Microorganisms occupy a peculiar place in the human view of life. They are almost unknown to the public except in the context of disease or food production. This is due to the fact that microbes are very small. Consequently, even many biologists consider microorganisms to be only a minor component of the global biomass. In reality, microbial communities represent more than half the biomass on Earth. Plant material accounts for most of the remainder, whereas animals do not contribute significantly (Whitman et al., 1998). Microbial life is present not only in our familiar world, i.e. air, soil, and lakes, but also the depths of the ocean and very deep in the crust of the Earth. Because of the large numbers of microorganisms and their metabolic capabilities, they play a crucial function in the planet's biochemical processes such as the decomposition of organic matter in soil and water, provision of atmospheric components, nitrogen fixation, and photosynthesis. It can be stated that the functioning of the whole biosphere depends absolutely on the activities of the microbial world (Madigan et al., 2003). This is not surprising if we consider how much older microbes are than all other forms of life on our planet (Fig. 1) .
The clear deduction from the limited fossil record is that cell-based life arose comparatively quickly after the planet formed 4.5x109 of years ago, and for two-thirds of the time since then, it was limited to prokaryotic-like life. Indeed, it was the impact and evolution of prokaryotic life that provided a suitable environment for the subsequent evolution of animal and plant species. For example, in geochemical terms, the formation of an oxygenated atmosphere suitable for the evolution of many eukaryotic species was primarily due to bacterial photosynthesis. In biological terms, bacteria provided the chloroplast and mitochondrial organelles found in many current eukaryotic cells through endosymbiotic events (Margulis, 1993).
Our understanding of the importance of microbes coexists with a limited knowledge of what the majority of microorganisms are actually doing in nature. A gram of soil, for example, contains millions of microorganisms and still only around 1% (at most) of them are identifiable (Torsvik et al., 1990). Microbes are individually invisible to the naked eye and even under the microscope, the morphologies of most microbe’s are usually nondescript rods or spheres. It is therefore difficult to determine the relatedness of different microorganisms on the basis of morphology in the same way as that performed for large organisms. A special scientific discipline termed "microbiology" was developed in order to study microorganisms in their environment.
Louis Pasteur (1822-1895), a French chemist, played a significant role in the development of microbiology with his experiments disproving the theory of spontaneous generation. This theory, which became popular during the 18th century, proposed that spoilage organisms arose spontaneously in putrefied food. Pasteur captured airborne microorganisms on guncotton filters to show that these airborne microbes were responsible for food spoilage and did not arise spontaneously.
In 1876 a German country physician named Robert Koch (1843-1910) discovered that the lethal, contagious cattle disease anthrax could be transmitted from animal to animal by injecting blood from an infected cow into a healthy cow. His experiments were formulated into a set of criteria, known as Koch’s postulates, that have become the cornerstone for associating specific microorganisms with specific infectious diseases. Koch’s postulates initiated an era known as the Golden Age of Microbiology (1876-1906), during which the causes of many microbial diseases were discovered.
In the early part of 20th century Winogradsky and Beijerinck developed enrichment culture techniques so that microbes could be studied as individual types, and described and classified by their phenotype. Phenotype is a broad term which encompasses the observable characteristics of a cell such as morphology, physiological activities (e.g. nutrient utilization), cell-wall structure (e.g. types of lipids) and sometimes the ecological niche the cell occupies. Unfortunately,
such characteristics provide little information about the evolutionary relatedness of microorganisms, and
many microbes are difficult to cultivate.
Naturalists have always tried to build a meaningful classification scheme for living things. Long before Darwin, plants and animals were believed to be the primary divisions of life. In 1866, Haeckel was the first to challenge this dichotomy by suggesting that the Protista should be considered a third kingdom, equal in stature to the Plantae and Animalia. The Bacteria or Monera were designated as the fourth kingdom by Copeland, in 1938. Whittaker added the fungi in 1959, and his five kingdom classification (Plantae, Animalia, Protista, Fungi and Monera) is still taught as part of basic biology curricula.
Over 50 years ago, Chatton, Stanier and van Niel suggested that life could be subdivided into two more fundamental cellular categories, prokaryotes and eukaryotes. The distinction between the two groups was subsequently refined through studies of cellular biology and genetics whereby prokaryotes became universally distinguishable from eukaryotes on the basis of lacking internal membranes (such as the nuclear membrane and endoplasmic recticulum), dividing by binary fission rather than mitosis, and the presence of a cell wall. The definition of eukaryotes was broadened to include Margulis’ endosymbiont hypothesis, which describes how eukaryotes improved their metabolic capacity by engulfing certain prokaryotes which were converted into intracellular organelles, principally mitochondria and chloroplasts.
In the late 1970s the fundamental belief in the prokaryote-eukaryote dichotomy was rejected by the work of Carl Woese and George Fox. By digesting in vivo labeled 16S rRNA using T1 ribonuclease, and accumulating and comparing catalogues of the resultant oligonucleotide “words”, Woese and Fox were able to derive dendrograms showing the relationships between different bacterial species. Analyses involving some unusual methanogenic “bacteria” revealed surprising and unique species clusterings among prokaryotes. The split in the prokaryotes was so deep that in 1977, Woese and Fox proposed that the methanogens and their relatives be termed the “archaebacteria”, a name which reflected their distinctness from the true bacteria or “eubacteria”, and also reflected contemporary preconceptions that these organisms might have thrived in the environmental conditions of a younger Earth (Brown, 1999).
The introduction of modern molecular tools which allowed the study of microbes without prior cultivation dramatically changed our perception of phylogeny and the diversity of life.
In 1990, Woese, Kandler and Wheelies (Woese et al., 1990) proposed the replacement of the bipartite view of life with a new tripartite scheme based on three urkingdoms or domains; the Bacteria (formerly eubacteria), Archaea (formerly archaebacteria) and Eucarya (formerly eukaryotes although this term is still more often used) (Fig. 2). The rationale behind this revision came from a growing body of biochemical, genomic and phylogenetic evidence which, when viewed collectively, suggested that the archaebacteria were worthy of a taxonomic status equal to that of eukaryotes and eubacteria.
At the centre of the controversy surrounding the concept of the three domains are the Archaea and their degree of uniqueness from the Bacteria. Although discovered much more recently than either the Bacteria or Eucarya, the biochemistry, genetics and evolutionary relationships of the Archaea have been intensively studied. In addition, complete genomic DNA sequences have been obtained for several archaeal species.
Archaea and Bacteria are both groups of prokaryotes, but are phylogenetically distinct from each other. There is evidence to suggest that Archaea and Eucarya are more closely related to each other than either are to Bacteria; the origin of life appears to be on the bacterial line of descent (Fig. 2). Many phenotypic properties of Archaea and Bacteria are consistent with this phylogenetic assessment (Woese, 1987). Archaeal and bacterial metabolic genes share common evolutionary aspects (Brown and Doolittle, 1997). However, transcription and translation machinery in Archaea and Eucarya have common features, distinct from those of Bacteria (Olsen and Woese, 1997). This will be discussed in section 1.3.1 of this thesis.
Novel molecular techniques (Pace et al., 1985; Giovannoni et al., 1988; Amann et al., 1992; Torsvik et al., 1998) have offered new ways of studying microorganisms in diverse environments "in situ". By analyzing relevant genes obtained directly from environmental samples, microorganisms from a particular habitat can be identified (to some extent), characterized and counted. Since 1987, the use of these innovative approaches has resulted in the number of recognized bacterial phyla increasing from the original estimate of 11(Woese, 1987) to 36 (Hugenholtz et al., 1998), more than one-third of which contain no cultured representatives.
One of the most remarkable findings to emerge from the application of new molecular approaches was the unexpected discovery of high numbers of novel "non-extreme" archaeal phenotypes in open ocean waters (Fuhrman et al., 1992; Delong, 1992; Fuhrman and Ouverney, 1998), the largest of all biotopes on our planet. Until this finding, Archaea were considered to be restricted to specialized environments including those at high temperature, high salinity, extremes of pH, or strict anoxic. After many studies over several years researchers have demonstrated the presence of "non-extreme" Archaea in a wide variety of temperate and cold environments including soils, marine and lake sediments, marine and freshwater picoplankton, etc., that is to say, virtually everywhere. These discoveries mark the beginning of a new era for investigating Archaea and, in particular, their physiological properties and biological roles in complex microbial populations.
In this thesis results on the phylogenetic diversity of Archaea in boreal forest soil (papers I and II), temperate estuarine sediment (paper III) and boreal freshwater lake (paper IV), obtained using molecular methods, will be reported.
