Metagenomic Profiling of Host-Associated Bacteria from 8 Datasets of 2 the Red Alga Porphyra Purpurea, with Metaphlan 3.0

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Metagenomic Profiling of Host-Associated Bacteria from 8 Datasets of 2 the Red Alga Porphyra Purpurea, with Metaphlan 3.0 bioRxiv preprint doi: https://doi.org/10.1101/2020.11.17.386862; this version posted November 18, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. 1 Metagenomic profiling of host-associated bacteria from 8 datasets of 2 the red alga Porphyra purpurea, with MetaPhlAn 3.0 3 4 Orestis Nousias a,b*, Federica Montesanto c,d 5 6 aInstitute of Marine Biology, Biotechnology and Aquaculture, Hellenic Centre for Marine 7 Research (HCMR) Crete, Greece 8 bDepartment of Biology, University of Crete, Greece 9 cDepartment of Biology, University of Bari Aldo Moro, Via Orabona 4, 70125, Bari, Italy 10 dCoNISMa, Piazzale Flaminio 9, 00197, Roma, Italy 11 12 *Corresponding author: O. Nousias, Institute of Marine Biology, Biotechnology and 13 Aquaculture, Hellenic Centre for Marine Research (HCMR) Crete, Greece. Email: 14 [email protected] 15 16 ON [email protected]: orcid.org/0000-0001-6644-6599 17 FM [email protected] orcid.org/0000-0001-6328-7596 18 bioRxiv preprint doi: https://doi.org/10.1101/2020.11.17.386862; this version posted November 18, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. 19 20 Abstract 21 Microbial communities play a fundamental role in the association with marine algae, in fact 22 they are recognized to be actively involved in growth and morphogenesis. 23 Porphyra purpurea is a red algae commonly found in the intertidal zone with an high 24 economical value, indeed several species belonging to the genus Porphyra are intensely 25 cultivated in the Eastern Asian countries. Moreover, P. purpurea is widely used as model 26 species in different fields, mainly due to its peculiar life cycle. Despite of that, little is known 27 about the microbial community associated to this species. Here we report the microbial- 28 associated diversity of P. purpurea in four different localities (Ireland, Italy United Kingdom 29 and USA) through the analysis of eight metagenomic datasets obtained from the publicly 30 available metagenomic nucleotide database (https://www.ebi.ac.uk/ena/). The metagenomic 31 datasets were quality controlled with FastQC version 0.11.8, pre-processed with Trimmomatic 32 version 0.39 and analysed with Methaplan 3.0, with a reference database containing clade 33 specific marker genes from ̴ 99.500 bacterial genomes, following the pan-genome approach, 34 in order to identify the putative bacterial taxonomies and their relative abundances. 35 Furthermore, we compared the results to the 16S rRNA metagenomic analysis pipeline of 36 MGnify database to evaluate the effectiveness of the two methods. Out of the 43 bacterial 37 species identified with MetaPhlAn 3.0 only 5 were common with the MGnify results and from 38 the 21 genera, only 9 were common. This approach highlighted the different taxonomical 39 resolution of a 16S rRNA OTU-based method in contrast to the pan-genome approach deployed 40 by MetaPhlAn 3.0. 41 Keywords 42 Metagenomics, microbial communities, Rhodophyta, Whole Genome Shotgun sequencing, 43 pan-genome. 44 1. Introduction 45 Microbial communities are the keystone in all terrestrial and marine habitats, being involved 46 in biogeochemical cycles, primary productivity, symbiotic relationships, metabolic pathways 47 and so on (Konopka, 2009). In the last decades, metagenomic studies in the marine 48 environment greatly enhanced the knowledge about the diversity and complexity of marine 49 microbial communities allowing straight sequencing of DNA from environmental samples or 50 directly from the hosts these communities are associated with (Biller et al., 2018). However, 51 the biodiversity of microbial communities as well as their relationship with the environment, 52 in terms of chemistry and interactions with its inhabitants is still scantly known (Biller et al., 53 2018). 54 The genus Porphyra C.Agardh, 1824 (Bangiales, Bangiophyceae) includes more than one 55 hundred species of red algae worldwide distributed, with a remarkable economical value since 56 they are cultivated in China, Korea and Japan as human food resource due to their contents of 57 proteins, vitamins and minerals, worthing around $1.4 billion/year (Yarish and Pereira, 2008). 58 Moreover, Porphyra is considered a model for basic and applied research, due to its unique 59 dimorphic cycle, which consists of a gametophyte forming a large and leafy thallus, alternate 60 with a filamentous sporophyte (Saga et al., 2002; Gantt et al., 2010). Thus, with regards to its bioRxiv preprint doi: https://doi.org/10.1101/2020.11.17.386862; this version posted November 18, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. 61 unique life cycle, economical value, as well as for the significant resilience to high light and 62 desiccation, Porphyra is considered also a model for genome sequencing (Gantt et al., 2010). 