Open access
21 May 2020

16S rRNA Gene Diversity in the Salt Crust of Salar de Uyuni, Bolivia, the World’s Largest Salt Flat


Salar de Uyuni is a vast, high-altitude salt flat in Bolivia with extreme physico-geochemical properties approaching multiple limits of life. Evidence for diverse halophilic bacteria and archaea was found in its surface and near-surface salt crust using 16S amplicon analysis, providing a snapshot of prokaryotic life.


Salar de Uyuni is the world’s largest salt flat, located in the southwestern Altiplano of Bolivia at an altitude of approximately 3,650 m above sea level (1, 2). The geochemical composition of brines and salt crusts (high in lithium, boron, magnesium, potassium, sodium, and chloride) and other physical conditions (high daily temperature fluctuations, UV radiation, and albedo) create a polyextreme environment close to multiple limits of life (35). In addition to an understanding of extremophilic life on Earth, characterization of the microbial communities of Salar de Uyuni will contribute to determining the potential habitability of other planets, as well as new biotechnology applications (69). To date, however, few microbial genomic studies have been conducted (1013). This study provides an initial snapshot of microbial diversity in the crust.
Samples were collected in March 2015 from a remote site (20°33′28.58ʺS, 67°12′29.56ʺW) in Salar de Uyuni from the surface salt crust (SSC) (BOL4) and at a depth of 5 to 15 cm (near-surface salt crust [NSSC] [BOL3]). DNA was extracted with the PowerLyzer PowerSoil DNA extraction kit (MO BIO Laboratories, Inc., Carlsbad, CA). Library construction and 16S amplicon sequencing of the V3 to V4 region were performed on a MiSeq platform according to the manufacturer’s recommendations (Illumina, Inc., San Diego, CA) using the primers Bakt_341F and Bakt_805R (1416).
Raw reads were processed with mothur (v1.39.5), and sequence data were aggregated with R (v3.4.1) (1619) ( Paired-end sequencing generated 213,999 raw reads (median length, 459 bp [range, 35 to 600 bp]). Reads were assembled with a quality score threshold of 20. Sequences longer than 475 bp and those with ambiguities and homopolymers (>8 bp), as well as chimeras, were removed, and sequences were aligned against the SILVA small subunit (SSU) Ref NR 99 database (v132) (20). Based on analysis using mothur, sequences with at least 97% similarity were binned into operational taxonomic units and classified (using a pseudobootstrap value of 80) against the reference database trimmed to positions 201 to 1000 of the 16S sequence of Escherichia coli (GenBank accession number J01859.1). Singletons were removed and only prokaryotic sequences were retained, resulting in 21,636 (SSC) and 3,625 (NSSC) sequences with a median length of 457 bp (range, 419 to 466 bp).
Archaea constituted 13.47% of the SSC sequences and 11.50% of the NSSC sequences, and bacteria constituted 86.53% and 88.50%, respectively. For archaea, all sequences were classified at the phylum level and 96.57% (SSC) and 91.85% (NSSC) at the genus level; 98.73% (SSC) and 93.29% (NSSC) were Euryarchaeota, and 1.27% (SSC) and 6.24% (NSSC) were Nanoarchaeota. Hadesarchaeota were present only in NSSC (0.48%). The most prevalent genera were Halonotius in SSC (53.09%) and Halodesulfurarchaeum in NSSC (47.96%) (Table 1). For bacteria, 99.71% (SSC) and 93.95% (NSSC) of sequences were classified at the phylum level and 91.36% (SSC) and 73.72% (NSSC) at the genus level. Bacteroidetes (58.25% [SSC] and 11.69% [NSSC]) and Proteobacteria (40.63% [SSC] and 73.72% [NSSC]) were most prevalent at the phylum level, and Salinibacter in SSC (53.21%) and Halorhodospira in NSSC (30.17%) were most prevalent at the genus level (Table 1). These findings represent a snapshot of considerable prokaryotic diversity in the largest salt flat on Earth.
TABLE 1 Prevalence of archaeal and bacterial 16S amplicons at the phylum and genus levels in the SSC and NSSC of Salar de Uyuni
Sample and taxonomic categoryaTotal no. of sequencesAbundance (%)b
SSC (BOL 4)  
NSSC (BOL 3)  
            “Candidatus Haloredivivus”40.96
The 3 most prevalent phyla and 10 most prevalent genera for each sample are shown.
Abundance was calculated based on the total number of sequences in each domain.

