A Metagenome-Based Investigation of Gene Relationships for Non-Substrate-Associated Microbial Phosphorus Cycling in the Water Column of Streams and Rivers
Phosphorus (P) is a nutrient of primary importance in all living systems, and it is especially important in streams and rivers which are sensitive to anthropogenic P inputs and eutrophication. Microbes are accepted as the primary mineralizers and solubilizers of P improving bioavailability for organisms at all trophic levels. Here, we use a genomics approach with metagenome sequencing of 24 temperate streams and rivers representing a total P (TP) gradient to identify relationships between functional genes, functional gene groupings, P, and organisms within the P biogeochemical cycle. Combining information from network analyses, functional groupings, and system P levels, we have constructed a System Relational Overview of Gene Groupings (SROGG) which is a cohesive system level representation of P cycle gene and nutrient relationships. Using SROGG analysis in concert with other statistical approaches, we found that the compositional makeup of P cycle genes is strongly correlated to environmental P whereas absolute abundance of P genes shows no significant correlation to environmental P. We also found orthophosphate (PO43−) to be the dominant factor correlating with system P cycle gene composition with little evidence of a strong organic phosphorous correlation present even in more oligotrophic streams.
KeywordsMetagenome Phosphorus Freshwater Microbial communities MiSeq Nutrient cycling
The authors thank Morgan Bettcher, Stephen Cook, Stephen Elser, Katherine Hooker, Lauren Housley, and Caleb Robbins for their help in collecting field samples. We also thank Owen Lind and J. Thad Scott for assistance with internal review. We acknowledge the research support by Baylor University Office of Research and Baylor University Center for Reservoir and Aquatic Systems Research (CRASR).
Compliance with Ethical Standards
Conflict of Interest
The authors declare that they have no conflict of interest.
- 8.Correll DL (1998) The role of phosphorus in the eutrophication of receiving waters: a review. J Environ Qual 27:261. https://doi.org/10.2134/jeq1998.00472425002700020004x CrossRefGoogle Scholar
- 15.Bennett EM, Carpenter SR, Caraco NF (2001) Human impact on erodable phosphorus and eutrophication: a global perspective increasing accumulation of phosphorus in soil threatens rivers, lakes, and coastal oceans with eutrophication. Bioscience 51:227–234. https://doi.org/10.1641/0006-3568(2001)051[0227:HIOEPA]2.0.CO;2Google Scholar
- 18.Gorniak A, Więcko A, Cudowski A (2013) Fungi biomass in lowland rivers of north-eastern Poland: effects of habitat conditions and nutrient concentrations. Pol J Ecol 61:749–758Google Scholar
- 25.Qi Y, Kobayashi Y, Hulett FM (1997) The pst operon of Bacillus subtilis has a phosphate-regulated promoter and is involved in phosphate transport but not in regulation of the pho regulon. J Bacteriol 179:2534–2539. https://doi.org/10.1128/jb.179.8.2534-2539.1997 CrossRefPubMedPubMedCentralGoogle Scholar
- 31.Saralov A, Mol’kov D, Bannikova O et al (2000) Intracellular accumulation of monomer precursors of polyphosphates and polyhydroxyalkanoates from Acinetobacter calcoaceticus and Escherichia coli. Mikrobiologiia 70:737–744Google Scholar
- 34.Green WR, Haggard BE (2001) Phosphorus and nitrogen concentrations and loads at Illinois River south of Siloam Springs, Arkansas, 1997-1999Google Scholar
- 41.APHA (1998) Standard methods for the examination of water and wastewater. Am Public Health Assoc APHA, Washington DCGoogle Scholar
- 42.R Core Team (2015) R: a language and environment for statistical computing. R Foundation for Statistical Computing, ViennaGoogle Scholar
- 44.Butts CT, Hunter D, Handcock M, et al. (2015) Network: classes for relational dataGoogle Scholar
- 45.Csardi G, Nepusz T (2006) The igraph software package for complex network research. Int J Complex Syst 1695:1–9Google Scholar
- 46.Oksanen J, Blanchet FG, Kindt R, et al (2016) Vegan: community ecology package. R package version 2.4–1Google Scholar
- 47.Nakazawa M (2017) fmsb: functions for medical statistics book with some demographic data. R package version 0.6.1. CRAN R-Proj Orgpackage FmsbGoogle Scholar
- 49.Wickham H (2006) ggplot: an implementation of the grammar of graphics. R Package Version 210Google Scholar
- 50.Wood S (2017) mgcv: Mixed GAM Computation Vehicle with GCV/AIC/REML Smoothness EstimationGoogle Scholar
- 52.Pérez GL, Torremorell A, Mugni H, Rodríguez P, Vera MS, Nascimento M, Allende L, Bustingorry J, Escaray R, Ferraro M, Izaguirre I, Pizarro H, Bonetto C, Morris DP, Zagarese H (2007) Effects of the herbicide roundup on freshwater microbial communities: a Mesocosm study. Ecol Appl 17:2310–2322. https://doi.org/10.1890/07-0499.1 CrossRefPubMedGoogle Scholar
- 54.Duggan A, Charnley G, Chen W, Chukwudebe A, Hawk R, Krieger RI, Ross J, Yarborough C (2003) Di-alkyl phosphate biomonitoring data: assessing cumulative exposure to organophosphate pesticides. Regul Toxicol Pharmacol 37:382–395. https://doi.org/10.1016/S0273-2300(03)00031-X CrossRefPubMedGoogle Scholar
- 57.Stapleton RD, Singh VP (2002) Biotransformations: bioremediation technology for health and environmental protection. Elsevier, AmsterdamGoogle Scholar