1. 1 Advanced Environmental Biotechnology II Week 12 - microbial ecology and genomics

2. 2 10 Lessons from the genomes: microbial ecology and genomics Andrew S.Whiteley, Mike Manefield, Sarah L.Turner and Mark J.Bailey

3. 3 10.1 Introduction Microbial ecology is the study of interactions between microbes and their biotic and abiotic environments. The genes of microbes determine their responses to their environment and how they affect their environment.

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8. 8 Microbes are constantly adapting to their environments through: -immediate responses already encoded on the genome, occurring through phenotypic changes mediated by the complex regulatory systems governing gene expression. This is fast yet relatively limited in what it can do. -adaptive evolution, which involves changes in the genetic composition of an organism, as selected for by the environment. This is a slow, longer-term response but appears to be unlimited.

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12. 12 Genomics can be divided into structural and functional aspects. ‘Structural genomics’ is the analysis of genome composition and architecture, which requires the sequencing of an organism’s entire genetic material. The ecologically significant characteristics of genomes can be found by comparing the genome structure of organisms with different roles in different ecosystems. Structural genomics corresponds to an analysis of genetic adaptation to environmental change.

13. 13 ‘Functional genomics’ is the analysis of global gene expression from genomes. It looks at regulatory systems and their effect upon gene expression underlying physiological responses to environmental change.

14. 14 10.2 Structural genomics To understand the complete biology of an organism we must first find its entire genome sequence. But genome sequences do not provide a complete biological understanding. The complete ecology of any bacterium has to be fully described.

15. 15 The first complete bacterial genome, of H. influenza, was reported to contain 1743 open reading frames (ORFs), of which 736 (42%) had ‘no role assignment’. Of these hypothetical ORFs, 347 matched other hypothetical proteins in the databases and 389 were unique to the H. influenza genome. Most of the predicted core metabolic functions necessary for free-living bacteria were found, except for those already predicted to be absent.

16. 16 Bioinformatic analysis of the genome sequence showed functional grouping of genes and previously unidentified genes, under the regulation of well- described transcriptional regulators.

17. 17 10.3 Comparative genomics Complete genome sequences are available for over 2370 Bacteria and 145 Archaea. http://www.ncbi.nlm.nih.gov/genomes/MICROBES/Complete.html http://www.ncbi.nlm.nih.gov/genomes/MICROBES/Complete.html Comparative genomic studies help understand basic bacterial genome organization, ie. gene content, order, regulation and evolution.

18. 18 10.3 Comparative genomics This is done by intra-species/genus genome comparisons and can include species that are distantly related but occupy a similar ecological niche, eg. The former comparisons might include intracellular pathogens Mycobacteria, Chlamydia, Rikettsia) and/or symbionts (Buchnera) of eukaryotes, to identify shared genome traits.

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20. 20 Comparisons can also be made to closely related bacterial species that occupy different ecological niches, eg. members of the Rhizobiaceae, which include the facultative intracellular pathogens Brucella spp. and plant/soil associated rhizobial species. However, most of the genomes completed are of pathogenenic species, and so, the diversity and representation of environmental ecotypes for comparison is restricted.

21. Composition of bacterial communities based on the percentages of different bacterial phyla documented in clone libraries of the 16S rRNA gene 21

22. Phylogenetic tree of Alphaproteobacteria groups commonly found in dark ocean habitats. 22

23. 23 10.3.1 Small genomes The genomes of two Buchnera aphidicola spp., isolated from different host aphids, give the simplest genomes for comparison. As obligate intracellular symbionts that are maternally transmitted between aphid generations, their ecology is relatively simple: they only experience a single largely unchanging environment. The symbiosis may have originated ~150 million years ago (MYA) and the two host species to have diverged ~50 MYA.

24. 24 10.3.1 Small genomes Ecologically, Buchnera provide the aphid host with metabolic pathways for the synthesis of essential amino acids, absent from phloem sap upon which the aphids feed. The two buchneral genomes are relatively small (~641 kbp) and share 526 of their 564 (Buchnera Ap) and 545 (Buchnera Sg) genes, all of which occur in the same order in each genome.

25. 25 Comparisons show that most differences are point mutations that generate pseudogenes and gene losses, with Buchnera Ap containing 13 and Buchnera Sg 38 pseudogenes.