63 Marine bacteria are actively involved in the normal growth and development of macro-algae, 64 but only few studies have been carried on this regards. 65 Despite of the economical and scientific importance of Porphyra and the recognized 66 implication of its microbial communities associated on its life cycle and not only, further 67 studies are needed to deeply understand the composition and the relationship of the species 68 belonging to the genus Porphyra with their microbiome. 69 Studies on Porphyra yezoensis have demonstrated that both the life cycle and growth of the 70 species are markedly affected by associated or symbiotic bacteria. Indeed, in axenic cultures, 71 P. yezoensis loose its typical morphogenesis during the gametophytic phase, although it kept 72 morphogenesis during the sporophytic phase; but adding specific symbiotic bacteria to the 73 xenic cultures, P. yezoensis recovered the deficient morphogenesis, restoring the typical folious 74 morphology of the gametophytic generation. These results lead to the conclusion that these 75 symbiontic bacteria are needed for the typical growth and morphogenesis of the thallus (Mori 76 et al., 2004; Tang et al., 2014). In particular Namba et al., (2010) analysed the 16S rDNA gene 77 from cultured strains of P. yezoensis finding sequences of several bacteria characterized into 78 six groups comprising α-, β-, and γ-proteobacteria, Lentisphaerae, Sphingobacteria, and 79 Flavobacteria. 80 On the other hand, since the reproductive phases among the Porphyra species can vary greatly, 81 it is likely that this could be reflected on the composition of the microbial species associated to 82 each different species belonging to this genus (Brodie and Irvine, 2003). It is also important to 83 underline that different species of macroalgae collected from the same area support different 84 bacterial communities, while the same species are often characterized by similar bacterial 85 communities even if collected from different localities, which can vary among each species at 86 season level (Lachnit et al., 2011). 87 To date, the most widely for characterizing the diversity of microbiota is amplicon sequencing. 88 This strategy is based on targeting and amplifying by PCR a taxonomically informative 89 genomic marker that is common to all organisms of interest. The resultant amplicons are 90 sequenced and characterized to determine which microbes are present in the sample and at what 91 relative abundance. In the case of Bacteria and Archaea, amplicon sequencing studies target 92 the small and large subunit of ribosomal RNA (16S) locus, which is an informative marker 93 both for phylogeny and taxonomy analyses (Pace et al., 1986; Hugenholtz and Pace, 1996). 94 Amplicon sequencing of the 16S locus has given insights on microbial diversity on Earth (Pace, 95 1997; Rappé and Giovannoni, 2003; Lozupone and Knight, 2007) and used to characterize the 96 biodiversity of microbes from a range of environments including ocean thermal vents 97 (McCliment et al., 2006), hot springs (Bowen De León et al., 2013), antarctic volcano mineral 98 soils (Soo et al., 2009). 99 Moreover, amplicon sequencing is not without limitation as it may not achieve a resolution of 100 a substantial fraction of the diversity in a community given various PCR associated biases 101 (Sharpton et al., 2011; Hong et al., 2009; Logares et al., 2013). Moreover, it can give 102 considerably varying estimates of diversity due to the 16S gene variants of the bacterial genera 103 targeted, the sequencing platform or the various centers of choice (A, B, C, D) inside each gene 104 variant window, e.g V1-V3. (Jumpstart Consortium Human Microbiome Project Data bioRxiv preprint doi: https://doi.org/10.1101/2020.11.17.386862; this version posted November 18, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. 105 Generation Working Group, 2012), whereas sequencing error and incorrectly assembled 106 amplicons (i.e., chimeras) are often difficult to identify (Wylie et al., 2012) due to the presence 107 of artifacts. Amplicon sequencing is limited to the analysis of taxa for which taxonomically 108 informative genetic markers are known and can be amplified. Since the 16S locus can be 109 transferred between distantly related taxa (i.e., horizontal gene transfer), analysis of 16S 110 sequences for the estimation of the community diversity may result in overestimations (Acinas 111 et al., 2004). Finally, the high level of its sequence conservation limits the power for resolving 112 closely related organisms (Mende et al., 2013) 113 However, apart from 16S rRNA amplicon sequencing, it is actually possible to infer OTU’s 114 based on raw metagenomic reads without PCR amplification, like in the case of the MGnify 115 analysis pipeline version 4.1 (https://www.ebi.ac.uk/metagenomics/pipelines/4.1) (Mitchel et 116 al.
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