Analysis of Christmas Shearwater Puffinus nativitatis from Kure - - PowerPoint PPT Presentation
Is it Better to be Seen or Sequenced? A Comparison of Methods in the Prey Analysis of Christmas Shearwater Puffinus nativitatis from Kure Atoll. JOHN BACZENAS MARS 4040 DR. HYRENBACH HAWAII PACIFIC UNIVERSITY Background By investigating
JOHN BACZENAS MARS 4040
HAWAII PACIFIC UNIVERSITY
By investigating ecological relationships between seabirds and their
communities (Harrison et al. 1983), knowledge of their diets can lead to an understanding of the integrity of the ecosystem
Through morphological methods, it is difficult to get a high resolution of
taxonomic data from diet samples due to high levels of digestion (McInnes et al. 2017)
Metabarcoding uses the “barcode of life” region of DNA and allows for
more accurate identification of prey items (Hirai et al. 2018)
95 samples were collected
during DLNR summer population surveys conducted on Kure Atoll
Stored in a plastic bag and
frozen in water to preserve samples
Screenshot of google maps
95 samples were collected
during DLNR summer population surveys conducted on Kure Atoll
Stored in a plastic bag and
frozen in water to preserve samples
Transported from Kure Atoll to
From September 2017- June 2018, 91
samples were visually sorted, weighed, and classified into food classes.
Ashmole & Ashmole (1967) method of
Mass was taken in grams for the
individual prey items
200-mL of sample water collected for
future metagenetic processing
Sorted prey items stored in freezer for
future analysis
CHSH regurgitation sample, sorted into individual prey items and food classes.
DNA was extracted from diet samples using a Phenol-Chloroform-Isoamyl
extraction method established by Renshaw et al. (2015)
Extracted DNA was cleaned using a magnetic bead procedure to
remove unwanted lengths of fragments
Due to limited amount of space during the MiSeq-Illumina sequencing run,
31 samples were selected at random to be further processed.
The 31 samples were processed through methods of PCR and specific
Cytochrome c Oxidase subunit I gene (CO1) markers were selected to attach to the desired fragments of DNA
These markers are described by Leray et al. (2013) and attach to the
“barcode of life” region of DNA
After DNA was duplicated, the samples were sent to the University of
Notre Dame to be sequenced using MiSeq-Illumina methods (Hirai et al. 2017)
After DNA was sequenced, the data was processed back at OI via
bioinformatics and comparing to the database GENBANK to obtain the taxonomic information of the samples
Squid Fish Total
% Number 27.27 72.73 100.00 % Mass 49.05 50.95 100.00
POO 50.00 50.00 100.00
Table 2. Metric calculations of the diet composition of 31 CHSH regurgitations collected on Kure Atoll between 2009 and 2017. Samples were processed using the morphological method of Ashmole & Ashmole (1967).
20 40 60 80 100 % Number % Mass POO % Squid Fish Figure 1. Metric calculations of the diet composition of 31 CHSH regurgitations collected on Kure Atoll between 2009 and 2017. Samples were processed using the morphological method of Ashmole & Ashmole (1967).
CO1 Markers Food Class Leray 1 Leray 2 B12 X2 P Squid 1156 158782 404428 109904.78 Fish
252283 1460242 1687752 Table 4. Contingency results comparing the association of three CO1 markers (Leray1, Leray 2, and B12) and the food classes analyzed from 31 CHSH regurgitations collected from Kure Atoll between 2009 and 2017.
20 40 60 80 100 Leray 1 Leray 2 B12 POO Squid Fish Figure 2. Metric calculations of the diet composition of 31 CHSH regurgitations collected on Kure Atoll between 2009 and 2017. Samples were processed using the metagenetic method with three different CO1 markers (Leray 1, Leray 2, and B12).
