Evolutionary invasion and escape in the presence of deleterious mutations

Using phylogeographic link-prediction in primates to prioritize human parasite screening

Objectives

The ongoing risk of emerging infectious disease has renewed calls for understanding the origins of zoonoses and identifying future zoonotic disease threats. Given their close phylogenetic relatedness and geographic overlap with humans, non-human primates (NHPs) have been the source of many infectious diseases throughout human evolution. NHPs harbor diverse parasites, with some infecting only a single host species while others infect species from multiple families.

Materials and Methods

We applied a novel link-prediction method to predict undocumented instances of parasite sharing between humans and NHPs. Our model makes predictions based on phylogenetic distances and geographic overlap among NHPs and humans in six countries with high NHP diversity: Columbia, Brazil, Democratic Republic of Congo, Madagascar, China and Indonesia.

Results

Of the 899 human parasites documented in the Global Infectious Diseases and Epidemiology Network (GIDEON) database for these countries, 12% were shared with at least one other NHP species. The link prediction model identified an additional 54 parasites that are likely to infect humans but were not reported in GIDEON. These parasites were mostly host generalists, yet their phylogenetic host breadth varied substantially.

Discussion

As human activities and populations encroach on NHP habitats, opportunities for parasite sharing between human and non-human primates will continue to increase. Our study identifies specific infectious organisms to monitor in countries with high NHP diversity, while the comparative analysis of host generalism, parasite taxonomy, and transmission mode provides insights to types of parasites that represent high zoonotic risk.

Live animal markets: Identifying the origins of emerging infectious diseases

Emerging infectious diseases (EIDs) of zoonotic origin appear, affect a population and can spread rapidly. At the beginning of 2020, the World Health Organization pronounced an emergency public health advisory because of the SARS-CoV-2 coronavirus outbreak, and declared that COVID-19 had reached the level of a pandemic, rapidly spreading around the world. In order to identify one of the origins of EIDs, and propose some control alternatives, an extensive review was conducted of the available literature. The problem can originate in live animal markets, where animal species of all kinds, from different origins, ecosystems, and taxonomic groups are caged and crowded together, sharing the same unsanitary and unnatural space, food, water, and also the ecto- and endoparasitic vectors of disease. They defecate on each other, leading to the exchange of pathogenic and parasitic microorganisms, forcing interactions among species that should never happen. This is the ideal scenario for causing zoonoses and outbreaks of EIDs. We must start by stopping the illegal collection and sale of wild animals in markets. The destruction of ecosystems and forests also promote zoonoses and outbreaks of EIDs. Science and knowledge should be the basis of the decisions and policies for the development of management strategies. Wildlife belongs in its natural habitat, which must be defended, conserved, and restored at all costs.

Cross-scale dynamics and the evolutionary emergence of infectious diseases

When emerging pathogens encounter new host species for which they are poorly adapted, they must evolve to escape extinction. Pathogens experience selection on traits at multiple scales, including replication rates within host individuals and transmissibility between hosts. We analyze a stochastic model linking pathogen growth and competition within individuals to transmission between individuals. Our analysis reveals a new factor, the cross-scale reproductive number of a mutant virion, that quantifies how quickly mutant strains increase in frequency when they initially appear in the infected host population. This cross-scale reproductive number combines with viral mutation rates, single-strain reproductive numbers, and transmission bottleneck width to determine the likelihood of evolutionary emergence, and whether evolution occurs swiftly or gradually within chains of transmission. We find that wider transmission bottlenecks facilitate emergence of pathogens with short-term infections, but hinder emergence of pathogens exhibiting cross-scale selective conflict and long-term infections. Our results provide a framework to advance the integration of laboratory, clinical, and field data in the context of evolutionary theory, laying the foundation for a new generation of evidence-based risk assessment of emergence threats.

Expected Effect of Deleterious Mutations on Within-Host Adaptation of Pathogens

Adaptation is a common theme in both pathogen emergence, for example, in zoonotic cross-species transmission, and pathogen control, where adaptation might limit the effect of the immune response and antiviral treatment. When such evolution requires deleterious intermediate mutations, fitness ridges and valleys arise in the pathogen's fitness landscape. The effect of deleterious intermediate mutations on within-host pathogen adaptation is examined with deterministic calculations, appropriate for pathogens replicating in large populations with high error rates. The effect of deleterious intermediate mutations on pathogen adaptation is smaller than their name might suggest: when two mutations are required and each individual single mutation is fully deleterious, the pathogen can jump across the fitness valley by obtaining two mutations at once, leading to a proportion of adapted mutants that is 20-fold lower than that in the situation where the fitness of all mutants is neutral. The negative effects of deleterious intermediates are typically substantially smaller and outweighed by the fitness advantages of the adapted mutant. Moreover, requiring a specific mutation order has a substantially smaller effect on pathogen adaptation than the effect of all intermediates being deleterious. These results can be rationalized when the number of routes of mutation available to the pathogen is calculated, providing a simple approach to estimate the effect of deleterious mutations. The calculations discussed here are applicable when the effect of deleterious mutations on the within-host adaptation of pathogens is assessed, for example, in the context of zoonotic emergence, antigenic escape, and drug resistance.

IMPORTANCE

Adaptation is critical for pathogens after zoonotic transmission into a new host species or to achieve antigenic immune escape and drug resistance. Using a deterministic approach, the effects of deleterious intermediate mutations on pathogen adaptation were calculated while avoiding commonly made simplifications that do not apply to large pathogen populations replicating with high mutation rates. Perhaps unexpectedly, pathogen adaptation does not halt when the intermediate mutations are fully deleterious. The negative effects of deleterious mutations are substantially outweighed by the fitness gains of adaptation. To gain an understanding of the effect of deleterious mutations on pathogen adaptation, a simple approach that counts the number of routes available to the pathogen with and without deleterious intermediate mutations is introduced. This methodology enables a straightforward calculation of the proportion of the pathogen population that will cross a fitness valley or traverse a fitness ridge, without reverting to more complicated mathematical models.

The evolution and genetics of virus host shifts

Emerging viral diseases are often the product of a host shift, where a pathogen jumps from its original host into a novel species. Phylogenetic studies show that host shifts are a frequent event in the evolution of most pathogens, but why pathogens successfully jump between some host species but not others is only just becoming clear. The susceptibility of potential new hosts can vary enormously, with close relatives of the natural host typically being the most susceptible. Often, pathogens must adapt to successfully infect a novel host, for example by evolving to use different cell surface receptors, to escape the immune response, or to ensure they are transmitted by the new host. In viruses there are often limited molecular solutions to achieve this, and the same sequence changes are often seen each time a virus infects a particular host. These changes may come at a cost to other aspects of the pathogen's fitness, and this may sometimes prevent host shifts from occurring. Here we examine how these evolutionary factors affect patterns of host shifts and disease emergence.

Promise and reality in the expanding field of network interaction analysis: metabolic networks

In the last few decades, metabolic networks revealed their capabilities as powerful tools to analyze the cellular metabolism. Many research fields (eg, metabolic engineering, diagnostic medicine, pharmacology, biochemistry, biology and physiology) improved the understanding of the cell combining experimental assays and metabolic network-based computations. This process led to the rise of the “systems biology” approach, where the theory meets experiments and where two complementary perspectives cooperate in the study of biological phenomena. Here, the reconstruction of metabolic networks is presented, along with established and new algorithms to improve the description of cellular metabolism. Then, advantages and limitations of modeling algorithms and network reconstruction are discussed.