Correlation between Environmental Factors and Prevalence of Vibrio parahaemolyticus in Oysters Harvested in the Southern Coastal Area of Sao Paulo State,Brazil

The presence of Vibrio parahaemolyticus in 123 oyster samples collected from an estuary on the southern coast of Sao Paulo state, Brazil, was investigated. Of the 123 samples, 99.2% were positive with densities ranging from <3 to 10⁵ most probable number (MPN)/g. Densities correlated significantly with water temperature (r = 0.48; P < 0.001) but not with salinity (r = −0.09; P = 0.34). The effect of harvest site on counts was not significant (P > 0.05). These data provide information for the assessment of exposure of V. parahaemolyticus in oysters at harvest.Infections caused by Vibrio parahaemolyticus have been reported in several countries (1, 3-5, 14, 15, 16, 17, 18, 19, 20, 22, 24, 26). Among other pathogenic features, V. parahaemolyticus strains produce a thermostable hemolysin, known as thermostable direct hemolysin (TDH), as well as TRH (a TDH-related hemolysin) (25, 29). However, not all strains are pathogenic, as less than 1% of food or environmental strains produce TDH or TRH (2, 7, 9, 10, 11).The most important vehicle for this microorganism is raw or partially cooked shellfish (8, 13, 25, 29). In this study, the densities of V. parahaemolyticus in oysters collected in six oyster bed sites in the estuary of Cananeia (25°S; 48°W) in the southern coastal area of Sao Paulo state, Brazil (Fig. ​(Fig.1)1) between May 2004 and June 2005 were determined using the most probable number (MPN) technique by the method of De Paola and Kaysner (12). Each sample consisted of 15 oysters, pooled in a plastic bag, and transported in a cold box to the laboratory located in the city of Sao Paulo, Brazil. The temperature during transportation did not exceed 13°C, and the travel time was around 5 h. In the laboratory, the oysters were kept under refrigeration (4 to 8°C) and analyzed within 24 h of collection. Oysters were cleaned and shucked by the method of Cook et al. (6). Identification of V. parahaemolyticus was based on traditional and API 20E strip biochemical tests (bioMérieux, France), using V. parahaemolyticus ATCC 17802 as the reference strain. The observed prevalence of this bacterium was high, as the microorganism was detected in 99.2% (122/123) of the samples and the densities varied between 0.78 and 5.04 log MPN/g.Open in a separate windowFIG. 1.Locations of oyster bed sites in the Cananeia estuary on the southern coast of Sao Paulo state, Brazil. (Courtesy of E. E. de Miranda and A. C. Coutinho [Embrapa Monitoramento por Satélite] [http://www.cdbrasil.cnpm.embrapa.br].)Strategies for the control of V. parahaemolyticus in oysters depend on understanding the seasonal and geographical distribution and the effects of environmental parameters on the growth of this pathogen. To verify the influence of salinity and temperature of seawater on the density of V. parahaemolyticus, samples of water (n = 123) were collected from the same depth of oyster beds using 250-ml plastic flasks. Salinity was determined using a salinometer (model RS10; Rosemount Analytical, Cedar Grove, NJ), and the temperature was determined at the time of collection using a digital thermometer (Hanna Instruments). The results are shown in Fig. ​Fig.22.Open in a separate windowFIG. 2.Total densities of Vibrio parahaemolyticus in oysters from the southern coast of Sao Paulo state, Brazil. Each bar or point represents the arithmetic mean of six sites, and each error bar represents the standard deviation.Total V. parahaemolyticus densities did not correlate significantly with water salinity, as determined by Pearson coefficient (r = −0.09; P = 0.34). However, the mean salinity varied significantly according to the sampling site and season (P < 0.05) (Table ​(Table1).1). The highest mean salinity (24.2 ppt) was detected at site 5 and was 1.4 times higher than at site 2 (17.3 ppt), the lowest mean salinity detected in this study.

TABLE 1.

