Nicole Rivera-Espinal

Program: Molecular Microbiology and Microbial Pathogenesis

Current advisor: Carolina B. López, PhD

Undergraduate university: University of Puerto Rico-Cayey, 2019

Enrollment year: 2020

Research summary

The activation of interferon-stimulated genes (ISGs) by interferon during an infection is a crucial component of the innate immune response against respiratory viruses in the lung. These ISGs, which are upregulated from low basal to high functional levels, include antiviral effectors that target various stages of the viral lifecycle. Recent findings reveal that some ISGs are constitutively expressed at relatively high levels in lung cells, both in vivo and in vitro, independent of infection or immune stimulation. This suggests that basal ISG expression serves as a pre-existing defense against infections, providing early protection and potentially reducing the need for aggressive immune responses. However, most studies observing this pattern have been limited by poor temporal resolution, often providing only 1-2 data points, which restricts understanding of potential fluctuations in ISG expression, particularly in the context of biological rhythms that regulate the timed expression of innate immune processes. Our work aims to bridge this gap by conducting a granular 48-hour transcriptomic analysis of entrained A549 cells to examine ISG fluctuation profiles during that period. Our study revealed that key ISGs, including IFITM3, IFIT3, and MX1, exhibit a basal 12-hour oscillatory pattern. Interestingly, these oscillating ISGs are among the first to be transcriptionally activated during respiratory viral infections, suggesting their oscillatory profiles play a crucial role in maintaining immune readiness and enhancing host defense. Future work will explore the molecular basis of ISG basal expression and the influence of circadian and ultradian rhythms on infection outcomes, further elucidating the role of biological rhythms in immune response modulation.

Graduate publications
Achouri E, Felt SA, Hackbart M, Rivera-Espinal NS, López CB. 2023 VODKA2: a fast and accurate method to detect non-standard viral genomes from large RNA-seq data sets. RNA, 30(1):16-25. PMCID: PMC10726161