Comparison of Quantitative PCR and Droplet Digital PCR Multiplex Assays for Two Genera of Bloom-Forming Cyanobacteria,Cylindrospermopsis and Microcystis

The increasing occurrence of harmful cyanobacterial blooms, often linked to deteriorated water quality and adverse public health effects, has become a worldwide concern in recent decades. The use of molecular techniques such as real-time quantitative PCR (qPCR) has become increasingly popular in the detection and monitoring of harmful cyanobacterial species. Multiplex qPCR assays that quantify several toxigenic cyanobacterial species have been established previously; however, there is no molecular assay that detects several bloom-forming species simultaneously. Microcystis and Cylindrospermopsis are the two most commonly found genera and are known to be able to produce microcystin and cylindrospermopsin hepatotoxins. In this study, we designed primers and probes which enable quantification of these genera based on the RNA polymerase C1 gene for Cylindrospermopsis species and the c-phycocyanin beta subunit-like gene for Microcystis species. Duplex assays were developed for two molecular techniques—qPCR and droplet digital PCR (ddPCR). After optimization, both qPCR and ddPCR assays have high linearity and quantitative correlations for standards. Comparisons of the two techniques showed that qPCR has higher sensitivity, a wider linear dynamic range, and shorter analysis time and that it was more cost-effective, making it a suitable method for initial screening. However, the ddPCR approach has lower variability and was able to handle the PCR inhibition and competitive effects found in duplex assays, thus providing more precise and accurate analysis for bloom samples.     

Detection of MET Gene Copy Number in Cancer Samples Using the Droplet Digital PCR Method

Purpose

The analysis of MET gene copy number (CN) has been considered to be a potential biomarker to predict the response to MET-targeted therapies in various cancers. However, the current standard methods to determine MET CN are SNP 6.0 in the genomic DNA of cancer cell lines and fluorescence in situ hybridization (FISH) in tumor models, respectively, which are costly and require advanced technical skills and result in relatively subjective judgments. Therefore, we employed a novel method, droplet digital PCR (ddPCR), to determine the MET gene copy number with high accuracy and precision.

Methods

The genomic DNA of cancer cell lines or tumor models were tested and compared with the MET gene CN and MET/CEN-7 ratio determined by SNP 6.0 and FISH, respectively.

Results

In cell lines, the linear association of the MET CN detected by ddPCR and SNP 6.0 is strong (Pearson correlation = 0.867). In tumor models, the MET CN detected by ddPCR was significantly different between the MET gene amplification and non-amplification groups according to FISH (mean: 15.4 vs 2.1; P = 0.044). Given that MET gene amplification is defined as MET CN >5.5 by ddPCR, the concordance rate between ddPCR and FISH was 98.0%, and Cohen''s kappa coefficient was 0.760 (95% CI, 0.498–1.000; P <0.001).

Conclusions

The results demonstrated that the ddPCR method has the potential to quantify the MET gene copy number with high precision and accuracy as compared with the results from SNP 6.0 and FISH in cancer cell lines and tumor samples, respectively.     

A Comparison between Transcriptome Sequencing and 16S Metagenomics for Detection of Bacterial Pathogens in Wildlife

Background

Rodents are major reservoirs of pathogens responsible for numerous zoonotic diseases in humans and livestock. Assessing their microbial diversity at both the individual and population level is crucial for monitoring endemic infections and revealing microbial association patterns within reservoirs. Recently, NGS approaches have been employed to characterize microbial communities of different ecosystems. Yet, their relative efficacy has not been assessed. Here, we compared two NGS approaches, RNA-Sequencing (RNA-Seq) and 16S-metagenomics, assessing their ability to survey neglected zoonotic bacteria in rodent populations.

Methodology/Principal Findings

We first extracted nucleic acids from the spleens of 190 voles collected in France. RNA extracts were pooled, randomly retro-transcribed, then RNA-Seq was performed using HiSeq. Assembled bacterial sequences were assigned to the closest taxon registered in GenBank. DNA extracts were analyzed via a 16S-metagenomics approach using two sequencers: the 454 GS-FLX and the MiSeq. The V4 region of the gene coding for 16S rRNA was amplified for each sample using barcoded universal primers. Amplicons were multiplexed and processed on the distinct sequencers. The resulting datasets were de-multiplexed, and each read was processed through a pipeline to be taxonomically classified using the Ribosomal Database Project. Altogether, 45 pathogenic bacterial genera were detected. The bacteria identified by RNA-Seq were comparable to those detected by 16S-metagenomics approach processed with MiSeq (16S-MiSeq). In contrast, 21 of these pathogens went unnoticed when the 16S-metagenomics approach was processed via 454-pyrosequencing (16S-454). In addition, the 16S-metagenomics approaches revealed a high level of coinfection in bank voles.