26. 26 Some gene inactivations fit with known ecological differences. Five of the Buchnera Sg pseudogenes are parts of the cysteine biosynthetic pathway which correlates with the higher levels of cysteine in the phloem of grasses, compared with pea, the main food plants of S. graminum and A. pisum respectively. Random mutation and the reduction of selective pressures to keep the function have probably contributed to the inactivation of these genes.

27. 27 Pseudogenes are relatively recent gene inactivations since, over time, useless DNA sequences will be deleted from the genome. Comparisons show that there are 14 gene sequences present only in Buchnera Ap and four in Buchnera Sg. All of these genes are similar to hypothetical proteins in E. coli, their closest free-living relative. All 18 were therefore likely to have been present in the last common ancestor of the Buchnera lineage Maybe differential loss or maintenance reflects host/niche adaptation.

28. 28 Despite their small genome sizes, ~14% of the open reading frames (‘ORFs’) of the Buchnera genomes code for ‘hypothetical’ proteins of unknown function. On average, at least 25% of the genes in each bacterial genome are ‘hypothetical”. This reaches a maximum in the archaeon, Aeropyrum pernix, within which 57% of the ORFs have no known function. Even though the genetics of Escherichia coli K12 and Bacillus subtilis have been studied intensively for >50 years, they still don’t have all their ORFs known.

29. 29 Studies have looked at phenotypic differences, in laboratory assays, and may have overlooked genes that enable E. coli to survive in the mammalian gut or B. subtilis in soil. eg. deleting up to 313 kbp of the E. coli genome doesn’t affect the growth rate of the mutant in laboratory culture. So there are high levels of functional redundancy and/or large numbers of genes which are only environmentally regulated. This is a big problem when analyzing an organism’s genome in the laboratory. Environmentally regulated genes might be missed.

30. 30 10.3.2 Large genomes The natural environment is highly complex, due to physical, chemical and biological differences in different places and times. All the larger genomes sequenced are from soil-associated bacteria. The largest examples include Mesorhizobium loti (7.04 Mbp), Bradyrhizobium japonicum (9.1 Mbp), Streptomyces coelicolor (8.67 Mbp), Pirellula sp. (7.14 Mbp) and Pseudomonas aeruginosa (6.26 Mbp). P. aeruginosa is a common environmental bacterium.

31. 31 Other large genomes include the plant- associated bacteria Sinorhizobium meliloti (6.8 Mbp), Agrobacterium tumefaciens (5.6 Mbp), Bacillus anthracis (5.23 Mbp) and Bacillus cereus (5.43 MBp) and Xanthomonas spp. (5.1 and 5.2 Mbp). The large genome size of P. aeruginosa along with high numbers of regulators enable it to sense and respond to environmental fluctuations; the same is possibly true for the genome of the S. meliloti, containing large numbers of ORFs with homology to membrane-associated transporter proteins.

32. 32 10.3.3 The horizontal gene pool (HGP) Comparison of benign and pathogenic strains have identified genes involved in pathogenicity. These genes are often in pathogenicity islands and/or mobile genetic elements (e.g. phage, plasmids, transposons), responsible for gene transfers between strains and species.

33. Naked DNA uptake (transformation), viruses (transduction), and plasmids (conjugation) are why the genetic units of heredity need not be inherited in the usual sense

35. 35 Horizontally transferred genes should display ‘patchy’ distributions across evolutionary lineages, within species and populations, and may be readily identified by %GC contents that differ markedly from adjacent chromosomal sequences. Such distributions have been described for pathogenicity traits in E. coli, Vibrio chloerae Streptococci, Helicobacter pylori and Shewanella spp.. The acquisition of pathogenicity may be adaptation by niche expansion. Similar evidence exists for non-pathogenic bacteria isolated from different environments, where ecologically relevant genes are found on ‘Ecoislands’ and plasmids.

36. 36 Gene loss seems to be a function of mutation and reduced selection, whilst the horizontal acquisition of advantageous genes enables niche expansion. Buchnera spp. may have reduced numbers of transposons and other repeat sequences. Such repeat sequences are hot-spots for recombination, enabling gene acquisition, gene losses, gene duplications and genome rearrangements).

