Macrogenomic Analysis Reveals Feeding and Habitat Adaptation Related to the Gut Microbiota of the Non-Obligate Cave Dweller (Megophryidae, Anura) among Cave and Culture Environments

Mueller, K., Ash, C., Pennisi, E., and Smith, O., The gut microbiota: introduction, Science, 2012, vol. 336, no. 6086, p. 1245. https://doi.org/10.1126/science.336.6086.1245

Article  CAS  PubMed  Google Scholar 

Kohl, K.D. and Carey, H.V., A place for host–microbe symbiosis in the comparative physiologist’s toolbox, J. Exp. Biol., 2016, vol. 219, no. 22, pp. 3496—3504. https://doi.org/10.1242/jeb.136325

Article  PubMed  Google Scholar 

McDiarmid, R.W. and Altig, R., Tadpoles: The Biology of Anuran Larvae, Chicago, IL: University of Chicago Press, 2000.

Google Scholar 

Jiménez, R.R. and Sommer, S., The amphibian microbiome: natural range of variation, pathogenic dysbiosis, and role in conservation, Biodiversity Conserv., 2017, vol. 26, no. 4, pp. 763—786. https://doi.org/10.1007/s10531-016-1272-x

Article  Google Scholar 

Reid, H.I., Treasurer, J.W., Adam, B., and Birkbeck, T.H., Analysis of bacterial populations in the gut of developing cod larvae and identification of Vibrio logei, Vibrio anguillarum and Vibrio splendidus as pathogens of cod larvae, Aquaculture, 2009, vol. 288, no. 1, pp. 36—43. https://doi.org/10.1016/j.aquaculture.2008.11.022

Article  Google Scholar 

Ingerslev, H.C., Strube, M.L., Jørgensen, L.G., et al., Diet type dictates the gut microbiota and the immune response against Yersinia ruckeri in rainbow trout (Oncorhynchus mykiss), Fish Shellfish Immunol., 2014, vol. 40, no. 2, pp. 624—633. https://doi.org/10.1016/j.fsi.2014.08.021

Article  CAS  PubMed  Google Scholar 

Li, J., Ni, J., Li, J., et al., Comparative study on gastrointestinal microbiota of eight fish species with different feeding habits, J. Appl. Microbiol., 2014, vol. 117, no. 6, pp. 1750—1760. https://doi.org/10.1111/jam.12663

Article  CAS  PubMed  Google Scholar 

Sullam, K.E., Rubin, B.E.R., Dalton, C.M., et al., Divergence across diet, time and populations rules out parallel evolution in the gut microbiomes of Trinidadian guppies, ISME J., 2015, vol. 9, no. 7, pp. 1508—1522. https://doi.org/10.1038/ismej.2014.231

Article  PubMed  PubMed Central  Google Scholar 

Fei, L., Ye, C., and Jiang, J., Colored Atlas of Chinese Amphibians and Their Distributions, Chengdu: Sichuan Publishing House of Science and Technology, 2012.

Google Scholar 

Liu, J.X., Ontogenesis and primary ecological study of Oreolalax rhodostigmatus, Bull. Biol., 2010, vol. 45, no. 1, pp. 50—52.

CAS  Google Scholar 

Zhao, Y., Chen, J., Wang, Z., et al., The complete mitochondrial genome of the vulnerable megophryid frog Oreolalax rhodostigmatus (Anura, Megophryidae), Conserv. Genet. Resour., 2018, vol. 10, no. 4, pp. 617—620. https://doi.org/10.1007/s12686-017-0878-y

Article  Google Scholar 

Zhou, S., Rajput, A.P., Mao, T., et al., Adapting to novel environments together: evolutionary and ecological correlates of the bacterial microbiome of the world’s largest cavefish diversification (Cyprinidae, Sinocyclocheilus), Front. Microbiol., 2022, vol. 13. https://doi.org/10.3389/fmicb.2022.823254

Chen, S., Zhou, Y., Chen, Y., and Gu, J., fastp: an ultra-fast all-in-one FASTQ preprocessor, Bioinformatics, 2018, vol. 34, no. 17, pp. i884—i890. https://doi.org/10.1093/bioinformatics/bty560

Article  CAS  PubMed  PubMed Central  Google Scholar 

Li, D., Liu, C.M., Luo, R., et al., MEGAHIT: an ultra-fast single-node solution for large and complex metagenomics assembly via succinct de Bruijn graph, Bioinformatics, 2015, vol. 31, no. 10, pp. 1674—1676. https://doi.org/10.1093/bioinformatics/btv033

Article  CAS  PubMed  Google Scholar 

Zhu, W., Lomsadze, A., and Borodovsky, M., Ab initio gene identification in metagenomic sequences, Nucleic Acids Res., 2010, vol. 38, no. 12, p. e132. https://doi.org/10.1093/nar/gkq275

Article  CAS  PubMed  PubMed Central  Google Scholar 

Fu, L., Niu, B., Zhu, Z., et al., CD-HIT: accelerated for clustering the next-generation sequencing data, Bioinformatics, 2012, vol. 28, no. 23, pp. 3150—3152. https://doi.org/10.1093/bioinformatics/bts565

Article  CAS  PubMed  PubMed Central  Google Scholar 

Langmead, B. and Salzberg, S.L., Fast gapped-read alignment with Bowtie 2, Nat. Methods, 2012, vol. 9, no. 4, pp. 357—359. https://doi.org/10.1038/nmeth.1923

