- Email: [email protected]
From functional genomics to systems (micro)biology
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From functional genomics to systems (micro)biology Editorial overview Carmen Buchrieser and Stewart T Cole Current Opinion in Microbiology 2009, 12:528–530 Available online 24th September 2009 1369-5274/$ – see front matter # 2009 Elsevier Ltd. All rights reserved. DOI 10.1016/j.mib.2009.09.001
Carmen Buchrieser Institut Pasteur, Biology of Intracellular Bacteria and CNRS URA 2171, 28 Rue du Docteur Roux, 75724 Paris Cedex 15, France e-mail: [email protected]
Carmen Buchrieser is head of the Biology of Intracellular Bacteria unit at the Institut Pasteur in Paris. She has been involved in the genomic analysis of several bacterial pathogens. Her group focusses now on the study of Legionella pathogenicity, diversity and evolution using different genomic approaches to understand how Legionella causes disease and to improve treatment, surveillance and risk prediction of legionellosis.
Stewart T Cole Global Health Institute, Ecole Polytechnique Fe´de´rale de Lausanne, CH-1015 Lausanne, Switzerland e-mail: [email protected]
Stewart Cole is director of EPFLs Global Health Institute in Lausanne. His group popularised the genomic approach to studying the genetics, evolution and pathogenicity of mycobacteria and is now using genome biology as a foundation for the discovery of new drugs to treat tuberculosis.
The phenomenal breakthroughs in our knowledge and understanding of the genetic basis of microbial life and behaviour, which arose from the pioneering genome sequencing projects, were the starting point for functional genomics and the basis for the development of systems biology approaches. Whilst the first complete bacterial genome sequence published was obtained from Haemophilus influenzae, a pathogen about which relatively little was known at the time [1], this was soon followed by the sequences of reference and model organisms. Subsequently, the power of genomics was extended to many clinical and environmental isolates of pathogenic and non-pathogenic microbes. To date, one or more isolates of each major microbial pathogen have seen their genomes sequenced, as have many environmental and biotechnologically important organisms. The advent of the new generation of ultra-low cost sequencing technologies [2], which are starting to be employed extensively, has opened the door to genome sequencing of many strains from the same species as well as to complex microbial communities like those in the human microbiome, in the organs of different animals or from soil, in addition to communities found in aquatic niches like marine water, hot spring water, or waste water. In parallel, the development and improvement of computational tools have advanced with impressive speed, allowing more efficient analysis of the mass of data obtained. Accompanying this revolution in microbial genomics and genetics, the functional analysis of the data collected has taken a giant step forward due to the development of many methods for large-scale functional analyses involving high-throughput phenotypic assays and the characterization of the transcriptomes and metabolomes of mutants, the elucidation of metabolic pathways, protein–protein interactions, and regulatory systems, to name but a few. The above-cited methods allowed the development of systems biology, an integrative approach based on computational modelling and simulation of large networks of interacting components. Systems biology aims to reveal the interrelationships of all of the elements in a functioning system in order to understand how the system works in an exact and quantitative manner. Collectively, these techniques are generating huge amounts of information and new knowledge that are substantially altering our view of bacterial lifestyles in the environment or the host, and the critical role played by bacteriophages in ecosystems. Bacteria have developed numerous strategies to adapt their gene expression to meet the challenges of an ever-changing environment. For many years, knowledge of gene regulation networks was obtained through studies of individual promoters and transcription factors, often only in vitro. New generation sequencing (NGS) technologies are now being applied successfully to functional genomics for the characterization of mRNAs, sRNAs,
Current Opinion in Microbiology 2009, 12:528–530
www.sciencedirect.com
Editorial overview Buchrieser and Cole 529
