The difficulties associated with the in situ identification, isolation and cultivation of microorganisms from soil have provided the impetus to develop molecular biological methods for the analysis of soil-borne microbial communities. In addition, the vast complexity of soil systems impedes steps to understand the structure and functioning of communities in this habitat. Indeed, even with the most elaborate and exhaustive molecular methods, the vast diversity of organisms inhabiting soil (Torsvik et al. 1990) precludes our ability to characterise all the organisms in this habitat completely. Clearly, choices have to be made as to the scope of the organisms to be examined and the detail to which they can be described (Fig. 8.1). There is generally no single 'correct' route to follow, as each approach has
-»■Individual cores -►Mixed samples "♦Specific soil compartments
The analysis of individual cores provides the statistical power to compare within and between samples, yet greatly increases analytical efforts.
Cell / n.a. isolation
^rCulturing rCell extraction—►DNA ^■RNA 'Direct n.a. extraction —
DNA-based analyses seek to reflect gene copy number (gene presence), whereas RNA-based methods detect transcript levels, which may provide Insight Into gene activity.
Broad (i.e. Bacteria, rEukarya & Archaea)
^Specific phylogenetic and/or functional groups
The resolution of microbial community analysis approaches generally increases as one narrows the focus of study. Broad approaches should target highly conserved markers, whereas tine taxonomic discrimination requires more variable markers.
Marker isolation / amplification
'Screening / hybridization 'PCR / RT-PCR
PCR extremely valuable and time-saving, but prone to biases. All methods restricted by accuracy of primers/probes.
Marker detection / analysis rProfiling approaches ^Cloning approaches
Profiling methods allow for the rapid comparison of multiple samples, cloning approaches provide details of individual community members.
Fig. 8.1. Major considerations when choosing the microbial community analysis approach its inherent limitations. The goal is to fit one's choice of approach to the research question and the type of information that is desired.
Any individual experimental design must provide maximum data output, while remaining feasible within budgetary and personnel limits. There has been a general dichotomy between in-depth studies, which lack statistical power because resources limit their scope to very few samples, and multiple sample comparisons, which often remain superficial. The introduction of new group-specific profiling methods, more powerful sequencing capabilities and microarray technologies (see also Chap. 9) may, however, help to break down this dichotomy in the coming years.
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