Evaluation of direct 16S rDNA sequencing as a metagenomics-based approach to screening bacteria in bottled water.

Deliberate or accidental contamination of food, feed, and water supplies poses a threat to human health worldwide. A rapid and sensitive detection technique that could replace the current labor-intensive and time-consuming culture-based methods is highly desirable. In addition to species-specific assays, such as PCR, there is a need for generic methods to screen for unknown pathogenic microorganisms in samples. This work presents a metagenomics-based direct-sequencing approach for detecting unknown microorganisms, using Bacillus cereus (as a model organism for B. anthracis) in bottled water as an example. Total DNA extraction and 16S rDNA gene sequencing were used in combination with principle component analysis and multicurve resolution to study detection level and possibility for identification. Results showed a detection level of 10(5) to 10(6) CFU/L. Using this method, it was possible to separate 2 B. cereus strains by the principal component plot, despite the close sequence resemblance. A linear correlation between the artificial contamination level and the relative amount of the Bacillus artificial contaminant in the metagenome was observed, and a relative amount value above 0.5 confirmed the presence of Bacillus. The analysis also revealed that background flora in the bottled water varied between the different water types that were included in the study. This method has the potential to be adapted to other biological matrices and bacterial pathogens for fast screening of unknown bacterial threats in outbreak situations.

Shift from farm to dairy tank milk microbiota revealed by a polyphasic approach is independent from geographical origin.

Detailed information on the natural microbial community present in raw milk, especially on the non-cultivable part of the milk microbiota, is rather limited as research in the past mainly focused on the detection of bacterial pathogens or microorganisms responsible for the deterioration of raw milk. In frame of the EU project BIOtracer raw milk samples from three different European countries were analyzed to gain a deeper insight into the diversity of the natural bacterial flora of raw milk by combining culture-dependent and -independent methods. Fourier-transform infrared (FTIR) spectroscopy was used as rapid and cost efficient metabolic fingerprinting technique to monitor the cultivable microbiota of raw milk. In addition, direct sequencing was applied to acquire additional information on the non-cultivable part of the bacterial raw milk flora. Subsequent performed biostatistical analysis revealed a high correlation between the data gathered by culture-dependent and independent methods. Both methods revealed significant differences between the microbiota of farm and dairy tank milk, which appeared to be rather independent from geographical regions. Based on the results from FTIR and direct sequencing, the predominant bacterial raw milk flora was determined, representative isolates were selected and two model floras, representative for farm tank milk and dairy bulk tank milk, were compiled. These bacterial model floras for raw milk are now available for the Biotracer partners and can be used for validation purposes or contamination scenarios. The knowledge gained on the variation range of the normal raw milk microbiota will help to identify raw milk with divergent microbiota, pointing towards potential pathogen contaminations.

Co-infection dynamics of a major food-borne zoonotic pathogen in chicken.

A major bottleneck in understanding zoonotic pathogens has been the analysis of pathogen co-infection dynamics. We have addressed this challenge using a novel direct sequencing approach for pathogen quantification in mixed infections. The major zoonotic food-borne pathogen Campylobacter jejuni, with an important reservoir in the gastrointestinal (GI) tract of chickens, was used as a model. We investigated the co-colonisation dynamics of seven C. jejuni strains in a chicken GI infection trial. The seven strains were isolated from an epidemiological study showing multiple strain infections at the farm level. We analysed time-series data, following the Campylobacter colonisation, as well as the dominant background flora of chickens. Data were collected from the infection at day 16 until the last sampling point at day 36. Chickens with two different background floras were studied, mature (treated with Broilact, which is a product consisting of bacteria from the intestinal flora of healthy hens) and spontaneous. The two treatments resulted in completely different background floras, yet similar Campylobacter colonisation patterns were detected in both groups. This suggests that it is the chicken host and not the background flora that is important in determining the Campylobacter colonisation pattern. Our results showed that mainly two of the seven C. jejuni strains dominated the Campylobacter flora in the chickens, with a shift of the dominating strain during the infection period. We propose a model in which multiple C. jejuni strains can colonise a single host, with the dominant strains being replaced as a consequence of strain-specific immune responses. This model represents a new understanding of C. jejuni epidemiology, with future implications for the development of novel intervention strategies.

