Genotypic and mass spectrometric comparative analysis of African and German Staphylococcus aureus isolates

Staphylococcus aureus (SA) is a worldwide distributed, opportunistic pathogen colonizing 25-30% of the human population mostly without signs of infections. However, if infections (e.g. wound-, organ infections, sepsis) occurs, those are often associated with a significant morbidity and mortality. SA possesses a broad range of pathogenicity-, virulence- and resistance factors, whose presence is partially associated with specific phylogenetic developmental lines. Thus, the evaluation of transmission of infections is essentially based on phylogenetic analytics. This requires the development of reproducible, highly discriminatory typing methods for distinction of different SA strains. Thus, reproducible, polymerase chain reaction and sequencing based methods such as spa (SA protein A)-typing, multilocus sequencing typing (MLST) up to whole genome sequencing were developed. In contrast to spa-typing which is based on the sequencing of the single gene spa, MLST is based on the sequencing of seven housekeeping genes defining different sequence types (STs) which can be clustered to clonal complexes (CC). STs and CCs are today the grid for the international SA nomenclature in epidemiologic studies. DNA microarrays (MA) represents a special technique in which ST and CC are deduced from characteristic hybridization patterns of numerous genloci which are compared to a database of a large strain collection. In addition to the phylogenetic analysis the DNA MA hold a large number of locis for adhesion, virulence, toxin and resistance genes and thus provide a large amount of data. Comparison of multiple isolates investigated by DMA MA thus, requires supplementary bioinformatic methods for interpretation and presentation. Overall, there are plenty of moleculargenetic based studies of infection epidemiology of SA. But, most of them referred to countries with a high level of microbiological diagnostic. For Africa there is only very limited epidemiological data on SA (inclusive methicillin-resistant SA [MRSA]) especially of non-nosocomial (this means not acquired in hospital) SA (e.g. community-associated (CA) methicillin-resistant or methicillin-susceptible SA [MRSA, MSSA]). In order to fill this knowledge gap, four studies were performed as basis for this doctoral thesis investigating a) different bioinformatic tools for analysis of the molecular epidemiology of SA, b) the epidemiology of African and German MSSA/MRSA originating outside healthcare institutions and c) the applicability of mass spectrometry for analysis of SA epidemiology. For characterization of the bioinformatic tools the subtyping potential of spa-typing versus DNA MA analysis were compared in a study with 46 nasal CA-MSSA and 46 CA-MRSA of infections, collected in the federal state of Saarland. Further, the results were evaluated by three bioinformatic methods (splits graph, hierarchical agglomerative clustering [HAC] and principal component analysis [PCA]). Finally, in order to test the applicability of the DNA MA analytics in the African cohort, a relatively small cohort of isolates of 52 Nigerian MSSA was analyzed by DNA MA and splits graph method. In a big, multicentric, African-German, cross-sectional geographic comparative analysis, 1200 CA-SA isolates of healthy volunteers and patients of Sub-Saharan Africa and Germany were subsequently analyzed by DNA MA. In addition, association and comparative analyses of STs, CCs and gene composition of these isolates with respect to geographic (Germany or Africa) or clinical/nasal origin (nasal/asymptomatic or clinical/invasive) were performed. Finally, the potential applicability of identification of CCs or spa–types of CA-SA of CC5, CC8, CC15, CC30, CC45, CC121 and spa-types t002, t003, t504 based on their MALDI-TOF mass spectrometric profile, were also analyzed. Expected results on the epidemiology of CA-MRSA/MSSA were firstly gained by the DNA MA study of the federal state of Saarland, showing a higher subtyping potential of the DNA MA compared to spa-typing. Evaluation of the DNA MA data by the three previously mentioned bioinformatic methods yielded a diverse assignment of CC5 isolates to 3 to 7 clusters with exception of 12 CC5 isolates that always clustered in two identical clusters. It does not make these methods a failure but the use of different mathematical algorithms analyzing hybridization pattern differences or similarities may lead to minor differences. Further, MSSA displayed a high degree of diversity in comparison to the CA-MRSA group, which was dominated by the CC5 Rhine-Hesse epidemic strain (89%). The further analysis of African MSSA of the study with Nigerian MSSA identified a heterogeneous and divergent nature of the examined Nigerian MSSA and confirmed that the DNA MA is a suitable