Microbiology Spectrum

In this review, which is a part of the Microbiology Spectrum Curated Collection: Advances in Molecular Epidemiology of Infectious Diseases, I present an overview of the principles used to classify organisms in the field of phylogenetics, highlight the methods used to infer the interrelationships of organisms, and summarize how these concepts are applied to molecular epidemiologic analyses. I present steps in analyses that come downstream of the assembly of a set of genomes or genes and the production of a multiple-sequence alignment or other matrices of putative orthologs for comparison. I focus on the history of the problem of phylogenetic reconstruction and debates within the field about the most appropriate methods. I illustrate methods that bridge the gap between molecular epidemiology and traditional epidemiology, including phylogenetic character evolution and geographic visualization. Finally, I provide practical advice on how to conduct an example analysis in the appendix.

One important scope of work of epidemiology is the investigation of infectious diseases that cluster in time and place. Clusters of infectious disease may represent outbreaks or epidemics in which the cases share in common a point source exposure or an infectious agent in a chain of transmission pathways. Investigations of outbreaks of an illness can facilitate identification of a source, risk, or cause of the illness. However, most infectious disease episodes occur not as part of any apparent outbreaks but as sporadic infections. Multiple sporadic infections that occur steadily in time and place are referred to as endemic disease. How does one investigate sources and risk factors for sporadic or endemic infections? As part of the Microbiology Spectrum Curated Collection: Advances in Molecular Epidemiology of Infectious Diseases, this review discusses limitations of traditional approaches and advantages of molecular epidemiology approaches to investigate sporadic and endemic infections. Using specific examples, the discussions show that most sporadic infections are actually part of unrecognized outbreaks and that what appears to be endemic disease occurrence is actually comprised of multiple small outbreaks. These molecular epidemiologic investigations have unmasked modes of transmission of infectious agents not known to cause outbreaks. They have also raised questions about the traditional ways to measure incidence and assess sources of drug-resistant infections in community settings. The discoveries made by the application of molecular microbiology methods in epidemiologic investigations have led to creation of new public health intervention strategies that have not been previously considered.

The MinION sequencer was launched by the Oxford Nanopore Technologies start-up as a disruptive technology for genome sequencing based on single-molecule synthesis. Its characteristics as a portable device, low cost, and simple library preparation have made it a good candidate for field researchers. MinION has been used to sequence a number of microorganisms, such as bacteria, viruses, and fungi. Based on the experience that characterized the Ebola virus genetic diversity in Guinea during the 2014-2015 outbreak, the ZiBRA (Zika in Brazil Real-time Analysis) project aimed to sequence a large number of Zika virus genomes during a mobile laboratory trip in northeast Brazil to provide important epidemiological information about the spread of this disease in this country. In response to the positive and rapid results obtained by the ZiBRA project, the Brazilian Ministry of Health and many leading institutions, such as the Pan American Health Organization and WHO, have shown interest in expanding the strategy used in this project to other countries dealing with arbovirus infection.

While disease and outbreaks are mainly clonal for bacteria and other asexually reproducing organisms, sexual reproduction in schistosomes and other helminths usually results in unique individuals. For sexually reproducing organisms, the traits conserved in clones will instead be conserved in the group of organisms that tends to breed together, the population. While the same tools are applied to characterize DNA, how results are interpreted can be quite different at times (see another article in this collection, http://www.asmscience.org/content/journal/microbiolspec/10.1128/microbiolspec.AME-0002-2018). It is difficult to know what the real effect any control program has on the parasite population without assessing the health of this population, how they respond to the control measure, and how they recover, if they do. This review, part of the Microbiology Spectrum Curated Collection: Advances in Molecular Epidemiology of Infectious Diseases, concentrates on one approach using pooled samples to study schistosome populations and shows how this and other approaches have contributed to our understanding of this parasite family’s biology and epidemiology.

Malaria is a vector-borne disease that involves multiple parasite species in a variety of ecological settings. However, the parasite species causing the disease, the prevalence of subclinical infections, the emergence of drug resistance, the scale-up of interventions, and the ecological factors affecting malaria transmission, among others, are aspects that vary across areas where malaria is endemic. Such complexities have propelled the study of parasite genetic diversity patterns in the context of epidemiologic investigations. Importantly, molecular studies indicate that the time and spatial distribution of malaria cases reflect epidemiologic processes that cannot be fully understood without characterizing the evolutionary forces shaping parasite population genetic patterns. Although broad in scope, this review in the Microbiology Spectrum Curated Collection: Advances in Molecular Epidemiology highlights the need for understanding population genetic concepts when interpreting parasite molecular data. First, we discuss malaria complexity in terms of the parasite species involved. Second, we describe how molecular data are changing our understanding of malaria incidence and infectiousness. Third, we compare different approaches to generate parasite genetic information in the context of epidemiologically relevant questions related to malaria control. Finally, we describe a few Plasmodium genomic studies as evidence of how these approaches will provide new insights into the malaria disease dynamics.

The mammalian nervous system is invaded by a number of intracellular bacterial pathogens which can establish and progress infection in susceptible individuals. Subsequent clinical manifestation is apparent with the impairment of the functional units of the nervous system, i.e., the neurons and the supporting glial cells that produce myelin sheaths around axons and provide trophic support to axons and neurons. Most of these neurotrophic bacteria display unique features, have coevolved with the functional sophistication of the nervous system cells, and have adapted remarkably to manipulate neural cell functions for their own advantage. Understanding how these bacterial pathogens establish intracellular adaptation by hijacking endogenous pathways in the nervous system, initiating myelin damage and axonal degeneration, and interfering with myelin maintenance provides new knowledge not only for developing strategies to combat neurodegenerative conditions induced by these pathogens but also for gaining novel insights into cellular and molecular pathways that regulate nervous system functions. Since the pathways hijacked by bacterial pathogens may also be associated with other neurodegenerative diseases, it is anticipated that detailing the mechanisms of bacterial manipulation of neural systems may shed light on common mechanisms, particularly of early disease events. This chapter details a classic example of neurodegeneration, that caused by Mycobacterium leprae, which primarily infects glial cells of the peripheral nervous system (Schwann cells), and how it targets and adapts intracellularly by reprogramming Schwann cells to stem cells/progenitor cells. We also discuss implications of this host cell reprogramming by leprosy bacilli as a model in a wider context.