Transcriptomics of immunity and disease in African Fruit Bats- important zoonotic reservoirs - ABSTRACT
In line with the funding goals of the NIH and the objectives of the R21 research program, this project uses
the power of transcriptomics to understand bat immune competence in relation to viral infection in a natural,
variable environment. This project will be jointly led at Bucknell University by co-PD/PIs Dr. DeeAnn Reeder
(internationally recognized expert in bat disease and comparative physiology) and Dr. Ken Field (classically
trained immunologist with expertise in applying transcriptomic approaches to bat disease ecology). The goals
of this work are to explore how intrinsic (age, sex, reproductive condition, current disease status) and extrinsic
(seasonal shifts in weather and food availability) factors underlie immunological variation in African fruit bats,
reservoirs for viruses of pandemic potential (including Ebola) that are becoming increasingly associated with
people due to habitat modification. While important progress has been made in recent years in understanding
bat immunity, much of this has been in cell culture or from limited sampling, largely from SE Asian and
Australian bats; this study will fill this taxonomic and geographic gap and transform our understanding of
variation in antiviral immunity by examining immune processes in the real world.
To perform this work, male and female foraging bats will be collected at field sites in South Sudan during
both the rainy and dry season. For Specific Aim 1, spleen tissue samples will be used to determine the
differential expression (Illumina HiSeq 4000 platform and Trinity analysis pipeline) of genes involved in immune
function, with an emphasis on antiviral immunity. Findings will be confirmed in subsequent qPCR studies and
will be used to test the recently proposed hypothesis that bat antiviral gene expression is “always on”, which
may be related to reservoir capacity. Relationships found between intrinsic and extrinsic factors and immune
gene expression will be used to describe periods of low antiviral immunity, which may increase spillover risk.
For Specific Aim 2, gene expression in relation to diseased state will be analyzed for bats with exceptionally
high malarial parasite (Hepatocystis) loads or with high viral loads (surveying filoviruses, coronaviruses,
paramyxoviruses and orthomyxoviruses), compared to matched controls. For genes with differential
expression, qPCR will be used to look for similar changes in other tissues, matched to viral findings (e.g., high
viral load from oral swabs will prompt gene expression examination in salivary glands). Relationships between
gene expression and disease state will be interpreted in the context of the influence of co-infection (malaria)
and of viral infection on antiviral mechanisms. If our proposed specific aims are achieved, we will significantly
enhance our understanding of bat immunity and the factors that influence it under natural conditions. This will
improve our ability to predict when viral spillovers may be more likely and how changing environmental
conditions, including the anthropogenic alteration of natural landscapes, may alter disease processes.
