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Current Research

Scientific Overview


RG
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Robert Gifford, Ph.D.
Assistant Professor

Research in my lab addresses questions about the ecology and evolution of viruses. Like all infectious diseases, viral diseases are underpinned by ecological and evolutionary processes. The interactions between viruses and cells, for example, have been shaped by evolution over millions of years. Across shorter timescales, viral spread between and replication within host organisms are functions of population dynamics and selection. Gaining a better understanding of these processes will advance efforts to anticipate, control and treat outbreaks of viral disease.

Our research focuses on two distinct areas; paleovirology and genetic epidemiology. In our paleovirological research, we seek to infer the long-term evolutionary history of viruses. The genomes of humans and other vertebrates contain the remnants of thousands of sequences derived from ancient viruses. The advance of whole genome sequencing projects is enabling us to explore this 'molecular fossil record' in detail, providing us with novel insights into viral evolution. For example, through the discovery of an ancient retroviral fossil in the mouse lemur (Microcebus murinus) genome, we and our collaborators have shown that lentiviruses - the group of retroviruses that includes HIV - were present in Malagasy primates many millions of years ago. Similarly, our identification of an ancient spumavirus in the genome of the two-toed sloth (Choloepus hoffmanni) indicates that this group of viruses has cospeciated with their mammalian hosts for over 100 million years. By providing information about the background of host and virus evolution, these discoveries complement studies of virus-cell interaction such as those being conducted by other researchers at the Aaron Diamond Center, with whom we work closely.

Our work in genetic epidemiology involves the use of sequence-based strategies to investigate the temporal and spatial characteristics of epidemics. We have developed methods for tracking the spread of viruses using routinely sampled gene sequence data, and have used these methods to investigate how the structuring of the HIV-1 epidemic is changing over time. With our collaborators at Stanford, we have developed software tools to support sequence-based strategies for early detection of transmitted HIV-1 drug resistance in resource-limited countries. Current recent focusses on the development of software and information exchange infrastructure to facilitate the use of viral gene sequence data within public health and research.