Particle size influences decay rates of environmental DNA in aquatic systems.
ddPCR
degradation
eDNA ecology
modelling
monitoring
removal rates
Journal
Molecular ecology resources
ISSN: 1755-0998
Titre abrégé: Mol Ecol Resour
Pays: England
ID NLM: 101465604
Informations de publication
Date de publication:
May 2023
May 2023
Historique:
revised:
19
12
2022
received:
08
07
2022
accepted:
28
12
2022
medline:
6
4
2023
pubmed:
13
1
2023
entrez:
12
1
2023
Statut:
ppublish
Résumé
Environmental DNA (eDNA) analysis is a powerful tool for remote detection of target organisms. However, obtaining quantitative and longitudinal information from eDNA data is challenging, requiring a deep understanding of eDNA ecology. Notably, if the various size components of eDNA decay at different rates, and we can separate them within a sample, their changing proportions could be used to obtain longitudinal dynamics information on targets. To test this possibility, we conducted an aquatic mesocosm experiment in which we separated fish-derived eDNA components using sequential filtration to evaluate the decay rate and changing proportion of various eDNA particle sizes over time. We then fit four alternative mathematical decay models to the data, building towards a predictive framework to interpret eDNA data from various particle sizes. We found that medium-sized particles (1-10 μm) decayed more slowly than other size classes (i.e., <1 and > 10 μm), and thus made up an increasing proportion of eDNA particles over time. We also observed distinct eDNA particle size distribution (PSD) between our Common carp and Rainbow trout samples, suggesting that target-specific assays are required to determine starting eDNA PSDs. Additionally, we found evidence that different sizes of eDNA particles do not decay independently, with particle size conversion replenishing smaller particles over time. Nonetheless, a parsimonious mathematical model where particle sizes decay independently best explained the data. Given these results, we suggest a framework to discern target distance and abundance with eDNA data by applying sequential filtration, which theoretically has both metabarcoding and single-target applications.
Identifiants
pubmed: 36633071
doi: 10.1111/1755-0998.13751
doi:
Substances chimiques
DNA, Environmental
0
DNA
9007-49-2
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
756-770Subventions
Organisme : U.S. Department of Defense
ID : SERDP/RC191276
Organisme : Rice University
Organisme : Research and Development
ID : RC19-1276
Informations de copyright
© 2023 John Wiley & Sons Ltd.
Références
Agrawal, Y. C., & Pottsmith, H. C. (2000). Instruments for particle size and settling velocity observations in sediment transport. Marine Geology, 168(1-4), 89-114.
Andruszkiewicz, A. E., Zhang, W. G., Lavery, A. C., & Govindarajan, A. F. (2021). Environmental DNA shedding and decay rates from diverse animal forms and thermal regimes. Environmental DNA, 3(2), 492-514.
Barnes, M. A., Chadderton, W. L., Jerde, C. L., Mahon, A. R., Turner, C. R., & Lodge, D. M. (2021). Environmental conditions influence eDNA particle size distribution in aquatic systems. Environmental DNA, 3(3), 643-653.
Barnes, M. A., & Turner, C. R. (2016). The ecology of environmental DNA and implications for conservation genetics. Conservation Genetics, 17, 1-17.
Baudry, T., Mauvisseau, Q., Goût, J. P., Arqué, A., Delaunay, C., Smith-Ravin, J., Sweet, M., & Grandjean, F. (2021). Mapping a super-invader in a biodiversity hotspot, an eDNA-based success story. Ecological Indicators, 126, 107637.
Beng, K. C., & Corlett, R. T. (2020). Applications of environmental DNA (eDNA) in ecology and conservation: Opportunities, challenges and prospects. Biodiversity and Conservation, 29(7), 2089-2121.
Burnham, K. P., & Anderson, D. R. (2004). Multimodel inference: Understanding AIC and BIC in model selection. Sociological Methods & Research, 33(2), 261-304.
Bylemans, J., Furlan, E. M., Gleeson, D. M., Hardy, C. M., & Duncan, R. P. (2018). Does size matter? An experimental evaluation of the relative abundance and decay rates of aquatic environmental DNA. Environmental Science & Technology, 52(11), 6408-6416.
