Dataset Information

Analysis of Staphylococcus aureus Transcriptome in Pediatric Soft Tissue Abscesses and Comparison to Murine Infections.

ABSTRACT: A comprehensive understanding of how Staphylococcus aureus adapts to cause infections in humans can inform development of diagnostic, therapeutic, and preventive approaches. Expression analysis of clinical strain libraries depicts in vitro conditions that differ from those in human infection, but low bacterial burden and the requirement for reverse transcription or nucleic acid amplification complicate such analyses of bacteria causing human infection. We developed methods to evaluate the mRNA transcript signature of S. aureus in pediatric skin and soft tissue infections (SSTI) directly ex vivo Abscess drainage from 47 healthy pediatric patients undergoing drainage of a soft tissue infection was collected, and RNA was extracted from samples from patients with microbiologically confirmed S. aureus abscesses (42% due to methicillin-resistant S. aureus [MRSA]). Using the NanoString platform and primers targeting S. aureus mRNA transcripts encoding surface-expressed or secreted proteins, we measured direct counts of 188 S. aureus mRNA transcripts in abscess drainage. We further evaluated this mRNA signature in murine models of S. aureus SSTI and nasal colonization where the kinetics of the transcriptome could be determined. Heat maps of the S. aureus mRNA signatures from pediatric abscesses demonstrated consistent per-target expression across patients. While there was significant overlap with the profiles from murine SSTI and nasal colonization, important differences were noted, which can inform efforts to develop therapeutic and vaccine approaches.

SUBMITTER: Moffitt K

PROVIDER: S-EPMC8090966 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:BackgroundStaphylococcus aureus is one predominant cause of skin and soft-tissue infections (SSTIs), but little information exists regarding the characterization of S. aureus from non-native patients with SSTIs in China.MethodsIn this study, we enrolled 52 non-native patients with S. aureus SSTIs, and 65 native control patients with S. aureus SSTIs in Shanghai. 52 and 65 S. aureus isolates were collected from both groups, respectively. S. aureus isolates were characterized by antimicrobial susceptibility testing, toxin gene detection, and molecular typing with sequence type, spa type, agr group and SCCmec type.ResultsMethicillin-resistant S. aureus (MRSA) was detected in 8 non-native patients and 14 native patients with SSTIs. Overall, antimicrobial susceptibilities of S. aureus isolated from non-native patients were found higher than those from native patients. CC59 (ST338 and ST59) was found in a total of 14 isolates (4 from non-native patients; 10 from native patients), 9 of which were carrying lukS/F-PV (3 from non-native patients; 6 from native patients). ST7 was found in 12 isolates and all 12 isolates were found in native patients. The livestock-associated clone ST398 was found in 11 isolates (6 from non-native patients; 5 from native patients), and 5 ST398 lukS/F-PV-positive methicillin-susceptible S. aureus (MSSA) were all discovered among non-native patients. The molecular epidemiology of S. aureus isolated from non-native patients was quite different from those from native patients. lukS/F-PV was more frequent in isolates originating from non-native patients with SSTIs compared to native patients (31 vs. 7, P <0.0001).ConclusionsCC59 was the most common clonal complex among patients with SSTIs in Shanghai. The other most common sequence types were ST7 and Livestock ST398. The molecular epidemiology of S. aureus isolated from non-native patients was quite different from those from native patients. S. aureus isolated from non-native patients was more likely to carry lukS/F-PV.

Project description:IntroductionTo promote judicious prescribing of methicillin-resistant Staphylococcus aureus (MRSA)-active therapy for skin and soft tissue infections (SSTI), we previously developed an MRSA risk assessment tool. The objective of this study was to validate this risk assessment tool internationally.MethodsA multicenter, prospective cohort study of adults with purulent SSTI was performed at seven international sites from July 2016 to March 2018. Patient MRSA risk scores were computed as follows: MRSA infection/colonization history (2 points); previous hospitalization, previous antibiotics, chronic kidney disease, intravenous drug use, human immunodeficiency virus/acquired immunodeficiency syndrome (HIV/AIDS), diabetes with obesity (1 point each). Predictive performance of MRSA surveillance percentage, MRSA risk score, and estimated MRSA probability (surveillance percentage adjusted by risk score) were quantified using the area under the receiver operating characteristic curves (aROC) and compared. Performance characteristics of different risk score thresholds across varying baseline MRSA prevalence were examined.ResultsTwo hundred three patients were included. Common SSTI were wounds (28.6%), abscess (25.1%), and cellulitis with abscess (20.7%). Patients with higher risk scores were more likely to have MRSA (P < 0.001). The MRSA risk score aROC (95%CI) [0.748 (0.678-0.819)] was significantly greater than MRSA surveillance percentage [0.646 (0.569-0.722)] (P = 0.016). Estimated MRSA probability aROC [0.781 (0.716-0.845)] was significantly greater than surveillance percentage (P < 0.001) but not the risk score (P = 0.192). The estimated negative predictive value (NPV) of an MRSA score ≥ 1 (i.e., a score of 0) was greater than 90% when MRSA prevalence was 30% or less.ConclusionThe MRSA risk score and estimated MRSA probability were significantly more predictive of MRSA compared with surveillance percentage. An MRSA risk score of zero had high predictive value and could help avoid unnecessary empiric MRSA coverage in low-acuity patients. Further study, including impact of such risk assessment tools on prescribing patterns and outcomes are required before implementation.

Dataset Information

Analysis of Staphylococcus aureus Transcriptome in Pediatric Soft Tissue Abscesses and Comparison to Murine Infections.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets