New Diagnostic Tool Able to Detect Key but Difficult Microbe in CF Lung Infections

Alice Melão, MSc avatar

by Alice Melão, MSc |

Share this article:

Share article via email
bacterial infections in CF

A research team has developed a new way of specifically and efficiently identifying bacterial infections caused by the Burkholderia cepacia complex (BCC) in patients with cystic fibrosis (CF).

This complex is among the most prevalent of bacterial infections detected in CF patients — who are known to be prone to chronic or recurrent lung infections by bacteria — but BCC remains difficult to diagnosis. Because effective treatment of CF lung infections require prompt clinical identification of the responsible microbes, BCC infection is also difficult to treat and is associated with a poor prognosis.

The authors of the study, “Evolving serodiagnostics by rationally designed peptide arrays: the Burkholderia paradigm in Cystic Fibrosis,” published in the journal Scientific Reports, for this reason set out to find a better way of identifying BCC infection in CF patients’ serum.

To do so, they made use of the design of peptide microarray platforms. These combine structural and genomic analyses of the interaction of proteins produced during infection with Burkholderia cepacia with analyses of CF patients’ immune systems.

Researchers evaluated 14 serum samples from patients with BCC infection, and 11 serum samples from CF patients without this infection. These were then compared to 14 samples from healthy individuals.

Results revealed that such peptide microarray platforms advanced the application of molecular diagnostics beyond its current limits, detecting BCC positive samples with confidence exceeding 97%. Importantly, this new method showed high diagnostic specificity and sensitivity even in the presence of other bacterial infections.

Current diagnostic techniques for detecting and identifying opportunistic infections in CF patients can be very expensive and time consuming. They can also lack the capacity to discriminate and specifically identify the pathogen involved. The researchers say this new diagnostics platform can overcome such limitations, and may be further improved to respond to a broader spectrum of CF-associated infections, with advantages like lower cost and increased effectiveness.

Although the study’s authors specifically designed and tested their method on BCC infection, they believe it has the potential to be extended to other pathogens or other diagnostic needs.

Further studies on a larger clinical scale, however, are required to confirm the diagnostic potential of this new tool.