Data availability.

The 16S rRNA gene amplicon data sets are available at NCBI under SRA accession numbers SRX7011107 (NSSC) and SRX7011108 (SSC).


The DasSarma laboratory was supported by NASA Exobiology grant 80NSSC19K0463, and F.L.M. was supported by the Fulbright Fellowship Program. D.G. thanks the Swedish International Development Cooperation Agency for supporting his work. The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.


Banks D, Markland H, Smith PV, Mendez C, Rodriguez J, Huerta A, Sæther OM. 2004. Distribution, salinity and pH dependence of elements in surface waters of the catchment areas of the Salars of Coipasa and Uyuni, Bolivian Altiplano. J Geochem Explor 84:141–166.
Risacher F, Fritz B. 2000. Bromine geochemistry of Salar de Uyuni and deeper salt crusts, central Altiplano, Bolivia. Chem Geol 167:373–392.
DasSarma S, DasSarma P. 2017. Halophiles. In eLS. John Wiley and Sons, Ltd., Chichester, United Kingdom.
Reuder J, Ghezzi F, Palenque E, Torrez R, Andrade M, Zaratti F. 2007. Investigations on the effect of high surface albedo on erythemally effective UV irradiance: results of a campaign at the Salar de Uyuni, Bolivia. J Photochem Photobiol B 87:1–8.
Risacher F, Fritz B. 1991. Quaternary geochemical evolution of the Salars of Uyuni and Coipasa, central Altiplano, Bolivia. Chem Geol 90:211–231.
DasSarma S, DasSarma P, Laye VJ, Schwieterman EW. 2020. Extremophilic models for astrobiology: haloarchaeal survival strategies and pigments for remote sensing. Extremophiles 24:31–41.
DasSarma S, DasSarma P. 2015. Halophiles and their enzymes: negativity put to good use. Curr Opin Microbiol 25:120–126.
Dumorné K, Córdova DC, Astorga-Eló M, Renganathan P. 2017. Extremozymes: a potential source for industrial applications. J Microbiol Biotechnol 27:649–659.
Merino N, Aronson HS, Bojanova DP, Feyhl-Buska J, Wong ML, Zhang S, Giovannelli D. 2019. Living at the extremes: extremophiles and the limits of life in a planetary context. Front Microbiol 10:780.
Haferburg G, Gröning JAD, Schmidt N, Kummer NA, Erquicia JC, Schlömann M. 2017. Microbial diversity of the hypersaline and lithium-rich Salar de Uyuni, Bolivia. Microbiol Res 199:19–28.
DasSarma P, Anton BP, DasSarma S, Laye VJ, Guzman D, Roberts RJ, DasSarma S. 2019. Genome sequence and methylation patterns of Halorubrum sp. strain BOL3-1, the first haloarchaeon isolated and cultured from Salar de Uyuni. Microbiol Resour Announc 8:e00386-19.
Ramos-Barbero MD, Martínez JM, Almansa C, Rodríguez N, Villamor J, Gomariz M, Escudero C, Rubin S, Antón J, Martínez‐García M, Amils R. 2019. Prokaryotic and viral community structure in the singular chaotropic salt lake Salar de Uyuni. Environ Microbiol 21:2029–2042.
Rubin SSC, Marín I, Gómez MJ, Morales EA, Zekker I, San Martín-Uriz P, Rodríguez N, Amils R. 2017. Prokaryotic diversity and community composition in the Salar de Uyuni, a large scale, chaotropic salt flat. Environ Microbiol 19:3745–3754.
Illumina. 2013. 16S Metagenomic sequencing library preparation preparing 16S ribosomal RNA gene amplicons for the Illumina MiSeq system. Illumina, San Diego, CA.
Herlemann DP, Labrenz M, Jürgens K, Bertilsson S, Waniek JJ, Andersson AF. 2011. Transitions in bacterial communities along the 2000 km salinity gradient of the Baltic Sea. ISME J 5:1571–1579.
Pecher WT, Al Madadha ME, DasSarma P, Ekulona F, Schott EJ, Crowe K, Stojkovic Gut B, DasSarma S. 2019. Effects of road salt on microbial communities: halophiles as biomarkers of road salt pollution. PLoS One 14:e0221355.
Schloss PD, Westcott SL, Ryabin T, Hall JR, Hartmann M, Hollister EB, Lesniewski RA, Oakley BB, Parks DH, Robinson CJ, Sahl JW, Stres B, Thallinger GG, Van Horn DJ, Weber CF. 2009. Introducing mothur: open-source, platform-independent, community-supported software for describing and comparing microbial communities. Appl Environ Microbiol 75:7537–7541.
Kozich JJ, Westcott SL, Baxter NT, Highlander SK, Schloss PD. 2013. Development of a dual-index sequencing strategy and curation pipeline for analyzing amplicon sequence data on the MiSeq Illumina sequencing platform. Appl Environ Microbiol 79:5112–5120.
R Core Team. 2017. R: a language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria.
SILVA Ribosomal RNA Database Project. 2017. Release information: SILVA 132.

