes were identified in 67% (194/289) of all isolates sequenced in Paper III, but mecA was frequently absent (89%, 63/71) from the SCC element in isolates from anterior nares, whereas composite elements (i.e., SCCmec carrying two or more ccr gene complexes) where abundant in isolates from PJIs (Figure 15). All isolates in the ST215 lineage carried SCCmec type I(1B), all ST5 isolates carried type IV(2B) or composite variants thereof, and all 15/16 mecA positive ST2a isolates carried type III(3A) or composite varians thereof, whereas multiple SCCmec elements were identified in ST2b isolates: type III(3A), type IV(2B), type V(5C2), and composite variants of thereof (Figure 14).

EMELI MÅNSSON Molecular epidemiology of S. epidermidis in PJIs 81

Figure 14. SCCmec and phylogenetic relationships of S. epidermidis isolates from PJIs (n=139; light red) and S. epidermidis isolates from nasal swabs from patients scheduled for arthroplasty surgery (n = 150; green in Paper III. Major PJI lineages (i.e., ST2a, ST2b, ST5, and ST215) are coloured in grey. SCCmec types are presented in shades of blue, from centre and outwards: I(1B), III(3A), IV(2B), V(5C2), VIII(4A), Composite, and SCC. The midpoint-rooted phylogeny was based on 95,245 SNPs and the scale-bar indicates substitutions per site.

82 EMELI MÅNSSON Molecular epidemiology of S. epidermidis in PJIs

Clinical aspects (Papers I, III and IV)

Is there a marker able to distinguish S. epidermidis isolates with a higher capacity to cause PJIs? As outlined in the introduction, differentiating culture contamination from a true PJI with S. epidermidis can be difficult, so a marker, easily detected by, for example, PCR, would ease clinical decision making. However, this assumes that S. epidermidis differs in terms of virulence between lineages or strains. The predominance of a few lineages in S. epidermidis PJIs, as demonstrated in this thesis, could be taken as indicating that such a difference exists, and during the last year, several studies investigating pathogenicity factors in S. epidermidis have been published. Four of these studies (174, 205-207) will be discussed below in relation to the findings of this thesis. The largest study included 415 S. epidermidis isolates from multiple sources: 141 isolates from healthy carriage obtained in both hospitals and in the community from 11 countries (most were sampled at a UK university), and 274 isolates from clinical infections (mainly PJIs but also other ODRIs, bacteraemia, and colonized catheters linked to infection) (174). Iso- lates from infections were present across the phylogenetic tree, interpreted as reflecting the emergence of infection from multiple genetic backgrounds. GWAS was performed on two datasets (n = 76 each) of paired isolates with different phenotypes (asymptomatic carriage vs. infection) but with high sequence similarity to identify k-mers associated with infection; 636 genes containing infection-associated k-mers were identified. The threshold for significance was set at p = 0.0001, unadjusted for multiple testing. Out of the top 40 genes (ranked according to p-values), nearly half (n = 17) were components of the SCCmec. Phenotypic testing found no difference between isolates representing colonization and infection in terms of biofilm formation or induction of IL-8 production in keratinocytes, but isolates from infections were more often methicillin resistant and displayed reduced cell toxicity. A single k-mer mapping to mecA was the best predictor of infection with a classification accuracy of 75% (174). In Paper III, the accuracy of mecA in predicting PJI origin was even higher (88%), but as demonstrated in Paper IV, colonization with mecA-positive S. epidermidis (plausibly in low relative abundance) is not uncommon in patients scheduled for TJA, and the accuracy of mecA to predict isolate origin (true infection vs contamination by colonising isolate) is likely to be

EMELI MÅNSSON Molecular epidemiology of S. epidermidis in PJIs 83 dependent on the patient population, as previously shown by Rohde et al. (113). A recent study (205) claimed that a marker gene – yxeP, encoding a hy- drolase – can identify isolates belonging to cluster A/C, one of two major S. epidermidis clusters defined by SNPs in core genes. The cluster A/C (known to include ST2) was inferred by phenotypic testing to be of higher pathogenic capacity, and to possibly occupy a different niche in the skin than isolates within the other cluster (B). The findings were based on a collection of 83 isolates, sampled between 1996 and 2001, representing 71 different STs, with a pan-genome of approximately 6700 genes. No differences in resistance to oxacillin was found between clusters A/C and B, but A/C isolates were more often resistant to gentamicin. The authors concluded that yxeP is a marker of cluster A/C that “can improve significantly the prognosis and management of medical-device related infections caused by this bacterium”; this would appear to be a somewhat bold statement, given the limited number of isolates included, and that isolates of clinical origin were found in cluster B. yxeP was not found to be significantly associated with PJI origin in Paper III by GWAS, and presence/absence of yxeP in our collection of S. epidermidis sequences has not been analysed. In a study focusing solely on genetic determinants for PJIs (206), 51 isolates from PJIs were compared with 51 isolates from healthy skin. PJI isolates were collected at a single centre in Mexico during a four-year period, and skin isolates were collected from the arms of healthy individuals that did not work in the hospital. All isolates were subjected to AST, determination of in vitro biofilm formation, and investigated for a set of 14 putative marker genes using PCR. The authors found that PJI isolates were distinguished by presence of icaA, in vitro biofilm formation, and resistance to oxacillin, fluoroquinolones, and gentamicin, whereas carriage isolates were associated with embp, sesA, sesB, sesC, sesD, sesE, sesG, and sesH genes. The association of embp with colonization is in contrast with the findings of Paper III, in which empb was found in all PJI lineages and identified by BLASTN in 133/139 isolates from PJIs. The difference in embp prevalence found in these two studies could be due to different methodologies (i.e., PCR versus BLASTN) and/or to differences in the predominating lineages in PJIs between Mexico and Sweden. The presence of icaA was found to be highly associated with ST2a/b in Paper III, and all PJI isolates that lacked embp (n = 6) were ST2b, suggesting that ST2b might be the predominant lineage in the Mexican study, but as PFGE and not MSLT was performed in that study, this remains a speculation.

84 EMELI MÅNSSON Molecular epidemiology of S. epidermidis in PJIs

In the last of the four studies aiming to identify genetic traits associated with S. epidermidis infections, comparative genomic analyses of 198 publicly available S. epidermidis sequences (207) were performed, finding no enrichment of genes that could distinguish blood cultures isolates from skin isolates. Whether isolates with metadata indicating “blood culture” were representatives of true infections or were mixed with contaminating isolates retrieved from blood cultures cannot be assessed, and the study by Su et al. (207) exemplifies the difficulties of extrapolating findings when data on case definitions and sampling procedures are missing. The associations between different markers and specific genetic backgrounds/lineages noted in Paper III highlights the importance of the relative abundance of STs/lineages in a study collection when genetic traits are associated with isolate origin (clinical versus colonization), emphasizing that population structure needs to be taken into account. For example, if isolates are selected based on resistance to rifampicin, an ST2-weighted collection is likely to be the result, as the dominant genetic determinant of rifampicin resistance in S. epidermidis, the dual rpoB::D471E/I527M mutations (6), is primarily found in ST2a isolates (Paper III). Likewise, if isolates are selected to achieve an even distribution of STs (205), this will skew the collection from the actual proportions of STs found in clinical infections and may also result in spurious associations. Furthermore, as noted in Paper III, the great diversity among nasal isolates sampled from what is, from an international perspective, a small area, and from patients of more or less similar age, as well as the within-host diversity of MRSE noted in Paper IV, suggest that to capture the true diversity of colonizing S. epidermidis isolates in comparative genomic studies, very large isolate collections are probably needed. In general, stricter adherence to the Strengthening the Reporting of Molecular Epidemiology for Infectious Diseases (STROME-ID) statement (45) could improve future studies in this field, and ease the extrapolation of results to other settings.

Or are all S. epidermidis isolates equally fit to cause PJIs? The overrepresentation of MDRSE in PJIs could also be regarded as illus- trating the principle that “opportunity makes a thief”: all S. epidermidis isolates may be of almost equal virulence, but their pathogenicity could differ due to host factors. The finding of a (limited) number of isolates lacking all genetic traits associated with PJIs, but still isolated from a PJI, in paper III supports the view of S. epidermidis as a truly accidental pathogen (98). This would mean that isolates lacking resistance genes only rarely get a

EMELI MÅNSSON Molecular epidemiology of S. epidermidis in PJIs 85 chance to establish a PJIs as they generally succumb to the prophylaxis measures: preoperative whole-body cleansing with CHG-containing soap, systemic antimicrobial prophylaxis with cloxacillin, and, in some cases, gentamicin admixed into bone fixation cement. The antimicrobial resistance profile of isolates from PJIs would, according to this theory, be the end result of selection by current prophylaxis regimens, and the predominance of certain lineages would be due to the acquisition of AMR genes rather than to increased virulence per se.

Can the proportion of MDRSE in S. epidermidis PJIs reflect adherence to prophylaxis regimens? If all S. epidermidis are able to cause PJIs, centres with a high incidence of S. epidermidis PJIs due to suboptimal adherence to prophylaxis regimens would be expected to have a lower relative abundance of MDRSE. The number of MDRSE PJIs as a proportion of all S. epidermidis PJIs could thus potentially be a proxy for adherence to prophylaxis guidelines that could be monitored, in addition to the total incidence of PJIs (which is influenced by the case-mix). However, also the relative proportion of MDRSE PJIs could reflect the case-mix: younger patients might harbour relatively less MDRSE in their microbiota (Paper IV), there may be a lower density of MDRSE in dedicated elective orthopaedic surgery wards due to a lower selection pressure from antibiotics (208); and it could be speculated that fewer patients may harbour MDRSE at the time of the surgery in hospitals admitting patients the day of planned arthroplasty, as transmission of MDRSE between patients via colonized or contaminated health care workers has been suggested (90) and carriage rate of MDR microorganisms (but not specifically MDRSE) has been found to increase within eight hours of admission to hospital (209). Centre-specific incidence rates of PJIs are reported by Swedish national joint arthroplasty registries, but these registries do not capture data on causative microorganisms.

