Redox traits characterize the organization of global microbial communities Salvador Ramírez-Flandesa,b,c,1, Bernardo Gonzálezd,e, and Osvaldo Ulloaa,b,1 aDepartamento de Oceanografía, Universidad de Concepción, 4070386 Concepción, Chile; bInstituto Milenio de Oceanografía, Universidad de Concepción, 4070386 Concepción, Chile; cPrograma de Doctorado en Ingeniería de Sistemas Complejos, Universidad Adolfo Ibáñez, 7941169 Santiago, Chile; dLaboratorio de Bioingeniería, Facultad de Ingeniería y Ciencias, Universidad Adolfo Ibáñez, 7941169 Santiago, Chile; and eCenter of Applied Ecology and Sustainability (CAPES), 8331150 Santiago, Chile Edited by Paul G. Falkowski, Rutgers, The State University of New Jersey, New Brunswick, NJ, and approved January 9, 2019 (received for review October 12, 2018) The structure of biological communities is conventionally de- and phages (7). Microbial ecologists have employed molecular scribed as profiles of taxonomic units, whose ecological functions taxonomic markers, primarily the small subunit ribosomal RNA are assumed to be known or, at least, predictable. In environmen- gene, to address the first and second problems, thereby operation- tal microbiology, however, the functions of a majority of micro- ally defining species and estimating their abundances and taxo- organisms are unknown and expected to be highly dynamic and nomic diversity (8). This taxonomic approach has been used to collectively redundant, obscuring the link between taxonomic explain and predict the microbial dynamics in diverse environments structure and ecosystem functioning. Although genetic trait- (9, 10). In such a context, the Earth Microbiome Project initiative based approaches at the community level might overcome this has recently reported microbial taxonomic diversity per biome on a problem, no obvious choice of gene categories can be identified as global scale with the use of standardized protocols to provide an appropriate descriptive units in a general ecological context. We organized and complete catalog of microbes (11). However, several used 247 microbial metagenomes from 18 biomes to determine studies have reported inconsistent taxonomical correlations under which set of genes better characterizes the differences among apparently similar ecological scenarios, finding better consistency biomes on the global scale. We show that profiles of oxidoreduc- only when using multiple protein-coding genes as traits and when tase genes support the highest biome differentiation compared the whole community is analyzed as the ecological unit (12–16). with profiles of other categories of enzymes, general protein-coding This has been performed in an attempt to address the third above- genes, transporter genes, and taxonomic gene markers. Based on oxidoreductases’ description of microbial communities, the role of mentioned problem. After all, it is the function, not the taxonomic energetics in differentiation and particular ecosystem function information, that has the actual ecological relevance (17). Un- of different biomes become readily apparent. We also show that fortunately, the selection of the ecologically relevant categories of taxonomic diversity is decoupled from functional diversity, e.g., protein-coding genes for use is not evident in the broad context of grasslands and rhizospheres were the most diverse biomes in oxi- planetary biomes (6, 18, 19). We analyzed 247 metagenomes from doreductases but not in taxonomy. Considering that microbes un- 18 biomes (Fig. 1) to tackle this issue and to determine under which derpin biogeochemical processes and nutrient recycling through specific nonexclusive set of genes the differences between biomes oxidoreductases, this functional diversity should be relevant for a are the highest. These gene sets included protein-coding genes with better understanding of the stability and conservation of biomes. associated orthology in the KEGG database (a typical approach in Consequently, this approach might help to quantify the impact of trait-based analyses), enzyme-coding genes, transporter-associated environmental stressors on microbial ecosystems in the context of the global-scale biome crisis that our planet currently faces. Significance microbial ecology | functional traits | oxidoreductases | biomes | Biological communities are conventionally described as assem- metagenomics blages of species, whose ecological roles are known or predict- able from their observable morphology. In microbial ecology, iological communities are conventionally described as as- such a taxonomic approach is hindered by limited capacity to Bsemblages of species whose ecological roles are known or discriminate among different microbes, which bear highly dy- predictable from their observable morphological