37. 37 Organisms in more heterogeneous environments (variable in space and time) will have a greater genetic potential. This will be seen both quantitatively (more DNA) and qualitatively (greater potential for recombination) and that a large proportion of genomic information will be associated with the HGP. Horizontal gene transfers provide a means for rapid adaptation to new or changing environments.

38. 38 10.3.4 Insights into phytogeny Bacterial genomes are dynamic, undergoing gene losses and gene acquisition by horizontal transfer or gene duplication. This dynamism can result in different (non- congruent) tree topologies when phylogenies are constructed from several different genes for a defined group of organisms.

39. 39 10.3.4 Insights into phytogeny To construct better phylogenies is to combine data for several genes, reducing the contribution of strange or weak evolutionary signals. An alternative approach is to use whole genome gene content and/or gene order as a measure of phylogenetic relatedness. These approaches produce phylogenies that largely agree with established single gene phylogenies, such as 16S ribosomal RNA, Horizontal gene transfers contribute significantly to short-term bacterial adaptation, but these are not enough to blur the evolutionary relationships of bacterial lineages.

41. 41 Comparative genomics says interesting things about bacterial evolution and patterns of adaptation, as a basis for understanding bacteria in an ecological context. eg. the horizontal gene pool is an important component of bacterial adaptation and that the amount of horizontally transferred DNA increases with genome size.

42. 42 10.4 Functional genomics in microbial ecology Functional genomics (the genome- wide analysis of gene expression) is a powerful way to describe how microorganisms will respond to their environment. Global analyses of mRNA transcript, protein and metabolite production constitute the three levels of functional genomics, each with their own limitations and advantages.

44. 44 10.4.1 Characterizing microbial responses to environmental change The characterization of genome- wide gene expression profiles has been most useful in analyzing the response of a microbe to changes in environmental parameters under controlled laboratory conditions.

45. 45 10.4.1 Characterizing microbial responses to environmental change For example, global changes in protein expression of E. coli K-12 in response to common environmental challenges such as starvation for carbon, nitrogen, phosphate and individual amino acids, oxidative stress, heat shock (42 and 50°C), shifts to and from anaerobic conditions and treatment with naladixic acid, quinone, 2,4-dinitrophenol and cadmium chloride, have been characterized.

47. 47 The analysis of any given proteome and the ability to isolate proteins of interest via two-dimensional gel electrophoresis is limited to subsets of an organism’s total protein content. This restricts the use of this analysis for the description of genome-wide gene expression. The difficulties associated with the isolation of membrane fractions may necessitate the separate analysis of the membrane subproteome and cytosolic proteomes.

48. 48 By contrast, microarrays enable the genome- wide assessment of gene expression in terms of mRNA transcript production (transcriptome analysis). Eg. high-density microarrays of 4290 open reading frames from E. coli K-12 have been used to profile the global transcriptional response of this organism in minimal and rich media. Increasingly, transcriptome- and proteome-based analyses are now being used in combination to investigate global gene expression in various organisms under various conditions.

49. 49 Isolating the entire transcriptome of an organism is a simpler task than isolating an entire proteome, but there are a number of limitations to transcriptomics. The analyses of transcriptomes as a means of describing genome-wide gene expression ignores post-transcriptional and post- translational levels of control in gene expression. DNA microarrays, until recently, have been relatively difficult to make but array developments help microarray production ‘off the shelf for ‘model’ organisms, or for those which are being sequenced independently by other researchers.

50. 50 10.4.2 Relating specific genes to specific functions It is hard to give a function to the large numbers of hypothetical genes in genome sequences. Genome sequencing projects have shown that there are many hypothetical genes. Their individual roles in defining metabolic, physiological, structural and morphological diversity are still unknown. A first goal in microbial ecology is to relate specific genes to particular ecological functions. Functional genomic analyses can be used to characterize the effects of mutations on gene expression and thereby relate the cellular role of a gene product to an ecologically relevant gene.

51. 51 One study compared the transcriptome and the proteome of a putative ferric uptake regulator (fur) mutant of Shewanella oneidensis with those of a wild type strain to confirm the role of fur in the regulation of siderophore-mediated iron assimilation. The results also showed fur is used in energy metabolism. There might be a regulatory framework underlying the ability of S. oneidensis to generate energy via the reduction of insoluble ferric iron. So this organism can live under oxygen-limited, iron- abundant conditions.

