Comparative study of multiple approaches for identifying cultivable microalgae population diversity from freshwater samples

Abstract

The vast diversity of microalgae imposes the challenge of identifying them through the most common and economical identification method, morphological identification, or through using the more recent molecular-level identification tools. Here we report an approach combining enrichment and metagenomic molecular techniques to enhance microalgae identification and identify microalgae diversity from environmental water samples. From this perspective, we aimed to identify the most suitable culturing media and molecular approach (using different primer sets and reference databases) for detecting microalgae diversity. Using this approach, we have analyzed three water samples collected from the River Nile on several enrichment media. A total of 37 microalgae were identified morphologically to the genus level. While sequencing the three-primer sets (16S rRNA V1-V3 and V4-V5 and 18S rRNA V4 region) and aligning them to three reference databases (GG, SILVA, and PR2), a total of 87 microalgae were identified to the genus level. The highest eukaryotic microalgae diversity was identified using the 18S rRNA V4 region and alignment to the SILVA database (43 genera). The two 16S rRNA regions sequenced added to the eukaryotic microalgae identification, 26 eukaryotic microalgae. Cyanobacteria were identified through the two sequenced 16S rRNA regions. Alignment to the SILVA database served to identify 14 cyanobacteria to the genera level, followed by Greengenes, 11 cyanobacteria genera. Our multiple-media, primer, and reference database approach revealed a high microalgae diversity that would have been overlooked if a single approach had been used over the other.

Fig 1. Freshwater microalgae taxa identified across different nutrient media.

Venn diagram illustrating the number of shared and unique freshwater microalgae taxa across different culture media. The number of microalgae taxa identified on media BG-11, BBM, MM, and MS using two identification methods (A) Morphological identification, (B) Molecular-level identification using different DNA barcodes. (C) The total number of microalgae taxa commonly shared or uniquely identified using morphological and molecular identification methods. The genera identified are presented in S5 Table.

Fig 2. Venn diagrams illustrating the unique and shared microalgae identified through the different databases (SILVA, GG, and PR²) and the different DNA barcodes sequenced.

Cyanobacteria genera were identified through (A) 16S V1-V3 region and (B) 16S V4-V5 rRNA region. (C) Eukaryotic genera identified through 18S rRNA gene annotated using SILVA database and 16S rRNA gene annotated using PR² database.

Fig 3. Cyanobacteria identification.

Relative abundance of cyanobacteria identified through 16S rDNA V1-V3 (top-half) and 16S rDNA V4-V5 region (bottom-half) annotated through (A & D) SILVA, (B & C) GG and (C & F) PR² databases.

Fig 4. Eukaryotic microalgae identification.

Relative abundance of eukaryotic microalgae identified through the different databases (SILVA, GG, and PR²) and the different DNA barcodes sequenced. (A-D) are eukaryotic microalgae identified through 18S rRNA gene annotated using SILVA database. Relative abundance of eukaryotic microalgae genera identified using 16S V1-V3 through Greengenes and PR² (E & F), respectively, 16S V4-V5 rRNA gene (G & H) Greengenes and PR², respectively.

Fig 5. Alpha diversity indices of total microbial community based on OTUs.

The total calculated alpha diversity are as follows: Good’s Coverage; S_obs (total number of OTUs observed); Shannon; InvSimpson and Breger-Parker. The first half belonging to the V1-V3 region (A-C) and the second-half represents the V4-V5 region (D-F), and last plot belongs to 18S V4. (A, D) SILVA, (B, E) GG, and (C, F) PR² database. (G) Alpha diversity indices calculated through 18S rRNA gene and SILVA.

Fig 6. Non-metric multidimensional scaling analysis (nMDS) computed on Bray-Curtis similarity index obtained for microbial community-identified using SILVA 18S V4, water samples, and media as factors.