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Microbial communities on painted wet and dry external surfaces of a historic fortress in Niterói, Brazil
International Biodeterioration & Biodegradation 123 (2017) 164e173
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Microbial communities on painted wet and dry external surfaces of a i, Brazil historic fortress in Nitero Akiko Ogawa a, 1, Sukriye Celikkol-Aydin a, Christine Gaylarde a, *, ^ nio Baptista-Neto b, Iwona Beech a Jose Anto a
University of Oklahoma, Department of Microbiology and Plant Biology, 770 Van Vleet Oval, Norman, OK 73019, USA Universidade Federal Fluminense, Departamento de Geologia e Geofísica, Av. General Milton Tavares de Souza, s/n, 4 Andar, Campus da Praia Vermelha, i, RJ, Brazil 24210-346, Nitero b
a r t i c l e i n f o
a b s t r a c t
Article history: Received 30 April 2017 Received in revised form 27 June 2017 Accepted 28 June 2017
Bacteria, algae and fungi colonising dry (F1) and wet (F2) white painted walls in the fortress of Santa Cruz i, Brazil, were detected using field emission-scanning electron microscopy (FE-SEM) and da Barra, Nitero next generation DNA sequencing (NGS) techniques. Major bacterial phyla Operational Taxonomic Units (OTUs) detected were Chloroflexi in the wet green biofilm F2 (38.85% compared with 7.56% in F1) and Proteobacteria in the dry grey biofilm F1 (57.17% compared with 28.69% in F2). Diatoms were detected at both sites by FE-SEM, but only at F1 by NGS. More algae and cyanobacteria were identified at F1, and this was the only biofilm containing Archaea, possibly related to the high level of salt efflorescences at this site. Although thinner, F1 biofilm showed considerably higher genus richness than the wet biofilm, F2. The thickness and appearance of the biofilms did not correlate with their genomic complexity. Ascomycetes of the Sordariomycetes were major fungi identified at both sites, Khuskia (3.33% OTUs) at F1 and Emericellopsis (7.99% OTUs) at F2, and few filamentous forms were seen by microscopy. However, many fungal OTUs could not be identified to phylum level. Potential bacterial and fungal paint deteriogens were detected at both sites. The results confirmed the importance of using a variety of techniques in the study of microbial communities. © 2017 Elsevier Ltd. All rights reserved.
Keywords: Biofilms Coatings Cultural property Metagenomics Moisture
1. Introduction i, Brazil, began conThe Fortress of Santa Cruz da Barra, Nitero struction in 1578, as the major defence for the entrance to Guanabara Bay in the city of Rio de Janeiro. The major stone used was the locally available augen gneiss. The fortress is still an important military base, but is open to the public and is the second most i. It is located at the most westerly point visited attraction in Nitero ~o de Açúcar of the Jurujuba peninsula, almost facing the Pa (Sugarloaf mountain) in Rio de Janeiro. Being military property, it is maintained in excellent condition, but is, nevertheless, subject to the adverse environmental conditions associated with the sub i has mean monthly air temtropical marine atmosphere. Nitero peratures varying from 20 C (July) to 27 C (February) and mean
* Corresponding author. E-mail address: [email protected] (C. Gaylarde). 1 Current address: Department of Chemistry and Biochemistry, National Institute of Technology, Suzuka College, Suzuka, Japan. http://dx.doi.org/10.1016/j.ibiod.2017.06.018 0964-8305/© 2017 Elsevier Ltd. All rights reserved.
annual rainfall of 1200 mm, ranging from 550 to 1900 mm. Grey, black, green, red and brown biofilms rapidly form on the white painted surfaces of the fort buildings, promoted by the high relative humidity, which is around 80% all year round. The potential problems associated with these biofilms include utilization of paint components by biofilm organisms that leads to degradation of the coating, production of microbial pigments causing discoloration of the paint film, and damage to the substratum by microorganisms, or microbial metabolites, penetrating the paint layer. The importance of microbial biofilms for the deterioration of stone surfaces was reviewed in 2009 (Scheerer et al., 2009) and of paint coatings in 2011 (Gaylarde et al., 2011). Overflows from drainage pipes on buildings lead to areas of permanent wetness, which are associated with thick biofilms (Crispim et al., 2004). There is considerable information about microbial growth on the external surfaces of historic and cultural buildings (Dakal and Cameotra, 2011; Scheerer et al., 2009, and references in both) and on the microorganisms growing on water damaged internal surfaces of buildings (Goll et al., 1952;
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Ignatavi cius and Ignatavi cius, 2005; Andersen et al., 2011). The phototrophic population prevalent on exterior areas of water overflow has been, to some extent, investigated by traditional culture and microscopy methods (Crispim et al., 2003; Gaylarde and Gaylarde, 2005). However, there is no published information on the difference between the constituents of the microbial biofilm on painted external surfaces of the same building in areas affected or not by constant wetness caused by overflow pipes, especially as identified by modern molecular analytical techniques. This article reports the use of Next Generation Sequencing (NGS), or metagenomic technology, together with traditional microscopy, to investigate these communities on the Fortress of Santa Cruz.
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2. Materials and methods 2.1. Sampling i, adhesive tape At the Fortress of Santa Cruz da Barra, Nitero and surface scraping samples were taken from growth on the painted entrance area of an external room, showing dry, mainly grey, biofilms and internal salt efflorescences, facing North-East (F1) and from a wet, heavily biofilmed overflow site (F2) on a painted external wall facing South (Fig. 1). Samples were taken as detailed in Gaylarde et al. (2017), with the additional use of sterile Eppendorf tubes for scraping samples from the solid
Fig. 1. The fortress of Santa Cruz, Niteroi, Brazil, showing sampling sites (red arrows); a) growth on overflow from drainage pipe (F2); b) entrance into open room on lower floor (F1); c) red/orange staining (arrow) caused by growth of the green alga Trentepohlia on stone wall of the fortress. Note grey lichen growth (white arrow) on surface of parapet in b). (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)
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Fig. 2. FE-SEM images of diatoms in the Santa Cruz fortress samples a) Diatoma in sample F1. Bar marker 10 mm; b) Fragilaria in sample F2 from overflow area. Groups of bacteria (mainly rod-shaped) are also seen (arrows). Bar marker 2 mm; c) Diatoms and bacterial agglomerates in sample F2. Bar marker 10 mm.
surfaces. A maximum depth of 3 mm was collected and separate layers were not maintained.
as: D ¼ s / √N
2.2. Sample analysis Samples were examined using the field emission scanning electron microscope, FE-SEM and by DNA analysis using Illumina Mi-Seq Next Generation Sequencing (NGS) with bacterial 519Fand 785R 16SrRNA gene primers and fungal ITS1F2 and ITS2 primers, all as described in Gaylarde et al. (2017). In all cases, at least two different samples (biological replicates) were analysed. 2.3. Data analysis The bacterial 16S rRNA gene libraries were pre-processed and analyzed using two pipelines that included either the Greengenes or the SILVA database, as described in Celikkol-Aydin et al. (2016). The fungal ITS gene libraries were treated using the UNITE database, as described in Gaylarde et al. (2017). Raw data files were deposited in the NCBI Sequence Read Archive (SRA) with accession number SRP076760. Menhinick's Index of genus richness at each site was calculated
Where s ¼ total number of different genera, and N ¼ total number of OTUs. The Jaccard Index of Similarity was calculated for both bacterial and fungal microbiomes, using the formula Sj ¼ j / (aþb-j) Where a ¼ number of OTU types at site 1 (dry), b ¼ number of OTU types at site 2 (wet) and j ¼ number of OTU types shared by both sites. Principal Components Analysis (PCA) was also used to compare the prokaryotic and the fungal populations at the two sites. PCA plots and loading plots were acquired from taxonomic abundances using the R environment (r-project.org).