genotyping method of African SA. The results of the multicentric consortium study showed a total of 40 different CCs and STs, including 5 new STs. The majority, 15 of the 22 (68%) most common CC’s, were either predominant in Sub-Saharan Africa (Gabon, Mozambique, Tanzania) (CC80, CC88, CC121, CC152) or Germany (CC22, CC30, CC45, CC398). The rate of MRSA carriers in the African (3%) and German populations (1%) were very low, probably because the investigation was limited to CA-SA. Analysis of gene profiles identified a high prevalence of the Panton-Valentine leukocidin encoding genes lukF/S-PV in African isolates. Generally, continent-specific differences for the CCs and the CA-SA gene profiles could be identified. Furthermore, it became apparent that in addition to the good first-line characterization by DNA MA, standardized, complex analytical methods for association and epidemiological analyses are required. The last investigation purpose, the evaluation of comparative mass spectra analysis showed that only SA of CC121 were correctly identified based on their mass spectrometric profile on the CC level, while no clear discrimination was achieved for other CCs or spa-types. Taken together, this work identified country specific differences in the distribution of CCs, and specific genes of the examined regions, especially concerning only clinical isolates. The work provide first clues to the genetic based reasons which may explain the purported difference in clinical presentation and course of diseases caused by SA. Additionally, it was shown that DNA MA in contrast to mass spectrometry is a suitable tool for SA characterization e.g. in outbreak situations. However, it should be noted that as specific requirement of a challenging DNA MA based phylogenetic analyses, application of complex bioinformatic analysis methods are required for interpretation of multiple isolates, and that the characteristics and algorithms of the chosen bioinformatic method may result in slight differences in the data interpretation.Staphylococcus aureus (SA) ist ein weltweit verbreitetes, opportunistisches Pathogen, dass 25-30% der Bevölkerung häufig symptomfrei kolonisiert. Treten jedoch invasive Infektionen auf (z.B. Wund-, Organinfektion, Sepsis), so sind diese mit erheblicher Morbidität und Mortalität assoziiert. SA besitzt ein breites Spektrum an Pathogenitäts-, Virulenz- und Resistenzfaktoren, deren Vorhandensein teilweise mit besonderen phylogenetischen Entwicklungslinien assoziiert ist. So basiert die Bewertung von Infektionsübertragung und Ausbruchsgeschehen vielfach auch auf phylogenetischer Analytik. Dies erfordert die Entwicklung reproduzierbarer Typisierungsverfahren, die die unterschiedlichen SA-Stämme auch ausreichend trennscharf charakterisieren können. Daher wurden reproduzierbare, einheitlich auswertbare Polymerasekettenreaktionen und Sequenzierungsmethoden wie spa (SA Protein A)- Typisierung, Multilokussequenztypisierung (MLST), bis hin zur Gesamtgenomsequenzierung entwickelt. Im Gegensatz zur spa-Typisierung, basierend auf der Sequenzierung des einzelnen Gens spa, basiert die MLST auf der Sequenzierung von insgesamt sieben Haushaltsgenen, die verschiedene Sequenztypen (ST) definieren, welche zu klonalen Komplexen (CC) gruppiert werden. STs und CCs bilden heutzutage das Gerüst der internationalen SA Nomenklatur in epidemiologischen Studien. Eine besondere Technik stellen DNA Microarrays (MA) dar, mit deren Hilfe ST und CC aus charakteristischen Hybridisierungsmustern zahlreicher Genloci durch Vergleich mit einer Datenbank einer großen Stammsammlung abgeleitet werden. Neben dieser phylogenetischen Zuordnung besitzt der DNA MA zahlreiche Loci für Adhäsions-, Virulenz- und Toxingene und liefert daher eine große Masse an Daten. Der Vergleich zahlreicher, mittels DNA MA untersuchter, Isolate erfordert daher zur Interpretation und Präsentation ergänzende bioinformatische Methoden. Insgesamt gibt es für SA eine umfangreiche Studienlage zur molekulargenetisch typisierten Infektionsepidemiologie; überwiegend bezieht diese sich jedoch auf Länder mit einem hohen Standard mikrobieller Diagnostik. Für Afrika gibt es nur wenige molekular-epidemiologische Daten von SA (inklusive Methicillin-resistenter SA [MRSA]), insbesondere von nicht nosokomialen (d.h., nicht im Krankenhaus erworbenen) SA (wie z.B. ambulant erworbener (CA) Methicillin-resistenter oder - empfindlicher SA [MRSA, MSSA]). Um diese Wissenslücke zu füllen, wurden als Grundlage dieser Promotionsarbeit vier Studien durchgeführt zur Untersuchung a) verschiedener bioinformatischer Werkzeuge zur Analyse der molekularen Epidemiologie von SA, b) der Epidemiologie von afrikanischen und deutschen CAMSSA/ MRSA, die nicht in Gesundheitsinstitutionen erworben wurden, und c) der Anwendbarkeit der Massenspektrometrie zur Analyse der Epidemiologie von SA. Zur Charakterisierung