Ocean-wide comparisons of mesopelagic planktonic community structures.

For decades, marine plankton have been investigated for their capacity to modulate biogeochemical cycles and provide fishery resources. Between the sunlit (epipelagic) layer and the deep dark waters, lies a vast and heterogeneous part of the ocean: the mesopelagic zone. How plankton composition is shaped by environment has been well-explored in the epipelagic but much less in the mesopelagic ocean. Here, we conducted comparative analyses of trans-kingdom community assemblages thriving in the mesopelagic oxygen minimum zone (OMZ), mesopelagic oxic, and their epipelagic counterparts. We identified nine distinct types of intermediate water masses that correlate with variation in mesopelagic community composition. Furthermore, oxygen, NO3- and particle flux together appeared as the main drivers governing these communities. Novel taxonomic signatures emerged from OMZ while a global co-occurrence network analysis showed that about 70% of the abundance of mesopelagic plankton groups is organized into three community modules. One module gathers prokaryotes, pico-eukaryotes and Nucleo-Cytoplasmic Large DNA Viruses (NCLDV) from oxic regions, and the two other modules are enriched in OMZ prokaryotes and OMZ pico-eukaryotes, respectively. We hypothesize that OMZ conditions led to a diversification of ecological niches, and thus communities, due to selective pressure from limited resources. Our study further clarifies the interplay between environmental factors in the mesopelagic oxic and OMZ, and the compositional features of communities.

Contribution of genome-scale metabolic modelling to niche theory.

Standard niche modelling is based on probabilistic inference from organismal occurrence data but does not benefit yet from genome-scale descriptions of these organisms. This study overcomes this shortcoming by proposing a new conceptual niche that resumes the whole metabolic capabilities of an organism. The so-called metabolic niche resumes well-known traits such as nutrient needs and their dependencies for survival. Despite the computational challenge, its implementation allows the detection of traits and the formal comparison of niches of different organisms, emphasising that the presence-absence of functional genes is not enough to approximate the phenotype. Further statistical exploration of an organism's niche sheds light on genes essential for the metabolic niche and their role in understanding various biological experiments, such as transcriptomics, paving the way for incorporating better genome-scale description in ecological studies.

Environmental vulnerability of the global ocean epipelagic plankton community interactome.

Marine plankton form complex communities of interacting organisms at the base of the food web, which sustain oceanic biogeochemical cycles and help regulate climate. Although global surveys are starting to reveal ecological drivers underlying planktonic community structure and predicted climate change responses, it is unclear how community-scale species interactions will be affected by climate change. Here, we leveraged Tara Oceans sampling to infer a global ocean cross-domain plankton co-occurrence network-the community interactome-and used niche modeling to assess its vulnerabilities to environmental change. Globally, this revealed a plankton interactome self-organized latitudinally into marine biomes (Trades, Westerlies, Polar) and more connected poleward. Integrated niche modeling revealed biome-specific community interactome responses to environmental change and forecasted the most affected lineages for each community. These results provide baseline approaches to assess community structure and organismal interactions under climate scenarios while identifying plausible plankton bioindicators for ocean monitoring of climate change.

A multi-objective constraint-based approach for modeling genome-scale microbial ecosystems.

Interplay within microbial communities impacts ecosystems on several scales, and elucidation of the consequent effects is a difficult task in ecology. In particular, the integration of genome-scale data within quantitative models of microbial ecosystems remains elusive. This study advocates the use of constraint-based modeling to build predictive models from recent high-resolution -omics datasets. Following recent studies that have demonstrated the accuracy of constraint-based models (CBMs) for simulating single-strain metabolic networks, we sought to study microbial ecosystems as a combination of single-strain metabolic networks that exchange nutrients. This study presents two multi-objective extensions of CBMs for modeling communities: multi-objective flux balance analysis (MO-FBA) and multi-objective flux variability analysis (MO-FVA). Both methods were applied to a hot spring mat model ecosystem. As a result, multiple trade-offs between nutrients and growth rates, as well as thermodynamically favorable relative abundances at community level, were emphasized. We expect this approach to be used for integrating genomic information in microbial ecosystems. Following models will provide insights about behaviors (including diversity) that take place at the ecosystem scale.

The bioleaching potential of a bacterial consortium.

This work presents the molecular foundation of a consortium of five efficient bacteria strains isolated from copper mines currently used in state of the art industrial-scale biotechnology. The strains Acidithiobacillus thiooxidans Licanantay, Acidiphilium multivorum Yenapatur, Leptospirillum ferriphilum Pañiwe, Acidithiobacillus ferrooxidans Wenelen and Sulfobacillus thermosulfidooxidans Cutipay were selected for genome sequencing based on metal tolerance, oxidation activity and bioleaching of copper efficiency. An integrated model of metabolic pathways representing the bioleaching capability of this consortium was generated. Results revealed that greater efficiency in copper recovery may be explained by the higher functional potential of L. ferriphilum Pañiwe and At. thiooxidans Licanantay to oxidize iron and reduced inorganic sulfur compounds. The consortium had a greater capacity to resist copper, arsenic and chloride ion compared to previously described biomining strains. Specialization and particular components in these bacteria provided the consortium a greater ability to bioleach copper sulfide ores.

Global transcriptional responses of Acidithiobacillus ferrooxidans Wenelen under different sulfide minerals.

