دورية أكاديمية

Fur microbiome as a putative source of symbiotic bacteria in sucking lice.

التفاصيل البيبلوغرافية
العنوان: Fur microbiome as a putative source of symbiotic bacteria in sucking lice.
المؤلفون: Martin Říhová J; Department of Parasitology, Faculty of Science, University of South Bohemia, České Budějovice, Czech Republic., Gupta S; Department of Parasitology, Faculty of Science, University of South Bohemia, České Budějovice, Czech Republic., Nováková E; Department of Parasitology, Faculty of Science, University of South Bohemia, České Budějovice, Czech Republic.; Institute of Parasitology, Biology Centre, ASCR, v.v.i, České Budějovice, Czech Republic., Hypša V; Department of Parasitology, Faculty of Science, University of South Bohemia, České Budějovice, Czech Republic. vacatko@prf.jcu.cz.; Institute of Parasitology, Biology Centre, ASCR, v.v.i, České Budějovice, Czech Republic. vacatko@prf.jcu.cz.
المصدر: Scientific reports [Sci Rep] 2024 Sep 27; Vol. 14 (1), pp. 22326. Date of Electronic Publication: 2024 Sep 27.
نوع المنشور: Journal Article
اللغة: English
بيانات الدورية: Publisher: Nature Publishing Group Country of Publication: England NLM ID: 101563288 Publication Model: Electronic Cited Medium: Internet ISSN: 2045-2322 (Electronic) Linking ISSN: 20452322 NLM ISO Abbreviation: Sci Rep Subsets: MEDLINE
أسماء مطبوعة: Original Publication: London : Nature Publishing Group, copyright 2011-
مواضيع طبية MeSH: Symbiosis* , Microbiota*, Animals ; Phylogeny ; RNA, Ribosomal, 16S/genetics ; Phthiraptera/microbiology ; Bacteria/genetics ; Bacteria/classification ; Bacteria/isolation & purification
مستخلص: Symbiosis between insects and bacteria has been established countless times. While it is well known that the symbionts originated from a variety of different bacterial taxa, it is usually difficult to determine their environmental source and a route of their acquisition by the host. In this study, we address this question using a model of Neisseriaceae symbionts in rodent lice. These bacteria established their symbiosis independently with different louse taxa (Polyplax, Hoplopleura, Neohaematopinus), most likely from the same environmental source. We first applied amplicon analysis to screen for candidate source bacterium in the louse environment. Since lice are permanent ectoparasites, often specific to the particular host, we screened various microbiomes associated with three rodent species (Microtus arvalis, Clethrionomys glareolus, and Apodemus flavicollis). The analyzed samples included fur, skin, spleen, and other ectoparasites sampled from these rodents. The fur microbiome data revealed a Neisseriaceae bacterium, closely related to the known louse symbionts. The draft genomes of the environmental Neisseriaceae, assembled from all three rodent hosts, converged to a remarkably small size of approximately 1.4 Mbp, being even smaller than the genomes of the related symbionts. Our results suggest that the rodent fur microbiome can serve as a source for independent establishment of bacterial symbiosis in associated louse species. We further propose a hypothetical scenario of the genome evolution during the transition of a free-living bacterium to the member of the rodent fur-associated microbiome and subsequently to the facultative and obligate louse symbionts.
(© 2024. The Author(s).)
