Estimating Bacterial Diversity for Ecological Studies: Methods,Metrics, and Assumptions

Methods to estimate microbial diversity have developed rapidly in an effort to understand the distribution and diversity of microorganisms in natural environments. For bacterial communities, the 16S rRNA gene is the phylogenetic marker gene of choice, but most studies select only a specific region of the 16S rRNA to estimate bacterial diversity. Whereas biases derived from from DNA extraction, primer choice and PCR amplification are well documented, we here address how the choice of variable region can influence a wide range of standard ecological metrics, such as species richness, phylogenetic diversity, β-diversity and rank-abundance distributions. We have used Illumina paired-end sequencing to estimate the bacterial diversity of 20 natural lakes across Switzerland derived from three trimmed variable 16S rRNA regions (V3, V4, V5). Species richness, phylogenetic diversity, community composition, β-diversity, and rank-abundance distributions differed significantly between 16S rRNA regions. Overall, patterns of diversity quantified by the V3 and V5 regions were more similar to one another than those assessed by the V4 region. Similar results were obtained when analyzing the datasets with different sequence similarity thresholds used during sequences clustering and when the same analysis was used on a reference dataset of sequences from the Greengenes database. In addition we also measured species richness from the same lake samples using ARISA Fingerprinting, but did not find a strong relationship between species richness estimated by Illumina and ARISA. We conclude that the selection of 16S rRNA region significantly influences the estimation of bacterial diversity and species distributions and that caution is warranted when comparing data from different variable regions as well as when using different sequencing techniques.     

Naive Bayesian classifier for rapid assignment of rRNA sequences into the new bacterial taxonomy

The Ribosomal Database Project (RDP) Classifier, a na?ve Bayesian classifier, can rapidly and accurately classify bacterial 16S rRNA sequences into the new higher-order taxonomy proposed in Bergey's Taxonomic Outline of the Prokaryotes (2nd ed., release 5.0, Springer-Verlag, New York, NY, 2004). It provides taxonomic assignments from domain to genus, with confidence estimates for each assignment. The majority of classifications (98%) were of high estimated confidence (> or = 95%) and high accuracy (98%). In addition to being tested with the corpus of 5,014 type strain sequences from Bergey's outline, the RDP Classifier was tested with a corpus of 23,095 rRNA sequences as assigned by the NCBI into their alternative higher-order taxonomy. The results from leave-one-out testing on both corpora show that the overall accuracies at all levels of confidence for near-full-length and 400-base segments were 89% or above down to the genus level, and the majority of the classification errors appear to be due to anomalies in the current taxonomies. For shorter rRNA segments, such as those that might be generated by pyrosequencing, the error rate varied greatly over the length of the 16S rRNA gene, with segments around the V2 and V4 variable regions giving the lowest error rates. The RDP Classifier is suitable both for the analysis of single rRNA sequences and for the analysis of libraries of thousands of sequences. Another related tool, RDP Library Compare, was developed to facilitate microbial-community comparison based on 16S rRNA gene sequence libraries. It combines the RDP Classifier with a statistical test to flag taxa differentially represented between samples. The RDP Classifier and RDP Library Compare are available online at http://rdp.cme.msu.edu/.     

Taxonomic Precision of Different Hypervariable Regions of 16S rRNA Gene and Annotation Methods for Functional Bacterial Groups in Biological Wastewater Treatment

High throughput sequencing of 16S rRNA gene leads us into a deeper understanding on bacterial diversity for complex environmental samples, but introduces blurring due to the relatively low taxonomic capability of short read. For wastewater treatment plant, only those functional bacterial genera categorized as nutrient remediators, bulk/foaming species, and potential pathogens are significant to biological wastewater treatment and environmental impacts. Precise taxonomic assignment of these bacteria at least at genus level is important for microbial ecological research and routine wastewater treatment monitoring. Therefore, the focus of this study was to evaluate the taxonomic precisions of different ribosomal RNA (rRNA) gene hypervariable regions generated from a mix activated sludge sample. In addition, three commonly used classification methods including RDP Classifier, BLAST-based best-hit annotation, and the lowest common ancestor annotation by MEGAN were evaluated by comparing their consistency. Under an unsupervised way, analysis of consistency among different classification methods suggests there are no hypervariable regions with good taxonomic coverage for all genera. Taxonomic assignment based on certain regions of the 16S rRNA genes, e.g. the V1&V2 regions – provide fairly consistent taxonomic assignment for a relatively wide range of genera. Hence, it is recommended to use these regions for studying functional groups in activated sludge. Moreover, the inconsistency among methods also demonstrated that a specific method might not be suitable for identification of some bacterial genera using certain 16S rRNA gene regions. As a general rule, drawing conclusions based only on one sequencing region and one classification method should be avoided due to the potential false negative results.     

