Natural killer (NK) cells are lymphocytes of the innate immune system that, following differentiation from CD56^bright to CD56^dim cells, have been thought to retain fixed functional and phenotypic properties throughout their lifespan. In contrast to this notion, we here show that CD56^dim NK cells continue to differentiate. During this process, they lose expression of NKG2A, sequentially acquire inhibitory killer cell inhibitory immunoglobulin-like receptors and CD57, change their expression patterns of homing molecules, and display a gradual decline in proliferative capacity. All cellular intermediates of this process are represented in varying proportions at steady state and appear, over time, during the reconstitution of the immune system, as demonstrated in humanized mice and in patients undergoing hematopoietic stem cell transplantation. CD56^dim NK-cell differentiation, and the associated functional imprint, occurs independently of NK-cell education by interactions with self–human leukocyte antigen class I ligands and is an essential part of the formation of human NK-cell repertoires.

Influenza A virus (IAV) infection represents a global threat causing seasonal outbreaks and pandemics. Additionally, secondary bacterial infections, caused mainly by Streptococcus pneumoniae, are one of the main complications and responsible for the enhanced morbidity and mortality associated with IAV infections. In spite of the significant advances in our knowledge of IAV infections, holistic comprehension of the interplay between IAV and the host immune response (IR) remains largely fragmented. During the last decade, mathematical modeling has been instrumental to explain and quantify IAV dynamics. In this paper, we review not only the state of the art of mathematical models of IAV infection but also the methodologies exploited for parameter estimation. We focus on the adaptive IR control of IAV infection and the possible mechanisms that could promote a secondary bacterial coinfection. To exemplify IAV dynamics and identifiability issues, a mathematical model to explain the interactions between adaptive IR and IAV infection is considered. Furthermore, in this paper we propose a roadmap for future influenza research. The development of a mathematical modeling framework with a secondary bacterial coinfection, immunosenescence, host genetic factors and responsiveness to vaccination will be pivotal to advance IAV infection understanding and treatment optimization.

Quantitative PCR (Q-PCR) is a fast and efficient tool to quantify target genes. In eukaryotic cells, quantitative reverse transcription-PCR (Q-RT-PCR) is also used to quantify gene expression, with stably expressed housekeeping genes as standards. In bacteria, such stable expression of housekeeping genes does not occur, and the use of DNA standards leads to a broad underestimation. Therefore, an accurate quantification of RNA is feasible only by using appropriate RNA standards. We established and validated a Q-PCR method which enables the quantification of not only the number of copies of target genes (i.e., the number of bacterial cells) but also the number of RNA copies. The genes coding for InvA and the 16S rRNA of Salmonella enterica serovar Typhimurium were selected for the evaluation of the method. As DNA standards, amplified fragments of the target genes were used, whereas the same DNA standards were transcribed in vitro for the development of appropriate RNA standards. Salmonella cultures and environmental water samples inoculated with bacteria were then employed for the final testing. Both experimental approaches led to a sensitive, accurate, and reproducible quantification of the selected target genes and RNA molecules by Q-PCR and Q-RT-PCR. It is the first time that RNA standards have been successfully used for a precise quantification of the number of RNA molecules in prokaryotes. This demonstrates the potential of this approach for determining the presence and metabolic activity of pathogenic bacteria in environmental samples.