R0: Host Longevity Matters

Infections of the lung: a predictive, preventive and personalized perspective through the lens of evolution, the emergence of SARS-CoV-2 and its pathogenesis

The long evolutionary battle between humans and pathogens has played an important role in shaping the current network of host-pathogen interactions. Each organ brings new challenges from the perspective of a pathogen to establish a suitable niche for survival while subverting the protective mechanisms of the host. Lungs, the organ for oxygen exchange, have been an easy target for pathogens due to its accessibility. The organ has evolved diverse capabilities to provide the flexibility required for an organism's health and at the same time maintain protective functionality to prevent and resolve assault by pathogens. The pathogenic invasions are strongly challenged by healthy lung architecture which includes the presence and activity of the epithelium, mucous, antimicrobial proteins, surfactants, and immune cells. Competitively, the pathogens in the form of viruses, bacteria, and fungi have evolved an arsenal of strategies that can over-ride the host's protective mechanisms. While bacteria such as Mycobacterium tuberculosis (M. tuberculosis) can survive in dormant form for years before getting active in humans, novel pathogens can wreak havoc as they pose a high risk of morbidity and mortality in a very short duration of time. Recently, a coronavirus strain SARS-CoV-2 has caused a pandemic which provides us an opportunity to look at the host manipulative strategies used by respiratory pathogens. Their ability to hide, modify, evade, and exploit cell's processes are key to their survival. While pathogens like M. tuberculosis have been infecting humans for thousands of years, SARS-CoV-2 has been the cause of the recent pandemic. Molecular understanding of the strategies used by these pathogens could greatly serve in design of predictive, preventive, personalized medicine (PPPM). In this article, we have emphasized on the clinically relevant evasive strategies of the pathogens in the lungs with emphasis on M. tuberculosis and SARS-CoV-2. The molecular basis of these evasive strategies illuminated through advances in genomics, cell, and structural biology can assist in the mapping of vulnerable molecular networks which can be exploited translationally. These evolutionary approaches can further assist in generating screening and therapeutic options for susceptible populations and could be a promising approach for the prediction, prevention of disease, and the development of personalized medicines. Further, tailoring the clinical data of COVID-19 patients with their physiological responses in light of known host-respiratory pathogen interactions can provide opportunities to improve patient profiling and stratification according to identified therapeutic targets.

A Mathematical Framework for Predicting Lifestyles of Viral Pathogens

Despite being similar in structure, functioning, and size, viral pathogens enjoy very different, usually well-defined ways of life. They occupy their hosts for a few days (influenza), for a few weeks (measles), or even lifelong (HCV), which manifests in acute or chronic infections. The various transmission routes (airborne, via direct physical contact, etc.), degrees of infectiousness (referring to the viral load required for transmission), antigenic variation/immune escape and virulence define further aspects of pathogenic lifestyles. To survive, pathogens must infect new hosts; the success determines their fitness. Infection happens with a certain likelihood during contact of hosts, where contact can also be mediated by vectors. Besides structural aspects of the host-contact network, three parameters appear to be key: the contact rate and the infectiousness during contact, which encode the mode of transmission, and third the immunity of susceptible hosts. On these grounds, what can be said about the reproductive success of viral pathogens? This is the biological question addressed in this paper. The answer extends earlier results of the author and makes explicit connection to another basic work on the evolution of pathogens. A mathematical framework is presented that models intra- and inter-host dynamics in a minimalistic but unified fashion covering a broad spectrum of viral pathogens, including those that cause flu-like infections, childhood diseases, and sexually transmitted infections. These pathogens turn out as local maxima of numerically simulated fitness landscapes. The models involve differential and integral equations, agent-based simulation, networks, and probability.