Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2019 May 7;9(1):7021.
doi: 10.1038/s41598-019-43489-9.

Streptophyta and Acetic Acid Bacteria Succession Promoted by Brass in Slow Sand Filter System Schmutzdeckes

Ma Carmen E Delgado-Gardea  1   2 , Patricia Tamez-Guerra  1 , Ricardo Gomez-Flores  1 , Mariela Garfio-Aguirre  1 , Beatriz A Rocha-Gutiérrez  2 , César I Romo-Sáenz  1 , Francisco Javier Zavala-Díaz de la Serna  2 , Gilberto Eroza-de la Vega  2 , Blanca Sánchez-Ramírez  2 , María Del Carmen González-Horta  2 , María Del Rocío Infante-Ramírez  3
Affiliations

Streptophyta and Acetic Acid Bacteria Succession Promoted by Brass in Slow Sand Filter System Schmutzdeckes

Ma Carmen E Delgado-Gardea et al. Sci Rep. .

Abstract

Macro- and microorganism activities are important for the effectiveness of the slow sand filtration (SSF), where native microorganisms remove contaminants mainly by substrate competition, predation, and antagonism. The aim of the present study was to evaluate the addition of the oligodynamic metals iron, copper, and brass, inserted separately into SSF to enhance pollutant removal in water samples. Four laboratory-scale SSFs were built and tested: control, iron, copper, and brass. Water analysis included physicochemical evaluation, total and fecal coliform quantification. An analysis on microbial communities in the SSFs schmutzdecke was achieved by using 16S rRNA amplification, the Illumina MiSeq platform, and the QIIME bioinformatics software. The results demonstrated that inorganic and organic contaminants such as coliforms were removed up to 90%. The addition of metals had no significant effect (p > 0.05) on the other parameters. The microbial community analysis demonstrated different compositions of the SSF with brass-influent, where the eukaryote Streptophyta was predominant (31.4%), followed by the acetic acid bacteria Gluconobacter (24.6%), and Acetobacteraceae (7.7%), these genera were absent in the other SSF treatments. In conclusion, the use of a SSF system can be a low cost alternative to reduce microbial contamination in water and thus reduce gastrointestinal diseases in rural areas.

PubMed Disclaimer

Conflict of interest statement

The authors declare no competing interests.

Figures

Figure 1
Figure 1
Most probable number (MPN) counts logarithm of (A) the total coliforms, where the blue line indicates the maximum limit according to the Mexican Standard procedures (NOM-127-SSA1-1994); (B) the fecal coliforms, where the red line indicates the maximum limit according to the Mexican Standard procedures (NOM-001-ECOL-1996). Results from the influent from SSF-1 (control); SSF-2 (iron); SSF-3 (copper); and SSF-4 (brass).
Figure 2
Figure 2
Dominant phyla in the tested slow sand filtration systems (SSFs). SSF-1 = control; SSF-2 = iron; SSF-3 = copper; SSF-4 = brass.
Figure 3
Figure 3
Dominant classes in the tested slow sand filtration systems (SSF). SSF-1 = control; SSF-2 = iron; SSF-3 = copper; SSF-4 = brass.
Figure 4
Figure 4
Dominant prokaryotic genera in the tested slow sand filtration systems (SSF). *Unknown genera. 1Streptophyta genera were recognized by the Illumina MiSeq platform and the QIIME bioinformatics program.
Figure 5
Figure 5
Dominant genera in the tested slow sand filtration systems (SSF). See Fig. 4 for detailed information. SSF-1 = control; SSF-2 = iron; SSF-3 = copper; SSF-4 = brass.
See this image and copyright information in PMC

References

    1. Souza-Freitas, B. L. & Sabogal-Paz, L. P. Pretreatment using Opuntia cochenillifera followed by household slow sand filters: technological alternatives for supplying isolated communities. Environ. technol., 1–30, 10.1080/09593330.2019.1582700 (2019). - PubMed
    1. Calvo LA, et al. Spatial and temporal analysis of the microbial community in slow sand filters used for treating horticultural irrigation water. Appl. Environ. Microbiol. 2003;69(4):2116–25. doi: 10.1128/AEM.69.4.2116. - DOI - PMC - PubMed
    1. Wotton RS. Water purification using sand. Hydrobiologia. 2002;469(1–3):193–201. doi: 10.1023/A:1015503005899. - DOI
    1. Pfannes Kristina R., Langenbach Kilian M. W., Pilloni Giovanni, Stührmann Torben, Euringer Kathrin, Lueders Tillmann, Neu Thomas R., Müller Jochen A., Kästner Matthias, Meckenstock Rainer U. Selective elimination of bacterial faecal indicators in the Schmutzdecke of slow sand filtration columns. Applied Microbiology and Biotechnology. 2015;99(23):10323–10332. doi: 10.1007/s00253-015-6882-9. - DOI - PubMed
    1. Haig SJ, Quince C, Davies RL, Dorea CC, Collins G. Replicating the microbial community and water quality performance of full-scale slow sand filters in laboratory-scale filters. Water Res. 2014;61:141–51. doi: 10.1016/j.watres.2014.05.008. - DOI - PubMed

Publication types