The Ravel Laboratory for Microbial Genomics
The focus of my research group is on the application of microbial genomics to three main topics:
1. Exploring the human microbiome: ecology and metagenomics
2. Microbial genome sequence comparative analyses: the making of a genome
3. Chemical genomics: from genes to structure.
1. Exploring the human microbiome: ecology and metagenomics
In addition to the numerous but poorly characterized beneficial effects of the endogenous microflora on human health, a proper understanding of community membership, relative abundance, and variations is critical for recognizing potential pathogens and patterns that are predictive of disease. Basic principles and paradigms in the field of ecology have not yet been applied to the study of the human microbial ecosystem. For example, we have virtually no information on the levels of microbial diversity (“richness”) and abundance (“evenness”) that are optimal for maintenance of local health, or of those that are associated with disease. We are only just recently learning about microbial partitioning within human micro-environments, and still understand little about inter-individual variability or variability (compositional and functional) as a function of time. The validity of the “intermediate disturbance theory” and its application to human endogenous microbial communities have not been explored. Furthermore, our capabilities to predict the effects of physical, chemical or disease perturbations on these microbial communities are extremely limited.
Metagenomic studies performed to date have fallen short from answering any major questions about the ecology of the human microbiome and its interaction with its host. These studies, limited in scope and number of subjects analyzed, are of little use in understanding human health and disease.
To address these issues, my group, in collaboration with Dr. Larry Forney at the University of Idaho, and Dr. Kevin Ault at Emory University, has initiated a 5-year NIAID funded project aiming at developing a better understanding of the ecology of the human vagina. The normal vaginal microflora in healthy women of reproductive age plays a key role in preventing successful colonization by “undesirable” organisms including those responsible for bacterial vaginosis, yeast infections, sexually transmitted diseases and urinary tract infections. The long-term goal of this project is to develop an accurate understanding of the composition and ecology of the vagina microbial ecosystem in normal, healthy women as an essential prerequisite for comprehending how the normal microflora reduces the risk of acquiring these communicable diseases and for defining the factors determining disease susceptibility. We believe that several factors have been overlook in previous metagenomic projects, mainly the fact that genetic backgrounds might influence the composition of the microflora and that while community compositions markerdly vary amongst human, the functional potential of a community might be similar.
In this project we are: 1) conducting a comprehensive survey the vaginal microflora in 400 women of different ethnic background using several 16S rRNA analysis technologies. We will correlate the community composition with genetic backgrounds; 2) developing a 16S rDNA-based molecular tool (molecular inversion probes) to rapidly and quantitatively measure the microbial species composition and abundance of a vaginal community. 3) will characterize the metabolic potential of the vaginal microflora of healthy women by community genomics of the most predominant community types. 4) developing the Vaginal Microbiome Expression GeneChip® array, a high density oligonucleotide microarray-based tool for functional genomic analyses of vaginal microbial community. Using this tool we will assess community gene expression over the course of two months, while monitoring reproductive hormone levels.
I envision an effort that applies genomic and post-genomic technologies towards the goal of generating a comprehensive understanding of microbial ecosystems and their genomic content within the human body. This effort will include: 1) the development of genomic tools to survey microbial community composition 2) a survey of gene and genomic diversity within these microbial populations; 2) developing post-genomic tools to understand variability in gene and genomic content and gene activity as a function of time, space and the effects of perturbations, such as disease; 3) developing a better understanding of the interaction of the human microbiome with its host and 4) studying the role of the mucosal immune system in microbial colonization and maintenance.
Future Projects on exploring the microbiome and its effect on health and disease.
These will explore the gut colonization process in term and pre-term babies and attempt at understanding the basis of necrotizing enterocolitis in preterm babies and Crohn’s disease development in children. In addition, the data generated under these projects will drive the program towards a greater integration of human genetics factors in establishing community types and disease susceptibility. This could lead to the development of diagnostic assays and the development of probiotics among others.
2. Microbial genome sequence comparative analyses: the making of a genome
No field of research has embraced and applied genomic technology more than the field of microbiology. While metagenomics approaches are allowing us to begin to probe complex microbial communities for the first time, and helping to unravel the relationships between microbial species, comparative microbial genomics is providing a foundation for a broad range of applications, from understanding basic biological processes (including evolution), host-pathogen interactions, to discovering DNA variations that can be used in genotyping or forensic analyses, as well as the engineering of microbes for industrial applications.
This program capitalizes on the amount of genome sequences for microbial pathogens that is now available. In the past 3 years my group has sequenced the genomes of over 50 important human pathogens, including Bacillus anthracis, Bacillus cereus, Yersinia pestis, Yersinia pseudotuberculosis, Enteropathogenic Escherichia coli (including E. coli 0157:H7 from contaminated food), Shigella spp., and Salmonella sp. To better gain insights into the evolution of these major human pathogens, my group is also sequencing and analyzing closely related non-pathogenic isolates, including E. coli, Bacillus subtilis, B. cereus, Bacillus subtilis and Bacillus megaterium.