Is preoperative whole-body cleansing with chlorhexidine driving the rate of MDRSE PJIs? It has been proposed that it might be time to discuss not only antibiotic but also biocide stewardship, as high prevalence of qacA/B (78–85%), associated with increased tolerance towards chlorhexidine, has been found in globally distributed MDR ST2 lineages (210). This is in line with our findings in Paper III, where the prevalences of qacA in PJI-associated lineages

86 EMELI MÅNSSON Molecular epidemiology of S. epidermidis in PJIs were: ST2a 75%, ST2b 93%, ST5 54%, and ST215 68%, whereas qacA was only found in 9% of methicillin-sensitive nasal isolates. In MRSE retrieved from patients before admittance to hospital for TJA, we found qacA to be present in 28/52 MRSE strains from 19/66 patients. Importantly, 8 out of 10 patients colonized with PJI-associated lineages were colonized with isolates harbouring qacA. It can be speculated that the relative abundance of MRSE might increase after pre-operative whole-body cleansing with CHG in patients colonized with qacA positive MRSE. If so, this could imply greater risk of peri-operative contamination of the wound, and subsequently the prosthetic joint, with S. epidermidis resistant to the systemic antimicrobial prophylaxis. Cleansing with CHG could also potentially increase the risk of acquisition of MDRSE from sources within the hospital, though this too remains to be demonstrated, and balanced against the likely beneficial effect against the other major pathogen in PJIs, S. aureus, although the evidence base for whole-body cleansing with CHG is limited (211). To summarize, the relative proportion of MDRSE in PJIs might be affected by the use of preoperative whole-body cleansing with CHG-containing soap, but the overall effect on PJI incidence may still be beneficial. In their analysis of MDR ST2 sequences, Zamudio et al. (210) also noted that the ST2-BPH0662 lineage (corresponding to ST2a) carried a composite SCCmec element composed of SCCmec type III and a copper and mercury resistance mobile element (COMER)-like locus orthologous to the SCCmec associated with COMER in community-associated MRSA USA300. In COMER-positive S. aureus, decreased susceptibility to copper has been linked to intracellular survival within macrophages (212), and Zamudio et al. (210) suggested that a similar increased resistance to innate immunity might be associated with carriage of SCCmec in association with metal resistance genes in MDRSE as well. In Paper III, 15/16 mecA-positive ST2a isolates carried SCCmec type III or composite variants thereof, but whether a COMER-like locus is present remains to be investigated. The nature of the hypothetical protein encoded by group_3224, associated with SCCmec, and identified by GWAS to be associated with PJI origin is also of interest in this matter. We have published two studies (213, 214) indicating that decreased host inflammatory response might contribute to the predominance of the ST2- and ST215 lineages in PJIs, but both host- and isolate-dependent differences were noted to be significant, and further studies in this field are needed.

EMELI MÅNSSON Molecular epidemiology of S. epidermidis in PJIs 87

Finally, gene variants associated with mupirocin resistance were found to be common in the global MDRSE lineages ST23 (56%) and ST2-BPH0662 (i.e., ST2a, 48%) (210). In contrast, Salih et al. (215) found that both PJI and nasal S. epidermidis isolates were generally susceptible to mupirocin (215), which could reflect the lower use of mupirocin in Sweden than in settings with higher rates of MRSA where mupirocin is used to eradicate MRSA. Two strains found to be mupirocin resistant in the study by Salih et al. (one PJI isolate and one nasal isolate) were sequenced within Paper III. Both were found to be ST218, but the genetic determinant(s) of mupirocin resistance has not been investigated.

Should the current antimicrobial prophylaxis regimens in TJA be adapted to cover for MDRSE? Treatment outcomes for patients with MRSE and aminoglycoside-resistant S. epidermidis PJIs are reportedly worse than those with susceptible S. epidermidis. In a study of 74 chronic hip- and knee staphylococcal PJIs treated with two-stage exchange, the vast majority (11/15, 73%) of patients who did not achieve clinical resolution of infection were patients with MRSE (Figure 15) (216).

Figure 15. Treatment outcome for 74 patients treated for hip- and knee prosthetic joint infection with 2-stage exchange procedure. The proportion of patients free of infection after ≥2 years of follow up was significantly lower for PJIs due to methicillin-resistant S. epidermidis (MRSE) compared to methicillin-susceptible S. aureus (MSSA) and S. epidermidis (MSSE) (p=0.027* and p=0.002**, respectively). (Free of infection was defined as no signs of infection, CRP<10 mg/dL, after ≥2 years of follow up.) Reprinted from (216) with permission.

88 EMELI MÅNSSON Molecular epidemiology of S. epidermidis in PJIs

Likewise, in a study of patients with different types of S. epidermidis ODRIs, genes associated with the SCCmec and qacA, were associated with a “not-cured” clinical outcome, as was phenotypic resistance towards aminoglycosides and biofilm formation (217). Genes associated with the SCC- mec and qacA were associated PJI origin in Paper III and found to be highly prevalent in the ST2a, ST2b, ST5, and ST215 lineages. It can therefore be argued that preventive strategies should take the risk of treatment failures in MDRSE PJIs into account, and that prophylaxis measures be adapted to cover MDRSE. Use of the glycopeptide vancomycin (effective against methicillin-resistant staphylococci) has been found to be inferior to use of a beta-lactam antibiotic as antimicrobial prophylaxis in TJA (218), but dual-agent antibiotic prophylaxis with vancomycin in combination with a beta-lactam (cefazolin) has been associated with reduced incidence of PJI after TJA (219), and in particular with lower incidence of methicillin-resistant microorganisms in PJIs (220). An alternative route to broader coverage of systemically administered antimicrobial prophylaxis would be to exchange gentamicin in bone cement with an antimicrobial agent to which MDRSE-lineages are generally susceptible. Based on in vitro studies, antibiotics admixed into bone polymethyl methacrylate (PMMA) cement are expected to continue to be eluted from the cement to various total extents and for various duration, but with significant drop of concentration noted after the first day (221), and could thus potentially offer protection against contamination of the prosthetic joint with S. epidermidis PJIs in the period immediately after surgery when tissue levels of systemically administered antimicrobial prophylaxis have dropped below MIC. Commercial formulations of antibiotic loaded bone PMMA cement have been found to release more antibiotics than do manually mixed prepara- tions, but are only available with vancomycin, clindamycin, tobramycin, and gentamicin (222). In paper III, most PJI isolates demonstrated vancomycin MICs at 2 mg/mL, clindamycin resistance was found in 59% of isolates, and resistance to gentamicin in 70% of isolates. Alternative agents are linezolid, that in vitro studies has been found to be more efficacious than vancomycin against S. epidermidis in PMMA cement, and the lipopeptide antibiotic daptomycin, that has also been found to be bioactive against S. epidermidis when admixed into bone cement (222). Also ceftaroline, a fifth- generation cephalosporin, could be of interest as an antimicrobial prophylactic agent in TJA. Ceftaroline has been found to be highly active against S. epidermidis isolated from clinical infections, including MRSE from PJIs

EMELI MÅNSSON Molecular epidemiology of S. epidermidis in PJIs 89

(223, 224), and in an in vitro study, ceftaroline was found to elute from PMMA cement and inhibit bacterial growth (of MRSA) without significantly weakening the biomechanical properties (225). However, a clinical breakpoint for ceftaroline for S. epidermidis has not been established (but based on in vitro data a breakpoint similar to that of S. aureus has been suggested as appropriate (224)), and there has been no clinical trial of ceftaroline, linezolid or daptomycin as prophylactic agents in TJA, neither administered locally nor systemically (clinicaltrials.gov, a clinical trial [NCT01196169] of daptomycin for intravenous antimicrobial prophylaxis in MRSA-colonized patients undergoing TJA was terminated due to slow rate of enrolment). To summarize, adjusting current antimicrobial prophylaxis regimens to include coverage for MDRSE is feasible, but as TJA is a high-volume surgery with over 30,000 procedures performed each year in Sweden alone, and as MDRSE PJIs are rare, the potential down-sides of broader antimicrobial prophylaxis in terms of further selection of resistance, side-effects, and costs must be considered. Preoperative identification of patients at a significantly higher risk of MDRSE PJI would enable targeted use of a combination of systemic antibiotics or an alternative agent to gentamicin in cemented procedures. However, the experience from Paper IV is that screening for MDRSE using culture-based techniques is labourious and, as such, associated with high costs.

What is the origin of S. epidermidis causing PJIs: selection from patients’ pre-hospital admission microbiota or nosocomial transmission? The relative sequence abundance of S. epidermidis in nasal samples has been shown to increase after antibiotic surgical prophylaxis with flucloxacillin and gentamicin (226). This could result from the selection of MDRSE already present in patients’ pre-hospital admission microbiota (by growth advantage), or from acquisition of hospital-adapted lineages from sources within the hospital environment, or both (Figure 16). In Paper IV, we investigated the former hypothesis and found that a subset of patients is colonized with MDRSE lineages associated with PJIs before admission to hospital, but we did not retrieve any isolates belonging to the ST2a lineage nor any rifampicin-resistant isolates. We have collected samples to investigate the second hypothesis, and, based on findings from metagenomic sequencing of the diversity and complexity of S. epidermidis communities in human microbiota (76, 78) and our experience from selective

90 EMELI MÅNSSON Molecular epidemiology of S. epidermidis in PJIs culturing (Paper IV) and standard culturing (Paper III), we believe that a targeted sequencing approach, enabling measurement of both relative and absolute abundance, is probably the best choice for investigating the possible in-hospital transmission of PJI-associated MDRSE-lineages.

Figure 16. Two hypotheses: MDRSE lineages predominant in PJIs (red) are selected from pre-hospital admission microbiota, low-relative-abundance populations by the prophylactic regimens, i.e., whole-body cleansing with chlorhexidine gluconate-containing soap and antimicrobial prophylaxis (systemic and local), and/or are acquired from sources in the hospital environment, i.e., health care workers and contact surfaces). Illustration by Tobias Flygar.