There is no consistent way to classify and relate microorganisms, both prokaryotes and eukaryotes, other than the use of modern methods of molecular phylogenetic analysis. The use of macromolecular sequence comparisons to define phylogenetic relationships is now well established (Zuckerkandl and Pauling, 1965). Protein sequences were most often used for phylogenetic determinations in the past as techniques for studying nucleic acid sequences were not available. Studies comparing cytochrome c, ribonucleases, globins, etc., have been rewarding, although they have proven most useful with higher eukaryotes (Goodman, 1982). Among microbes, phylogenetic and biochemical diversity is such that even the identification of homologous proteins is not a straightforward task. Because they are required by all cells for protein synthesis, the nucleic acid elements of the translation apparatus - the protein-synthesizing machinery - seem best suited for broad phylogenetic analysis. The translation of mRNAs into proteins using ribosomes and the tRNAs is an ancient mechanism. The similar architecture of the ribosomes and tRNAs in the three primary kingdoms - Archaea, Bacteria and Eucarya - means that the translation apparatus emerged largely in its modern form before the phylogenetic radiation of the three kingdoms. Thus, phylogenetic analysis of the components of the translation apparatus allow, in principle, the relationships among organisms to be traced nearly to the time of the origin of life on the earth.
However, tRNAs are not very useful for phylogenetic characterizations because they are too constrained in structure. The tRNA structure is tightly locked up in a complex tertiary organization. Almost every residue in a tRNA molecule has contact with at least one other residue, and the tight interlocking of the molecule imposes conformational constraints on all residues. Another major problem is the limited number of mutable residues in homologous tRNAs. The small number of changes in compared molecules means that the statistical error in a calculated evolutionary distance is great.
We are therefore left with rRNAs as the most useful tools for phylogenetic explorations. There are several explicit reasons for focusing on the ribosomal RNAs:
the rRNAs, as key elements of the protein-synthesizing machinery, are of profound importance to all organisms.
the rRNAs are ancient molecules and extremely conserved in overall structure. Thus, homologous forms of rRNA are readily identified by their sizes alone.
the conserved nature of rRNA structure extends to the nucleotide sequence level. Some segments of rRNA sequences do not vary among the biological kingdoms (domains), whereas others vary to greater or lesser extents (Gutell et al., 1994; van de Peer Y. et al., 1996). The conserved sequences and secondary structure allow disparate sequences to be aligned, so that only homologous sequences are used in phylogenetic analysis. The highly conserved regions also provide convenient hybridization targets for cloning rRNA genes and sequencing techniques.
in general, rRNAs are essential and conserved across all phylogenetic domains, thus "universal" tracts of sequences can be identified (Olsen et al., 1986). In addition, it is possible to identify sequence motifs of increasing phylogenetic resolution and recognize "signature" sequences for the domains Archaea, Bacteria, and Eucarya and their subdivisions (Giovannoni et al., 1988; Woese, 1987).
rRNA constitutes a significant component of cellular mass, and is generally recovered easily from all types of organisms.
rRNA sequences are sufficiently long to provide statistically significant comparisons.
rRNA genes seem to be free from artifacts of lateral transfer between phylogenetically distant organisms. Thus, relationships established by rRNA sequence comparisons represent true evolutionary relationships (Stackebrandt and Woese, 1981).
Taken together, these features indicate that rRNAs may be uniquely suitable for establishing phylogenetic relationships among very different organisms.
Of the three ribosomal RNAs (5S, 16S/18S and 23S/28S), the 5S is too small (~120 nucleotides) to be used indiscriminately for phylogenetic inferences. One might expect that the 23S/28S rRNA (23S rRNA in most prokaryotes, containing approximately 2900 nucleotides) would provide about twice the phylogenetic information compared with the 16S/18S rRNA (16S rRNA, containing approximately 1500 nucleotides). This is true within limits - the average rate of sequence change (as reflected in frequency of differences between corresponding sequences from a pair of organisms) of 23S rRNA is significantly faster than that of 16S rRNA. Thus, for close relationships, the larger molecule can be quite valuable although it has not proved to be as proportionately useful in the deepest branches of the tree (Olsen and Woese, 1993). Generally, when both sequences are available for a set of organisms, the phylogenies inferred by each rRNA tend to be similar (Ludwig et al., 1995). As 16S and 23S rRNAs are not functionally independent, it is not surprising that they give congruent pictures. We should also take into account the fact that the number of currently available complete 23S rRNA sequences in the databases is rather poor in comparison to the number of 16S rRNA sequences.
Therefore, SSU rRNA has served as the “gold standard” in elucidating bacterial phylogeny in recent years, and the new edition of both Bergey’s Manual of Systematic Bacteriology (Garrity, 2001, second edition) and "Brock Biology of Microorganisms"(Madigan et al., 2003, tenth edition) base their respective phylogenetic relationships among microorganisms upon the SSU rRNA tree.
Figure 3 is a current phylogenetic tree based on small-subunit (SSU, 16S/18S) rRNA sequences of the organisms represented. The constructionof such a tree is theoretically simple (Swofford et al., 1996). Firstly, rRNA sequences from different organisms are aligned. Pairwise comparisons are then made between all the sequences and the differences counted are considered to be some measure of the "evolutionary distance"between the organisms.
There is no consideration given to the passageof time but only changes in nucleotide sequence. Pairwise comparisons of different sequences between many organisms can then be used to infer phylogenetictrees, maps that represent the evolutionary paths leading to themodern-day sequences. The tree in Figure 3 is largely congruentwith trees made using any molecule involved in the nucleic acid-based,information-processing system of cells (Pace, 1997). Conversely, phylogenetictrees based on metabolic genes involved in the manipulationof small molecules and in interaction with the environment, commonlydo not agree with the rRNA-based version (Doolittle and Brown, 1994; Palmer, 1997). Differences in the phylogenetic trees made with differentmolecules may reflect lateral transfers or even the intermixingof genomes during the course of evolution. Some metabolic archaealgenes, for instance, appear much more related to specificbacterial versions than to their eukaryal homologs. Other archaealgenes seem decidedly eukaryotic in nature; still other archaealgenes are unique. Nonetheless, the so far determined sequencesof the archaeons Methanococcus jannaschii (Bult et al., 1996), Methanobacterium thermoautotrophicum (Smith et al., 1997), Archaeoglobus fulgidus(Klenk et al., 1997), Pyrococcus horikoshii(Kawarabayasi et al., 1998), Aeropyrum pernix (Kawarabayasi et al., 1999), Halobacterium sp. (Ng et al., 2000), Thermoplasma acidophilum (Ruepp et al., 2000), Thermoplasma volcanium (Kawashima, 2000) and Sulfolobus solfataricus (She et al., 2001) show that the evolutionarylineage of Archaea is independent of both Eucarya and Bacteria.
"Evolutionary distance" in this type of phylogenetic tree, the extent of sequence change, is read along line segments.The tree can be considered a rough map of the evolution of the genetic core of the cellular lineages that led to the modern organisms(sequences) included in the tree. The time of occurrence of evolutionaryevents cannot be extracted reliably from phylogenetic trees, despitecommon attempts to do so. Time cannot be accurately correlated with sequence change because the evolutionary clock is not constant in different lineages (Woese, 1987). This inconsistency is shown in Figure 3 by the fact that lines leading to the different reference organismsare not all of the same length as these different lineages have experiencedsequence changes to different extents. Nonetheless, the order ofoccurrence of branching in the trees can be interpreted as a genealogy, and intriguing insights into the evolution of cellsare emerging.
Molecular ecology has two general approaches: identification of the species present in an environment, and analysis of their populations in that environment. In the first case, organisms in an environment are “surveyed” using methods similar to analysis of cultivated species. This approach starts with an environmental sample and ends with sequence and phylogenetic data. In the second approach, organisms are studied in terms of their physical arrangement in the microenvironment using rRNA sequences to determine numbers and population dynamics, and distinguish one species or phylogenetic group from the rest. This approach starts with sequence and phylogenetic information and ends with environmental data - the reverse of the previous case. Some of the ways this approach can be used are:
identification of the predominant microbial groups in a consortium by counting sequences obtained from various phylogenetic groups to assess their abundance in the ecosystem
use of fluorescently-labeled rRNA sequences (oligonucleotides) as probes for the identification or enumeration of specific organisms or groups in environmental samples by whole-cell hybridization
assessment of enrichments aimed at cultivating organisms previously identified by their rRNA sequences
The characterization of an organism in terms of its phylotype requires only a gene sequence, not a functioning cell. Genes can be obtained by cloning nucleic acids, which can be isolated directly from the environment using standard techniques. Phylogenetic analysis of rRNA genes from the environment provides a survey of the phylotypes present. The retrieved sequence information can then be used to gain further information about, or even retrieve, an organism of particular interest (Head et al., 1998). Figure 4 outlines ”full-cycle” rRNA approach - methods and tools used in the molecular analysis of microbial ecosystems. These techniques avoid the need to cultivate organisms in order to identify them (Pace et al., 1986; Amann et al., 1995). Several specialized methods are available for the extraction and purification of nucleic acids from a wide range of environmental samples, including soil, water, tissue and even rocks. Methods are usually based on chemical and/or physical disruption of cells, combined with treatments to remove contaminating materials, such as humic acids and metals, that "poison" enzymatic steps. A number of strategies can be used to obtain rRNA gene clones from "total community" nucleic acids (Fig. 4).