3. Results and discussion Sampled biofilms were grey/light green in the case of F1, the dry
A. Ogawa et al. / International Biodeterioration & Biodegradation 123 (2017) 164e173 Table 1 Weight of samples and extracted DNA, together with total number of OTUs identified. Sample
Weight (g)
Collected DNA (ng)
No. of bacterial OTUs
No. of fungal OTUs
F1a F1b F2a F2b
0.05 <0.01 0.02 0.07
1430 1040 662 626
15726 9287 19611 9395
19635 8601 21680 18056
Duplicate biological samples from F1 (entrance) and F2 (wet wall).
site, and brown/dark green in the case of the wet biofilm, F2 (Fig. 1). In addition, red/orange biofilms of the green alga Trentepohlia were seen on south-west facing stone surfaces and the grey lichen Parmelia saxatilis (whose photobiont comprises species of the coccoid alga Trebouxia) was present on upper surfaces of the unpainted stone walls (Fig. 1). The orientation pattern of Trentepohlia growth on surfaces receiving lower levels of solar irradiation conforms to that reported at the Rio Bec style Mayan buildings in the Mexican State of Campeche (Ortega-Morales et al., 2013), facing in the opposing direction in this southern hemisphere site. The presence of the lichen indicates the low air pollution around the fortress, which is situated far from major roads and surrounded on three sides by the Atlantic Ocean. Quantities of DNA extracted from the samples are shown in Table 1, together with the total number of Operational Taxonomic Units (OTUs) identified. Although only low levels of DNA were extracted from some samples, amplification and sequencing analysis were achieved.
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3.1. Bacteria and phototrophs The results of the bacterial DNA analyses are shown in Figs. 3 and 4. The major phyla OTUs detected were of Chloroflexi in the wet biofilm F2 (38.85% compared with 7.56% in F1) and Proteobacteria in the dry biofilm F1 (57.17% compared with 28.69% in F2). This may be correlated with the surface discoloration produced by the biofilms, bright green in the case of F2 and mainly grey in F1. There were some differences between taxa detected by the two different pipelines, a fact that has also been pointed out for stone church façades in Rio de Janeiro (Ogawa et al., 2017) and for hot et al., 2016), and which may, spring bacterial NGS analyses (Krakova in large part, be due to the database used. The Greengenes database-containing pipeline was better able to identify phototrophs and Clostridiales than that containing the SILVA database. A lower proportion of alphaproteobacteria was detected overall with the former pipeline. Neverthess, alphaproteobacteria was still identified as the major class in the dry biofilm, F1. The Rhodospirillales order was the major component, with 13.64% OTUs (2.87% in F2), and within that order an unidentified Acetobacteriaceae was the main genus (6.6% genus OTUs). Within the lower abundance of alphaproteobacteria in the wet biofilm, the Rhodospirillales family Caulobacteriaceae was the main component at 4.13% family OTUs, the principal genus being Brevundimonas (3.22% genus OTUs). Figures given are from the Greengenes database analysis. Rhodospirillales have been found to be particularly abundant in the marine atmosphere (Klein et al., 2016). They may produce acids during their metabolism, which would cause paint film damage, and some members possess cellulase activity (Mehdipour-Moghaddam et al., 2010), which could also lead to paint degradation. Hence these
Fig. 3. Bacterial phylum OTUs (%) identified using the Greengenes database in duplicate (biological) samples from the Fortress of Santa Cruz, Niteroi. F1 e dried entrance biofilm; F2 e wet external biofilm. OTU abundances <0.06% not included. Key colours begin at 12 o'clock with Unidentified and continue in a clockwise manner from left to right and top to bottom rows, finishing just before 12 o'clock with Thermi. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)
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Fig. 4. Bacterial class OTUs identified at the two sites on the fortress of Santa Cruz. F1 ¼ dry site, F2 ¼ wet site; a) and b) are duplicate (biological) samples. Analysis was carried out using the SILVA database and OTUs below 0.06% are not included. Key colours begin at 12 o'clock with Acidobacteria and continue in a clockwise manner and from left to right and top to bottom rows, finishing just before 12 o'clock with Gammaproteobacteria. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)
could be important community members for coatings biodegradation. Of particular microbiological interest is the presence of low levels of Archaea in the dry biofilm; Halobacteria was present at an average of 0.2% OTUs, Thaumarchaeota; Marine Group I at 0.02% and Thaumarchaeota; Soil Crenarchaeotic Group at 0.03% OTUs. Archaea were absent from F2. The difference may be related with the salt deposits observed at F1; archaeal groups detected were mainly halophilic. No Archaea were detected by NGS on the painted surface of a 19th century house in Lodz, Poland, using either archaea-specific or bacteria-specific primers, although they were present on the brick (Adamiak et al., 2017). On the Santa Cruz fortress, there was also an interesting higher abundance of anaerobes, in the form of the order Clostridiales, at site F2 (0.56% compared to 0.04% at F1, and 0.70% compared to 0.085% at F1, for Greengenes and SILVA analyses, respectively). This may be explained by the greater thickness of the wet biofilm, allowing the production of anaerobic conditions at its base. However, there was no significant difference between the abundances of facultative and microaerophilic groups at the sites. It was anticipated that algae would be present at higher levels in the wet green biofilm, F2. It has long been known that high water activity promotes the growth of algae, which are more prevalent in
wet sites than in drier areas (Gillatt and Tracey, 1987; Crispim et al., 2003; Li et al., 2016). These studies, which show more algae in wetter locations, were non-molecular, and one of the present authors has found similar results in widely differing locations. For example, in a thick green biofilm in the water run-off from the capital of a pillar in the Echevery Palace, Bogota, Colombia, principal microorganisms detected were the algae Klebsormidium and Stichococcus, together with actinomycetes and rotifers, while the humid base of a stature in Queen's Square, London, UK, was colonised mainly by the algae Hormidium, Chlorosarcina and diatoms, along with Chloroflexi, protozoa and a Geodermatophiluslike Actinobacteria (CG, unpublished observations). However, in the current (molecular) investigation an average of 1.22% chloroplast OTUs (representing algae) were detected in F1 compared with only 0.12% at the wet site, F2, and FE-SEM did not indicate the presence of higher numbers of algae in the wet biofilm. Liquid water or 100% air humidity are said to be necessary for optimum photosynthesis €ubner et al., 2006). and growth of aeroterrestrial microalgae (Ha These authors investigated the effect of changing water availability and air humidity on an aeroterrestrial green algal biofilm on a building surface over several months. The photosynthetic activity correlated with the presence of water condensing on the façade. As insolation increased during the day, the water evaporated and
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Fig. 5. Fungal Class OTUs (%) identified in duplicate (biological) samples from the Fortress of Santa Cruz, Niteroi. F1 ¼ dried entrance biofilm; F2 ¼ wet external biofilm. A very high percentage of OTUs could not be identified as any fungal class. Key colours begin at 12 o'clock with Botryosphaeriaceae and continue in a clockwise manner from left to right and top to bottom rows, finishing just before 12 o'clock with Zygomycota. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)
photosynthesis was inhibited, recovering within minutes after artificial moistening. Similar high tolerance to dehydration has been described for soil-crust green algae of the genus Klebsormidium (http://journal.frontiersin.org/article/10.3389/fpls.2013. 00327/full, Karsten and Holzinger, 2012). In the Santa Cruz biofilm samples, the Greengenes pipeline, but not that containing the SILVA database, allowed the detection of 2% unidentified Chlorococcales, 1.18% Streptophyta (which includes the genus Klebsormidium) and 0.19% Stramenopiles (diatoms) in F1. All these OTU groups were absent from the F2 analyses, but diatoms were detected in both F1 and F2 by FE-SEM (Fig. 2). Cave biofilms have been found to be dominated by diatoms, if they are wet and
exposed to light (Falasco et al., 2014), but it is normally assumed that diatoms do not survive desiccation. The current results suggest that this is not true; high temperatures on the painted surfaces during the day rapidly cause dehydration of biofilms in this subtropical location and yet diatoms were common in dry biofilm F1. Souffreau et al. (2011) showed that although desiccation effectively kills most diatoms, terrestrial isolates of diatom species normally found in aquatic locations survived drying at þ40 C. Diatoms were not seen in the Santa Cruz biofilms using light microscopy, but were visualised by FE-SEM. These results confirm the importance of using a variety of techniques in the study of microbial communities. Using the Greengenes pipeline, 0.12% chlorophyta were detected
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in F2, as compared with 0% in F1. This could explain the dark green colour of the former, wet biofilm, in conjunction with the presence within it of 38.85% Chloroflexi OTUs (compared with only 7.56% in F1) and 0.22% OTUs of the anaerobic green sulfur bacteria, Chlorobi, which were absent from F1. Indeed, Chloroflexi was the major bacterial phylum detected in biofilm F2. However, there may be no direct relationship between moisture levels and formation of green biofilms (Cutler et al., 2013). Phototrophs are not considered to be physically damaging to painted surfaces, apart from their waterholding capacity, but many are pigmented, leading to aesthetic deterioration, and, of course, they can provide nutrients for other, deteriogenic, organisms. Previous work in the sub-tropics (Gaylarde and Gaylarde, 2005) has shown that cyanobacteria are the major phototrophs on dry building surfaces and may form biofilms of various colours, though rarely bright green. Desiccation tolerance is well documented for cyanobacteria and lichens (Holzinger and Karsten, 2013, and references therein). In the case of Santa Cruz fortress, over 7% of phylum OTUs at both sites belonged to these organisms, similar to the proportion of Chloroflexi detected in F1. Of these Cyanobacteria, class OTU abundances of 3.19% Nostocophycideae in F2, and 4.95% Oscillatoriophycideae and 2.34% Synechococcophycideae in F1 were identified by the Greengenes database, which continues to use the botanical nomenclature system for these prokaryotes.
