Metabolomic and high-throughput sequencing analysis—modern approach for the assessment of biodeterioration of materials from historic buildings

Preservation of cultural heritage is of paramount importance worldwide. Microbial colonization of construction materials, such as wood, brick, mortar and stone in historic buildings can lead to severe deterioration. The aim of the present study was to give modern insight into the phylogenetic diversity and activated metabolic pathways of microbial communities colonized historic objects located in the former Auschwitz II-Birkenau concentration and extermination camp in Oświęcim, Poland. For this purpose we combined molecular, microscopic and chemical methods. Selected specimens were examined using Field Emission Scanning Electron Microscopy (FESEM), metabolomic analysis and high-throughput Illumina sequencing. FESEM imaging revealed the presence of complex microbial communities comprising diatoms, fungi and bacteria, mainly cyanobacteria and actinobacteria, on sample surfaces. Microbial diversity of brick specimens appeared higher than that of the wood and was dominated by algae and cyanobacteria, while wood was mainly colonized by fungi. DNA sequences documented the presence of 15 bacterial phyla representing 99 genera including Halomonas, Halorhodospira, Salinisphaera, Salinibacterium, Rubrobacter, Streptomyces, Arthrobacter and 9 fungal classes represented by 113 genera including Cladosporium, Acremonium, Alternaria, Engyodontium, Penicillium, Rhizopus and Aureobasidium. Most of the identified sequences were characteristic of organisms implicated in deterioration of wood and brick. Metabolomic data indicated the activation of numerous metabolic pathways, including those regulating the production of primary and secondary metabolites, for example, metabolites associated with the production of antibiotics, organic acids and deterioration of organic compounds. The study demonstrated that a combination of electron microscopy imaging with metabolomic and genomic techniques allows to link the phylogenetic information and metabolic profiles of microbial communities and to shed new light on biodeterioration processes

Similar Gene Estimates from Circular and Linear Standards in Quantitative PCR Analyses Using the Prokaryotic 16S rRNA Gene as a Model

Conceived and designed the experiments: ALO KED. Performed the experiments: ALO. Analyzed the data: ALO. Contributed reagents/materials/analysis tools: KED. Wrote the paper: ALO KED. Revised and approved final version of paper: ALO KED.Quantitative PCR (qPCR) is one of the most widely used tools for quantifying absolute numbers of microbial gene copies in test samples. A recent publication showed that circular plasmid DNA standards grossly overestimated numbers of a target gene by as much as 8-fold in a eukaryotic system using quantitative PCR (qPCR) analysis. Overestimation of microbial numbers is a serious concern in industrial settings where qPCR estimates form the basis for quality control or mitigation decisions. Unlike eukaryotes, bacteria and archaea most commonly have circular genomes and plasmids and therefore may not be subject to the same levels of overestimation. Therefore, the feasibility of using circular DNA plasmids as standards for 16S rRNA gene estimates was assayed using these two prokaryotic systems, with the practical advantage being rapid standard preparation for ongoing qPCR analyses. Full-length 16S rRNA gene sequences from Thermovirga lienii and Archaeoglobus fulgidus were cloned and used to generate standards for bacterial and archaeal qPCR reactions, respectively. Estimates of 16S rRNA gene copies were made based on circular and linearized DNA conformations using two genomes from each domain: Desulfovibrio vulgaris, Pseudomonas aeruginosa, Archaeoglobus fulgidus, and Methanocaldocococcus jannaschii. The ratio of estimated to predicted 16S rRNA gene copies ranged from 0.5 to 2.2-fold in bacterial systems and 0.5 to 1.0-fold in archaeal systems, demonstrating that circular plasmid standards did not lead to the gross over-estimates previously reported for eukaryotic systems.Yeshttp://www.plosone.org/static/editorial#pee

Performance of microbial standard DNA in qPCR reactions.