Community DNA can be size-fractionated and shotgun-cloned into bacteriophage lambda (or into bacterial artificial chromosome (BAC) vectors which are able to "hold" larger size fragments), and then screened for the presence of rRNA genes. This is laborious procedure, as rRNA genes will only constitute a small fraction of the total clones. A big advantage of such libraries is that they are also sources of genes other than those encoding for rRNA.
The simplest way to obtain phylotypes from the environment is through the use of the polymerase chain reaction (PCR) (Saiki et al., 1988). rRNA genes can be PCR-amplified directly from community DNA using rRNA-specific primers, and then cloned by standard methods. The resulting "snapshot" of community diversity will depend upon the specificity of the PCR primers and the efficiency with which the rRNA genes are amplified. Taking advantage of the conserved nature of rRNA, "universal" primers which are capable of annealing to rRNA genes from all three phylogenetic domains have been designed. Specific phylogenetic groups of interest in a total community can also be characterized using group-specific primers for rRNA. Although the analysis of a microbial community by PCR and cloning provides a convenient and rapid alternative to shortgun cloning, selective amplification of rRNA genes may bias diversity estimates (Head et al., 1998).
The third alternative for obtaining rRNA gene clones from extracted nucleic acids is to use reverse transcriptase and universal or group-specific primers to make single-stranded DNA that is complementary to rRNA, and then to use PCR to make duplex ribosomal DNA for cloning (RT-PCR). The resulting community profile will offer some reflection of the most metabolically active organisms, because cells that produce more RNA (i.e. those that are metabolically more active) will be represented to a greater extent in the clone library than metabolically inactive cells.
A complete survey of phylotypes in a particular rRNA gene library would require sequence analysis of all unique clones in the library. Natural microbial communities are highly complex, so several hundreds or thousands of individual clones would require sequencing. Dot- or colony-blotting using specific probes can be useful to sort clones and to identify specific targets for sequencing or other analyses. Screening clones in a library can also be facilitated by restriction fragment length polymorphism (RFLP) and single-nucleotide sequencing. Non-sequencing methods are also available which allows a microbial community to be monitored over space and time without cloning. Denaturing gradient gel electrophoresis (DGGE) (Muyzer et al., 1993; Øvreås et al., 1997), for example, separates different rRNA genes on the basis of their G+C content, and RFLP analysis of community rRNA genes produces rRNA gene fragments that may be specific for different community members. These methods are most informative when used in conjunction with sequence information, allowing individual community members to be qualitatively tracked in environmental samples.
A joint approach with cloning for the characterization of microbes in the environment is the use of nucleic acid probes - oligonucleotides complementary to rRNA or rRNA gene targets (Amann et al., 1992). Qualitative and quantitative estimates of community structure can be made using oligonucleotide hybridization probes (Fig. 4). Hierarchal probes can be custom-made that target broadly (e.g. at the domain level) or more specifically (e.g. at the strain level). These probes can be visualized directly in the environmental samples using fluorescently labeled oligonucleotide probes and epifluorescence microscopy to establish morphotype and cell numbers (Glöckner et al., 1996). Fluorescently labeled probes can also be combined with confocal scanning laser microscopy to describe spatial arrangements of cells, such as in biofilms and flocks.
Oligonucleotide probes and PCR primers are excellent tools for describing natural communities, but they rely on sequence data for their design. The more data that exist for a particular environment, the more accurate the designed probes and primers will be. At the same time, after adding new data to the database, old probes and primers may not be specific for the new sequences.
The most commonly used form of comparative rRNA gene sequence analysis involves the construction of phylogenetic trees. There are a number of procedures used to achieve this, but the first stage in these analyses is always the careful alignment of the rRNA sequences. This is a relatively straightforward task for regions that have a highly conserved sequence. However, it is considerably more problematic in regions of greater sequence variability. Comparison with the secondary structure model of rRNA can often resolve these difficulties. The importance of careful alignment cannot be overstated. In any phylogenetic analysis, we must compare like with like if we are to be confident that a nucleotide substitution at any particular position in the sequence is, in fact, the result of an evolutionary event. Regions of sequences that cannot be unambiguously aligned are normally not included in phylogenetic analyses.
Once the rRNA sequences have been aligned, taking into account secondary structure interactions, phylogenetic analyses can be undertaken. Three widely used approaches for inferring phylogenetic trees are pairwise distance, parsimony, and maximum likelihood analysis (Swofford et al., 1996). Distance methods perform a modified cluster analysis of matrix of binary distance values. In contrast, the maximum parsimony and maximum likelihood procedures are used for analyzing primary sequence data. These procedures do not only compute the number of changes, but also take into account the character of those changes.
The distance methods (Fitch and Margoliash, 1967) are conceptually most simple. Pairwise comparisons of a set of aligned sequences are used to construct a distance matrix. The distances calculated are generally not simple binary similarities, but include a model of base substitution to account for multiple substitutions at a single site, for example, the Jukes and Cantor model (Jukes and Cantor, 1969). The distance matrix can then be converted into a phylogenetic tree by grouping the most closely related pairs of sequences.
Maximum parsimony procedures search for tree topologies which require a minimum number of base changes to correlate with the sequence data. The maximum likelihood procedure is considered the most sophisticated method for developing a phylogenetic tree (Felsenstein, 1981). It also searches tree topologies in ways that reflect how current sequences were most likely to have been generated, according to the criteria specified by whichever model is being applied. Not surprisingly, applying different treeing methods upon the same data often results in locally different tree topologies.
All these methods may assign organisms incorrectly to positions along a phylogenetic tree as a result of "false identity" in sequence positions. However, the extent of this problem varies from one method to another. Identical residues at particular alignment positions are typically treated as evolutionarily identical. This practice holds also for plesiomorphies which may have resulted from multiple base changes during the course of evolution. Depending on the number of "false'' identities in a sequence data set, misleading branch attractions may occur in a particular tree, which are difficult to detect as such. Branch attraction as a result of "false identities" may also prevent a stable positioning of long "naked'' branches represented by only one or a few sequences.
Because of such difficulties, the topology of every tree needs to be carefully evaluated. Maximum likelihood and, to a lesser extent, maximum parsimony methods handle these assignment problems more efficiently than distance methods. Therefore, different methods should be applied to estimate the robustness of any tree's topology. The use of filters that remove, include, or give weight to particular sequence positions according to overall or positional variability also helps to detect and reduce the impact of "false identities" on tree topologies (Ludwig and Schleifer, 1999). The choice of tree-building method is somewhat arbitrary and often depends on time requirements, or the philosophical predisposition of the researcher. This is due to two reasons. Firstly, no method is uniformly better in reconstructing the true tree when the sequence length is small and secondly, all methods tend to perform well given enough data (Nei and Kumar, 2000).
The next step in constructing a sequence phylogeny is to assess the reliability of the inferred branching pattern. This is often accomplished by a bootstrap analysis (Felsenstein, 1985). Bootstrap procedures involve construction of new sequence sets by resampling with replacement sites (columns) of the original set, building a tree for each new set, and calculating the percentage of times a cluster reappears in the bootstrap replications. This percentage is called the bootstrap value and clusters with a bootstrap value >95% are widely considered to reflect correct relationships, although some authors have suggested that 70% may be a more realistic cutoff point.
While we have undoubtedly gained much new and valuable knowledge using the techniques described, as with all methods, there are important limitations that must be minimized, eradicated, or, at the very least, recognized. The limitations relate to the extraction of nucleic acids from natural samples, biases, and artifacts associated with enzymatic amplification of the nucleic acids, cloning of PCR products, and sensitivity and target site accessibility in whole-cell hybridization techniques (Head et al., 1998).
A major limitation of all the methods described, with the exception of whole-cell hybridization techniques, is the quantitative recovery of nucleic acids from environmental samples. There is always the philosophical argument that if you do not know the total amount of nucleic acids present in a sample, then it is difficult to assess the efficiency of recovery by any extraction technique. This is compounded by the fact that Gram-positive cells are more resistant to cell lysis than Gram-negative cells. While this is irrefutable, a reasonable indication of the efficiency of cell lysis in an environmental sample can be obtained by microscopic enumeration of the cells in a sample before and after lysis treatments. There are many published methods for extracting DNA from natural samples (Fuhrman et al., 1988; Tsai and Olson, 1991) but there have been few systematic studies that have addressed this issue. It is possible that the same lysis technique may give different results with different types of sample such as water, sediment, or soil, and the degree of cell lysis should be determined independently. It has been demonstrated that a combination of physical and chemical treatments, such as freezing and thawing, lysis with detergents, and bead beating can lyse approximately 96% of cells in soil and also lyse bacterial endospores with high efficiency (More et al., 1994). It was noted however, that smaller cells (0.3-1.2 µm) were more resistant to lysis. This clearly has implications for the recovery of sequences from environmental samples where many cells may be in a state of starvation and, hence are likely to be small. Other workers have found, however, that, even without harsh physical treatments such as bead beating, up to 99.8% lysis can be obtained (Rochelle et al., 1992), although this did require long incubations with lysozyme and up to six freeze-thaw cycles.