der bioinformatischen Werkzeuge wurde das Subtypisierungspotential der spa-Typisierung und der DNA MA Analyse in einer Studie mit 46 nasalen CA-MSSA und 46 von Infektionen stammenden CA-MRSA des Bundeslandes Saarland verglichen. Zudem wurden die Ergebnisse mit drei bioinformatischen Methoden („splits graph“, hierarchische agglomerative Gruppierung [HAC] und Hauptkomponentenanalyse [PCA]) zur DNA Analyse evaluiert. Um die Anwendbarkeit der DNA MA Analytik auch in afrikanischen Kohorten zu überprüfen, wurde eine relativ kleine Isolatkohorte von 52 nigerianischen MSSA Isolaten mittels DNA MA und splits graph Analyse untersucht. In einer großen, multizentrischen, afrikanisch-deutschen, geographisch vergleichenden Querschnittsuntersuchung wurden 1200 CA-SA Isolate, gesunder Freiwilliger und von Patienten aus Sub-Sahara Afrika und Deutschland, mittels DNA MA analysiert. Zudem wurden Assoziations- und vergleichende Analysen der CC, ST und der Genausstattung der Isolate, hinsichtlich ihrer geographischen Herkunft (Deutschland oder Afrika) bzw. ihres klinischen/kommensalen Ursprung, durchgeführt. Schließlich wurde die mögliche Anwendbarkeit der Identifikation von CCs oder spa–Typen von CA-SA des CC5, CC8, CC15, CC30, CC45, CC121 und der spa- Typen t002, t003, t504 basierend auf MALDITOF Massenspektrometrieprofilen analysiert. Die mit diesen Untersuchungen angestrebten Ergebnisse, zur Epidemiologie von CAMSSA/ MRSA, wurden zunächst mit der DNA MA Studie des Bundeslandes Saarland gewonnen, welche ein höheres Subtypisierungspotential für den DNA MA im Vergleich zur spa–Typisierung zeigte. Die Auswertung der DNA MA Daten mittels der zuvor genannten drei bioinformatischen Methoden zeigte eine unterschiedliche Zuordnung von CC5 Isolaten zu 3 bis 7 Isolatgruppen mit Ausnahme von zwölf CC5 Isolaten. Diese zwölf CC5 Isolate wurden immer zwei identischen Isolatgruppen zugeordnet. Dies heißt nicht, dass die Methoden fehlerhaft sind, sondern dass die Anwendung unterschiedlicher mathematischen Algorithmen, die entweder die Unterschiede oder die Ähnlichkeiten der Hybridisierungsmuster untersuchen, zu geringfügigen Unterschieden führen. Zudem zeigten die MSSA eine hohe Diversität im Vergleich zur CA-MRSA Gruppe, die vom CC5 Rhine-Hesse epidemischen Stamm dominiert wurde (89%). Die weitere Analyse afrikanischer Stämme aus der Studie mit nigerianischen MSSA zeigte eine heterogene und divergente Natur der untersuchten nigerianischen MSSA und bestätigte, dass der DNA MA eine geeignete Methode zur Genotypisierung afrikanischer SA ist. Die Ergebnisse der multizentrischen deutsch-afrikanischen Konsortialstudie wies innerhalb der Isolatgruppe insgesamt 40 verschiedene CCs und STs nach, einschließlich 5 neuer STs. Die Mehrheit, 15 von 22 (68%) der CCs, die auch am häufigsten identifiziert wurden, waren entweder in Sub-Sahara Afrika (Gabon, Mozambique, Tanzania) (CC80, CC88, CC121, CC152) oder Deutschland (CC22, CC30, CC45, CC398) vorherrschend. Die Rate an MRSA Trägern in der afrikanischen (3%) und deutschen Bevölkerung (1%) war sehr gering, vermutlich durch die auf CASA beschränkte Untersuchung. Die Analyse der Genprofile zeigte eine hohe Prävalenz der Panton-Valentin Leukozidin kodierenden Gene lukF/S-PV in afrikanischen Isolaten. Allgemein konnten kontinentspezifische Unterschiede für die CC und CA-SA Genprofile identifiziert werden. Zudem wurde ersichtlich, dass ergänzend zur guten Erstcharakterisierung durch den DNA MA, standardisierte, komplexe analytische Methoden für Assoziationsanalysen und epidemiologische Untersuchungen erforderlich sind. Das letzte Untersuchungsziel, die Bewertung vergleichender Massenspektrometrieanalysen zeigte, dass - basierend auf ihrem Spektrometrieprofil - nur SA des CC121 korrekt identifiziert werden konnten, während keine korrekte Identifikation anderer CC oder spa-Typen möglich war. Zusammenfassend identifizierte diese Arbeit länderspezifische Unterschiede in der Verteilung klonaler Komplexe und spezifischer Gene in den untersuchten Regionen, insbesondere bei alleiniger Betrachtung klinischer Isolate. Sie gibt wertvolle Hinweise auf die genetisch basierten Gründe, welche die angeblichen Unterschiede in der klinischen Präsentation und dem Verlauf von durch SA verursachten Infektionen in sich entwickelnden und industriellen Ländern erklären könnten. Zudem wurde gezeigt, dass der DNA MA im Gegensatz zur Massenspektrometrie eine geeignete Methode zur SA Charakterisierung z.B. in Ausbruchssituationen ist. Es darf jedoch nicht unerwähnt bleiben, dass als besondere Anforderung an eine anspruchsvolle, DNA MA-basierte phylogenetische Analytik mehrerer Isolate die Anwendung komplexer bioinformatischer Analysemethoden zur Interpretation erforderlich ist, und dass die Charakteristiken und Algorithmen der gewählten bioinformatischen Methode zu geringfügigen Unterschieden in der Dateninterpretation führen kann

