One Minute Insight
Professor Gordon Dougan talks about the body’s resistance to antibiotics and how our researchers are are looking at the DNA of different bacteria to help track and prevent their spread in humans.
How DNA technologies are helping pneumonia patients fight back
Many patients who are admitted to intensive care show signs of pneumonia, and they are given antibiotics on admission to try and prevent it taking hold. However, this is not always successful and clinicians can find it hard to identify what kind of pneumonia it is.
The antimicrobial resistance team have been working with researchers from Public Health England and clinicians in the Intensive Care Unit at Cambridge University Hospitals to better understand the different types of pneumonia patients may have and to try and identify if they have an infection faster.
To do this, they are using revolutionary DNA-analysis and sequencing technologies that can help them identify exactly which microbes (if any) are contributing to a patient’s pneumonia. Using these technologies, researchers are now able to screen for around 100 kinds of microbes within hours of a sample being taken from the patient and identify which is the best antibiotic to use. Also some patients look like they are infected but are not and these can be quickly picked up. They can also identify how the patient is responding to the infection and help guide better treatment.
Quick identification of the right microbe will enable researchers to select and develop the right antibiotics to fight infection and prevent the disease from developing in vulnerable patients.
Cambridge researchers wanted to investigate how these ‘resistant’ bacteria could be identified faster, so that outbreaks can be reduced and treatments can be given sooner to patients who may be diagnosed with an infection.
Researchers looked at using whole genome sequencing or WGS (a complete set of all the genes of the bacteria including those causing resistance) and examined whether this technique would be an effective mechanism to detect these infectious threats as well as understand their biology and how they are spreading.
Researchers found they were able to identify the bacteria and their resistance patterns (e.g. which antibiotics work and which do not) directly from clinical samples taken from patients, using information gleaned from WGS. They noticed that using WGS gave more accurate information about the microbes and that it provided much better and much more detailed information than normal laboratory methods.
Researchers are continuing to look at ways of improving how these technologies can prevent the spread of infections and improve treatment selection.