title: Interpreting ecological diversity indices applied to terminal restriction fragment length polymorphism data: insights from simulated microbial communities.
abstract: Ecological diversity indices are frequently applied to molecular profiling methods, such as terminal restriction fragment length polymorphism (T-RFLP), in order to compare diversity among microbial communities. We performed simulations to determine whether diversity indices calculated from T-RFLP profiles could reflect the true diversity of the underlying communities despite potential analytical artifacts. These include multiple taxa generating the same terminal restriction fragment (TRF) and rare TRFs being excluded by a relative abundance (fluorescence) threshold. True community diversity was simulated using the lognormal species abundance distribution. Simulated T-RFLP profiles were generated by assigning each species a TRF size based on an empirical or modeled TRF size distribution. With a typical threshold (1%), the only consistently useful relationship was between Smith and Wilson evenness applied to T-RFLP data (TRF-E(var)) and true Shannon diversity (H'), with correlations between 0.71 and 0.81. TRF-H' and true H' were well correlated in the simulations using the lowest number of species, but this correlation declined substantially in simulations using greater numbers of species, to the point where TRF-H' cannot be considered a useful statistic. The relationships between TRF diversity indices and true indices were sensitive to the relative abundance threshold, with greatly improved correlations observed using a 0.1% threshold, which was investigated for comparative purposes but is not possible to consistently achieve with current technology. In general, the use of diversity indices on T-RFLP data provides inaccurate estimates of true diversity in microbial communities (with the possible exception of TRF-E(var)). We suggest that, where significant differences in T-RFLP diversity indices were found in previous work, these should be reinterpreted as a reflection of differences in community composition rather than a true difference in community diversity.
authors.affiliation: Department of Biological Sciences, Kent State University, Kent, OH 44242, USA. cblackwo@kent.edu
authors.forename: Christopher B
authors.initials: CB
authors.lastname: Blackwood
authors.forename: Deborah
authors.initials: D
authors.lastname: Hudleston
authors.forename: Donald R
authors.initials: DR
authors.lastname: Zak
authors.forename: Jeffrey S
authors.initials: JS
authors.lastname: Buyer
mesh_terms: D000465:Algorithms; D001419:Bacteria / Q000145:classification / Q000235:genetics* / Q000254:growth & development; D044822:Biodiversity; D003198:Computer Simulation; D004269:DNA, Bacterial / Q000235:genetics / Q000378:metabolism; D004275:DNA, Ribosomal / Q000235:genetics / Q000378:metabolism; D008954:Models, Biological; D012150:Polymorphism, Restriction Fragment Length
chemical_list: D004269:DNA, Bacterial; D004275:DNA, Ribosomal