Microbial Ecology Improved Strategy for Comparing Microbial Assemblage Fingerprints Ian Hewson and Jed A. Fuhrman Department of Biological Sciences, University of Southern California, 3616 Trousdale Pkwy AHF 107, Los Angeles, CA 90089-0371, USA Received: 13 July 2005 / Accepted: 19 September 2005 / Online publication: 1 February 2006 Abstract Microbial fingerprinting techniques permit the rapid visualization of entire assemblages in single assays, allowing direct comparison of communities in different samples, where the null hypothesis of such analyses is that all samples are the same. The comparison of fingerprints relies upon the precise estimation of all amplified DNA fragment lengths, which correspond to operational taxonomic units (OTU; analogous, but not equal to, a taxon in macroorganism studies). However, computer interpolation of size standards (and conse- quently OTU size calling) can be imprecise between gel runs, which can lead to imprecise calculation of simi- larity indices between multiple assemblages. To account for OTU size calling imprecision, all fragments within a range of sizes (a window) can be combined (i.e., ‘‘binned’’) where the window is as wide as the impreci- sion of OTU size calling. However, artifacts may occur upon binning samples that may cause samples to appear less similar to each other, caused by splitting of OTU between adjacent bin windows. In this work we present an improved binning technique that accounts for OTU size calling imprecision in the comparison of multiple fingerprints. This technique comprises binning all pair- wise comparisons in multiple bin window frames, where the starting size of the window (i.e., frame) is shifted by +1 bp for a total of x frames, where x bp is the width of the maximum bin window size in any binning scheme. Pairwise similarity indices between different community fingerprints are calculated for each of the x frames. To best address the null hypothesis of the community com- parison, the maximum similarity value of all x frames is then used in downstream analyses to compare the communities. We believe this binning technique provides the most accurate and least biased comparison between different microbial fingerprints. Introduction The study of microbial diversity in aquatic environments has recently attracted attention as a result of a growing awareness of the key roles that microorganisms play in marine and freshwater environments [2, 7, 8, 11, 22]. Among the methods used to examine microbial diversity, which include hybridization, DNA–DNA reannealing kinetics, cloning and sequencing of universally conserved genes (e.g., 16S and 23S), whole-genome shotgun sequenc- ing, and fluorescence in situ hybridization (reviewed in [12]), microbial community fingerprinting techniques offer a high-resolution view of operational taxonomic units (OTU) and can be argued as the most time- and cost- effective methods to observe clear differences between communities [1, 10]. Additionally, microbial community fingerprinting methods are promising because they allow entire assemblages to be visualized in single fingerprints, and then compared numerically to other assemblage fingerprints. Fingerprinting approaches include denatur- ing gradient gel electrophoresis (DGGE), which relies upon sequence (and therefore denaturing characteristics) [16, 25]; terminal restriction fragment length polymor- phism (TRFLP) on conserved genes, which also relies on heterogeneity in restriction digest sites between taxa [1]; and automated rRNA intergenic spacer analysis (ARISA), which uses 16S–23S intergenic spacer length heterogene- ity [3, 10]. TRFLP and ARISA are potentially more useful than DGGE for comparing communities, because they can be standardized between different runs and between different laboratories, and information on fragment lengths can be organized into a database and cross-referenced by other researchers [5, 14, 18, 19]. Correspondence to: Ian Hewson at present address: Department of Ocean Sciences, University of California, Santa Cruz, 1156 High Street EMS D446, Santa Cruz, CA 95604, USA; E-mail: hewson@ucsc.edu DOI: 10.1007/s00248-005-0144-9 & Volume 51, 147–153 (2006) & * Springer Science+Business Media, Inc. 2006 147