Toolbox Approaches Using Molecular Markers and 16S rRNA Gene Amplicon Data Sets for Identification of Fecal Pollution in Surface Water

In this study, host-associated molecular markers and bacterial 16S rRNA gene community analysis using high-throughput sequencing were used to identify the sources of fecal pollution in environmental waters in Brisbane, Australia. A total of 92 fecal and composite wastewater samples were collected from different host groups (cat, cattle, dog, horse, human, and kangaroo), and 18 water samples were collected from six sites (BR1 to BR6) along the Brisbane River in Queensland, Australia. Bacterial communities in the fecal, wastewater, and river water samples were sequenced. Water samples were also tested for the presence of bird-associated (GFD), cattle-associated (CowM3), horse-associated, and human-associated (HF183) molecular markers, to provide multiple lines of evidence regarding the possible presence of fecal pollution associated with specific hosts. Among the 18 water samples tested, 83%, 33%, 17%, and 17% were real-time PCR positive for the GFD, HF183, CowM3, and horse markers, respectively. Among the potential sources of fecal pollution in water samples from the river, DNA sequencing tended to show relatively small contributions from wastewater treatment plants (up to 13% of sequence reads). Contributions from other animal sources were rarely detected and were very small (<3% of sequence reads). Source contributions determined via sequence analysis versus detection of molecular markers showed variable agreement. A lack of relationships among fecal indicator bacteria, host-associated molecular markers, and 16S rRNA gene community analysis data was also observed. Nonetheless, we show that bacterial community and host-associated molecular marker analyses can be combined to identify potential sources of fecal pollution in an urban river. This study is a proof of concept, and based on the results, we recommend using bacterial community analysis (where possible) along with PCR detection or quantification of host-associated molecular markers to provide information on the sources of fecal pollution in waterways.     

16S rRNA Gene Sequence Analysis of Drinking Water Using RNA and DNA Extracts as Targets for Clone Library Development

The bacterial composition of chlorinated drinking water was analyzed using 16S rRNA gene clone libraries derived from DNA extracts of 12 samples and compared to clone libraries previously generated using RNA extracts from the same samples. Phylogenetic analysis of 761 DNA-based clone sequences showed that unclassified bacteria were the most abundant group, representing nearly 62% of all DNA sequences analyzed. Other phylogenetic groups identified included Proteobacteria (20%), Actinobacteria (9%), Cyanobacteria (4%), and Bacteroidetes (2%). The composition of RNA-based libraries (1122 sequences) was similar to the DNA-based libraries with a few notable exceptions: Proteobacteria were more dominant in the RNA clone libraries (i.e., 35% RNA; 20% DNA). Differences in the Proteobacteria composition were also observed; alpha-Proteobacteria was 22 times more abundant in the RNA-based clones while beta-Proteobacteria was eight times more abundant in the DNA libraries. Nearly twice as many DNA operational taxonomic units (OTUs) than RNA OTUs were observed at distance 0.03 (101 DNA; 53 RNA). Twenty-four OTUs were shared between all RNA- and DNA-based libraries (OTU_0.03) representing only 18% of the total OTUs, but 81% (1527/1883) of all sequences. Such differences between clone libraries demonstrate the necessity of generating both RNA- and DNA-derived clone libraries to compare these two different molecular approaches for community analyses.     

Quantitative identification of fecal water pollution sources by TaqMan real-time PCR assays using Bacteroidales 16S rRNA genetic markers

PCR-based analysis of Bacteroidales 16S rRNA genes has emerged as a promising tool to identify sources of fecal water pollution. In this study, three TaqMan real-time PCR assays (BacGeneral, BacHuman, and BacBovine) were developed and evaluated for their ability to quantitatively detect general (total), human-specific, and bovine-specific Bacteroidales 16S rRNA genetic markers. The detection sensitivity was determined to be 6.5 copies of 16S rRNA gene for the BacGeneral and BacHuman assays and 10 copies for the BacBovine assay. The assays were capable of detecting approximately one to two cells per PCR. When tested with 70 fecal samples from various sources (human, cattle, pig, deer, dog, cat, goose, gull, horse, and raccoon), the three assays positively identified the target markers in all samples without any false-negative results. The BacHuman and BacBovine assays exhibited false-positive reactions with non-target samples in a few cases. However, the level of the false-positive reactions was about 50 times smaller than that of the true-positive ones, and therefore, these cross-reactions were unlikely to cause misidentifications of the fecal pollution sources. Microbial source-tracking capability was tested at two freshwater streams of which water quality was influenced by human and cattle feces, respectively. The assays accurately detected the presence of the corresponding host-specific markers upon fecal pollution and the persistence of the markers in downstream areas. The assays are expected to reliably determine human and bovine fecal pollution sources in environmental water samples.     