Seasonal distribution of the total density of Vibrio parahaemolyticus in oysters, water temperature, and salinity in the southern coastal area of Sao Paulo state, Brazil

Growth of Arthrobacter sp. Strain JBH1 on Nitroglycerin as the Sole Source of Carbon and Nitrogen

Arthrobacter sp. strain JBH1 was isolated from nitroglycerin-contaminated soil by selective enrichment. Detection of transient intermediates and simultaneous adaptation studies with potential intermediates indicated that the degradation pathway involves the conversion of nitroglycerin to glycerol via 1,2-dinitroglycerin and 1-mononitroglycerin, with concomitant release of nitrite. Glycerol then serves as the source of carbon and energy.Nitroglycerin (NG) is manufactured widely for use as an explosive and a pharmaceutical vasodilator. It has been found as a contaminant in soil and groundwater (7, 9). Due to NG''s health effects as well as its highly explosive nature, NG contamination in soils and groundwater poses a concern that requires remedial action (3). Natural attenuation and in situ bioremediation have been used for remediation in soils contaminated with certain other explosives (16), but the mineralization of NG in soil and groundwater has not been reported.To date, no pure cultures able to grow on NG as the sole carbon, energy, and nitrogen source have been isolated. Accashian et al. (1) observed growth associated with the degradation of NG under aerobic conditions by a mixed culture originating from activated sludge. The use of NG as a source of nitrogen has been studied in mixed and pure cultures during growth on alternative sources of carbon and energy (3, 9, 11, 20). Under such conditions, NG undergoes a sequential denitration pathway in which NG is transformed to 1,2-dinitroglycerin (1,2DNG) or 1,3DNG followed by 1-mononitroglycerin (1MNG) or 2MNG and then glycerol, under both aerobic and anaerobic conditions (3, 6, 9, 11, 20), and the enzymes involved in denitration have been characterized in some detail (4, 8, 15, 21). Pure cultures capable of completely denitrating NG as a source of nitrogen when provided additional sources of carbon include Bacillus thuringiensis/cereus and Enterobacter agglomerans (11) and a Rhodococcus species (8, 9). Cultures capable of incomplete denitration to MNG in the presence of additional carbon sources were identified as Pseudomonas putida, Pseudomonas fluorescens (4), an Arthobacter species, a Klebsiella species (8, 9), and Agrobacterium radiobacter (20).Here we describe the isolation of bacteria able to degrade NG as the sole source of carbon, nitrogen, and energy. The inoculum for selective enrichment was soil historically contaminated with NG obtained at a facility that formerly manufactured explosives located in the northeastern United States. The enrichment medium consisted of minimal medium prepared as previously described (17) supplemented with NG (0.26 mM), which was synthesized as previously described (18). During enrichment, samples of the inoculum (optical density at 600 nm [OD₆₀₀] ∼ 0.03) were diluted 1/16 in fresh enrichment medium every 2 to 3 weeks. Isolates were obtained by dilution to extinction in NG-supplemented minimal medium. Cultures were grown under aerobic conditions in minimal medium at pH 7.2 and 23°C or in tryptic soy agar (TSA; 1/4 strength).Early stages of enrichment cultures required extended incubation with lag phases of over 200 h and exhibited slow degradation of NG (less than 1 μmol substrate/mg protein/h). After a number of transfers over 8 months, the degradation rates increased substantially (2.2 μmol substrate/mg protein/h). A pure culture capable of growth on NG was identified based on 16S rRNA gene analysis (504 bp) as an Arthrobacter species with 99.5% similarity to Arthrobacter pascens (GenBank accession no. {"type":"entrez-nucleotide","attrs":{"text":"GU246730","term_id":"289474572","term_text":"GU246730"}}GU246730). Purity of the cultures was confirmed microscopically and by formation of a single colony type on TSA plates. 