A critical issue to understanding how populations adapt to new selective pressures is the relative contribution of the initial standing genetic diversity versus that generated de novo. RNA viruses are an excellent model to study this question, as they form highly heterogeneous populations whose genetic diversity can be modulated by factors such as the number of generations, the size of population bottlenecks, or exposure to new environment conditions. In this work, we propagated at nonoptimal temperature (43 °C) two bacteriophage Qβ populations differing in their degree of heterogeneity. Deep sequencing analysis showed that, prior to the temperature change, the most heterogeneous population contained some low-frequency mutations that had previously been detected in the consensus sequences of other Qβ populations adapted to 43 °C. Evolved populations with origin in this ancestor reached similar growth rates, but the adaptive pathways depended on the frequency of these standing mutations and the transmission bottleneck size. In contrast, the growth rate achieved by populations with origin in the less heterogeneous ancestor did depend on the transmission bottleneck size. The conclusion is that viral diversification in a particular environment may lead to the emergence of mutants capable of accelerating adaptation when the environment changes.
The effect of a third vaccine dose (3D) of homologous mRNA vaccine on blood levels of SARS-CoV-2-receptor binding domain (RBD)-total antibodies was assessed in 40 hemodialysis patients (HD) and 21 kidney transplant recipients (KTR) at a median of 46 days after 3D. Anti-RBD antibodies were detected in 39/40 HD and 19/21 KTR. Overall, 3D boosted anti-RBD antibody levels (median: 58-fold increase). Neutralizing antibodies (NtAb) against the Wuhan-Hu-1, Delta, and Omicron variants were detected in 14, 13, and 11 out of 14 HD patients, and in 5, 5, and 4 out of 8 KTR patients, respectively. The median fold increase in NtAb titers in HD patients was 77, 28, and 5 and 56, 37, and 9 in KTR patients for each respective variant. SARS-CoV-2-S S-IFN-γ-producing CD8+ and CD4+ T-cell responses were detected in the majority of HD (35 and 36/37, respectively) and all KTR (16/16) patients at 3D. Overall, the administration of 3D boosted T-cell levels in both population groups. In conclusion, a homologous mRNA COVID-19 vaccine 3D exerts a booster effect on anti-RBD antibodies, NtAb binding to Wuhan-Hu-1, Delta, and Omicron variants, and SARS-CoV-2-S-IFN-γ-producing T cells in both HD and KTR patients. The magnitude of the effect was more marked in HD than KTR patients.
IntroductionHost density is one of the main factors affecting the infective capacity of viruses. When host density is low, it is more difficult for the virus to find a susceptible cell, which increases its probability of being damaged by the physicochemical agents of the environment. Nevertheless, viruses can adapt to variations in host density through different strategies that depend on the particular characteristics of the life cycle of each virus. In a previous work, using the bacteriophage Qβ as an experimental model, we found that when bacterial density was lower than optimal the virus increased its capacity to penetrate into the bacteria through a mutation in the minor capsid protein (A1) that is not described to interact with the cell receptor.ResultsHere we show that the adaptive pathway followed by Qβ in the face of similar variations in host density depends on environmental temperature. When the value for this parameter is lower than optimal (30°C), the mutation selected is the same as at the optimal temperature (37°C). However, when temperature increases to 43°C, the mutation selected is located in a different protein (A2), which is involved both in the interaction with the cell receptor and in the process of viral progeny release. The new mutation increases the entry of the phage into the bacteria at the three temperatures assayed. However, it also considerably increases the latent period at 30 and 37°C, which is probably the reason why it is not selected at these temperatures.ConclusionThe conclusion is that the adaptive strategies followed by bacteriophage Qβ, and probably other viruses, in the face of variations in host density depend not only on their advantages at this selective pressure, but also on the fitness costs that particular mutations may present in function of the rest of environmental parameters that influence viral replication and stability.
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