DNA or RNA regions bound by certain proteins and other DNA or RNA regions involved in gene expression and regulation. As an illustration of how regulatory networks of bacteria can be studied in situ at the whole genome level, Grainger et al. provide an update of some newly developed powerful technologies. ChIP-on chip identifies DNA–protein interaction in vivo on the genome and originally involved chromatin immunoprecipitation (ChIP) and hybridization to microarrays [3]. This allowed complete regulatory networks to be defined in many different bacteria as exemplified in the first article of this issue. ChIP technology has evolved with the microarrays now being replaced by sequencers. NGS makes it possible to identify immunoprecipitated DNA by sequencing and to study gene regulation free from the bias associated with hybridization to arrays and ChIPNGS can even be applied to bacteria whose genomes are not sequenced yet. Secondly, DNA sampling is an exciting, complementary ChIP-based method, which was recently developed to identify all of the regulatory proteins bound at a specific DNA region, as described by Grainger et al. Another rapidly expanding area of gene regulation studies is the discovery and characterization of small noncoding regulatory RNAs. Many of these control bacterial pathogenicity and the adaptation of bacteria to environmental stresses and to their hosts. However, to date, these studies have mainly been performed in a few model organisms and are still at a preliminary stage. Sharma and Vogel present a comprehensive and detailed overview of the various experimental approaches used to detect and study these important regulatory elements, as well as the techniques for sRNA target discovery. In parallel to different bioinformatics approaches, tiling arrays were for several years the method of choice for transcriptome profiling and discovery of regulatory RNAs. Again, the arrival of NGS changed the field considerably. RNA-seq, massively parallel short-tag sequencing of cDNAs, helped, like no other technology before, to unravel the diversity and importance of small RNAs in all kingdoms of life. Combined with sRNA pulse-expression, transcriptomics and immunoprecipitation with RNA-binding proteins this approach has led to the identification of the targets of sRNAs. Together with the exponential growth of sequence data, metabolic studies through in silico analysis of genomes, coupled with innovative high-throughput functional assays are giving important insight into the metabolism of bacteria in the environment and in the host. This has led to a welcome renaissance of studies devoted to the metabolism and physiology of microbes and consequently to the development of the field of metabolomics. Many different methods are being developed to study a microorganism’s metabolism in a defined condition. In the third article of this issue Trent Northen gives an excellent www.sciencedirect.com
introduction to the use of mass spectrometry (MS)-based enzymatic assays and metabolomics for functional characterization of genes and metabolic characterization of microorganisms. He shows that MS-based metabolic profiling is a powerful tool to validate homology-based metabolite assignments, to discover and characterize undefined metabolic capabilities and pathways, or to identify specific metabolic activities in complex microbial communities. A detailed analysis of how the combination of metabolomics and 13C-flux analysis offers increased sensitivity and coverage of metabolomics methods, by enabling direct detection of labelling patterns in pathway intermediates, is provided by Zamboni and Sauer. Furthermore, the initial dynamics of label propagation through pathway intermediates can be used to assess flux responses. The power of these techniques is demonstrated by different examples. It is clearly shown that the combination of transcriptomics, proteomics, metabolomics and flux analysis provides the most comprehensive datasets for data mining and extraction of biological insight. In the following article, Buman presents Salmonella as a specific example of how the extensive study and knowledge of metabolism can be used for a systems biology approach to host–pathogen interactions and also for systems level infection biology in general. Metabolic, transcriptomic, proteomic and mutant phenotype data are integrated and visualized in networks. Further in silico modelling can then be used to comprehensively interrogate these networks leading to the identification of potential new drug targets or the fine-tuning of live vaccines. A masterly account of the metabolic systems biology of the environmental bacterium Acinetobacter bayleri is presented by Berardinis and coworkers. On the basis of the genome sequence, a collection of single gene mutants and a genome-scale metabolic model, the essentiality of genes, isofunctionality