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Cited by 168Bacterial Identification and Susceptibility TestingWound Healing and TreatmentsActinomycetales infections and treatment

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Clinical identification of bacteria in human chronic wound infections: culturing vs. 16S ribosomal DNA sequencing

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Rhoads, Daniel D, Cox, Stephen B, Rees, Eric J, Sun, Yan, Wolcott, Randall D·2012·BMC Infectious Diseases
DOI 10.1186/1471-2334-12-321PMC PMC3542000
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Abstract

Background: Chronic wounds affect millions of people and cost billions of dollars in the United States each year. These wounds harbor polymicrobial biofilm communities, which can be difficult to elucidate using culturing methods. Clinical molecular microbiological methods are increasingly being employed to investigate the microbiota of chronic infections, including wounds, as part of standard patient care. However, molecular testing is more sensitive than culturing, which results in markedly different results being reported to clinicians. This study compares the results of aerobic culturing and molecular testing (culture-free 16S ribosomal DNA sequencing), and it examines the relative abundance score that is generated by the molecular test and the usefulness of the relative abundance score in predicting the likelihood that the same organism would be detected by culture. Methods: Parallel samples from 51 chronic wounds were studied using aerobic culturing and 16S DNA sequencing for the identification of bacteria. Results: One hundred forty-five (145) unique genera were identified using molecular methods, and 68 of these genera were aerotolerant. Fourteen (14) unique genera were identified using aerobic culture methods. One-third (31/92) of the cultures were determined to be < 1% of the relative abundance of the wound microbiota using molecular testing. At the genus level, molecular testing identified 85% (78/92) of the bacteria that were identified by culture. Conversely, culturing detected 15.7% (78/497) of the aerotolerant bacteria and detected 54.9% of the collective aerotolerant relative abundance of the samples. Aerotolerant bacterial genera (and individual species including Staphylococcus aureus , Pseudomonas aeruginosa , and Enterococcus faecalis ) with higher relative abundance scores were more likely to be detected by culture as demonstrated with regression modeling. Conclusion: Discordance between molecular and culture testing is often observed. However, culture-free 16S ribosomal DNA sequencing and its relative abundance score can provide clinicians with insight into which bacteria are most abundant in a sample and which are most likely to be detected by culture.

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Crossref · 10.1186/1471-2334-12-321

