Patrik D'haeseleer

How does gene expression clustering work

Clustering is often one of the first steps in gene expression analysis. How do clustering algorithms work, which ones should we use and what can we expect from them?

Microbial gene functions enriched in the Deepwater Horizon deep-sea oil plume

The Deepwater Horizon oil spill in the Gulf of Mexico is the deepest and largest offshore spill in the United State history and its impacts on marine ecosystems are largely unknown. Here, we showed that the microbial community functional composition and structure were dramatically altered in a deep-sea oil plume resulting from the spill. A variety of metabolic genes involved in both aerobic and anaerobic hydrocarbon degradation were highly enriched in the plume compared with outside the plume, indicating a great potential for intrinsic bioremediation or natural attenuation in the deep sea. Various other microbial functional genes that are relevant to carbon, nitrogen, phosphorus, sulfur and iron cycling, metal resistance and bacteriophage replication were also enriched in the plume. Together, these results suggest that the indigenous marine microbial communities could have a significant role in biodegradation of oil spills in deep-sea environments.

What are DNA sequence motifs

Sequence motifs are becoming increasingly important in the analysis of gene regulation. How do we define sequence motifs, and why should we use sequence logos instead of consensus sequences to represent them? Do they have any relation with binding affinity? How do we search for new instances of a motif in this sea of DNA?

Targeted Discovery of Glycoside Hydrolases from a Switchgrass-Adapted Compost Community

Development of cellulosic biofuels from non-food crops is currently an area of intense research interest. Tailoring depolymerizing enzymes to particular feedstocks and pretreatment conditions is one promising avenue of research in this area. Here we added a green-waste compost inoculum to switchgrass (Panicum virgatum) and simulated thermophilic composting in a bioreactor to select for a switchgrass-adapted community and to facilitate targeted discovery of glycoside hydrolases. Small-subunit (SSU) rRNA-based community profiles revealed that the microbial community changed dramatically between the initial and switchgrass-adapted compost (SAC) with some bacterial populations being enriched over 20-fold. We obtained 225 Mbp of 454-titanium pyrosequence data from the SAC community and conservatively identified 800 genes encoding glycoside hydrolase domains that were biased toward depolymerizing grass cell wall components. Of these, ∼10% were putative cellulases mostly belonging to families GH5 and GH9. We synthesized two SAC GH9 genes with codon optimization for heterologous expression in Escherichia coli and observed activity for one on carboxymethyl cellulose. The active GH9 enzyme has a temperature optimum of 50°C and pH range of 5.5 to 8 consistent with the composting conditions applied. We demonstrate that microbial communities adapt to switchgrass decomposition using simulated composting condition and that full-length genes can be identified from complex metagenomic sequence data, synthesized and expressed resulting in active enzyme.

A Thermophilic Ionic Liquid-Tolerant Cellulase Cocktail for the Production of Cellulosic Biofuels

Generation of biofuels from sugars in lignocellulosic biomass is a promising alternative to liquid fossil fuels, but efficient and inexpensive bioprocessing configurations must be developed to make this technology commercially viable. One of the major barriers to commercialization is the recalcitrance of plant cell wall polysaccharides to enzymatic hydrolysis. Biomass pretreatment with ionic liquids (ILs) enables efficient saccharification of biomass, but residual ILs inhibit both saccharification and microbial fuel production, requiring extensive washing after IL pretreatment. Pretreatment itself can also produce biomass-derived inhibitory compounds that reduce microbial fuel production. Therefore, there are multiple points in the process from biomass to biofuel production that must be interrogated and optimized to maximize fuel production. Here, we report the development of an IL-tolerant cellulase cocktail by combining thermophilic bacterial glycoside hydrolases produced by a mixed consortia with recombinant glycoside hydrolases. This enzymatic cocktail saccharifies IL-pretreated biomass at higher temperatures and in the presence of much higher IL concentrations than commercial fungal cocktails. Sugars obtained from saccharification of IL-pretreated switchgrass using this cocktail can be converted into biodiesel (fatty acid ethyl-esters or FAEEs) by a metabolically engineered strain of E. coli. During these studies, we found that this biodiesel-producing E. coli strain was sensitive to ILs and inhibitors released by saccharification. This cocktail will enable the development of novel biomass to biofuel bioprocessing configurations that may overcome some of the barriers to production of inexpensive cellulosic biofuels.

Global transcriptome response to ionic liquid by a tropical rain forest soil bacterium, Enterobacter lignolyticus

To process plant-based renewable biofuels, pretreatment of plant feedstock with ionic liquids has significant advantages over current methods for deconstruction of lignocellulosic feedstocks. However, ionic liquids are often toxic to the microorganisms used subsequently for biomass saccharification and fermentation. We previously isolated Enterobacter lignolyticus strain SCF1, a lignocellulolytic bacterium from tropical rain forest soil, and report here that it can grow in the presence of 0.5 M 1-ethyl-3-methylimidazolium chloride, a commonly used ionic liquid. We investigated molecular mechanisms of SCF1 ionic liquid tolerance using a combination of phenotypic growth assays, phospholipid fatty acid analysis, and RNA sequencing technologies. Potential modes of resistance to 1-ethyl-3-methylimidazolium chloride include an increase in cyclopropane fatty acids in the cell membrane, scavenging of compatible solutes, up-regulation of osmoprotectant transporters and drug efflux pumps, and down-regulation of membrane porins. These findings represent an important first step in understanding mechanisms of ionic liquid resistance in bacteria and provide a basis for engineering microbial tolerance.