Rapid Estimation of Numbers of Fecal Bacteroidetes by Use of a Quantitative PCR Assay for 16S rRNA Genes

Assessment of health risk associated with fecal pollution requires a reliable fecal indicator and a rapid quantification method. We report the development of a Taq nuclease assay for enumeration of 16S rRNA genes of Bacteroidetes. Sensitivity and correlation with standard fecal indicators provide experimental evidence for application of the assay in monitoring fecal pollution.     

Quantitative Real-Time PCR Assays for Sensitive Detection of Canada Goose-Specific Fecal Pollution in Water Sources

Canada geese (Branta canadensis) are prevalent in North America and may contribute to fecal pollution of water systems where they congregate. This work provides two novel real-time PCR assays (CGOF1-Bac and CGOF2-Bac) allowing for the specific and sensitive detection of Bacteroides 16S rRNA gene markers present within Canada goose feces.The Canada goose (Branta canadensis) is a prevalent waterfowl species in North America. The population density of Canada geese has doubled during the past 15 years, and the population was estimated to be close to 3 million in 2007 (4). Canada geese often congregate within urban settings, likely due to available water sources, predator-free grasslands, and readily available food supplied by humans (6). They are suspected to contribute to pollution of aquatic environments due to the large amounts of fecal matter that can be transported into the water. This can create a public health threat if the fecal droppings contain pathogenic microorganisms (6, 7, 9, 10, 12, 13, 19). Therefore, tracking transient fecal pollution of water due to fecal inputs from waterfowl, such as Canada geese, is of importance for protecting public health.PCR detection of host-specific 16S rRNA gene sequences from Bacteroidales of fecal origin has been described as a promising microbial source-tracking (MST) approach due to its rapidity and high specificity (2, 3). Recently, Lu et al. (15) characterized the fecal microbial community from Canada geese by constructing a 16S rRNA gene sequence database using primers designed to amplify all bacterial 16S rRNA gene sequences. The authors reported that the majority of the 16S rRNA gene sequences obtained were related to Clostridia or Bacilli and to a lesser degree Bacteroidetes, which represent possible targets for host-specific source-tracking assays.The main objective of this study was to identify novel Bacteroidales 16S rRNA gene sequences that are specific to Canada goose feces and design primers and TaqMan fluorescent probes for sensitive and specific quantification of Canada goose fecal contamination in water sources.Primers 32F and 708R from Bernhard and Field (2) were used to construct a Bacteroidales-specific 16S rRNA gene clone library from Canada goose fecal samples (n = 15) collected from grass lawns surrounding Wascana Lake (Regina, SK, Canada) in May 2009 (for a detailed protocol, see File S1 in the supplemental material). Two hundred eighty-eight clones were randomly selected and subjected to DNA sequencing (at the Plant Biotechnology Institute DNA Technologies Unit, Saskatoon, SK, Canada). Representative sequences of each operational taxonomic unit (OTU) were recovered using an approach similar to that described by Mieszkin et al. (16). Sequences that were less than 93% similar to 16S rRNA gene sequences from nontarget host species in GenBank were used in multiple alignments to identify regions of DNA sequence that were putatively goose specific. Subsequently, two TaqMan fluorescent probe sets (targeting markers designated CGOF1-Bac and CGOF2-Bac) were designed using the RealTimeDesign software provided by Biosearch Technologies (http://www.biosearchtech.com/). The newly designed primer and probe set for the CGOF1-Bac assay included CG1F (5′-GTAGGCCGTGTTTTAAGTCAGC-3′) and CG1R (5′-AGTTCCGCCTGCCTTGTCTA-3′) and a TaqMan probe (5′-6-carboxyfluorescein [FAM]-CCGTGCCGTTATACTGAGACACTTGAG-Black Hole Quencher 1 [BHQ-1]-3′), and the CGOF2-Bac assay had primers CG2F (5′-ACTCAGGGATAGCCTTTCGA-3′) and CG2R (5′-ACCGATGAATCTTTCTTTGTCTCC-3′) and a TaqMan probe (5′-FAM-AATACCTGATGCCTTTGTTTCCCTGCA-BHQ-1-3′). Oligonucleotide specificities for the Canada goose-associated Bacteroides 16S rRNA primers were verified through in silico analysis using BLASTN (1) and the probe match program of the Ribosomal Database Project (release 10) (5). Host specificity was further confirmed using DNA extracts from 6 raw human sewage samples from various geographical locations in Saskatchewan and 386 fecal samples originating from 17 different animal species in Saskatchewan, including samples from Canada geese (n = 101) (Table ​(Table1).1). An existing nested PCR assay for detecting Canada goose feces (15) (targeting genetic marker CG-Prev f5) (see Table S1 in the supplemental material) was also tested for specificity using the individual fecal and raw sewage samples (Table ​(Table1).1). All fecal DNA extracts were obtained from 0.25 g of fecal material by using the PowerSoil DNA extraction kit (Mo Bio Inc., Carlsbad, CA) (File S1 in the supplemental material provides details on the sample collection).

