| Literature DB >> 33303927 |
Dóra Anda1, Attila Szabó2, Petra Kovács-Bodor3, Judit Makk2, Tamás Felföldi2, Éva Ács4,5, Judit Mádl-Szőnyi3, Andrea K Borsodi6,7.
Abstract
Attachment of microorganisms to natural or artificial surfaces and the development of biofilms are complex processes which can be influenced by several factors. Nevertheless, our knowledge on biofilm formation in karstic environment is quite incomplete. The present study aimed to examine biofilm development for a year under controlled conditions in quasi-stagnant water of a hydrothermal spring cave located in the Buda Thermal Karst System (Hungary). Using a model system, we investigated how the structure of the biofilm is formed from the water and also how the growth rate of biofilm development takes place in this environment. Besides scanning electron microscopy, next-generation DNA sequencing was used to reveal the characteristic taxa and major shifts in the composition of the bacterial communities. Dynamic temporal changes were observed in the structure of bacterial communities. Bacterial richness and diversity increased during the biofilm formation, and 9-12 weeks were needed for the maturation. Increasing EPS production was also observed from the 9-12 weeks. The biofilm was different from the water that filled the cave pool, in terms of the taxonomic composition and metabolic potential of microorganisms. In these karstic environments, the formation of mature biofilm appears to take place relatively quickly, in a few months.Entities:
Mesh:
Year: 2020 PMID: 33303927 PMCID: PMC7729855 DOI: 10.1038/s41598-020-78759-4
Source DB: PubMed Journal: Sci Rep ISSN: 2045-2322 Impact factor: 4.379
Figure 1Geographic location of the sampling site (A). The arrangement of the in situ experimental model system in the RT spring cave (B,C).
Figure 2SEM micrographs of biofilm samples developing on the glass slides during a one year period (3 weeks (A,B), 9 weeks (C,D), 12 weeks (E), 21 weeks (F), 30 weeks (G), 1-year-old biofilm (H)) in the RT thermal spring. Scale bar (A,B,D,F) 2 µm, (C,E,G) 10 µm, (H) 20 µm.
Bacterial species richness (ACE and Chao1) and diversity indices (inverse Simpsons and Shannon–Wiener) calculated from NGS data.
| Sample ID | No. of sequencesa | Sobs | Chao1 | ACE | Shannon | Inverse Simpson |
|---|---|---|---|---|---|---|
| RTW | 2954 (6536) | 46 ± 2.5 | 59 ± 8.2 | 65 ± 10.7 | 0.4 ± 0.02 | 1.1 ± 0.01 |
| 3 weeks | 2954 (2954) | 143 | 162 | 173 | 3.5 | 17.1 |
| 6 weeks | 2954 (9010) | 176 ± 5.3 | 240 ± 21.8 | 266 ± 37.9 | 3.3 ± 0.03 | 10.5 ± 0.3 |
| 9 weeks | 2954 (5986) | 198 ± 4.9 | 260 ± 20.7 | 273 ± 27.9 | 3.8 ± 0.02 | 17.4 ± 0.5 |
| 12 weeks | 2954 (7291) | 172 ± 5.6 | 243 ± 24.4 | 265 ± 39.9 | 3.6 ± 0.02 | 17.4 ± 0.4 |
| 15 weeks | 2954 (13,152) | 190 ± 6.2 | 269 ± 24.9 | 287 ± 40.2 | 3.6 ± 0.03 | 14.1 ± 0.5 |
| 18 weeks | 2954 (8225) | 193 ± 5.7 | 273 ± 24.9 | 320 ± 49.7 | 3.7 ± 0.02 | 17.8 ± 0.5 |
| 21 weeks | 2954 (8555) | 199 ± 6.3 | 288 ± 28.4 | 360 ± 52.5 | 3.7 ± 0.03 | 14.6 ± 0.5 |
| 24 weeks | 2954 (5102) | 204 ± 4.6 | 263 ± 18.4 | 302 ± 37.8 | 3.8 ± 0.02 | 18.3 ± 0.5 |
| 27 weeks | 2954 (4800) | 202 ± 4.5 | 253 ± 15.7 | 266 ± 14.6 | 3.8 ± 0.02 | 18.9 ± 0.4 |
| 30 weeks | 2954 (8352) | 216 ± 6.5 | 311 ± 28.3 | 351 ± 51.2 | 4.0 ± 0.02 | 25.6 ± 0.7 |
| 1 year | 2954 (3431) | 187 ± 2.2 | 213 ± 6.9 | 222 ± 6.1 | 3.9 ± 0.01 | 23.7 ± 0.3 |
aNumbers in parentheses stand for the total number of sequences obtained with NGS; for calculating richness estimators and diversity indices, read numbers were subsampled to the read number of the sample having the lowest sequence count.
Figure 3Percentile distribution of amplicon sequences on genus level revealed from the RTW sample and changes in the bacterial composition of biofilm communities in the one year period based on the 16S rRNA gene amplicon sequence data. Genera having < 2% relative abundance are combined in the “Other” category.
Figure 4NMDS ordination based on Bray–Curtis distance of the bacterial OTUs from biofilm developed for years on the rock (RTB), glass slides (3–30 week and 1 year) and water samples (RTW) of the RT spring (stress: 0.03). Based on SIMPER analysis, OTUs responsible for 60% dissimilarity among samples are shown in gray. Figure is based on the combination the results of this study and Enyedi et al. (2019).