Sorting out the mix in microbial genomics

Microbiota and metabolite profiling reveal specific alterations in bacterial community structure and environment in the cystic fibrosis airway during exacerbation

Chronic polymicrobial infections of the lung are the foremost cause of morbidity and mortality in cystic fibrosis (CF) patients. The composition of the microbial flora of the airway alters considerably during infection, particularly during patient exacerbation. An understanding of which organisms are growing, their environment and their behaviour in the airway is of importance for designing antibiotic treatment regimes and for patient prognosis. To this end, we have analysed sputum samples taken from separate cohorts of CF and non-CF subjects for metabolites and in parallel, and we have examined both isolated DNA and RNA for the presence of 16S rRNA genes and transcripts by high-throughput sequencing of amplicon or cDNA libraries. This analysis revealed that although the population size of all dominant orders of bacteria as measured by DNA- and RNA- based methods are similar, greater discrepancies are seen with less prevalent organisms, some of which we associated with CF for the first time. Additionally, we identified a strong relationship between the abundance of specific anaerobes and fluctuations in several metabolites including lactate and putrescine during patient exacerbation. This study has hence identified organisms whose occurrence within the CF microbiome has been hitherto unreported and has revealed potential metabolic biomarkers for exacerbation.

Biochemical diversity of carboxyl esterases and lipases from Lake Arreo (Spain): a metagenomic approach

The esterases and lipases from the α/β hydrolase superfamily exhibit an enormous sequence diversity, fold plasticity, and activities. Here, we present the comprehensive sequence and biochemical analyses of seven distinct esterases and lipases from the metagenome of Lake Arreo, an evaporite karstic lake in Spain (42°46'N, 2°59'W; altitude, 655 m). Together with oligonucleotide usage patterns and BLASTP analysis, our study of esterases/lipases mined from Lake Arreo suggests that its sediment contains moderately halophilic and cold-adapted proteobacteria containing DNA fragments of distantly related plasmids or chromosomal genomic islands of plasmid and phage origins. This metagenome encodes esterases/lipases with broad substrate profiles (tested over a set of 101 structurally diverse esters) and habitat-specific characteristics, as they exhibit maximal activity at alkaline pH (8.0 to 8.5) and temperature of 16 to 40°C, and they are stimulated (1.5 to 2.2 times) by chloride ions (0.1 to 1.2 M), reflecting an adaptation to environmental conditions. Our work provides further insights into the potential significance of the Lake Arreo esterases/lipases for biotechnology processes (i.e., production of enantiomers and sugar esters), because these enzymes are salt tolerant and are active at low temperatures and against a broad range of substrates. As an example, the ability of a single protein to hydrolyze triacylglycerols, (non)halogenated alkyl and aryl esters, cinnamoyl and carbohydrate esters, lactones, and chiral epoxides to a similar extent was demonstrated.

Telling the whole story in a 10,000-genome world

BACKGROUND

Genome sequencing has revolutionized our view of the relationships among genomes, particularly in revealing the confounding effects of lateral genetic transfer (LGT). Phylogenomic techniques have been used to construct purported trees of microbial life. Although such trees are easily interpreted and allow the use of a subset of genomes as "proxies" for the full set, LGT and other phenomena impact the positioning of different groups in genome trees, confounding and potentially invalidating attempts to construct a phylogeny-based taxonomy of microorganisms. Network and graph approaches can reveal complex sets of relationships, but applying these techniques to large data sets is a significant challenge. Notwithstanding the question of what exactly it might represent, generating and interpreting a Tree or Network of All Genomes will only be feasible if current algorithms can be improved upon.

RESULTS

Complex relationships among even the most-similar genomes demonstrate that proxy-based approaches to simplifying large sets of genomes are not alone sufficient to solve the analysis problem. A phylogenomic analysis of 1173 sequenced bacterial and archaeal genomes generated phylogenetic trees for 159,905 distinct homologous gene sets. The relationships inferred from this set can be heavily dependent on the inclusion of other taxa: for example, phyla such as Spirochaetes, Proteobacteria and Firmicutes are recovered as cohesive groups or split depending on the presence of other specific lineages. Furthermore, named groups such as Acidithiobacillus, Coprothermobacter and Brachyspira show a multitude of affiliations that are more consistent with their ecology than with small subunit ribosomal DNA-based taxonomy. Network and graph representations can illustrate the multitude of conflicting affinities, but all methods impose constraints on the input data and create challenges of construction and interpretation.

CONCLUSIONS

These complex relationships highlight the need for an inclusive approach to genomic data, and current methods with minor alterations will likely scale to allow the analysis of data sets with 10,000 or more genomes. The main challenges lie in the visualization and interpretation of genomic relationships, and the redefinition of microbial taxonomy when subsets of genomic data are so evidently in conflict with one another, and with the "canonical" molecular taxonomy.

Interplay of heritage and habitat in the distribution of bacterial signal transduction systems

Comparative analysis of the complete genome sequences from a variety of poorly studied organisms aims at predicting ecological and behavioral properties of these organisms and helping in characterizing their habitats. This task requires finding appropriate descriptors that could be correlated with the core traits of each system and would allow meaningful comparisons. Using the relatively simple bacterial models, first attempts have been made to introduce suitable metrics to describe the complexity of organism's signaling machinery, which included introducing the "bacterial IQ" score. Here, we use an updated census of prokaryotic signal transduction systems to improve this parameter and evaluate its consistency within selected bacterial phyla. We also introduce a more elaborate descriptor, a set of profiles of relative abundance of members of each family of signal transduction proteins encoded in each genome. We show that these family profiles are well conserved within each genus and are often consistent within families of bacteria. Thus, they reflect evolutionary relationships between organisms as well as individual adaptations of each organism to its specific ecological niche.