TABLE 1.

Specificities of the CGOF1-Bac, CGOF2-Bac, and CG-Prev f5 PCR assays for different species present in Saskatchewan, Canada

Use of Bacteroidales Microbial Source Tracking To Monitor Fecal Contamination in Fresh Produce Production

In recent decades, fresh and minimally processed produce items have been associated with an increasing proportion of food-borne illnesses. Most pathogens associated with fresh produce are enteric (fecal) in origin, and contamination can occur anywhere along the farm-to-fork chain. Microbial source tracking (MST) is a tool developed in the environmental microbiology field to identify and quantify the dominant source(s) of fecal contamination. This study investigated the utility of an MST method based on Bacteroidales 16S rRNA gene sequences as a means of identifying potential fecal contamination, and its source, in the fresh produce production environment. The method was applied to rinses of fresh produce, source and irrigation waters, and harvester hand rinses collected over the course of 1 year from nine farms (growing tomatoes, jalapeño peppers, and cantaloupe) in Northern Mexico. Of 174 samples, 39% were positive for a universal Bacteroidales marker (AllBac), including 66% of samples from cantaloupe farms (3.6 log₁₀ genome equivalence copies [GEC]/100 ml), 31% of samples from tomato farms (1.7 log₁₀ GEC/100 ml), and 18% of samples from jalapeño farms (1.5 log₁₀ GEC/100 ml). Of 68 AllBac-positive samples, 46% were positive for one of three human-specific markers, and none were positive for a bovine-specific marker. There was no statistically significant correlation between Bacteroidales and generic Escherichia coli across all samples. This study provides evidence that Bacteroidales markers may serve as alternative indicators for fecal contamination in fresh produce production, allowing for determination of both general contamination and that derived from the human host.     

菌种1137116S rRNA序列分析及鉴定

通过PCR方法扩增菌种11371的16S rRNA基因并测序,将序列提交GenBank(登录号:DQ531606),并与其他链霉菌属种进行比较,通过DNAStar软件得到菌种16S rRNA基因序列进化树。同时采用插片法、显微镜观察等方法对株菌11371进行形态特征、培养特征、生理生化特征鉴定。结果表明,11371的16S rRNA序列与其他链霉菌具有一定的同源性,结合生理、生化指标鉴定结果,进一步确定菌种为不吸水链霉菌一株新亚种(Streptomyces ahygroscopicus subsp.wuzhouensis n.sub-sp.),菌株11371 16S rRNA序列为GenBank中首例Streptomyces ahygroscopicus的16S rRNA序列。     

Comparison of Bacteroides-Prevotella 16S rRNA Genetic Markers for Fecal Samples from Different Animal Species

To effectively manage surface and ground waters it is necessary to improve our ability to detect and identify sources of fecal contamination. We evaluated the use of the anaerobic bacterial group Bacteroides-Prevotella as a potential fecal indicator. Terminal restriction length polymorphism (T-RFLP) of the 16S rRNA genes from this group was used to determine differences in populations and to identify any unique populations in chickens, cows, deer, dogs, geese, horses, humans, pigs, and seagulls. The group appears to be a good potential fecal indicator in all groups tested except for avians. Cluster analysis of Bacteroides-Prevotella community T-RFLP profiles indicates that Bacteroides-Prevotella populations from samples of the same host species are much more similar to each other than to samples from different source species. We were unable to identify unique peaks that were exclusive to any source species; however, for most host species, at least one T-RFLP peak was identified to be more commonly found in that species, and a combination of peaks could be used to identify the source. T-RFLP profiles obtained from water spiked with known-source feces contained the expected diagnostic peaks from the source. These results indicate that the approach of identifying Bacteroides-Prevotella molecular markers associated with host species might be useful in identifying sources of fecal contamination in the environment.     