because temperatures in the latter regions tend to be higher, reducing the time for which liquid water is present on building surfaces (“time of wetness”). On stone, algae formed the major biomass on most European monuments, while cyanobacteria, more resistant to adverse conditions, were the principal colonisers in Latin America. 3.3. Comparison of microbial communities As indicated above, there was considerable dissimilarity between the wet and the dry biofilms. The Jaccard Indices of Similarity between the two sites for bacterial and fungal communities
3.2. Fungi Fungi have been considered the major deteriogenic organisms of wet surfaces in building interiors (Goll et al., 1952; Ignatavi cius and Ignatavi cius, 2005; Andersen et al., 2011), although they may be superseded on external walls by phototrophic microorganisms. Fungi have been found, by traditional culture and microscopy techniques, to form the major biomass on external painted surfaces in Latin America (Gaylarde and Gaylarde, 2005), but few filamentous fungi were seen in the Santa Cruz samples by microscopy. Fungal classes identified at the two sites by the sequencing analysis are presented in Fig. 5. Since few filamentous fungi were seen by FE-SEM, it is not surprising that the majority of OTUs detected belonged to the ascomycetes, dimorphic fungi that can occur in yeast-like forms. Other genera identified by the NGS technology were probably present on the surfaces as spores. The major fungi identified at the wet site, F2, were ascomycetes of the genus Emericellopsis (7.99% OTUs), whilst F1 contained a more mixed group of Sordariomycete families as the main colonisers, with 2 genera predominating, Khuskia (3.33% OTUs) and Haematonectria (2.76% OTUs). These are all common soil fungi. Overall, 6.99% class OTUs in F1 and 8.12% in F2 represented Sordariomycetes, one of the largest classes in the ascomycetes. Figures are low because of the high proportion of fungal sequences that could not be identified (86.5%). Another class of ascomycetes, the Dothideomycetes, the black rock-inhabiting fungi, were present at 1.53% OTUs in the dry biofilm, F1, but only 0.04% in F2. This could be related to the water content of the biofilms; Dothideomycetes are found in nature under very hostile conditions, including extreme fluctuations of moisture and temperature (Onofri et al., 2014; De Leo and Urzì, 2015). They are slow-growing and would be overrun by more rapidly growing species under wet conditions. Fungal activity requires a minimum relative humidity of 80%e 95% depending on temperature, type and surface conditions of building materials (Viitanen et al., 2009). For decay development, the critical relative humidity is above 95%. Gaylarde and Gaylarde (2005), basing results on the analysis of 230 exterior painted surface samples by culture and microscope techniques, noted that major colonisers in Europe were algae, whilst in Latin America, fungi, folowed by phototrophs, were more prevalent, probably
Fig. 6. PCA plots of bacterial (a) and fungal (b) genomes identified in the Fortress of Santa Cruz, RJ, Brazil, based on the pipelines containing the SILVA and UNITE databases, respectively. F1 ¼ two replicate samples from room opening (dry biofilm), F2 ¼ 2 replicate samples from growth on overflow (wet biofilm).
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were 24.1% and 22.2%, respectively, indicating low similarity between the two at the genus level (identity is indicated by 100%). This was confirmed by the Principal Components Analysis (PCA) for both bacteria and fungi (Fig. 6). Of the bacterial community, 92% (87.7% in the Greengenes analysis) was represented by PC1. The distance between duplicates of F1 on the y (PC2) axis is not
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significant, since it corresponds to only 6% (6.4% in Greengenes) of the community. The duplicates are located on the same line on the PC1 axis, showing that they are practically identical. The bacterial loading plots (Fig. 7) clearly show the dissimilarity between the two sites. More points are seen on the plot calculated from the Greengenes-containing pipeline, since this was able to
Fig. 7. Loading plots of bacterial OTU abundances, based on the pipelines containing the SILVA (a) and Greengenes (b) databases. F1 is represented in red, mainly on the left-hand side and F2 in blue, on the right. The few purple dots seen on the right-hand side represent shared taxa. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)
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Table 2 Microbial groups (mainly phyla) detected in the wet (F2) and dry (F1) wall samples. In the case of NGS detection, only groups present at above 1% OTUs are shown. Principal organisms
Detection method
Present in Potential deteriogenic activity References F1
F2
Acidobacteria
NGS
þ
þ
Actinobacteria Bacteroidetes (e.g. Rhodothermi)
NGS NGS
þ
þ þ
Chloroflexi (e.g. Anaerolineae) Cyanobacteria: Synechococcophycideae Nostocophycideae Oscillatoriophycidiae Firmicutes (e.g. Bacilli) Gemmatimonadetes Planctomycetes Proteobacteria Alphaproteobacteria (e.g.,Rhodospirillales) Betaproteobacteria Gammaproteobacteria Algae: Diatoms Streptophyta Ascomycetes: Emericellopsis Khuskia Haematonectria Dothideomycetes
NGS NGS
þ þþ þþ þþ þ þþþ þþ þ þ þþ þ þ þþ þþ þþ þþ
þ þ þ þ þþ þþ
NGS NGS NGS NGS NGS NGS NGS NGS NGS&SEM NGS NGS
Chen et al., 2016, and refs therein; Raymond, 2008
þþ þ
Acid production, discolouration Degradation, discolouration Discolouration, acid production Discolouration, degradation Discolouration
þþ þ þ þ þþþ þþ
Discolouration Discolouration Unknown Acid production, discolouration
Khaneja et al., 2010 Zhang et al., 2003 Mehdipour-Moghaddam et al., 2010;Imhoff, 2006;Garrity, 2006
Discolouration
Gaylarde and Gaylarde, 2005, and refs therein
Acid production Physical penetration Discolouration
De Leo and Urzì, 2015
detect many more different taxa down to the genus level. It is more difficult to interpret the fungal PCAs in this way because of the high percentage of unidentified OTUs. Of those identified, 60.9% of the species were represented by PC1 and 24.7% by PC2. However, the PCA analysis does not show an identical distribution for duplicate samples. This difference might be due to the heterogeneity within each sample; it has previously been noted that fungi on buildings are more heterogeneously distributed than bacteria (Gaylarde et al., 2017). In addition, 72.39%e96.01% of the fungi in F1 and 86.02%e91.45% of those in F2 were assigned as unidentified in the UNITE database. The PCA and loading plots are thus not meaningful for this particular case. The bacterial genus richness, D, for each sample was 0.50 for F1 and 0.344 for F2. The equivalent values for fungal communities were 0.57 (F1) and 0.215 (F2). Unexpectedly, in view of the macroscopic appearance of the biofilms, the dry biofilm community, F1, was much richer than the wet. The thickness and appearance of the biofilms did not correlate with their genomic complexity. These results may be compared with those of Chase et al. (2016), who were unable to find meaningful correlations between levels of community richness, composition, or abundance of specific taxa of interest and equilibrium relative humidity of building surfaces inside offices in North America. A proportion of bacteria, and many fungal OTUs, could not be classified by the NGS technology (16.63% and 86.5%, respectively). This is not dissimilar to results of other molecular analyses of historic buildings. Li et al. (2016) found that 81.74% of bacteria and 64.89% of fungi on the stone surfaces of statues in the Hangzhou province of China were unclassifiable using High Throughput Sequencing with similar amplification and analysis systems to those employed in the current research. Similar high levels of unidentifiable fungal OTUs have been reported for unpainted stone churches in central Rio de Janeiro (Gaylarde et al., 2017). Primer or database inadequacy or failures in DNA extraction may explain