Analysis of the dynamics of Staphylococcus aureus binding to white blood cells using whole blood assay and geno-to-pheno mapping

Given that binding and internalization of bacteria to host cells promotes infections and invasion, we aimed at characterizing how various S. aureus isolates adhere to and are internalized by different white blood cells. In particular, the role of genetic determinants on the association kinetics should be unveiled. A flow cytometric (FACS) whole blood assay with fluorescently labelled isolates was applied to 56 clinical S. aureus isolates. This phenotypic data was then linked to previously obtained genotyping data (334 genes) with the help of a redescription mining algorithm. Professional phagocytes showed a time-dependent increase of bacterial adhesion and internalization. Isolates showing higher affinity to granulocytes were associated with lower binding to monocytes. In contrast binding activity between S. aureus and lymphocytes could be subdivided into two phases. Preliminary binding (phase 1) was highest directly after co-incubation and was followed by S. aureus detachment or by sustained binding of a small lymphocyte subset (phase 2). Strain-dependent low granulocyte binding was observed for clonal complex 5 (CC5) isolates (MRSA), as compared to CC30 and CC45 (MSSA). S. aureus isolates associated with low granulocyte phagocytosis were characterized by the presence (cap8, can) and the absence (sasG, lukD, isdA, splA, setC) of specific hybridization signals

Molecular Characterization of Community Acquired Staphylococcus aureus Bacteremia in Young Children in Southern Mozambique, 2001–2009

