Hector Garcia Martin

Metagenomic and functional analysis of hindgut microbiota of a wood-feeding higher termite

From the standpoints of both basic research and biotechnology, there is considerable interest in reaching a clearer understanding of the diversity of biological mechanisms employed during lignocellulose degradation. Globally, termites are an extremely successful group of wood-degrading organisms and are therefore important both for their roles in carbon turnover in the environment and as potential sources of biochemical catalysts for efforts aimed at converting wood into biofuels. Only recently have data supported any direct role for the symbiotic bacteria in the gut of the termite in cellulose and xylan hydrolysis. Here we use a metagenomic analysis of the bacterial community resident in the hindgut paunch of a wood-feeding ‘higher’ Nasutitermes species (which do not contain cellulose-fermenting protozoa) to show the presence of a large, diverse set of bacterial genes for cellulose and xylan hydrolysis. Many of these genes were expressed in vivo or had cellulase activity in vitro, and further analyses implicate spirochete and fibrobacter species in gut lignocellulose degradation. New insights into other important symbiotic functions including H2 metabolism, CO2-reductive acetogenesis and N2 fixation are also provided by this first system-wide gene analysis of a microbial community specialized towards plant lignocellulose degradation. Our results underscore how complex even a 1-μl environment can be.

Metagenomic analysis of two enhanced biological phosphorus removal (EBPR) sludge communities

Enhanced biological phosphorus removal (EBPR) is one of the best-studied microbially mediated industrial processes because of its ecological and economic relevance. Despite this, it is not well understood at the metabolic level. Here we present a metagenomic analysis of two lab-scale EBPR sludges dominated by the uncultured bacterium, “Candidatus Accumulibacter phosphatis.” The analysis sheds light on several controversies in EBPR metabolic models and provides hypotheses explaining the dominance of A. phosphatis in this habitat, its lifestyle outside EBPR and probable cultivation requirements. Comparison of the same species from different EBPR sludges highlights recent evolutionary dynamics in the A. phosphatis genome that could be linked to mechanisms for environmental adaptation. In spite of an apparent lack of phylogenetic overlap in the flanking communities of the two sludges studied, common functional themes were found, at least one of them complementary to the inferred metabolism of the dominant organism. The present study provides a much needed blueprint for a systems-level understanding of EBPR and illustrates that metagenomics enables detailed, often novel, insights into even well-studied biological systems.

Dissecting biological "dark matter" with single-cell genetic analysis of rare and uncultivated TM7 microbes from the human mouth.

We have developed a microfluidic device that allows the isolation and genome amplification of individual microbial cells, thereby enabling organism-level genomic analysis of complex microbial ecosystems without the need for culture. This device was used to perform a directed survey of the human subgingival crevice and to isolate bacteria having rod-like morphology. Several isolated microbes had a 16S rRNA sequence that placed them in candidate phylum TM7, which has no cultivated or sequenced members. Genome amplification from individual TM7 cells allowed us to sequence and assemble >1,000 genes, providing insight into the physiology of members of this phylum. This approach enables single-cell genetic analysis of any uncultivated minority member of a microbial community.

Accurate phylogenetic classification of variable-length DNA fragments.

Metagenome studies have retrieved vast amounts of sequence data from a variety of environments leading to new discoveries and insights into the uncultured microbial world. Except for very simple communities, the encountered diversity has made fragment assembly and the subsequent analysis a challenging problem. A taxonomic characterization of metagenomic fragments is required for a deeper understanding of shotgun-sequenced microbial communities, but success has mostly been limited to sequences containing phylogenetic marker genes. Here we present PhyloPythia, a composition-based classifier that combines higher-level generic clades from a set of 340 completed genomes with sample-derived population models. Extensive analyses on synthetic and real metagenome data sets showed that PhyloPythia allows the accurate classification of most sequence fragments across all considered taxonomic ranks, even for unknown organisms. The method requires no more than 100 kb of training sequence for the creation of accurate models of sample-specific populations and can assign fragments ≥1 kb with high specificity.

Advances in analysis of microbial metabolic fluxes via 13C isotopic labeling

Metabolic flux analysis via (13)C labeling ((13)C MFA) quantitatively tracks metabolic pathway activity and determines overall enzymatic function in cells. Three core techniques are necessary for (13)C MFA: (1) a steady state cell culture in a defined medium with labeled-carbon substrates; (2) precise measurements of the labeling pattern of targeted metabolites; and (3) evaluation of the data sets obtained from mass spectrometry measurements with a computer model to calculate the metabolic fluxes. In this review, we summarize recent advances in the (13)C-flux analysis technologies, including mini-bioreactor usage for tracer experiments, isotopomer analysis of metabolites via high resolution mass spectrometry (such as GC-MS, LC-MS, or FT-ICR), high performance and large-scale isotopomer modeling programs for flux analysis, and the integration of fluxomics with other functional genomics studies. It will be shown that there is a significant value for (13)C-based metabolic flux analysis in many biological research fields.