To address this, our collaborators at Statens Serum Institut, Copenhagen, are working to develop a targeted sequencing method – the “Epidome” – (227). At present, in-hospital transmission of PJI-associated lineages of S. epidermidis to patients undergoing TJA can neither be confirmed nor disproved.

EMELI MÅNSSON Molecular epidemiology of S. epidermidis in PJIs 91 Limitations

Paper I The main limitation in Paper I is the limited number of procedures during which air sampling was performed, which means that intraoperative transmission of ST2 and ST215 could be neither verified, nor disproved. Another limitation is that no patient data were collected and follow-up of patients thus impossible.

Paper III Limitations in Paper III are as follows: only limited patient data was collected and PJI diagnosis thus not confirmed in medical records; pre-admission nasal isolates were not from the same patients who had a S. epidermidis PJIs; and only a single nasal S. epidermidis colony was included from each of 150 patients (due to high diversity, a collection of a larger number of colonizing isolates, possibly from different body areas, would have strength- ened the study).

Paper IV Limitations in Paper IV are the size of the study population (n = 66), and the selection of patients with previously identified growth of S. epidermidis in nasal samples cultured on standard medium, as well as that no data on previous admissions to hospital or stay in long-term care facilities were collected. Furthermore, the colonization rate of MRSE might have been under- estimated for the following reasons: i) MRSE might have been outgrown by other species and/or by MSSE in the first culture on standard medium; ii) use of a relatively small sample volume (10 µL + 10 µL) of the frozen bacterial suspensions for selective culturing; iii) the chosen cefoxitin concentration (5 mg/mL) in the supplemented plates was based on expert opinion (Bo Söderquist and Robert Skov) and no tests were performed with plates of different cefoxitin concentrations; and iv) sampling was restricted to five CoNS colonies per sample.

92 EMELI MÅNSSON Molecular epidemiology of S. epidermidis in PJIs

Genomic relatedness of S. pettenkoferi isolates of different origins (Paper II)

Study collection Nine S. pettenkoferi isolates retrieved from intraoperative air sampling during one TKA and one THA were included in the analysis together with the reference strain CCUG 51270T and 16 S. pettenkoferi isolates from blood cultures, of which 11/13 were deemed as probable contaminants (defined as only one positive blood culture bottle; no data for three isolates). Species identification was performed with MALDI-TOF MS and verified by rpoB-sequencing.

Repetitive sequenced-based PCR typing A dendrogram and scatter plot showed two major clades, clade A (n = 7) and clade B (n = 11) (Figure 17). Three isolates (i.e., Vaxjo_3, Vaxjo_8, and Vaxjo_5) clustered together in a possible third clade, whereas the remaining four isolates were scattered. The reference strain CCUG 51270T was found in clade A together with isolates representing both probable blood culture contaminants as well as isolates retrieved from intra-operative air sampling. Based on the results of repetitive-sequence–based PCR typing, genomic differences between isolates in clades A and B were substantial, with the similarity estimated at ≈ 55% (Figure 17).

EMELI MÅNSSON Molecular epidemiology of S. epidermidis in PJIs 93

Fig. 1(b) Fig. 1(a)

a) b) Key P Isolate ID Source Gel-like image SCATTERPLOT. Gridline spacing: 5 % similarity. Source: Air 1 1 Vasteras 17:2 A A BC Blood culture RF Ref. strain 2 1 Vasteras 17:1 A

CLADE A CLADE 26 3 8 CCUG51270 RS 9 4 3 JMI 16 BC 5 3 JMI 15 BC 14 6 4 Vaxjo 9* BC 7 4 Vaxjo 6 BC 13 8 9 Vaxjo 2 BC 12 9 10 Vasteras 18:1 A 11 10 10 12 Vaxjo 3 BC 11 11 Vaxjo 8 BC 25 12 13 Vaxjo 5 BC 23 22 16 13 14 Vaxjo 12 BC 21 7 14 15 Vaxjo 13 BC 20 6 15 5 Vaxjo 1 BC 15 5 16 5 Vaxjo 11 BC 24 19 18 17 4 1 2 3

17 6 Vasteras 17:5 A Clade B Clade A

18 6 Vasteras 17:3 A B CLADE 8 19 16 Vaxjo 4 BC 20 7 Vasteras 17:6 A 21 7 Vasteras 17:7 A 22 7 Vasteras 17:8 A 23 7 Vaxjo 10 BC 24 17 Vasteras 17:4 A 25 18 Orebro 14* BC 26 19 Vaxjo 7 BC

50 60 70 80 90 100 % similarity Figure 17. Dendrogram a) and scatterplot b) showing repetitive-sequenced–based PCR typing of n = 26 S. pettenkoferi isolates of different origins. Source is isolate orgin; A = intraoperative air sampling (blue dot in scatter plot), RS = reference strain (pink), BC = blood cultures (green). Isolates marked with * were retrieved from more than one blood culture bottle.

Phylogenetic relationships The genomic relatedness of S. pettenkoferi isolates of different origin was verified by analysing the phylogenetic relationships inferred from SNPs in the core genome after the WGS of all isolates (Figure 18). Clades A and B differed by >58,000 SNPs, whereas the intra-clade diversity was <2000 SNPs and <700 SNPs, respectively. The environmental isolate Vast- eras_18:1, with a unique rep-PCR fingerprinting pattern, differed from isolates in clades A and B by a minimum of 85,000 SNPs. The overall resem- blance to the reference chromosome NZ_JVVL00000000.1 (strain 1286_SHAE) was ≈87%.

94 EMELI MÅNSSON Molecular epidemiology of S. epidermidis in PJIs

Figure 18. Phylogenetic relationships of S. pettenkoferi isolates of different origins based on 157,438 core genome SNPs. Scale bare indicates SNP distances.

Methicillin resistance and presence of mecA Three isolates from blood cultures were cefoxitin resistant (zone diameter <22 mm) and mecA was detected by PCR (and WGS) in two of these isolates (Table 12). None of the six additional S. pettenkoferi isolates with a cefoxitin zone diameter of <25mm (the break point for S. epidermidis) harboured mecA, indicating that the current clinical breakpoint for cefoxitin (22mm) is valid and distinguishes mecA positive S. pettenkoferi isolates (Table 12).

EMELI MÅNSSON Molecular epidemiology of S. epidermidis in PJIs 95

Isolate ID Cefoxitin (mm) mecA Vaxjo_1 19 0 Vaxjo_2 30 0 Vaxjo_3 30 0 Vaxjo_4 26 0 Vaxjo_5 30 0 Vaxjo_6 6 1 Vaxjo_7 27 0 Vaxjo_8 28 0 Vaxjo_9 6 1 Vaxjo_10 23 0 Vaxjo_11 22 0 Vaxjo_12 32 0 Vaxjo_13 26 0 Orebro_14 n.d. 0 JMI_15 23 0 JMI_16 25 0 Vasteras_17:1 31 0 Vasteras_17:2 29 0 Vasteras_17:3 25 0 Vasteras_17:4 25 0 Vasteras_17:5 24 0 Vasteras_17:6 27 0 Vasteras_17:7 25 0 Vasteras_17:8 23 0 Vasteras_18:1 25 0

Table 12. Cefoxitin zone diameters (mm) determined by disk diffusion testing and mecA presence/absence for the 25 S. pettenkoferi isolates sequenced in Paper II.

96 EMELI MÅNSSON Molecular epidemiology of S. epidermidis in PJIs

Prediction of pathogenicity The assembled genomes of S. pettenkoferi isolates sequenced within Paper II were investigated for genes coding for proteins associated with pathogenicity by PathogenFinder 1.1, using the model created for Firmicutes (unpublished data). For comparison two S. epidermidis isolates from PJIs (representing the ST2a and ST215 lineages) were also investigated by PathogenFinder. All S. pettenkoferi isolates were classified as probable human pathogens (probability 0.872–0.954, Table 13). The total number of identified genes were similar between S. pettenkoferi genomes and S. epidermidis genomes, but the average number of matched S. pettenkoferi genes (matched to pathogenic and non-pathogenic families; the proteome coverage) was lower for S. pettenkoferi genomes. A sequence with 96.82% identity to S. aureus glycosyl transferase group 1 family protein (protein ID AAW38701) was identified in 10/11 genomes in clade B, but not in any other S. pettenkoferi genome.

Table 13. Prediction of pathogenicity based on identified protein sequences within S. pettenkoferi genomes sequenced within Paper II. A = pathogen probability, B = proteome coverage, C = matched pathogenic families, D = matched non-pathogenic families.

EMELI MÅNSSON Molecular epidemiology of S. epidermidis in PJIs 97

Digital DNA:DNA hybridization The clustering yielded 17 species clusters (Figure 19, this thesis). All isolates within clade A clustered with the type strain S. pettenkoferi CCUG 51720T (included in the analysis by TYGS based on the 16S rDNA gene similarity as outlined in the “Materials and methods” section). Isolate Vasteras_18_1 was defined as a unique species cluster not represented in the TYGS database, and the remaining S. pettenkoferi isolates were defined as a second unique species cluster not represented in the TYGS database, with isolates within clade B representing a subspecies cluster.

Figure 19. Midpoint-rooted tree inferred with FastME v2.1.6.1 from GBDP distances calculated from genome sequences. The branch lengths are scaled in terms of GBDP distance formula d5.

The tree inferred from GBDP distances calculated from 16S rDNA gene sequences data demonstrates that species identification based on 16S rDNA gene sequence (extracted from sequencing data) of S. pettenkoferi, and the two suggested staphylococcal species that hitherto are unrepresented in the TYGS database, is troublesome (Figure 20).

98 EMELI MÅNSSON Molecular epidemiology of S. epidermidis in PJIs

Figure 20. Midpoint-rooted tree inferred with FastME v2.1.6.1 from GBDP distances calculated from 16S rDNA gene sequences. The branch lengths are scaled in terms of GBDP distance formula d5.

