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Chapter three of Thomas Brock's classic microbial ecology text (Brock, 1966) is prefaced by a quote attributed as a graduate student motto. The motto simply states, ‘microbial ecology is microbial physiology under the worst possible conditions’. After more than a quarter century, the statement still captures the essence of a fundamental obstacle to progress in microbial ecology – attributing a microbially catalysed process, measured in a complex environmental milieu, with a specific organism or organisms. This remains a challenge to contemporary microbial ecologists. In specific cases, such as microbial mat communities, which are highly structured and dominated by a relatively small number of morphologically recognizable taxa, it has been possible to measure rates of photosynthesis or sulphide oxidation and relate these specifically to the organisms present (Revsbech and Jørgensen, 1986). These studies are the exception, and there is a need to develop approaches that allow explicit links to be made between the presence of specific organisms and the processes they catalyse. This has become more pressing given the tantalizing and growing insight into the complexity and dynamics of natural bacterial and archaeal communities offered by culture-independent analyses (Amann et al., 1995; Head et al., 1998; Hugenholtz et al., 1998). There are now many major groups of Bacteria and Archaea known only from molecular sequences and, until these organisms can be cultivated, the only means of understanding their role in the environment is through culture-independent characterization linked to determination of in situ metabolic activity. Even when an organism can be cultivated, properties determined in the laboratory may not necessarily reflect the activities and physiology of their counterparts in the environment (Brock, 1987), where factors such as resource competition, environmental heterogeneity, predation and other interactions are prevalent. This review aims to highlight selected recent developments that are revealing the metabolic capabilities and ecological role of the uncultured majority Characterization of an organism's habitat and establishing its distribution within the habitat has long been a tool available to microbial ecologists to infer ecological function (Brock, 1966). This approach has been useful because the presence of natural gradients of light, temperature, salinity, electron acceptors and donors, etc. is a feature of many natural environments. Determining bacterial community structure in relation to such gradients may allow the organisms present to be associated with specific ecological properties and may identify potential factors responsible for the emergence of diversity in specific groups of organisms. This is exemplified by recent studies of prochlorophytes. Several related (≈ 2–3% 16S rRNA sequence divergence) photosynthetic picoplankton from the genus Prochlorococcus have been isolated from the same location in the North Atlantic. Physiological studies of the isolated prochlorophytes revealed that they comprised evolutionarily distinct clades each adapted to different optimal illumination conditions. These findings led to the proposal that the congruent physiological and evolutionary diversity observed was driven by adaptation to different light intensities within the water column of oligotrophic marine environments. Although this conclusion was derived from the study of pure cultures of Prochlorococcus (Moore et al., 1998), the application of culture-independent methods to determine the composition of prochlorophyte communities and the relative abundance of different genotypes in relation to gradients of light has placed the laboratory studies in an environmental context. West and Scanlan (1999) determined the relative abundance of high (HLI) and low light-adapted (LL) Prochlorococcus genotypes in samples taken from different depths in the water column. Relative quantification of the different genotypes was determined by probing of polymerase chain reaction (PCR)-amplified 16S rRNA gene fragments with oligonucleotides characteristic of the HLI and LL genotypes. Denaturing gradient gel electrophoresis (DGGE) was used to determine qualitative changes in the composition of the prochlorophyte community with depth. This indicated a clear depth- and light intensity-related, differential distribution of the HLI (distributed between 0 and 50 m) and the LL (distributed between 30 and 90 m) genotypes in water column samples from the North Atlantic (Fig. 1). The authors concluded that niche partitioning as a result of adaptation to environments experiencing different light intensity played a fundamental role in driving the diversity and distribution of the different Prochlorococcus species. However, it was also clear from the field studies that environmental factors such as nutrient status, turbulence or temperature played a role in defining the finer scale fluctuations in genotype depth distribution that was apparent in different water column profiles. Vertical distribution of high light (HLI) and low light (LL)-adapted Prochlorococcus genotypes in the water column of the eastern North Atlantic. From West and Scanlan (1999). Reproduced with permission. The co-existence of closely related sulphur bacteria from the genus Achromatium has been explained in part by culture-independent analysis of the distribution of morphologically similar, distinct genotypes in relation to redox gradients in a freshwater sediment (Gray et al., 1999a). 