Anthony King
A new lab technique can speed up vaccine development by shortening the time and effort required to identify antibodies of interest. It relies on cryo-electron microscopy (cryoEM) to examine mixtures of antibody-antigen from sera and a computational algorithm to reveal the sequences of these antibodies.
Serum samples are chock full of antibodies. If you want to identify a particular neutralising antibody against a microbe, thousands of B cells must usually be cloned and then their antibodies individually isolated and studied. Sometimes a person has a particularly effective neutralising antibody in their blood after infection, which can give clues as to what sort of vaccine response is desirable. But it can take months to fully characterise antibodies after vaccination or infection.
Now, a research team led by the Scripps Research Institute in La Jolla, California, US, has developed a method of taking all serum antibodies, imaging them, and computationally sorting the images into similar complexes (Sci. Adv., 2022, 8, eabk2039). ‘We basically capture all of the binding antibodies to the antigen [of interest],’ explains Andrew Ward, a structural biologist at Scripps Research. ‘The breakthrough is that we could discriminate and sort through very complex mixtures.’
The cryoEM allowed for antibody-antigen complexes to be mapped to a few angstroms and an algorithm tapped into a vast structural library to determine the likeliest amino acid sequence of the antibody. ‘Our process gets to the level of monoclonal antibodies in a matter of weeks,’ says Ward. ‘Characterising antibodies individually is usually a pretty laborious process and takes months.’
The technique was demonstrated using published experiments on macaque antibody responses to an HIV envelope glycoprotein. Most antibodies against viruses are raised against glycoproteins on their surfaces, with the spike of SARS-CoV-2 the most famous. But the challenge is the time it takes to identify the most potent neutralising antibodies in a serum sample. ‘If I take a sample of your blood after immunisation, we don’t have any idea what the sequence of your antibodies are,’ says Ward. ‘They are randomly generated through a stochastic process, which is partly how your antibodies recognise such a wide array of antigens and pathogens.’
Ward is using the technique now to search for neutralising antibodies against influenza, Lassa and Ebola viruses, as well as the malaria parasite. ‘We can go to people who have been previously infected with Lassa and search within them for really good antibodies,’ explains Ward. There is also potential to search for anti-cancer and autoimmune antibodies.
This ‘provides a new tool in the important task of analysing antibody responses to infection and to vaccination at a detailed molecular level,’ comments Dennis Burton, an immunologist at Scripps, who was not involved in the research. ‘This approach cuts out the monoclonal antibody generation step and looks directly at how mixtures of polyclonal antibodies bind to their target. The advantage is speed and an ability to see a fuller picture of what is happening in a response,’ he explains.
‘This is fantastic work,’ comments Rogier Sanders, a medical microbiologist at Amsterdam University Medical Centre, the Netherlands, adding that previously the polyclonal antibody response was seen as too heterogenous to be analysed by high-resolution structural biology methods. ‘It is a surprise to me that this was possible.’
He says the technique ‘tells you with one experiment what antibody specificities are elicited by a vaccine or pathogen, what epitopes are immunodominant, what epitopes are subdominant [and] provides atomic level detail on all these points’. This will allow for the redesign or improvement of vaccines ‘based on this one analysis,’ he adds. He is optimistic this will allow HIV-1 vaccine candidates from his own lab to be improved.
Image Credit: Kateryna Kon/Science Photo Library
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