Byrd, R. H., Hribar, M. E., & Nocedal, J. (1999). An interior point algorithm for large-scale nonlinear programming. SIAM Journal on Optimization, 9(4), 877-900.
Byrd, R. H., Schnabel, R. B., & Shultz, G. A. (1988). Approximate solution of the trust region problem by minimization over two-dimensional subspaces. Mathematical Programming, 40(1), 247-263.
Carraro, L., Mächler, E., Wüthrich, R., & Altermatt, F. (2020). Environmental DNA allows upscaling spatial patterns of biodiversity in freshwater ecosystems. Nature Communications, 11(1), 1-12.
Carraro, L., Stauffer, J. B., & Altermatt, F. (2021). How to design optimal eDNA sampling strategies for biomonitoring in river networks. Environmental DNA, 3(1), 157-172.
Cavanaugh, J. E. (1997). Unifying the derivations for the Akaike and corrected Akaike information criteria. Statistics & Probability Letters, 33(2), 201-208.
Cooper, M. K., Villacorta-Rath, C., Burrows, D., Jerry, D. R., Carr, L., Barnett, A., Huveneers, C., & Simpfendorfer, C. A. (2022). Practical eDNA sampling methods inferred from particle size distribution and comparison of capture techniques for a Critically Endangered elasmobranch. Environmental DNA, 4(5), 1011-1023.
Coyne, K. J., Handy, S. M., Demir, E., Whereat, E. B., Hutchins, D. A., Portune, K. J., Doblin, M. A., & Cary, S. C. (2005). Improved quantitative real-time PCR assays for enumeration of harmful algal species in field samples using an exogenous DNA reference standard. Limnology and Oceanography: Methods, 3(9), 381-391.
Deiner, K., Bik, H. M., Mächler, E., Seymour, M., Lacoursière-Roussel, A., Altermatt, F., Creer, S., Bista, I., Lodge, D. M., de Vere, N., Pfrender, M. E., & Bernatchez, L. (2017). Environmental DNA metabarcoding: Transforming how we survey animal and plant communities. Molecular Ecology, 26(21), 5872-5895.
Deiner, K., Lopez, J., Bourne, S., Holman, L. E., Seymour, M., Grey, E. K., Lacoursière-Roussel, A., Li, Y., Renshaw, M., Pfrender, M., Rius, M., Bernatchez, L., & Lodge, D. M. (2018). Optimising the detection of marine taxonomic richness using environmental DNA metabarcoding: The effects of filter material, pore size and extraction method. Metabarcoding and Metagenomics, 2, e28963.
Dougherty, M. M., Larson, E. R., Renshaw, M. A., Gantz, C. A., Egan, S. P., Erickson, D. M., & Lodge, D. M. (2016). Environmental DNA (eDNA) detects the invasive rusty crayfish Orconectes rusticus at low abundances. Journal of Applied Ecology, 53(3), 722-732.
Drummond, J. A., Larson, E. R., Li, Y., Lodge, D. M., Gantz, C. A., Pfrender, M. E., Renshaw, M. A., Correa, A. M. S., & Egan, S. P. (2021). Diversity metrics are robust to differences in sampling location and depth for environmental DNA of plants in small Temperate Lakes. Frontiers in Environmental Science, 9, 617924.
Duda, J. J., Hoy, M. S., Chase, D. M., Pess, G. R., Brenkman, S. J., McHenry, M. M., & Ostberg, C. O. (2021). Environmental DNA is an effective tool to track recolonizing migratory fish following large-scale dam removal. Environmental DNA, 3(1), 121-141.
Fukaya, K., Murakami, H., Yoon, S., Minami, K., Osada, Y., Yamamoto, S., Masuda, R., Kasai, A., Miyashita, K., Minamoto, T., & Kondoh, M. (2021). Estimating fish population abundance by integrating quantitative data on environmental DNA and hydrodynamic modelling. Molecular Ecology, 30(13), 3057-3067.