References: McCutcheon, J. P., Boyd, B. M. & Dale, C. The life of an insect endosymbiont from the cradle to the grave. Curr. Biol.29, R485–R495. https://doi.org/10.1016/j.cub.2019.03.032 (2019). (PMID: 10.1016/j.cub.2019.03.03231163163)
Husník, F., Chrudimský, T. & Hypša, V. Multiple origins of endosymbiosis within the Enterobacteriaceae (γ-Proteobacteria): convergence of complex phylogenetic approaches. BMC Biol.9, 87. https://doi.org/10.1186/1741-7007-9-87 (2011). (PMID: 10.1186/1741-7007-9-87222015293271043)
Gerhart, J. G., Moses, A. S. & Raghavan, R. A Francisella-like endosymbiont in the Gulf Coast tick evolved from a mammalian pathogen. Sci. Rep.6 (1), 33670. https://doi.org/10.1038/srep33670 (2016). (PMID: 10.1038/srep33670276457665028885)
Chari, A. et al. Phenotypic characterization of Sodalis praecaptivus sp. nov., a close non-insect-associated member of the Sodalis-allied lineage of insect endosymbionts. Int. J. Syst. Evol. Microbiol.65, 1400–1405. https://doi.org/10.1099/ijs.0.000113 (2015). (PMID: 10.1099/ijs.0.000113257827684635462)
Husník, F. Host–symbiont–pathogen interactions in blood-feeding parasites: Nutrition, immune cross-talk and gene exchange. Parasitology. 145, 1294–1303. https://doi.org/10.1017/S0031182018001104 (2018). (PMID: 10.1017/S003118201800110429642965)
Nishide, Y. et al. Endosymbiotic bacteria of the boar louse Haematopinus apri (Insecta: Phthiraptera: Anoplura). Front. Microbiol.13, 962252. https://doi.org/10.3389/fmicb.2022.962252 (2022). (PMID: 10.3389/fmicb.2022.962252360039349393614)
Říhová, J., Bell, K. C., Nováková, E. & Hypša, V. Lightella neohaematoaini: A new lineage of highly reduced endosymbionts coevolving with chipmunk lice of the genus Neohaematopinus. Front. Microbiol.13, 900312. https://doi.org/10.3389/fmicb.2022.900312 (2022). (PMID: 10.3389/fmicb.2022.900312359794969376444)
Říhová, J. et al. A new symbiotic lineage related to Neisseria and Snodgrassella arises from the dynamic and diverse microbiomes in sucking lice. Mol. Ecol.30, 2178–2196. https://doi.org/10.1111/mec.15877 (2021). (PMID: 10.1111/mec.1587733639022)
Moran, N. A., McCutcheon, J. P. & Nakabachi, A. Genomics and evolution of heritable bacterial symbionts. Annu. Rev. Genet.42, 165–190. https://doi.org/10.1146/annurev.genet.41.110306.130119 (2008). (PMID: 10.1146/annurev.genet.41.110306.13011918983256)
Singleton, C. M. et al. Connecting structure to function with the recovery of over 1000 high quality metagenome-assembled genomes from activated sludge using long-read sequencing. Nat. Commun. 12, ; (2009). https://doi.org/10.1038/s41467-021-22323-6 (2021).
Myers, G. S. et al. Genome sequence and identification of candidate vaccine antigens from the animal pathogen Dichelobacter nodosus. Nat. Biotechnol.25, 569–575. https://doi.org/10.1038/nbt1292 (2007). (PMID: 10.1038/nbt129217468768)
Siozios, S. et al. Genome dynamics across the evolutionary transition to endosymbiosis. bioRxiv. https://doi.org/10.1101/2023.05.10.540192 (2023). (PMID: 10.1101/2023.05.10.540192)
Bi, H., Zhu, L., Jia, J. & Cronan, J. E. A biotin biosynthesis gene restricted to Helicobacter. Sci. Rep.6, 21162. https://doi.org/10.1038/srep21162 (2016). (PMID: 10.1038/srep21162268684234751477)
Hang, X., Zeng, Q., Zeng, L., Jia, J. & Bi, H. Functional replacement of the BioC and BioH proteins of Escherichia coli biotin precursor biosynthesis by Ehrlichia chaffeensis novel proteins. Curr. Microbiol.76, 626–636. https://doi.org/10.1007/s00284-019-01679-x (2019). (PMID: 10.1007/s00284-019-01679-x30915508)
Mol. Biol. Evol. 34, 1743–1757; 10.1093/molbev/msx117 (2017).