16S gene sequencing and identification were done by MIDI Labs (Newark, DE) and SeqWright DNA Technology Services (Houston, TX). The Arthrobacter cells stained primarily as Gram-negative rods with a small number of Gram-positive cocci (data not shown); Gram variability is also a characteristic of the closely related Arthrobacter globiformis (2, 19). The optimum growth temperature is 30°C, and the optimum pH is 7.2. Higher pH values were not investigated because NG begins to undergo hydrolysis above pH 7.5 (data not shown). The isolated culture can grow on glycerol, acetate, succinate, citrate, and lactate, with nitrite as the nitrogen source. Previous authors described an Arthrobacter species able to use NG as a nitrogen source in the presence of additional sources of carbon. However, only dinitroesters were formed, and complete mineralization was not achieved (9).To determine the degradation pathway, cultures of the isolated strain (5 ml of inoculum grown on NG to an OD₆₀₀ of 0.3) were grown in minimal medium (100 ml) supplemented with NG at a final concentration of 0.27 mM. Inoculated bottles and abiotic controls were continuously mixed, and NG, 1,2DNG, 1,3DNG, 1MNG, 2MNG, nitrite, nitrate, CO₂, total protein, and optical density were measured at appropriate intervals. Nitroesters were analyzed with an Agilent high-performance liquid chromatograph (HPLC) equipped with an LC-18 column (250 by 4.6 mm, 5 μm; Supelco) and a UV detector at a wavelength of 214 nm (13). Methanol-water (50%, vol/vol) was used as the mobile phase at a flow rate of 1 ml/min. Nitrite and nitrate were analyzed with an ion chromatograph (IC) equipped with an IonPac AS14A anion-exchange column (Dionex, CA) at a flow rate of 1 ml/min. Carbon dioxide production was measured with a Micro Oxymax respirometer (Columbus Instruments, OH), and total protein was quantified using the Micro BCA protein assay kit (Pierce Biotechnology, IL) according to manufacturer''s instructions. During the degradation of NG the 1,2DNG concentration was relatively high at 46 and 72 h (Fig. ​(Fig.1).1). 1,3DNG, detected only at time zero, resulted from trace impurities in the NG stock solution. Trace amounts of 1MNG appeared transiently, and trace amounts of 2MNG accumulated and did not disappear. Traces of nitrite at time zero were from the inoculum. The concentration of NG in the abiotic control did not change during the experiment (data not shown).Open in a separate windowFIG. 1.Growth of strain JBH1 on NG. ×, NG; ▵, 1,2DNG; ⋄, 1MNG; □, 2MNG; ○, protein.Results from the experiment described above were used to calculate nitrogen and carbon mass balances (Tables ​(Tables11 and ​and2).2). Nitrogen content in protein was approximated using the formula C₅H₇O₂N (14). Because all nitrogen was accounted for throughout, we conclude that the only nitrogen-containing intermediate compounds are 1,2DNG and 1MNG, which is consistent with previous studies (6, 9, 20). The fact that most of the nitrogen was released as nitrite is consistent with previous reports of denitration catalyzed by reductase enzymes (4, 8, 21). The minor amounts of nitrate observed could be from abiotic hydrolysis (5, 12) or from oxidation of nitrite. Cultures supplemented with glycerol or other carbon sources assimilated all of the nitrite (data not shown).