16S rRNA sequence analysis and fluorescence in situ hybridization (FISH) clearly demonstrated that Achromatium communities comprised several co-existing, closely related Achromatium species (Head et al., 1996; Glöckner et al., 1999; Gray et al., 1999a). The distribution of different Achromatium genotypes in relation to sediment redox profiles indicated that each was adapted to different redox conditions (Fig. 2). Although all genotypes were identified at all depths in the sediment, the relative proportions of two of the genotypes (RY 7/8 and RY 5) changed with the transition between the oxidized and the reduced zones in the sediment. The RY 7/8 cells comprised 67.8% (n = 1137) of cells in the oxidized zone and represented a significantly (P < 0.001) smaller proportion of the population (50.1%, n = 373) in the reduced zone. Conversely, the RY 5 cell type, which represented 14.8% (n = 1089) of the Achromatium population in the oxidized zone, represented a significantly (P < 0.001) larger proportion of the population (34.6%, n = 399) under more reducing conditions. This suggested that divergent co-existing Achromatium genotypes may occupy different ecological niches within the sediments they inhabit. However, in contrast to studies of populations of Prochlorococcus spp., the mechanisms that lead to the diversification observed in Achromatium communities remain to be determined. Depth profile of (A) redox-sensitive chemical species (Fe2+, filled circles; and SO42–, open circles) and (B) the relative abundance of the three main Achromatium genotypes (RY1, RY5, RY7/8) identified in a sediment core from Rydal Water. The trend lines show a three-point moving average of the data, and error bars represent 95% confidence intervals for counts of the Achromatium subpopulations. The oxidized zone is characterized by high levels of SO42– and low levels of Fe2+, and the reduced zone by low SO42– and high Fe2+. From Gray et al. (1999a). Reproduced with permission. Niche partitioning engendered by differences in physicochemical conditions can clearly occur over very different spatial scales – metres in the case of water column communities of Prochlorococcus and millimetres in sediment environment Achromatium spp. Perhaps one of the most exciting developments in recent years has been the application of microsensor measurements in culture-independent studies of bacterial community structure to provide analysis of chemical and physical gradients on a submillimetre scale combined with information on the distribution of specific microorganisms. Studies of a hypersaline cyanobacterial mat community from Solar Lake, have revealed properties of bacteria that the et al., the populations were within the of the bacterial mat et al., a growing of that not conditions to function and et al., the distribution of on analysis of was related to the of et al., In diversity was in samples from the with samples from depth in the In specific clades of clear for redox with bacteria most to and identified in where was present and between the to at In sequences from depth intervals were not closely related to characterized of This with laboratory studies of that several spp. have a high for they are not et al., spp. sequences were from the Solar mat samples et al., The of or spp. has been from studies culture-independent characterization of specific bacterial populations with to their under environmental for of chemical profiles in relation to the distribution of different bacterial may be used not only to identify environmental conditions by can also be used to specific The of chemical species in a given environment can be from measured chemical profiles and properties and combined with to provide of the abundance of specific specific rates and can be at the of populations or application of this approach has been the determination of the of environmental conditions on the and distribution of and bacteria and in a et al., and oxidation rates were measured in from a was to a zone within the and was used to and the bacteria and within the zone of of and within the were used to and oxidation and of the and rates of and oxidation to be for different within the conditions in which was there was a clear in the population structure of bacteria in the that with of and oxidation rates were significantly at the of the and, were still present in low at the of the oxidation not be In contrast and oxidation rates from the to the of the of oxidation of electron indicated that the activities of the were than of the the cell The reaction was from the or at different in depth profiles. 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These not only allow microbial ecologists to identify specific metabolic activities of within a complex community by the of specific metabolic properties to natural or it is possible to determine environmental factors that the activity. is a with which the of specific by cells can be determined. This has been in many ecological studies and and and Gray et al., its major is the to the of a by a cell with its In the of uncultured cells to be because and are can be concluded a metabolic capabilities (Amann et al., 1996; and and have been combined to the of the two number of have been for the different approaches et al., and and and However, all the methods only in and to by the more combined and (Gray et al., combined and have been in a small number of studies of natural and environments. 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Reproduced with permission. of this study was that of was only in a of each of the three by the was suggested that this was of in Achromatium because of the of the sediment, there may be cells different metabolic this conclusion is and of the that be when from combined and in the study of Achromatium spp., the in be explained simply by diversity that was at a of than the 16S rRNA were to In a more of combined and be with complex simply be from the of a Although of by Achromatium cells that they have it is also known that bacteria can and, in such cases, to cell (Gray et al., the of by marine Archaea not their of other as is known these of other and, more and These Archaea may to be more and in the of and and In it be in with may be by other the of by an organism may not necessarily have from the of the also have from of from This can be to by the of this approach is by means In a of is that it The that for this are highly and be used to to the same as or other more of the bacterial such as studies to physiology at the species or levels be with in situ methods et al., 1995; et al., This the in situ of cells on more of the and can of a specific with the presence of a gene or that are known to be in of the of combined and is to methods such as or and and to relative or rates within measurements the of In natural communities, these methods have been to the of morphologically species and However, with the of in situ cell by these quantification methods can now be to a of activities and physiological may possible to such as and for uncultured organisms through of in In the the application of to determine of microbial communities by analysis of has been used in the study of microbial ecology et al., 1998; et al., This approach is on the of or by of samples with and analysis of by et al., 1998). 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Gray et al. (Wed,) studied this question.
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