In order to provide new information about the adaptation of Acidithiobacillus ferrooxidans during the bioleaching process, the current analysis presents the first report of the global transcriptional response of the native copper mine strain Wenelen (DSM 16786) oxidized under different sulfide minerals. Microarrays were used to measure the response of At. ferrooxidans Wenelen to shifts from iron supplemented liquid cultures (reference state) to the addition of solid substrates enriched in pyrite or chalcopyrite. Genes encoding for energy metabolism showed a similar transcriptional profile for the two sulfide minerals. Interestingly, four operons related to sulfur metabolism were over-expressed during growth on a reduced sulfur source. Genes associated with metal tolerance (RND and ATPases type P) were up-regulated in the presence of pyrite or chalcopyrite. These results suggest that At. ferrooxidans Wenelen presents an efficient transcriptional system developed to respond to environmental conditions, namely the ability to withstand high copper concentrations.

A new genome of Acidithiobacillus thiooxidans provides insights into adaptation to a bioleaching environment.

Acidithiobacillus thiooxidans is a sulfur oxidizing acidophilic bacterium found in many sulfur-rich environments. It is particularly interesting due to its role in bioleaching of sulphide minerals. In this work, we report the genome sequence of At. thiooxidans Licanantay, the first strain from a copper mine to be sequenced and currently used in bioleaching industrial processes. Through comparative genomic analysis with two other At. thiooxidans non-metal mining strains (ATCC 19377 and A01) we determined that these strains share a large core genome of 2109 coding sequences and a high average nucleotide identity over 98%. Nevertheless, the presence of 841 strain-specific genes (absent in other At. thiooxidans strains) suggests a particular adaptation of Licanantay to its specific biomining environment. Among this group, we highlight genes encoding for proteins involved in heavy metal tolerance, mineral cell attachment and cysteine biosynthesis. Several of these genes were located near genetic motility genes (e.g. transposases and integrases) in genomic regions of over 10 kbp absent in the other strains, suggesting the presence of genomic islands in the Licanantay genome probably produced by horizontal gene transfer in mining environments.

Enterococcus faecalis reconfigures its transcriptional regulatory network activation at different copper levels.

A global transcriptional regulatory network was generated in the pathogenic bacterium Enterococcus faecalis in order to understand how this organism can activate and coordinate its expression at different copper concentrations. The topological evaluation of the network showed common patterns described in other organisms. Integrating microarray experiments allowed the identification of two sub-networks activated at low (0.05 mM CuSO4) and high (0.5 mM CuSO4) concentrations of copper. The analysis indicates the presence of specific functionally activated modules induced by copper levels, highlighting the regulons LysR and ArgR as global regulators and CopY, Fur and LexA as local regulators. Taking advantage of the fact that E. faecalis presented a homeostatic module, we produced an in vivo intervention by removing this system from the cell without affecting the connectivity of the global transcriptional network. This strategy led us to find that this bacterium can reconfigure its gene expression to maintain cellular homeostasis, activating new modules principally related to glucose metabolism and transcriptional processes. Finally, these results position E. faecalis as the most complete and controllable systemic model organism for copper homeostasis available to date.

Stoichiometric modeling of oxidation of reduced inorganic sulfur compounds (Riscs) in Acidithiobacillus thiooxidans.

The prokaryotic oxidation of reduced inorganic sulfur compounds (RISCs) is a topic of utmost importance from a biogeochemical and industrial perspective. Despite sulfur oxidizing bacterial activity is largely known, no quantitative approaches to biological RISCs oxidation have been made, gathering all the complex abiotic and enzymatic stoichiometry involved. Even though in the case of neutrophilic bacteria such as Paracoccus and Beggiatoa species the RISCs oxidation systems are well described, there is a lack of knowledge for acidophilic microorganisms. Here, we present the first experimentally validated stoichiometric model able to assess RISCs oxidation quantitatively in Acidithiobacillus thiooxidans (strain DSM 17318), the archetype of the sulfur oxidizing acidophilic chemolithoautotrophs. This model was built based on literature and genomic analysis, considering a widespread mix of formerly proposed RISCs oxidation models combined and evaluated experimentally. Thiosulfate partial oxidation by the Sox system (SoxABXYZ) was placed as central step of sulfur oxidation model, along with abiotic reactions. This model was coupled with a detailed stoichiometry of biomass production, providing accurate bacterial growth predictions. In silico deletion/inactivation highlights the role of sulfur dioxygenase as the main catalyzer and a moderate function of tetrathionate hydrolase in elemental sulfur catabolism, demonstrating that this model constitutes an advanced instrument for the optimization of At. thiooxidans biomass production with potential use in biohydrometallurgical and environmental applications.

Metabolomic study of Chilean biomining bacteria Acidithiobacillus ferrooxidans strain Wenelen and Acidithiobacillus thiooxidans strain Licanantay.

In this study, we present the first metabolic profiles for two bioleaching bacteria using capillary electrophoresis coupled with mass spectrometry. The bacteria, Acidithiobacillus ferrooxidans strain Wenelen (DSM 16786) and Acidithiobacillus thiooxidans strain Licanantay (DSM 17318), were sampled at different growth phases and on different substrates: the former was grown with iron and sulfur, and the latter with sulfur and chalcopyrite. Metabolic profiles were scored from planktonic and sessile states. Spermidine was detected in intra- and extracellular samples for both strains, suggesting it has an important role in biofilm formation in the presence of solid substrate. The canonical pathway for spermidine synthesis seems absent as its upstream precursor, putrescine, was not present in samples. Glutathione, a catalytic activator of elemental sulfur, was identified as one of the most abundant metabolites in the intracellular space in A. thiooxidans strain Licanantay, confirming its participation in the sulfur oxidation pathway. Amino acid profiles varied according to the growth conditions and bioleaching species. Glutamic and aspartic acid were highly abundant in intra- and extracellular extracts. Both are constituents of the extracellular matrix, and have a probable role in cell detoxification. This novel metabolomic information validates previous knowledge from in silico metabolic reconstructions based on genomic sequences, and reveals important biomining functions such as biofilm formation, energy management and stress responses. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s11306-012-0443-3) contains supplementary material, which is available to authorized users.