Complete genome sequence of “Enterobacter lignolyticus” SCF1

In an effort to discover anaerobic bacteria capable of lignin degradation, we isolated “Enterobacter lignolyticus” SCF1 on minimal media with alkali lignin as the sole source of carbon. This organism was isolated anaerobically from tropical forest soils collected from the Short Cloud Forest site in the El Yunque National Forest in Puerto Rico, USA, part of the Luquillo Long-Term Ecological Research Station. At this site, the soils experience strong fluctuations in redox potential and are net methane producers. Because of its ability to grow on lignin anaerobically, we sequenced the genome. The genome of “E. lignolyticus” SCF1 is 4.81 Mbp with no detected plasmids, and includes a relatively small arsenal of lignocellulolytic carbohydrate active enzymes. Lignin degradation was observed in culture, and the genome revealed two putative laccases, a putative peroxidase, and a complete 4-hydroxyphenylacetate degradation pathway encoded in a single gene cluster.

Proteogenomic Analysis of a Thermophilic Bacterial Consortium Adapted to Deconstruct Switchgrass

Thermophilic bacteria are a potential source of enzymes for the deconstruction of lignocellulosic biomass. However, the complement of proteins used to deconstruct biomass and the specific roles of different microbial groups in thermophilic biomass deconstruction are not well-explored. Here we report on the metagenomic and proteogenomic analyses of a compost-derived bacterial consortium adapted to switchgrass at elevated temperature with high levels of glycoside hydrolase activities. Near-complete genomes were reconstructed for the most abundant populations, which included composite genomes for populations closely related to sequenced strains of Thermus thermophilus and Rhodothermus marinus, and for novel populations that are related to thermophilic Paenibacilli and an uncultivated subdivision of the little-studied Gemmatimonadetes phylum. Partial genomes were also reconstructed for a number of lower abundance thermophilic Chloroflexi populations. Identification of genes for lignocellulose processing and metabolic reconstructions suggested Rhodothermus, Paenibacillus and Gemmatimonadetes as key groups for deconstructing biomass, and Thermus as a group that may primarily metabolize low molecular weight compounds. Mass spectrometry-based proteomic analysis of the consortium was used to identify >3000 proteins in fractionated samples from the cultures, and confirmed the importance of Paenibacillus and Gemmatimonadetes to biomass deconstruction. These studies also indicate that there are unexplored proteins with important roles in bacterial lignocellulose deconstruction.

Microbial genotype–phenotype mapping by class association rule mining

Motivation: Microbial phenotypes are typically due to the concerted action of multiple gene functions, yet the presence of each gene may have only a weak correlation with the observed phenotype. Hence, it may be more appropriate to examine co-occurrence between sets of genes and a phenotype (multiple-to-one) instead of pairwise relations between a single gene and the phenotype. Here, we propose an efficient class association rule mining algorithm, netCAR, in order to extract sets of COGs (clusters of orthologous groups of proteins) associated with a phenotype from COG phylogenetic profiles and a phenotype profile. netCAR takes into account the phylogenetic co-occurrence graph between COGs to restrict hypothesis space, and uses mutual information to evaluate the biconditional relation. Results: We examined the mining capability of pairwise and multiple-to-one association by using netCAR to extract COGs relevant to six microbial phenotypes (aerobic, anaerobic, facultative, endospore, motility and Gram negative) from 11 969 unique COG profiles across 155 prokaryotic organisms. With the same level of false discovery rate, multiple-to-one association can extract about 10 times more relevant COGs than one-to-one association. We also reveal various topologies of association networks among COGs (modules) from extracted multiple-to-one correlation rules relevant with the six phenotypes; including a well-connected network for motility, a star-shaped network for aerobic and intermediate topologies for the other phenotypes. netCAR outperforms a standard CAR mining algorithm, CARapriori, while requiring several orders of magnitude less computational time for extracting 3-COG sets. Availability: Source code of the Java implementation is available as Supplementary Material at the Bioinformatics online website, or upon request to the author. Contact: makio323@gmail.com Supplementary information: Supplementary data are available at Bioinformatics online.

Identification of Biofilm Matrix-Associated Proteins from an Acid Mine Drainage Microbial Community†

ABSTRACT In microbial communities, extracellular polymeric substances (EPS), also called the extracellular matrix, provide the spatial organization and structural stability during biofilm development. One of the major components of EPS is protein, but it is not clear what specific functions these proteins contribute to the extracellular matrix or to microbial physiology. To investigate this in biofilms from an extremely acidic environment, we used shotgun proteomics analyses to identify proteins associated with EPS in biofilms at two developmental stages, designated DS1 and DS2. The proteome composition of the EPS was significantly different from that of the cell fraction, with more than 80% of the cellular proteins underrepresented or undetectable in EPS. In contrast, predicted periplasmic, outer membrane, and extracellular proteins were overrepresented by 3- to 7-fold in EPS. Also, EPS proteins were more basic by ∼2 pH units on average and about half the length. When categorized by predicted function, proteins involved in motility, defense, cell envelope, and unknown functions were enriched in EPS. Chaperones, such as histone-like DNA binding protein and cold shock protein, were overrepresented in EPS. Enzymes, such as protein peptidases, disulfide-isomerases, and those associated with cell wall and polysaccharide metabolism, were also detected. Two of these enzymes, identified as β-N-acetylhexosaminidase and cellulase, were confirmed in the EPS fraction by enzymatic activity assays. Compared to the differences between EPS and cellular fractions, the relative differences in the EPS proteomes between DS1 and DS2 were smaller and consistent with expected physiological changes during biofilm development.