Chen et al., 2016, and refs therein, Trujillo, 2016 Oren, 2006 Imhoff, 2014; Sun et al., 2016 Gaylarde and Gaylarde, 2005, and refs therein
these results in part, and these potential problems are discussed in relation to microbiomes of indoor environments in Adams et al. (2016), but it is obvious that there is considerable unexplained diversity in biofilms formed on external building surfaces. More investigations, using a variety of detection and identification techniques, together with activity measurements such as metabolomics, are essential before this knowledge can confidently be used in the targeted control of coatings biodeterioration. 4. Conclusions Next Generation Sequencing (NGS) techniques allowed a much more detailed analysis of the biofilms on painted wet and dry i, Brazil, than surfaces on the Fortress of Santa Cruz da Barra, Nitero more traditional methods, but these traditional methods were necessary for a more complete analysis. For example, FE-SEM allowed the detection of diatoms in the wet biofilm in addition to the dry one, in which diatom DNA was identified. The principal microbial groups, together with the methods whereby they were detected and their potential deteriogenic activities, are shown in Table 2. Major bacterial phyla Operational Taxonomic Units (OTUs) identified were Chloroflexi in the wet green biofilm and Proteobacteria in the dry grey biofilm. Of the latter, the principal group was the Rhodospiralles, known acid producers. More algae and cyanobacteria were found at the dry site, in spite of its lesser green colouration, and this was the only biofilm containing Archaea, probably related to the high level of salt efflorescences. Ascomycetes of the Sordariomycetes were major fungi identified at both sites, but many OTUs could not be assigned to any particular fungal class. A higher abundance of Dothideomycete OTUs was found in the dry than the wet biofilm, correlating with its darker appearance. Although thinner, the dry biofilm showed considerably higher genus richness than the wet biofilm. The targeted control of paint film biodeterioration requires biofilm analysis using both modern
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and traditional methods, and the new techniques of metabolomics will be of particular interest. References Adamiak, J., Otlewska, A., Tafer, H., Lopandic, K., Gutarowska, B., Sterflinger, K., ~ ar, G., 2017. First evaluation of the microbiome of built cultural heritage by Pin using the ion torrent next generation sequencing platform. Intern. Biodet Biodeg. http://dx.doi.org/10.1016/j.ibiod.2017.01.040. Adams, R.I., Bhangar, S., Dannemiller, K.C., Eisen, J.A., Fierer, N., Gilbert, J.A., Green, J.L., Marr, L.C., Miller, S.L., Siegel, J.A., Stephens, B., Waring, M.S., Bibby, K., 2016. Ten questions concerning the microbiomes of buildings. Build. Environ. 109, 224e234. http://dx.doi.org/10.1016/j.buildenv.2016.09.001. Andersen, B., Frisvad, J.C., Søndergaard, I., Rasmussen, I.S., Larsen, L.S., 2011. Associations between fungal species and water-damaged building materials. Appl. Environ. Microbiol. 77, 4180e4188. Celikkol-Aydin, S., Gaylarde, C.C., Lee, T., Melchers, R.E., Witt, D.E., Beech, I.B., 2016. 16S rRNA gene profiling of planktonic and biofilm microbial populations in the Gulf of Guinea using Illumina NGS. Mar. Environ. Res. 122, 105e112. Chase, J., Fouquier, J., Zare, M., Sonderegger, D.L., Knight, R., Kelley, S.T., Siegel, J., Caporaso, J.G., 2016. Geography and location are the primary drivers of office microbiome composition. mSystems 1 (2). http://dx.doi.org/10.1128/mSystems.00022-16 e00022e16. Chen, P., Zhang, L., Guo, X., Dai, X., Liu, L., Xi, L., et al., 2016. Diversity, biogeography, and biodegradation potential of actinobacteria in the deep-sea sediments along the deep sea sediments along the Southwest Indian Ridge. Front. Microbiol. 7 (1340) http://dx.doi.org/10.3389/fmicb.2016.01340. Crispim, C.A., Gaylarde, P.M., Gaylarde, C.C., 2003. Algal and cyanobacterial biofilms on calcareous historic buildings. Curr. Microbiol. 46, 79e82. Crispim, C.A., Gaylarde, C.C., Gaylarde, P.M., 2004. Biofilms on church walls in Porto Alegre, RS, Brazil, with special attention to cyanobacteria. Intern. Biodet Biodeg 54, 121e124. Cutler, N.A., Viles, H.A., Ahmad, S., McCabe, S., Smith, B.J., 2013. Algal 'greening' and the conservation of stone heritage structures. Sci. Total Environ. 442, 152e164. Dakal, T.C., Cameotra, S.S., 2011. Geomicrobiology of cultural monuments and artworks: mechanism of biodeterioration, bioconservation strategies and applied molecular approaches. In: Mason, A.C. (Ed.), Bioremediation: Biotechnology, Engineering and Environment Management. Nova Science, Hauppauge (NY), pp. 233e266. De Leo, F., Urzì, C., 2015. Microfungi from deteriorated materials of cultural heritage. In: Misra, J.K., Deshmukh, S.K. (Eds.), Fungi from Different Substrates, vol. 7. Science Publishers, Press, pp. 144e158. Falasco, E., Ector, L., Isaia, M., Wetzel, C.E., Hoffmann, L., Bona, F., 2014. Diatom flora in subterranean ecosystems: a review. Intern. J. Speleol. 43, 231e251. Garrity, G., 2006. Bergey's Manual® of Systematic Bacteriology: Volume Two: the Proteobacteria, Part a Introductory Essays, Vol. 2. Springer Science & Business Media. Gaylarde, C.C., Gaylarde, P.M., 2005. A comparative study of the major microbial biomass of biofilms on exteriors of buildings in Europe and Latin America. Intern. Biodet Biodeg 55, 131e139. Gaylarde, C.C., Morton, L.H.G., Loh, K., Shirakawa, M.A., 2011. Biodeterioration of external architectural paint filmsda review. Intern. Biodet Biodeg 65, 1189e1198. Gaylarde, C., Ogawa, A., Beech, I., Kowalski, M., Baptista-Neto, J.A., 2017. Analysis of dark crusts on the church of Nossa Senhora do Carmo in Rio de Janeiro, Brazil, using chemical, microscope and metabarcoding microbial identification techniques. Intern. Biodet Biodeg 117, 60e67. Gillatt, J.W., Tracey, J.A., 1987. The biodeterioration of applied surface coatings and its prevention. In: Morton, L.H.G. (Ed.), Biodeterioration of Constructional Materials. The Biodeterioration Society, Kew, pp. 103e112. Goll, M., Snyder, H.D., Bernbaum, H.A., 1952. A study of discoloured paint on 600 painted house exteriors in America. Am. Paint J. 28, 66e73. €ubner, N., Schumann, R., Karsten, U., 2006. Aeroterrestrial algae growing in Ha biofilms on facades e response to temperature and water stress. Microb. Ecol. 51, 285e293. http://dx.doi.org/10.1007/s00248-006-9016-1. Ignatavi Ignatavi cius, C., cius, G., 2005. Investigation of damage and microclimate
