Microbiota fingerprints within the oral cavity of cetaceans as indicators for population biomonitoring

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Abstract

The composition of mammalian microbiota has been related with the host health status. In this study, we assessed the oral microbiome of 3 cetacean species most commonly found stranded in Iberian Atlantic waters ( Delphinus delphis, Stenella coeruleoalba and Phocoena phocoena), using 16S rDNA-amplicon metabarcoding. All oral microbiomes were dominated by Proteobacteria, Firmicutes, Bacteroidetes and Fusobacteria bacteria, which were also predominant in the oral cavity of Tursiops truncatus. A Constrained Canonical Analysis (CCA) showed that the major factors shaping the composition of 38 oral microbiomes (p-value < 0.05) were: (i) animal species and (ii) age class, segregating adults and juveniles. The correlation analysis also grouped the microbiomes by animal stranding location and health status. Similar discriminatory patterns were detected using the data from a previous study on Tursiops truncatus, indicating that this correlation approach may facilitate data comparisons between different studies on several cetacean species. This study identified a total of 15 bacterial genera and 27 OTUs discriminating between the observed CCA groups, which can be further explored as microbiota fingerprints to develop (i) specific diagnostic assays for cetacean population conservation and (ii) bio-monitoring approaches to assess the health of marine ecosystems from the Iberian Atlantic basin, using cetaceans as bioindicators.

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mixOmics: An R package for ‘omics feature selection and multiple data integration

Florian Rohart, Benoît Gautier, Amrit Singh … (2017)

The advent of high throughput technologies has led to a wealth of publicly available ‘omics data coming from different sources, such as transcriptomics, proteomics, metabolomics. Combining such large-scale biological data sets can lead to the discovery of important biological insights, provided that relevant information can be extracted in a holistic manner. Current statistical approaches have been focusing on identifying small subsets of molecules (a ‘molecular signature’) to explain or predict biological conditions, but mainly for a single type of ‘omics. In addition, commonly used methods are univariate and consider each biological feature independently. We introduce mixOmics, an R package dedicated to the multivariate analysis of biological data sets with a specific focus on data exploration, dimension reduction and visualisation. By adopting a systems biology approach, the toolkit provides a wide range of methods that statistically integrate several data sets at once to probe relationships between heterogeneous ‘omics data sets. Our recent methods extend Projection to Latent Structure (PLS) models for discriminant analysis, for data integration across multiple ‘omics data or across independent studies, and for the identification of molecular signatures. We illustrate our latest mixOmics integrative frameworks for the multivariate analyses of ‘omics data available from the package.

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Defining the healthy "core microbiome" of oral microbial communities

Egija Zaura, Bart JF Keijser, Susan M. Huse … (2009)

Background Most studies examining the commensal human oral microbiome are focused on disease or are limited in methodology. In order to diagnose and treat diseases at an early and reversible stage an in-depth definition of health is indispensible. The aim of this study therefore was to define the healthy oral microbiome using recent advances in sequencing technology (454 pyrosequencing). Results We sampled and sequenced microbiomes from several intraoral niches (dental surfaces, cheek, hard palate, tongue and saliva) in three healthy individuals. Within an individual oral cavity, we found over 3600 unique sequences, over 500 different OTUs or "species-level" phylotypes (sequences that clustered at 3% genetic difference) and 88 - 104 higher taxa (genus or more inclusive taxon). The predominant taxa belonged to Firmicutes (genus Streptococcus, family Veillonellaceae, genus Granulicatella), Proteobacteria (genus Neisseria, Haemophilus), Actinobacteria (genus Corynebacterium, Rothia, Actinomyces), Bacteroidetes (genus Prevotella, Capnocytophaga, Porphyromonas) and Fusobacteria (genus Fusobacterium). Each individual sample harboured on average 266 "species-level" phylotypes (SD 67; range 123 - 326) with cheek samples being the least diverse and the dental samples from approximal surfaces showing the highest diversity. Principal component analysis discriminated the profiles of the samples originating from shedding surfaces (mucosa of tongue, cheek and palate) from the samples that were obtained from solid surfaces (teeth). There was a large overlap in the higher taxa, "species-level" phylotypes and unique sequences among the three microbiomes: 84% of the higher taxa, 75% of the OTUs and 65% of the unique sequences were present in at least two of the three microbiomes. The three individuals shared 1660 of 6315 unique sequences. These 1660 sequences (the "core microbiome") contributed 66% of the reads. The overlapping OTUs contributed to 94% of the reads, while nearly all reads (99.8%) belonged to the shared higher taxa. Conclusions We obtained the first insight into the diversity and uniqueness of individual oral microbiomes at a resolution of next-generation sequencing. We showed that a major proportion of bacterial sequences of unrelated healthy individuals is identical, supporting the concept of a core microbiome at health.