Information & Contributors


Published In

cover image Microbiology Resource Announcements
Microbiology Resource Announcements
Volume 9Number 2121 May 2020
eLocator: 10.1128/mra.00374-20
Editor: Kenneth M. Stedman, Portland State University


Received: 9 April 2020
Accepted: 1 May 2020
Published online: 21 May 2020



Wolf T. Pecher
Institute of Marine and Environmental Technology, Department of Microbiology and Immunology, University of Maryland School of Medicine, Baltimore, Maryland, USA
Yale Gordon College of Arts and Sciences, University of Baltimore, Baltimore, Maryland, USA
Fabiana L. Martínez
Institute of Marine and Environmental Technology, Department of Microbiology and Immunology, University of Maryland School of Medicine, Baltimore, Maryland, USA
Instituto de Investigaciones para la Industria Química, Consejo Nacional de Investigaciones Científicas y Técnicas, Universidad Nacional de Salta, Salta, Argentina
Priya DasSarma
Institute of Marine and Environmental Technology, Department of Microbiology and Immunology, University of Maryland School of Medicine, Baltimore, Maryland, USA
Daniel Guzmán
Centro de Biotecnología, Faculty of Sciences and Technology, Universidad Mayor de San Simón, Cochabamba, Bolivia
Shiladitya DasSarma
Institute of Marine and Environmental Technology, Department of Microbiology and Immunology, University of Maryland School of Medicine, Baltimore, Maryland, USA


Kenneth M. Stedman
Portland State University


Address correspondence to Shiladitya DasSarma, [email protected].

Metrics & Citations


Note: There is a 3- to 4-day delay in article usage, so article usage will not appear immediately after publication.

Citation counts come from the Crossref Cited by service.


If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click Download.

View Options

Figures and Media






Share the article link

Share with email

Email a colleague

Share on social media

American Society for Microbiology ("ASM") is committed to maintaining your confidence and trust with respect to the information we collect from you on websites owned and operated by ASM ("ASM Web Sites") and other sources. This Privacy Policy sets forth the information we collect about you, how we use this information and the choices you have about how we use such information.
FIND OUT MORE about the privacy policy