Evaluating Bias of Illumina-Based Bacterial 16S rRNA Gene Profiles

Massively parallel sequencing of 16S rRNA genes enables the comparison of terrestrial, aquatic, and host-associated microbial communities with sufficient sequencing depth for robust assessments of both alpha and beta diversity. Establishing standardized protocols for the analysis of microbial communities is dependent on increasing the reproducibility of PCR-based molecular surveys by minimizing sources of methodological bias. In this study, we tested the effects of template concentration, pooling of PCR amplicons, and sample preparation/interlane sequencing on the reproducibility associated with paired-end Illumina sequencing of bacterial 16S rRNA genes. Using DNA extracts from soil and fecal samples as templates, we sequenced pooled amplicons and individual reactions for both high (5- to 10-ng) and low (0.1-ng) template concentrations. In addition, all experimental manipulations were repeated on two separate days and sequenced on two different Illumina MiSeq lanes. Although within-sample sequence profiles were highly consistent, template concentration had a significant impact on sample profile variability for most samples. Pooling of multiple PCR amplicons, sample preparation, and interlane variability did not influence sample sequence data significantly. This systematic analysis underlines the importance of optimizing template concentration in order to minimize variability in microbial-community surveys and indicates that the practice of pooling multiple PCR amplicons prior to sequencing contributes proportionally less to reducing bias in 16S rRNA gene surveys with next-generation sequencing.     

Chemical Contamination of California Drinking Water

Drinking water contamination by toxic chemicals has become widely recognized as a public health concern since the discovery of 1,2-dibromo-3-chloropropane in California''s Central Valley in 1979. Increased monitoring since then has shown that other pesticides and industrial chemicals are present in drinking water. Contaminants of drinking water also include naturally occurring substances such as asbestos and even the by-products of water chlorination. Public water systems, commercially bottled and vended water and mineral water are regulated, and California is also taking measures to prevent water pollution by chemicals through various new laws and programs.     

Discrimination of Viable and Dead Fecal Bacteroidales Bacteria by Quantitative PCR with Propidium Monoazide