Background: The emergence of community-acquired Staphylococcus aureus infections is increasingly recognized as life threating problem worldwide. In Manhiça district, southern Mozambique, S. aureus is the leading cause of community-acquired bacteremia in neonates.Methods: Eighty-four S. aureus isolates from children less than 5 years admitted to Manhiça District Hospital from 2001 to 2009 were randomly selected and genetically characterized by DNA microarray and spa typing. Antimicrobial susceptibility was determined by VITEK 2.Results: Thirty-eight different spa types and 14 clonal complexes (CC) were identified. Spa-type t084 (n = 10; 12%) was the most predominant while CC8 (n = 18; 21%) and CC15 (n = 14; 16%) were the most frequent CCs. Mortality tended to be higher among children infected with CC45 (33.3%, 1/3) and CC8 (27.8%, 5/18). The majority of isolates possessed the accessory gene regulator I (45%) and belonged to either capsule type 8 (52%) or 5 (47%). Panton valentine leukocidin (PVL) encoding genes were detected in 30%. Antibiotic resistance was high for penicillin (89%), tetracycline (59%) and Trimethoprim Sulfamethoxazole (36%) while MRSA was uncommon (8%).Conclusions: Although MRSA were uncommon, we found high genetic diversity of methicillin susceptible S. aureus causing bacteremia in Mozambican children, associated with high resistance to the most available antibiotics in this community. Some CCs are likely to be more lethal indicating the need for prompt recognition and appropriate treatment

Matched-cohort DNA microarray diversity analysis of methicillin sensitive and methicillin resistant Staphylococcus aureus isolates from hospital admission patients.

As genotyping of S. aureus is important for epidemiologic research and for hygiene management, methods are required for standardized fast and easily applicable evaluation of closely related epidemic strains with high prevalence in hospitals. In this single centre matched control study we compared a new commercially available DNA microarray (IdentiBAC) with standard spa-typing for S. aureus genotyping. Included in the study was a subgroup of 46 MRSA and matched 46 MSSA nasal isolates of the Saarland University Medical Center collected during a state-wide admission prevalence screening. Microarray (MA) and also spa-typing could easily differentiate the genetically diverse MSSA group. However, due to the predominance of CC5/t003 in the MRSA group a sufficient subtyping required analysis of more complex genetic profiles as was shown here by the MA comprising a total number of 334 different hybridization probes. The genetic repertoire of the MRSA group was characterized by more virulence genes as compared to the MSSA group. The standard evaluation of MA results by the original software into CCs, agr-, SCCmec- and capsule-types was substituted in the present study by implementation of multivariate subtyping of closely related CC5 isolates using three different bioinformatic methods (splits graph, cluster dendrogram, and principal component analysis). Each method used was applicable for standardized and highly discriminative subtyping with high concordance. We propose that the identified S. aureus subtypes with characteristic virulence gene profiles are presumably associated also with virulence and pathogenicity in vivo; however, this remains to be analyzed in future studies. MA was superior to spa-typing for epidemiologic and presumably also provide functional respectively virulence associated characterization of S. aureus isolates. This is of specific importance for the hospital setting. In future, MA could become a new standard test for S. aureus typing in combination with multivariate bioinformatic analysis

Diversity analysis of all MSSA (S1–S46) and MRSA (R1–R46) isolates by splits graph.

<p>(A) Splits graph constructed based on cost distance matrix produced by Ridom StaphType and (B) on default settings of the IdentiBAC microarray hybridization profiles of 334 genes and alleles. Clonal complexes (CC) as well as the most abundant <i>spa</i>-types t003 (circles) and t012 (quadrates) were highlighted.</p

Subclassification analysis of 41 MRSA (R1–R41) and two MSSA (S42, S43) of CC5.

<p>(A) Splits graph based on cost distance matrix computed by Ridom StaphType software. (B) Splits graph based on MA hybridization profiles. Characteristic gene profiles for isolate cluster assignment were arbitrarily stated into group A-E. The most common MRSA <i>spa</i>-types t003 (circles), t504 (quadrates) and t010 (hexagons) were highlighed.</p

Principal component cluster analysis (PCA) of 41 MRSA (R1–R41) and two MSSA (S42, S43) of CC5.

<p>(A) Clustering of the 43 CC5 isolates by PCA as well as (B) subclustering of 30 MRSA CC5 cluster I isolates using a higher resolution PCA plot for in-depth identification of additional subgroups (Ia–Id).</p

CC5 isolates (n = 43) characterized by <i>spa</i>-typing and comprehensive MA subgroup analysis using three different bioinformatic modes (principal component analyses, splits graph and cluster dendrogram).

<p>CC5 isolates (n = 43) characterized by <i>spa</i>-typing and comprehensive MA subgroup analysis using three different bioinformatic modes (principal component analyses, splits graph and cluster dendrogram).</p

Risk factors of MRSA and matched MSSA control group isolates.

#<p>statistical analysis was not performed for clinical criteria applied for selection of matched MSSA cases, ns =  not significant.</p