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Marine mammals as sentinel species for oceans and human health.

Gregory Bossart (2011)

The long-term consequences of climate change and potential environmental degradation are likely to include aspects of disease emergence in marine plants and animals. In turn, these emerging diseases may have epizootic potential, zoonotic implications, and a complex pathogenesis involving other cofactors such as anthropogenic contaminant burden, genetics, and immunologic dysfunction. The concept of marine sentinel organisms provides one approach to evaluating aquatic ecosystem health. Such sentinels are barometers for current or potential negative impacts on individual- and population-level animal health. In turn, using marine sentinels permits better characterization and management of impacts that ultimately affect animal and human health associated with the oceans. Marine mammals are prime sentinel species because many species have long life spans, are long-term coastal residents, feed at a high trophic level, and have unique fat stores that can serve as depots for anthropogenic toxins. Marine mammals may be exposed to environmental stressors such as chemical pollutants, harmful algal biotoxins, and emerging or resurging pathogens. Since many marine mammal species share the coastal environment with humans and consume the same food, they also may serve as effective sentinels for public health problems. Finally, marine mammals are charismatic megafauna that typically stimulate an exaggerated human behavioral response and are thus more likely to be observed.

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Author and article information

Contributors

Pedro Miguel Santos:

ORCID: http://orcid.org/0000-0003-3234-4265

psantos@bio.uminho.pt

Journal

Journal ID (nlm-ta): Sci Rep

Journal ID (iso-abbrev): Sci Rep

Title: Scientific Reports

Publisher: Nature Publishing Group UK (London )

ISSN (Electronic): 2045-2322

Publication date (Electronic): 23 September 2019

Publication date PMC-release: 23 September 2019

Publication date Collection: 2019

Volume: 9

Electronic Location Identifier: 13679

Affiliations

[1 ]ISNI 0000 0001 2159 175X, GRID grid.10328.38, Department of Biology and Centre for Molecular and Environmental Biology (CBMA), , University of Minho, Campus de Gualtar, ; 4710-087 Braga, Portugal

[2 ]ISNI 0000 0004 0462 1680, GRID grid.267033.3, University of Puerto Rico, School of Medicine, Department of Microbiology and Medical Zoology, Microbial Ecology and Genomics Lab, GPO Box 365067, ; San Juan, Puerto Rico 00936-5067 USA

[3 ]Portuguese Wildlife Society (SPVS), Quiaios, Field Station, Apartado 16 EC Quiaios, 3081-101 Figueira da Foz, Portugal

[4 ]Coordinadora para o Estudo dos Mamíferos Mariños (CEMMA), P.O. Box 15, 36380 Pontevedra, Gondomar Spain

[5 ]ISNI 0000000123236065, GRID grid.7311.4, Department of Biology and CESAM, , University of Aveiro, ; 3810-193 Aveiro, Portugal

Author information

Pedro Soares-Castro http://orcid.org/0000-0003-0578-0299

Pablo Covelo http://orcid.org/0000-0002-4507-2943

Pedro Miguel Santos http://orcid.org/0000-0003-3234-4265

Article

Publisher ID: 50139

DOI: 10.1038/s41598-019-50139-7

PMC ID: 6757053

PubMed ID: 31548611

SO-VID: 01f778a8-fb45-4ff9-9fb4-15fdf03d8e16

License:

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

History

Date received : 14 March 2019

Date accepted : 5 September 2019

Funding

Funded by: NIH RCMI Grant No. 2U54MD007600

Funded by: Fundação para a Ciência e a Tecnologia, grant SFRH/BD/30240/2006

Funded by: Fundação para a Ciência e a Tecnologia, grants: UID/AMB/50017/2013 and RECI/AAGGLO/0470/2012

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ScienceOpen disciplines: Uncategorized

Keywords: microbial ecology,metagenomics,microbiome,food webs

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ScienceOpen disciplines: Uncategorized

Keywords: microbial ecology, metagenomics, microbiome, food webs

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Microbiota fingerprints within the oral cavity of cetaceans as indicators for population biomonitoring

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Most cited references 61

mixOmics: An R package for ‘omics feature selection and multiple data integration

Defining the healthy "core microbiome" of oral microbial communities

Marine mammals as sentinel species for oceans and human health.

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