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Figure 1 Frequently identified bacteria genera. Rank abundance distribution of the 145 bacterial genera detected by 16S DNA sequencing methods. Here, abundance is based on the sum of relative abundances from all samples. Red dots represent genera that were cultured aerobically. Only the 14 most abundant genera are labeled.
Figure 1 Frequently identified bacteria genera. Rank abundance distribution of the 145 bacterial genera detected by 16S DNA sequencing methods. Here, abundance is based on the sum of relative abundances from all samples. Red dots represent genera that were cultured aerobically. Only the 14 most abundant genera are labeled.CC BY · PubMed Central
Figure 2 Relative abundance of wound bacteria influences their likelihood of culture detection. Mosaic plot of the number of times a detected bacterial genus (as determined by molecular methods) was cultured (as shown in gray). Only aerobic bacteria were considered, and bacterial genera were divided into dominant (>10%), major (1-10%), or minor (<1%) components of each sample based upon their relative abundance within each sample. Areas of each component of the plot are proportional to the observed number of occurrences. Dominant genera were cultured 47% (43/91) of the time. Major genera were cultured 15% (18/120) of the time. Minor genera were cultured 5.9% (17/286) of the time.
Figure 2 Relative abundance of wound bacteria influences their likelihood of culture detection. Mosaic plot of the number of times a detected bacterial genus (as determined by molecular methods) was cultured (as shown in gray). Only aerobic bacteria were considered, and bacterial genera were divided into dominant (>10%), major (1-10%), or minor (<1%) components of each sample based upon their relative abundance within each sample. Areas of each component of the plot are proportional to the observed number of occurrences. Dominant genera were cultured 47% (43/91) of the time. Major genera were cultured 15% (18/120) of the time. Minor genera were cultured 5.9% (17/286) of the time.CC BY · PubMed Central
Figure 3 Increased relative abundance of a bacterial genus increases the likelihood that the genus will be cultured. Each dot represents the detection of a bacterial genus by 16S DNA sequencing. Genera that were detected by culture (response = 1) are represented by dots at the top of the figure, and genera that were not cultured (response = 0) are represented as dots at the bottom of the figure. The proportion of occurrences that were detected by culture was modeled as a function of the observed relative abundance (as determined using molecular testing) using logistic regression (indicated by the blue line). The results demonstrate that an increased relative abundance of a bacterial genus subsequently increases the likelihood that the genus will be cultured. The shaded region indicates the 95% confidence interval of the predicted proportion.
Figure 3 Increased relative abundance of a bacterial genus increases the likelihood that the genus will be cultured. Each dot represents the detection of a bacterial genus by 16S DNA sequencing. Genera that were detected by culture (response = 1) are represented by dots at the top of the figure, and genera that were not cultured (response = 0) are represented as dots at the bottom of the figure. The proportion of occurrences that were detected by culture was modeled as a function of the observed relative abundance (as determined using molecular testing) using logistic regression (indicated by the blue line). The results demonstrate that an increased relative abundance of a bacterial genus subsequently increases the likelihood that the genus will be cultured. The shaded region indicates the 95% confidence interval of the predicted proportion.CC BY · PubMed Central
Figure 4 Increased relative abundance of a bacterial species increases the likelihood that the species will be cultured. Each dot represents the detection of the species by 16S deep sequencing. Species that were detected by culture (response = 1) are represented by dots at the top of the figure, and species that were not cultured (response = 0) are represented as dots at the bottom of the figure. The proportion of occurrences that were detected by culture was modeled as a function of the observed relative abundance (as determined using molecular testing) using logistic regression (indicated by the blue line). The shaded region indicates the 95% confidence interval of the predicted proportion. The trend was significantly positive for Pseudomonas aeruginosa (OR = 1.17; 95% CI, 1.08-1.31) and Staphylococcus aureus (OR = 1.08; 95% CI, 1.03-1.15), and it approached significance for Enterococcus faecalis (OR = 1.05; 95% CI, 0.98-1.16). The results demonstrate that an increased relative abundance of one of these species within a sample subsequently increases the likelihood that the species will be cultured.
Figure 4 Increased relative abundance of a bacterial species increases the likelihood that the species will be cultured. Each dot represents the detection of the species by 16S deep sequencing. Species that were detected by culture (response = 1) are represented by dots at the top of the figure, and species that were not cultured (response = 0) are represented as dots at the bottom of the figure. The proportion of occurrences that were detected by culture was modeled as a function of the observed relative abundance (as determined using molecular testing) using logistic regression (indicated by the blue line). The shaded region indicates the 95% confidence interval of the predicted proportion. The trend was significantly positive for Pseudomonas aeruginosa (OR = 1.17; 95% CI, 1.08-1.31) and Staphylococcus aureus (OR = 1.08; 95% CI, 1.03-1.15), and it approached significance for Enterococcus faecalis (OR = 1.05; 95% CI, 0.98-1.16). The results demonstrate that an increased relative abundance of one of these species within a sample subsequently increases the likelihood that the species will be cultured.CC BY · PubMed Central

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Metadata

Authors
Rhoads, D. D., Cox, S. B., Rees, E. J., Sun, Y., & Wolcott, R. D.
Affiliations
  • University of Pittsburgh Medical Center (US)
  • Southwest Regional Wound Care Center (US)
Corresponding author
Wolcott, Randall D
ORCID
Venue
BMC Infectious Diseases
Publisher
Springer Science and Business Media LLC
Published
2012-11-24
Volume
12
Issue
1
Pages
321-321
ISSN
1471-2334 (ISSN-L)
DOI
10.1186/1471-2334-12-321
PMC
PMC3542000
OpenAlex
W2115171049
Cited by
167
References
17
Citations by year
2026: 6 · 2025: 5 · 2024: 15 · 2023: 15 · 2022: 11 · 2021: 15 · 2020: 12 · 2019: 19 · 2018: 15 · 2017: 14 · 2016: 10 · 2015: 11 · 2014: 13 · 2013: 6
FWCI
6.16
Type
journal article
Language
en
Open access
Licence
Locations
  • BMC Infectious Diseases (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • D-Scholarship@Pitt (University of Pittsburgh) (acceptedVersion)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
Topics
  • Health Sciences › Medicine › Microbiology (medical) › Bacterial Identification and Susceptibility Testing
  • Health Sciences › Medicine › Surgery › Wound Healing and Treatments
  • Health Sciences › Medicine › Microbiology (medical) › Actinomycetales infections and treatment
Keywords
chronic wound infection, wound microbiota, polymicrobial biofilms, Staphylococcus aureus, Pseudomonas aeruginosa, Enterococcus faecalis, bacterial identification
MeSH terms
Bacteria, Bacterial Infections, Bacteriological Techniques, Chronic Disease, DNA, Ribosomal, Humans, RNA, Ribosomal, 16S, United States, Wound Infection, Molecular Diagnostic Techniques

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