Diphtheria is a highly contagious and potentially fatal infection yet it is easily preventable. Researchers have noticed as it evolves it is becoming resistant to a number of antibiotics.

In high-income countries, babies are vaccinated against infection. However, diphtheria is still problematic in low- and middle-income countries, where the disease can still cause infections in those who are unvaccinated. The disease can be spread through coughs, sneezes or close contact with someone who has been infected. Antibiotics is still the main method to treat the disease.

Researchers analysed the genomes of 61 bacteria isolated from patients and combining these with 441 publicly available genomes, the researchers were able to build a phylogenetic tree – a genetic ‘family tree’ – to see how the infections are related and understand how they spread. They also used this information to assess the presence of antimicrobial resistance (AMR) genes and assess toxin variation.

When the team looked for genes that might identify any resistance to antimicrobials, they found that the average number of AMR genes per genome was increasing each decade. Genomes of bacteria isolated from infections from the most recent decade (2010-19) showed the highest average number of AMR genes per genome, almost four times as many on average than in the next highest decade, the 1990s.

Read the full press release from 8 March 2021

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.