Improved detection of bifidobacteria with optimised 16S rRNA-gene based pyrosequencing

The 16S rRNA gene is conserved across all bacteria and as such is routinely targeted in PCR surveys of bacterial diversity. PCR primer design aims to amplify as many different 16S rRNA gene sequences from as wide a range of organisms as possible, though there are no suitable 100% conserved regions of the gene, leading to bias. In the gastrointestinal tract, bifidobacteria are a key genus, but are often under-represented in 16S rRNA surveys of diversity. We have designed modified, 'bifidobacteria-optimised' universal primers, which we have demonstrated detection of bifidobacterial sequence present in DNA mixtures at 2% abundance, the lowest proportion tested. Optimisation did not compromise the detection of other organisms in infant faecal samples. Separate validation using fluorescence in situ hybridisation (FISH) shows that the proportions of bifidobacteria detected in faecal samples were in agreement with those obtained using 16S rRNA based pyrosequencing. For future studies looking at faecal microbiota, careful selection of primers will be key in order to ensure effective detection of bifidobacteria.     

Evaluation of different partial 16S rRNA gene sequence regions for phylogenetic analysis of microbiomes

Operational taxonomic units (OTUs) are conventionally defined at a phylogenetic distance (0.03—species, 0.05—genus, 0.10—family) based on full-length 16S rRNA gene sequences. However, partial sequences (700 bp or shorter) have been used in most studies. This discord may affect analysis of diversity and species richness because sequence divergence is not distributed evenly along the 16S rRNA gene. In this study, we compared a set each of bacterial and archaeal 16S rRNA gene sequences of nearly full length with multiple sets of different partial 16S rRNA gene sequences derived therefrom (approximately 440-700 bp), at conventional and alternative distance levels. Our objective was to identify partial sequence region(s) and distance level(s) that allow more accurate phylogenetic analysis of partial 16S rRNA genes. Our results showed that no partial sequence region could estimate OTU richness or define OTUs as reliably as nearly full-length genes. However, the V1-V4 regions can provide more accurate estimates than others. For analysis of archaea, we recommend the V1-V3 and the V4-V7 regions and clustering of species-level OTUs at 0.03 and 0.02 distances, respectively. For analysis of bacteria, the V1-V3 and the V1-V4 regions should be targeted, with species-level OTUs being clustered at 0.04 distance in both cases.     

Impact of training sets on classification of high-throughput bacterial 16s rRNA gene surveys

Taxonomic classification of the thousands–millions of 16S rRNA gene sequences generated in microbiome studies is often achieved using a naïve Bayesian classifier (for example, the Ribosomal Database Project II (RDP) classifier), due to favorable trade-offs among automation, speed and accuracy. The resulting classification depends on the reference sequences and taxonomic hierarchy used to train the model; although the influence of primer sets and classification algorithms have been explored in detail, the influence of training set has not been characterized. We compared classification results obtained using three different publicly available databases as training sets, applied to five different bacterial 16S rRNA gene pyrosequencing data sets generated (from human body, mouse gut, python gut, soil and anaerobic digester samples). We observed numerous advantages to using the largest, most diverse training set available, that we constructed from the Greengenes (GG) bacterial/archaeal 16S rRNA gene sequence database and the latest GG taxonomy. Phylogenetic clusters of previously unclassified experimental sequences were identified with notable improvements (for example, 50% reduction in reads unclassified at the phylum level in mouse gut, soil and anaerobic digester samples), especially for phylotypes belonging to specific phyla (Tenericutes, Chloroflexi, Synergistetes and Candidate phyla TM6, TM7). Trimming the reference sequences to the primer region resulted in systematic improvements in classification depth, and greatest gains at higher confidence thresholds. Phylotypes unclassified at the genus level represented a greater proportion of the total community variation than classified operational taxonomic units in mouse gut and anaerobic digester samples, underscoring the need for greater diversity in existing reference databases.     