52. 52 Another example is the characterization of genes regulated by intercellular signals in bacteria. An E. coli DNA microarray was used to find which genes display altered expression levels during quorum sensing by investigating gene expression in a luxS mutant that was unable to synthesize the signalling pheromone AI-2. If the AI-2 signal was added to growth medium, >5% of E. coli ORFs were responsive to the presence of the signal, including genes involved in cell division, morphogenesis and cell surface architecture.

53. 53 Saccharomyces cerevisiae was grown in glucose-limited chemostats over 250 generations and genome-wide transcription of the resulting strains was compared with that of the parent. DNA microarrays revealed that all successful populations had alterations in their central metabolism to allow the complete oxidation of glucose.

54. 54 Like proteins, metabolites have direct functional roles in cellular activities. Metabolomics, however, is complicated by the fact that in most cases there is no direct relationship between genes and metabolites, in contrast to the obvious link between mRNA transcripts and proteins. But, the use of metabolomics to show the phenotypes of apparent silent mutations in S. cerevisiae has been demonstrated.

55. 55 10.4.3 Expression of genes from components of a genome Gene transfer is of great interest to the microbial ecologist. Autonomous and mobile genetic elements such as plasmids and phages have genes which help the hosts in certain environments, so can help explain microbial population dynamics. The expression and the induction or repression of environmentally responsive genes on mobile genetic elements can be assessed using the tools of functional genomics.

56. 56 Microorganisms typically have a limited ability to move significant distances within their given environment and hence evade environmental challenges. Environmental changes will produce physiological responses by the microbe that may be controlled by environmental control of gene regulation in the cell. Consequently, investigation of the regulatory mechanisms controlling such physiological responses will contribute substantially to our understanding of microbial ecology.

57. 57 However, the response of pure cultures of bacteria under controlled laboratory conditions to changes in specific environmental parameters may not represent the response of any given organism to the same change in situ. Microbes do not notice individual environmental parameters but respond to the interaction beteen all such parameters, including the effects of other members in mixed microbial communities. Recognize that it is not feasible to conduct comprehensive multifactorial functional genomic studies of microbial responses to all environmental parameters in vitro.

58. 58 10.5 The application of genomic tools in situ Can we study functional genomics in situ?

59. 59 10.5.1 Organism diversity Significant developments in microbial ecology are because of the use of 16S rRNA as a phylogenetic marker. 16S rRNA sequencing has revealed that the diversity of organisms in the natural environment is extensive, with prokaryotes occupying the major portion of the ‘tree of life’. Molecular ecologists are interested in the microbial diversity in an environmental subsample, in terms of the numbers of species, their richness and evenness.

60. 60 Array-based probing technologies are the first genomic tools to be applied to microbial ecology in situ. A group of 16S rDNA probes was directed to key nitrifying genera immobilized in a simple array format. Successful detection of specific groups was demonstrated using reverse hybridization techniques using fluorescently labeled rRNA or in vitro-transcribed targets generated from cloned rDNA. A similar strategy was later used for PCR-amplified rDNA, or in vitro- transcribed rRNA targets, for successful biotin-label- based detection of Geobacter and Desulfovibrio groups. Fragmented rRNA hybridized easier than intact rRNA and a minimum detection limit of 10 6 cells was determined. These data showed that soil extracts spiked into reactions inhibited the efficiency of rRNA hybridization, a major consideration for future environmental studies.

61. 61 More recently, an array system termed the SRP- PhyloChip has been designed and applied to examine all known members of the sulfate-reducing prokaryotes, using 132 16S rRNA targeted 18-mer oligonucleotides. The work represented one of the first comprehensive attempts at array-based 16S analysis in the environment. The chip was tested with DNA samples from a hypersaline microbial mat following PCR-based amplification of 16S rDNA prior to subsequent labeling and array analysis. The chip accurately detected sulfate-reducing organisms in environmental samples that could be subsequently confirmed by array-independent technologies such as PCR amplification, sequencing and gene-specific analyses.

62. 62 Key points for optimization within array formats include the quality of the probe design, the type and quality of nucleic acids that are hybridized with the array (purity and size of the DNA, RNA, or cDNA, and the strength of the fluorescent labels used), and finally the strategies for, and accuracy of, signal quantification. It is important to find the optimal hybridization stringency conditions required for accurate analyses. For arrays, if hybridization is to be effective the probe suite needs to be empirically analyzed under different stringency conditions (e.g. hybridization temperature and salt concentrations) with reference targets of known divergence from the probe sequence.

