Infection burden can be more accurately determined through a high-resolution method assigning species-level context to 16S rRNA gene sequence data.
Ninalynn Daquigan, MS
A US study published in Nature Research Journals' Biofilms and Microbiomes suggests that microbiome profiling identification relative to the total gut microbiome can serve as a useful tool for revealing insights into the burden of Clostridium difficile infections (CDI) for patients.
The study argues for the use of a new high-resolution method which is more accurate in determining taxonomies for microbiome profiling, as this method may prove useful in assessments of colonization in research studies, and could serve as a "prognostic indicator for patients with CDI."
The use of the new high-resolution method to determine C. difficile burden, according to lead author Ninalynn Daquigan, MS, Resphera Biosciences, in Baltimore, MD, may provide useful data for the development and testing of new CDI therapies.
Daquigan and colleagues assert that microbiome profiling via the use of 16S rRNA gene sequencing has been established as an important tool characterizing the diversity and composition of gut microbial communities, especially in relation to understanding CDI development and recurrence.
"Given the intricate relationship between the gut microbiota and CDI, accurate identification of C. difficile directly from 16S rRNA profiles in patient populations could be a valuable measure in future studies," Daquigan writes.
Daquigan and colleagues caution, however, a fundamental challenge to the study of CDI through 16S rRNA gene sequencing due to the nature of CDI. 16S rRNA gene sequencing utilizes higher aggregate taxonomic categories, identifying markers in the Clostridium XI cluster, which includes other organisms related to C. difficile.
These related organisms complicate quantification by serving as a "proxy for the organism itself" creating either false positives or skewing burden data.
The study suggests that by using a high-resolution method (Resphera Insight) to assign species-level context to 16S rRNA gene sequence data, the C. difficile burden can be more accurately determined in different patient populations.
Daquigan and colleagues suggest accurate data provided by this new method will lead to a greater understanding of community aspects of C. difficile colonization and resistance against the infection.
In order to test the effectiveness of the high-resolution taxonomic assignment method, the researchers used a validated algorithm previously used to identify listeria and salmonella in 16S rRNA gene sequence datasets and applied it to detection of 804 novel C. difficile isolates.
Data from the applied method saw an average Diagnostic True Positive Rate (DTP) of 99.9%, ranging between 98.92—100% per isolate. The method was successful in not only identifying C. difficile from among 22 related species in the clostridium XI cluster, but also resulted in 0 false positive C. difficile assignments from 20 of those 22-related species.
Overall, the ability of the method to stimulate 10,000 16S rRNA gene sequence reads per species resulted in a 0.5% error rate for detection of C. difficile among related species.
Daquigan and colleagues write the method has successfully indicated "sufficient sensitivity to detect C. difficile from short 16S rRNA gene sequence reads." The researchers utilized the new method to determine the presence of C. difficile in various human populations by re-examining existing published 16S rRNA gene sequencing datasets using the newly validated method.
The application of the new method determined that 91.5% of healthy controls in those datasets had no detectable C. difficile, and 0.9% maintained C. difficile levels higher than 0.1%.
In comparison, there was a fairly high burden of C. difficile in the gut microbiome of CDI index patients. Data showed that patients with CDI showed a wide distribution of C. difficile in the microbiota, and that C. difficile was unlikely to reside in healthy adults.
The study also applied the high-resolution taxonomic assignment method to CDI case studies with collected data on infants, and found that similar low levels of C. difficile in microbiota were present in healthy controls, at a higher ratio than that of healthy adult patients.
In one retroactive re-examination of study data on 753 pediatric patients, Daquigan and colleagues found that 6.6% of healthy infants were positive for C. difficile. Daquigan argues that many CDIs in infants are asymptomatic due to "the expected lack of specific toxin receptors and under-developed signaling pathways in the gut" and/or the protective aspects of breast-feeding on infant gut microbiota.
In examining the relationships between C. difficile and other gut microbiota, the researchers also revealed a significant negative correlation between C. difficile and other microbiota such as C. scindens, and several members of the Blautia genus, which suggests these microbiota may have a protective aspect and provide relevant functional capabilities in the context of CDI, proving to be informative in the development of future microbial-based therapeutics.
Daquigan and colleagues write that although microbiome profiling via 16S rRNA gene sequencing is unlikely to replace current methods for routine diagnosis of CDI, the sequence-based assessment of infection levels in the context of microbiota profiling may prove valuable in surveillance of C. difficile in patient populations, prediction of disease outcome, or the development of new therapies.
Since CDI poses such an extreme healthcare burden on the global population, Daquigan and colleagues hope the insights provided by the new high-resolution method will assist researchers and epidemiologists with the battle against CDI.
The study, "High-resolution profiling of the gut microbiome reveals the extent of clostridium difficile burden," appeared in NPJ Biofilms Microbiomes in December 2017.