BLAST of the rpoB sequence of the proposed species “S. pseudolugdunensis” The dDDH results suggested that isolates in clade B in Paper II are representatives of a separate species that is currently not represented in the type strain database. Likewise, the dDDH results suggested that isolate Vast- eras_18_1 is a separate hitherto unrepresented species in the database. In Trülzsch et al.’s description of the novel species S. pettenkoferi (34), one of the strains that was originally proposed to represent S. pettenkoferi (32) (strain A6664) was not included due to differences in the results of physiological and chemotaxonomic investigations, and DNA-DNA hybridization data, but this strain displayed identical 16S rRNA sequence with the S. pettenkoferi strains and 99.2% similarity to the partial rpoB sequence (equivalent to 4 SNVs in the 485 bp fragment). Twelve CoNS isolates that were found to be positive for pyrrolidonyl arylamidase(PYR)/ornithine decarboxylase (ODC) (a test used to discriminate the CoNS species S. lugdunensis in the era before MALDI-TOF MS

EMELI MÅNSSON Molecular epidemiology of S. epidermidis in PJIs 99 was introduced in clinical practice) but was different to S. lugdunensis according to 16S rRNA and tuf sequence analysis were characterised in 2008 and proposed to be a novel species with the suggested name “S. pseudolugdunensis” (228). The full 16S rRNA sequence was closely (99.94% sequence similarity) related to that of S. pettenkoferi. The 16S rRNA and tuf sequences, but not rpoB sequence, of the proposed species “S. pseudolugdunensis” were deposited in the GenBank database (228). This proposed species “S. pseudolugdunensis” was included in recent study investigating the performance of the 16S–23S rRNA region to assign staphylococcal species from short-read sequencing data in comparison with Sanger sequencing of the 16S rRNA, rpoB, sodA, and tuf genes (229). In this study, S. pettenkoferi could not be discriminated from “S. pseudolugdunensis” by sequencing of the 16S rRNA gene or the tuf gene. S. pettenkoferi was found to differ from “S. pseudolugdunensis” with 4 nucleotides in the sodA sequence and 13 nucleotides in the rpoB sequence. A high sequence similarity (99.8% sequence similarity, a seven-nucleotide difference) was found between S. pettenkoferi and “S. pseudolugdunensis” in the >4000-bp-long 16S–23S rRNA region (229). By nucleotide BLAST(230) (https://blast.ncbi.nlm.nih.gov/), an identical sequence (100% hit, 100% identity) to the 838 bp rpoB sequence from “S. pseudolugdunensis” (accession number MF679125) was found within isolates belonging to cluster B in Paper IV (this thesis). Likewise, a 100% hit with 99.05% identity to the rpoB sequence from “S. pseudolugdunensis” was found in the representative genome NZ_CP022096.2 deposited in FDA-ARGOs, a quality-controlled public database of reference genomes (231). In comparison, the 838 bp rpoB sequence from S. pettenkoferi (accession MF679122) was identified to 98.45% identity in isolates belonging to cluster B (13 nucleotide difference), and to 98.45% identity in the representative S. pettenkoferi draft genome NZ_CP022096.2. To summarize, isolates in clade B, assigned to S. pettenkoferi by MALDI- TOF MS and by partial sequencing of the rpoB gene in Paper II are potentially representatives of the proposed staphylococcal species “S. pseudolugdunensis”, as could potentially be the case for a number of publicly available sequences currently deposited as S. pettenkoferi. It is possible that S. pettenkoferi and the proposed species “S. pseudolugdunensis” can be discriminated by the phenotypic test ODC.

100 EMELI MÅNSSON Molecular epidemiology of S. epidermidis in PJIs

Clinical aspects The clinical significance of S. pettenkoferi (and of “S. pseudolugdunensis”) is likely limited. All S. pettenkoferi (n = 7) isolates in a single-centre retrospective study in Germany of the clinical significance of non-S. epidermidis CoNS (31) retrieved from blood cultures over 4.5 years were considered contaminants. However, an outbreak of linezolid-resistant S. pettenkoferi has been reported in a French intensive care unit (41), and a daptomycin-resistant S. pettenkoferi isolate has been reported from a bacteremic patient in Polen (232), suggesting that S. pettenkoferi can harbour resistance traits, and thus potentially act as a reservoir for antibiotic resistance traits that can spread to more pathogenic staphylococcal species (233). The finding of S. pettenkoferi in the operating field air during joint arthroplasty (Paper II) suggested a presence in human microbiota that was verified in Paper IV, where we found presumably methicillin-resistant S. pettenkoferi (able to grow on cefoxitin-supplemented plates) in pre-admission samples from 11/66 patients. A higher rate of S. pettenkoferi nasal carriage was previously reported from a non-culture–based study in which S. pettenkoferi (in low relative abundance) was identified in the nasal microbiome of 7/18 patients at admission to hospital (226). This is in contrast to a culture-based study (using non-selective medium) in which S. pettenkoferi was only retrieved from nasal samples from 1/34 patients (234). An association between S. pettenkoferi carriage and contact with cats could be hypothesised based on the species repeatedly being reported to be associated with cats: isolated from a cat cage (44); the oral microbiota of cats (235); and from the peritoneal fluid of a cat with peritonitis (236). S. pettenkoferi was retrieved from culturing the airborne dust in an urban home in a study of concentrations of staphylococcal species in indoor air (237), but no data on the presence of domestic animals was presented in the study, and neither do we know whether any of the patients from whom S. pettenkoferi were retrieved in Paper IV are cat owners.

Limitations Closely related S. pettenkoferi isolates identified in air samples from the same operation are likely multiple isolates of the same S. pettenkoferi strain. Assembled genomes (i.e., FASTA files) were uploaded to the online tools PathogenFinder and TYGS, and the data were interpreted following the sites’ instructions. The data are thus preliminary, yet interesting, and merit

EMELI MÅNSSON Molecular epidemiology of S. epidermidis in PJIs 101 confirmation through further phenotypic and genotypic characterization of the isolates.

102 EMELI MÅNSSON Molecular epidemiology of S. epidermidis in PJIs

Conclusions

• S. epidermidis PJIs in Region Örebro County and Region Östergöt- land were dominated by MDRSE ST2a, ST2b, ST5, and ST215 lineages, whereas isolates from the nares of patients scheduled for TJA were genetically diverse (Paper III). • Analysis of the genomic relatedness of S. epidermidis based on SNPs in the core genome identified distinct S. epidermidis lineages comprising isolates of several MLSTs, and ST2 was found within more than one distinct lineage (Paper III). S. epidermidis MLST may thus be suboptimal for surveillance of the molecular epidemiology of S. epidermidis in PJIs. • Genetic traits associated with antimicrobial resistance and tolerance of chlorhexidine gluconate distinguished S. epidermidis from PJIs from nasal isolates retrieved from cultures on standard medium (Paper III). New successful MDRSE lineages may arise by horizontal gene transfer of these traits to new genetic backgrounds. • No putative virulence factor was identified in GWAS, and so selection by antimicrobial prophylaxis was found to be the likely explanation for the success of MDRSE lineages in PJIs (Paper III). • Using selective media, a substantial proportion of patients scheduled for TJA were found to be colonized with genotypic MRSE before admission to hospital, plausibly in low relative abundance (Pa- per IV). A subset of these patients was colonized with MDRSE lineages that were found to predominate in S. epidermidis PJIs in Paper III (Paper IV). These patients may have a higher risk of S. epidermidis PJI. • S. epidermidis ST2, ST5, and ST215 were not found in the air of the operating field during arthroplasty surgery (Paper I). Airborne transmission of these PJI-associated STs of S. epidermidis during surgery could thus not be verified (Paper I). S. epidermidis isolates retrieved from air sampling were generally susceptible to the systemic antimicrobial prophylaxis (cloxacillin) and to the antibiotic that is admixed into bone fixation cement (gentamicin) (Paper I).

EMELI MÅNSSON Molecular epidemiology of S. epidermidis in PJIs 103

• Analysis of the genomic relatedness of isolates identified as S. pettenkoferi by MALDI-TOF showed two distinct clades and a single isolate that was distant (Paper II). Further genomic analysis within this thesis suggests that two hitherto unrecognized staphylococcal species are misidentified as S. pettenkoferi by MALDI-TOF. This could potentially be of clinical significance when the the numbers of positive samples (i.e., blood cultures or biopsies) are used in in- terpreting of the likelihood of clinical relevance.

104 EMELI MÅNSSON Molecular epidemiology of S. epidermidis in PJIs

Future perspectives The incidence of S. epidermidis PJIs is low, but for the individual patient the end result of a PJI can be devastating. To optimize preventive measures, we need to identify patients at higher risk of MDRSE PJIs, and achieve insights into how MDRSE colonization might affect this risk. The first objective calls for a high-coverage, optimized nationwide quality registry for PJIs. Based on their divergent clinical presentations, it is reasonable to expect the risk factors for species such as S. aureus and S. epidermidis PJIs to both overlap and be species specific, but no study identifying patients at higher risk of S. epidermidis PJIs was found during the liter- ature search conducted for thesis project. Likewise, there is a need for species-specific incidence data: a two-to-three-fold higher than expected number of cases was noted when comparing the number of S. epidermidis isolates from PJIs identified in a 10-year period in Region Örebro County and Region Östergötland, with the crude estimates based on available data. The SKAR and SHAR are quality registries with high coverage of all THAs and TKAs performed in Sweden, and a PJI registry linked to these, combining data on surgical procedures, clinical functional outcome, antibiotic prescription/use, and microbiology reports, would have enormous potential for clinical research. Infectious disease physicians and orthopaedic surgeons work together in multidisciplinary teams to offer the best care to PJI patients. A new joint (!) registry should preferably be designed to support clinical decision making during the course of treatment, by enabling visualization of the often complicated course of the multiple procedures performed, the multiple cultures obtained, and the different antibiotics prescribed (like the successful HIV and hepatitis registries in Sweden). If patients at higher risk for MDRSE PJIs could be characterised, the next step would be to investigate colonization with MDRSE within this group. As outlined in the previous chapter, a promising sequencing-based method (the Epidome) has been developed with the potential to describe changes in the relative and absolute abundance of different lineages of S. epidermidis during a time-course. Briefly, Epidome uses two primers to amplify the genes yycH and g216, and the amplicons are then sequenced using short-read technology. This could enable a high enough discriminatory capacity to study differences in pre-admission S. epidermidis communities between patients at presumed higher risk for MDRSE and other TJA patients, and to study how S. epidermidis communities may change during the course of hospitalization

EMELI MÅNSSON Molecular epidemiology of S. epidermidis in PJIs 105 for TJA. Furthermore, changes in S. epidermidis communities over time in relation to whether patients are admitted directly to the operating department or admitted the day before surgery, or between patients admitted to centres dedicated to planned procedures or to orthopaedic wards with both elective and acute surgery, could also be investigated. If patients are found to acquire S. epidermidis lineages not present in the pre-admission microbiome during hospitalization for TJA, studies investigating MDRSE colonization in health-care workers and on contact surfaces would be called for. Finally, to me, mecA represents the most promising factor to be used in a clinical setting to infer the probability of true infection in single positive cultures obtained during revision for presumed PJI or assumed aseptic loosening. It would be interesting to use data from a national registry as did Milandt et al. (137), to study whether patients with MRSE retrieved in single positive cultures (interpreted as contamination in the clinical context) are more likely to later be revised for infection than patients with MSSE. However, the performance of mecA as a predictor of true infection is likely to be affected by the patient’s previous exposure to healthcare, as the abundance of MRSE in the microbiome is likely to increase during hospitalization.