Gabriel, M. N., Huffine, E. F., Ryan, J. H., Holland, M. M., & Parsons, T. J. (2001). Improved MtDNA sequence analysis of forensic remains using a “mini-primer set” amplification strategy. Journal of Forensic Science, 46(2), 247-253.
Gantz, C. A., Renshaw, M. A., Erickson, D., Lodge, D. M., & Egan, S. P. (2018). Environmental DNA detection of aquatic invasive plants in lab mesocosm and natural field conditions. Biological Invasions, 20(9), 2535-2552.
Hansen, B. K., Bekkevold, D., Clausen, L. W., & Nielsen, E. E. (2018). The sceptical optimist: Challenges and perspectives for the application of environmental DNA in marine fisheries. Fish and Fisheries, 19, 751-768.
Hansen, B. K., Jacobsen, M. W., Middelboe, A. L., Preston, C. M., Marin, R., Bekkevold, D., Knudsen, S. W., Møller, P. R., & Nielsen, E. E. (2020). Remote, autonomous real-time monitoring of environmental DNA from commercial fish. Scientific Reports, 10(1), 13272.
Huggett, J. F. (2020). The digital MIQE guidelines update: Minimum information for publication of quantitative digital PCR experiments for 2020. Clinical Chemistry, 66(8), 1012-1029.
Jerde, C. L., Chadderton, W. L., Mahon, A. R., Renshaw, M. A., Corush, J., Budny, M. L., Mysorekar, S., & Lodge, D. M. (2013). Detection of Asian carp DNA as part of a Great Lakes basin-wide surveillance program. Canadian Journal of Fisheries and Aquatic Sciences, 70(4), 522-526.
Jo, T., Arimoto, M., Murakami, H., Masuda, R., & Minamoto, T. (2019). Particle size distribution of environmental DNA from the nuclei of marine fish. Environmental Science & Technology, 53(16), 9947-9956.
Jo, T., & Minamoto, T. (2021). Complex interactions between environmental DNA (eDNA) state and water chemistries on eDNA persistence suggested by meta-analyses. Molecular Ecology Resources, 21(5), 1490-1503.
Jo, T., Murakami, H., Masuda, R., & Minamoto, T. (2020). Selective collection of long fragments of environmental DNA using larger pore size filter. Science of the Total Environment, 735, 139462.
Jo, T., Murakami, H., Masuda, R., Sakata, M. K., Yamamoto, S., & Minamoto, T. (2017). Rapid degradation of longer DNA fragments enables the improved estimation of distribution and biomass using environmental DNA. Molecular Ecology Resources, 17(6), e25-e33.
Jürgens, K., & Matz, C. (2002). Predation as a shaping force for the phenotypic and genotypic composition of planktonic bacteria. Antonie Van Leeuwenhoek, 81(1), 413-434.
Klymus, K. E., Merkes, C. M., Allison, M. J., Goldberg, C. S., Helbing, C. C., Hunter, M. E., Jackson, C. A., Lance, R. F., Mangan, A. M., Monroe, E. M., Piaggio, A. J., Stokdyk, J. P., Wilson, C. C., & Richter, C. A. (2020). Reporting the limits of detection and quantification for environmental DNA assays. Environmental DNA, 2(3), 271-282.
Kumar, G., Farrell, E., Reaume, A. M., Eble, J. A., & Gaither, M. R. (2022). One size does not fit all: Tuning eDNA protocols for high-and low-turbidity water sampling. Environmental DNA, 4(1), 167-180.
Lacoursière-Roussel, A., Rosabal, M., & Bernatchez, L. (2016). Estimating fish abundance and biomass from eDNA concentrations: Variability among capture methods and environmental conditions. Molecular Ecology Resources, 16(6), 1401-1414.
Lance, R. F., Klymus, K. E., Richter, C. A., Guan, X., Farrington, H. L., Carr, M. R., Thompson, N., Chapman, D., & Baerwaldt, K. L. (2017). Experimental observations on the decay of environmental DNA from bighead and silver carps. Management of Biological Invasions, 8(3), 343-359.