TABLE 1.

Nitrogen mass balance

Nonpathogenic Simian Immunodeficiency Virus Infection of Sooty Mangabeys Is Not Associated with High Levels of Autologous Neutralizing Antibodies

Simian immunodeficiency virus (SIV) infection of natural-host species, such as sooty mangabeys (SMs), is characterized by a high level of viral replication and a low level of generalized immune activation, despite evidence of an adaptive immune response. Here the ability of SIV-infected SMs to mount neutralizing antibodies (Nab) against autologous virus was compared to that of human immunodeficiency virus type 1 (HIV-1) subtype C-infected subjects. While high levels of Nab were observed in HIV-1 infection, samples obtained at comparable time points from SM exhibited relatively low titers of autologous Nab. Nevertheless, SM plasma with higher Nab titers also contained elevated peripheral CD4⁺ T-cell levels, suggesting a potential immunologic benefit for SMs. These data indicate that AIDS resistance in these primates is not due to high Nab titers and raise the possibility that low levels of Nab might be an inherent feature of natural-host SIV infections.More than 40 species of African nonhuman primates (NHPs) naturally harbor CD4⁺-tropic lentiviruses that are collectively known as simian immunodeficiency viruses (SIVs) and represent the ancestors of the human pathogens human immunodeficiency virus type 1 (HIV-1) and HIV-2. Interestingly, African NHPs infected with their cognate SIV generally do not progress to AIDS, despite high levels of sustained virus replication, with the only known exception being chimpanzee SIV (SIVcpz)-infected chimpanzees (16). Among the natural hosts for SIV infection, the sooty mangabey ([SM] Cercocebus atys) is of particular interest, because cross-species transmission of SM SIV (SIVsm) from this natural host into humans initiated the HIV-2 epidemic in West Africa (17). In addition, SIVsm (herein referred to as SIV) is the ancestor of the rhesus macaque SIV (SIVmac) viruses that are used in disease pathogenesis and vaccination studies in the rhesus macaque model (17). Both naturally infected and experimentally inoculated SMs remain healthy, maintain CD4⁺ T cells, and do not progress to AIDS-like disease, despite sustained high levels of virus replication (31).Nonpathogenic infection of SMs is characterized by low levels of immune activation during the chronic phase of infection, which are reached after a transient immune activation that occurs during primary infection (reviewed in reference 31). These findings have led to the hypothesis that the absence of generalized immune activation in SIV-infected SMs during the chronic phase of infection is an important feature that favors the preservation of CD4⁺ T-cell homeostasis, thereby avoiding disease progression (31). However, most of these earlier studies focused on T cells and innate immune cells, with a significant gap existing in our understanding of whether humoral immunity might also differ between pathogenic and nonpathogenic infections. In HIV-1-infected patients, B cells produce neutralizing antibodies against the infecting (autologous) virus, which drives viral escape, continuous de novo antibody production (26-28, 32), and B-cell dysfunction (24). The striking differences in both the clinical outcomes of infection and the levels of immune activation between SIV-infected SMs and HIV-1-infected humans prompted us to compare the neutralizing antibody (Nab) response against the autologous virus in these two populations. To this end, we utilized a pseudovirus assay that has been used extensively by our group and others to evaluate Nab against HIV-1 and SIV envelope (Env) glycoproteins (15, 19, 22, 26, 28, 32, 33; also unpublished data). All SMs were housed at the Yerkes National Primate Research Center (Atlanta, GA) and maintained in accordance with National Institutes of Health guidelines. The Emory University Animal Care and Use Committee approved these studies. Details of