63. 63 Establishment of hybridization conditions which encompass high stringency for exact match probes but also allow hybridization at moderate divergence (e.g. 20% sequence divergence) will be the most applicable to the analysis of environmental nucleic acids. This is due to the expectation of divergent targets within a given gene family in the environment and the need for this diversity to be accounted for. Specifically, using the dissociation temperature (Td), calculated by melting profiles of the probe is a good basis for assessing hybridization conditions and stringency in multi-probe formats. Perhaps use nested probes of increasing phylogenetic resolution. Including redundant probes to critically examine stringency during hybridizations could be a form of internal standardization.

64. 64 10.5.2 Functional genes Although a knowledge of the organisms present in any given environment is a prerequisite for many applications of microbial ecology, it is also fundamental to establish the function(s) of the constituents of the communities. Microbial functionality regulates the majority of biogeochemical cycles in the biosphere, serves as a reservoir for potential bioprospecting and provides potential solutions through ‘green’ microbial biotechnologies. An understanding of the diversity and amount (gene dosage) of functional genes present and, in the future, the degree to which they are expressed at the mRNA level are central components to the understanding of microbial functionality. To examine the diversity of genes in the environment, two approaches have been taken utilizing genomic technology. The first takes the form of shotgun cloning and sequencing, the so-called ‘metagenomics’ approach. The second approach is clearly an analogue of rRNA analysis in the environment, in that array formats have been used to look at the presence and/or expression of specific pathways.

65. 65 10.5.3 Metagenomics Metagenomics is the application of structural genomics to the environment, where gene libraries are constructed from the shotgun cloning of environmentally recovered DNA followed by sequence analyses. The technique provides a comprehensive way of isolating environmentally relevant genes, and as such is heavily utilized as a tool in the field of novel gene/pathway discovery.

66. 66 However, within an ecological context metagenomics suffers from two pitfalls. First, it may be difficult to assign a taxonomic framework to the genes observed unless a 16S rRNA gene or robust phylogenetic marker is located within a sequenced fragment, or sequencing is restricted to taxonomically identified fragments. Second, the characterization of ‘unknown’ genes is hampered in that a function for any given gene can only be assigned on the basis of similarity to known functional genes. This problem is exacerbated as most of the genomic datasets are from eukaryotes or clinically important bacteria, as opposed to prokaryotes from the environment. Despite these points, several major successes have been afforded by environmental metagenomic approaches.

67. 67 The discovery that heterotrophic processes in the open ocean were contributed to by heterotrophs which contained light-harvesting systems for energy generation (proteorhodopsin) was a direct result of a metagenomics approach. This significant finding was found by sequencing oceanic- derived genomic libraries constructed in bacterial artificial chromosome (‘BAC’) libraries. Later, proteorhodopsin homologues linked with a 16S rRNA gene representative of the SAR86 cluster in oceanic waters were observed. Homologies with the well-described bacterial pigments could be identified and the active nature of the pathway in the environments subsequently demonstrated.

68. 68 Significantly, the metagenomic approach also led to an insight into the ecology of the organisms containing proteorhodopsin, through the elucidation of spectral variants occupying distinct geographical locations. Similar approaches using BAC library technology applied to soil have indicated the potential of metagenomics for accessing genes from uncultured soil organisms, such as the members of the Acidobacterium phyla, and the expression of their metabolites in a recombinant host. Applications of metagenomics are beginning to reveal the gene contents and differences between members of the Crenarcheota, an environmentally important group containing non-thermophilic members with widespread distributions in marine, freshwater and soil habitats.

69. 69 On a larger scale, metagenomics has been employed to describe the genomic content of entire ecosystems. Tyson et al. assembled genome sequences of the dominant prokaryotes (Leptospira and Ferroplasma) together with three other partial genomes using shotgun sequencing of a small insert plasmid library derived from plasmid DNA isolated from an acid mine drainage biofilm. Venter et al. have applied similar methods to study the bacterial community present in surface waters from the Sargasso Sea. The authors generated a phenomenal 1.045 billion base pairs of non- redundant sequence that they assembled into near-complete or partial genome sequences from an estimated 1800 bacterial species. In particular, large sequence scaffolds were generated that showed strong similarities to Burkholderia, Shewanella, SAR86 and Prochlorococcus genomes, but in addition sequences were derived from an estimated 148 novel phylotypes. These ecosystem level datasets, when combined with new projects aiming to generate environmental genomic datasets from both marine and terrestrial ecosystems, represent an outstanding opportunity to expand our knowledge and understanding of the microbial diversity in the natural environment.