106 EMELI MÅNSSON Molecular epidemiology of S. epidermidis in PJIs

Populärvetenskaplig sammanfattning Risken att drabbas av en ledprotesinfektion är liten (ca 1%), men eftersom det totala antalet patienter som får en ny protesled ökar år från år, ökar också antalet patienter som drabbas av en ledprotesinfektion. Dessa patienter behöver ofta genomgå förnyad operation där hela eller delar av ledprotesen byts ut, och behandlas med en kombination av olika antibiotikasorter under en längre tid. Det funktionella utfallet efter en ledprotesinfektion kan bli bra, men det finns också en risk för kvarstående försämrad rörelseförmåga och smärta. Förebyggande arbete för att förhindra att patienter drabbas av en infektion efter en ledprotesoperation är därför viktigt. En betydande andel av alla infektioner i höft- och knäprotesleder orsakas av Staphylococcus epidermidis bakterier. Staphylococcus epidermidis (förkortas S. epidermidis) är vanligt före- kommande på vår hud och våra slemhinnor, vilket vi har nytta av då S. epidermidis tex deltar i kroppens försvar mot mer aggressiva bakterier, sam- spelar med vårt immunförsvar i reglering av inflammation och tom har as- socierats med lägre risk för en form av hudcancer. S. epidermidis är bakterier som i regel inte orsakar sjukdom hos friska, men som kan orsaka infektioner i anslutning till kroppsfrämmande material som tex katetrar, me- kaniska hjärtklaffar eller ledproteser, och hos individer med nedsatt immun- försvar, tex efter cellgiftsbehandling. Inom arten S. epidermidis kan man genetiskt särskilja olika linjer (”lineages”), sekvenstyper (ST), och stammar. Den genetiska variationen hos S. epidermidis i normalfloran är stor; flera olika stammar återfinns samtidigt på ett litet hudområde, olika stammar förekommer i olika omfattning på olika kroppsdelar, och i olika omfattning mellan individer, och länder. Variationen i genetisk likhet hos S. epidermidis som orsakar infektioner är däremot mindre, och det har tidigare visats att ledprotesinfektioner huvudsakligen orsakas av tre sekvenstyper; ST2, ST5 och ST215. I studie I undersökte vi om sekvenstyper av S. epidermidis som är vanligt förekommande i ledprotesinfektioner återfinns i luften på operationssalen under ledproteskirurgi. Med hjälp av en speciell apparat samlade vi in luft och isolerade bakterier som fanns i luften. Under mer än hälften av alla operationer återfanns S. epidermidis i luften, men dessa utgjordes inte av de sekvenstyper som är vanliga vid ledprotesinfektion. Det antibiotika som patienter får för att förhindra infektion (profylax) vid ledprotesoperation var effektivt mot nästan alla S. epidermidis som återfanns i luften.

EMELI MÅNSSON Molecular epidemiology of S. epidermidis in PJIs 107

I luften i operationsområdet identifierade vi en annan, betydligt mer ovanlig, stafylokockart – Staphylococcus pettenkoferi. I studie II karaktäri- serade vi S. pettenkoferi bakterier som återfanns i luften i studie I och S. pettenkoferi bakterier från blododlingar, genom att kartlägga den genetiska koden i de olika stammarnas kromosom (bakterier har en enda cirkulär kromosom). Med denna metod (helgenomsekvensering, på engelska whole- genome sequencing, WGS) visade vi att S. pettenkoferi av olika ursprung var nära besläktade, men utgjordes av två större delvis skilda grupper av isolat. Senare analys antyder att en av dessa grupper kan utgöras av en annan, hittills inte officiellt erkänd, stafylokockart. I det tredje delarbetet använde vi WGS för att karaktärisera S. epidermidis från höft- och knäledprotesinfektioner, och jämföra dessa med S. epidermidis som vi identifierat i näsprov från patienter som skulle genomgå ledproteskirurgi. Vi såg att isolat från ledprotesinfektioner huvudsakligen tillhörde fyra olika linjer, medan isolat från näsprov var betydligt mer heterogena. Genetiska drag (“traits”, inkluderar gener, kortare DNA-se- kvenser och punktmutationer) som är kopplade till motståndskraft (re- sistens) mot antibiotika och nedsatt känslighet för klorhexidin (vilket an- vänds för helkroppstvätt inför ledprotesoperation för att minska mängden bakterier på huden) var vanligare hos S. epidermidis från ledprotesinfektioner än från S. epidermidis från näsprov. Ingen annan gemensam faktor som förklarar ökad sjukdomsframkallande förmåga (virulens) hos S. epidermidis som orsakar ledprotesinfektion kunde identifieras, och vår tolk- ning av resultaten är att de flesta (kanske rent av alla) S. epidermidis sano- likt har förmågan att orsaka infektion i anslutning till en ledprotes. I det sista delarbetet undersökte vi om de linjer av S. epidermidis som var överrepresenterade bland isolat från ledprotesinfektioner i studie III åter- finns i normalfloran hos patienter som ska genomgå ledproteskirurgi. Vi odlade prov från näsöppning, ljumske och knä/höft på agarplattor som främjar bakterier som är motståndskraftiga (resistenta) mot antibiotika. Vi visade att uppemot hälften av alla patienter bär på S. epidermidis bakterier som är motståndskraftiga mot det antibiotika som används för att före- bygga ledprotesinfektion, och att en andel av dessa patienter bär på linjer av S. epidermidis som är överrepresenterade i ledprotesinfektioner. Sammanfattningsvis kan överrepresentation av vissa linjer av S. epidermidis i ledprotesinfektioner förklaras av att dessa linjer har förvärvat mot- ståndskraft mot det antibiotika som används som profylax, och mot klorhexidin som används för att minska mängden bakterier på huden inför ki- rurgi. Framtida studier behövs för att undersöka om patienter som bär på

108 EMELI MÅNSSON Molecular epidemiology of S. epidermidis in PJIs

S. epidermidis som är motståndskraftiga mot antibiotika löper ökad risk att drabbas av ledprotesinfektion med S. epidermidis, samt om/hur normalfloran förändras under sjukhusvistelse i samband med ledprotesoperation, och om S. epidermidis som är motståndskraftiga mot antibiotika riskerar att överföras till patienter från sjukhusmiljön under vårdtiden.

EMELI MÅNSSON Molecular epidemiology of S. epidermidis in PJIs 109

Acknowledgments No woman is an island, and research is truly a team effort. I want to express my profound gratitude to the following:

Bo Söderquist, main supervisor, master of staphylococci, and the recipient of quite possibly thousands of emails from my account over these years – on those few occasions when you were unable to provide a quick response, I started texting you instead. Sorry about that. I’m truly grateful for your patience with my impatience, and for all off-work hours you spent on this thesis project when you could have been tasting wine instead ;-).

Martin Sundquist, when you signed on to be co-supervisor, I was happy to have the rising star of Swedish microbiology on board, and by now you are its chair. Thank you for always being truly supportive, for giving very useful hands-on practical advice in the laboratory, and for the honest proofread- ing.

Åsa Nilsdotter-Augustinsson, co-supervisor, always greeting with a warm smile. This last year your workload has been crazy, but I’m sure the decen- tralized medical programme in Norrköping will be a great success with you at the steering wheel. Thank you for enabling this thesis project by year after year collecting S. epidermidis isolates from PJIs in Region Östergöt- land.

Eva Särndahl, co-supervisor, Berolla Sahdo, co-author, and Isak Demirel, co-author – you introduced me to the fascinating field of immunology and I respect your profound knowledge of and ability to navigate that field. The NLRP3 inflammasome and I were not a perfect match, but I really appreci- ate the work you put in and the experience I gained.

Marc Stegger, co-author – working with you has been an absolute pleasure. When we first met I knew almost nothing about bacterial genomics and sequencing, and most of what I know today I owe to you. Hold on to your God of Thunder, Thor Bech Johannesen, co-author, because he is your way to success (but you know that). Thanks also to Paul Skytt Andersen, co- author, Amalie Rendboe, Søren Iversen, Sharmin Baig, and all the others involved at the Department of Bacteria, Parasites and Fungi, Statens Serum Institut, Copenhagen.

110 EMELI MÅNSSON Molecular epidemiology of S. epidermidis in PJIs

Bengt Hellmark co-author, a true pedagogue, for teaching me the basics of microbiological culturing (over and over again), and all your hard work with the samples and isolates included in this thesis. Ellionor Rapp for kind assistance with MALDI-TOF MS. Susanne Jacobsson for excellent help with the DNA extraction of isolates in Paper III. All the staff at the Depart- ment of Clinical Microbiology, Örebro University Hospital – I know I used up a lot of matrix …

Staffan Tevell, co-author – sharing is caring. Thank you for making it easy to share supervisors and research field during our years as research students. I look forward to future collaboration.