of genes, alternative metabolic pathways, physiological differences (as compared to Escherichia coli) or erroneous annotations are discovered. The authors highlight the power of systematic profiling for the growth of mutant strains and analysis of phenotypic data combined with studies of genomic context and synteny conservation among organisms as an efficient approach to explore gene functions. A manually curated in silico reconstruction of the metabolic pathways and a genome-scale mathematical model derived from this metabolic network are used to model the metabolism at the cellular scale, by focussing on the reaction fluxes at steady state. Through a systems biology approach this model can be confronted with experimental growth phenotypes of the mutant collection opening the way for systematic and accurate functional annotation of the metabolic pathways of this environmental model organism. Studying A. bayleri offers an attractive alternative to Current Opinion in Microbiology 2009, 12:528–530
530 Genomics
some of the earlier model organisms that influenced genome annotation and may have inadvertently misrepresented bacterial metabolism and physiology. In the penultimate, article of this issue Wren and Kay present a general summary of the state of the art of systems microbiology. In addition to the previously discussed techniques and approaches used for systems biology analyses, Wren and Kay point to the importance and advancement of imaging techniques making it possible to study single cells for instance or even single proteins within a cell. Finally, an illuminating account of the biodiversity and biogeography of phages from Vega Thurber reminds us how these parasites act as ecological and evolutionary forces, by shaping the destiny of their bacterial hosts. Whilst acting across spatial and temporal ranges, phages contribute indirectly to nutrient recycling thus influencing the metabolism of microbial communities — a perfect case of intersecting systems microbiology. The challenge of extracting meaningful data in systems biology depends on our ability to integrate and model
Current Opinion in Microbiology 2009, 12:528–530
these multiplatform datasets as highlighted by the latest advances and concepts presented in this edition of Current Opinion in Microbiology. To understand a bacterial system fully and to appreciate the diverse and multifactorial interactions, the powerful approaches of functional genomics and systems biology, developed for model organisms, pathogens and environmental bacteria, are becoming increasingly useful and important, as discussed here. The field of systems microbiology is moving ahead and, in conjunction with the avalanche of data and improvements in analytical methods, will lead to many exciting new discoveries.
References 1.
Fleischmann RD, Adams MD, White O, Clayton RA, Kirkness EF, Kerlavage AR, Bult CJ, Tomb JF, Dougherty BA, Merrick JM et al.: Whole-genome random sequencing and assembly of Haemophilus influenzae Rd. Science 1995, 269:496-512.
2.
Shendure J, Ji H: Next-generation DNA sequencing. Nat Biotechnol 2008, 26:1135-1145.
3.
Grainger DC, Hurd D, Harrison M, Holdstock J, Busby SJ: Studies of the distribution of Escherichia coli cAMP-receptor protein and RNA polymerase along the E. coli chromosome. Proc Natl Acad Sci U S A 2005, 102:17693-17698.
www.sciencedirect.com
From functional genomics to systems (micro)biology Editorial overview Carmen Buchrieser and Stewart T Cole Current Opinion in Microbiology 2009, 12:528–530 Available online 24th September 2009 1369-5274/$ – see front matter # 2009 Elsevier Ltd. All rights reserved. DOI 10.1016/j.mib.2009.09.001
Carmen Buchrieser Institut Pasteur, Biology of Intracellular Bacteria and CNRS URA 2171, 28 Rue du Docteur Roux, 75724 Paris Cedex 15, France e-mail: [email protected]
Carmen Buchrieser is head of the Biology of Intracellular Bacteria unit at the Institut Pasteur in Paris. She has been involved in the genomic analysis of several bacterial pathogens. Her group focusses now on the study of Legionella pathogenicity, diversity and evolution using different genomic approaches to understand how Legionella causes disease and to improve treatment, surveillance and risk prediction of legionellosis.
Stewart T Cole Global Health Institute, Ecole Polytechnique Fe´de´rale de Lausanne, CH-1015 Lausanne, Switzerland e-mail: [email protected]
Stewart Cole is director of EPFLs Global Health Institute in Lausanne. His group popularised the genomic approach to studying the genetics, evolution and pathogenicity of mycobacteria and is now using genome biology as a foundation for the discovery of new drugs to treat tuberculosis.