Conclusions/Significance

We concluded that RNA-Seq and 16S-MiSeq are equally sensitive in detecting bacteria. Although only the 16S-MiSeq method enabled identification of bacteria in each individual reservoir, with subsequent derivation of bacterial prevalence in host populations, and generation of intra-reservoir patterns of bacterial interactions. Lastly, the number of bacterial reads obtained with the 16S-MiSeq could be a good proxy for bacterial prevalence.     

Bacterial diversity in two coastal lagoons deduced from 16S rDNA PCR amplification and partial sequencing

Abstract: Amplification and sequence analysis of the 16S rRNA genes from DNA samples extracted directly from the environment allows the study of microbial diversity in natural ecosystems without the need for cultivation. In this study this methodology has been applied to two coastal lagoons. Activity and numbers of heterotrophic bacteria have indicated that, as expected, Prévost lagoon (located on the French Mediterranean coast) is more eutrophic than that of the Arcachon Bay (French Atlantic coast). Analysis of partial 16S rRNA gene sequences revealed that, in both environments, a relatively large number of clones related to Cytophaga/Flexibacter/Bacteroides as well as to α-Proteobacteria were found. One hundred percent similarity with the sequences of the data bases were not found for any of the more than a hundred clones studied, in fact for most clones maximum similarity was below 95% for the approx. 200 bases sequenced. Similarity was not higher with any of the sequences found for the 14 isolates (pure cultures) obtained from the same samples. Redundancy, i.e. number of identical sequences, was higher in the samples from Arcachon. In addition, sequences related to representatives of ten major phylogenetic branches of Bacteria were obtained from Prévost lagoon; however only five branches were represented by the data from Arcachon. These findings indicated a higher bacterial phylogenetic diversity in the Prévost lagoon.     

Analysis of the Cystic Fibrosis Lung Microbiota via Serial Illumina Sequencing of Bacterial 16S rRNA Hypervariable Regions

The characterization of bacterial communities using DNA sequencing has revolutionized our ability to study microbes in nature and discover the ways in which microbial communities affect ecosystem functioning and human health. Here we describe Serial Illumina Sequencing (SI-Seq): a method for deep sequencing of the bacterial 16S rRNA gene using next-generation sequencing technology. SI-Seq serially sequences portions of the V5, V6 and V7 hypervariable regions from barcoded 16S rRNA amplicons using an Illumina short-read genome analyzer. SI-Seq obtains taxonomic resolution similar to 454 pyrosequencing for a fraction of the cost, and can produce hundreds of thousands of reads per sample even with very high multiplexing. We validated SI-Seq using single species and mock community controls, and via a comparison to cystic fibrosis lung microbiota sequenced using 454 FLX Titanium. Our control runs show that SI-Seq has a dynamic range of at least five orders of magnitude, can classify >96% of sequences to the genus level, and performs just as well as 454 and paired-end Illumina methods in estimation of standard microbial ecology diversity measurements. We illustrate the utility of SI-Seq in a pilot sample of central airway secretion samples from cystic fibrosis patients.     

Comparison of the SuperARMS and Droplet Digital PCR for Detecting EGFR Mutation in ctDNA From NSCLC Patients

BACKGROUND: Liquid biopsy is emerging as an important approach for tumor genotyping in non-small cell lung cancer, ddPCR and SuperARMS are both methods with high sensitivity and specificity for detecting EGFR mutation in plasma. We aimed to compare ddPCR and SuperARMS to detect plasma EGFR status in a cohort of advanced NSCLC patients. METHOD: A total of 79 tumor tissues and paired plasma samples were collected. The EGFR mutation status in tissue was tested by ADx-ARMS, matched plasma was detected by ddPCR and SuperARMS, respectively. RESULTS: The EGFR mutation rates were identified as 64.6% (tissue, ARMS), 55.7% (plasma, ddPCR), and 49.4% (plasma, Super ARMS), respectively. The sensitivity of ddPCR was similar with Super-ARMS in plasma EGFR detection (80.4% vs 76.5%), as well as the specificity (89.3% vs 100%). And the McNemar’s test showed there was no significant difference (P = .125). The concordance rate between SuperARMS and ddPCR was 91.1%. A significant interaction was observed between cfDNA EGFR mutation status and EGFR-TKIs treatment tested by both methods. CONCLUSION: Super-ARMS and ddPCR share the similar accuracy for EGFR mutation detection in plasma biopsy; both methods predicted well the efficacy of EGFR-TKIs by detecting plasma EGFR status.     