Christer Häggström, for air sampling in Paper I, everyone at the Department of Clinical Microbiology in Västerås involved in shipping samples to Öre- bro, and in particular Camilla Svensson for help identifying S. epidermidis isolates from PJIs in 2012–2013.

Thomas Ekblom and Anna-Lena Lindgren at the Department of Orthopae- dics, Västerås – thank you for the superb co-operation at the outpatient clinic for PJI patients, and for your help with sampling patients in the colonization study. And no, the results are still not finalized, but yes, I will present the data when we have them. A big thank you also to all involved in sampling of patients in the colonization study in Region Värmland, Region Östergötland, and Region Örebro County.

Tina Carlander, for scientific support in its widest definition, whenever needed (which was a lot), and for your access to you know what, which has tremendously expanded the size of my Endnote library. Honestly, I don’t think this thesis would have been completed without your support when I needed it the most.

Albin Månsson, for great assistance with figures and posters.

Centre for Clinical Research in Region Västmanland, for generous financial support. A special thank you to the current and former unit heads, Kent Nilsson and Mats Enlund, and to the superb trio Mariana Pettersson, Maria Persson, and Maria Dell’Uva Karlsson.

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Infektionskliniken Västerås. It might not look like much from the outside, but inside it is pure gold. Research is important for the patients of tomor- row, but the work you all put in, around the clock, every day of the year, is what matters to the patients of today. I look forward to spending more time with you again. Thank you to the present and former department heads, Cherin Kamil and Tomas Vikerfors, for the opportunity to combine research with clinical work.

All our friends in Västerås, who besides bringing joy into our lives, have also made the super-advanced logistics of three kids’ spare-time activities doable in combination with two parents working (more than) full time.

My dearest Anna-Karin and Nina, for always being there.

Inga-Britt and Bengt, Johanna and Mattias, for your love and support.

Mamma, your attitude to life, in which there is a way around all potential obstacles – I try to live by. Pappa, you beat me to it and finished your book first, but I think it might be a tie in terms of numbers of readers ;-). Jon, Albin, and Klara, I cherish you enormously.

♥Daniel, you’re even more intelligent, funny, and good-looking today than you were when we first met more than 20 years ago. Thank you for making me a better me. ♥Gustav, ♥Svante, and ♥Thure, I love you from the bottom of my heart.

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229. Kosecka-Strojek M, Sabat AJ, Akkerboom V, Becker K, van Zanten E, Wisselink G, et al. Development and validation of a reference data set for assigning Staphylococcus species based on next-generation Sequencing of the 16S-23S rRNA Region. Front Cell Infect Microbiol. 2019;9:278. 230. Zhang Z, Schwartz S, Wagner L, Miller W. A greedy algorithm for aligning DNA sequences. J Comput Biol. 2000;7(1-2):203-14. 231. Sichtig H, Minogue T, Yan Y, Stefan C, Hall A, Tallon L, et al. FDA- ARGOS is a database with public quality-controlled reference genomes for diagnostic use and regulatory science. Nat Commun. 2019;10(1):3313. 232. Savini V, Kosecka M, Siegwart E, Marrollo R, Polilli E, Palmieri D, et al. Daptomycin-resistant Staphylococcus pettenkoferi of human origin. Acta Biochim Pol. 2016;63(2):297-301. 233. Heilmann C, Ziebuhr W, Becker K. Are coagulase-negative staphylococci virulent? Clin Microbiol Infect. 2018. 234. Kaspar U, Kriegeskorte A, Schubert T, Peters G, Rudack C, Pieper DH, et al. The culturome of the human nose habitats reveals individual bacterial fingerprint patterns. Environ Microbiol. 2016;18(7):2130-42. 235. Rossi CC, da Silva Dias I, Muniz IM, Lilenbaum W, Giambiagi- deMarval M. The oral microbiota of domestic cats harbors a wide variety of Staphylococcus species with zoonotic potential. Vet Microbiol. 2017;201:136-40. 236. Dutta TK, Chakraborty S, Das M, Mandakini R, Vanrahmlimphuii, Roychoudhury P, et al. Multidrug-resistant Staphylococcus pettenkoferi isolated from cat in India. Vet World. 2018;11(10):1380-4. 237. Madsen AM, Moslehi-Jenabian S, Islam MZ, Frankel M, Spilak M, Frederiksen MW. Concentrations of Staphylococcus species in indoor air as associated with other bacteria, season, relative humidity, air change rate, and S. aureus-positive occupants. Environ Res. 2018;160:282-91.