The phenomenal breakthroughs in our knowledge and understanding of the genetic basis of microbial life and behaviour, which arose from the pioneering genome sequencing projects, were the starting point for functional genomics and the basis for the development of systems biology approaches. Whilst the first complete bacterial genome sequence published was obtained from Haemophilus influenzae, a pathogen about which relatively little was known at the time [1], this was soon followed by the sequences of reference and model organisms. Subsequently, the power of genomics was extended to many clinical and environmental isolates of pathogenic and non-pathogenic microbes. To date, one or more isolates of each major microbial pathogen have seen their genomes sequenced, as have many environmental and biotechnologically important organisms. The advent of the new generation of ultra-low cost sequencing technologies [2], which are starting to be employed extensively, has opened the door to genome sequencing of many strains from the same species as well as to complex microbial communities like those in the human microbiome, in the organs of different animals or from soil, in addition to communities found in aquatic niches like marine water, hot spring water, or waste water. In parallel, the development and improvement of computational tools have advanced with impressive speed, allowing more efficient analysis of the mass of data obtained. Accompanying this revolution in microbial genomics and genetics, the functional analysis of the data collected has taken a giant step forward due to the development of many methods for large-scale functional analyses involving high-throughput phenotypic assays and the characterization of the transcriptomes and metabolomes of mutants, the elucidation of metabolic pathways, protein–protein interactions, and regulatory systems, to name but a few. The above-cited methods allowed the development of systems biology, an integrative approach based on computational modelling and simulation of large networks of interacting components. Systems biology aims to reveal the interrelationships of all of the elements in a functioning system in order to understand how the system works in an exact and quantitative manner. Collectively, these techniques are generating huge amounts of information and new knowledge that are substantially altering our view of bacterial lifestyles in the environment or the host, and the critical role played by bacteriophages in ecosystems. Bacteria have developed numerous strategies to adapt their gene expression to meet the challenges of an ever-changing environment. For many years, knowledge of gene regulation networks was obtained through studies of individual promoters and transcription factors, often only in vitro. New generation sequencing (NGS) technologies are now being applied successfully to functional genomics for the characterization of mRNAs, sRNAs,
Current Opinion in Microbiology 2009, 12:528–530
www.sciencedirect.com
Editorial overview Buchrieser and Cole 529
DNA or RNA regions bound by certain proteins and other DNA or RNA regions involved in gene expression and regulation. As an illustration of how regulatory networks of bacteria can be studied in situ at the whole genome level, Grainger et al. provide an update of some newly developed powerful technologies. ChIP-on chip identifies DNA–protein interaction in vivo on the genome and originally involved chromatin immunoprecipitation (ChIP) and hybridization to microarrays [3]. This allowed complete regulatory networks to be defined in many different bacteria as exemplified in the first article of this issue. ChIP technology has evolved with the microarrays now being replaced by sequencers. NGS makes it possible to identify immunoprecipitated DNA by sequencing and to study gene regulation free from the bias associated with hybridization to arrays and ChIPNGS can even be applied to bacteria whose genomes are not sequenced yet. Secondly, DNA sampling is an exciting, complementary ChIP-based method, which was recently developed to identify all of the regulatory proteins bound at a specific DNA region, as described by Grainger et al. Another rapidly expanding area of gene regulation studies is the discovery and characterization of small noncoding regulatory RNAs. Many of these control bacterial pathogenicity and the adaptation of bacteria to environmental stresses and to their hosts. However, to date, these studies have mainly been performed in a few model organisms and are still at a preliminary stage. Sharma and Vogel present a comprehensive and detailed overview of the various experimental approaches used to detect and study these important regulatory elements, as well as the techniques for sRNA target discovery. In parallel to different bioinformatics approaches, tiling arrays were for several years the method of choice for transcriptome profiling and discovery of regulatory RNAs. Again, the arrival of NGS changed the field considerably. RNA-seq, massively parallel short-tag sequencing of cDNAs, helped, like no other technology before, to unravel the diversity and importance of small RNAs in all kingdoms of life. Combined with sRNA pulse-expression, transcriptomics and immunoprecipitation with RNA-binding proteins this approach has led to the identification of the targets of sRNAs. Together with the exponential growth of sequence data, metabolic studies through in silico analysis of genomes, coupled with innovative high-throughput functional assays are giving important insight into the metabolism of bacteria in the environment and in the host. This has led to a welcome renaissance of studies devoted to the metabolism and physiology of microbes and consequently to the development of the field of metabolomics. Many different methods are being developed to study a microorganism’s metabolism in a defined condition. In the third article of this issue Trent Northen gives an excellent www.sciencedirect.com