Martin Říhová, J., Gupta, S., Darby, A. C., Nováková, E. & Hypša, V. Arsenophonus symbiosis with louse fmultipleltiple origins, coevolutionary dynamics, and metabolic significance. mSystems. 8, e00706–e00723. https://doi.org/10.1128/msystems.00706-23 (2023). (PMID: 10.1128/msystems.00706-233775068210654098)
Říhová, J., Nováková, E., Husník, F. & Hypša, V. Legionella becoming a mutuaadaptiveaptive processes shaping the genome of symbiont in the louse Polyplax serrata. Genome Biol. Evol.9, 2946–2957. https://doi.org/10.1093/gbe/evx219 (2017). (PMID: 10.1093/gbe/evx219290693495714129)
Vibrio fischeri. Microbiology 169, 001302; 10.1099/mic.0.001302 (2023). Suria, A. M., Smith, S., Speare, L., Chen, Y., Chien, I., Clark, E. G., … Septer,A. N. Prevalence and diversity of type VI secretion systems in a model beneficial symbiosis. Front. Microbiol. 13, 988044; 10.3389/fmicb.2022.988044 (2022).
Front. Microbiol. 13, 988044; 10.3389/fmicb.2022.988044 (2022).
Takeshita, K. & Kikuchi, Y. Genomic comparison of insect gut symbionts from divergent Burkholderia subclades. Genes. 11, 744. https://doi.org/10.3390/genes11070744 (2020). (PMID: 10.3390/genes11070744326353987397029)
Parada, A. E., Needham, D. M. & Fuhrman, J. A. Every base matters: assessing small subunit rRNA primers for marine microbiomes with mock communities, time series and global field samples. Environ. Microbiol.18, 1403–1414. https://doi.org/10.1111/1462-2920.13023 (2016). (PMID: 10.1111/1462-2920.1302326271760)
mSystems 1, 10-1128; 10.1128/mSystems.00009–15 (2016).
Andrews, S. & FastQC A quality control tool for high throughput sequence data. (2010). http://www.bioinformatics.babraham.ac.uk/projects/fastqc.
Edgar, R. C. & UPARSE Highly accurate OTU sequences from microbial amplicon reads. Nat. Methods. 10, 996–998. https://doi.org/10.1038/nmeth.2604 (2013). (PMID: 10.1038/nmeth.260423955772)
Triatominae). Microbiome 8, 1–16; 10.1186/s40168-020-00863-4 (2020).
Rodríguez-Ruano, S. M., Juhaňáková, E., Vávra, J. & Nováková, E. Methodological insight into mosquito microbiome studies. Front. Cell. Infect. Microbiol.10, 86. https://doi.org/10.3389/fcimb.2020.00086 (2020). (PMID: 10.3389/fcimb.2020.00086322579627089923)
Camacho, C. BLAST plus: architecture and applications. BMC Bioinform.10, 421. https://doi.org/10.1186/1471-2105-10-421 (2009). (PMID: 10.1186/1471-2105-10-421)
Nucleic Acids Res. 41, D590-D596; 10.1093/nar/gks1219 (2012).
Nat. Methods 7, 335–336; 10.1038/nmeth.f.303 (2010).
Morgulis, A. et al. Database indexing for production MegaBLAST searches. Bioinformatics. 24, 1757–1764. https://doi.org/10.1093/bioinformatics/btn322 (2008). (PMID: 10.1093/bioinformatics/btn322185679172696921)
Jones, R. T., McCormick, K. F. & Martin, A. P. Bacterial communities of Bartonella-positive fleas: diversity and community assembly patterns. Appl. Environ. Microbiol.74, 1667–1670. https://doi.org/10.1128/AEM.01310-07 (2008). (PMID: 10.1128/AEM.01310-07182038622258626)
Katoh, K., Misawa, K., Kuma, K. I. & Miyata, T. MAFFT: a novel method for rapid multiple sequence alignment based on fast Fourier transform. Nucleic Acids Res.30, 3059–3066. https://doi.org/10.1093/nar/gkf436 (2002). (PMID: 10.1093/nar/gkf43612136088135756)
Bioinformatics 28, 1647–1649; 10.1093/bioinformatics/bts199 (2012).