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deterioration caused by dampness in the Palace of signatories to the declaration of independence. Indoor Built Environ. 14, 89e95. Imhoff, J.F., 2006. The phototrophic betaproteobacteria. In: Dworkin, M., Falkow, S., Rosenberg, E., Schleifer, K.-H., Stackebrandt, E. (Eds.), The Prokaryotes. A Handbook on the Biology of Bacteria, , third ed.vol. 5. Springer Verlag, New York, pp. 593e601. Imhoff, J.F., 2014. Biology of Green Sulfur Bacteria. eLS. http://dx.doi.org/10.1002/ 9780470015902.a0000458.pub2. Karsten, U., Holzinger, A., 2012. Light, temperature and desiccation effects on photosynthetic activity and drought-induced ultrastructural changes in the green alga Klebsormidium dissectum(Streptophyta) from a high alpine soil crust. Microb. Ecol. 63, 51e63. http://dx.doi.org/10.1007/s00248-011-9924-6. Khaneja, R., PerezFons, L., Fakhry, S., Baccigalupi, L., Steiger, S., To, E., Sandmann, G., Dong, T.C., Ricca, E., et al., 2010. Carotenoids found in Bacillus. J. Appl. Microbiol. 108, 1889e1902. Klein, A.M., Bohannan, B.J.M., Jaffe, D.A., Levin, D.A., Green, J.L., 2016. Molecular evidence for metabolically active bacteria in the atmosphere. Front. Microbiol. 7, 772. http://dx.doi.org/10.3389/fmicb.2016.00772. s, F., Pangallo, D., Szemes, T., 2016. Krakov a, L., Soltys, K., Budis, J., Grivalský, T., Duri Investigation of bacterial and archaeal communities: novel protocols using modern sequencing by Illumina MiSeq and traditional DGGE-cloning. Extremophiles 20, 795e808. Li, Q., Zhang, B., He, Z., Yang, X., 2016. Distribution and diversity of bacteria and fungi colonization in stone monuments analyzed by High-Throughput Sequencing. PLoS One 11 (9), e0163287. http://dx.doi.org/10.1371/ journal.pone.0163287. Mehdipour-Moghaddam, M.J., Emtiazi, G., Bouzari, M., Salehi, Z., 2010. Novel phytase and cellulase activities in endophytic azospirilla. World Appl. Sci. J. 10, 1129e1135. Ogawa, A., Celikkol-Aydin, S., Gaylarde, C., Baptista-Neto, J.A., Beech, I., 2017. Microbiomes of biofilms on decorative siliceous stone: drawbacks and advantages of Next Generation Sequencing. Curr. Microbiol. http://dx.doi.org/10.1007/ s00284-017-1257-3. Onofri, S., Zucconi, L., Isola, D., Selbmann, L., 2014. Rock-inhabiting fungi and their role in deterioration of stone monuments in the Mediterranean area. Plant Biosyst. 148, 384e391. Oren, A., 2006. The genera rhodothermus, thermonema, hymenobacter and Salinibacter. In: Prokaryotes 7, pp. 712e738. http://dx.doi.org/10.1007/0-387-307478_29. Ortega-Morales, B.O., Gaylarde, C., Anaya-Hernandez, A., Chan-Bacab, M.J., De la Rosa-García, S.C., Arano-Recio, D., Montero, M.J., 2013. Orientation affects Trentepohlia-dominated biofilms on mayan monuments of the Rio Bec style. Intern. Biodet Biodeg 84, 351e356. Raymond, J., 2008. Coloring in the tree of life. Trends Microbiol 16, 41e43. http:// dx.doi.org/10.1016/j.tim.2007.11.003. Scheerer, S., Ortega-Morales, O., Gaylarde, C., 2009. Microbial deterioration of stone monuments e an updated overview. Adv. Appl. Microbiol. 66, 97e139. http:// dx.doi.org/10.1016/S0065-2164(08)00805-8. Souffreau, C., Vanormelingen, P., Verleyen, E., Sabbe, K., Vyverman, W., 2011. Tolerance of benthic diatoms from temperate aquatic and terrestrial habitats to experimental desiccation and temperature stress. Phycologia 49, 309e324. Sun, L., Toyonaga, M., Ohashi, A., Matsuura, N., Tourlousse, D.M., Meng, X.-Y., et al., 2016. Isolation and characterization of Flexilinea flocculi gen. nov., sp. nov., a filamentous anaerobic bacterium belonging to the class Anaerolineae in the phylum Chloroflexi. Int. J. Syst. Evol. Microbiol. 66, 988e996. http://dx.doi.org/ 10.1099/ijsem.0.000822. Trujillo, M.E., 2016. Actinobacteria. eLS, pp. 1e16. http://dx.doi.org/10.1002/ 9780470015902.a0020366.pub2. Viitanen, H., Vinha, J., Salminen, K., Ojanen, T., Peuhkuri, R., Paajanen, L., Lahdesesmaki, K., 2009. Moisture and bio-deterioration risk of building materials and structures. J. Build. Phys. 33, 201e224. Zhang, H., Sekiguchi, Y., Hanada, S., Hugenholtz, P., Kim, H., Kamagata, Y., Nakamura, K., 2003. Gemmatimonas aurantiaca gen. nov., sp nov., a Gramnegative, aerobic, polyphosphate-accumulating micro-organism, the first cultured representative of the new bacterial phylum Gemmatimonadetes phyl. nov. Int. J. Syst. Evol. Microbiol. 53, 1155e1163.
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Microbial communities on painted wet and dry external surfaces of a i, Brazil historic fortress in Nitero Akiko Ogawa a, 1, Sukriye Celikkol-Aydin a, Christine Gaylarde a, *, ^ nio Baptista-Neto b, Iwona Beech a Jose Anto a
University of Oklahoma, Department of Microbiology and Plant Biology, 770 Van Vleet Oval, Norman, OK 73019, USA Universidade Federal Fluminense, Departamento de Geologia e Geofísica, Av. General Milton Tavares de Souza, s/n, 4 Andar, Campus da Praia Vermelha, i, RJ, Brazil 24210-346, Nitero b
a r t i c l e i n f o
a b s t r a c t
Article history: Received 30 April 2017 Received in revised form 27 June 2017 Accepted 28 June 2017
Bacteria, algae and fungi colonising dry (F1) and wet (F2) white painted walls in the fortress of Santa Cruz i, Brazil, were detected using field emission-scanning electron microscopy (FE-SEM) and da Barra, Nitero next generation DNA sequencing (NGS) techniques. Major bacterial phyla Operational Taxonomic Units (OTUs) detected were Chloroflexi in the wet green biofilm F2 (38.85% compared with 7.56% in F1) and Proteobacteria in the dry grey biofilm F1 (57.17% compared with 28.69% in F2). Diatoms were detected at both sites by FE-SEM, but only at F1 by NGS. More algae and cyanobacteria were identified at F1, and this was the only biofilm containing Archaea, possibly related to the high level of salt efflorescences at this site. Although thinner, F1 biofilm showed considerably higher genus richness than the wet biofilm, F2. The thickness and appearance of the biofilms did not correlate with their genomic complexity. Ascomycetes of the Sordariomycetes were major fungi identified at both sites, Khuskia (3.33% OTUs) at F1 and Emericellopsis (7.99% OTUs) at F2, and few filamentous forms were seen by microscopy. However, many fungal OTUs could not be identified to phylum level. Potential bacterial and fungal paint deteriogens were detected at both sites. The results confirmed the importance of using a variety of techniques in the study of microbial communities. © 2017 Elsevier Ltd. All rights reserved.