Natural Course of Chlamydia trachomatis Bacterial Load in the Time Interval between Screening and Treatment in Anogenital Samples

Introduction

Although Chlamydia trachomatis (CT) is the most common bacterial sexually transmitted infection worldwide, little is known about the natural course of the bacterial load during infection. We investigated the natural course of the bacterial load in the interval between screening and returning for treatment in genital and anorectal CT-infections.

Materials & Methods

CT-positive patients, visiting our STI-clinic in the Netherlands from June 2011–January 2014, provided a second urogenital and/or anorectal sample when returning for treatment (diagnostic sample = T1; treatment sample = T2). Patient-record provided data about the days between samples and the date of last unsafe sex. Included patients were ≥18 years old, HIV-negative and did not report antibiotic use in the study-interval. CT load was quantified using qPCR. CT load was log-transformed, and a CT load difference (Δ-CT load) of >1 log was deemed clinically relevant. Chi-square test compared load category distributions over time (decrease/equal/increase), between sample types.

Results

274 patients provided 296 paired samples. Majority of samples had a stable CT load in the interval T1-T2 (66.3%, 73.1% and 48.6% for vaginal swabs, urine and anorectal swabs resp. p = 0.07). Load decreased in 17–41% of patients, while ±10% of patients showed an increase in CT load. No association between Δ-CT load and the interval T1-T2 was observed. Large variations can be seen in CT load at T1 and over time.

Discussion

The majority (±90%) of patients have a stable or decreasing CT load in the time interval between screening and returning for treatment. The number of days between sampling was not associated with change in CT load. In the first month after the last unsafe sex, only stable CT loads were seen. Our data seems to indicate that when most patients visit an STI-clinic, recommended 2 weeks after infection, the infection has already been established or is in its downward phase.     

A Hybrid DNA Extraction Method for the Qualitative and Quantitative Assessment of Bacterial Communities from Poultry Production Samples

The efficacy of DNA extraction protocols can be highly dependent upon both the type of sample being investigated and the types of downstream analyses performed. Considering that the use of new bacterial community analysis techniques (e.g., microbiomics, metagenomics) is becoming more prevalent in the agricultural and environmental sciences and many environmental samples within these disciplines can be physiochemically and microbiologically unique (e.g., fecal and litter/bedding samples from the poultry production spectrum), appropriate and effective DNA extraction methods need to be carefully chosen. Therefore, a novel semi-automated hybrid DNA extraction method was developed specifically for use with environmental poultry production samples. This method is a combination of the two major types of DNA extraction: mechanical and enzymatic. A two-step intense mechanical homogenization step (using bead-beating specifically formulated for environmental samples) was added to the beginning of the “gold standard” enzymatic DNA extraction method for fecal samples to enhance the removal of bacteria and DNA from the sample matrix and improve the recovery of Gram-positive bacterial community members. Once the enzymatic extraction portion of the hybrid method was initiated, the remaining purification process was automated using a robotic workstation to increase sample throughput and decrease sample processing error. In comparison to the strict mechanical and enzymatic DNA extraction methods, this novel hybrid method provided the best overall combined performance when considering quantitative (using 16S rRNA qPCR) and qualitative (using microbiomics) estimates of the total bacterial communities when processing poultry feces and litter samples.     

Comparative Analysis of Cell-Associated HIV DNA Levels in Cerebrospinal Fluid and Peripheral Blood by Droplet Digital PCR

Background

Measurement of HIV DNA-bearing cells in cerebrospinal fluid (CSF) is challenging because few cells are present. We present a novel application of the sensitive droplet digital (dd)PCR in this context.

