Unveiling abundance-dependent metabolic phenotypes of microbial communities.

IMPORTANCE: In nature, organisms live in communities and not as isolated species, and their interactions provide a source of resilience to environmental disturbances. Despite their importance in ecology, human health, and industry, understanding how organisms interact in different environments remains an open question. In this work, we provide a novel approach that, only using genomic information, studies the metabolic phenotype exhibited by communities, where the exploration of suboptimal growth flux distributions and the composition of a community allows to unveil its capacity to respond to environmental changes, shedding light of the degrees of metabolic plasticity inherent to the community.

Integration of Biological Networks for Acidithiobacillus thiooxidans Describes a Modular Gene Regulatory Organization of Bioleaching Pathways.

Acidithiobacillus thiooxidans is one of the most studied biomining species, highlighting its ability to oxidize reduced inorganic sulfur compounds, coupled with its elevated capacity to live under an elevated concentration of heavy metals. In this work, using an in silico semi-automatic genome scale approach, two biological networks for A. thiooxidans Licanantay were generated: (i) An affinity transcriptional regulatory network composed of 42 regulatory family genes and 1,501 operons (57% genome coverage) linked through 2,646 putative DNA binding sites (arcs), (ii) A metabolic network reconstruction made of 523 genes and 1,203 reactions (22 pathways related to biomining processes). Through the identification of confident connections between both networks (V-shapes), it was possible to identify a sub-network of transcriptional factor (34 regulators) regulating genes (61 operons) encoding for proteins involved in biomining-related pathways. Network analysis suggested that transcriptional regulation of biomining genes is organized into different modules. The topological parameters showed a high hierarchical organization by levels inside this network (14 layers), highlighting transcription factors CysB, LysR, and IHF as complex modules with high degree and number of controlled pathways. In addition, it was possible to identify transcription factor modules named primary regulators (not controlled by other regulators in the sub-network). Inside this group, CysB was the main module involved in gene regulation of several bioleaching processes. In particular, metabolic processes related to energy metabolism (such as sulfur metabolism) showed a complex integrated regulation, where different primary regulators controlled several genes. In contrast, pathways involved in iron homeostasis and oxidative stress damage are mainly regulated by unique primary regulators, conferring Licanantay an efficient, and specific metal resistance response. This work shows new evidence in terms of transcriptional regulation at a systems level and broadens the study of bioleaching in A. thiooxidans species.

The genome sequence of the soft-rot fungus Penicillium purpurogenum reveals a high gene dosage for lignocellulolytic enzymes.

The high lignocellulolytic activity displayed by the soft-rot fungus Penicillium purpurogenum has made it a target for the study of novel lignocellulolytic enzymes. We have obtained a reference genome of 36.2 Mb of non-redundant sequence (11,057 protein-coding genes). The 49 largest scaffolds cover 90% of the assembly, and Core Eukaryotic Genes Mapping Approach (CEGMA) analysis reveals that our assembly captures almost all protein-coding genes. RNA-seq was performed and 93.1% of the reads aligned to the assembled genome. These data, plus the independent sequencing of a set of genes of lignocellulose-degrading enzymes, validate the quality of the genome sequence. P. purpurogenum shows a higher number of proteins with CAZy motifs, transcription factors and transporters as compared to other sequenced Penicillia. These results demonstrate the great potential for lignocellulolytic activity of this fungus and the possible use of its enzymes in related industrial applications.

Codon usage bias reveals genomic adaptations to environmental conditions in an acidophilic consortium.

The analysis of codon usage bias has been widely used to characterize different communities of microorganisms. In this context, the aim of this work was to study the codon usage bias in a natural consortium of five acidophilic bacteria used for biomining. The codon usage bias of the consortium was contrasted with genes from an alternative collection of acidophilic reference strains and metagenome samples. Results indicate that acidophilic bacteria preferentially have low codon usage bias, consistent with both their capacity to live in a wide range of habitats and their slow growth rate, a characteristic probably acquired independently from their phylogenetic relationships. In addition, the analysis showed significant differences in the unique sets of genes from the autotrophic species of the consortium in relation to other acidophilic organisms, principally in genes which code for proteins involved in metal and oxidative stress resistance. The lower values of codon usage bias obtained in this unique set of genes suggest higher transcriptional adaptation to living in extreme conditions, which was probably acquired as a measure for resisting the elevated metal conditions present in the mine.

Putative bacterial interactions from metagenomic knowledge with an integrative systems ecology approach.

Following the trend of studies that investigate microbial ecosystems using different metagenomic techniques, we propose a new integrative systems ecology approach that aims to decipher functional roles within a consortium through the integration of genomic and metabolic knowledge at genome scale. For the sake of application, using public genomes of five bacterial strains involved in copper bioleaching: Acidiphilium cryptum, Acidithiobacillus ferrooxidans, Acidithiobacillus thiooxidans, Leptospirillum ferriphilum, and Sulfobacillus thermosulfidooxidans, we first reconstructed a global metabolic network. Next, using a parsimony assumption, we deciphered sets of genes, called Sets from Genome Segments (SGS), that (1) are close on their respective genomes, (2) take an active part in metabolic pathways and (3) whose associated metabolic reactions are also closely connected within metabolic networks. Overall, this SGS paradigm depicts genomic functional units that emphasize respective roles of bacterial strains to catalyze metabolic pathways and environmental processes. Our analysis suggested that only few functional metabolic genes are horizontally transferred within the consortium and that no single bacterial strain can accomplish by itself the whole copper bioleaching. The use of SGS pinpoints a functional compartmentalization among the investigated species and exhibits putative bacterial interactions necessary for promoting these pathways.

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.

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.