Effect of primers hybridizing to different evolutionarily conserved regions of the small-subunit rRNA gene in PCR-based microbial community analyses and genetic profiling

Genetic profiling techniques of microbial communities based on PCR-amplified signature genes, such as denaturing gradient gel electrophoresis or single-strand-conformation polymorphism (SSCP) analysis, are normally done with PCR products of less than 500-bp. The most common target for diversity analysis, the small-subunit rRNA genes, however, are larger, and thus, only partial sequences can be analyzed. Here, we compared the results obtained by PCR targeting different variable (V) regions (V2 and V3, V4 and V5, and V6 to V8) of the bacterial 16S rRNA gene with primers hybridizing to evolutionarily conserved flanking regions. SSCP analysis of single-stranded PCR products generated from 13 different bacterial species showed fewer bands with products containing V4-V5 (average, 1.7 bands per organism) than with V2-V3 (2.2 bands) and V6-V8 (2.3 bands). We found that the additional bands (>1 per organism) were caused by intraspecies operon heterogeneities or by more than one conformation of the same sequence. Community profiles, generated by PCR-SSCP from bacterial-cell consortia extracted from rhizospheres of field-grown maize (Zea mays), were analyzed by cloning and sequencing of the dominant bands. A total of 48 sequences could be attributed to 34 different strains from 10 taxonomical groups. Independent of the primer pairs, we found proteobacteria (alpha, beta, and gamma subgroups) and members of the genus Paenibacillus (low G+C gram-positive) to be the dominant organisms. Other groups, however, were only detected with single primer pairs. This study gives an example of how much the selection of different variable regions combined with different specificities of the flanking "universal" primers can affect a PCR-based microbial community analysis.     

Acidobacteria form a coherent but highly diverse group within the bacterial domain: evidence from environmental genomics

Acidobacteria have been established as a novel phylum of Bacteria that is consistently detected in many different habitats around the globe by 16S rDNA-based molecular surveys. The phylogenetic diversity, ubiquity and abundance of this group, particularly in soil habitats, suggest an important ecological role and extensive metabolic versatility. However, the genetic and physiological information about Acidobacteria is scarce. In order to gain insight into genome structure, evolution and diversity of these microorganisms we have initiated an environmental genomic approach by constructing large insert libraries directly from DNA of a calcerous grassland soil. Genomic fragments of Acidobacteria were identified with specific 16S rDNA probes and sequence analyses of six independently identified clones were performed, representing in total more than 210,000 bp. The 16S rRNA genes of the genomic fragments differed between 2.3% and 19.9% and were placed into two different subgroups of Acidobacteria (groups III and V). Although partial co-linearity was found between genomic fragments, the gene content around the rRNA operons was generally not conserved. Phylogenetic reconstructions with orthologues that were encoded on two of the six genomic fragments (PurF, PurL, PurB and formamidopyrimidine-DNA glycosylase) confirmed the coherence of the acidobacterial phylum. One genomic fragment harboured a cluster of eight genes which was syntenic and highly homologous to genomic regions in Rhodopseudomonas palustris and Bradyrhizobium japonicum, including a conserved two-component system. Phylogenetic analysis of the putative response regulator confirmed that this similarity between Rhizobiales and Acidobacteria might be due to a horizontal gene transfer. In total, our data give first insight into the genome content and diversity of the ubiquitously distributed but poorly characterized phylum of Acidobacteria. Furthermore they support the phylogenetic inferences made from 16S rRNA gene libraries, suggesting that Acidobacteria form a broad group in the same sense and with a similar diversity as that of many well-studied bacterial phyla.     

Phylogenetic diversity of bacteria in an earth-cave in Guizhou province, southwest of China

The objective of this study was to analyze the phylogenetic composition of bacterial community in the soil of an earth-cave (Niu Cave) using a culture-independent molecular approach. 16S rRNA genes were amplified directly from soil DNA with universally conserved and Bacteria-specific rRNA gene primers and cloned. The clone library was screened by restriction fragment length polymorphism (RFLP), and representative rRNA gene sequences were determined. A total of 115 bacterial sequence types were found in 190 analyzed clones. Phylogenetic sequence analyses revealed novel 16S rRNA gene sequence types and a high diversity of putative bacterial community. Members of these bacteria included Proteobacteria (42.6%), Acidobacteria (18.6%), Planctomycetes (9.0%), Chloroflexi (Green nonsulfur bacteria, 7.5%), Bacteroidetes (2.1%), Gemmatimonadetes (2.7%), Nitrospirae (8.0%), Actinobacteria (High G+C Gram-positive bacteria, 6.4%) and candidate divisions (including the OP3, GN08, and SBR1093, 3.2%). Thirty-five clones were affiliated with bacteria that were related to nitrogen, sulfur, iron or manganese cycles. The comparison of the present data with the data obtained previously from caves based on 16S rRNA gene analysis revealed similarities in the bacterial community components, especially in the high abundance of Proteobacteria and Acidobacteria. Furthermore, this study provided the novel evidence for presence of Gemmatimonadetes, Nitrosomonadales, Oceanospirillales, and Rubrobacterales in a karstic hypogean environment.     

