A new method incorporating matrix-assisted laser desorption ionization time-of-flight mass spectrometry, or MALDI-TOF, can help laboratories quickly identify hospital outbreaks of Clostridium difficile, according to research published in PLoS One.
“Within 30 minutes you can tell whether you have strains of the same clonal type and, therefore, a probable transmission between patients, or whether a patient has symptoms from his or her own bacteria,” Thomas Akerlund, PhD, a microbiologist at the Public Health Agency of Sweden, said in a press release.
Early detection of transmission of C. difficile between patients enables faster action from health facilities to limit the outbreak, according to Akerlund and his colleague, Kristina Rizzardi, PhD, a molecular biologist at the agency.
Akerlund and Rizzardi developed a new MALDI-TOF method known as high molecular weight (HMW) typing to identify specific proteins on the surface of bacteria. HMW typing was used to monitor the first outbreak of moxifloxacin-resistant C. difficile PCR ribotype 027 in Sweden in January 2014, according to the researchers. The process takes approximately 15 minutes, or 30 minutes if ethanol/formic acid extraction is also performed — much faster than traditional PCR ribotyping. Additionally, it costs approximately $0.50 per sample.
To compare this new method to PCR ribotyping, Akerlund and Rizzardi studied 500 isolates representing 59 PCR ribotypes. A total of 35 HMW types could be resolved using the new method.
The researchers acknowledged that HMW typing is less discriminatory than PCR ribotyping, but its cost and effectiveness make it an attractive option to monitor outbreaks of C. difficile. Additionally, combining HMW typing and PCR ribotyping results could improve surveillance even further, they said.
“The method developed in this study, HMW typing, is in our mind an important complement to other typing methods … ” the researchers wrote. “As MALDI-TOF has become a standard tool in many clinical laboratories, the HMW typing method has the potential to rapidly analyze a large number of strains and improve local surveillance at a low running cost.” – by David Jwanier
Disclosure: The researchers report no relevant financial disclosures.