Propidium monoazide (PMA) was optimized to discriminate between viable and dead Bacteroides fragilis cells and extracellular DNA at different concentrations of solids using quantitative PCR. Conditions of 100 μM PMA and a 10-min light exposure also excluded DNA from heat-treated cells of nonculturable Bacteroidales in human feces and wastewater influent and effluent.The aim of microbial source tracking (MST) methods is to identify, and in some cases quantify, the dominant sources of fecal contamination in surface waters and groundwater (2, 16). One of the most promising library- and cultivation-independent approaches utilizes fecal Bacteroidales bacteria and quantitative PCR (qPCR) assays to measure gene copies of host-specific genetic markers for 16S rRNA (4, 5, 10, 14). Currently, molecular assays do not directly discriminate between viable and nonviable cells since DNA of both live and dead cells and extracellular DNA can be amplified. Consequently, source tracking data based on detection of genetic markers by PCR cannot distinguish between recent and past contamination events since DNA of selected pathogens can persist after cell death for more than 3 weeks (6). Hence, it would be preferable to detect host-specific markers in viable cells of Bacteroidales bacteria, which are strictly anaerobic microorganisms and unlikely to survive in water.Previous studies have suggested the use of intercalating DNA-binding chemicals combined with PCR to inhibit PCR amplification of DNA derived from dead cells (8, 9, 11, 15). For example, ethidium monoazide (EMA) has been investigated as a means of reducing the PCR signal from DNA originating from dead bacterial cells (7, 15, 19). However, the use of EMA prior to DNA extraction has been found to result in a significant loss of the genomic DNA of viable cells in the case of Escherichia coli 0157:H7, Campylobacter jejuni, and Listeria monocytogenes (3, 7). Recently propidium monoazide (PMA) has been proposed as a more selective agent, penetrating only dead bacterial cells but not viable cells with intact membranes (8). EMA/PMA in combination with PCR or qPCR has been applied to identify viable food-borne pathogens in a simple matrix (3, 7, 8, 11), and possible restrictions in the use of PMA in environmental samples were reported (9, 19). Yet the feasibility of applying PMA in environmental samples or MST studies using fecal Bacteroidales bacteria has not been systematically studied. Any meaningful application of EMA or PMA in stool or natural water samples must consider potential interferences due to particulate matter present in the environmental matrix. Similarly, procedures for the concentration of large volumes of water samples to simultaneously monitor pathogens and MST identifiers can lower the limit of detection (4, 12), but they concentrate solids or other inhibitors of quantitative PCR (qPCR) as well, which might interfere in the covalent binding of PMA to DNA.The objectives of this study were, therefore, the following: (i) to evaluate the applicability of PMA-qPCR methods to detect culturable Bacteroides fragilis, (ii) to determine the feasibility of PMA-qPCR analysis for environmental samples containing different concentrations of solids, and (iii) to validate the utility of the PMA-qPCR method for the detection of fecal Bacteroidales bacteria in defined live and heat-treated mixtures of human feces and in wastewater treatment plant influent and effluent.Pure cultures of Bacteroides fragilis (ATCC 25285) were grown in thioglycolate broth (Anaerobe System, Morgan Hill, CA) under anaerobic conditions in GasPak anaerobic jars (Becton Dickinson Microbiology Systems, Cockeysville, MD). The solids were obtained by hollow-fiber ultrafiltration as described previously (12, 13). Ultrasonification and heat sterilization in an autoclave were used for removing attached bacteria or DNA from solids and inactivating residual DNA. Finally, the solids were resuspended with 1× phosphate-buffered saline (PBS) solution to 100 mg liter⁻¹ or 1,000 mg liter⁻¹ of suspended solids. The concentration of total suspended solids (TSS) was measured using method 2450 C (1). Next, 1 ml of broth medium containing 2 × 10⁹ viable or 2 × 10⁸ heat-treated B. fragilis cells, which had been exposed at 80°C for 20 min, was spiked into 1× PBS buffer solutions containing 0 mg liter⁻¹, 100 mg liter⁻¹, or 1,000 mg liter⁻¹ of TSS. Before the cells were spiked, 1 ml of Bacteroides fragilis cell suspension was enumerated with the Live/Dead BacLight bacterial viability kit (Molecular Probes Inc., Eugene, OR) using a hemacytometer and an Axioskop 2 Plus epifluorescence microscope (Zeiss, Thornwood, NY) equipped with two filter sets (fluorescein isothiocyanate and Texas Red). The inoculated samples were incubated under anaerobic conditions in GasPak anaerobic jars (Becton Dickinson Microbiology Systems, Cockeysville, MD) for 4 h at 20°C to allow sufficient time for the cells to sorb to solids.A fresh human fecal specimen was obtained from a healthy adult. Two grams of feces was suspended in 25 ml 1× PBS. The fecal suspension was diluted 1:10 and 1:100 in a 1× PBS solution, and aliquots were subjected to heat treatment at 80°C for 20 min. The heat-treated fecal portions were mixed with fresh diluted samples (1:10 and 1:100 dilutions) in defined ratios, with fresh feces representing 0%, 10%, 20%, 30%, 40%, 50%, 60%, 70%, 80%, 90%, and 100% of the total, respectively. Effluent and influent water samples were collected in sterile 2-liter bottles from the University of California, Davis, wastewater treatment plant. The effluent samples were concentrated to approximately 200 ml by hollow-fiber ultrafiltration (12).PMA (Biotium Inc., Hayward, CA) was prepared, stored, and used as described in previous studies (8, 9), but PMA concentrations and light exposure time were varied to determine the optimal condition of PMA-qPCR; the PMA concentrations were 2 μM, 6 μM, 20 μM, and 100 μM. Light exposure times were 1 min, 5 min, 10 min, and 20 min. Genomic DNA was extracted using the FastDNA spin kit for soil (Biomedicals, Solon, OH). Cell lysis was achieved by bead beating using a bead mill Minibread beater (Biospec Products Inc., Bartlesville, OK) at 2,400 rpm for 20 s. Otherwise, DNA extraction was performed according to the manufacturer''s instructions. TaqMan probe and primer assays targeting the rRNA genes of all fecal Bacteroidales bacteria (BacUni-UCD) and mixed human-specific Bacteroidales bacteria (BacHum-UCD), developed by Kildare et al. (4), were used to detect and quantify fecal Bacteroidales bacteria present in fecal and (waste)water samples.We explored the ability of PMA-qPCR to discriminate between viable and heat-killed cells at different solids concentrations using Bacteroides fragilis cultures (Fig. ​(Fig.1).1). PMA did not influence the PCR amplification of DNA derived from viable cells when no solids were present (TSS = 0 mg liter⁻¹) (Fig. ​(Fig.1A).1A). The level of PMA concentration slightly affected the mean cycle threshold differences (ΔC_T) of viable cells at higher solids concentrations (TSS = 100 and 1,000 mg liter⁻¹) (Fig. 1C and E). The signal reductions in the amplification of heat-killed cells were a function of both the PMA concentration and exposure time (Fig. 1B, D, and F). Lower solids concentrations did not inhibit the efficacy of discrimination from heat-killed cells. However, solids at 1,000 mg liter⁻¹ affected the amplification of DNA derived from heat-killed cells. Higher solids concentrations affected the suppression of PCR amplification from heat-treated cells by interfering with the cross-linking of PMA. In agreement with previous reports, the number of viable Bacteroides fragilis cells was underestimated in our study when EMA-treated and untreated samples containing only viable cells were compared because mean ΔC_T values were as high as 10 (data not shown). In contrast to EMA, PMA seems to not penetrate live cells, since higher selectivity of PMA is most probably associated with the higher charge of the molecule (8).Open in a separate windowFIG. 1.Effect of PMA on amplification of BacUni-UCD universal marker in viable and dead Bacteroides fragilis cells with different concentrations of solids. The contour lines represented ΔC_T values and were generated by the Origin Pro 8 software program. The mean cycle threshold differences (ΔC_T) were calculated by subtracting C_T values obtained without PMA treatment from C_T values obtained with PMA treatment. (A and B) ΔC_T for viable cells (A) or dead cells (B) in the absence of added solids. (C and D) ΔC_T for viable cells (C) or dead cells (D) at a solids concentration of 100 mg liter⁻¹. (E and F) ΔC_T for viable cells (E) or dead cells (F) at a solids concentration of 1,000 mg liter⁻¹.A factorial three-way analysis of variance including the PMA concentration, exposure time, and TSS concentration was performed to determine the interferences of solids and the optimal PMA-qPCR condition in the differentiation of viable cells from dead cells (Table ​(Table1).1). The mean ΔC_T of viable cells in the PMA experiments was slightly influenced by the PMA concentration (P = 0.05) in the absence of solids (TSS = 0 mg liter⁻¹), but the effect was biologically insignificant (mean ΔC_T = 0.004). The PMA concentration had a significant effect on ΔC_T values for both viable and dead cells in the presence of higher solids concentrations (TSS = 100 and 1,000 mg liter⁻¹), as shown in Table ​Table1.1. However, the effect of exposure time in PMA treatment was insignificant at a TSS concentration of 1,000 mg liter⁻¹ (P > 0.4). The solids concentration caused significantly different ΔC_T values for viable and dead cells in the PMA treatments (P < 0.001) as determined by factorial three-way analysis. The greatest differences in the mean ΔC_T values between viable and dead cells were seen at 100 μM of PMA and with a 10-min exposure time, as determined by Tukey''s comparison test, for TSS concentrations of 100 mg liter⁻¹ and 1,000 mg liter⁻¹. Ideally, shorter light exposure and a lower concentration of dye can minimize the penetration of live cells. However, these conditions were not compatible with sufficient inhibition of amplification of DNA from dead cells for PMA treatment.