Selectivity in PCR amplification of rRNA genes is another source of bias that can affect the results of molecular measures of diversity. Small differences in the sequence of universally conserved regions may result in selective amplification of some sequences, particularly when primer annealing is at high stringency. The frequency of different sequence types in PCR-derived rRNA gene clone libraries has sometimes been assumed to accurately represent the relative abundance of different components of a microbial community. This cannot be claimed with any confidence, as the copy number of rRNA genes present within the genomes of different organisms can range from 1 to 14 (Cole and Saint, I, 1994). Thus, assuming unbiased amplification, a mixture of equal cell numbers of Bacillus subtilis (10 rRNA operons) and Thermus thermophilus (2 rRNA operons) would produce a library that indicated a 5 to 1 greater number of B. subtilis in the original mixture. In this example, the copy number of the genes in each genome and the size of the genome of both bacteria are known, and this can be accounted for in our estimation of species abundance. In natural samples, we have no such information about the constituent microbial types. There is also concern that more abundant sequences are preferentially amplified, and low-abundance sequences are discriminated against (Ward et al., 1992). It has been further suggested that high percent G+C templates are discriminated against due to lower efficiency of strand separation during the denaturation step of the PCR reaction (Reysenbach et al., 1992). PCR amplification using artificial mixes of genomic DNA from organisms with different genome sizes and numbers of rRNA operons has demonstrated that, in general, the ratio of rRNA genes in the PCR product mix do, in fact, reflect the ratio in the starting mixture of DNA (Farrelly et al., 1995). However, when rRNA operons are clustered together rather than evenly distributed throughout a genome, the clustered genes dominate in PCR products (Farrelly et al., 1995). The implication of these results is that we can never confidently extrapolate sequence composition of a clone library to a quantitative population composition of an environmental sample.
The formation of chimeric PCR products has also been observed where fragments from two different sequences become fused during the amplification process (Liesack et al., 1991). One study demonstrated that up to 30% of the products generated during coamplification of similar templates were chimeric (Wang and Wang, 1996). The experimental conditions used may well have promoted chimera formation to some extent. Nonetheless, the results demonstrated the considerable potential for chimera formation during PCR amplification.
A number of computer programs have been developed to help identify chimeric sequences (Kopczynski et al., 1994), but these have difficulty in identifying chimeras when the two sequences from which the chimera is formed show greater than 85% homology. The programs may also indicate the presence of chimeric sequences even when none exist (Kopczynski et al., 1994). These programs are best used as a guide to the presence of chimeric sequences. The authenticity of a sequence should be confirmed by independent sequence analyses, using the putative chimeric fragments. Discrepancies in secondary structure can also aid in the identification of genuine chimeric molecules.
While the complex problems of enumeration associated with quantitative analyses involving PCR do not hold for whole cell hybridization, a number of other methodological constraints do exist. These can be divided into four main categories: cell permeability problems, target site accessibility, target site specificity and sensitivity.
The first obstacle that must be overcome for successful in situ whole-cell hybridization is entry of the probe into the cell. This is normally achieved by fixation with denaturants such as alcohols, or cross-linking reagents such as formaldehyde or paraformaldehyde. These fixation procedures not only aid in cell permeability, but also help maintain the cells morphological integrity during hybridization.
Even when cell permeabilization has been achieved, there is no guarantee that probe hybridization to rRNA will occur within the cell. This is believed to be the result of the target sequence in the rRNA being inaccessible due to strong interactions with ribosomal proteins or highly stable secondary structure elements of the rRNA itself. This problem can normally be detected by a strong hybridization signal being obtained with a universal probe that is known to target an accessible site on the rRNA molecule. If another probe does not give a hybridization signal in the same cell(s), this generally indicates poor accessibility of the target site (Amann et al., 1995).
The sensitivity of in situ hybridization is also an issue. In general, probes containing a single labeled molecule give a strong signal only if cells are metabolically active and, hence, contain large numbers of ribosomes and target rRNA (Hahn et al., 1992; Manz et al., 1993). A number of approaches have been used to improve sensitivity by using multiple singly labeled probes (Amann et al., 1990; Lee et al., 1993), multiple labeled probes (Wallner et al., 1993), and enzyme-linked probes or detection systems (Zarda et al., 1991; Amann et al., 1992) that allow signal amplification. In addition, the development of highly sensitive cameras has improved the sensitivity of in situ hybridization assays.
As more rRNA sequences become available in sequence databases, the problem of probe specificity has been highlighted, and the design of diagnostic probes is becoming more difficult. While this problem has always existed, it is only with the rapidly expanding database of sequences that the problem has become more apparent. These problems are not exclusive to whole-cell hybridization but are equally relevant to PCR and other oligonucleotide-dependent techniques. It has been stated that for an 18mer probe targeting a variable region of an rRNA molecule, there is a 1:418 chance of an unrelated target cell being detected. However, because there may be only a few positions that vary between taxa even in variable regions, the probability of detecting an unrelated cell is increased considerably (1:45, if only 5 positions are variable). It has been suggested that this problem can be overcome by using multiple specific oligonucleotide probes that target different sites on the rRNA molecule and are labeled with different fluorochromes (Amann, 1995). An elegant solution which takes advantage of additive color mixing is the use of differently labeled probes. This method has been demonstrated to work well and considerably reduces the detection of false positives (Amann, 1995).
Analogous to this approach is the use of specific PCR primers and confirmation of the identity of the amplified sequence(s) by the use of a specific oligonucleotide probe. While a single oligonucleotide target sequence may be found in a number of related taxa, the probability that target sites for three specifically designed oligonucleotides are found in a non-target organism is much reduced.
Due to the limitations of traditional culture-dependent methods the use of molecular techniques has become of growing importance for the study of microbial communities in various ecosystems. Above all, the rRNA approach has been successfully applied to reveal the existence of several novel lineages of hitherto unknown prokaryotes leading to a broadening of our view on microbial diversity. It must be stressed, however, that cultivation-independent, PCR-based methods can also have inherent biases preventing a reliable assessment of the structure of bacterial populations which may lead to a misinterpretation of the abundance of certain phylogenetic groups. Such pitfalls may be avoided by hybridizing whole cells or extracted rRNA from the studied habitat with specific oligonucleotide probes in order to verify the initial results. Furthermore, the retrieval of a novel 16S rRNA sequence reveals very little about the phenotypic traits of the respective organism and its metabolic activity. It is only when the retrieved sequence can be clearly affiliated to a monophyletic lineage which is characterized by a common phenotypic trait that some conclusions may be drawn about the function of the corresponding microorganism. In most cases, however, the simple knowledge of the phylogenetic diversity in an environment is not very helpful in understanding the interacting metabolic processes and factors which control them. Nevertheless, a molecular approach can help in the identification of microorganisms which are ecologically relevant because of their abundance or activity. These microorganisms can then be the subject of detailed studies or a target of directed cultivation experiments.
The majority of prokaryotes living in natural environments are rather inconspicuous. Therefore, several molecular techniques were developed in order to overcome the lack of information about the function of bacteria identified by cultivation-independent methods. Despite the progress which has been made in linking the identification of distinct microorganisms with their functions in situ, it may still be necessary to isolate or enrich novel bacteria to reveal their metabolic potential under various environmental conditions.
The results of molecular ecology research has established that experimental strategies based on the combination of molecular techniques with traditional cultivation-dependent methods have great potential in revealing some of the hidden complexity of natural microbial ecosystems.
In order to study and be able to predict properties of the uncultivated Archaea, one must be familiar with the main features, properties and ecology of this kingdom's known cultivated members (Huber and Stetter, 1999a; Huber and Stetter, 1999b; Madigan et al., 2003).
Microbiologists have perceived Archaea as exotic, highly atypical microorganisms. Prior to their recognition as a phylogenetically coherent group (Woese and Fox, 1977) however, their individual idiosyncrasies were interpreted simply as adaptations: the lipids of Thermoplasma were unusual because the organism evolved to live at high temperatures or in highly acidic environments or both (Brock, 1978); the wall of Halococcus was an adaptation to an extremely saline environment (Larsen, 1973); the uniqueness of their coenzymes merely reflected the capacity of methanogens to produce methane from carbon dioxide (Zeikus, 1977). The fact that different Archaea had the same unusual lipids was even interpreted as convergent adaptation (Brock, 1978).
The Archaea share a number of features with both the Bacteria and the Eucarya, but they also possess some unique characteristics (Beveridge, 2001; König, 2001). Typical bacterial features are the small cell size, the lack of a nucleus, a small genome size and non-mitotic cell division. The circular chromosome is not membrane bound and exhibits a large range of DNA base composition (Thomas et al., 2001). Restriction enzymes are present. The sedimentation coefficient of the ribosomes is 70S. The cells can possess polyphosphate and polyhydroxybutyrate inclusions. Membrane-surrounded organelles are absent, which is also true, however, for some eukaryotic Archaezoa. Like Bacteria, the flagella are single filamentous protein helices. Some Archaea are able to fix dinitrogen. The organization of the rRNA cistrons (except Thermoplasma) is also bacteria-like.