the Zambia Emory HIV Research Project (ZEHRP) have been described elsewhere (2, 10, 21). The Emory University Institutional Review Board and the University of Zambia School of Medicine Research Ethics Committee approved informed-consent and human subject protocols. None of the subjects received antiretroviral therapy during the evaluation period.In HIV-1 infection, autologous Nabs develop to relatively high titers against the newly transmitted virus within the first few months (15, 19, 26-28, 32). Here we sought to test whether a similar increase in Nab titer occurs during nonpathogenic SIV infection of SMs. Samples were obtained from five animals that were inoculated intravenously with plasma from a naturally infected SM as part of a previous study (30). Multiple, biologically functional Envs were cloned from plasma collected at day 14 postinoculation (Table ​(Table1),1), and Nab activity was evaluated in plasma collected at 6 months postinoculation. To facilitate comparison with early HIV-1 infection, Nab activity in plasma was also evaluated between 2 and 9 months against Envs that were cloned between 31 and 88 estimated days after infection from four subtype C HIV-1-infected seroconverters in Zambia (Table ​(Table1).1). Figure ​Figure1A1A demonstrates that Nab activity in plasma diluted 1:100 was readily detectable in all HIV-1-infected subjects at levels approaching 100% neutralization. However, Nab activity in the SM plasma was significantly lower than in the human subjects (median, 10% versus 93%, respectively; P = 0.02). Binding antibody was detected in all five SMs at titers greater than 1:51,200 by enzyme-linked immunosorbent assay (ELISA), demonstrating that all monkeys had seroconverted by 6 months and maintained high titers of binding antibody throughout the evaluation period (Fig. ​(Fig.1B).1B). Thus, the low level of Nab was not due to a diminished humoral immune response.Open in a separate windowFIG. 1.Autologous Nab activity and B-cell proliferation during experimental infection of SMs. (A) Neutralization activity levels in plasma from five SMs (filled black circles), which were experimentally inoculated with plasma from a naturally SIV-infected SM, and four HIV-1-infected Zambian subjects (half-filled squares), who were recently infected through heterosexual contact, are shown. The horizontal bars represent the median for each group. To assess neutralizing activity, pseudoviruses were created by expressing each cloned Env with an HIV-1 env-deficient backbone (ΔSG3). JC53-BL (Tzm-bl) cells were infected with each pseudovirus in the presence or absence of serially diluted autologous plasma. Each point represents the average level of neutralization at a 1:100 dilution of plasma for at least two Env clones (see Table ​Table11 for number of Envs tested). Each neutralization assay was performed twice independently, using duplicate wells. Statistical significance between the groups was determined by a Mann-Whitney test, using GraphPad Prism 5. Longitudinal measurements of endpoint antibody ELISA titers in plasma (filled green circles) (23) (B), autologous neutralization activity in plasma (filled blue diamonds) (C), percentages of Ki-67⁺ CD20⁺ cells in blood (filled black triangles) (D), and percentages of CD20⁺ cells in blood (filled red squares) (E) are shown for the five experimentally inoculated SMs combined. In panel C, each point represents average neutralization at a 1:100 dilution of plasma over time for at least two day 14 Env clones from each SM. For panels D and E, PBMCs were gated by forward and side scatter, and the CD3⁻ CD20⁺ population was assessed for Ki-67 staining (D) by flow cytometry. SP34-2 was used to stain CD3, L27 was used for CD20, and B56 was used for Ki-67 (all from BD Biosciences). Error bars represent the standard errors of the means (SEMs). Plasma viral load peaked at day 14 (data not shown). Filled symbols in panels A through E indicate data generated from experimentally infected SMs.

