Appropriate Sampling and Longer Follow-Up Are Required to Rigorously Evaluate Longevity of Humoral Memory After Vaccination.

One of the goals of vaccination is to induce long-lived immunity against the infection and/or disease. Many studies have followed the generation of humoral immunity to SARS-CoV-2 after vaccination; however, such studies typically varied by the duration of the follow-up and the number of time points at which immune response measurements were done. How these parameters (the number of time points and the overall duration of the follow-up) impact estimates of immunity longevity remain largely unknown. Several studies, including one by Arunachalam et al. (2023. J. Clin. Invest. 133: e167955), evaluated the humoral immune response in individuals receiving either a third or fourth dose of mRNA COVID-19 vaccine; by measuring Ab levels at three time points (prior to vaccination and at 1 and 6 mo), Arunachalam et al. found similar half-life times for serum Abs in the two groups and thus suggested that additional boosting is unnecessary to prolong immunity to SARS-CoV-2. I demonstrate that measuring Ab levels at these three time points and only for 6 mo does not allow one to accurately evaluate the long-term half-life of vaccine-induced Abs. By using the data from a cohort of blood donors followed for several years, I show that after revaccination with vaccinia virus, vaccinia virus-specific Abs decay biphasically, and even the late decay rate exceeds the true slow loss rate of humoral memory observed years prior to the boosting. Mathematical models of Ab response kinetics, parameterized using preliminary data, should be used for power analysis to determine the most appropriate timing and duration of sampling to rigorously determine the duration of humoral immunity after vaccination.

Mathematical modeling suggests heterogeneous replication of Mycobacterium tuberculosis in rabbits.

Tuberculosis (TB), the disease caused by Mycobacterium tuberculosis (Mtb), remains a major health problem with 10.6 million cases of the disease and 1.6 million deaths in 2021. It is well understood that pulmonary TB is due to replication of Mtb in the lung but quantitative details of Mtb replication and death in lungs of patients and how these rates are related to the degree of lung pathology are unknown. We performed experiments with rabbits infected with a novel, virulent clinical Mtb isolate of the Beijing lineage, HN878, carrying an unstable plasmid pBP10. In our in vitro experiments we found that pBP10 is more stable in HN878 strain than in a more commonly used laboratory-adapted Mtb strain H37Rv (the segregation coefficient being s=0.10 in HN878 vs. s=0.18 in H37Rv). Interestingly, the kinetics of plasmid-bearing bacteria in lungs of Mtb-infected rabbits did not follow an expected monotonic decline; the percent of plasmid-bearing cells increased between 28 and 56 days post-infection and remained stable between 84 and 112 days post-infection despite a large increase in bacterial numbers in the lung at late time points. Mathematical modeling suggested that such a non-monotonic change in the percent of plasmid-bearing cells can be explained if the lung Mtb population consists of several (at least 2) sub-populations with different replication/death kinetics: one major population expanding early and being controlled/eliminated, while another, a smaller population expanding at later times causing a counterintuitive increase in the percent of plasmid-bearing cells. Given that HN878 forms well circumscribed granulomas in rabbits, our results suggest independent bacterial dynamics in subsets of such granulomas. Our model predictions can be tested in future experiments in which HN878-pBP10 dynamics in individual granulomas is followed over time.