70. 70 10.5.4 Functional gene arrays Metagenomic approaches reveal a large number of functional genes of interest in the environment. However, in order to assess the distribution and functioning of these genes, analyses other than the labour-intensive sequencing-based strategies are required, ideal candidates being those of the array technologies. The first attempt at a relatively comprehensive array-based detection of the genes present in environmental samples concentrated on the genes involved in nitrogen and methane cycling. Wu et al. used immobilized probes constructed by PCR amplification of 89 nirS, nirK, amoA and amoP sequences on a glass slide array.

71. 71 Hybridization with labeled targets from cultures and environmental samples provided some interesting insights into gene detection in the environment and, predictably, highlighted some of the pitfalls previously discussed. Under the hybridization conditions employed (65°C), targets with ≥80–85% identity could be efficiently detected (rising to 90% at 75°C). Furthermore, they estimated that target abundances of 1 ng of pure genomic DNA and 25 ng of environmental DNA were required for nirS detection. These levels of detection, in principle, seem hopeful when considering potential applications in ecosystems such as soils and water. In terms of signal quantification, linear signal intensities were observed for pure genomic DNA in the range of 1 to 100 ng, but the signal intensity was found to vary, depending upon the degree of target divergence, as would be theoretically predicted. The authors highlighted that a key requirement for future quantification of both 16S and functional gene arrays is the ability to differentiate signal intensities which arise from variations in target abundance from those that arise simply due to sequence divergence. As suggested, since signal intensity at lower stringencies of hybridization was relatively unaffected by sequence divergence (if <20%; although the effect became more pronounced at higher stringencies), a sequential hybridization strategy could be employed to differentiate abundance/divergence signal variations.

72. 72 Whilst signal intensity criteria are important issues to resolve in environmental applications of arrays, the issue of standardization and sample-to-sample comparison are also key areas for development. Single stringency hybridizations with exact match probes and targets have been employed to demonstrate the use of internal standardization as a tool for more robust quantification in array technologies. Internal array standardization allows multiple samples, with differing target concentrations, to be compared on a rational basis by correcting for uneven array printing and hybridization variation. Moreover, internal standardization affords the ability to quantify mRNA levels in the environment from multiple samples, a criterion currently limited to comparison of two environmental conditions or bacterial strains (e.g. wild type vs. mutant) using current competitive dual-color hybridizations.

73. 73 Despite such challenges, microbial ecologists seem set to embrace array-based methods for investigating gene distribution, diversity and expression. Recent applications of array approaches have included development of small microarrays (68 probes) targeted at methane monooxygenase (pmoA) and ammonia monooyxgenase (amoA) genes for studying methanotrophs in landfills, and a macroarray (40 probes) consisting of PCR-amplified environmental nifH genes used to investigate spatial variability in marine diazotroph communities. Most recently, Rhee et al. reported the development, testing and application of a 1662 probe 50-mer microarray based on genes involved in biodegradation and metal resistance, and used this to show that degradation genes from members of the β-proteobacteria were dominant in napthalene-amended microcosms.

74. 74 10.5.5 Diversity, function and process A primary concern for microbial ecologists is that the tools of genomics are problematic when analyzing organisms of interest in situ amidst a background of non-target microbes (e.g. within a complex soil community). Moreover, it could be said that the analyses tend to lack a context, in terms of directly linking the functional pathways/organisms with environmental processes, e.g. carbon cycling. In this respect we anticipate the development of complementary approaches to relate the genomic analyses of an organism to the process it performs within a mixed community in situ.

75. 75 One way of using genomic technologies in an environmental context is the design and implementation of experimental techniques which can separate out the true signal of a target organism/group in mixed microbial communities from all of the organisms present within the sample. At present, cells or extracted rRNA for standard or genomic analyses can be recovered from environments with reference to a phylogenetic framework by oligonucleotide probe capture. One interesting facet of the rRNA hybridization capture method is the ability to link the phylogenetic analysis with a process the organism may be performing using stable isotope detection within their nucleic acids (e.g. 13C or 15N).