TABLE 1.

Autologous Nab activity in experimentally SIV-infected SM and acutely HIV-1-infected humans

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

Laboratory Strains of Bacillus subtilis Do Not Exhibit Swarming Motility

We redemonstrate that SwrA is essential for swarming motility in Bacillus subtilis, and we reassert that laboratory strains of B. subtilis do not swarm. Additionally, we find that a number of other genes, previously reported to be required for swarming in laboratory strains, are dispensable for robust swarming motility in an undomesticated strain. We attribute discrepancies in the literature to a lack of reproducible standard experimental conditions, selection for spontaneous swarming suppressors, inadvertent genetic linkage to swarming mutations, and auxotrophy.Many species of bacteria are capable of flagellum-mediated swimming motility in liquid broth. Of those species, a subset is also capable of a related, but genetically separable, form of flagellum-mediated surface movement called swarming motility (17). Examples of swarming-proficient species include Proteus mirabilis, Vibrio parahaemolyticus, Serratia marcescens, Escherichia coli, Salmonella enterica, and Bacillus subtilis (1, 15, 16, 20, 28). In general, swarming requires a surfactant or wetting agent to reduce surface tension, an increase in flagellar number per cell, and other genetic features that are distinct from swimming (7, 14).There is confusion in the literature concerning the genetic requirements of the swarming phenotype of B. subtilis. It is generally accepted that the ancestral undomesticated strain B. subtilis 3610 exhibits robust swarming motility (18, 20, 33). Swarming motility of strain 3610 requires the production of a secreted surfactant, called surfactin (6, 20), to reduce surface tension and permit surface spreading, and it also requires the protein SwrA to activate flagellar biosynthesis gene expression and increase the number of flagella on the cell surface (5, 20). Some reports claim that domesticated derivatives of 3610, such as the commonly used laboratory strain 168, are also swarming proficient (10, 18, 19, 24). Strain 168, however, is defective in both surfactin production (9, 25) and SwrA (5, 21, 31), and thus, swarming 168 strains challenge the genetic definition of swarming motility. Our lab has never observed swarming in laboratory strains, and here we investigated swarming motility in a reportedly swarming-proficient 168 strain.We obtained a reportedly swarming-proficient 168 strain (13) (generous gift of Simone Séror, Orsay University, Paris-Sud, France) (Table ​(Table1)1) and compared its swarming phenotype to that of 3610 under our standard conditions (20). Swarm plates were prepared one day prior to use with 25 ml of LB medium (10 g Bacto tryptone, 5 g Bacto yeast extract, 5 g NaCl per liter) fortified with 0.7% Bacto agar. To minimize water on the agar surface and thus minimize the potentially confounding influence of swimming motility, plates were dried 20 min prior to inoculation and 10 min postinoculation open-faced in a laminar flow hood. For qualitative swarm assays, plates were centrally inoculated with cells from a freshly grown overnight colony using a sterile stick. For quantitative swarm expansion assays, 1 ml of cells grown to mid-exponential phase (optical density at 600 nm [OD₆₀₀], 0.5) was resuspended in PBS buffer (8 g NaCl, 0.2 g KCl, 1.44 g Na₂HPO₄, 0.24 g KH₂PO₄ per liter, pH 7.0) containing 0.5% India ink (Higgins) to an OD₆₀₀ of 10 and centrally spotted (10 μl). Swarm expansion was measured at 0.5-h intervals along a transect on the plate. Plates were incubated at 37°C in 20 to 30% humidity. Whereas strain 3610 was swarming proficient, strain 168 (Orsay) was swarming deficient (Fig. ​(Fig.1A).1A). Thus, strain 168 (Orsay) appeared to behave similarly to all other laboratory strains we have tested previously (20, 21).Open in a separate windowFIG. 1.Swarming motility on LB and B media. In qualitative plate images, colonized agar appears white and uncolonized agar appears black on LB and B media, as indicated. Swarming cells colonize a larger surface area than nonswarming cells. All strains are derivatives of strain 3610 unless otherwise indicated. Bar, 2 cm. (A) Quantitative swarm expansion assays on solid medium and growth in liquid medium of the indicated strains on LB medium (closed symbols) and on B medium (open symbols). To indicate variability in a particular experiment, we have reproduced the quantitative swarm expansion assay of strain 3610 on LB and B media with error bars in Fig. S5 in the supplemental material. (B) Quantitative swarm expansion assays on LB (closed symbols) and B (open symbols) media. The following strains were used: DS3337 (sfp), DS2415 (swrA), DS5106 (168 swrA⁺), DS5758 (168 sfp⁺), and DS5759 (168 swrA⁺ sfp⁺). In all assays, B medium was made according to reference 2 except for strain DS5759, for which B medium was supplemented with 780 μM threonine to compensate for thrC auxotrophy. (C) Swarm plates of the indicated strains on LB medium made with equal parts peptone instead of tryptone. (D) Quantitative swarm expansion assays of the indicated 3610-derived mutant strains on LB medium (closed symbols) and on B medium (open symbols). The following strains were used: DS72 (yvzB), DS2268 (epr), DS3903 (phrC), DS4978 (rapC), DS4979 (oppD), DS2509 (swrB), and DS3649 (degU). All points are averages for three replicates.

TABLE 1.