EMELI MÅNSSON Molecular epidemiology of S. epidermidis in PJIs 137

Publications in the series Örebro Studies in Medicine

1. Bergemalm, Per-Olof (2004). Audiologic and cognitive long-term sequelae from closed head injury. 2. Jansson, Kjell (2004). Intraperitoneal Microdialysis. Technique and Results. 3. Windahl, Torgny (2004). Clinical aspects of laser treatment of lichen sclerosus and squamous cell carcinoma of the penis. 4. Carlsson, Per-Inge (2004). Hearing impairment and deafness. Genetic and environmental factors – interactions – consequences. A clinical audiological approach. 5. Wågsäter, Dick (2005). CXCL16 and CD137 in Atherosclerosis. 6. Jatta, Ken (2006). Inflammation in Atherosclerosis. 7. Dreifaldt, Ann Charlotte (2006). Epidemiological Aspects on Malignant Diseases in Childhood. 8. Jurstrand, Margaretha (2006). Detection of Chlamydia trachomatis and Mycoplasma genitalium by genetic and serological methods. 9. Norén, Torbjörn (2006). Clostridium difficile, epidemiology and antibiotic resistance. 10. Anderzén Carlsson, Agneta (2007). Children with Cancer – Focusing on their Fear and on how their Fear is Handled. 11. Ocaya, Pauline (2007). Retinoid metabolism and signalling in vascular smooth muscle cells. 12. Nilsson, Andreas (2008). Physical activity assessed by accelerometry in children. 13. Eliasson, Henrik (2008). Tularemia – epidemiological, clinical and diagnostic aspects. 14. Walldén, Jakob (2008). The influence of opioids on gastric function: experimental and clinical studies. 15. Andrén, Ove (2008). Natural history and prognostic factors in localized prostate cancer. 16. Svantesson, Mia (2008). Postpone death? Nurse-physician perspectives and ethics rounds. 17. Björk, Tabita (2008). Measuring Eating Disorder Outcome – Definitions, dropouts and patients’ perspectives. 18. Ahlsson, Anders (2008). Atrial Fibrillation in Cardiac Surgery. 19. Parihar, Vishal Singh (2008). Human Listeriosis – Sources and Routes. 20. Berglund, Carolina (2008). Molecular Epidemiology of Methicillin- Resistant Staphylococcus aureus. Epidemiological aspects of MRSA and the dissemination in the community and in hospitals. 21. Nilsagård, Ylva (2008). Walking ability, balance and accidental falls in persons with Multiple Sclerosis. 22. Johansson, Ann-Christin (2008). Psychosocial factors in patients with lumbar disc herniation: Enhancing postoperative outcome by the identification of predictive factors and optimised physiotherapy. 23. Larsson, Matz (2008). Secondary exposure to inhaled tobacco products. 24. Hahn-Strömberg, Victoria (2008). Cell adhesion proteins in different invasive patterns of colon carcinoma: A morphometric and molecular genetic study. 25. Böttiger, Anna (2008). Genetic Variation in the Folate Receptor-α and Methylenetetrahydrofolate Reductase Genes as Determinants of Plasma Homocysteine Concentrations. 26. Andersson, Gunnel (2009). Urinary incontinence. Prevalence, treatment seeking behaviour, experiences and perceptions among persons with and without urinary leakage. 27. Elfström, Peter (2009). Associated disorders in celiac disease. 28. Skårberg, Kurt (2009). Anabolic-androgenic steroid users in treatment: Social background, drug use patterns and criminality. 29. de Man Lapidoth, Joakim (2009). Binge Eating and Obesity Treatment – Prevalence, Measurement and Long-term Outcome. 30. Vumma, Ravi (2009). Functional Characterization of Tyrosine and Tryptophan Transport in Fibroblasts from Healthy Controls, Patients with Schizophrenia and Bipolar Disorder. 31. Jacobsson, Susanne (2009). Characterisation of Neisseria meningitidis from a virulence and immunogenic perspective that includes variations in novel vaccine antigens. 32. Allvin, Renée (2009). Postoperative Recovery. Development of a Multi-Dimensional Questionnaire for Assessment of Recovery. 33. Hagnelius, Nils-Olof (2009). Vascular Mechanisms in Dementia with Special Reference to Folate and Fibrinolysis. 34. Duberg, Ann-Sofi (2009).Hepatitis C virus infection. A nationwide study of assiciated morbidity and mortality. 35. Söderqvist, Fredrik (2009). Health symptoms and potential effects on the blood-brain and blood-cerebrospinal fluid barriers associated with use of wireless telephones. 36. Neander, Kerstin (2009). Indispensable Interaction. Parents’ perspectives on parent–child interaction interventions and beneficial meetings. 37. Ekwall, Eva (2009). Women’s Experiences of Gynecological Cancer and Interaction with the Health Care System through Different Phases of the Disease. 38. Thulin Hedberg, Sara (2009). Antibiotic susceptibility and resistance in Neisseria meningitidis – phenotypic and genotypic characteristics. 39. Hammer, Ann (2010). Forced use on arm function after stroke. Clinically rated and self-reported outcome and measurement during the sub-acute phase. 40. Westman, Anders (2010). Musculoskeletal pain in primary health care: A biopsychosocial perspective for assessment and treatment. 41. Gustafsson, Sanna Aila (2010). The importance of being thin – Perceived expectations from self and others and the effect on self-evaluation in girls with disordered eating. 42. Johansson, Bengt (2010). Long-term outcome research on PDR brachytherapy with focus on breast, base of tongue and lip cancer. 43. Tina, Elisabet (2010). Biological markers in breast cancer and acute leukaemia with focus on drug resistance. 44. Overmeer, Thomas (2010). Implementing psychosocial factors in physical therapy treatment for patients with musculoskeletal pain in primary care. 45. Prenkert, Malin (2010). On mechanisms of drug resistance in acute myloid leukemia. 46. de Leon, Alex (2010). Effects of Anesthesia on Esophageal Sphincters in Obese Patients. 47. Josefson, Anna (2010). Nickel allergy and hand eczema – epidemiological aspects. 48. Almon, Ricardo (2010). Lactase Persistence and Lactase Non- Persistence. Prevalence, influence on body fat, body height, and relation to the metabolic syndrome. 49. Ohlin, Andreas (2010). Aspects on early diagnosis of neonatal sepsis. 50. Oliynyk, Igor (2010). Advances in Pharmacological Treatment of Cystic Fibrosis. 51. Franzén, Karin (2011). Interventions for Urinary Incontinence in Women. Survey and effects on population and patient level. 52. Loiske, Karin (2011). Echocardiographic measurements of the heart. With focus on the right ventricle. 53. Hellmark, Bengt (2011). Genotypic and phenotypic characterisation of Staphylococcus epidermidis isolated from prosthetic joint infections. 54. Eriksson Crommert, Martin (2011). On the role of transversus abdominis in trunk motor control. 55. Ahlstrand, Rebecca (2011). Effects of Anesthesia on Esophageal Sphincters. 56. Holländare, Fredrik (2011). Managing Depression via the Internet – self-report measures, treatment & relapse prevention. 57. Johansson, Jessica (2011). Amino Acid Transport and Receptor Binding Properties in Neuropsychiatric Disorders using the Fibroblast Cell Model. 58. Vidlund, Mårten (2011). Glutamate for Metabolic Intervention in Coronary Surgery with special reference to the GLUTAMICS-trial. 59. Zakrisson, Ann-Britt (2011). Management of patients with Chronic Obstructive Pulmonary Disease in Primary Health Care. A study of a nurse-led multidisciplinary programme of pulmonary rehabilitation. 60. Lindgren, Rickard (2011). Aspects of anastomotic leakage, anorectal function and defunctioning stoma in Low Anterior Resection of the rectum for cancer. 61. Karlsson, Christina (2011). Biomarkers in non-small cell lung carcinoma. Methodological aspects and influence of gender, histology and smoking habits on estrogen receptor and epidermal growth factor family receptor signalling. 62. Varelogianni, Georgia (2011). Chloride Transport and Inflammation in Cystic Fibrosis Airways. 63. Makdoumi, Karim (2011). Ultraviolet Light A (UVA) Photoactivation of Riboflavin as a Potential Therapy for Infectious Keratitis. 64. Nordin Olsson, Inger (2012). Rational drug treatment in the elderly: ”To treat or not to treat”. 65. Fadl, Helena (2012). Gestational diabetes mellitus in Sweden: screening, outcomes, and consequences. 66. Essving, Per (2012). Local Infiltration Analgesia in Knee Arthroplasty. 67. Thuresson, Marie (2012). The Initial Phase of an Acute Coronary Syndrome. Symptoms, patients’ response to symptoms and opportunity to reduce time to seek care and to increase ambulance use. 68. Mårild, Karl (2012). Risk Factors and Associated Disorders of Celiac Disease. 69. Fant, Federica (2012). Optimization of the Perioperative Anaesthetic Care for Prostate Cancer Surgery. Clinical studies on Pain, Stress Response and Immunomodulation. 70. Almroth, Henrik (2012). Atrial Fibrillation: Inflammatory and pharmacological studies. 71. Elmabsout, Ali Ateia (2012). CYP26B1 as regulator of retinoic acid in vascular cells and atherosclerotic lesions. 72. Stenberg, Reidun (2012). Dietary antibodies and gluten related seromarkers in children and young adults with cerebral palsy. 73. Skeppner, Elisabeth (2012). Penile Carcinoma: From First Symptom to Sexual Function and Life Satisfaction. Following Organ-Sparing Laser Treatment. 74. Carlsson, Jessica (2012). Identification of miRNA expression profiles for diagnosis and prognosis of prostate cancer. 75. Gustavsson, Anders (2012): Therapy in Inflammatory Bowel Disease. 76. Paulson Karlsson, Gunilla (2012): Anorexia nervosa – treatment expectations, outcome and satisfaction. 77. Larzon, Thomas (2012): Aspects of endovascular treatment of abdominal aortic aneurysms. 78. Magnusson, Niklas (2012): Postoperative aspects of inguinal hernia surgery – pain and recurrences. 79. Khalili, Payam (2012): Risk factors for cardiovascular events and incident hospital-treated diabetes in the population. 80. Gabrielson, Marike (2013): The mitochondrial protein SLC25A43 and its possible role in HER2-positive breast cancer. 81. Falck, Eva (2013): Genomic and genetic alterations in endometrial adenocarcinoma. 82. Svensson, Maria A (2013): Assessing the ERG rearrangement for clinical use in patients with prostate cancer. 83. Lönn, Johanna (2013): The role of periodontitis and hepatocyte growth factor in systemic inflammation. 84. Kumawat, Ashok Kumar (2013): Adaptive Immune Responses in the Intestinal Mucosa of Microscopic Colitis Patients. 85. Nordenskjöld, Axel (2013): Electroconvulsive therapy for depression. 86. Davidsson, Sabina (2013): Infection induced chronic inflammation and its association with prostate cancer initiation and progression. 87. Johansson, Benny (2013): No touch vein harvesting technique in coronary by-pass surgery. Impact on patency rate, development of atherosclerosis, left ventricular function and clinical outcome during 16 years follow-up. 88. Sahdo, Berolla (2013): Inflammasomes: defense guardians in host-microbe interactions. 89. Hörer, Tal (2013): Early detection of major surgical postoperative complications evaluated by microdialysis. 90. Malakkaran Lindqvist, Breezy (2013): Biological signature of HER2- positive breast cancer. 91. Lidén, Mats (2013): The stack mode review of volumetric datasets – applications for urinary stone disease. 92. Emilsson, Louise (2013): Cardiac Complications in Celiac Disease. 93. Dreifaldt, Mats (2013): Conduits in coronary artery bypass grafting surgery: Saphenous vein, radial and internal thoracic arteries. 94. Perniola, Andrea (2013): A new technique for postoperative pain management with local anaesthetic after abdominal hysterectomy. 95. Ahlstrand, Erik (2013): Coagulase-negative Staphylococci in Hematological Malignancy. 96. Sundh, Josefin (2013):Quality of life, mortality and exacerbations in COPD. 97. Skoog, Per (2013): On the metabolic consequences of abdominal compartment syndrome. 98. Palmetun Ekbäck, Maria (2013): Hirsutism and Quality of Life with Aspects on Social Support, Anxiety and Depression. 99. Hussain, Rashida (2013): Cell Responses in Infected and Cystic Fibrosis Respiratory Epithelium. 100. Farkas, Sanja (2014): DNA methylation in the placenta and in cancer with special reference to folate transporting genes. 101. Jildenstål, Pether (2014): Influence of depth of anaesthesia on postoperative cognitive dysfunction (POCD) and inflammatory marker. 