Microbial synthesis of pinene.

The volumetric heating values of todays biofuels are too low to power energy-intensive aircraft, rockets, and missiles. Recently, pinene dimers were shown to have a volumetric heating value similar to that of the tactical fuel JP-10. To provide a sustainable source of pinene, we engineered Escherichia coli for pinene production. We combinatorially expressed three pinene synthases (PS) and three geranyl diphosphate synthases (GPPS), with the best combination achieving ~28 mg/L of pinene. We speculated that pinene toxicity was limiting production; however, toxicity should not be limiting at current titers. Because GPPS is inhibited by geranyl diphosphate (GPP) and to increase flux through the pathway, we combinatorially constructed GPPS-PS protein fusions. The Abies grandis GPPS-PS fusion produced 32 mg/L of pinene, a 6-fold improvement over the highest titer previously reported in engineered E. coli. Finally, we investigated the pinene isomer ratio of our pinene-producing microbe and discovered that the isomer profile is determined not only by the identity of the PS used but also by the identity of the GPPS with which the PS is paired. We demonstrated that the GPP concentration available to PS for cyclization alters the pinene isomer ratio.

An experimental metagenome data management and analysis system

The application of shotgun sequencing to environmental samples has revealed a new universe of microbial community genomes (metagenomes) involving previously uncultured organisms. Metagenome analysis, which is expected to provide a comprehensive picture of the gene functions and metabolic capacity for microbial communities, needs to be conducted in the context of a comprehensive data management and analysis system. We present in this paper IMG/M, an experimental metagenome data management and analysis system that is based on the Integrated Microbial Genomes (IMG) system. IMG/M provides tools and viewers for analyzing both metagenomes and isolate genomes individually or in a comparative context. IMG/M is available at http://img.jgi.doe.gov/m.

On the origin and robustness of power-law species–area relationships in ecology

We present an explanation for the widely reported power-law species–area relationship (SAR), which relates the area occupied by a biome to the number of species that it supports. We argue that power-law SARs are a robust consequence of a skewed species abundance distribution resembling a lognormal with higher rarity, together with the observation that individuals of a given species tend to cluster. We show that the precise form of the SAR transcends the specific details of organism interactions, enabling us to characterize its broad trends across taxa.

Synthetic and systems biology for microbial production of commodity chemicals

The combination of synthetic and systems biology is a powerful framework to study fundamental questions in biology and produce chemicals of immediate practical application such as biofuels, polymers, or therapeutics. However, we cannot yet engineer biological systems as easily and precisely as we engineer physical systems. In this review, we describe the path from the choice of target molecule to scaling production up to commercial volumes. We present and explain some of the current challenges and gaps in our knowledge that must be overcome in order to bring our bioengineering capabilities to the level of other engineering disciplines. Challenges start at molecule selection, where a difficult balance between economic potential and biological feasibility must be struck. Pathway design and construction have recently been revolutionized by next-generation sequencing and exponentially improving DNA synthesis capabilities. Although pathway optimization can be significantly aided by enzyme expression characterization through proteomics, choosing optimal relative protein expression levels for maximum production is still the subject of heuristic, non-systematic approaches. Toxic metabolic intermediates and proteins can significantly affect production, and dynamic pathway regulation emerges as a powerful but yet immature tool to prevent it. Host engineering arises as a much needed complement to pathway engineering for high bioproduct yields; and systems biology approaches such as stoichiometric modeling or growth coupling strategies are required. A final, and often underestimated, challenge is the successful scale up of processes to commercial volumes. Sustained efforts in improving reproducibility and predictability are needed for further development of bioengineering.

Principal component analysis of proteomics (PCAP) as a tool to direct metabolic engineering

Targeted proteomics is a convenient method determining enzyme expression levels, but a quantitative analysis of these proteomic data has not been fully explored yet. Here, we present and demonstrate a computational tool (principal component analysis of proteomics, PCAP) that uses quantitative targeted proteomics data to guide metabolic engineering and achieve higher production of target molecules from heterologous pathways. The method is based on the application of principal component analysis to a collection of proteomics and target molecule production data to pinpoint specific enzymes that need to have their expression level adjusted to maximize production. We illustrated the method on the heterologous mevalonate pathway in Escherichia coli that produces a wide range of isoprenoids and requires balanced pathway gene expression for high yields and titers. PCAP-guided engineering resulted in over a 40% improvement in the production of two valuable terpenes. PCAP could potentially be productively applied to other heterologous pathways as well.