Dataset Information

The Epidome - a species-specific approach to assess the population structure and heterogeneity of Staphylococcus epidermidis colonization and infection.

ABSTRACT:

Background

Although generally known as a human commensal, Staphylococcus epidermidis is also an opportunistic pathogen that can cause nosocomial infections related to foreign body materials and immunocompromized patients. Infections are often caused by multidrug-resistant (MDR) lineages that are difficult and costly to treat, and can have a major adverse impact on patients' quality of life. Heterogeneity is a common phenomenon in both carriage and infection, but present methodology for detection of this is laborious or expensive. In this study, we present a culture-independent method, labelled Epidome, based on an amplicon sequencing-approach to deliver information beyond species level on primary samples and to elucidate clonality, population structure and temporal stability or niche selection of S. epidermidis communities.

Results

Based on an assessment of > 800 genes from the S. epidermidis core genome, we identified genes with variable regions, which in combination facilitated the differentiation of phylogenetic clusters observed in silico, and allowed classification down to lineage level. A duplex PCR, combined with an amplicon sequencing protocol, and a downstream analysis pipeline were designed to provide subspecies information from primary samples. Additionally, a probe-based qPCR was designed to provide valuable absolute abundance quantification of S. epidermidis. The approach was validated on isolates representing skin commensals and on genomic mock communities with a sensitivity of < 10 copies/μL. The method was furthermore applied to a sample set of primary skin and nasal samples, revealing a high degree of heterogeneity in the S. epidermidis populations. Additionally, the qPCR showed a high degree of variation in absolute abundance of S. epidermidis.

Conclusions

The Epidome method is designed for use on primary samples to obtain important information on S. epidermidis abundance and diversity beyond species-level to answer questions regarding the emergence and dissemination of nosocomial lineages, investigating clonality of S. epidermidis communities, population dynamics, and niche selection. Our targeted-sequencing method allows rapid differentiation and identification of clinically important nosocomial lineages in low-biomass samples such as skin samples.

SUBMITTER: Rendboe AK

PROVIDER: S-EPMC7691061 | biostudies-literature | 2020 Nov

REPOSITORIES: biostudies-literature

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Publications

The Epidome - a species-specific approach to assess the population structure and heterogeneity of Staphylococcus epidermidis colonization and infection.

Rendboe Amalie Katrine AK Johannesen Thor Bech TB Ingham Anna Cäcilia AC Månsson Emeli E Iversen Søren S Baig Sharmin S Edslev Sofie S Jensen Jørgen Skov JS Söderquist Bo B Andersen Paal Skytt PS Stegger Marc M

BMC microbiology 20201126 1

<h4>Background</h4>Although generally known as a human commensal, Staphylococcus epidermidis is also an opportunistic pathogen that can cause nosocomial infections related to foreign body materials and immunocompromized patients. Infections are often caused by multidrug-resistant (MDR) lineages that are difficult and costly to treat, and can have a major adverse impact on patients' quality of life. Heterogeneity is a common phenomenon in both carriage and infection, but present methodology for d ...[more]

PMID: 33243146

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Project description:Preterm infants are at increased risk of infections caused by coagulase-negative staphylococci (CoNS) that colonize skin. Technical barriers in sequencing low-microbial-biomass skin swabs from preterm infants hinder attempts to gain a strain-level understanding of CoNS colonization dynamics within their developing skin microbiome. Here, the microbiome of five skin sites and available stool was studied from four preterm infants hospitalized over their first 2 months of life. We used propidium monoazide treatment of samples to enrich for the viable microbiome and metagenomic shotgun sequencing to resolve species and strains. The microbiome of different skin sites overlapped with each other, was dominated by the CoNS species Staphylococcus epidermidis and Staphylococcus capitis, and was distinct from stool. Species diversity on skin increased over time despite antibiotic exposure. Evidence of antagonism between the most common S. epidermidis strains, ST2 and ST59, included negative relationships for species correlation networks and in situ replication rates and that ST2 colonized skin earlier but was often replaced by ST59 over time. Experiments done with reference isolates showed that ST2 produced more biofilm than ST59 on plastic surfaces, which was reduced in mixed culture. We also discovered that a rare S. epidermidis strain, ST5, grew rapidly in stool in association with Stenotrophomonas maltophilia from a suspected episode of infection. Viability treatment of samples and moderate throughput shotgun sequencing provides strain-level information about CoNS colonization dynamics of preterm infant skin that ultimately might be exploited to prevent infections. IMPORTANCE The skin is a habitat for microbes that commonly infect preterm infants, but the use of sequencing for fine-scale study of the microbial communities of skin that develop in these infants has been limited by technical barriers. We treated skin swabs of preterm infants with a photoreactive dye that eliminates DNA from nonviable microbes and then sequenced the remaining DNA. We found that two strains of the most common species, Staphylococcus epidermidis, showed an antagonistic relationship on skin by cooccurring with different species, replicating fastest in different samples, and dominating skin sites at different times. Representatives of these strains also differed in their ability to stick to plastic surfaces-an important pathogenicity trait of this species. Our study shows the feasibility of gaining detailed information about strain colonization dynamics from this difficult-to-sequence body site of preterm infants, which might be used to guide novel approaches to prevent infections.

Project description:BackgroundComplex transmission models of healthcare-associated infections provide insight for hospital epidemiology and infection control efforts, but they are difficult to implement and come at high computational costs. Structuring more simplified models to incorporate the heterogeneity of the intensive care unit (ICU) patient-provider interactions, we explore how methicillin-resistant Staphylococcus aureus (MRSA) dynamics and acquisitions may be better represented and approximated.MethodsUsing a stochastic compartmental model of an 18-bed ICU, we compared the rates of MRSA acquisition across three ICU population interaction structures: a model with nurses and physicians as a single staff type (SST), a model with separate staff types for nurses and physicians (Nurse-MD model), and a Metapopulation model where each nurse was assigned a group of patients. The proportion of time spent with the assigned patient group (γ) within the Metapopulation model was also varied.ResultsThe SST, Nurse-MD, and Metapopulation models had a mean of 40.6, 32.2 and 19.6 annual MRSA acquisitions respectively. All models were sensitive to the same parameters in the same direction, although the Metapopulation model was less sensitive. The number of acquisitions varied non-linearly by values of γ, with values below 0.40 resembling the Nurse-MD model, while values above that converged toward the Metapopulation structure.DiscussionInclusion of complex population interactions within a modeled hospital ICU has considerable impact on model results, with the SST model having more than double the acquisition rate of the more structured metapopulation model. While the direction of parameter sensitivity remained the same, the magnitude of these differences varied, producing different colonization rates across relatively similar populations. The non-linearity of the model's response to differing values of a parameter gamma (γ) suggests simple model approximations are appropriate in only a narrow space of relatively dispersed nursing assignments.ConclusionSimplifying assumptions around how a hospital population is modeled, especially assuming random mixing, may overestimate infection rates and the impact of interventions. In many, if not most, cases more complex models that represent population mixing with higher granularity are justified.

Dataset Information

The Epidome - a species-specific approach to assess the population structure and heterogeneity of Staphylococcus epidermidis colonization and infection.

Background

Results

Conclusions

Publications

The Epidome - a species-specific approach to assess the population structure and heterogeneity of Staphylococcus epidermidis colonization and infection.

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