A number of features are Eucarya-like (eukaryal). The elongation factor EF-2 contains the amino acid diphthamide and is therefore ADP-ribosylated by the diphtheria toxin. Amino acid sequences of the ribosomal A proteins exhibit sequence homologies with the corresponding eukaryotic proteins. The methionyl initiator tRNA is not formylated and some tRNA genes contain introns. The aminoacyl stem of the initiator tRNA terminates with the base pair AU. Like the a-DNA polymerases of Eucarya, the replicating archaeal DNA polymerases are not inhibited by aphidicolin and butylphenyl-dGTP. The inhibition of peptide synthesis by anisomycin, but not by chloramphenicol, is also a eukaryotic feature. The pigment retinal is a compound found formerly in Eucarya only.
A unique archaeal feature is the membrane structure. (1) The membrane lipids are glycerol isopranyl ethers; (2) the Archaea possess unique cell envelopes; and (3) interestingly, there is an absence of ribothymidine in the “common” arm of the tRNAs. In the Archaea, it is replaced by 1-methyl-pseudouridine or pseudouridine. In addition, especially in methanogens, a number of unusual cofactors have been found.
The Archaea possess no common cell wall polymer and all Archaea lack murein (Kandler and König, 1993). The cell walls of Gram-positive Archaea consist of pseudomurein (König et al., 1982), methanochondroitin, heterosaccharide or a glutaminylglycan. The Gram-negative Archaea possess surface layers of protein or glycoprotein subunits forming two-dimensional crystalline arrays which are directly located on the outside of the plasma membrane. The Thermoplasmas are cell wall-less and Methanospirilli possess additional proteinaceous sheaths. Due to their distinct chemical composition, the Archaea exhibit high resistance against cell wall antibiotics and lytic agents. The biosynthetic pathways follow different modes compared to the well-known pathways of cell wall polymers in bacteria.
Typical fatty acid glycerolipids are absent in archaeal membranes. Instead, glycerol phytanyl diether and biphytanyl tetraether lipids form the lipids of the plasma membrane (Langworthy, 1985). The isopranyl glycerol ethers are a convenient molecular marker to distinquish Archaea from Bacteria and Eucarya. The phytanyl residues are linked to atoms C2 and C3 of glycerol, while in the other domains the atoms C1 and C2 are substituted with fatty acids. The tetraethers form monolayered and not bilayered membranes.
The cultivated Archaea, as recognized from a phenotypic perspective, comprise of three different phenotypes: the methanogens (that produce methane), the extreme halophiles (that live at very high concentrations of salt (NaCl)) and the extreme thermophiles (that live at very high temperatures) (Woese, 1987).
On the basis of SSU rRNA analysis, the domain Archaea consists of two phylogenetically distinct phyla, the Euryarchaeota and the Crenarchaeota. Pure culture of a third kingdom, the Korarchaeota (Fig. 3, clones pJP78 and pJP27) are not yet available, although stable mixed cultures, containing representatives of this group, can be grown in the laboratory (Burggraf et al., 1997). From the media and incubation conditions supporting these cultures, we can deduce that the Korarchaeota are hyperthermophiles and may have metabolic properties similar to those of the hyperthermophilic Crenarchaeota.
A cultured nanosized hypertermophylic symbiont (Huber et al., 2002a) and several novel SSU rRNA clones, which constitute new sister clades, were reported recently (Kim et al., 2000; Takai and Horikoshi, 1999, Fig. 5A).
Cultivatedcrenarchaeotes are phenotypically monotonous in that they all possess a thermoacidophilic phenotype. The term "cren" means spring or fount and should express "the ostensible resemblance of this phenotype to the ancestor (source) of the domain Archaea". In contrast, the Euryarchaeota phylum contains organisms that are highly diverse in their physiology, morphology and natural habitats. The term "eury" takes this into account with its meaning of "broad" or "wide".
The following descriptions of the most studied members of the cultivated Archaea are based on Bergey’s Manual of Systematic Bacteriology (Table 1, Garrity, 2001) as a leading reference source in prokaryotic taxonomy.
The Crenarchaeota are a well-defined branch of the archaeal domain, which is obvious from sequence data and biochemical investigations.
All cultured representatives of the Crenarchaeota are extreme thermophiles or hyperthermophiles. A broad variety of metabolic pathways is evident (Stetter, 1998). Aerobically growing chemolithotrophs gain energy by the oxidation of various sulfur compounds, molecular hydrogen or ferrous iron. Anaerobic chemolithotrophs reduce sulfur, thiosulfate or produce nitrate, hydrogen sulfide or ammonia. Organotrophic growth occurs on complex organic substrates, sugars, amino acids or polymers such as starch (Robb and Place, 1995).
One should remember that even though we think of thermophilic environments as being unusual, they are actually quite common. Hot springs, after all, are just the "tip of the iceberg" of the thermophilic world below us. All the subterranean environments and the mid-oceanic spreading zones form a continuous ecosystem several kilometers wide and deep. All indications are that the water that saturates the crushed rock and sinter in the spreading zone is full of thermophilic microbial growth. Water that flows out from hot springs contains typically 107 to 108 cells per milliliter, and these are just the cells that grow in suspension.
Within the Crenarchaeota, a broad variety of morphologies exist including rods of different width and length, regular or highly irregular cocci, and very unusual disc-shaped cells integrated in a network of hollow cannulae (Huber and Stetter, 1999a). As in all Archaea, no murein (peptidoglycan) is present in the cell walls of the Crenarchaeota. All Crenarchaeota species stain Gram-negative.
The rod-shaped representatives of the Crenarchaeota are found within the order Thermoproteales. The separation into the two families Thermoproteaceae and Thermofilaceae is in agreement with morphological characteristics. The members of the Thermoproteaceae exhibit cell diameters of 0.4 to 0.5 µm, while the Thermofilaceae are thin rods (filaments), with cell diameters of 0.15 to 0.35 µm. The length of all these rod-shaped organisms is usually between 1 and 8 µm, although cells of up to 100 µm occur within the genus Thermofilum and Thermoproteus.
As indicated by the name ”lobus”, cells representative of the order Sulfolobales are usually lobed cocci with cell diameters between 0.5 and 2 µm occurring singly or in pairs. As an exception, both Metallosphaera species exhibit a regular coccoid shape.
The representatives of the Desulfurococcales are cocci or discs with diameters between 0.3 and 5 µm, which are often highly irregular. The cells occur usually singly or in pairs. In addition, the cells of Thermosphaera aggregans and Staphylothermus marinus form short chains or grape-like aggregates. In culture media inoculated with Pyrodictium cells, greyish flakes 1 to 10 µm in diameter, can be seen macroscopically. These flakes are composed of cells interconnected by a network of hollow cannulae. This unique interconnecting structure is formed only by Pyrodictium species (Rieger et al., 1995). Single cannulae have a diameter of 25 nm, and can aggregate in bundles of 10 or more. The cells of Pyrodictium display a further unusual feature, the so-called ultraflat areas, with a width of only 80 to 100 nm. The two cytoplasmic sites of the membrane are often in direct contact, with hardly any cytoplasm left in between.
The phylum Crenarchaeota comprises of one Class - Thermoprotei which consists of three orders: Thermoproteales (Zillig et al., 1981), Sulfolobales (Stetter, 1989) and Desulfurococcales (Zillig et al., 1982) (Table 1).
All members of the Thermoproteales live at a neutral or slightly acidic pH. With the exception of Pyrobaculum aerophilum, they are strict anaerobes, which gain energy by respiration of elemental sulfur using organic compounds as substrates, yielding carbon dioxide and hydrogen sulfide. In addition, Thermoproteus tenax, Thermoproteus neutrophilus and Pyrobaculum islandicum can grow chemolithotrophically by H2/S autotrophy. In contrast, growth of Pyrobaculum aerophilum is inhibited by elemental sulfur. This organism grows autotrophically by oxidation of molecular hydrogen or thiosulfate, using oxygen, nitrate or nitrite as electron acceptors. Complex organic compounds are used during heterotrophic growth in the presence of nitrate. Pyrobaculum aerophilum is the only aerobic representative of the Thermoproteales. The two Thermofilum species can be distinguished by the requirement for a polar lipid of Thermoproteus tenax or cell extracts of other archaea by Thermofilum pendens. Thermofilum librum grows without these supplements in the culture medium.
The Thermoproteales are hyperthermophiles with temperature optima between 85 and 100°C and temperature maxima from 95 to 104°C. With the exception of Pyrobaculum aerophilum, the only marine species within the order, they are found in soils, mud holes or surface waters of solfataric fields which exhibit low ionic strength. Therefore, growth occurs at sodium chloride concentrations between 0 and 2% in the culture medium. Pyrobaculum aerophilum grows between 0 and 3.6% NaCl with an optimum at 1.5% (Huber and Stetter, 1992).
