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Microbial Ecology on Solar Panels in Berkeley, CA, United States

DOI:10.3389/fmicb.2018.03043 期刊:Frontiers in Microbiology 出版年份:2018 更新时间:2025-09-19 17:15:36
摘要: Solar panels can be found practically all over the world and represent a standard surface that can be colonized by microbial communities that are resistant to harsh environmental conditions, including high irradiation, temperature fluctuations and desiccation. These properties make them not only ideal sources of stress-resistant bacteria, but also standard devices to study the microbial communities and their colonization process from different areas of Earth. We report here a comprehensive description of the microbial communities associated with solar panels in Berkeley, CA, United States. Cultivable bacteria were isolated to characterize their adhesive capabilities, and UV- and desiccation-resistance properties. Furthermore, a parallel culture-independent metagenomic and metabolomic approach has allowed us to gain insight on the taxonomic and functional nature of these communities. Metagenomic analysis was performed using the Illumina HiSeq2500 sequencing platform, revealing that bacterial population of the Berkeley solar panels is composed mainly of Actinobacteria, Bacteroidetes and Proteobacteria, as well as lower amounts of Deinococcus-Thermus and Firmicutes. Furthermore, a clear predominance of Hymenobacter sp. was also observed. A functional analysis revealed that pathways involved in the persistence of microbes on solar panels (i.e., stress response, capsule development, and metabolite repair) and genes assigned to carotenoid biosynthesis were common to all metagenomes. On the other hand, genes involved in photosynthetic pathways and general autotrophic subsystems were rare, suggesting that these pathways are not critical for persistence on solar panels. Metabolomics was performed using a liquid chromatography tandem mass spectrometry (LC-MS/MS) approach. When comparing the metabolome of the solar panels from Berkeley and from Valencia (Spain), a very similar composition in polar metabolites could be observed, although some metabolites appeared to be differentially represented (for example, trigonelline, pantolactone and 5-valerolactone were more abundant in the samples from Valencia than in the ones from Berkeley). Furthermore, triglyceride metabolites were highly abundant in all the solar panel samples, and both locations displayed similar profiles. The comparison of the taxonomic profile of the Californian solar panels with those previously described in Spain revealed striking similarities, highlighting the central role of both selective pressures and the ubiquity of microbial populations in the colonization and establishment of microbial communities.
作者: Manuel Porcar,Katherine B. Louie,Suzanne M. Kosina,Marc W. Van Goethem,Benjamin P. Bowen,Kristie Tanner,Trent R. Northen
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To comprehensively characterize the microbial communities associated with solar panels in Berkeley, CA, United States, including their taxonomic and functional diversity, and compare them with those from Valencia, Spain, to understand the colonization and establishment processes under harsh environmental conditions.

The microbial communities on solar panels in Berkeley are dominated by stress-resistant bacteria such as Hymenobacter spp., with functional adaptations including stress response and carotenoid biosynthesis pathways. Similarities with Valencia panels suggest common selective pressures and microbial ubiquity. The panels serve as rich sources for biotechnologically interesting bacteria. Future studies should explore broader geographic ranges and mechanistic insights into stress resistance.

The study is limited to specific geographic locations (Berkeley and Valencia) and may not represent solar panels in other climates. The culture-dependent methods might not capture the entire microbial diversity. The metabolomics approach relies on detection limits and ionization efficiencies, and absolute quantification was not performed. The functional inferences are based on genomic predictions and require experimental validation.

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