Characterization of black patina from the Tiber River embankments using Next-Generation Sequencing

Abstract

Black patinas are very common biological deterioration phenomena on lapideous artworks in outdoor environments. These substrates, exposed to sunlight, and atmospheric and environmental agents (i.e. wind and temperature changes), represent extreme environments that can only be colonized by highly versatile and adaptable microorganisms. Black patinas comprise a wide variety of microorganisms, but the morphological plasticity of most of these microorganisms hinders their identification by optical microscopy. This study used Next-Generation Sequencing (NGS) (including shotgun and amplicon sequencing) to characterize the black patina of the travertine embankments (muraglioni) of the Tiber River in Rome (Italy). Overall, the sequencing highlighted the rich diversity of bacterial and fungal communities and allowed the identification of more than one hundred taxa. NGS confirmed the relevance of coccoid and filamentous cyanobacteria observed by optical microscopy and revealed an informative landscape of the fungal community underlining the presence of microcolonial fungi and phylloplane yeasts. For the first time high-throughput sequencing allowed the exploration of the expansive diversity of bacteria in black patina, which has so far been overlooked in routine analyses. Furthermore, the identification of euendolithic microorganisms and weathering agents underlines the biodegradative role of black patina, which has often been underestimated. Therefore, the use of NGS to characterize black patinas could be useful in choosing appropriate conservation treatments and in the monitoring of stone colonization after the restoration interventions.

Fig 1. The northwestern embankment of the Tiber River along Porto di Ripa Grande.

The arrows indicate two examples of sampled areas (black arrow = B; white arrow = U).

Fig 2. Optical microscope images of the microorganisms observed in B samples.

(A) Chroococcus litophilus (Cyanobacteria); (B) coccoid green alga (Chlorophyta); (C) meristematic fungus.

Fig 3. Statistical analyses of 16S rRNA gene sequencing data.

(A) Beta diversity represented by Principle Coordinate Analysis Emperor plot on a Bray-Curtis distance matrix; (B) Boxplots of Alpha-diversity Index (calculated as Shannon index) in both black patina and uncolonized region samples; (C) Stacked bar charts of the taxonomic profile at family level, low abundance taxa are lumped together in the “Others” category.

Fig 4. Statistics about ITS2 data.

(A) Beta diversity represented by a Principle Coordinate Analysis Emperor plot on a Bray-Curtis distance matrix; (B) Stacked bar charts of the taxonomic profile at species level, low abundance taxa are lumped together in the “Others” category.

Fig 5. Species found to be differentially abundant using LEfSe analysis on shotgun metagenomics data analyzed using kraken.

Fig 6. Bar charts summarizing the number of proteins annotated (y-axis) in a specific COG category (on the x) in the seven MAGs.

Fig 7. Boxplots showing the differential abundance of specific bacterial taxa.

The graphics are divided according to the phyla they belong.

Fig 8. Boxplots showing the differential abundance of specific fungal taxa.

The graphics are divided according to the order they belong.