All members of the order Desulfurococcales are neutrophiles with pH optima between 5 and 8. The representatives of the two families are diverse in their temperature maxima: while the Desulfurococcaceae can grow up to around 100°C, the Pyrodictiaceae reach temperature maxima between 108 and 113°C. Below 80°C, no growth can be obtained with any representatives of the Pyrodictiaceae. Pyrolobus fumarii (Blöchl et al., 1997) is unable to grow even below 90°C and exhibits the highest growth temperature of all known organisms, 113°C. It gains energy anaerobically by reduction of nitrate (forming ammonia) or thiosulfate (forming hydrogen sulfide). Under microaerobic conditions it can grow by oxidation of molecular hydrogen. The closely related members of the genera Pyrodictium and Hyperthermus (Zillig et al., 1991) exhibit different metabolisms. The Pyrodictium species grow chemolithoautotrophically by reduction of elemental sulfur using molecular hydrogen. Sulfur can be replaced by sulfite or thiosulfate in some strains. In addition, P. abyssi (Pley et al., 1991) gains energy by fermentation of peptides. The obligate fermentative Hyperthermus produces organic acids and butanol from peptides. All members of the Pyrodictiaceae have been exclusively isolated from shallow submarine hydrothermal systems and from deep-sea hot vents.
With the exception of Igneococcus, all representatives of the family Desulfurococcaceae are obligate organotrophs. Members of the genera Thermosphaera, Sulfophobococcus and Staphylothermus gain energy by fermentation of sugars or complex organic substrates, such as yeast extract or peptides. Furthermore, sulfur respiration, yielding hydrogen sulfide in addition to organic acids or alcohols, is found within the genera Desulfurococcus, Thermodiscus and Stetteria. In addition, Desulfurococcus amylolyticus can use starch as an organic substrate. The only obligate aerobic member of this family, Aeropyrum pernix (Sako et al., 1996), grows by respiration of complex organic material in the presence of oxygen. Igneococcus gains energy by reduction of elemental sulfur using molecular hydrogen as an electron donor (Huber et al., 2000). Members of the Desulfurococcaceae have been isolated from continental and marine high temperature biotopes all over the world.
Due to their hyperthermophily, some species have been examined for heat-shock proteins. In Pyrodictium a thermosome (a chaperonin-like protein complex with ATPase activity) is expressed which is accumulated after heat shock. Chaperone-like heat-shock protein can be detected in cells of Pyrolobus after immunoblotting crude cell extracts.
Formerly, representatives of the Crenarchaeota were often termed the "sulfur-metabolizing" hyperthermophiles. However, several representatives of this kingdom are not only unable to metabolize sulfur (e.g. growing obligately by fermentation), but are even inhibited by elemental sulfur. This includes Pyrolobus fumarii, Sulfophobococcus zilligii and Thermosphaera aggregans.
As a rule, all members of the order Sulfolobales are thermoacidophiles, exhibiting temperature optima between 65 and 90°C and pH optima between 1.5 and 4 (Brock et al., 1972). The six genera within this group are well defined by physiological and biochemical properties, although this chemotaxonomic classification does not always correlate with their phylogeny, based on 16S rRNA sequence data.
Representatives of the genera Sulfolobus, Metallosphaera and Sulfurococcus are obligate aerobes. Acidianus and the recently described Sulfurisphaera are facultative anaerobes, while Stygiolobus is an obligate anaerobe. For Sulfolobus, Metallosphaera, Sulfurococcus and Acidianus, the typical energy-yielding reaction is the oxidation of elemental sulfur to sulfuric acid. Alternatively, sulfide, tetrathionate or ferrous iron can serve as electron donors for several species. However, it should be mentioned that the type strains of Sulfolobus acidocaldarius and S. solfataricus, deposited in culture collections, have lost their capability of oxidizing elemental sulfur. Due to their ability to oxidize sulfides, some of these strains are highly efficient in mobilizing metals from sulfidic ores producing soluble sulfates (Huber et al., 1989). Oxygen can be replaced by MoO42- or ferric iron as electron acceptors. Furthermore, most strains can gain energy by the oxidation of molecular hydrogen (the "Knallgas" reaction). However, significant differences have been determined for the optimal concentration of oxygen in different strains. It varies from 0.5% (Metallosphaera sedula) to 12% (Metallosphaera prunae) oxygen in the atmosphere. In addition to chemolithoautotrophic growth, many strains are able to grow on complex organic substrates, like yeast extract peptone, tryptone, meat extract or casamino acids. Some Sulfolobus and Sulfurococcus strains can use various sugars and amino acids as carbon and energy sources. In the absence of oxygen, Acidianus is able to grow by reduction of elemental sulfur. Anaerobic growth occurs via S/H2 autotrophy and large amounts of H2S are produced. This reaction is also characteristic for the strictly anaerobic Stygiolobus. Sulfurisphaera is a facultative aerobe, which grows on complex organic substrates, or under anaerobic conditions on elemental sulfur.
The Sulfolobales are usually found in biotopes of low ionic strength (and low pH), like sulfur rich solfataric fields. Therefore, optimal growth occurs at NaCl concentrations between 0 and 1% NaCl in the culture medium. An exception, however, is Acidianus, which can grow at concentrations of up to 4% NaCl.
Five major groups are known within this kingdom; the obligate anaerobic methanogens, the extreme halophiles, the hyperthermophilic sulfate reducers, the Thermoplasma group, and finally the Thermococcus-Pyrococcus group. During the last decade, numerous reclassifications within the Euryarchaeota have been carried out, mainly based on results of 16S rRNA sequence comparisons. This is especially true for the orders Halobacteriaceae, the Methanobacteriaceae, and the Methanomicrobiales.
Within the Euryarchaeota a broad variety of morphologies is evident. Besides straight to crooked rods (sometimes embedded in a sheath) of different width and length, regular or highly irregular cocci, or pleiomorphic forms occur; with some even lacking a cell wall (Garrity, 2001). Although no murein (or peptidoglycan) is present in the cell walls of the Euryarchaeota, a quite similar structure called pseudomurein is found within the Methanobacteriales and the Methanopyrales. Therefore, in addition to the halococci and some strains of the genus Methanosarcina, these organisms stain Gram-positive. All other Euryarchaeota exhibit a Gram-negative reaction.
Within the Methanopyrales, all cells are exclusively rod-shaped, while all members of the Methanococcales are regular cocci. With the exception of the coccoid Methanosphaera species, the Methanobacteriales harbour only rod-shaped strains and species, which, however, differ significantly in width and length. Several genera of the Methanomicrobiales and Methanosarcinales exhibit quite unusual cell morphologies, like the plate- or disc-shaped Methanoplanus, the pleiomorphic Methanolacina, the aggregate-forming Methanosarcina, or the spiral-shaped Methanospirillum. Methanospirillum and Methanosaeta have unique ultrastructures. The individual cells are covered by a sheath with a striated surface appearance and are spaced apart by multiple lamellae or a plug composed of concentric rings. The filaments of Methanosaeta form large bundles or mats and are up to several 100 µm long. The sheaths exhibit remarkable resistance to chemical reagents. Different types of cell walls have been observed for methanogens. Many methanogens (especially coccoid organisms) are motile by one or more flagella, which are sometimes arranged in a polar tuft. Due to the possession of F420 all methanogens show a blue-green fluorescence under an ultraviolet microscope at 436 nm. In a few species, cylindrically shaped gas vesicles are found (e.g. Methanosarcina vacuolata).The Thermococcales are characterized by a coccoid shape. With the exception of Thermococcus litoralis, all Thermococcus and Pyrococcus species are motile and possess one or more flagella (in Pyrococcus they are always arranged in at least one polar tuft). Archaeoglobus and Ferroglobus cells are highly irregular cocci, occurring singly or in pairs. Very often they are triangular-shaped and appear to be flat at the broader base. Cell diameters vary from 0.7 to 1.3 µm. Like the methanogens, all members of the Archaeoglobales show a blue-green fluorescence under the UV microscope. Most of the strains are flagellated.
The lack of a cell wall is characteristic for members of the genus Thermoplasma. Consequently, their cell shape and diameters are highly variable. During early exponential growth phase, filamentous, disc-shaped and coccoid-shaped cells occur with diameters between 0.2 and 5 µm. Later, spherical forms predominate. All strains are motile by possession of flagella. Members of the Halobacteriaceae are rods, cocci, sarcinas, or flat triangles and squares. These organisms stain Gram positive or negative, depending on the species.
Due to their extreme diversity, the Euryarchaeota cover the whole spectrum of physiological properties: from psychrophiles to hyperthermophiles, from strict aerobes to obligate anaerobes, from freshwater strains to extreme halophiles, and from extreme acidophiles to alkalophiles (Zinder, 1993). Furthermore, a broad variety of metabolic pathways is evident, represented by strict chemolithoautotrophy to organotrophy.