Effect of Primers Hybridizing to Different Evolutionarily Conserved Regions of the Small-Subunit rRNA Gene in PCR-Based Microbial Community Analyses and Genetic Profiling

Genetic profiling techniques of microbial communities based on PCR-amplified signature genes, such as denaturing gradient gel electrophoresis or single-strand-conformation polymorphism (SSCP) analysis, are normally done with PCR products of less than 500-bp. The most common target for diversity analysis, the small-subunit rRNA genes, however, are larger, and thus, only partial sequences can be analyzed. Here, we compared the results obtained by PCR targeting different variable (V) regions (V2 and V3, V4 and V5, and V6 to V8) of the bacterial 16S rRNA gene with primers hybridizing to evolutionarily conserved flanking regions. SSCP analysis of single-stranded PCR products generated from 13 different bacterial species showed fewer bands with products containing V4-V5 (average, 1.7 bands per organism) than with V2-V3 (2.2 bands) and V6-V8 (2.3 bands). We found that the additional bands (>1 per organism) were caused by intraspecies operon heterogeneities or by more than one conformation of the same sequence. Community profiles, generated by PCR-SSCP from bacterial-cell consortia extracted from rhizospheres of field-grown maize (Zea mays), were analyzed by cloning and sequencing of the dominant bands. A total of 48 sequences could be attributed to 34 different strains from 10 taxonomical groups. Independent of the primer pairs, we found proteobacteria (α, β, and γ subgroups) and members of the genus Paenibacillus (low G+C gram-positive) to be the dominant organisms. Other groups, however, were only detected with single primer pairs. This study gives an example of how much the selection of different variable regions combined with different specificities of the flanking “universal” primers can affect a PCR-based microbial community analysis.     

Genetic diversity of bacterial strains isolated from soils, contaminated with polycyclic aromatic hydrocarbons, by 16S rRNA gene sequencing and amplified fragment length polymorphism fingerprinting

In order to study microbial diversity in a polycyclic aromatic hydrocarbon-impacted soil, 14 bacterial strains were analyzed by 16S rRNA gene sequencing and amplified fragment length polymorphism (AFLP) analysis. Bacterial strains isolated from two different hydrocarbon-polluted sites were identified to the species level by 16S rRNA full-gene sequencing using MicroSeq 16S rRNA gene sequencing. Their genome was subsequently analyzed by high-resolution genotyping with AFLP analysis, in order to monitor species variability and to differentiate closely related strains. Cluster analysis based on AFLP fingerprinting showed intra-specific polymorphism, even among strains with 100% 16S rRNA gene sequence identity. The results show that AFLP is a powerful, highly reproducible and discriminatory tool for revealing genetic relationships in bacterial populations. The ability to differentiate and track related closely microbes is fundamental for studying structure and dynamics of microbial communities in contaminated ecosystems.     

Generation of multimillion-sequence 16S rRNA gene libraries from complex microbial communities by assembling paired-end illumina reads

Microbial communities host unparalleled taxonomic diversity. Adequate characterization of environmental and host-associated samples remains a challenge for microbiologists, despite the advent of 16S rRNA gene sequencing. In order to increase the depth of sampling for diverse bacterial communities, we developed a method for sequencing and assembling millions of paired-end reads from the 16S rRNA gene (spanning the V3 region; ～200 nucleotides) by using an Illumina genome analyzer. To confirm reproducibility and to identify a suitable computational pipeline for data analysis, sequence libraries were prepared in duplicate for both a defined mixture of DNAs from known cultured bacterial isolates (>1 million postassembly sequences) and an Arctic tundra soil sample (>6 million postassembly sequences). The Illumina 16S rRNA gene libraries represent a substantial increase in number of sequences over all extant next-generation sequencing approaches (e.g., 454 pyrosequencing), while the assembly of paired-end 125-base reads offers a methodological advantage by incorporating an initial quality control step for each 16S rRNA gene sequence. This method incorporates indexed primers to enable the characterization of multiple microbial communities in a single flow cell lane, may be modified readily to target other variable regions or genes, and demonstrates unprecedented and economical access to DNAs from organisms that exist at low relative abundances.     