Methods

We analyzed CSF cell pellets and paired peripheral blood mononuclear cells (PBMC) from 28 subjects, 19 of whom had undetectable HIV RNA (<48 copies/mL) in both compartments. We extracted DNA from PBMC using silica-based columns and used direct lysis on CSF cells. HIV DNA and the host housekeeping gene (RPP30) were measured in CSF and PBMC by (dd)PCR. We compared HIV DNA levels in virally-suppressed and-unsuppressed subgroups and calculated correlations between HIV DNA and RNA levels in both compartments using non-parametric tests.

Results

HIV DNA was detected in 18/28 (64%) CSF cell pellets, including 10/19 (53%) samples with undetectable HIV RNA. HIV DNA levels in CSF cell pellets were not correlated with RPP30 (p = 0.3), but correlated positively with HIV RNA in CSF (p = 0.04) and HIV DNA in PBMC (p = 0.03). Cellular HIV DNA in CSF was detected in comparable levels in HIV RNA-suppressed and unsuppressed subjects (p = 0.14). In contrast, HIV DNA levels in PBMC were significantly lower in HIV RNA-suppressed than in unsuppressed subjects (p = 0.014). Among subjects with detectable HIV DNA in both compartments, HIV DNA levels in CSF were significantly higher than in PBMC (p<0.001).

Conclusions

Despite low mononuclear cell numbers in CSF, HIV DNA was detected in most virally suppressed individuals. In contrast to PBMC, suppressive ART was not associated with lower HIV DNA levels in CSF cells, compared to no ART, perhaps due to poorer ART penetration, slower decay of HIV DNA, or enrichment of HIV DNA-bearing mononuclear cells into the CSF, compared to blood. Future studies should determine what fraction of HIV DNA is replication-competent in CSF leukocytes, compared to PBMC.     

A Highly Selective PCR Protocol for Detecting 16S rRNA Genes of the Genus Pseudomonas (Sensu Stricto) in Environmental Samples

Pseudomonas species are plant, animal, and human pathogens; exhibit plant pathogen-suppressing properties useful in biological control; or express metabolic versatilities valued in biotechnology and bioremediation. Specific detection of Pseudomonas species in the environment may help us gain a more complete understanding of the ecological significance of these microorganisms. The objective of this study was to develop a PCR protocol for selective detection of Pseudomonas (sensu stricto) in environmental samples. Extensive database searches identified a highly selective PCR primer pair for amplification of Pseudomonas 16S rRNA genes. A protocol that included PCR amplification and restriction analysis, a general cloning and sequencing strategy, and phylogenetic analyses was developed. The PCR protocol was validated by testing 50 target and 14 nontarget pure cultures, which confirmed the selectivity to 100%. Further validation used amplification of target sequences from purified bulk soil DNA followed by cloning of PCR products. Restriction analysis with HaeIII revealed eight different fragmentation patterns among 36 clones. Sequencing and phylogenetic analysis of 8 representative clones indicated that 91.7% of the products were derived from target organisms of the PCR protocol. Three patterns, representing only 8.3% of the 36 clones, were derived from non-Pseudomonas or chimeric PCR artifacts. Three patterns, representing 61.1% of the clones, clustered with sequences of confirmed Pseudomonas species, whereas two patterns, representing 30.6% of the clones, formed a novel phylogenetic cluster closely associated with Pseudomonas species. The results indicated that the Pseudomonas-selective PCR primers were highly specific and may represent a powerful tool for Pseudomonas population structure analyses and taxonomic confirmations.     

Evaluation of PCR Primer Selectivity and Phylogenetic Specificity by Using Amplification of 16S rRNA Genes from Betaproteobacterial Ammonia-Oxidizing Bacteria in Environmental Samples

The effect of primer specificity for studying the diversity of ammonia-oxidizing betaproteobacteria (βAOB) was evaluated. βAOB represent a group of phylogenetically related organisms for which the 16S rRNA gene approach is especially suitable. We used experimental comparisons of primer performance with water samples, together with an in silico analysis of published sequences and a literature review of clone libraries made with four specific PCR primers for the βAOB 16S rRNA gene. With four aquatic samples, the primers NitA/NitB produced the highest frequency of ammonia-oxidizing-bacterium-like sequences compared to clone libraries with products amplified with the primer combinations βAMOf/βAMOr, βAMOf/Nso1255g, and NitA/Nso1225g. Both the experimental examination of ammonia-oxidizing-bacterium-specific 16S rRNA gene primers and the literature search showed that neither specificity nor sensitivity of primer combinations can be evaluated reliably only by sequence comparison. Apparently, the combination of sequence comparison and experimental data is the best approach to detect possible biases of PCR primers. Although this study focused on βAOB, the results presented here more generally exemplify the importance of primer selection and potential primer bias when analyzing microbial communities in environmental samples.     