TABLE 1.

Statistical analysis for differences (ΔC_T) between nontreatment and PMA treatment for experiments where Bacteroides fragilis was spiked^a

Riboprinting and 16S rRNA Gene Sequencing for Identification of Brewery Pediococcus Isolates

A total of 46 brewery and 15 ATCC Pediococcus isolates were ribotyped using a Qualicon RiboPrinter. Of these, 41 isolates were identified as Pediococcus damnosus using EcoRI digestion. Three ATCC reference strains had patterns similar to each other and matched 17 of the brewery isolates. Six other brewing isolates were similar to ATCC 25249. The other 18 P. damnosus brewery isolates had unique patterns. Of the remaining brewing isolates, one was identified as P. parvulus, two were identified as P. acidilactici, and two were identified as unique Pediococcus species. The use of alternate restriction endonucleases indicated that PstI and PvuII could further differentiate some strains having identical EcoRI profiles. An acid-resistant P. damnosus isolate could be distinguished from non-acid-resistant varieties of the same species using PstI instead of EcoRI. 16S rRNA gene sequence analysis was compared to riboprinting for identifying pediococci. The complete 16S rRNA gene was PCR amplified and sequenced from seven brewery isolates and three ATCC references with distinctive riboprint patterns. The 16S rRNA gene sequences from six different brewery P. damnosus isolates were homologous with a high degree of similarity to the GenBank reference strain but were identical to each other and one ATCC strain with the exception of 1 bp in one strain. A slime-producing, beer spoilage isolate had 16S rRNA gene sequence homology to the P. acidilactici reference strain, in agreement with the riboprint data. Although 16S rRNA gene sequencing correctly identified the genus and species of the test Pediococcus isolates, riboprinting proved to be a better method for subspecies differentiation.     