Strains

Animal-to-Animal Variation in Fecal Microbial Diversity among Beef Cattle

The intestinal microbiota of beef cattle are important for animal health, food safety, and methane emissions. This full-length sequencing survey of 11,171 16S rRNA genes reveals animal-to-animal variation in communities that cannot be attributed to breed, gender, diet, age, or weather. Beef communities differ from those of dairy. Core bovine taxa are identified.The gastrointestinal tracts (GIT) of beef cattle are colonized by microorganisms that profoundly impact animal physiology, nutrition, health, and productivity (5). The GIT microbiota potentially impact food safety via pathogen shedding (13) by interacting with organisms such as Salmonella and competing for resources in the GIT. Cattle intestinal microbiota also play an important role in methane emissions, with U.S. beef cattle alone contributing an estimated 3.87 million metric tons of methane into the environment each year, both from rumen and large-intestine fermentations (7). Although the bovine fecal microbiota have been well characterized using culture-based methods, these techniques are necessarily limited to characterizing bacteria that can be grown in the laboratory. Culture-independent methods can reveal community members that are recalcitrant to culture. Only a handful of deep-sequencing studies have been done using culture-independent 16S rRNA-based methods (1, 11, 12, 14), all with dairy cattle, which have a fundamentally different diet and metabolism from beef cattle. Despite the potential contributions of the beef cattle GIT microbiota to animal health, food safety, and global warming, these communities remain poorly characterized. With the advent of pyrosequencing technology, researchers now have the tools to characterize these important communities. Pyrosequencing will allow rapid characterization of large-sample data sets (1). However, the taxonomic information generated by rapid sequencing is approximate by necessity (9), and full-length 16S-rRNA sequencing remains the “gold standard” method. Accordingly, we have characterized fecal bacteria from six feedlot cattle by full-length capillary sequence analysis of 11,171 16S rRNA gene clones (Fig. ​(Fig.11).Open in a separate windowFIG. 1.Bacterial diversity of six feedlot beef cattle. Gray bars represent the percentages of all 16S sequences that were assigned to each taxonomy. Colored dots represent the percentages of 16S sequences from each library that were assigned to each taxonomic group. Asterisks indicate unclassified members of the named taxon. Panel A shows the data for the first 99% of all the sequences. Panel B shows the data for the remaining 1% of sequences. Note differences in scales for panels A and B.Rectal grab fecal samples (n = 6) were collected according to institutional animal care guidelines. All animals were female cross-bred MARCIII beef heifers, 6 to 8 months of age, 214 to 241 kg, housed in the same feedlot pen for 2 months prior to fecal collection, and fed the same typical feedlot beef production growing rations consisting of 61.6% corn silage (41.3% dry matter), 15.2% alfalfa hay, 20.9% corn, and 2.3% liquid supplement.Total fecal DNA was isolated from homogenized samples using MoBio UltraClean fecal kit (Carlsbad, CA). PCR was performed using 27F and 1392R primers (11). Amplification consisted of 25 cycles, with an annealing temperature of 55°C. Amplicons from three reactions per sample were pooled (8), cloned using the Invitrogen TOPO TA cloning kit (Carlsbad, CA), and sequenced bidirectionally with M13 primers using an ABI 3700 sequencer (17). Low-quality and chimeric sequences (6) were excluded from further analysis. Distance matrices were compiled from ClustalW alignments (18) in PHYLIP (4). Pairwise estimates of shared richness were calculated using EstimateS, version 8.2 (R. K. Colwell; http://purl.oclc.org/estimates). DOTUR (16) was used to identify operational taxonomic units (OTUs) and to generate rarefaction curves (Fig. ​(Fig.2),2), richness and evenness estimates, and Shannon''s and Simpson''s diversity indices (Table ​(Table1).1). A 97% similarity cutoff and an 85% similarity cutoff for estimating OTUs were used to approximate species and class-level designations (15). Taxonomies were assigned to one member of each OTU using the RDP “classifier” tool (19), and the RDP taxonomic information was used for Fig. ​Fig.11 and ​and3.3. Common bovine taxa were identified based on inclusion in all three U.S. culture-independent studies (this study and references 1 and 11).Open in a separate windowFIG. 2.Rarefaction curves for six feedlot beef cattle. OTUs were assigned at the 85% DNA sequence similarity level. For comparison purposes, all six curves were truncated after 1,321 sequences.Open in a separate windowFIG. 3.Phylum-level distribution of bacterial sequences from six beef feedlot cattle. Asterisks indicate unclassified members of the named taxon.

TABLE 1.

Richness and diversity indices for 6 beef feedlot cattle