Similar Gene Estimates from Circular and Linear Standards in Quantitative PCR Analyses Using the Prokaryotic 16S rRNA Gene as a Model

Quantitative PCR (qPCR) is one of the most widely used tools for quantifying absolute numbers of microbial gene copies in test samples. A recent publication showed that circular plasmid DNA standards grossly overestimated numbers of a target gene by as much as 8-fold in a eukaryotic system using quantitative PCR (qPCR) analysis. Overestimation of microbial numbers is a serious concern in industrial settings where qPCR estimates form the basis for quality control or mitigation decisions. Unlike eukaryotes, bacteria and archaea most commonly have circular genomes and plasmids and therefore may not be subject to the same levels of overestimation. Therefore, the feasibility of using circular DNA plasmids as standards for 16S rRNA gene estimates was assayed using these two prokaryotic systems, with the practical advantage being rapid standard preparation for ongoing qPCR analyses. Full-length 16S rRNA gene sequences from Thermovirga lienii and Archaeoglobus fulgidus were cloned and used to generate standards for bacterial and archaeal qPCR reactions, respectively. Estimates of 16S rRNA gene copies were made based on circular and linearized DNA conformations using two genomes from each domain: Desulfovibrio vulgaris, Pseudomonas aeruginosa, Archaeoglobus fulgidus, and Methanocaldocococcus jannaschii. The ratio of estimated to predicted 16S rRNA gene copies ranged from 0.5 to 2.2-fold in bacterial systems and 0.5 to 1.0-fold in archaeal systems, demonstrating that circular plasmid standards did not lead to the gross over-estimates previously reported for eukaryotic systems.     

16S Ribosomal DNA-Based Analysis of Bacterial Diversity in Purified Water Used in Pharmaceutical Manufacturing Processes by PCR and Denaturing Gradient Gel Electrophoresis

The bacterial community in partially purified water, which is prepared by ion exchange from tap water and is used in pharmaceutical manufacturing processes, was analyzed by denaturing gradient gel electrophoresis (DGGE). 16S ribosomal DNA fragments, including V6, -7, and -8 regions, were amplified with universal primers and analyzed by DGGE. The bacterial diversity in purified water determined by PCR-DGGE banding patterns was significantly lower than that of other aquatic environments. The bacterial populations with esterase activity sorted by flow cytometry and isolated on soybean casein digest (SCD) and R2A media were also analyzed by DGGE. The dominant bacterium in purified water possessed esterase activity but could not be detected on SCD or R2A media. DNA sequence analysis of the main bands on the DGGE gel revealed that culturable bacteria on these media were Bradyrhizobium sp., Xanthomonas sp., and Stenotrophomonas sp., while the dominant bacterium was not closely related to previously characterized bacteria. These data suggest the importance of culture-independent methods of quality control for pharmaceutical water.     

家蚕幼虫中肠细菌群落多样性的PCR-DGGE和16S rDNA文库序列分析

采用基于16S rDNA 的变性梯度凝胶电泳（denaturing gradient gel electrophoresis, DGGE）和16S rDNA文库序列分析的手段,研究了重要经济昆虫家蚕Bombyx mori 2个品系——专食性品系C108和广食性品系SCN2幼虫中肠内的细菌群落多样性,同时还探讨了食料对家蚕中肠内细菌群落结构的影响。文库序列分析表明,PCR 扩增得到的16S rDNA基因代表了家蚕中肠内的41种细菌系统发育型（phylotype）,大多数属于Proteobacteria,其次是Lactobacillales。此外,还有少数属于Deinococcus-Thermus、Bacillales、Clostridiales和Actinobacteria,尚有5种系统发育型不能确定其所属类型。家蚕的这2个品系中,肠球菌属Enterococcus是其中肠细菌的优势菌群,栖热菌属Thermus是次优势菌群。优势菌肠球菌属的组成在品系和不同食料喂养条件下有着一定的变化,无桑饲料喂养条件下SCN2品系中肠内还出现了新的次优势菌葡萄球菌（Staphylococcus）。DGGE图谱显示家蚕低龄幼虫和高龄幼虫肠道细菌格局存在差异,推测可能与其发育期生理状态的差异有关。本研究结果提示家蚕肠道特殊菌群的出现可能与其特殊的食性有一定的关系,食料改变、生长受阻后肠道微生态平衡也发生变化。     