Within the methanogens five orders have been described (Balch et al., 1979; Kurr et al., 1991), the Methanopyrales, the Methanococcales, the Methanobacteriales, the Methanomicrobiales, and the Methanosarcinales (Table 1).
In contrast to their enormous phylogenetic diversity, methanogens can only use a few simple substrates, most of them being C1 compounds, like H2/CO2, formate, methanol or methylamines. With the exception of Methanosarcina and Methanolacina, many strains are restricted to only one or two such energy sources. The most common energy-yielding reaction within the methanogens is the reduction of carbon dioxide by molecular hydrogen producing methane, followed by the utilization of formate. Only the representatives of the Methanosarcinaceae and Methanosphaera are unable to grow on these substrates. Acetate can be used by Methanosarcina and Methanosaeta, while the methylotrophic genera (e.g. most members of the Methanosarcinaceae) utilize methanol, several methylamines or methylsulfide. Furthermore, some species grow on primary and secondary short-chain alcohols. Many species are dependent on special growth factors like vitamins, amino acids or acetate. All methanogens can use ammonium as a nitrogen source. In addition, a few species are able to fix molecular nitrogen (e.g. Methanosarcina barkeri (Scherer, 1989) and Methanococcus thermolithotrophicus).
All methanogens are strict anaerobes, although some strains tolerate oxygen for a short time (especially Methanosarcina). They usually grow at neutral pH, but a few strains of Methanobacterium still grow at pH 5 and Methanohalobium zhilinae exhibits a pH optimum of 9.2. Most of the methanogens live in environments of low ionic strength (e.g. Methanobacteriales) or in marine biotopes (e.g. Methanopyrales, Methanococcales). However, some methylotrophic methanogens, such as Methanohalobium evestigatum (Zhilina and Zavarzin, 1987), Methanohalophilus mahii and M. halophilus, grow in salt concentrations of up to 3 or 4 mol/l NaCl. Although most methanogens are mesophiles, numerous thermophilic and hyperthermophilic strains and species have been isolated. While Methanothermobacter thermoautotrophicum, the first thermophilic methanogenic organism to be described, grows at temperatures up to 75°C, the hyperthermophilic Methanothermus fervidus (Stetter et al., 1981) and Methanopyrus kandleri (Kurr et al., 1991) have extended the maximum growth temperature of methanogens, growing at 97°C and 110°C, respectively. Within the Methanococcales two hyperthermophiles are known, M. jannaschii and M. igneus, the latter growing at temperatures up to 91°C. Recently, one psychrophilic species, Methanogenium frigidum, has been described (Franzmann et al., 1997). This marine organism grows from the freezing point of the medium to 17°C with an optimum at 15°C.
Methanogens are common organisms, found in all types of anaerobic environments, and are certainly the most prevalent cultivated Archaea in the "moderate" world:
anoxic sediments and soils - "swamp gas" is methane, which, because of its low ignition temperature and low threshold concentration, is readily ignited, resulting in the faint white glow of "will-o-the-wisps" visible at night in swamps.
animal digestive tracts -
rumen of ruminant animals such as cattle, sheep, elk, deer and camels. A cow belches about 50 liters of methane a day during the process of eructation (chewing the cud)
cecum of cecal animals such as horses and rabbits
large intestine of monogastric animals such as humans, swine, and dogs
hindgut of cellulolytic insects (termites). African termite mounds are thoroughly aerated by the insects not for oxygen, but to keep methane concentrations low
wastewater and landfills - the whole anaerobic wastewater process works because organics in the wastewater are converted first to biomass (in the early stages of treatment), then digested anaerobically to H2, CO2, and acetate which in turn is converted by methanogenesis into methane, which diffuses into the atmosphere.
oil deposits - natural gas is methane, produced by methanogens living in the subterranean oil deposits, or geochemically in the deeper layers of the bedrock.
geothermal sources of H2+CO2: hydrothermal vents.
Methanogens form a variety of symbioses with plants, animals and protists, but despite these close associations there are no known pathogenic methanogens. Methanogens also form close syntrophic associations with heterotrophic Bacteria that generate hydrogen (i.e. use protons as the terminal electron acceptor). Hydrogen-generating heterotrophism is only energetically-favorable where the ambient concentration of hydrogen is extremely low. Methanogens associate with these organisms, utilizing the hydrogen they generate for methanogenesis maintain a low hydrogen concentration favourable to the heterotrophs. Neither of these organisms could persist in the environment alone, but together they are successful.
The Class consists of one order - Archaeoglobales, contains two genera, Archaeoglobus (Stetter, 1988) and Ferroglobus (Hafenbradl et al., 1996) (Table 1).
All members of the Archaeoglobales are strict anaerobic hyperthermophiles, growing between 60 and 95°C with an optimum at 80-85°C. They are neutrophilic with a pH optimum around pH 7 (range pH 4.5 to 8.5). Due to their natural habitat (abyssal hot sediments, submarine hydrothermal systems), sodium chloride concentrations up to 4.5% are tolerated, although all species grow optimally at around 2%.
Representatives of the Archaeoglobi show the same blue-green fluorescence that is characteristic of methanogens. Moreover, in Archaeoglobus fulgidus, most of the enzymes and coenzymes typical of methanogenesis are present (with the exception of coenzyme M and F430). Lactate is oxidized to carbon dioxide via a modified acetyl-CoA/CO dehydrogenase pathway, where the methyl group is successively converted to CO2 by the reversion of the methane formation pathway from CO2 in methanogens. Members of the genus Archaeoglobus are resistant to ampicillin, vancomycin, rifampicin and streptolydigin.
The Class consists of one order - Thermococcales. Three genera in one family, represented by numerous species, have been described: Thermococcus, Pyrococcus and very recently Palaeococcus (Takai et al., 2000) (Table 1). Due to its fast growth and easy cultivation, Pyrococcus furiosus (Fiala and Stetter, 1986) has become a model organism for molecular and biochemical studies of (hyperthermophilic) archaea.
All members of the order Thermococcales are strict anaerobic hyperthermophiles with temperature maxima between 85 and 105°C. Optimal growth temperatures are between 75 and 88°C for Thermococcus species and 96-100°C for representatives of the genus Pyrococcus. With the exception of T. alcaliphilus (pH optimum 9.0, maximum 10.5) all organisms are neutrophiles with pH optima between 6 and 8. They grow optimally at NaCl concentrations of between 2 and 3%. This is in agreement with the natural habitats of the Thermococcales, which are marine hydrothermal systems, shallow solfataric marine water holes or hot oil reservoirs. The Thermococcales grow heterotrophically by fermentation or sulfur respiration on a variety of organic compounds such as peptone, yeast extract, meat extract, casein, peptides, casamino acids, and starch. Some strains can use maltose or pyruvate as substrates, and growth on chitin was reported for T. chitonophagus (Huber et al., 1995). The main fermentation products are carbon dioxide, hydrogen, organic acids (isovaleriate, isobutyrate, acetate, formate, lactate), alcohols (e.g. butanol) and amino acids (e.g. alanine). Elemental sulfur significantly stimulates growth of many strains and hydrogen sulfide is produced. For some species (e.g. P. furiosus, P. abyssi, P. horikoshii) molecular hydrogen inhibits growth and the production of hydrogen sulfide in the presence of elemental sulfur is a kind of a detoxification reaction. Growth by sulfur respiration was reported for P. woesei (Zillig et al., 1987) and some Thermococcus strains.
Due to their ability to use a great variety of substrates, members of the Thermococcales contain many extracellular hydrolases. Especially in Pyrococcus furiosus, the pathways of sugar or pyruvate degradation have been intensively studied. Although not all strains and species have been investigated, the Thermococcales exhibit resistance to the following antibiotics: vancomycin, penicillin, kanamycin, streptomycin and chloramphenicol. Some species are sensitive to rifampicin (e.g. T. profundus, T. stetteri, T. litoralis), while T. celer is resistant.
The Class consists of one order - Thermoplasmatales, which contains three families; the Thermoplasmaceae, the Picrophilaceae, and the new mesophilic Ferroplasmataceae (Golyshina et al., 2000) (Table 1).
Representatives of this Class are extreme acidophiles, exhibiting pH optima between 0.7 and 2. Picrophilus (Schleper et al., 1995) surpasses all other prokaryotes in this ability by growing well even at around pH 0. All species (exept Ferroplasmataceae family) exhibit temperature optima of around 60°C and a maxima of between 65 and 67°C. Due to their natural habitat (solfataric springs or smouldering coal refuse piles), they need culture media with low ionic strength.