Multivariate analysis of complex DNA sequence electropherograms for high-throughput quantitative analysis of mixed microbial populations.

High-throughput quantification of genetically coherent units (GCUs) is essential for deciphering population dynamics and species interactions within a community of microbes. Current techniques for microbial community analyses are, however, not suitable for this kind of high-throughput application. Here, we demonstrate the use of multivariate statistical analysis of complex DNA sequence electropherograms for the effective and accurate estimation of relative genotype abundance in cell samples from mixed microbial populations. The procedure is no more labor-intensive than standard automated DNA sequencing and provides a very effective means of quantitative data acquisition from experimental microbial communities. We present results with the Campylobacter jejuni strain-specific marker gene gltA, as well as the 16S rRNA gene, which is a universal marker across bacterial assemblages. The statistical models computed for these genes are applied to genetic data from two different experimental settings, namely, a chicken infection model and a multispecies anaerobic fermentation model, demonstrating collection of time series data from model bacterial communities. The method presented here is, however, applicable to any experimental scenario where the interest is quantification of GCUs in genetically heterogeneous DNA samples.

Quencher extension for single nucleotide polymorphism quantification in bacterial typing and microbial community analyses.

Quencher extension is a novel single-step closed tube real-time method to quantify single nucleotide polymorphisms (SNPs) in combination with primer extension. A probe with a 5'-reporter is single-base extended with a dideoxy nucleotide containing a quencher if the target SNP allele is present. The reaction is measured from the quenching (reduced fluorescence) of the reporter. The relative amount of a specific SNP allele is determined from the nucleotide incorporation rate in a thermocycling reaction. The quencher extension protocol presented was developed for SNP allele quantification in Listeria monocytogenes and for microbial community analyses.

Comparison of chicken gut colonisation by the pathogens Campylobacter jejuni and Clostridium perfringens by real-time quantitative PCR.

We compared the colonisation of the chicken gut by the two important pathogens Campylobacter jejuni (frequent food-borne pathogen) and alpha-toxin gene containing Clostridium perfringens (causative agent of necrotic enteritis in chickens) using a new high-throughput automated DNA purification method for microbial biodiversity analyses. The method gave high reproducibility (standard deviation of 1.1 C(T)-values for a universal 16S rDNA real-time PCR), and inhibition was observed in only 0.9% of the individual DNA purifications (n = 753). We analysed 253 randomly collected chicken caecal samples (sampled in 2001 and 2003) from Norwegian chicken flocks by real-time quantitative PCR. Our results showed positive correlation (P = 0.009) in chicken caecal colonisation between C. jejuni and Cl. perfringens. We also found that there was a significant underrepresentation (P = 0.008) of chickens containing high levels of Cl. perfringens and low levels of C. jejuni. This indicates a possible interaction between these bacteria. Potential interaction between pathogens and other bacteria in the gut will certainly be important research fields in the future. As demonstrated here, the development of new tools for high-throughput analyses will be of key importance for these studies.

Explorative screening of complex microbial communities by real-time 16S rDNA restriction fragment melting curve analyses.

We have developed restriction fragment melting curve analyses (RFMCA), which is a novel method for the real-time analysis of microbial communities. The major advantage of RFMCA compared to, for example, terminal restriction fragment length polymorphism (T-RFLP) or temperature/denaturing gradient gel electrophoresis (TGGE/DGGE) is that the physical separation of DNA fragments is avoided. The RFMCA detection is done by melting point analyses in closed tube systems, which enables high-throughput applications. The robustness of RFMCA was demonstrated by analyzing both mixtures of known samples and the microbial communities in the cecal content of poultry. Our conclusions are that RFMCA is robust, gives a relatively high resolution, and has the potential for high-throughput explorative screenings of microbial communities and large clone libraries.