Quantitative real-time PCR (qPCR) detection chemistries affect enumeration of the Dehalococcoides 16S rRNA gene in groundwater

Quantitative real-time PCR (qPCR) commonly uses the fluorogenic 5′ nuclease (TaqMan) and SYBR Green I (SG) detection chemistries to enumerate biomarker genes. Dehalococcoides (Dhc) are keystone bacteria for the detoxification of chlorinated ethenes, and the Dhc 16S ribosomal RNA (rRNA) gene serves as a biomarker for monitoring reductive dechlorination in contaminated aquifers. qPCR enumeration of Dhc biomarker genes using the TaqMan or SG approach with the same primer set yielded linear calibration curves over a seven orders of magnitude range with similar amplification efficiencies. The TaqMan assay discriminates specific from nonspecific amplification observed at low template concentrations with the SG assay, and had a 10-fold lower limit of detection of ~3 copies per assay. When applied to Dhc pure cultures and Dhc-containing consortia, both detection methods enumerated Dhc biomarker genes with differences not exceeding 3-fold. Greater variability was observed with groundwater samples, and the SG chemistry produced false-positive results or yielded up to 6-fold higher biomarker gene abundances compared to the TaqMan method. In most cases, the apparent error associated with SG detection resulted from quantification of nonspecific amplification products and was more pronounced with groundwater samples that had low biomarker concentrations or contained PCR inhibitors. Correction of the apparent error using post-amplification melting curve analysis produced 2 to 21-fold lower abundance estimates; however, gel electrophoretic analysis of amplicons demonstrated that melting curve analysis was insufficient to recognize all nonspecific amplification. Upon exclusion of nonspecific amplification products identified by combined melting curve and electrophoretic amplicon analyses, the SG method produced false-negative results compared to the TaqMan method. To achieve sensitive and accurate quantification of Dhc biomarker genes in environmental samples (e.g., groundwater) and avoid erroneous conclusions, the analysis should rely on TaqMan detection chemistry, unless additional analyses validate the results obtained with the SG approach.     

Bacterial Community Composition in Different Sediments from the Eastern Mediterranean Sea: a Comparison of Four 16S Ribosomal DNA Clone Libraries

The regional variability of sediment bacterial community composition and diversity was studied by comparative analysis of four large 16S ribosomal DNA (rDNA) clone libraries from sediments in different regions of the Eastern Mediterranean Sea (Thermaikos Gulf, Cretan Sea, and South lonian Sea). Amplified rDNA restriction analysis of 664 clones from the libraries indicate that the rDNA richness and evenness was high: for example, a near-1:1 relationship among screened clones and number of unique restriction patterns when up to 190 clones were screened for each library. Phylogenetic analysis of 207 bacterial 16S rDNA sequences from the sediment libraries demonstrated that Gamma-, Delta-, and Alphaproteobacteria, Holophaga/Acidobacteria, Planctomycetales, Actinobacteria, Bacteroidetes, and Verrucomicrobia were represented in all four libraries. A few clones also grouped with the Betaproteobacteria, Nitrospirae, Spirochaetales, Chlamydiae, Firmicutes, and candidate division OPl 1. The abundance of sequences affiliated with Gammaproteobacteria was higher in libraries from shallow sediments in the Thermaikos Gulf (30 m) and the Cretan Sea (100 m) compared to the deeper South Ionian station (2790 m). Most sequences in the four sediment libraries clustered with uncultured 16S rDNA phylotypes from marine habitats, and many of the closest matches were clones from hydrocarbon seeps, benzene-mineralizing consortia, sulfate reducers, sulk oxidizers, and ammonia oxidizers. LIBSHUFF statistics of 16S rDNA gene sequences from the four libraries revealed major differences, indicating either a very high richness in the sediment bacterial communities or considerable variability in bacterial community composition among regions, or both.