introduction to the use of mass spectrometry (MS)-based enzymatic assays and metabolomics for functional characterization of genes and metabolic characterization of microorganisms. He shows that MS-based metabolic profiling is a powerful tool to validate homology-based metabolite assignments, to discover and characterize undefined metabolic capabilities and pathways, or to identify specific metabolic activities in complex microbial communities. A detailed analysis of how the combination of metabolomics and 13C-flux analysis offers increased sensitivity and coverage of metabolomics methods, by enabling direct detection of labelling patterns in pathway intermediates, is provided by Zamboni and Sauer. Furthermore, the initial dynamics of label propagation through pathway intermediates can be used to assess flux responses. The power of these techniques is demonstrated by different examples. It is clearly shown that the combination of transcriptomics, proteomics, metabolomics and flux analysis provides the most comprehensive datasets for data mining and extraction of biological insight. In the following article, Buman presents Salmonella as a specific example of how the extensive study and knowledge of metabolism can be used for a systems biology approach to host–pathogen interactions and also for systems level infection biology in general. Metabolic, transcriptomic, proteomic and mutant phenotype data are integrated and visualized in networks. Further in silico modelling can then be used to comprehensively interrogate these networks leading to the identification of potential new drug targets or the fine-tuning of live vaccines. A masterly account of the metabolic systems biology of the environmental bacterium Acinetobacter bayleri is presented by Berardinis and coworkers. On the basis of the genome sequence, a collection of single gene mutants and a genome-scale metabolic model, the essentiality of genes, isofunctionality of genes, alternative metabolic pathways, physiological differences (as compared to Escherichia coli) or erroneous annotations are discovered. The authors highlight the power of systematic profiling for the growth of mutant strains and analysis of phenotypic data combined with studies of genomic context and synteny conservation among organisms as an efficient approach to explore gene functions. A manually curated in silico reconstruction of the metabolic pathways and a genome-scale mathematical model derived from this metabolic network are used to model the metabolism at the cellular scale, by focussing on the reaction fluxes at steady state. Through a systems biology approach this model can be confronted with experimental growth phenotypes of the mutant collection opening the way for systematic and accurate functional annotation of the metabolic pathways of this environmental model organism. Studying A. bayleri offers an attractive alternative to Current Opinion in Microbiology 2009, 12:528–530
530 Genomics
some of the earlier model organisms that influenced genome annotation and may have inadvertently misrepresented bacterial metabolism and physiology. In the penultimate, article of this issue Wren and Kay present a general summary of the state of the art of systems microbiology. In addition to the previously discussed techniques and approaches used for systems biology analyses, Wren and Kay point to the importance and advancement of imaging techniques making it possible to study single cells for instance or even single proteins within a cell. Finally, an illuminating account of the biodiversity and biogeography of phages from Vega Thurber reminds us how these parasites act as ecological and evolutionary forces, by shaping the destiny of their bacterial hosts. Whilst acting across spatial and temporal ranges, phages contribute indirectly to nutrient recycling thus influencing the metabolism of microbial communities — a perfect case of intersecting systems microbiology. The challenge of extracting meaningful data in systems biology depends on our ability to integrate and model
Current Opinion in Microbiology 2009, 12:528–530
these multiplatform datasets as highlighted by the latest advances and concepts presented in this edition of Current Opinion in Microbiology. To understand a bacterial system fully and to appreciate the diverse and multifactorial interactions, the powerful approaches of functional genomics and systems biology, developed for model organisms, pathogens and environmental bacteria, are becoming increasingly useful and important, as discussed here. The field of systems microbiology is moving ahead and, in conjunction with the avalanche of data and improvements in analytical methods, will lead to many exciting new discoveries.
References 1.
Fleischmann RD, Adams MD, White O, Clayton RA, Kirkness EF, Kerlavage AR, Bult CJ, Tomb JF, Dougherty BA, Merrick JM et al.: Whole-genome random sequencing and assembly of Haemophilus influenzae Rd. Science 1995, 269:496-512.
2.
Shendure J, Ji H: Next-generation DNA sequencing. Nat Biotechnol 2008, 26:1135-1145.
3.
Grainger DC, Hurd D, Harrison M, Holdstock J, Busby SJ: Studies of the distribution of Escherichia coli cAMP-receptor protein and RNA polymerase along the E. coli chromosome. Proc Natl Acad Sci U S A 2005, 102:17693-17698.
www.sciencedirect.com