102. Söderström, Ulf (2014): Type 1 diabetes in children with non-Swedish background – epidemiology and clinical outcome 103. Wilhelmsson Göstas, Mona (2014): Psychotherapy patients in mental health care: Attachment styles, interpersonal problems and therapy experiences 104. Jarl, Gustav (2014): The Orthotics and Prosthetics Users´ Survey: Translation and validity evidence for the Swedish version 105. Demirel, Isak (2014): Uropathogenic Escherichia coli, multidrug- resistance and induction of host defense mechanisms 106. Mohseni, Shahin (2014): The role of ß-blockade and anticoagulation therapy in traumatic brain injury 107. Bašić, Vladimir T. (2014): Molecular mechanisms mediating development of pulmonary cachexia in COPD 108. Kirrander, Peter (2014): Penile Cancer: Studies on Prognostic Factors 109. Törös, Bianca (2014): Genome-based characterization of Neisseria meningitidis with focus on the emergent serogroup Y disease 110. von Beckerath, Mathias (2014): Photodynamic therapy in the Head and Neck 111. Waldenborg, Micael (2014): Echocardiographic measurements at Takotsubo cardiomyopathy - transient left ventricular dysfunction. 112. Lillsunde Larsson, Gabriella (2014): Characterization of HPV-induced vaginal and vulvar carcinoma. 113. Palm, Eleonor (2015): Inflammatory responses of gingival fibroblasts in the interaction with the periodontal pathogen Porphyromonas gingivlis. 114. Sundin, Johanna (2015): Microbe-Host Interactions in Post-infectious Irritable Bowel Syndrome. 115. Olsson, Lovisa (2015): Subjective well-being in old age and its association with biochemical and genetic biomarkers and with physical activity. 116. Klarström Engström, Kristin (2015): Platelets as immune cells in sensing bacterial infection. 117. Landström, Fredrik (2015): Curative Electrochemotherapy in the Head and Neck Area. 118. Jurcevic, Sanja (2015): MicroRNA expression profiling in endometrial adenocarcinoma. 119. Savilampi, Johanna (2015): Effects of Remifentanil on Esophageal Sphincters and Swallowing Function. 120. Pelto-Piri, Veikko (2015): Ethical considerations in psychiatric inpatient care. The ethical landscape in everyday practice as described by staff. 121. Athlin, Simon (2015): Detection of Polysaccharides and Polysaccharide Antibodies in Pneumococcal Pneumonia. 122. Evert, Jasmine (2015): Molecular Studies of Radiotheray and Chemotherapy in Colorectal Cancer. 123. Göthlin-Eremo, Anna (2015): Biological profiles of endocrine breast cancer. 124. Malm, Kerstin (2015): Diagnostic strategies for blood borne infections in Sweden. 125. Kumakech, Edward (2015): Human Immunodeficiency Virus (HIV), Human Papillomavirus (HPV) and Cervical Cancer Prevention in Uganda: Prevalence, Risk factors, Benefits and Challenges of Post- Exposure Prophylaxis, Screening Integration and Vaccination. 126. Thunborg, Charlotta (2015): Exploring dementia care dyads’ person transfer situations from a behavioral medicine perspective in physiotherapy. Development of an assessmement scale. 127. Zhang, Boxi (2015): Modulaton of gene expression in human aortic smooth muscle cells by Porphyromonas gingivalis - a possible association between periodontitis and atherosclerosis. 128. Nyberg, Jan (2015): On implant integration in irradiated bone: - clinical and experimental studies. 129. Brocki, Barbara C. (2015): Physiotherapy interventions and outcomes following lung cancer surgery. 130. Ulfenborg, Benjamin (2016): Bioinformatics tools for discovery and evaluation of biomarkers. Applications in clinical assessment of cancer. 131. Lindström, Caisa (2016): Burnout in parents of chronically ill children. 132. Günaltay, Sezin (2016): Dysregulated Mucosal Immune Responses in Microscopic Colitis Patients. 133. Koskela von Sydow, Anita (2016): Regulation of fibroblast activity by keratinocytes, TGF-β and IL-1α –studies in two- and three dimensional in vitro models. 134. Kozlowski, Piotr (2016): Prognostic factors, treatment and outcome in adult acute lymphoblastic leukemia. Population-based studies in Sweden. 135. Darvish, Bijan (2016): Post-Dural Puncture Headache in Obstetrics. Audiological, Clinical and Epidemiological studies. 136. Sahlberg Bang, Charlotte (2016): Carbon monoxide and nitric oxide as antimicrobial agents – focus on ESBL-producing uropathogenic E. coli. 137. Alshamari, Muhammed (2016): Low-dose computed tomography of the abdomen and lumbar spine. 138. Jayaprakash, Kartheyaene (2016): Monocyte and Neutrophil Inflammatory Responses to the Periodontopathogen Porphyromonas gingivalis. 139. Elwin Marie (2016): Description and measurement of sensory symptoms in autism spectrum. 140. Östlund Lagerström, Lina (2016): ”The gut matters” - an interdisciplinary approach to health and gut function in older adults. 141. Zhulina, Yaroslava (2016): Crohn’s disease; aspects of epidemiology, clinical course, and fecal calprotectin. 142. Nordenskjöld, Anna (2016): Unrecognized myocardial infarction and cardiac biochemical markers in patients with stable coronary artery disease. 143. Floodeen, Hannah (2016): Defunctioning stoma in low anterior resection of the rectum for cancer: Aspects of stoma reversal, anastomotic leakage, anorectal function, and cost-effectiveness. 144. Duberg, Anna (2016): Dance Intervention for Adolescent Girls with Inter- nalizing Problems. Effects and Experiences. 145. Samano, Ninos (2016): No-Touch Saphenous Veins in Coronary Artery Bypass Grafting. Long-term Angiographic, Surgical, and Clinical Aspects. 146. Rönnberg, Ann-Kristin (2016): Gestational Weight Gain. Implications of an Antenatal Lifestyle Intervention. 147. Erik Stenberg (2016): Preventing complications in bariatric surgery. 148. Humble, Mats B. (2016): Obsessive-compulsive disorder, serotonin and oxytocin: treatment response and side effects. 149. Asfaw Idosa, Berhane (2016): Inflammasome Polymorphisms and the Inflammatory Response to Bacterial Infections. 150. Sagerfors, Marcus (2016): Total wrist arthroplasty. A clinical, radiographic and biomechanical investigation. 151. Nakka, Sravya Sowdamini (2016): Development of novel tools for prevention and diagnosis of Porphyromonas gingivalis infection and periodontitis. 152. Jorstig, Stina (2016): On the assessment of right ventricular function using cardiac magnetic resonance imaging and echocardiography. 153. Logotheti, Marianthi (2016): Integration of Functional Genomics and Data Mining Methodologies in the Study of Bipolar Disorder and Schizophrenia. 154. Paramel Varghese, Geena (2017): Innate Immunity in Human Atherosclerosis and Myocardial Infarction: Role of CARD8 and NLRP3. 155. Melinder, Carren Anyango (2017): Physical and psychological characteristics in adolescence and risk of gastrointestinal disease in adulthood. 156. Bergh, Cecilia (2017): Life-course influences on occurrence and outcome for stroke and coronary heart disease. 157. Olsson, Emma (2017): Promoting Health in Premature Infants – with special focus on skin-to-skin contact and development of valid pain assessment. 158. Rasmussen, Gunlög (2017): Staphylococcus aureus bacteremia, molecular epidemiology and host immune response. 159. Bohr Mordhorst, Louise (2017): Predictive and prognostic factors in cervical carcinomas treated with (chemo-) radiotherapy. 160. Wickbom, Anna (2017): Epidemiological aspects of Microscopic Colitis. 161. Cajander, Sara (2017): Dynamics of Human Leukocyte Antigen – D Related expression in bacteremic sepsis. 162. Zetterlund, Christina (2017): Visual, musculoskeletal and balance symptoms in people with visual impairments. 163. Sundelin, Heléne E.K. (2017): Comorbidity and Complications in Neurological Diseases. 164. Wijk, Lena (2017): Enhanced Recovery After Hysterectomy. 165. Wanjura, Viktor (2017): Register-based studies on cholecystectomy. Quality of life after cholecystec-tomy, and cholecystectomy incidence and complications after gastric bypass. 166. Kuchálik, Ján (2017): Postoperative pain, inflammation and functional recovery after total hip arthroplasty. Prospective, randomized, clinical studies. 167. Ander, Fredrik (2017): Perioperative complications in obese patients. A thesis on risk reducing strategies. 168. Isaksson, Helena (2017): Clinical studies of RNA as a prognostic and diagnostic marker for disease. 169. Fengsrud, Espen (2017): Atrial Fibrillation: Endoscopic ablation and Postoperative studies. 170. Amcoff, Karin (2018): Serological and faecal biomarkers in inflammatory bowel disease. 171. Kennedy, Beatrice (2018): Childhood bereavment, stress resilience, and cancer risk: an integrated register-based approach. 172. Andersson, Karin (2018): Metal artifacts in Computed Tomography- impact of reduction methods on image quality and radiotherapy treatment planning. 173. Calais, Fredrik (2018): Coronary artery disease and prognosis in relation to cardiovascular risk factors, interventional techniques and systemic atherosclerosis. 174. Meehan, Adrian (2018): Lithium-associated hyperparathyroidism: Prevalence, Pathophysiology, Management. 175. Björkenheim, Anna (2018): Catheter ablation for atrial fibrillation – effects on rhythm, symptoms and health-related quality of life. 176. Andersson, Tommy (2018): Atrial fibrillation and cause of death, sex differences in mortality, and anticoagulation treatment in low-risk patients. 177. Christos Karefylakis (2018): Vitamin D and its role in obesity and other associated conditions. 178. Eriksson, Carl (2018): Epidemiological and therapeutic aspects of inflammatory bowel disease. 179. Arinell, Karin (2018): Immobilization as a risk factor for arterial and venous thrombosis. 180. Ganda Mall, John-Peter (2018): Non-digestible Polysaccharides and Intestinal Barrier Function - specific focus on its efficacy in elderly and patients with Crohn’s disease. 181. Wickberg, Åsa (2018): Adjuvant treatments to prevent local recurrence after breast-conserving surgery for early breast cancer – radiation, endocrine- or brachytherapy. 182. Dahlberg, Karuna (2018): e-Assessed follow-up of postoperative recovery – development, evaluation and patient experiences. 183. Ziegler, Ingrid (2018): Quantitative detection of bacterial DNA in whole blood in bloodstream infection. 184. Carling, Anna (2018): Impaired balance and fall risk in people with multiple sclerosis. 185. Hildén, Karin (2018): Gestational diabetes, obesity and pregnancy outcomes in Sweden. 186. Björkman Hjalmarsson, Louise (2018): Aspects of neonatal septicaemia – prevention and complications. 187. Lindstedt, Katarina (2019): A life put on hold – Inside and outside perspectives on illness, treatment, and recovery in adolescents with restrictive eating disorders. 188. Röckert Tjernberg, Anna (2019): Celiac Disease and Infections. 189. Göransson, Carina (2019): Developing and evaluating an interactive app to support self-care among older persons receiving home care. 190. Jerlström, Tomas (2019): Clinical Aspects of Cystectomy and Urinary Diversion. 191. Ugge, Henrik (2019): Inflammation and prostate carcinogenesis: influence of immune characteristics and early adulthood exposure to inflammatory conditions on prostate cancer risk. 192. Jonsson, Marcus (2019): Physiotherapy and physical activity in patients undergoing cardiac or lung cancer surgery. 193. Göras, Camilla (2019): Open the door to complexity – safety climate and work processes in the operating room. 194. Ahl, Aline Rebecka Irene (2019): The Association Between Beta- Blockade and Clinical Outcomes in the Context of Surgical and Traumatic Stress. 195. Kardeby, Caroline (2019): Studies of platelet signalling and endothe- lial cell responses using unique synthetic drugs. 196. Sundin, Per-Ola (2019): A life-course approach to chronic kidney disease – risks and consequences. 197. Wennberg, Pär (2019): Pain management in older persons with hip fractures. 198. Fischer, Per (2019): Hemi and total wrist arthroplasty. 199. Sadeghi, Mitra (2019): Resuscitative endovascular balloon occlusion of the aorta; Physiology and clinical aspects of an emerging technique. 200. Tevell, Staffan (2019): Staphylococcal prosthetic joint infections: similar, but still different. 201. Fernberg, Ulrika (2019): Arterial stiffness and cardiovascular risk factors in young adults. 202. Fägerstad, Anida (2019): No-shows in dental care – perspectives on adolescents’ attendance pattern. 203. Månsson, Emeli (2019): Molecular epidemiology of Staphylococcus epidermidis in prosthetic joint infections.