引物应用策略：基于2对古菌16S rRNA基因通用引物对环境样品古菌多样性分析

【目的】找到适宜的16S rRNA基因通用引物应用策略,应对复杂环境微生物多样性调查,尤其目前高速发展的高通量测序技术带来的巨大挑战。【方法】用Oligocheck软件分别将两对应试的古菌16S rRNA基因通用引物与RDP(Ribosomal database project)数据库中古菌16S rRNA基因序列进行匹配比对。用两对应试引物分别构建海洋沉积物样品的古菌16S rRNA基因文库。【结果】软件匹配结果显示引物f109/r958与目的基因的匹配程度高于引物f21/r958。该结果与古菌16S rRNA基因文库RFLP分析、古菌多样性指数分析结果相吻合。数据还表明,2对引物的综合文库能更好满足该沉积物样品的古菌多样性分析。【结论】选用与数据库中目的基因匹配性高的通用引物和多个引物的联合使用,可以有效提高环境样品微生物多样性调查的分辨率。     

Biased Diversity Metrics Revealed by Bacterial 16S Pyrotags Derived from Different Primer Sets

In recent years, PCR-based pyrosequencing of 16S rRNA genes has continuously increased our understanding of complex microbial communities in various environments of the Earth. However, there is always concern on the potential biases of diversity determination using different 16S rRNA gene primer sets and covered regions. Here, we first report how bacterial 16S rRNA gene pyrotags derived from a series of different primer sets resulted in the biased diversity metrics. In total, 14 types of pyrotags were obtained from two-end pyrosequencing of 7 amplicon pools generated by 7 primer sets paired by 1 of 4 forward primers (V1F, V3F, V5F, and V7F) and 1 of 4 reverse primers (V2R, V4R, V6R, and V9R), respectively. The results revealed that: i) the activated sludge exhibited a large bacterial diversity that represented a broad range of bacterial populations and served as a good sample in this methodology research; ii) diversity metrics highly depended on the selected primer sets and covered regions; iii) paired pyrotags obtained from two-end pyrosequencing of each short amplicon displayed different diversity metrics; iv) relative abundance analysis indicated the sequencing depth affected the determination of rare bacteria but not abundant bacteria; v) the primer set of V1F and V2R significantly underestimated the diversity of activated sludge; and vi) the primer set of V3F and V4R was highly recommended for future studies due to its advantages over other primer sets. All of these findings highlight the significance of this methodology research and offer a valuable reference for peer researchers working on microbial diversity determination.     

Salinity and Bacterial Diversity: To What Extent Does the Concentration of Salt Affect the Bacterial Community in a Saline Soil?

In this study, the evaluation of soil characteristics was coupled with a pyrosequencing analysis of the V2-V3 16S rRNA gene region in order to investigate the bacterial community structure and diversity in the A horizon of a natural saline soil located in Sicily (Italy). The main aim of the research was to assess the organisation and diversity of microbial taxa using a spatial scale that revealed physical and chemical heterogeneity of the habitat under investigation. The results provided information on the type of distribution of different bacterial groups as a function of spatial gradients of soil salinity and pH. The analysis of bacterial 16S rRNA showed differences in bacterial composition and diversity due to a variable salt concentration in the soil. The bacterial community showed a statistically significant spatial variability. Some bacterial phyla appeared spread in the whole area, whatever the salinity gradient. It emerged therefore that a patchy saline soil can not contain just a single microbial community selected to withstand extreme osmotic phenomena, but many communities that can be variously correlated to one or more environmental parameters. Sequences have been deposited to the SRA database and can be accessed on ID Project PRJNA241061.     