Laporte, M., Bougas, B., Côté, G., Champoux, O., Paradis, Y., Morin, J., & Bernatchez, L. (2020). Caged fish experiment and hydrodynamic bidimensional modeling highlight the importance to consider 2D dispersion in fluvial environmental DNA studies. Environmental DNA, 2(3), 362-372.
Lenth, R., Singmann, H., Love, J., Buerkner, P., & Herve, M. (2019). Emmeans: Estimated marginal means, aka least-squares means. R package version 1.4. https://CRAN.R-project.org/package=emmeans
Lever, M. A., Torti, A., Eickenbusch, P., Michaud, A. B., Šantl-Temkiv, T., & Jørgensen, B. B. (2015). A modular method for the extraction of DNA and RNA, and the separation of DNA pools from diverse environmental sample types. Frontiers in Microbiology, 6, 476.
Lohr, D., & Hereford, L. (1979). Yeast chromatin is uniformly digested by DNase-I. Proceedings of the National Academy of Sciences of the United States of America, 76(9), 4285-4288.
MacCrimmon, H. (1971). World distribution of rainbow trout (Salmo gairdneri). Journal of the Fisheries Research Board of Canada, 28, 663-704.
Mauvisseau, Q., Harper, L., Sander, M., Hanner, R. H., Kleyer, H., & Deiner, K. ( 2021 ). The multiple states of environmental DNA and what is known about their persistence in aquatic environments. Environmental Science and Technology, 56(9), 5322-5333.
Minshall, G. W., Thomas, S. A., Newbold, J. D., Monaghan, M. T., & Cushing, C. E. (2000). Physical factors influencing fine organic particle transport and deposition in streams. Journal of the North American Benthological Society, 19(1), 1-16.
Nagler, M., Podmirseg, S. M., Ascher-Jenull, J., Sint, D., & Traugott, M. (2022). Why eDNA fractions need consideration in biomonitoring. Molecular Ecology Resources, 22, 2458-2470.
Nevers, M. B., Przybyla-Kelly, K., Shively, D., Morris, C. C., Dickey, J., & Byappanahalli, M. N. (2020). Influence of sediment and stream transport on detecting a source of environmental DNA. PLoS One, 15(12), e0244086.
Oka, S. I., Doi, H., Miyamoto, K., Hanahara, N., Sado, T., & Miya, M. (2021). Environmental DNA metabarcoding for biodiversity monitoring of a highly diverse tropical fish community in a coral reef lagoon: Estimation of species richness and detection of habitat segregation. Environmental DNA, 3(1), 55-69.
R Core Team. (2019). R: A language and environment for statistical computing. R Foundation for Statistical Computing. https://www.R-project.org/
Ruppert, K. M., Kline, R. J., & Rahman, M. S. (2019). Past, present, and future perspectives of environmental DNA (eDNA) metabarcoding: A systematic review in methods, monitoring, and applications of global eDNA. Global Ecology and Conservation, 17, e00547.
Sales, N. G., Wangensteen, O. S., Carvalho, D. C., Deiner, K., Praebel, K., Coscia, I., McDevitt, A. D., & Mariani, S. (2021). Space-time dynamics in monitoring neotropical fish communities using eDNA metabarcoding. Science of the Total Environment, 754, 142096.
Sambrook, J., & Russell, D. W. (2006). Purification of nucleic acids by extraction with phenol: Chloroform. Cold Spring Harbor Protocols, 2006(1), pdb-prot4455.
Sassoubre, L. M., Yamahara, K. M., Gardner, L. D., Block, B. A., & Boehm, A. B. (2016). Quantification of environmental DNA (eDNA) shedding and decay rates for three marine fish. Environmental Science & Technology, 50(19), 10456-10464.
Schwarz, G. (1978). Estimating the dimension of a model. The Annals of Statistics, 6, 461-464.
Seymour, M., Durance, I., Cosby, B. J., Ransom-Jones, E., Deiner, K., Ormerod, S. J., Colbourne, J. K., Wilgar, G., Carvalho, G. R., de Bruyn, M., Edwards, F., Emmett, B. A., Bik, H. M., & Creer, S. (2018). Acidity promotes degradation of multi-species environmental DNA in lotic mesocosms. Communications Biology, 1(1), 1-8.