Minh, B. Q. et al. IQ-TREE 2: New models and efficient methods for phylogenetic inference in the genomic era. Mol. Biol. Evol.37, 1530–1534. https://doi.org/10.1093/molbev/msaa015 (2020). (PMID: 10.1093/molbev/msaa015320117007182206)
J. Comput. Biol. 19, 455–477; 10.1089/cmb.2012.0021 (2012).
Altschul, S. F., Gish, W., Miller, W., Myers, E. W. & Lipman, D. J. Basic local alignment search tool. J. Mol. Biol.215, 403–410. https://doi.org/10.1016/S0022-2836(05)80360-2 (1990). (PMID: 10.1016/S0022-2836(05)80360-22231712)
Guindon, S. et al. New algorithms and methods to estimate maximum-likelihood phylogenies: assessing the performance of PhyML 3.0. Syst. Biol.59, 307–321. https://doi.org/10.1093/sysbio/syq010 (2010). (PMID: 10.1093/sysbio/syq01020525638)
Seemann, T. PROKKA: Rapid prokaryotic genome annotation. Bioinformatics. 30, 2068–2069. https://doi.org/10.1093/bioinformatics/btu153 (2014). (PMID: 10.1093/bioinformatics/btu15324642063)
Arndt, D. et al. PHASTER: A better, faster version of the PHAST phage search tool. Nucleic Acids Res.44, W16–W21. https://doi.org/10.1093/nar/gkw387 (2016). (PMID: 10.1093/nar/gkw387271419664987931)
Syberg-Olsen, M. J., Garber, A. I., Keeling, P. J., McCutcheon, J. P. & Husnik, F. Pseudofinder: detection of pseudogenes in prokaryotic genomes. Mol. Biol. Evol.39, msac213. https://doi.org/10.1093/molbev/msac213 (2022). (PMID: 10.1093/molbev/msac213)
Simão, F. A., Waterhouse, R. M., Ioannidis, P., Kriventseva, E. V. & Zdobnov, E. M. BUSCO: assessing genome assembly and annotation completeness with single-copy orthologs. Bioinformatics. 31, 3210–3212. https://doi.org/10.1093/bioinformatics/btv351 (2015). (PMID: 10.1093/bioinformatics/btv35126059717)
Yoon, S. H., Ha, S. M., Lim, J., Kwon, S. & Chun, J. A large-scale evaluation of algorithms to calculate average nucleotide identity. Antonie Van Leeuwenhoek. 110, 1281–1286. https://doi.org/10.1007/s10482-017-0844-4 (2017). (PMID: 10.1007/s10482-017-0844-428204908)
Emms, D. M., Kelly, S. & OrthoFinder Phylogenetic orthology inference for comparative genomics. Genome Biol.20, 1–14. https://doi.org/10.1186/s13059-019-1832-y (2019). (PMID: 10.1186/s13059-019-1832-y)
Kanehisa, M., Sato, Y. & Morishima, K. BlastKOALA and GhostKOALA: KEGG tools for functional characterization of genome and metagenome sequences. J. Mol. Biol.428, 726–731. https://doi.org/10.1016/j.jmb.2015.11.006 (2016). (PMID: 10.1016/j.jmb.2015.11.00626585406)
Talavera, G. & Castresana, J. Improvement of phylogenies after removing divergent and ambiguously aligned blocks from protein sequence alignments. Syst. Biol.56, 564–577. https://doi.org/10.1080/10635150701472164 (2007). (PMID: 10.1080/1063515070147216417654362)
Lartillot, N., Rodrigue, N., Stubbs, D., Richer, J. & PhyloBayes, M. P. I. Phylogenetic reconstruction with infinite mixtures of profiles in a parallel environment. Syst. Biol.62, 611–615. https://doi.org/10.1093/sysbio/syt022 (2013). (PMID: 10.1093/sysbio/syt02223564032)
معلومات مُعتمدة: GA20-07674S Grantová Agentura České Republiky
فهرسة مساهمة: Keywords: Anoplura; Fur microbiome; Metagenomics; Rodents; Sucking lice; Symbiosis
المشرفين على المادة: 0 (RNA, Ribosomal, 16S)
تواريخ الأحداث: Date Created: 20240927 Date Completed: 20240927 Latest Revision: 20240927
رمز التحديث: 20240928
DOI: 10.1038/s41598-024-73026-2
PMID: 39333204
قاعدة البيانات: MEDLINE
الوصف
تدمد:2045-2322
DOI:10.1038/s41598-024-73026-2