16S rRNA Gene Survey of Microbial Communities in Winogradsky Columns

A Winogradsky column is a clear glass or plastic column filled with enriched sediment. Over time, microbial communities in the sediment grow in a stratified ecosystem with an oxic top layer and anoxic sub-surface layers. Winogradsky columns have been used extensively to demonstrate microbial nutrient cycling and metabolic diversity in undergraduate microbiology labs. In this study, we used high-throughput 16s rRNA gene sequencing to investigate the microbial diversity of Winogradsky columns. Specifically, we tested the impact of sediment source, supplemental cellulose source, and depth within the column, on microbial community structure. We found that the Winogradsky columns were highly diverse communities but are dominated by three phyla: Proteobacteria, Bacteroidetes, and Firmicutes. The community is structured by a founding population dependent on the source of sediment used to prepare the columns and is differentiated by depth within the column. Numerous biomarkers were identified distinguishing sample depth, including Cyanobacteria, Alphaproteobacteria, and Betaproteobacteria as biomarkers of the soil-water interface, and Clostridia as a biomarker of the deepest depth. Supplemental cellulose source impacted community structure but less strongly than depth and sediment source. In columns dominated by Firmicutes, the family Peptococcaceae was the most abundant sulfate reducer, while in columns abundant in Proteobacteria, several Deltaproteobacteria families, including Desulfobacteraceae, were found, showing that different taxonomic groups carry out sulfur cycling in different columns. This study brings this historical method for enrichment culture of chemolithotrophs and other soil bacteria into the modern era of microbiology and demonstrates the potential of the Winogradsky column as a model system for investigating the effect of environmental variables on soil microbial communities.     

Host Distributions of Uncultivated Fecal Bacteroidales Bacteria Reveal Genetic Markers for Fecal Source Identification

The purpose of this study was to examine host distribution patterns among fecal bacteria in the order Bacteroidales, with the goal of using endemic sequences as markers for fecal source identification in aquatic environments. We analyzed Bacteroidales 16S rRNA gene sequences from the feces of eight hosts: human, bovine, pig, horse, dog, cat, gull, and elk. Recovered sequences did not match database sequences, indicating high levels of uncultivated diversity. The analysis revealed both endemic and cosmopolitan distributions among the eight hosts. Ruminant, pig, and horse sequences tended to form host- or host group-specific clusters in a phylogenetic tree, while human, dog, cat, and gull sequences clustered together almost exclusively. Many of the human, dog, cat, and gull sequences fell within a large branch containing cultivated species from the genus Bacteroides. Most of the cultivated Bacteroides species had very close matches with multiple hosts and thus may not be useful targets for fecal source identification. A large branch containing cultivated members of the genus Prevotella included cloned sequences that were not closely related to cultivated Prevotella species. Most ruminant sequences formed clusters separate from the branches containing Bacteroides and Prevotella species. Host-specific sequences were identified for pigs and horses and were used to design PCR primers to identify pig and horse sources of fecal pollution in water. The primers successfully amplified fecal DNAs from their target hosts and did not amplify fecal DNAs from other species. Fecal bacteria endemic to the host species may result from evolution in different types of digestive systems.     

Assessing the Fecal Microbiota: An Optimized Ion Torrent 16S rRNA Gene-Based Analysis Protocol

Assessing the distribution of 16S rRNA gene sequences within a biological sample represents the current state-of-the-art for determination of human gut microbiota composition. Advances in dissecting the microbial biodiversity of this ecosystem have very much been dependent on the development of novel high-throughput DNA sequencing technologies, like the Ion Torrent. However, the precise representation of this bacterial community may be affected by the protocols used for DNA extraction as well as by the PCR primers employed in the amplification reaction. Here, we describe an optimized protocol for 16S rRNA gene-based profiling of the fecal microbiota.     

Free-Living Protozoa in Two Unchlorinated Drinking Water Supplies,Identified by Phylogenic Analysis of 18S rRNA Gene Sequences