Shogren, A. J., Tank, J. L., Andruszkiewicz, E., Olds, B., Mahon, A. R., Jerde, C. L., & Bolster, D. (2017). Controls on eDNA movement in streams: Transport, retention, and resuspension. Scientific Reports, 7(1), 1-11.
Shogren, A. J., Tank, J. L., Egan, S. P., August, O., Rosi, E. J., Hanrahan, B. R., Renshaw, M. A., Gantz, C. A., & Bolster, D. (2018). Water flow and biofilm cover influence environmental DNA detection in recirculating streams. Environmental Science & Technology, 52(15), 8530-8537.
Spiess, A. N., & Neumeyer, N. (2010). An evaluation of R2 as an inadequate measure for nonlinear models in pharmacological and biochemical research: A Monte Carlo approach. BMC Pharmacology, 10(1), 1-11.
Stoeckle, B. C., Beggel, S., Kuehn, R., & Geist, J. (2021). Influence of stream characteristics and population size on downstream transport of freshwater mollusk environmental DNA. Freshwater Science, 40(1), 191-201.
Takahara, T., Minamoto, T., Yamanaka, H., Doi, H., & Kawabata, Z. I. (2012). Estimation of fish biomass using environmental DNA. PLoS One, 7(4), e35868.
Turner, C. R., Barnes, M. A., Xu, C. C., Jones, S. E., Jerde, C. L., & Lodge, D. M. (2014). Particle size distribution and optimal capture of aqueous macrobial eDNA. Methods in Ecology and Evolution, 5(7), 676-684.
Weber, M. J., & Brown, M. L. (2011). Relationships among invasive common carp, native fishes and physicochemical characteristics in upper Midwest (USA) lakes. Ecology of Freshwater Fish, 20(2), 270-278.
Wilcox, T. M., Carim, K. J., McKelvey, K. S., Young, M. K., & Schwartz, M. K. (2015). The dual challenges of generality and specificity when developing environmental DNA markers for species and subspecies of Oncorhynchus. PLoS One, 10(11), e0142008.
Wood, Z. T., Erdman, B. F., York, G., Trial, J. G., & Kinnison, M. T. (2020). Experimental assessment of optimal lotic eDNA sampling and assay multiplexing for a critically endangered fish. Environmental DNA, 2(4), 407-417.
Wood, Z. T., Lacoursière-Roussel, A., LeBlanc, F., Trudel, M., Kinnison, M. T., Garry McBrine, C., Pavey, S. A., & Gagné, N. (2021). Spatial heterogeneity of eDNA transport improves stream assessment of threatened salmon presence, abundance, and location. Frontiers in Ecology and Evolution, 9, 650717.
Wu, Q., Kawano, K., Ishikawa, T., Sakata, M. K., Nakao, R., Hiraiwa, M. K., Tsuji, S., Yamanaka, H., & Minamoto, T. (2019). Habitat selection and migration of the common shrimp, Palaemon paucidens in Lake Biwa, Japan-An eDNA-based study. Environmental DNA, 1(1), 54-63.
Yates, M. C., Glaser, D. M., Post, J. R., Cristescu, M. E., Fraser, D. J., & Derry, A. M. (2021). The relationship between eDNA particle concentration and organism abundance in nature is strengthened by allometric scaling. Molecular Ecology, 30(13), 3068-3082.
Zeileis, A., Cribari-Neto, F., Gruen, B., Kosmidis, I., Simas, A. B., Rocha, A. V., & Zeileis, M. A. (2016). Package ‘betareg’. R package, 3(2).
Zhang, S., Lu, Q., Wang, Y., Wang, X., Zhao, J., & Yao, M. (2020). Assessment of fish communities using environmental DNA: Effect of spatial sampling design in lentic systems of different sizes. Molecular Ecology Resources, 20(1), 242-255.
Zhao, B., van Bodegom, P. M., & Trimbos, K. (2021). The particle size distribution of environmental DNA varies with species and degradation. Science of the Total Environment, 797, 149175.