by Getty
Three years into the Covid-19 pandemic, it’s clear that some of us produce stronger immune responses to infection than others. Some may only experience mild flu-like symptoms, while others may be hospitalized or worse. Recent research suggests that there is more to humans’ variable ability to control infections than pure chance. Common variations in immune-related genes strongly influence our immune responses to invading pathogens, including SARS-CoV-2.
Antibodies inherit their structure from the germline locus of the genetic Ig. The exact physical structure of the antibody is determined by the patient’s genetic predispositions, which is why one patient can develop much more effective antibodies than another, even if infected with the same virus at the same time.
FIGURE 1: Antibody structure and genetic coding.
After exposure to Covid-19, our immune system develops antibodies specifically adapted against the virus. These antibodies are highly variable in their effectiveness. pushparaj and others shed some light on this variation. They found that small differences in our genes and the antibody genes we inherit can also influence the structure and effectiveness of the antibodies we develop after infections. Here, we discuss the implications of their findings and how we can use this data to better inform future antibody discovery efforts.
Change measured in response to Covid-19 infection
Researchers drew serum from 14 healthcare workers seven months after their May 2020 infections. All patients developed antibodies against SARS-CoV-2, but across a wide range of genetic diversity. Antibodies are encoded by B cell receptor sequences, which often vary significantly, leading to significant genetic diversity of antibodies produced.
From the sera, they analyzed individual antibodies. From these antibody structures, they could determine the exact inherited germline, that is, every single genetic detail of the sequence that would encode the antibody. By analyzing each allele individually, they were able to compare the relative presence in neutralizing antibodies.
They found that the number of coded alleles added up to between 44 and 61 per patient. One of the most critical alleles for antibody potency, IGHV1-69, showed six variants among the 14 patients: IGHV1-69∗01, ∗02, ∗04, ∗06, ∗09, and ∗20. This will be the focus of Pushparaj and othersare moving forward, as they aim to understand the impact of genetic polymorphisms on the effectiveness of antibodies.
FIGURE 2: A summary graph showing which IGHV1-69 alleles were present in each study participant.
The effectiveness of antibodies is related to genetic variation
Using sera from SP14, a patient who had the IGHV1-69∗01, IGHV1-69∗02 and IGHV1-69∗20 alleles, the researchers generated several heavy and light chains. These are the building blocks of antibodies. From that single patient, they generated 29 spike-specific monoclonal antibodies, 15 of which were neutralizing against wild-type SARS-CoV-2. All those that neutralized bound the virus receptor binding domain.
Notably, most neutralizing antibodies used a variation of IGHV1-69, specifically IGHV1-69∗02 or IGHV1-69∗20. To reiterate, these patients had between 44 and 61 alleles each. Still, a variation of IGHV1-69 was found in the vast majority of neuralizing antibodies in this particular patient, reinforcing the notion that this specific allele is critical for the development of potent neutralizing antibodies in the immune system.
However, IGHV1-69 has allelic variation. Each variant allele may contain one or more somatic hypermutations that make it different from the others. These small genetic variations in the alleles, once encoded in a monoclonal antibody, can account for some or all of the antibody’s neutralizing ability, or lack thereof.
The use of the IGHV1-69 allele influences the neutralization of antibody activity
Next, they tested the value of somatic hypermutations (SHMs) in the allele for the ultimate neutralization of the produced antibody. In other words, do mutations in the important alleles make a difference? pushparaj and others found that by removing the SHMs from the IGHV1-69∗20 allele found in patient SP14, the resulting antibody lost its neutralizing capacity against SARS-CoV-2.
They repeated this process with all other variations of IGHV1-69 and found similar results. In essence, SHMs are critical to neutralizing capability.
FIGURE 3: The neutralizing activity of the variant mAbs against the ancestral SARS-CoV-2 strain is shown … (+)
Structural analysis reveals basis for IGHV allele requirement
To better understand why certain hypermutational somatic differences in specific alleles are so important, the researchers performed a cryoelectron microscopy analysis of the previous antibody in question: CAB-I47. They wanted to see up close the binding differences between the antibody produced from the SHM and non-SHM alleles.
FIGURE 4: Molecular details of the interaction of CAB-I47 Fab and RBD with important residues for the … (+)
Like many monoclonal antibodies, CAB-I47 makes contact with the receptor binding domain to block binding to the human ACE2 receptor. There are some critical contacts between the antibody and the receptor binding domain, most notably the interaction between R50 of the antibody and E484 and G482 of the receptor binding domain.
One amino acid can make a big difference. A single amino acid variation in inherited structure can produce a significant difference in antibody binding and neutralizing. R50 is variable between different versions of the IGHV1-69. Some transform arginine (R) into glycine (G), while others leave it intact. The R50G mutation appears to be to blame for the loss of neutralizing activity, as the unmutated version forms hydrogen bonds and salt bridges between the virus and the antibody.
Discussion
This is just a single example of a small germline variation in the antibody completely reducing the neutralizing ability of a candidate antibody. There are probably thousands, if not millions, of equally crucial allele modifications that can make or break a potential monoclonal antibody. Not only can small variations negatively impact an antibody, but they can also dramatically improve neutralizing effectiveness.
How can we identify and maximize these small differences to our advantage? We recently detailed an AI engine designed to do just that; it identifies and tests small antibody variations to identify the most potent germline sequence possible. It is conceivable that allele genetic variation could be incorporated into this mechanism to further optimize the system. We can only hope that such a process will be implemented soon, as hundreds of people succumb to Covid-19, in desperate need of effective monoclonal drugs to fight this disease.
