Microbial Diversity and Activity of Biofilms from Geothermal Springs in Croatia

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Abstract

Hot spring biofilms are stable, highly complex microbial structures. They form at dynamic redox and light gradients and are composed of microorganisms adapted to the extreme temperatures and fluctuating geochemical conditions of geothermal environments. In Croatia, a large number of poorly investigated geothermal springs host biofilm communities. Here, we investigated the microbial community composition of biofilms collected over several seasons at 12 geothermal springs and wells. We found biofilm microbial communities to be temporally stable and highly dominated by Cyanobacteria in all but one high-temperature sampling site (Bizovac well). Of the physiochemical parameters recorded, temperature had the strongest influence on biofilm microbial community composition. Besides Cyanobacteria, the biofilms were mainly inhabited by Chloroflexota, Gammaproteobacteria, and Bacteroidota. In a series of incubations with Cyanobacteria-dominated biofilms from Tuhelj spring and Chloroflexota- and Pseudomonadota-dominated biofilms from Bizovac well, we stimulated either chemoorganotrophic or chemolithotrophic community members, to determine the fraction of microorganisms dependent on organic carbon (in situ predominantly produced via photosynthesis) versus energy derived from geochemical redox gradients (here simulated by addition of thiosulfate). We found surprisingly similar levels of activity in response to all substrates in these two distinct biofilm communities, and observed microbial community composition and hot spring geochemistry to be poor predictors of microbial activity in the study systems.

Supplementary Information

The online version contains supplementary material available at 10.1007/s00248-023-02239-1.

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Most cited references 115

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DADA2: High resolution sample inference from Illumina amplicon data

Benjamin J. Callahan, Paul McMurdie, Michael Rosen … (2016)

We present DADA2, a software package that models and corrects Illumina-sequenced amplicon errors. DADA2 infers sample sequences exactly, without coarse-graining into OTUs, and resolves differences of as little as one nucleotide. In several mock communities DADA2 identified more real variants and output fewer spurious sequences than other methods. We applied DADA2 to vaginal samples from a cohort of pregnant women, revealing a diversity of previously undetected Lactobacillus crispatus variants.

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phyloseq: An R Package for Reproducible Interactive Analysis and Graphics of Microbiome Census Data

Paul McMurdie, Susan Holmes (2013)

Background The analysis of microbial communities through DNA sequencing brings many challenges: the integration of different types of data with methods from ecology, genetics, phylogenetics, multivariate statistics, visualization and testing. With the increased breadth of experimental designs now being pursued, project-specific statistical analyses are often needed, and these analyses are often difficult (or impossible) for peer researchers to independently reproduce. The vast majority of the requisite tools for performing these analyses reproducibly are already implemented in R and its extensions (packages), but with limited support for high throughput microbiome census data. Results Here we describe a software project, phyloseq, dedicated to the object-oriented representation and analysis of microbiome census data in R. It supports importing data from a variety of common formats, as well as many analysis techniques. These include calibration, filtering, subsetting, agglomeration, multi-table comparisons, diversity analysis, parallelized Fast UniFrac, ordination methods, and production of publication-quality graphics; all in a manner that is easy to document, share, and modify. We show how to apply functions from other R packages to phyloseq-represented data, illustrating the availability of a large number of open source analysis techniques. We discuss the use of phyloseq with tools for reproducible research, a practice common in other fields but still rare in the analysis of highly parallel microbiome census data. We have made available all of the materials necessary to completely reproduce the analysis and figures included in this article, an example of best practices for reproducible research. Conclusions The phyloseq project for R is a new open-source software package, freely available on the web from both GitHub and Bioconductor.

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Every base matters: assessing small subunit rRNA primers for marine microbiomes with mock communities, time series and global field samples.