Keywords: Biofilms Coatings Cultural property Metagenomics Moisture
1. Introduction i, Brazil, began conThe Fortress of Santa Cruz da Barra, Nitero struction in 1578, as the major defence for the entrance to Guanabara Bay in the city of Rio de Janeiro. The major stone used was the locally available augen gneiss. The fortress is still an important military base, but is open to the public and is the second most i. It is located at the most westerly point visited attraction in Nitero ~o de Açúcar of the Jurujuba peninsula, almost facing the Pa (Sugarloaf mountain) in Rio de Janeiro. Being military property, it is maintained in excellent condition, but is, nevertheless, subject to the adverse environmental conditions associated with the sub i has mean monthly air temtropical marine atmosphere. Nitero peratures varying from 20 C (July) to 27 C (February) and mean
* Corresponding author. E-mail address: [email protected] (C. Gaylarde). 1 Current address: Department of Chemistry and Biochemistry, National Institute of Technology, Suzuka College, Suzuka, Japan. http://dx.doi.org/10.1016/j.ibiod.2017.06.018 0964-8305/© 2017 Elsevier Ltd. All rights reserved.
annual rainfall of 1200 mm, ranging from 550 to 1900 mm. Grey, black, green, red and brown biofilms rapidly form on the white painted surfaces of the fort buildings, promoted by the high relative humidity, which is around 80% all year round. The potential problems associated with these biofilms include utilization of paint components by biofilm organisms that leads to degradation of the coating, production of microbial pigments causing discoloration of the paint film, and damage to the substratum by microorganisms, or microbial metabolites, penetrating the paint layer. The importance of microbial biofilms for the deterioration of stone surfaces was reviewed in 2009 (Scheerer et al., 2009) and of paint coatings in 2011 (Gaylarde et al., 2011). Overflows from drainage pipes on buildings lead to areas of permanent wetness, which are associated with thick biofilms (Crispim et al., 2004). There is considerable information about microbial growth on the external surfaces of historic and cultural buildings (Dakal and Cameotra, 2011; Scheerer et al., 2009, and references in both) and on the microorganisms growing on water damaged internal surfaces of buildings (Goll et al., 1952;
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Ignatavi cius and Ignatavi cius, 2005; Andersen et al., 2011). The phototrophic population prevalent on exterior areas of water overflow has been, to some extent, investigated by traditional culture and microscopy methods (Crispim et al., 2003; Gaylarde and Gaylarde, 2005). However, there is no published information on the difference between the constituents of the microbial biofilm on painted external surfaces of the same building in areas affected or not by constant wetness caused by overflow pipes, especially as identified by modern molecular analytical techniques. This article reports the use of Next Generation Sequencing (NGS), or metagenomic technology, together with traditional microscopy, to investigate these communities on the Fortress of Santa Cruz.
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2. Materials and methods 2.1. Sampling i, adhesive tape At the Fortress of Santa Cruz da Barra, Nitero and surface scraping samples were taken from growth on the painted entrance area of an external room, showing dry, mainly grey, biofilms and internal salt efflorescences, facing North-East (F1) and from a wet, heavily biofilmed overflow site (F2) on a painted external wall facing South (Fig. 1). Samples were taken as detailed in Gaylarde et al. (2017), with the additional use of sterile Eppendorf tubes for scraping samples from the solid
Fig. 1. The fortress of Santa Cruz, Niteroi, Brazil, showing sampling sites (red arrows); a) growth on overflow from drainage pipe (F2); b) entrance into open room on lower floor (F1); c) red/orange staining (arrow) caused by growth of the green alga Trentepohlia on stone wall of the fortress. Note grey lichen growth (white arrow) on surface of parapet in b). (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)
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Fig. 2. FE-SEM images of diatoms in the Santa Cruz fortress samples a) Diatoma in sample F1. Bar marker 10 mm; b) Fragilaria in sample F2 from overflow area. Groups of bacteria (mainly rod-shaped) are also seen (arrows). Bar marker 2 mm; c) Diatoms and bacterial agglomerates in sample F2. Bar marker 10 mm.
surfaces. A maximum depth of 3 mm was collected and separate layers were not maintained.
as: D ¼ s / √N
2.2. Sample analysis Samples were examined using the field emission scanning electron microscope, FE-SEM and by DNA analysis using Illumina Mi-Seq Next Generation Sequencing (NGS) with bacterial 519Fand 785R 16SrRNA gene primers and fungal ITS1F2 and ITS2 primers, all as described in Gaylarde et al. (2017). In all cases, at least two different samples (biological replicates) were analysed. 2.3. Data analysis The bacterial 16S rRNA gene libraries were pre-processed and analyzed using two pipelines that included either the Greengenes or the SILVA database, as described in Celikkol-Aydin et al. (2016). The fungal ITS gene libraries were treated using the UNITE database, as described in Gaylarde et al. (2017). Raw data files were deposited in the NCBI Sequence Read Archive (SRA) with accession number SRP076760. Menhinick's Index of genus richness at each site was calculated
Where s ¼ total number of different genera, and N ¼ total number of OTUs. The Jaccard Index of Similarity was calculated for both bacterial and fungal microbiomes, using the formula Sj ¼ j / (aþb-j) Where a ¼ number of OTU types at site 1 (dry), b ¼ number of OTU types at site 2 (wet) and j ¼ number of OTU types shared by both sites. Principal Components Analysis (PCA) was also used to compare the prokaryotic and the fungal populations at the two sites. PCA plots and loading plots were acquired from taxonomic abundances using the R environment (r-project.org).
3. Results and discussion Sampled biofilms were grey/light green in the case of F1, the dry
A. Ogawa et al. / International Biodeterioration & Biodegradation 123 (2017) 164e173 Table 1 Weight of samples and extracted DNA, together with total number of OTUs identified. Sample
Weight (g)
Collected DNA (ng)
No. of bacterial OTUs
No. of fungal OTUs
F1a F1b F2a F2b
0.05 <0.01 0.02 0.07
1430 1040 662 626
15726 9287 19611 9395
19635 8601 21680 18056
Duplicate biological samples from F1 (entrance) and F2 (wet wall).
site, and brown/dark green in the case of the wet biofilm, F2 (Fig. 1). In addition, red/orange biofilms of the green alga Trentepohlia were seen on south-west facing stone surfaces and the grey lichen Parmelia saxatilis (whose photobiont comprises species of the coccoid alga Trebouxia) was present on upper surfaces of the unpainted stone walls (Fig. 1). The orientation pattern of Trentepohlia growth on surfaces receiving lower levels of solar irradiation conforms to that reported at the Rio Bec style Mayan buildings in the Mexican State of Campeche (Ortega-Morales et al., 2013), facing in the opposing direction in this southern hemisphere site. The presence of the lichen indicates the low air pollution around the fortress, which is situated far from major roads and surrounded on three sides by the Atlantic Ocean. Quantities of DNA extracted from the samples are shown in Table 1, together with the total number of Operational Taxonomic Units (OTUs) identified. Although only low levels of DNA were extracted from some samples, amplification and sequencing analysis were achieved.
