This is a new application for an R01 grant to establish the intellectual and technical framework to permit the study of viral infection on the single-cell level to be as tractable as the study of viral infection on the population level using the plaque assay. The world is ill equipped to deal with the (re)emergence of diseases caused by RNA viruses. The viral RNA genome is replicated by the virus-encoded RNA-dependent RNA polymerase (RdRp), an enzyme that, in most cases, lacks proofreading activity and a cellular repair mechanism to usurp. As a result, each progeny genome differs from another in the population by one or more nucleotide changes. The Cameron laboratory and colleagues have discovered that the genetic diversity created by replication errors made by the RdRp permits the virus to clear bottlenecks that would otherwise lead to viral extinction. Therefore, it is becoming increasingly clear that attenuated viruses for use as vaccine strains can be created by altering the nucleotide incorporation fidelity of the RdRp. Unexpectedly, the Cameron laboratory has observed that using conventional approaches to study this class of vaccine candidate in cell culture masks the attenuated phenotype. The attenuated phenotype is only observed by evaluating the infection at the level of the single cell instead of the population. This observatio motivated the development of techniques to study viral infection on the single-cell level. Our foray into this area was funded by the PSU Huck Institutes of the Life Sciences. In this proposal, we present a set of experimental objectives that will move single-cell virology from a descriptive art to a quantitative science that can be implemented broadly by the virology community not only to understand viral population dynamics but to reveal between-individual differences that may underlie susceptibility to viral infection. Importantly, this technology is essential to advancing RdRp fidelity as a target and mechanism for viral attenuation and vaccine development, thereby addressing an urgent public-health need. We will, therefore, pursue the following specific aims: (1) Elucidate parameters governing diverse kinetics of viral genome replication at the single-cell level; (2) Establish a data and statistical analysis pipeline for th single-cell virology experiment and develop mechanistic models of infection; and (3) Enhance capabilities of the microfluidic platform for characterization of viral infections at the single-cel level.
The overarching objective of this proposal is to create the technical and intellectual advances necessary to make the practice of single-cell virology readily accessible to the virology community. The ability to characterize an infection at this level may be the only approach that will permit connections to be made regarding viral genotype and an attenuated phenotype and/or a host genotype/transcriptome to a host-susceptibility phenotype. This fundamental knowledge will be essential to the successful implementation of any paradigm of personalized medicine with a goal of predicting susceptibility to viral infection or developing personalized prophylactic or therapeutic regimen.
| Lee, Dong Jun; Mai, John; Huang, Tony Jun (2018) Microfluidic approaches for cell-based molecular diagnosis. Biomicrofluidics 12:051501 |
| Ozcelik, Adem; Rufo, Joseph; Guo, Feng et al. (2018) Acoustic tweezers for the life sciences. Nat Methods 15:1021-1028 |
| Caglar, M Umut; Teufel, Ashley I; Wilke, Claus O (2018) Sicegar: R package for sigmoidal and double-sigmoidal curve fitting. PeerJ 6:e4251 |
| Guo, Feng; Li, Sixing; Caglar, Mehmet Umut et al. (2017) Single-Cell Virology: On-Chip Investigation of Viral Infection Dynamics. Cell Rep 21:1692-1704 |
| Jackson, Eleisha L; Spielman, Stephanie J; Wilke, Claus O (2017) Computational prediction of the tolerance to amino-acid deletion in green-fluorescent protein. PLoS One 12:e0164905 |
| Teufel, Ashley I; Wilke, Claus O (2017) Accelerated simulation of evolutionary trajectories in origin-fixation models. J R Soc Interface 14: |
| Li, Sixing; Ma, Fen; Bachman, Hunter et al. (2017) Acoustofluidic bacteria separation. J Micromech Microeng 27: |
| Echave, Julian; Wilke, Claus O (2017) Biophysical Models of Protein Evolution: Understanding the Patterns of Evolutionary Sequence Divergence. Annu Rev Biophys 46:85-103 |
| Caglar, Mehmet U; Houser, John R; Barnhart, Craig S et al. (2017) The E. coli molecular phenotype under different growth conditions. Sci Rep 7:45303 |
| Li, Sixing; Ren, Liqiang; Huang, Po-Hsun et al. (2016) Acoustofluidic Transfer of Inflammatory Cells from Human Sputum Samples. Anal Chem 88:5655-61 |
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