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Metabolic Diversity Among Main Microorganisms Inside an Arsenic-Rich Ecosystem Revealed by Meta- and Proteo-Genomics

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Metabolic Diversity Among Main Microorganisms Inside an Arsenic-Rich Ecosystem Revealed by Meta- and Proteo-Genomics The ISME Journal (2011) 5, 1735–1747 & 2011 International Society for Microbial Ecology All rights reserved 1751-7362/11 www.nature.com/ismej ORIGINAL ARTICLE Metabolic diversity among main microorganisms inside an arsenic-rich ecosystem revealed by meta- and proteo-genomics Philippe N Bertin1, Audrey Heinrich-Salmeron1, Eric Pelletier2,3,4, Florence Goulhen- Chollet1, Florence Arse`ne-Ploetze1,Se´bastien Gallien5,Be´atrice Lauga6, Corinne Casiot7, Alexandra Calteau3,4,8, David Vallenet3,4,8, Violaine Bonnefoy9, Odile Bruneel7,Be´atrice Chane-Woon-Ming3,4,8, Jessica Cleiss-Arnold1, Robert Duran6, Franc¸oise Elbaz-Poulichet7, Nuria Fonknechten2,3,4, Ludovic Giloteaux6, David Halter1, Sandrine Koechler1, Marie Marchal1, Damien Mornico3,4,8, Christine Schaeffer5, Adam Alexander Thil Smith3,4,8, Alain Van Dorsselaer5, Jean Weissenbach2,3,4, Claudine Me´digue3,4,8 and Denis Le Paslier2,3,4 1Ge´ne´tique Mole´culaire, Ge´nomique et Microbiologie, UMR7156 CNRS and UdS, Strasbourg, France; 2CEA, DSV, IG, Genoscope, Laboratoire de Me´tage´nomique des Procaryotes, France; 3CNRS, UMR8030, Evry, France; 4UEVE, Universite´ d0Evry, France; 5Laboratoire de Spectrome´trie de Masse Bio-Organique, Institut Pluridisciplinaire Hubert Curien, UMR7178 CNRS and UdS, Strasbourg, France; 6Equipe Environnement et Microbiologie, UMR5254 CNRS and UPPA, Institut Pluridisciplinaire de Recherche sur l0Environnement et les Mate´riaux, Pau, France; 7Laboratoire HydroSciences Montpellier, UMR 5569, Montpellier, France; 8CEA, DSV, IG, Genoscope, Laboratoire d’Analyses Bioinformatiques pour la Ge´nomique et le Me´tabolisme, France and 9Laboratoire de Chimie Bacte´rienne, UPR9043 CNRS et Universite´ de la Me´diterrane´e, Marseille, France By their metabolic activities, microorganisms have a crucial role in the biogeochemical cycles of elements. The complete understanding of these processes requires, however, the deciphering of both the structure and the function, including synecologic interactions, of microbial communities. Using a metagenomic approach, we demonstrated here that an acid mine drainage highly contaminated with arsenic is dominated by seven bacterial strains whose genomes were reconstructed. Five of them represent yet uncultivated bacteria and include two strains belonging to a novel bacterial phylum present in some similar ecosystems, and which was named ‘Candidatus Fodinabacter communificans.’ Metaproteomic data unravelled several microbial capabilities expressed in situ, such as iron, sulfur and arsenic oxidation that are key mechanisms in biomineralization, or organic nutrient, amino acid and vitamin metabolism involved in synthrophic associations. A statistical analysis of genomic and proteomic data and reverse transcriptase–PCR experiments allowed us to build an integrated model of the metabolic interactions that may be of prime importance in the natural attenuation of such anthropized ecosystems. The ISME Journal (2011) 5, 1735–1747; doi:10.1038/ismej.2011.51; published online 12 May 2011 Subject Category: integrated genomics and post-genomics approaches in microbial ecology Keywords: microbial genomics; extreme environment; uncultured microorganism; bacterial phylum; synecology; functional ecology Introduction microbial ecosystems constitute a major reservoir of our planet’s genetic biodiversity, it is generally Microorganisms are involved in biogeochemical recognized that most of the microorganisms present nutrient cycles and have, therefore, a crucial role in the environment are not accessible by the current in the biosphere (Haferburg and Kothe, 2007; culture-dependent techniques. The recent develop- Falkowski et al., 2008; Konopka, 2009). Although ments in genomics have given an unprecedented opportunity to gain insight into the structure and the functioning of microbial communities (Allen Correspondence: PN Bertin, Ge´ne´tique Mole´culaire, Ge´nomique and Banfield, 2005; Bertin et al., 2008; Wilmes et al., et Microbiologie, Institut de Botanique, Universite´ de Strasbourg, 2009). Indeed, environmental genomics has ex- 28 rue Goethe, Strasbourg 67000, France. E-mail: [email protected] tended their analysis far beyond the sole taxonomic Received 19 November 2010; revised 17 February 2011; accepted studies, allowing the characterization of the whole 29 March 2011; published online 12 May 2011 community gene pool and its expression. Such Genomic deciphering of an arsenic-rich ecosystem PN Bertin et al 1736 approaches give rise to an integrated picture of covering these sediments was collected in triplicate ecosystems and are, therefore, of great interest to and filtered (300 