characteristics. namic genomes and establish complex associations. Approaches In the early twentieth century, Lotka and Volterra pioneered the based on culture-independent functional genes profiling might development of theoretical ecology using species numbers as the overcome these problems, but a set of usable established genes master variable in differential equations that describe the inter- in a general situation is still lacking. We show that genes related actions and complexity of ecological systems (1). Since then, to reduction-oxidation (redox) processes separate microbial com- most theoretical ecologists have used species numbers as the munities into their corresponding biomes. This redox-based ecological unit for developing an extensive body of theory, which characterization is linked to the microbial energetics of eco- includes elaborate mathematical models to explain the dynamics systems and to most biogeochemical cycles and might be use- of populations and communities (1). In practice, this approach ful for assessing the impact of environmental degradation on requires the categorization of every observed individual into a the ecosystem services, underpinned by microorganisms. taxonomic unit —which is not a trivial task in some cases (2), and Author contributions: S.R.-F. designed research; S.R.-F. performed research; S.R.-F. ana- it is definitively a problem in microbial ecology (3–5). In the lyzed data; S.R.-F., B.G., and O.U. wrote the paper; and B.G. and O.U. supervised research. latter context, microbial ecologists face three main problems. The authors declare no conflict of interest. First, observable morphological attributes do not provide suffi- This article is a PNAS Direct Submission. cient discriminatory or functional characterization. Second, the This open access article is distributed under Creative Commons Attribution-NonCommercial- isolation of microbial species to assess their physiology and NoDerivatives License 4.0 (CC BY-NC-ND). ecological function is rarely possible, a phenomenon that is re- 1To whom correspondence may be addressed. Email: [email protected] or [email protected]. lated to the so-called Great Plate Count Anomaly (6). Third, This article contains supporting information online at www.pnas.org/lookup/suppl/doi:10. prokaryotic genomes are highly dynamic, mainly due to pervasive 1073/pnas.1817554116/-/DCSupplemental. horizontal gene transfers and the effect of mobile DNA elements Published online February 11, 2019. 3630–3635 | PNAS | February 26, 2019 | vol. 116 | no. 9 www.pnas.org/cgi/doi/10.1073/pnas.1817554116 Downloaded by guest on September 24, 2021 A hot spring forest soil animal associated mangrove solar saltern sediment lake marine photic zone subterraneum river hot desert hot spring Fig. 1. Biomes and categories of genes. (A) Sketch oxygen minimum polar desert grassland zone marine of the biomes from which metagenomes (as proxies subterraneum rhizosphere cold seep aphotic for microbial communities) were included in this zone hydrothermal paper. The animal-associated biome includes meta- vent genomes from terrestrial animals only. A complete benthic zone & list and origin of these metagenomes can be found in subsea floor the SI Appendix, Table S1.(B) Organized list of the B biomes illustrated in A. The number of metagenomes C per biome is shown in parentheses besides the biome name, which is displayed in the color code utilized in the rest of the figures. (C) Categories of gene profiles considered in the analyses. All protein orthologies refer to the protein orthologies present in the KEGG protein database. The fourth rank taxonomy typi- cally corresponds to a phylum in the prokaryotic taxonomy (see SI Appendix for details). genes, and taxonomic marker genes (Fig. 1). We found that the set of molecular processes through functional genes, it is natural to ask genes that were encoding enzymes better differentiated the bi- whether all of them have the same ecological relevance to dif- ECOLOGY omes than the other gene categories. In particular, the profiles ferentiate one biome from another (Fig. 1). Our results show of genes that were encoding oxidoreductases composed the set that redox functions supported the highest statistical differenti- with the highest cohesion and separation of biome groups, ation among biomes when taxonomic and functional sets of suggesting that they can better describe the association of the genes were compared (Table 1 and SI Appendix, Fig. S5 and microbial communities to their respective biomes. In addition, Table S2). The discriminatory power of oxidoreductase genes for we found no correspondence in biome maximum diversity between grouping biomes can be visualized in networks of correlations the functional and the taxonomic approaches.