» Articles » PMID: 23431390

Can Abundance of Protists Be Inferred from Sequence Data: a Case Study of Foraminifera

Overview
Journal PLoS One
Date 2013 Feb 23
PMID 23431390
Citations 44
Authors
Affiliations
Soon will be listed here.
Abstract

Protists are key players in microbial communities, yet our understanding of their role in ecosystem functioning is seriously impeded by difficulties in identification of protistan species and their quantification. Current microscopy-based methods used for determining the abundance of protists are tedious and often show a low taxonomic resolution. Recent development of next-generation sequencing technologies offered a very powerful tool for studying the richness of protistan communities. Still, the relationship between abundance of species and number of sequences remains subjected to various technical and biological biases. Here, we test the impact of some of these biological biases on sequence abundance of SSU rRNA gene in foraminifera. First, we quantified the rDNA copy number and rRNA expression level of three species of foraminifera by qPCR. Then, we prepared five mock communities with these species, two in equal proportions and three with one species ten times more abundant. The libraries of rDNA and cDNA of the mock communities were constructed, Sanger sequenced and the sequence abundance was calculated. The initial species proportions were compared to the raw sequence proportions as well as to the sequence abundance normalized by rDNA copy number and rRNA expression level per species. Our results showed that without normalization, all sequence data differed significantly from the initial proportions. After normalization, the congruence between the number of sequences and number of specimens was much better. We conclude that without normalization, species abundance determination based on sequence data was not possible because of the effect of biological biases. Nevertheless, by taking into account the variation of rDNA copy number and rRNA expression level we were able to infer species abundance, suggesting that our approach can be successful in controlled conditions.

Citing Articles

Endolithic Fungal Diversity in Antarctic Oligocene Rock Samples Explored Using DNA Metabarcoding.

Rabelo N, Goncalves V, Carvalho M, Scheffler S, Santiago G, Sucerquia P Biology (Basel). 2024; 13(6).

PMID: 38927294 PMC: 11200754. DOI: 10.3390/biology13060414.


Fungal diversity present in snow sampled in summer in the north-west Antarctic Peninsula and the South Shetland Islands, Maritime Antarctica, assessed using metabarcoding.

de Menezes G, Lopes F, Santos K, Silva M, Convey P, Camara P Extremophiles. 2024; 28(2):23.

PMID: 38575688 DOI: 10.1007/s00792-024-01338-2.


Benthic Heterotrophic Protist Communities of the Southern Baltic Analyzed with the Help of Curated Metabarcoding Studies.

Sachs M, Dunn M, Arndt H Biology (Basel). 2023; 12(7).

PMID: 37508439 PMC: 10376117. DOI: 10.3390/biology12071010.


Macroevolutionary patterns in intragenomic rDNA variability among planktonic foraminifera.

Greco M, Morard R, Darling K, Kucera M PeerJ. 2023; 11:e15255.

PMID: 37123000 PMC: 10143585. DOI: 10.7717/peerj.15255.


Soil Fungal Diversity and Ecology Assessed Using DNA Metabarcoding along a Deglaciated Chronosequence at Clearwater Mesa, James Ross Island, Antarctic Peninsula.

Goncalves V, Lirio J, Coria S, Lopes F, Convey P, Oliveira F Biology (Basel). 2023; 12(2).

PMID: 36829552 PMC: 9953209. DOI: 10.3390/biology12020275.


References
1.
Bartram A, Lynch M, Stearns J, Moreno-Hagelsieb G, Neufeld J . Generation of multimillion-sequence 16S rRNA gene libraries from complex microbial communities by assembling paired-end illumina reads. Appl Environ Microbiol. 2011; 77(11):3846-52. PMC: 3127616. DOI: 10.1128/AEM.02772-10. View

2.
Rodriguez-Martinez R, Labrenz M, Del Campo J, Forn I, Jurgens K, Massana R . Distribution of the uncultured protist MAST-4 in the Indian Ocean, Drake Passage and Mediterranean Sea assessed by real-time quantitative PCR. Environ Microbiol. 2009; 11(2):397-408. DOI: 10.1111/j.1462-2920.2008.01779.x. View

3.
Amend A, Seifert K, Bruns T . Quantifying microbial communities with 454 pyrosequencing: does read abundance count?. Mol Ecol. 2010; 19(24):5555-65. DOI: 10.1111/j.1365-294X.2010.04898.x. View

4.
Farrelly V, Rainey F, Stackebrandt E . Effect of genome size and rrn gene copy number on PCR amplification of 16S rRNA genes from a mixture of bacterial species. Appl Environ Microbiol. 1995; 61(7):2798-801. PMC: 167554. DOI: 10.1128/aem.61.7.2798-2801.1995. View

5.
Martin-Laurent F, Philippot L, Hallet S, Chaussod R, Germon J, Soulas G . DNA extraction from soils: old bias for new microbial diversity analysis methods. Appl Environ Microbiol. 2001; 67(5):2354-9. PMC: 92877. DOI: 10.1128/AEM.67.5.2354-2359.2001. View