Wed, Aug 17, 2022: 2:45 PM-3:00 PM
520C
Background/Question/MethodsBiological monitoring methods based on environmental DNA (eDNA) have emerged to complement traditional methods. These eDNA methods allow for the non-invasive detection of species and the reconstruction of community assemblages, but the reliance on DNA limits their applications to species identifications. In contrast, the RNA molecule can provide an additional layer of functional information. Harnessing functional information from environmental RNA (eRNA) has recently been proposed as a non-invasive method for assessing the ecological health of communities and physiological status of organisms through gene expression profiling. We broadly define eRNA as the RNA extracted from the environment, which includes extra-organismal RNA (eoRNA) released by macroorganisms into the environment, as well as whole microorganisms. In this study, we test whether environmental transcriptomics, defined as eRNA based gene expression profiling, can provide functional insights into the ecological health of communities. We exposed to heat stress a simple freshwater community composed of bacterio- and phyto-plankton and the macro-zooplankton Daphnia pulex. We collected and sequenced eRNA (after the removal of Daphnia) as well as organismal RNA (oRNA) directly from Daphnia tissue, enabling comparisons between eRNA and oRNA based gene expression profiles.
Results/ConclusionsEnvironmental transcriptomics remained untested, despite recent work demonstrating the persistence and extractability of eoRNA from the environment. Our findings revealed that environmental transcriptomics is sensitive enough to detect the heat stress response of progenitor organisms in the absence of these organisms. From eoRNA, we detected thousands of Daphnia pulex genes and identified a subset of genes that were differentially expressed (DE) between the control and heat stress temperature conditions. These eoRNA identified DE genes exhibited similar levels of relative expression as their oRNA counterparts. Additionally, within all eRNA reads, we detected a community wide response including microorganism DE genes and a shift in protein groups and functional pathways as a response to the heat stress. Our study demonstrates that environmental transcriptomics can reveal the functional response of macro- and micro- organisms (both eukaryotic and prokaryotic) to heat stress. The capacity to infer the physiological states of organisms from non-invasive eRNA samples would represent a substantial improvement for animal welfare. We believe that environmental transcriptomics has broad potential implications for biological monitoring applications as it allows for the non-invasive monitoring of health for multi-trophic communities, and tracking of conditions at the ecosystem level.
Results/ConclusionsEnvironmental transcriptomics remained untested, despite recent work demonstrating the persistence and extractability of eoRNA from the environment. Our findings revealed that environmental transcriptomics is sensitive enough to detect the heat stress response of progenitor organisms in the absence of these organisms. From eoRNA, we detected thousands of Daphnia pulex genes and identified a subset of genes that were differentially expressed (DE) between the control and heat stress temperature conditions. These eoRNA identified DE genes exhibited similar levels of relative expression as their oRNA counterparts. Additionally, within all eRNA reads, we detected a community wide response including microorganism DE genes and a shift in protein groups and functional pathways as a response to the heat stress. Our study demonstrates that environmental transcriptomics can reveal the functional response of macro- and micro- organisms (both eukaryotic and prokaryotic) to heat stress. The capacity to infer the physiological states of organisms from non-invasive eRNA samples would represent a substantial improvement for animal welfare. We believe that environmental transcriptomics has broad potential implications for biological monitoring applications as it allows for the non-invasive monitoring of health for multi-trophic communities, and tracking of conditions at the ecosystem level.