Alma Parada, David M Needham, Jed Fuhrman (2016)

Microbial community analysis via high-throughput sequencing of amplified 16S rRNA genes is an essential microbiology tool. We found the popular primer pair 515F (515F-C) and 806R greatly underestimated (e.g. SAR11) or overestimated (e.g. Gammaproteobacteria) common marine taxa. We evaluated marine samples and mock communities (containing 11 or 27 marine 16S clones), showing alternative primers 515F-Y (5'-GTGYCAGCMGCCGCGGTAA) and 926R (5'-CCGYCAATTYMTTTRAGTTT) yield more accurate estimates of mock community abundances, produce longer amplicons that can differentiate taxa unresolvable with 515F-C/806R, and amplify eukaryotic 18S rRNA. Mock communities amplified with 515F-Y/926R yielded closer observed community composition versus expected (r(2) = 0.95) compared with 515F-Y/806R (r(2) ∼ 0.5). Unexpectedly, biases with 515F-Y/806R against SAR11 in field samples (∼4-10-fold) were stronger than in mock communities (∼2-fold). Correcting a mismatch to Thaumarchaea in the 515F-C increased their apparent abundance in field samples, but not as much as using 926R rather than 806R. With plankton samples rich in eukaryotic DNA (> 1 μm size fraction), 18S sequences averaged ∼17% of all sequences. A single mismatch can strongly bias amplification, but even perfectly matched primers can exhibit preferential amplification. We show that beyond in silico predictions, testing with mock communities and field samples is important in primer selection.

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Author and article information

Contributors

Petra Pjevac:

ORCID: https://orcid.org/0000-0001-7344-302X

petra.pjevac@univie.ac.at

Journal

Journal ID (nlm-ta): Microb Ecol

Journal ID (iso-abbrev): Microb Ecol

Title: Microbial Ecology

Publisher: Springer US (New York )

ISSN (Print): 0095-3628

ISSN (Electronic): 1432-184X

Publication date (Electronic): 20 May 2023

Publication date PMC-release: 20 May 2023

Publication date (Print): 2023

Volume: 86

Issue: 4

Pages: 2305-2319

Affiliations

[1 ]Division of Materials Chemistry, Ruđer Bošković Institute, ( https://ror.org/02mw21745) Zagreb, Croatia

[2 ]Center of Excellence for Science and Technology-Integration of Mediterranean Region (STIM), Split, Croatia

[3 ]Croatian Geological Survey, ( https://ror.org/02hmaq742) Zagreb, Croatia

[4 ]Joint Microbiome Facility of the Medical University of Vienna and the University of Vienna, ( https://ror.org/03prydq77) Vienna, Austria

[5 ]Department of Laboratory Medicine, Medical University of Vienna, ( https://ror.org/05n3x4p02) Vienna, Austria

[6 ]Centre for Microbiology and Environmental Systems Science, Department of Microbiology and Ecosystem Science, University of Vienna, ( https://ror.org/03prydq77) Vienna, Austria

Author information

Petra Pjevac https://orcid.org/0000-0001-7344-302X

Article

Publisher ID: 2239

DOI: 10.1007/s00248-023-02239-1

PMC ID: 10640420

PubMed ID: 37209180

SO-VID: 551ce5be-f492-4619-8b74-4d3793cbff3f

License:

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

History

Date received : 3 March 2023

Date accepted : 7 May 2023

Funding

Funded by: University of Vienna

Open Access :

Open access funding provided by University of Vienna.

Custom metadata

ScienceOpen disciplines: Microbiology & Virology

Keywords: hot spring,biofilm,16s rrna gene amplicon analysis,boncat,card-fish

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ScienceOpen disciplines: Microbiology & Virology

Keywords: hot spring, biofilm, 16s rrna gene amplicon analysis, boncat, card-fish

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Microbial Diversity and Activity of Biofilms from Geothermal Springs in Croatia

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Bacterial vaginosis and biofilm

Most cited references 115

DADA2: High resolution sample inference from Illumina amplicon data

phyloseq: An R Package for Reproducible Interactive Analysis and Graphics of Microbiome Census Data

Every base matters: assessing small subunit rRNA primers for marine microbiomes with mock communities, time series and global field samples.

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