Leray 1 Squid Fish Total % Number 0.46 99.54 100 POO 24.24 75.76 100 % FOO 25.81 80.65 106.45 Leray 2 % Number 9.81 90.19 100 POO 47.46 52.54 100 % FOO 90.32 100 190.32 B12 % Number 19.33 80.67 100 POO 44.44 55.56 100 % FOO 77.42 96.77 174.19
Table 5. Metric calculations of the diet composition of 31 CHSH regurgitations collected on Kure Atoll between 2009 and 2017. Samples were processed using the metagenetic method with three different CO1 markers (Leray 1, Leray 2, and B12).
Fish Method Present Absent X2 P Leray 1
Metagenetic 25 6 0.48 0.49 Morphological
27 4
Leray 2
Metagenetic 31 4.28 0.04 Morphological
27 4
B12
Metagenetic 30 1 1.96 0.16 Morphological
27 4
Squid Leray 1
Metagenetic 8 23 23.68 0.00 Morphological
27 4
Leray 2
Metagenetic 28 3 0.16 0.69 Morphological
27 4
B12
Metagenetic 24 7 0.99 0.32 Morphological
27 4
Table 6. Contingency results the association of the presence/ absence of two food classes (fish/squid) and the method (morphological/metagenetic) used to process the samples.
Fish Method Present Absent X2 P Leray 1
Metagenetic 25 6 0.48 0.49 Morphological
27 4
Leray 2
Metagenetic 31 4.28 0.04 Morphological
27 4
B12
Metagenetic 30 1 1.96 0.16 Morphological
27 4
Squid Leray 1
Metagenetic 8 23 23.68 0.00 Morphological
27 4
Leray 2
Metagenetic 28 3 0.16 0.69 Morphological
27 4
B12
Metagenetic 24 7 0.99 0.32 Morphological
27 4
Table 6. Contingency results the association of the presence/ absence of two food classes (fish/squid) and the method (morphological/metagenetic) used to process the samples.
Both methods produced similar results with respects to POO Based on the contingency tests, there was a lack of association between
the two food classes and which method was used.
Confirmed that metagenetics is a viable method for analyzing seabird
diet composition
For future studies, try and expand the database to obtain more accurate
taxonomic information
See if there is any additional methods of setting a threshold to further
“clean up” the metagenetic data
Ashmole, N. P., & Ashmole, M. J. (1967). Comparative feeding ecology of sea birds of a tropical oceanic island. Peabody Museum of Natural History Bulletin, Yale University, 24, 1-139.
Harrison, C. S., Hida, T. S., & Seki, M. P. (1983). Hawaiian Seabird Feeding Ecology. Wildlife Monographs, 85, 3–71.
Hirai, J., Nagai, S., & Hidaka, K. (2017). Evaluation of metagenetic community analysis of planktonic copepods using illumina miseq: Comparisons with morphological classification and metagenetic analysis using roche 454. [PDF]. PLoS ONE, 12(7), 1-19.
Hirai, J., Hamamoto, Y., Honda, D., & Hidaka, K. (2018). Possible aplanochytrid (Labyrinthulea) prey detected using 18S metagenetic diet analysis in the key copepod species calanus sinicus in the coastal waters of the subtropical western north pacific. Plankton & Benthos Research, 13(2), 75-82.
Leray, M., Yang, J. Y., Meyer, C. P., Mills, S. C., Agudelo, N., Ranwez, V., . . . Machida, R. J. (2013). A new versatile primer set targeting a short fragment of the mitochondrial COI region for metabarcoding metazoan diversity: Application for characterizing coral reef fish gut contents [PDF]. Frontiers in Zoology, 10(34), 1-14.
McInnes, J. C., Alderman, R., Lea, M.-A., Raymond, B., Deagle, B. E., Phillips, R. A., . . . Jarman, S. N. (2017). High
Molecular Ecology, 26, 4831-4845.
Renshaw, M. A., Olds, B. P., Jerde, C. L., Mcveigh, M. M., & Lodge, D. M. (2015). The room temperature preservation of filtered environmental DNA samples and assimilation into a phenol- chloroform-isoamyl alcohol DNA extraction. Molecular Ecology Resources, 15(1), 168–176.