76. 76 Quantification of isotopic signatures within recovered nucleic acids will, in principle, provide a very powerful way to determine the nature and rates of processes and link this with genomic detection strategies. Other applications include pulsing stable-isotope-labeled substrates into communities and recovering ‘heavy’ DNA containing the genomes of the organisms that were involved in processing the substrate, and the recovery of RNA to access rRNA or the transcriptome. More recently, Adamczyk et al. have combined radioactive isotopes of carbon, in the form of 14C- bicarbonate, with a microarray analysis to investigate ammonia-oxidizing bacteria in activated sludge. This elegant work first detected the groups present by microarray hybridization and subsequently measured radioactive incorporation directly on the arrays, to give a combined phylogeny and function analysis.

77. 77 The additional combination of the aforementioned approaches with the future application of isotope-labeled protein strategies such as ICAT (isotope-coded affinity tag) offers enormous potential for investigation of microbial community function at the level of the genome, metagenome, transcriptome and proteome.

78. 78 There are several techniques that do not directly link molecular signatures to biogeochemistry through isotopic tracer studies, but which operationally define subgroups with microbial communities. Such methods include fluorescent in situ hybridization and/or activity measures coupled to flow cytometric cell sorting for the recovery of specific bacterial populations. We predict that these tools will become a central form of sample collection for in situ studies prior to genomic applications in the coming years. Techniques that allow directed genomic analyses will target the community in an effective way, could link genomics to microbially driven processes and substantially increase the success of genomic analyses in situ.

79. 79 10.6 Lessons learned and future perspectives The discipline of microbial ecology is firmly rooted in understanding the ecology of microbes in the ‘real world’. This encompasses microbial evolution, adaptation, community structure and function, together with their effects upon biogeochemical cycles at scales which span millimeters, kilometers, continents and oceans. Genomics is a tool which aids us in this endeavor. As we have stated in the preceding sections, certain obstacles need to be overcome prior to the widespread use of genomics in microbial ecology. These obstacles are by no means insurmountable, and we would formalize these as five ‘lessons’ learned for future consideration.

80. 80 (i) Progress will be directly proportional to database size. The current size of databases with fully annotated genomes and functional analyses for environmental organisms limits genomic application for microbial ecologists. A key requirement is the analysis of multiple representatives of the key environmental groups or lineages thus far identified. Specific tasks involved with this are: assessing culture requirements, isolation of pure cultures, directed sequencing programs and effective functional analyses (both in silico and biochemically) of these isolates.

81. 81 (ii) The horizontal gene pool. The importance of the HGP to the evolution of environmental microbes and their pathways cannot be understated. As such, intensive sequencing/functional analyses for mediators of the HGP (plasmids, transposons etc.) should be undertaken for a range of habitats and processes, and their results given equal significance to those placed upon chromosomal sequences.

82. 82 (iii) Ex situ vs. in situ. Genomic ex situ studies using cultured isolates can be used to determine underlying principles of bacterial survival/adaptation/functionality in the environment. However, in order to extrapolate ex situ experiments to observations made in situ, great care must be required for the ex situ experimental design and execution. For example, microbes continuously experience multiple stresses and significant variation in both the type and concentrations of nutrient sources. Microbes rarely, if ever, exist in a ‘batch’ culture scenario with optimal growth conditions. Experimental manipulations using genomic analyses should reflect the continuous and multifactoral lifestyle that microbes experience

83. 83 (iv) Signals and noise. The successful application of genomic approaches in situ requires the development of methods that provide significant resolution of signal against noise. An example would be the requirements for the detection of the 16S rRNA genes of a specific species against a background of large numbers of co-habiting organisms. A large amount of research on standardization and calibration is still required prior to the widespread application of genomic technologies in environmental samples.

84. 84 (v) Genomics and biogeochemistry. An important role of genomics in microbial ecology will be to relate features of microbial communities detectable by genomic strategies to environmental processes. As an example, the determination of abundances of methane oxidizers and their functional transcripts should be related to methane oxidation rates. The absence of a link between environmental process measurements and genomic detection of organism and transcript abundances will ultimately lead to an increase in information at the expense of ecological understanding.