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3.1. Bacteria and phototrophs The results of the bacterial DNA analyses are shown in Figs. 3 and 4. The major phyla OTUs detected were of Chloroflexi in the wet biofilm F2 (38.85% compared with 7.56% in F1) and Proteobacteria in the dry biofilm F1 (57.17% compared with 28.69% in F2). This may be correlated with the surface discoloration produced by the biofilms, bright green in the case of F2 and mainly grey in F1. There were some differences between taxa detected by the two different pipelines, a fact that has also been pointed out for stone church façades in Rio de Janeiro (Ogawa et al., 2017) and for hot et al., 2016), and which may, spring bacterial NGS analyses (Krakova in large part, be due to the database used. The Greengenes database-containing pipeline was better able to identify phototrophs and Clostridiales than that containing the SILVA database. A lower proportion of alphaproteobacteria was detected overall with the former pipeline. Neverthess, alphaproteobacteria was still identified as the major class in the dry biofilm, F1. The Rhodospirillales order was the major component, with 13.64% OTUs (2.87% in F2), and within that order an unidentified Acetobacteriaceae was the main genus (6.6% genus OTUs). Within the lower abundance of alphaproteobacteria in the wet biofilm, the Rhodospirillales family Caulobacteriaceae was the main component at 4.13% family OTUs, the principal genus being Brevundimonas (3.22% genus OTUs). Figures given are from the Greengenes database analysis. Rhodospirillales have been found to be particularly abundant in the marine atmosphere (Klein et al., 2016). They may produce acids during their metabolism, which would cause paint film damage, and some members possess cellulase activity (Mehdipour-Moghaddam et al., 2010), which could also lead to paint degradation. Hence these
Fig. 3. Bacterial phylum OTUs (%) identified using the Greengenes database in duplicate (biological) samples from the Fortress of Santa Cruz, Niteroi. F1 e dried entrance biofilm; F2 e wet external biofilm. OTU abundances <0.06% not included. Key colours begin at 12 o'clock with Unidentified and continue in a clockwise manner from left to right and top to bottom rows, finishing just before 12 o'clock with Thermi. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)
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Fig. 4. Bacterial class OTUs identified at the two sites on the fortress of Santa Cruz. F1 ¼ dry site, F2 ¼ wet site; a) and b) are duplicate (biological) samples. Analysis was carried out using the SILVA database and OTUs below 0.06% are not included. Key colours begin at 12 o'clock with Acidobacteria and continue in a clockwise manner and from left to right and top to bottom rows, finishing just before 12 o'clock with Gammaproteobacteria. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)
could be important community members for coatings biodegradation. Of particular microbiological interest is the presence of low levels of Archaea in the dry biofilm; Halobacteria was present at an average of 0.2% OTUs, Thaumarchaeota; Marine Group I at 0.02% and Thaumarchaeota; Soil Crenarchaeotic Group at 0.03% OTUs. Archaea were absent from F2. The difference may be related with the salt deposits observed at F1; archaeal groups detected were mainly halophilic. No Archaea were detected by NGS on the painted surface of a 19th century house in Lodz, Poland, using either archaea-specific or bacteria-specific primers, although they were present on the brick (Adamiak et al., 2017). On the Santa Cruz fortress, there was also an interesting higher abundance of anaerobes, in the form of the order Clostridiales, at site F2 (0.56% compared to 0.04% at F1, and 0.70% compared to 0.085% at F1, for Greengenes and SILVA analyses, respectively). This may be explained by the greater thickness of the wet biofilm, allowing the production of anaerobic conditions at its base. However, there was no significant difference between the abundances of facultative and microaerophilic groups at the sites. It was anticipated that algae would be present at higher levels in the wet green biofilm, F2. It has long been known that high water activity promotes the growth of algae, which are more prevalent in
wet sites than in drier areas (Gillatt and Tracey, 1987; Crispim et al., 2003; Li et al., 2016). These studies, which show more algae in wetter locations, were non-molecular, and one of the present authors has found similar results in widely differing locations. For example, in a thick green biofilm in the water run-off from the capital of a pillar in the Echevery Palace, Bogota, Colombia, principal microorganisms detected were the algae Klebsormidium and Stichococcus, together with actinomycetes and rotifers, while the humid base of a stature in Queen's Square, London, UK, was colonised mainly by the algae Hormidium, Chlorosarcina and diatoms, along with Chloroflexi, protozoa and a Geodermatophiluslike Actinobacteria (CG, unpublished observations). However, in the current (molecular) investigation an average of 1.22% chloroplast OTUs (representing algae) were detected in F1 compared with only 0.12% at the wet site, F2, and FE-SEM did not indicate the presence of higher numbers of algae in the wet biofilm. Liquid water or 100% air humidity are said to be necessary for optimum photosynthesis €ubner et al., 2006). and growth of aeroterrestrial microalgae (Ha These authors investigated the effect of changing water availability and air humidity on an aeroterrestrial green algal biofilm on a building surface over several months. The photosynthetic activity correlated with the presence of water condensing on the façade. As insolation increased during the day, the water evaporated and
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Fig. 5. Fungal Class OTUs (%) identified in duplicate (biological) samples from the Fortress of Santa Cruz, Niteroi. F1 ¼ dried entrance biofilm; F2 ¼ wet external biofilm. A very high percentage of OTUs could not be identified as any fungal class. Key colours begin at 12 o'clock with Botryosphaeriaceae and continue in a clockwise manner from left to right and top to bottom rows, finishing just before 12 o'clock with Zygomycota. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)
photosynthesis was inhibited, recovering within minutes after artificial moistening. Similar high tolerance to dehydration has been described for soil-crust green algae of the genus Klebsormidium (http://journal.frontiersin.org/article/10.3389/fpls.2013. 00327/full, Karsten and Holzinger, 2012). In the Santa Cruz biofilm samples, the Greengenes pipeline, but not that containing the SILVA database, allowed the detection of 2% unidentified Chlorococcales, 1.18% Streptophyta (which includes the genus Klebsormidium) and 0.19% Stramenopiles (diatoms) in F1. All these OTU groups were absent from the F2 analyses, but diatoms were detected in both F1 and F2 by FE-SEM (Fig. 2). Cave biofilms have been found to be dominated by diatoms, if they are wet and
exposed to light (Falasco et al., 2014), but it is normally assumed that diatoms do not survive desiccation. The current results suggest that this is not true; high temperatures on the painted surfaces during the day rapidly cause dehydration of biofilms in this subtropical location and yet diatoms were common in dry biofilm F1. Souffreau et al. (2011) showed that although desiccation effectively kills most diatoms, terrestrial isolates of diatom species normally found in aquatic locations survived drying at þ40 C. Diatoms were not seen in the Santa Cruz biofilms using light microscopy, but were visualised by FE-SEM. These results confirm the importance of using a variety of techniques in the study of microbial communities. Using the Greengenes pipeline, 0.12% chlorophyta were detected
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in F2, as compared with 0% in F1. This could explain the dark green colour of the former, wet biofilm, in conjunction with the presence within it of 38.85% Chloroflexi OTUs (compared with only 7.56% in F1) and 0.22% OTUs of the anaerobic green sulfur bacteria, Chlorobi, which were absent from F1. Indeed, Chloroflexi was the major bacterial phylum detected in biofilm F2. However, there may be no direct relationship between moisture levels and formation of green biofilms (Cutler et al., 2013). Phototrophs are not considered to be physically damaging to painted surfaces, apart from their waterholding capacity, but many are pigmented, leading to aesthetic deterioration, and, of course, they can provide nutrients for other, deteriogenic, organisms. Previous work in the sub-tropics (Gaylarde and Gaylarde, 2005) has shown that cyanobacteria are the major phototrophs on dry building surfaces and may form biofilms of various colours, though rarely bright green. Desiccation tolerance is well documented for cyanobacteria and lichens (Holzinger and Karsten, 2013, and references therein). In the case of Santa Cruz fortress, over 7% of phylum OTUs at both sites belonged to these organisms, similar to the proportion of Chloroflexi detected in F1. Of these Cyanobacteria, class OTU abundances of 3.19% Nostocophycideae in F2, and 4.95% Oscillatoriophycideae and 2.34% Synechococcophycideae in F1 were identified by the Greengenes database, which continues to use the botanical nomenclature system for these prokaryotes.