Free-living protozoan communities in water supplies may include hosts for Legionella pneumophila and other undesired bacteria, as well as pathogens. This study aimed at identifying free-living protozoa in two unchlorinated groundwater supplies, using cultivation-independent molecular approaches. For this purpose, samples (<20°C) of treated water, distributed water, and distribution system biofilms were collected from supply A, with a low concentration of natural organic matter (NOM) (<0.5 ppm of C), and from supply B, with a high NOM concentration (7.9 ppm of C). Eukaryotic communities were studied using terminal restriction fragment length polymorphism and clone library analyses of partial 18S rRNA gene fragments and a Hartmannella vermiformis-specific quantitative PCR (qPCR). In both supplies, highly diverse eukaryotic communities were observed, including free-living protozoa, fungi, and metazoa. Sequences of protozoa clustered with Amoebozoa (10 operational taxonomic units [OTUs]), Cercozoa (39 OTUs), Choanozoa (26 OTUs), Ciliophora (29 OTUs), Euglenozoa (13 OTUs), Myzozoa (5 OTUs), and Stramenopiles (5 OTUs). A large variety of protozoa were present in both supplies, but the estimated values for protozoan richness did not differ significantly. H. vermiformis was observed in both supplies but was not a predominant protozoan. One OTU with the highest similarity to Acanthamoeba polyphaga, an opportunistic human pathogen and a host for undesired bacteria, was observed in supply A. The high level of NOM in supply B corresponded with an elevated level of active biomass and with elevated concentrations of H. vermiformis in distributed water. Hence, the application of qPCR may be promising in elucidating the relationship between drinking water quality and the presence of specific protozoa.Free-living protozoa are ubiquitous in natural freshwater environments (7, 38, 51, 71) but also proliferate in engineered water systems, including water treatment systems (3, 47, 70), distribution systems (6, 75), and tap water installations inside buildings (54, 69). Concentrations of protozoa, determined using cultivation methods and microscopy, range from <1 to 10⁴ cells liter⁻¹ in treated water (3, 47, 70, 75) and from <1 to 7 × 10⁵ cells liter⁻¹ in distribution systems (6, 61, 64, 75). Genera of free-living protozoa commonly observed in these systems and in tap water installations include Acanthamoeba, Echinamoeba, Hartmannella, Platyamoeba, Vahlkampfia, and Vannella (47, 58, 69, 70). In warm water systems, certain free-living protozoa, e.g., Acanthamoeba spp. (57), Balamuthia mandrillaris (62), Echinamoeba exandans (16), Hartmannella spp. (39, 56), Naegleria spp. (49, 57), Tetrahymena spp. (18, 33), and Vahlkampfia jugosa (56), serve as hosts for Legionella pneumophila, the etiologic agent of Legionnaires'' disease. High concentrations of L. pneumophila are generally associated with the proliferation of host protozoa in biofilms (38, 53). In addition, other amoeba-resistant, potentially pathogenic bacteria, e.g., Burkholderia spp. (28) and Mycobacterium spp. (37), have been observed in man-made aquatic environments (24). Free-living protozoa may enhance the multiplication of bacteria, serve as a transmission vector, or serve as a shelter against unfavorable environmental conditions, such as the presence of disinfectants. Furthermore, certain free-living protozoa are human pathogens, e.g., Naegleria fowleri (81), Balamuthia mandrillaris (77), and Acanthamoeba spp. (12) can cause encephalitis. Acanthamoeba spp. have also been associated with keratitis in persons wearing contact lenses (31).Free-living protozoa feed on bacteria, algae, fungi, other protozoa, and organic detritus in biofilms or in the planktonic phase, thereby affecting the structure of microbial communities. In turn, the community of free-living protozoa depends on the diversity and abundance of bacteria in the biofilm and in the planktonic phase (26, 50, 51, 55, 63, 65). Water quality is a critical factor for biofilm formation in distribution systems and tap water installations and therefore will affect the abundance and diversity of free-living protozoa in these systems (72, 78). However, information about the presence and identity of free-living protozoa in water supplies in relation to the quality of treated water is scarce, which may be attributed to the limitations of microscopic techniques and cultivation methods for detection and identification of these organisms, e.g., low detection limits and selectivity for specific groups (19).In this study, we applied a variety of cultivation-independent techniques, viz., quantitative PCR, terminal restriction fragment length polymorphism (T-RFLP) analysis, and cloning and sequencing of eukaryotic 18S rRNA gene fragments, for the detection and identification of free-living protozoa predominating in two unchlorinated groundwater supplies. The concentrations of dissolved natural organic matter (NOM) in treated water at the plant were <0.5 mg C liter⁻¹ and 7.9 mg C liter⁻¹, covering the entire range of NOM concentrations in drinking water in The Netherlands. The objectives of the study were (i) to elucidate the identities of and diversity in the free-living protozoa predominating in these two different water supplies and (ii) to trace the presence of host protozoa for L. pneumophila and pathogenic free-living protozoa. The study revealed that treated water and biofilms in the distribution systems of both water supplies contained a large variety of free-living protozoa, including protozoan hosts for Legionella bacteria.     

Quantitative comparisons of 16S rRNA gene sequence libraries from environmental samples

To determine the significance of differences between clonal libraries of environmental rRNA gene sequences, differences between homologous coverage curves, CX(D), and heterologous coverage curves, CXY(D), were calculated by a Cramér-von Mises-type statistic and compared by a Monte Carlo test procedure. This method successfully distinguished rRNA gene sequence libraries from soil and bioreactors and correctly failed to find differences between libraries of the same composition.