Phylogenetic Concepts and Tools Applied to Epidemiologic Investigations of Infectious Diseases

Fundamentals of genomic epidemiology, lessons learned from the coronavirus disease 2019 (COVID-19) pandemic, and new directions

The coronavirus disease 2019 (COVID-19) pandemic was one of the significant causes of death worldwide in 2020. The disease is caused by severe acute coronavirus syndrome (SARS) coronavirus 2 (SARS-CoV-2), an RNA virus of the subfamily Orthocoronavirinae related to 2 other clinically relevant coronaviruses, SARS-CoV and MERS-CoV. Like other coronaviruses and several other viruses, SARS-CoV-2 originated in bats. However, unlike other coronaviruses, SARS-CoV-2 resulted in a devastating pandemic. The SARS-CoV-2 pandemic rages on due to viral evolution that leads to more transmissible and immune evasive variants. Technology such as genomic sequencing has driven the shift from syndromic to molecular epidemiology and promises better understanding of variants. The COVID-19 pandemic has exposed critical impediments that must be addressed to develop the science of pandemics. Much of the progress is being applied in the developed world. However, barriers to the use of molecular epidemiology in low- and middle-income countries (LMICs) remain, including lack of logistics for equipment and reagents and lack of training in analysis. We review the molecular epidemiology literature to understand its origins from the SARS epidemic (2002-2003) through influenza events and the current COVID-19 pandemic. We advocate for improved genomic surveillance of SARS-CoV and understanding the pathogen diversity in potential zoonotic hosts. This work will require training in phylogenetic and high-performance computing to improve analyses of the origin and spread of pathogens. The overarching goals are to understand and abate zoonosis risk through interdisciplinary collaboration and lowering logistical barriers.

Genetic capitalism and stabilizing selection of antimicrobial resistance genotypes in Escherichia coli

Antimicrobial resistance (AMR) in pathogenic strains of bacteria, such as Escherichia coli (E. coli), adversely impacts personal and public health. In this study, we examine competing hypotheses for the evolution of AMR including (i) 'genetic capitalism' in which genotypes that confer antibiotic resistance are gained and not often lost in lineages, and (ii) 'stabilizing selection' in which genotypes that confer antibiotic resistance are gained and lost often. To test these hypotheses, we assembled a dataset that includes annotations for 409 AMR genotypes and a phylogenetic tree based on genome-wide single nucleotide polymorphisms from 29 255 isolates of E. coli collected over the past 134 years. We used phylogenetic methods to count the times each AMR genotype was gained and lost across the tree and used model-based clustering of the genotypes with respect to their gain and loss rates. We demonstrate that many genotypes cluster to support the hypothesis for genetic capitalism while a few genotypes cluster to support the hypothesis for stabilizing selection. Comparing the sets of genotypes that fall under each of the hypotheses, we found a statistically significant difference in the breakdown of resistance mechanisms through which the AMR genotypes function. The result that many AMR genotypes cluster under genetic capitalism reflects that strong positive selective forces, primarily induced by human industrialization of antibiotics, outweigh the potential fitness costs to the bacterial lineages for carrying the AMR genotypes. We expect genetic capitalism to further drive bacterial lineages to resist antibiotics. We find that antibiotics that function via replacement and efflux tend to behave under stabilizing selection and thus may be valuable in an antibiotic cycling strategy.