Article  CAS  PubMed  PubMed Central  Google Scholar 

Hong, C., Manimaran, S., Shen, Y., et al., PathoScope 2.0: a complete computational framework for strain identification in environmental or clinical sequencing samples, Microbiome, 2014, vol. 2. https://doi.org/10.1186/2049-2618-2-33

Qin, J., Li, Y., Cai, Z., et al., A metagenome-wide association study of gut microbiota in type 2 diabetes, Nature, 2012, vol. 490, no. 7418, pp. 55—60. https://doi.org/10.1038/nature11450

Article  CAS  PubMed  Google Scholar 

Menzel, P., Ng, K.L., and Krogh, A., Fast and sensitive taxonomic classification for metagenomics with Kaiju, Nat. Commun., 2016, vol. 7, no. 1, p. 1. https://doi.org/10.1038/ncomms11257

Article  CAS  Google Scholar 

Buchfink, B., Xie, C., and Huson, D., Fast and sensitive protein alignment using DIAMOND, Nat. Methods, 2015, vol. 12, no. 1, pp. 59—60. https://doi.org/10.1038/nmeth.3176

Article  CAS  PubMed  Google Scholar 

Krzywinski, M., Schein, J., Birol, I., et al., Circos: an information aesthetic for comparative genomics, Genome Res., 2009, vol. 19, no. 9, pp. 1639—1645. https://doi.org/10.1101/gr.092759.109

Article  CAS  PubMed  PubMed Central  Google Scholar 

Stevens, M. and Wagner, H., Vegan: community ecology package: R package version 1.17-4, 2010.

Wickham, H., ggplot2, WIREs Comput. Stat., 2011, vol. 3, no. 2, pp. 180—185. https://doi.org/10.1002/wics.147

Article  Google Scholar 

Han, H., Wei, W., Hu, Y., et al., Diet evolution and habitat contraction of giant pandas via stable isotope analysis, Curr. Biol., 2019, vol. 29, no. 4, pp. 664—669. https://doi.org/10.1016/j.cub.2018.12.051

Article  CAS  PubMed  Google Scholar 

Hughes, R.L., Marco, M.L., Hughes, J.P., et al., The role of the gut microbiome in predicting response to diet and the development of precision nutrition models: I. Overview of current methods, Adv. Nutr. (Bethesda, Md), 2019, vol. 10, no. 6, pp. 953—978. https://doi.org/10.1093/advances/nmz022

Article  Google Scholar 

Grier, A., Qiu, X., Bandyopadhyay, S., et al., Impact of prematurity and nutrition on the developing gut microbiome and preterm infant growth, Microbiome, 2017, vol. 5, no. 1, p. 158. https://doi.org/10.1186/s40168-017-0377-0

Article  PubMed  PubMed Central  Google Scholar 

Vences, M., Lyra, M.L., Kueneman, J.G., et al., Gut bacterial communities across tadpole ecomorphs in two diverse tropical anuran faunas, Sci. Nat., 2016, vol. 103, no. 3, p. 25. https://doi.org/10.1007/s00114-016-1348-1

Article  CAS  Google Scholar 

Kohl, K.D., Cary, T.L., Karasov, W.H., and Dearing, M.D., Restructuring of the amphibian gut microbiota through metamorphosis, Environ. Microbiol. Rep., 2013, vol. 5, no. 6, pp. 899—903. https://doi.org/10.1111/1758-2229.12092

Article  PubMed  Google Scholar 

Ramakrishna, B.S., Role of the gut microbiota in human nutrition and metabolism, J. Gastroenterol. Hepatol., 2013, vol. 28, suppl. 4, pp. 9—17. https://doi.org/10.1111/jgh.12294

Article  CAS  PubMed  Google Scholar 

Zhang, M., Chen, H., Liu, L., et al., The changes in the frog gut microbiome and its putative oxygen-related phenotypes accompanying the development of gastrointestinal complexity and dietary shift, Front. Microbiol., 2020, vol. 11. https://doi.org/10.3389/fmicb.2020.00162

Neiße, N., Santon, M., Bitton, P.P., and Michiels, N.K., Small benthic fish strike at prey over distances that fall within theoretical predictions for active sensing using light, J. Fish Biol., 2020, vol. 97, no. 4, pp. 1201—1208. https://doi.org/10.1111/jfb.14502

Article  PubMed  Google Scholar 

Qing-Hong, D.U., Chen, K., Huang, Z., et al., Community characteristics of phytoplankton in Anhai Bay, J. Fish. Res., 2018, vol. 40, no. 1, p. 42.

Google Scholar 

Alberdi, A., Aizpurua, O., Bohmann, K., et al., Do vertebrate gut metagenomes confer rapid ecological adaptation?, Trends Ecol. Evol., 2016, vol. 31, no. 9, pp. 689—699. https://doi.org/10.1016/j.tree.2016.06.008

Article  PubMed  Google Scholar 

Nicholson, J.K., Holmes, E., Kinross, J., et al., Host—gut microbiota metabolic interactions, Science, 2012, vol. 336, no. 6086, pp. 1262—1267. https://doi.org/10.1126/science.1223813

Article  CAS  PubMed  Google Scholar 

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