This program, while broad in scope, is focused on deciphering the evolutionary processes driving these important human pathogens. It also includes the development of genotyping and forensic analysis tools. Development of novel bioinformatics tools is driving these efforts. This tools includes 1) a bioinformatic pipeline that incorporates the whole genome alignment tool MUMmer to extract single nucleotide polymorphisms (SNPs) and insertion/deletion (INDELs) from genome sequences (draft or closed) when compared to a reference genome. A phylogenetic component to this pipeline including the PAML software has also been implemented; 2) The BLAST Score Ratio (BSR) approach, classifies all putative peptides within several genomes using a measure of similarity based on the ratio of BLAST scores and allows rapid identification of conserved genomic regions as well as a number of common genomic rearrangements such as insertions, deletions and inversions. 3) whole genome tiling microarrays and the software necessary to visualize and analyze the data. These custom-designed Affymetrix GeneChips comprise of 2,5 million 25-mer oligonucleotides offset by only 5 nucleotides tile both strands of an entire genome. These GeneChips are used as a comparative hybridization tool for polymorphism discovery and genotyping, but also have applications in transcriptomics (expression and transcript mapping) and the study of small regulatory RNA among others.
These tools are being applied to the study of the evolutionary history of the Bacillus cereus group of organisms, including B. anthracis, the genus Bacillus, and the enteric pathogens Yersinia sp., Salmonella sp. and Escherichia coli.
These projects are supported by funds from the NIH and grants from the National Science Foundation.
3. Chemical genomics: from genes to structures
This program is supported by two grants from the National Science Foundation and one from the National Institutes of Health, and aims at deciphering microbial secondary metabolites biosynthesis.
This program was initiated through a grant from the NSF to sequence the genome of Prochloron didemni, an obligate cyanobacterial symbiont of the coral reef ascidian Lissoclinum patella. Many secondary metabolites are found in Prochloron-bearing ascidians, among those are cytotoxic cyclic peptides of the class patellamides. In collaboration with Eric Schmidt at the University of Utah and as part of the P. didemni sequencing project we identified the patellamides biosynthetic gene cluster and establish its microbial origin. We confirmed its functions by heterologous expression of the entire microcin-like pathway in E. coli. This work led to the engineering of the pathway in E. coli and the discovery of the enormous genetic diversity, hence structure diversity of the this class of compound. These findings have implications on the evolution of the pathway and on the vertical transmission of P. didemni. This work was leveraged into a five year award from NIH to study this important class of compounds.
The genomic study of secondary metabolite producers was expanded to two plant biocontrol agents, Pseudomonas fluorescens and Lysobacter enzymogenes. The analysis of the genome of P. fluorescens shed light on its capacity to produce secondary metabolites, and led to the prediction of the structure of a novel cyclic pentapeptide, which was later chemically confirmed. The project aiming at sequencing the genome of L. enzymogenes has just started and similarly, is expected to produce interesting findings.
Bioinformatic tools developed to analyze the secondary metabolic potential of these organisms were developed. These tools are now the focus of this program and are being integrated as part of 2METDB: a knowledge-based predictive tools for secondary metabolism.
Genome sequencing data are accumulating at a phenomenal rate. Arguably, the greatest challenge posed by these data is the assignment of a protein function from its primary sequence. Assuming proteins of a similar sequence perform similar functions, many proteins can be assigned a putative function via homology-based analyses. However, these analysis are often less useful for enzymes because only the type of reaction catalyzed and not the substrate(s) or product(s) of the reaction can be predicted. Secondary metabolite biosynthetic pathways consist of gene clusters encoding for such enzymes, thus making their predictive annotation an extremely difficult task that has not yet been addressed by scientists. Considering the impact that secondary metabolites have had and continue to have on human life, possessing bioinformatics tools that could predict pathway and natural product structures are critical to facilitate and accelerate the discovery of novel secondary metabolites.
A wealth of information that needs to be archived
Microbial secondary metabolites show enormous functional diversity and include antimicrobial, anti-fungal, anti-viral, anti-parasitic, anti-tumor, anti-inflammatory, immunosuppressant, hypocholesterolemic and siderophores among others. Interestingly, the majority of the antibiotics used medicinally are of microbial origin, as is the case for our last line of defense against microbial infections, the peptide vancomycin. Over the past decade, the development of molecular genetic tools has created a new understanding of the way in which microorganisms make secondary metabolites. It is now possible to dissect the gene clusters for biosynthetic pathways, to assign chemical functions to specific genes, and tools are now available to manipulate short clusters for the biosynthesis of hybrid molecules, as shown with the patellamides. Creative use of these same tools and knowledge has allowed scientists in the field of natural product discovery to access the genetic information responsible for these unusual metabolites, and design studies to elucidate their biosynthesis at the molecular and biochemical level. These studies have generated a wealth of genetic and biochemical information for pathways of very important secondary metabolites. However, this information has not been compiled into a resource that the broad scientific community can freely access.
Current annotation pipelines perform extremely poorly at predicting secondary metabolite biosynthetic pathways. One of the main reasons is the lack of knowledge-based resources that can be used by the annotation engine. Molecular genetic tools have allowed chemists and biochemists to generate a better understanding of the way microorganisms synthesize such metabolites. We are compiling this wealth of genetic, biochemical and chemical information into 2METDB, a knowledge-based resource for secondary metabolism. This bioinformatics resource builds upon scripts that allow for predictive analysis of biosynthetic pathways. We are developing a web-interface to 2METDB that will be freely available to the scientific community, and will have applications in genome annotation, biochemical studies of previously unknown compounds, and in developing a better understanding of the evolutionary origin of such complex pathways.
PROJECTS
