Development and validation of novel methods for microbial source tracking based on Escherichia coli as an indicator of water quality

Microbial pollution in water periodically affects human health in Australia, particularly in times of drought and flood. There is an increasing need for the control of waterborn microbial pathogens. Methods, allowing the determination of the origin of faecal contamination in water, are generally referred to as Microbial Source Tracking (MST). Various approaches have been evaluated as indicatorsof microbial pathogens in water samples, including detection of different microorganisms and various host-specific markers. However, until today there have been no universal MST methods that could reliably determine the source (human or animal) of faecal contamination. Therefore, the use of multiple approaches is frequently advised. MST is currently recognised as a research tool, rather than something to be included in routine practices. The main focus of this research was to develop novel and universally applicable methods to meet the demands for MST methods in routine testing of water samples. Escherichia coli was chosen initially as the object organism for our studies as, historically and globally, it is the standard indicator of microbial contamination in water. In this thesis, three approaches are described: single nucleotide polymorphism (SNP) genotyping, clustered regularly interspaced short palindromic repeats (CRISPR) screening using high resolution melt analysis (HRMA) methods and phage detection development based on CRISPR types. The advantage of the combination SNP genotyping and CRISPR genes has been discussed in this study. For the first time, a highly discriminatory single nucleotide polymorphism interrogation of E. coli population was applied to identify the host-specific cluster. Six human and one animal-specific SNP profile were revealed. SNP genotyping was successfully applied in the field investigations of the Coomera watershed, South-East Queensland, Australia. Four human profiles [11], [29], [32] and [45] and animal specific SNP profile [7] were detected in water. Two human-specific profiles [29] and [11] were found to be prevalent in the samples over a time period of years. The rainfall (24 and 72 hours), tide height and time, general land use (rural, suburban), seasons, distance from the river mouth and salinity show a lack of relashionship with the diversity of SNP profiles present in the Coomera watershed (p values > 0.05). Nevertheless, SNP genotyping method is able to identify and distinquish between human- and non-human specific E. coli isolates in water sources within one day. In some samples, only mixed profiles were detected. To further investigate host-specificity in these mixed profiles CRISPR screening protocol was developed, to be used on the set of E. coli, previously analysed for SNP profiles. CRISPR loci, which are the pattern of previous DNA coliphages attacks, were considered to be a promising tool for detecting host-specific markers in E. coli. Spacers in CRISPR loci could also reveal the dynamics of virulence in E. coli as well in other pathogens in water. Despite the fact that host-specificity was not observed in the set of E. coli analysed, CRISPR alleles were shown to be useful in detection of the geographical site of sources. HRMA allows determination of ‘different’ and ‘same’ CRISPR alleles and can be introduced in water monitoring as a cost-effective and rapid method. Overall, we show that the identified human specific SNP profiles [11], [29], [32] and [45] can be useful as marker genotypes globally for identification of human faecal contamination in water. Developed in the current study, the SNP typing approach can be used in water monitoring laboratories as an inexpensive, high-throughput and easy adapted protocol. The unique approach based on E. coli spacers for the search for unknown phage was developed to examine the host-specifity in phage sequences. Preliminary experiments on the recombinant plasmids showed the possibility of using this method for recovering phage sequences. Future studies will determine the host-specificity of DNA phage genotyping as soon as first reliable sequences can be acquired. No doubt, only implication of multiple approaches in MST will allow identification of the character of microbial contamination with higher confidence and readability.

Conformational epitopes on the diabetes autoantigen GAD65 identified by peptide phage display and molecular modeling

The major diabetes autoantigen, glutamic acid decarboxylase (GAD65), contains a region of sequence similarity, including six identical residues PEVKEK, to the P2C protein of coxsackie B virus, suggesting that cross-reactivity between coxsackie B virus and GAD65 can initiate autoimmune diabetes. We used the human islet cell mAbs MICA3 and MICA4 to identify the Ab epitopes of GAD65 by screening phage-displayed random peptide libraries. The identified peptide sequences could be mapped to a homology model of the pyridoxal phosphate (PLP) binding domain of GAD65. For MICA3, a surface loop containing the sequence PEVKEK and two adjacent exposed helixes were identified in the PLP binding domain as well as a region of the C terminus of GAD65 that has previously been identified as critical for MICA3 binding. To confirm that the loop containing tile PEVKEK sequence contributes to the MICA3 epitope, this loop was deleted by mutagenesis. This reduced binding of MICA3 by 70%. Peptide sequences selected using MICA4 were rich in basic or hydroxyl-containing amino acids, and the surface of the GAD65 PLP-binding domain surrounding Lys358, which is known to be critical for MICA4 binding, was likewise rich in these amino acids. Also, the two phage most reactive width MICA4 encoded the motif VALxG, and the reverse of this sequence, LAV, was located in this same region. Thus, we have defined the MICA3 and MICA4 epitopes on GAD65 using the combination of phage display, molecular modeling, and mutagenesis and have provided compelling evidence for the involvement of the PEVKEK loop in the MICA3 epitope.