In contrast to the obligate aerobe Picrophilus, Thermoplasma species are facultative anaerobes. They are able to grow in the absence of oxygen by respiration on elemental sulfur with production of hydrogen sulfide. Under aerobic conditions, sulfur is not metabolized (e.g. to sulfuric acid). All Thermoplasmatales are obligate heterotrophs growing on yeast extract, meat extract or bacterial extracts from, for example, Bacillus acidocaldarius, Sulfolobus solfataricus or Desulfurococcus species. It is probably oligopeptides present in these substrates which are metabolized. Therefore, they are scavengers utilizing decomposition products of organisms present in their natural habitat. The addition of sugars results in higher final cell densities, although no growth is obtained on sugars alone. Carbon dioxide, acetate and formate are mainly detected as metabolic products.
Members of the Thermoplasmatales are resistant to vancomycin, bacitracin and streptomycin.
The extremely halophilic Archaea require at least 2M NaCl or equivalent ionic strength for growth - most grow in saturated or near-saturated brines. They are the primary inhabitants of salt lakes. Red pigments make it obvious when large numbers of these organisms are present - blooms often occur after a rain carries organic material into a salt lake, and the Red Sea gets its name from such blooms. They are common in hypersaline seas, salt evaporation pools, salted meats, dry soil, salt marshes, etc. They are also found in subterranean salt deposits, where micropockets of saturated water "diffuse" around the otherwise solid salt. Other halophilic organisms (e.g.fungi, brine shrimp) have normal cytoplasmic salt concentrations, expending energy to continuously pumping salt out of the cell and water into the cell, and contain organic osmolytes like glycerol or sugars. Halophilic Archaea grow at much higher salt concentrations, and the internal salt concentrations are as high as they are outside. For this reason, there is little or no osmotic pressure on the cell wall, and some organisms take advantage of this by adopting high surface-area shapes that are not possible for organisms in "normal" ionic strength. One example is Haloarcula (Oren et al., 1999), which occurs in squares and triangles with straight edges, sharp corners, and is very flat. Other halophiles are rods or cocci.
The Class Halobacteria (Grant and Larsen, 1989) consists of one order - Halobacteriales, with one family Halobacteriaceae including 15 genera (Table 1).
Halophiles are mesophilic facultative aerobes. Aerobically, they grow heterotrophically, via respiration using oxygen as the terminal electron acceptor. Anaerobically, they grow photochemotrophically - obtaining energy (ATP) from light, but still require organic compounds as a carbon source.
They do not contain the usual photosystems or electron transport chain for gathering energy from light. Phototrophy is driven by a single protein, bacteriorhodopsin, a light-driven proton pump. This proton pump generates a proton gradient used to make ATP via ATPase, just like in other organisms. It is not nearly as efficient as the bacterial photosystems, but light is rarely limits growth in the desert salt lakes where they predominate.
Some halophiles grow at high pH (up to pH 10-10.5) i.e. Natronobacterium (Xin et al., 2001) in soda lakes. At that pH, any protons pumped to the outside, by electron transport or rhodopsin, are gone forever. Even though the resulting electric potential is still there, it cannot be harvested by an ATPase unless it can obtain protons from the outside. How they get around this is not known, and it is probably this issue that limits the upper pH range of life.
The known phenotypic patterns of cultivated Archaea (see the previous sections 1.3.1-1.3.4) are still largely represented by extreme halophiles, thermoacidophiles and methanogens. Judging solely from cultivated strains, archaeal phenotypic diversity appears limited, in comparison to the wide variety of phenotypes in the Bacteria (Woese, 1987). Consequently it was assumed that Archaea were of ecological significance only in few highly specialized (and predominantly anaerobic) „extreme“ habitats, and were therefore described as "extremophiles". This picture has altered considerably as new molecular biological methods have been applied to the study of naturally occurring microorganisms (Pace, 1997).
The presence of novel uncultivated types of Archaea was first suggested during molecular phylogenetic surveys of marine planktonic microorganisms. This survey of PCR-amplified SSU rRNA genes revealed archaeal-like rRNA gene sequences in seawater samples from 100 m and 500 m depth in the Pacific Ocean (Fuhrman et al., 1992). These oceanic archaeal rRNAs were most closely related to those of Crenarchaeota, a branch of Archaea previously thought to consist of hypertermophiles exclusively. At the same time, microorganisms collected in surface water off the North American coast showed the presence of two new archaeal groups; one crenarchaeotal, one euryarchaeotal (Delong, 1992). Initially, it had to be considered that the planktonic archaea might be allochthonous thermophiles, transported far from a putative hydrothermal vent habitat. However, due to the widespread distribution and the relatively high abundance of the planktonic Archaea, it was thought unlikely. The discovery of high numbers of Archaea in anaerobic, Antarctic waters at temperatures of minus 1.8°C (Delong et al., 1994) and the association of one crenarchaeotal species, Cenarchaeum symbiosum, with a marine sponge living at 10°C (Preston et al., 1996) provided further evidence that the new Archaea were native to cold seawater biotopes.
Since their initial detection, evidence for a widespread distribution of new, uncultivated Archaea has been further extended to marine plankton, shallow and deep-sea sediments, freshwater lakes and sediments, various soils and many other "extreme" and "non-extreme" environments. Table 2 lists the key published research work (up to May 2002) performed on the subject of uncultivated environmental archaeal SSU rRNA. Three major new uncultured archaeal groups (Delong, 1998) were (until recently) encountered in culture-independent ecological surveys (Table 2, Fig. 5 B, C). Group I includes Archaea living in a variety of soil, sediment, marine and freshwater habitats and is related to Crenarchaeota. The other two archaeal clades (Group II and III) fall within the Euryarchaeota with little less variation in habitat occupation.
Studies of the phylogenetic identity, diversity, and distribution of the new uncultivated archaeal groups have revealed that with respect to their ecological distribution, the non-thermophilic Crenarchaeota from Group I seem to be the most widely distributed and abundant form of all known Archaea. They occupy many different habitats and ecological niches (Table 2). A recent study of Archaea in the mesopelagic zone of the Pacific Ocean shows that pelagic Crenarchaeota represent one of the ocean’s single most abundant cell types and, globally, the oceans harbor approximately 1.3x1028 archaeal cells (comparing to 3.1 x1028 of bacterial cells) (Karner et al., 2001). Current data suggests that several lineages of hyperthermophilic crenarchaeotes adapted to colder habitats independently (Pace, 1997; Hershberger et al., 1996; Barns et al. 1996) and their expansion into non-thermophilic habitats occurred during the mid-Cretaceous period (124 to 83 millions years ago) (Kuypers et al., 2001). Analysis of available sequences indicates that there is greater sequence divergence in euryarchaeal Group II rRNA genes isolated from the same biotop, relative to that of sympatric marine Group I rRNA genes. The significant rRNA sequence divergence among the new archaeal types probably reflects substantial physiological diversity too. On the basis of their phylogenetic position, it appears that the non-thermophilic archaea have thermophilic ancestries.
In the latest review “Exploring prokaryotic diversity in the genomic era” by Hugenholtz, 2002, 18 archaeal phylum-level lineages were described, 8 had cultivated representatives and 10 that did not.
The ease and accessibility of gene amplification via the PCR approach has opened the gates to a remarkable amount of comparative rRNA sequence data. Although necessary and extremely useful, gene phylogenies and associated phylogenetic probes do not provide comprehensive biological characterization. The recovery of rRNA and rRNA genes from the environment allows phylogenetic analysis and quantification of uncultivated Archaea in environmental samples. Reproducible patterns of distribution and variability monitored by phylogenetic probes can lead to clues about habitat preferences, probable energy sources, and physicochemical tolerances, but such conclusions are necessarily tentative and require further verification via more detailed physiological, biochemical and genetic characterization. What progress can be made in the characterization of these organisms in the absence of pure cultures? The development of general approaches for characterizing as yet uncultivated microbial species presents a major challenge for modern microbiologists. Uncultivated Archaea represent good test organism for new approaches, as their phylogenetic diversity is reasonably limited and unique archaeal biochemical signatures (such as specific rRNA sequence motifs, or cell membrane lipids) can be detected in mixed populations.
Advances in genomic analysis are providing new technologies that may be useful for characterizing uncultivated prokaryotes. The main requirement is the availability of pure, intact, high molecular weight genomic DNA. Large DNA fragments can be recovered from mixed microbial populations using modern genomic techniques. Analysis of these large fragments can yield information on gene organization, structure and content of uncultivated Archaea. The archived genome fragments of uncultivated microbes can be viewed as reagents, useful for expressing protein-encoding genes, determining enzyme structure and function, or dissecting metabolic pathways. Microbial groups previously defined solely by rRNA gene phylogeny can, at least partially, be characterized by genome content and biochemical characteristics. Examples of such an approach resulting in the genomic analysis of "non-thermophilic" crenarchaeotes are the fosmid DNA libraries prepared from a marine picoplankton assemblage (Stein et al., 1996) and the discovered archaeal symbiont Cenarchaeum symbiosum (Preston et al., 1996; Schleper et al., 1997b). Two other examples are the construction of large-insert bacterial artificial chromosome (BAC) libraries from the genomic DNA of planktonic marine microbial assemblages (Beja et al., 2000) and from genomic DNA isolated directly from soil (Rondon et al., 2000).