because temperatures in the latter regions tend to be higher, reducing the time for which liquid water is present on building surfaces (“time of wetness”). On stone, algae formed the major biomass on most European monuments, while cyanobacteria, more resistant to adverse conditions, were the principal colonisers in Latin America. 3.3. Comparison of microbial communities As indicated above, there was considerable dissimilarity between the wet and the dry biofilms. The Jaccard Indices of Similarity between the two sites for bacterial and fungal communities
3.2. Fungi Fungi have been considered the major deteriogenic organisms of wet surfaces in building interiors (Goll et al., 1952; Ignatavi cius and Ignatavi cius, 2005; Andersen et al., 2011), although they may be superseded on external walls by phototrophic microorganisms. Fungi have been found, by traditional culture and microscopy techniques, to form the major biomass on external painted surfaces in Latin America (Gaylarde and Gaylarde, 2005), but few filamentous fungi were seen in the Santa Cruz samples by microscopy. Fungal classes identified at the two sites by the sequencing analysis are presented in Fig. 5. Since few filamentous fungi were seen by FE-SEM, it is not surprising that the majority of OTUs detected belonged to the ascomycetes, dimorphic fungi that can occur in yeast-like forms. Other genera identified by the NGS technology were probably present on the surfaces as spores. The major fungi identified at the wet site, F2, were ascomycetes of the genus Emericellopsis (7.99% OTUs), whilst F1 contained a more mixed group of Sordariomycete families as the main colonisers, with 2 genera predominating, Khuskia (3.33% OTUs) and Haematonectria (2.76% OTUs). These are all common soil fungi. Overall, 6.99% class OTUs in F1 and 8.12% in F2 represented Sordariomycetes, one of the largest classes in the ascomycetes. Figures are low because of the high proportion of fungal sequences that could not be identified (86.5%). Another class of ascomycetes, the Dothideomycetes, the black rock-inhabiting fungi, were present at 1.53% OTUs in the dry biofilm, F1, but only 0.04% in F2. This could be related to the water content of the biofilms; Dothideomycetes are found in nature under very hostile conditions, including extreme fluctuations of moisture and temperature (Onofri et al., 2014; De Leo and Urzì, 2015). They are slow-growing and would be overrun by more rapidly growing species under wet conditions. Fungal activity requires a minimum relative humidity of 80%e 95% depending on temperature, type and surface conditions of building materials (Viitanen et al., 2009). For decay development, the critical relative humidity is above 95%. Gaylarde and Gaylarde (2005), basing results on the analysis of 230 exterior painted surface samples by culture and microscope techniques, noted that major colonisers in Europe were algae, whilst in Latin America, fungi, folowed by phototrophs, were more prevalent, probably
Fig. 6. PCA plots of bacterial (a) and fungal (b) genomes identified in the Fortress of Santa Cruz, RJ, Brazil, based on the pipelines containing the SILVA and UNITE databases, respectively. F1 ¼ two replicate samples from room opening (dry biofilm), F2 ¼ 2 replicate samples from growth on overflow (wet biofilm).
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were 24.1% and 22.2%, respectively, indicating low similarity between the two at the genus level (identity is indicated by 100%). This was confirmed by the Principal Components Analysis (PCA) for both bacteria and fungi (Fig. 6). Of the bacterial community, 92% (87.7% in the Greengenes analysis) was represented by PC1. The distance between duplicates of F1 on the y (PC2) axis is not
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significant, since it corresponds to only 6% (6.4% in Greengenes) of the community. The duplicates are located on the same line on the PC1 axis, showing that they are practically identical. The bacterial loading plots (Fig. 7) clearly show the dissimilarity between the two sites. More points are seen on the plot calculated from the Greengenes-containing pipeline, since this was able to
Fig. 7. Loading plots of bacterial OTU abundances, based on the pipelines containing the SILVA (a) and Greengenes (b) databases. F1 is represented in red, mainly on the left-hand side and F2 in blue, on the right. The few purple dots seen on the right-hand side represent shared taxa. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)
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Table 2 Microbial groups (mainly phyla) detected in the wet (F2) and dry (F1) wall samples. In the case of NGS detection, only groups present at above 1% OTUs are shown. Principal organisms
Detection method
Present in Potential deteriogenic activity References F1
F2
Acidobacteria
NGS
þ
þ
Actinobacteria Bacteroidetes (e.g. Rhodothermi)
NGS NGS
þ
þ þ
Chloroflexi (e.g. Anaerolineae) Cyanobacteria: Synechococcophycideae Nostocophycideae Oscillatoriophycidiae Firmicutes (e.g. Bacilli) Gemmatimonadetes Planctomycetes Proteobacteria Alphaproteobacteria (e.g.,Rhodospirillales) Betaproteobacteria Gammaproteobacteria Algae: Diatoms Streptophyta Ascomycetes: Emericellopsis Khuskia Haematonectria Dothideomycetes
NGS NGS
þ þþ þþ þþ þ þþþ þþ þ þ þþ þ þ þþ þþ þþ þþ
þ þ þ þ þþ þþ
NGS NGS NGS NGS NGS NGS NGS NGS NGS&SEM NGS NGS
Chen et al., 2016, and refs therein; Raymond, 2008
þþ þ
Acid production, discolouration Degradation, discolouration Discolouration, acid production Discolouration, degradation Discolouration
þþ þ þ þ þþþ þþ
Discolouration Discolouration Unknown Acid production, discolouration
Khaneja et al., 2010 Zhang et al., 2003 Mehdipour-Moghaddam et al., 2010;Imhoff, 2006;Garrity, 2006
Discolouration
Gaylarde and Gaylarde, 2005, and refs therein
Acid production Physical penetration Discolouration
De Leo and Urzì, 2015
detect many more different taxa down to the genus level. It is more difficult to interpret the fungal PCAs in this way because of the high percentage of unidentified OTUs. Of those identified, 60.9% of the species were represented by PC1 and 24.7% by PC2. However, the PCA analysis does not show an identical distribution for duplicate samples. This difference might be due to the heterogeneity within each sample; it has previously been noted that fungi on buildings are more heterogeneously distributed than bacteria (Gaylarde et al., 2017). In addition, 72.39%e96.01% of the fungi in F1 and 86.02%e91.45% of those in F2 were assigned as unidentified in the UNITE database. The PCA and loading plots are thus not meaningful for this particular case. The bacterial genus richness, D, for each sample was 0.50 for F1 and 0.344 for F2. The equivalent values for fungal communities were 0.57 (F1) and 0.215 (F2). Unexpectedly, in view of the macroscopic appearance of the biofilms, the dry biofilm community, F1, was much richer than the wet. The thickness and appearance of the biofilms did not correlate with their genomic complexity. These results may be compared with those of Chase et al. (2016), who were unable to find meaningful correlations between levels of community richness, composition, or abundance of specific taxa of interest and equilibrium relative humidity of building surfaces inside offices in North America. A proportion of bacteria, and many fungal OTUs, could not be classified by the NGS technology (16.63% and 86.5%, respectively). This is not dissimilar to results of other molecular analyses of historic buildings. Li et al. (2016) found that 81.74% of bacteria and 64.89% of fungi on the stone surfaces of statues in the Hangzhou province of China were unclassifiable using High Throughput Sequencing with similar amplification and analysis systems to those employed in the current research. Similar high levels of unidentifiable fungal OTUs have been reported for unpainted stone churches in central Rio de Janeiro (Gaylarde et al., 2017). Primer or database inadequacy or failures in DNA extraction may explain
Chen et al., 2016, and refs therein, Trujillo, 2016 Oren, 2006 Imhoff, 2014; Sun et al., 2016 Gaylarde and Gaylarde, 2005, and refs therein
these results in part, and these potential problems are discussed in relation to microbiomes of indoor environments in Adams et al. (2016), but it is obvious that there is considerable unexplained diversity in biofilms formed on external building surfaces. More investigations, using a variety of detection and identification techniques, together with activity measurements such as metabolomics, are essential before this knowledge can confidently be used in the targeted control of coatings biodeterioration. 4. Conclusions Next Generation Sequencing (NGS) techniques allowed a much more detailed analysis of the biofilms on painted wet and dry i, Brazil, than surfaces on the Fortress of Santa Cruz da Barra, Nitero more traditional methods, but these traditional methods were necessary for a more complete analysis. For example, FE-SEM allowed the detection of diatoms in the wet biofilm in addition to the dry one, in which diatom DNA was identified. The principal microbial groups, together with the methods whereby they were detected and their potential deteriogenic activities, are shown in Table 2. Major bacterial phyla Operational Taxonomic Units (OTUs) identified were Chloroflexi in the wet green biofilm and Proteobacteria in the dry grey biofilm. Of the latter, the principal group was the Rhodospiralles, known acid producers. More algae and cyanobacteria were found at the dry site, in spite of its lesser green colouration, and this was the only biofilm containing Archaea, probably related to the high level of salt efflorescences. Ascomycetes of the Sordariomycetes were major fungi identified at both sites, but many OTUs could not be assigned to any particular fungal class. A higher abundance of Dothideomycete OTUs was found in the dry than the wet biofilm, correlating with its darker appearance. Although thinner, the dry biofilm showed considerably higher genus richness than the wet biofilm. The targeted control of paint film biodeterioration requires biofilm analysis using both modern
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