1. The document discusses two complimentary methods, DNA-based DGGE and lipid biomarker analysis, for assessing soil microbial communities. 2. It provides examples of how these methods have been used to study microbial community structure and diversity across different soil environments and conditions. 3. Specifically, it summarizes two studies that used these methods: one found evidence of "microbial diversity patchiness" correlated with vegetation in Negev desert soils, while the other found bacterial community succession along a desert rainfall gradient.

1. 1 Choice of methods for soil microbial community analysis Eric Ben-David Environment Division, Australian Nuclear Science and Technology Organisation (ANSTO) School of Biotechnology and Biomolecular Sciences, University of New South Wales (UNSW)

2. 2

3. 3 Why Soil Microbes are Important? Soil microbes play pivotal roles in various biogeochemical cycles (BGC) and are responsible for the cycling of organic compounds. Soil microorganisms also influence above-ground ecosystems by contributing to plant nutrition, plant health, soil structure and soil fertility

5. Most looks similar under light microscope – difficult to group by simple shape criteria

6. Problematic to find suitable growing conditions for different microbes

7. Some will grow slowly, some will not grow in lab

9. 6 The DGGE Technique Denaturing gradient gel electrophoresis (DGGE) is a nucleic acid based (DNA or RNA) technique which can be used to profile and identify dominant members of the microbial community based on their genetic fingerprint.

11. 8

13. 10 Lipid Biomarker Analysis

15. 13 Phospholipids have a polar head group and two hydrocarbon tails. saturated fatty acid-> ←unsaturated fatty acid

17. 15 PLFA Analysis Distribution of lipids can be very species specific. Bacteria typically contain odd chain and branched fatty acids as well as cyclopropane and α- or β- derivatives Consequently, profiles based on the composition of phospholipid-linked fatty acids (PLFA) can be used to indicate community structure of bacteria and eucarya but not archaea (because they do NOT have fatty acids in their phospholipids).

18. 16 There are many classes of fatty acids.They are designated according to:1. The total number of C atoms 2. Degree of unsaturation (double bonds)3. Position of the double bonds 4. Branching patterns

20. 18:25 = 18 carbons, 2 double bonds at the 5th position from the aliphatic end

22. 19 CO2 x AM: amb, -AM amb, +AM ele, -AM ele, +AM Community fingerprint Principle Components Analysis (PCA) and cluster analysis can then be used to group microbial communities based upon their similarities:

24. Algae = 20:53, 18:33

25. Fungi = 18:26

26. Actinomycetes = 10Me17:0, 10Me18:0

27. Sulfate reducers = i17:1, 10Me16:0

29. 22 Lipid Extraction

30. 23 GC-MS analysis Gas-phase ions are separated according to mass/charge ratio and sequentially detected

31. 24 How Can We Analyse the Microbial Community Structure? Pure culture studies, mixed enrichment cultures and manipulative lab and field experiments established the link between groups of microbes and specific PLFAs We group together suites of microbes that share biochemical characteristics. ie. eukaryotes vs prokaryotes

32. 25 Example 1 Patchiness of microbial community structure in Negev desert soils Question: Does the vegetation patchiness in desert landscapes is also being reflected in the microbial community structure of two sites from two climatic zones in the Negev, Israel?

33. 26 Multivariate analysis (PCA) of the PLFA data AVDAT SAYERET SHAKED Zygophyllum dumosum (Zd) Hammada scoparia (Hs) Intershrub patches (ISPA) Noaea mucronata (Nm) Thymelaea hirsute (Th) Intershrub patches (ISPS)

34. 27 Redundancy analysis to correlate between PLFA and soil chemistry data AVDAT SAYERET SHAKED

35. 28 Conclusions multivariate statistics suggest the occurrence of “microbial diversity patchiness” in the Negev desert Gram -ve anaerobe indicators (Cy17:0, Cy19:0) dominated the ISP while the Gram +ve indicators (i15:0, a15:0 and i16:0) were associated with SUC samples Halophyte plants may have a distinct effect influence on the community structure Nitrate, EC and OM have a significant bearing on microbial community structure

36. 29 EXAMPLE 2Microbial community succession along a desert rainfall gradient

37. 30 BSC have a significant role in desert ecosystems: Influencing overland runoff production, soil moisture content,water infiltration and holding capacity Preventing soil erosion by water or wind, and are responsible for the stabilization of sand dunes Improve soil fertility by production of organic carbon and nitrogen

39. 33 Geomorphological and biophysiological parameters of the biological soil crusts along the rainfall gradient

41. The samples of site 85 were dispersed throughout the diagram

42. 35 Relative abundance of PLFA indicator groups Significantly higher cyanobacteria in site 115 Significantly higher G+ve in site 62

43. 36 DGGE patterns of the three sites 115 85 62

44. 37 Ward's cluster analysis of the DGGE banding patterns of the three sites; 62, 85, and 115

45. 38 Phylogenetic distribution of prominent 16S rRNA gene sequences

46. 39 Conclusions Both methods showed that the northern site (62) microbial community was significantly different from the southern site (115). Site 115 was dominated by the resilient cyanobacteriaMicrocoleusvaginatus However, a shift to a more diverse population as seen in sites 85 and 62 may reflect development in the BSC succesional stage. Both methods correlated well with the geomorphological parameters

47. 40 Acknowledgments Many thanks to: Prof Ali Nejidat Dr Eli Tzaadi