ml) through sterile 0.22 mm nucle- interpret the metabolisms present in ecological niches pore filters. These filters were transferred into a considered as extreme, including those impacted by collection tube, frozen in liquid nitrogen and stored human activities. Among the most toxic anthropo- at À80 1C until further analysis. The main physico- genic contaminants, arsenic is at the origin of serious chemical parameters (pH, T1, dissolved oxygen) forms of water pollution in industrial and post- were determined in the field and arsenic speciation, industrial areas all over the world. In particular, high Fe(II) and sulfate analyses were performed as arsenic contents are encountered in mine drainage previously described (Bruneel et al., 2008). waters, where the metalloid is usually associated with sulfur, iron and other metals (Vaughan, 2006). Few forms of life are known to thrive in these often acid DNA isolation and sequencing waters, as compared with neutral waters (Johnson and DNA was extracted from the cellular fraction either Hallberg,2003;Denefet al., 2010). In this respect, the directly using the UltraClean Soil DNA Isolation As(III) form (arsenite) can provide chemolithotrophic kit (MoBio Laboratories Inc., Carlsbad, CA, USA), or organisms with energy (Silver and Phung, 2005; Stolz after separation of microbial cells by Nycodenz et al., 2006). gradient, using the Wizard Genomic DNA Extraction The former mine of Carnoule`s, Gard (France) kit (Promega, Madison, WI, USA) and stored at provides an outstanding example of such an extreme À20 1C (Supplementary Information). Nebulized environment. The sulfurous wastes contain As-rich DNA fragments ranging from 3 to 5 kb were used to pyrite and the leached waters are the source of a construct a genomic library and DNA inserts were small stream called the Reigous that contains sequenced, as previously described (Muller et al., between 50 and 350 mg lÀ1 of soluble arsenic, mainly 2007), giving rise to 550 920 Sanger reads. In in the form of As(III) (Casiot et al., 2003; Egal et al., parallel, 281 758 DNA reads were obtained by GS- 2010). However, although the arsenic levels remain FLEX pyrosequencing using standard procedures. still high, this concentration decreases by 95% Both methods produced a total of 430.3 Mbp. between the source of the Reigous and its con- fluence with the river Amous, 1.5 km downstream. This natural process of attenuation seems to be Clone library and phylogenetic analyses mainly due to microbial metabolism, leading to the Bacterial diversity was analyzed by cloning and oxidation of iron and arsenic into Fe(III) and As(V), sequencing PCR-amplified 16S rRNA genes (Sup- and their co-precipitation with sulfur. In addition, plementary Information). Sequences were compared laboratory experiments suggest that bacteria belong- with the RDP database (http://rdp.cme.msu.edu) ing to Thiomonas or Acidithiobacillus genera are (Wang et al., 2007) and BLAST (Basic Local involved in this process in situ (Bruneel et al., 2003; Alignment Search Tool) online searches (Altschul Casiot et al., 2003; Duquesne et al., 2003; Morin et al., 1997). Phylogenies were constructed with the et al., 2003; Egal et al., 2009). However, 16S-based molecular evolutionary genetics analysis v4.0 pro- community analyses have revealed that other genera gram (Tamura et al., 2007) using maximum are present in this ecosystem (Duquesne et al., 2003, composite-likelihood model and neighbor-joining 2008; Bruneel et al., 2003, 2006, 2008, 2011). The algorithm. The sequences of clones CG determined biological activity of these uncultured bacteria may in this study were submitted to the EMBL database have a significant impact on the functioning of this and were given accession numbers FN391809 to ecosystem. In the present study, we used a multi- FN391849. disciplinary approach that took advantage of the ‘omics’ methods, to decipher the role of microorgan- isms, including uncultured bacteria, in the complex Bioinformatics, statistical analysis and phylogenomic metabolic processes at work in the Carnoule`s acid approach mine drainage (AMD), an arsenic-rich ecosystem. Two-third of the metagenomic sequences were successfully organized in seven bins (Supplemen- tary Information) and were then integrated into the Materials and methods MicroScope platform for the prediction of coding sequences, followed by automatic and expert anno- Sampling and chemical analysis tation (Vallenet et al., 2009). The mean polymor- Samples were collected in May 2007 at the station phism frequency in the population was assessed called COWG (Carnoule`s Oxydizing Wetland, G) using SNIPer (Ning et al., 2001). Molecular phylo- located 30 m downstream of the spring (Bruneel genies were inferred using 27 universal marker et al., 2003). In all, 5 cm deep white sediments were genes chosen from a reference gene set (Ciccarelli collected at the bottom of the creek using
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