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. 2018 Dec 5;6(1):216.
doi: 10.1186/s40168-018-0599-9.

Rock Substrate Rather Than Black Stain Alterations Drives Microbial Community Structure in the Passage of Lascaux Cave

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Free PMC article

Rock Substrate Rather Than Black Stain Alterations Drives Microbial Community Structure in the Passage of Lascaux Cave

Lise Alonso et al. Microbiome. .
Free PMC article

Abstract

Background: The World-famous UNESCO heritage from the Paleolithic human society, Lascaux Cave (France), has endeavored intense microclimatic perturbations, in part due to high touristic pressure. These perturbations have resulted in numerous disturbances of the cave ecosystem, including on its microbial compartment, which resulted in the formation of black stains especially on the rock faces of the passage. We investigated the cave microbiome in this part of Lascaux by sampling three mineral substrates (soil, banks, and inclined planes) on and outside stains to assess current cave microbial assemblage and explore the possibility that pigmented microorganisms involved in stain development occur as microbial consortia.

Methods: Microbial abundance and diversity were assessed by means of quantitative PCR and high-throughput sequencing (Illumina MiSeq) of several DNA and cDNA taxonomic markers. Five sampling campaigns were carried out during winter and summer to embrace potential seasonal effect in this somewhat stable environment (based on measurements of temperature and CO2 concentration).

Results: While the season or type of mineral substrate did not affect the abundances of bacteria and micro-eukaryotes on or outside stains, mineral substrate rather than stain presence appears to be the most significant factor determining microbial diversity and structuring microbial community, regardless of whether DNA or cDNA markers were considered. A phylogenetic signal was also detected in relation to substrate types, presence of stains but not with season among the OTUs common to the three substrates. Co-occurrence network analyses showed that most bacterial and fungal interactions were positive regardless of the factor tested (season, substrate, or stain), but these networks varied according to ecological conditions and time. Microorganisms known to harbor pigmentation ability were well established inside but also outside black stains, which may be prerequisite for subsequent stain formation.

Conclusions: This first high throughput sequencing performed in Lascaux Cave showed that black stains were secondary to mineral substrate in determining microbiome community structure, regardless of whether total or transcriptionally active bacterial and micro-eukaryotic communities were considered. These results revealed the potential for new stain formation and highlight the need for careful microbiome management to avoid further cave wall degradation.

Keywords: Bacterial-fungal co-occurrence; Lascaux Cave; Microbial community; Microbial degradation.

Conflict of interest statement

Ethics approval and consent to participate

Not applicable.

Consent for publication

S. Konik, Centre National de la Préhistoire, consents the publication of the photographic picture presented in Fig.1. The DRAC Nouvelle Aquitaine (Bordeaux, France) consents the use of temperature and CO2 concentration data recorded during sampling period.

Competing interests

The authors declare they have no competing interests.

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Figures

Fig. 1
Fig. 1
Map of Lascaux Cave with location of the passage (source: MCC-CNP) and internal structure of the passage with the three mineral substrates studied (soil, banks, inclined planes) (source: S. Konik, Centre National de la Préhistoire; photograph taken on 29 September 2017)
Fig. 2
Fig. 2
Bacterial and micro-eukaryotic abundances according to presence of black stains. Abundance data are shown as mean log number of 16S rRNA and 18S rRNA genes copies ± standard errors. Quantitative PCR analysis was performed in duplicate. Letters indicate post-hoc grouping according to significant differences between sample origin
Fig. 3
Fig. 3
Alpha diversity indices of microbial communities according to mineral substrate and stain presence, based on estimated richness (Chao 1 index), diversity (Shannon H′ index), and evenness (Simpson index). For each index × community combination, significant differences according to mineral substrate and stain presence and post-hoc grouping are shown with letters (Wilcoxon tests, P < 0.05). The same findings were obtained when using the observed number of taxa instead of Chao 1 index (not shown)
Fig. 4
Fig. 4
Non-metric multidimensional scaling (NMDS) analysis of microbial community structure in the passage according to time, mineral substrate and stain presence. Results are shown for bacteria (a), micro-eukaryotes (b), and fungi (c), and ellipses (95% confidence intervals) indicate the different mineral substrates
Fig. 5
Fig. 5
Non-metric multidimensional scaling (NMDS) analysis of the entire (DNA analysis) and transcriptionally-active (RNA analysis) microbial communities in the passage according to mineral substrate (banks and inclined planes) and stain presence. Data are shown for bacteria (a), all micro-eukaryotes (b), and only fungi (c). Ellipses correspond to 95% confidence intervals for each mineral substrate
Fig. 6
Fig. 6
Phylogenetic tree of OTUs common to the three mineral substrates based on analysis of 16S rRNA genes (a), 18S rRNA genes (b), and fungal ITS (c). The size of pie charts represents the relative abundance of each OTU, and colors the distribution across mineral substrates (soil in red, banks in green, and inclined planes in blue). Groups of OTUs (i.e., groups 1–34 in a, 1–14 in b, and 1–8 in c) used to compute NRI and NTI values listed in Table S1 are indicated on the outside
Fig. 7
Fig. 7
The co-occurrence networks of bacteria and fungi based on 16S rRNA and ITS MiSeq Illumina sequences. Connections materialize strong (Spearman’s ǀρǀ > 0.85) and significant (P < 0.001) correlations. Co-occurrence networks are shown after combining all data for December 2014 (a), June–July 2015 (b), December 2016 (c), soil (d), banks (e), inclined planes (f), unstained parts (g), and black stains (h). Blue nodes depict bacterial taxa and green nodes fungal taxa. Links in gray indicate positive co-occurrence and links in red negative co-occurrence. The size of nodes is scaled to their Eigenvector centrality

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