An assessment of actinobacterial diversity in the marine environment

The 16S rRNA gene sequence diversity within the Phylum Actinobacteria was assessed from four sources: PCR-generated V6 sequence tags derived from seawater samples, metagenomic data from the Global Ocean Sampling (GOS) expedition, marine-derived sequences maintained in the Ribosomal Database Project (RDP), and select cultured strains for which sequence data is not yet available in the RDP. This meta-analysis revealed remarkable levels of phylogenetic diversity and confirms the existence of major, deeply rooted, and as of yet uncharacterized lineages within the phylum. A dramatic incongruence among cultured strains and those detected using culture-independent techniques was also revealed. Redundancy among the actinobacteria detected using culture-independent techniques suggests that greater sequence coverage or improved DNA extraction efficiencies may be required to detect the rare phylotypes that can be readily cultured from marine samples. Conversely, new strategies need to be developed for the cultivation of frequently observed but yet to be cultured marine actinobacteria.     

Diversity in methane enrichments from agricultural soil revealed by DGGE separation of PCR amplified 16S rDNA fragments

Denaturing gradient gel electrophoresis (DGGE) profiles of PCR amplified V3 regions of 16S rRNA genes were used to assess the diversity in enrichment cultures with methane as the only carbon and energy source. The enrichments originated from two agricultural soils. One was a sandy soil with low (10%) organic content, the other an organic soil with approximately 50% organic content. DGGE provided a fast evaluation of the distribution of amplifiable sequence types indicating that specific bacterial populations had been enriched from each soil. The DGGE profiles revealed a broader range of amplified V3 fragments in the community derived from organic soil than from sandy soil. Fragments from 19 individual DGGE bands were sequenced and compared with 27 previously published 16S rRNA gene sequences. The sequences confirmed the high diversity with the presence of different methylotrophic populations in each enrichment. No affiliation was found with type I methanotrophs, instead type II methanotroph sequences were found in the enrichments from both soil types. Some of the fragments from the organic soil enrichment were not affiliated with methylotrophs. Most of the sequences clustered distantly on a branch within the α-Proteobacteria. These facts suggested that previously undescribed methylotrophs are abundant in methane enrichments from agricultural soil.     

The Effect of Primer Choice and Short Read Sequences on the Outcome of 16S rRNA Gene Based Diversity Studies

Different regions of the bacterial 16S rRNA gene evolve at different evolutionary rates. The scientific outcome of short read sequencing studies therefore alters with the gene region sequenced. We wanted to gain insight in the impact of primer choice on the outcome of short read sequencing efforts. All the unknowns associated with sequencing data, i.e. primer coverage rate, phylogeny, OTU-richness and taxonomic assignment, were therefore implemented in one study for ten well established universal primers (338f/r, 518f/r, 799f/r, 926f/r and 1062f/r) targeting dispersed regions of the bacterial 16S rRNA gene. All analyses were performed on nearly full length and in silico generated short read sequence libraries containing 1175 sequences that were carefully chosen as to present a representative substitute of the SILVA SSU database. The 518f and 799r primers, targeting the V4 region of the 16S rRNA gene, were found to be particularly suited for short read sequencing studies, while the primer 1062r, targeting V6, seemed to be least reliable. Our results will assist scientists in considering whether the best option for their study is to select the most informative primer, or the primer that excludes interferences by host-organelle DNA. The methodology followed can be extrapolated to other primers, allowing their evaluation prior to the experiment.     

Influence of long‐term land application of Class B biosolids on soil bacterial diversity

Aim: To evaluate the effect of long‐term annual land applications of Class B biosolids on soil bacterial diversity at University of Arizona Marana Agricultural Field Center, Tucson, Arizona. Methods and Results: Following the final of 20 consecutive years of application of Class B biosolids in March 2005, followed by cotton growth from April to November 2005 surface soil samples (0–30 cm) were collected from control (unamended) and biosolid‐amended plots. Total bacterial community DNA was extracted, amplified using 16S rRNA primers, cloned, and sequenced. All 16S rRNA sequences were identified by 16S rRNA sequence analysis and comparison to known sequences in GenBank (NCBI Blast N and Ribosomal Database Project II, RDP). Results showed that the number of known genera (identifiable > 96%) increased in the high rate biosolid plots compared to control plots. Biosolids‐amended soils had a broad phylogenetic diversity comprising more than four major phyla: Proteobacteria (32%), Acidobacteria (21%), Actinobacteria (16%), Firmicutes (7%), and Bacteroidetes (6%) which were typical to bacterial diversity found in the unamended arid southwestern soils. Conclusion: Bacterial diversity was either enhanced or was not negatively impacted following 20 years of land application of Class B biosolids. Significance and Impact of the Study: This study illustrates that long‐term land application of biosolids to arid southwestern desert soils has no deleterious effect on soil microbial diversity.