a<p>Linear regression between Ct (y-intercept) and log₁₀ starting copy number (x, i.e. slope).</p>b<p>Efficiency (%) calculated: E = (10^1/slope−1)×100.</p>c<p>Bacteria: <i>T. lienii.</i></p>d<p>Archaea: <i>A. fulgidus.</i></p

Estimated and expected 16S rRNA gene copies in microbial gDNA samples based on qPCR standard curves.

a<p>Ratio of estimated divided by predicted 16S copies averaged across the three dilutions.</p>b<p>Predicted copies calculated as described in <b>Methods</b>.</p

Standard setup and Ct range for qPCR reactions.

a<p>Ct value for the NTC (no template control).</p>b<p>Bacteria: <i>T. lienii.</i></p>c<p>Archaea: <i>A. fulgidus.</i></p

List of primers used to amplify the 16S rRNA gene.

<p>List of primers used to amplify the 16S rRNA gene.</p

Comparison of expected and estimated 16S rRNA gene copies in archaeal DNA samples.

<p>Expected archaeal 16S rRNA gene copies were calculated based on one and two 16S copies per genome for (<b>a</b>) <i>A. fulgidus</i> and (<b>b</b>) <i>M. jannaschii</i>, respectively. Black bars = predicted 16S copies. White bars = estimated 16S copies based on supercoiled plasmid standard. Grey bars = estimated 16S copies based on nicked circular plasmid standard. Black and white striped bars = estimated 16S copies based on linearized plasmid standard. Black and gray striped bars = estimated 16S copies based on amplicon standard. Data shown are representative of two experiments. Data are the average (n = 3) and error bars are ±1 standard deviation among replicates.</p

Preparation of 16S rRNA gene standards.

<p>Representative archaeal (<i>A. fulgidus</i>) and bacterial (<i>T. lienii</i>) (<b>a</b>) plasmids: Marker = 1 kb DNA ladder, S = freshly isolated supercoiled plasmid, L = linearized plasmid (<i>SpeI</i>-digested), and N = nicked circular plasmid (<i>Nb.BtsI</i>-digested) and (<b>b</b>) PCR amplicons: Marker = low range DNA ladder.</p

Molecular tools to track bacteria responsible for fuel deterioration and microbiologically influenced corrosion

<div><p>Investigating the susceptibility of various fuels to anaerobic biodegradation has become complicated with the recognition that the fuels themselves are not sterile. Bacterial DNA could be obtained when various fuels were filtered through a hydrophobic teflon (0.22 μm) membrane filter. Bacterial 16S rRNA genes from these preparations were PCR amplified, cloned, and the resulting libraries sequenced to identify the fuel-borne bacterial communities. The most common sequence, found in algal- and camelina-based biofuels as well as in ultra-low sulfur diesel (ULSD) and F76 diesel, was similar to that of a <i>Tumebacillus</i>. The next most common sequence was similar to <i>Methylobacterium</i> and was found in the biofuels and ULSD. Higher level phylogenetic groups included representatives of the Firmicutes (<i>Bacillus</i>, <i>Lactobacillus</i> and <i>Streptococcus</i>), several Actinobacteria, Deinococcus-Thermus, Chloroflexi, Cyanobacteria, Bacteroidetes, Alphaproteobacteria (<i>Methylobacterium</i> and Sphingomonadales), Betaproteobacteria (Oxalobacteraceae and Burkholderiales) and Deltaproteobacteria. All of the fuel-associated bacterial sequences, except those obtained from a few facultative microorganisms, were from aerobes and only remotely affiliated with sequences that resulted from anaerobic successional events evident when ULSD was incubated with a coastal seawater and sediment inoculum. Thus, both traditional and alternate fuel formulations harbor a characteristic microflora, but these microorganisms contributed little to the successional patterns that ultimately resulted in fuel decomposition, sulfide formation and metal biocorrosion. The findings illustrate the value of molecular approaches to track the fate of bacteria that might come in contact with fuels and potentially contribute to corrosion problems throughout the energy value chain.</p> </div