Environmental Forensics The Use Of Molecular Techniques Biology Essay

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This literature review will consist of the discussion of scientific articles and journals that have contributed to the testing and understanding of molecular techniques and various other methods which are used to analyse data that provide information about the diversity of communities that reside within a particular environment. Reviewing this information will allow me to enhance my knowledge of environmental forensics and the types of practical procedures that are conducted on environmental samples; which will in turn allow me to decide upon a project area.

Introduction

The use of environmental forensic procedures have proven to play an essential role in categorising biological communities and developing databases containing vital information that can be used to evaluate evidence in the court of law. Environmental forensics can be broken down into more specific areas of research, including: ecology, botany, mycology and bacteriology, amongst many others. Information obtained from sources such as soil samples can be studied and the effects of biological, chemical and physical changes in the environment surrounding microbial communities can be monitored and investigated further (Hirsch et al., 2010). By delving deeper into the studies conducted about the communities present in soil samples, it can be seen that specific regions within the DNA and RNA of these environmental samples show patterns and differences that have allowed for them to be forensically analysed using culture-independent techniques. Analysis of soil samples is a common procedure used to investigate the microbial communities and taxa present in the sample such as bacteria and fungi (Curtis and Sloan, 2005). The ribosomal RNA (rRNA) obtained from the active members of each species in the community can undergo microarrays, high-throughput sequencing, terminal restriction fragment length polymorphisms (TRFLP) and denaturing gradient gel electrophoresis (DGGE) to determine which is the most dominant species within the community (Lerner et al., 2005 and Hirsch et al., 2010). These molecular techniques can help identify different microorganisms within the soil sample population based on the information collected from the rRNA of the organisms and comparing it to data already catalogued in electronic databases such as GenBank (Porter and Golding, 2012). One of the most important techniques used for forensic analysis of biological communities is the polymerase chain reaction (PCR). Many older studies found that extracting the desired nucleic acids from samples was difficult in the sense that only a small amount of functioning cells could be obtained and worked on. The use of PCR has allowed for specific regions of the DNA and RNA in these cells to be amplified, which results in numerous experiments being able to be performed from what was originally a very small sample. PCR is an example of a technique which is used in support of other molecular techniques previously mentioned in the introduction and its use in previous studies will be discussed further in the review (Hirsch et al., 2010). Taxonomic identification and species barcoding is the foundation of all information related to species and taxa identification. The rRNA genes are considered to be a reliable source of identification of species within a biological community population due to their high conservation across the different species. rRNAs global occurrence allows for them to be used as nuclear markers in the identification of species, which could potentially provide evidence and information more specific than the current methods which use the cytochrome oxidase I gene (COI) as mitochondrial markers for their eukaryotic DNA sequencing tool (Sonnenberg et al., 2007). Sections of the ribosomal genes that are used as markers contain divergent parts in combination with the conserved parts. The ribosomal DNA (rDNA) in these genes contains a large subunit and a small subunit - LSU and SSU respectively. The LSU of these genes (16s rDNA) contains the divergent regions D1-D2 which although small, can be amplified using the correct primers in PCR and then further evaluated to differentiate species within a given ecological sample (Sonnenberg et al., 2007). These divergent regions can be used to sequence the species found in biological communities, e.g. fungi, and molecular techniques such as: the BLAST + Metagenomic Analyser (BLAST + MEGAN), the Statistical Alignment Package (SAP) and Ribosomal Database Project naïve Bayesian classifier (NBC) can be used to test how sequence length, primer choice and the errors that come with these choices can affect how accurate the classification of the species being tested is (Porter and Golding, 2012).

Discussion

Soil samples: Microorganism detection, extraction and purification

Figure 1. A flow chart showing the processes whereby DNA and RNA are extracted and analysed from a soil sample (Hirsch et al., 2010).The studies carried out by Curtis and Sloan (2005) and Gans et al. (2005) showed that there will always be a bias present when working with soil sample communities due to the large numbers and high diversity rate of the microorganisms that are available in each gram of the soil sample (Curtis and Sloan., 2005 and Gans et al., 2005). It is important to remember this statement when selecting the appropriate technique needed to evaluate the sample in order to utilize the most effective method and eliminate or reduce any bias that could occur. It has also been suggested by Hirsch et al. (2010) that methods using culture-dependent techniques are less reliable and affective in comparison to culture-independent techniques because on average only 1% of active cells in a soil sample gram are thought to be able to undergo culture-dependent techniques, which is such a small percentage overall (Skinner et al., 1952; Davis et al., 2005 and Hirsch et al., 2010). This is an excellent example of why PCR is such a vital procedure in forensic analysis of biological communities; it allows for the DNA and RNA of the small amount of active cells present in the sample to be amplified and analysed on a much larger scale - which is extremely advantageous. Studies conducted by authors Hirsch et al. (2010) have shown ways by which DNA and RNA can be extracted and labelled from a soil sample (Figure 1) and numerous molecular methods that can be used for their analysis (Table 1). As mentioned previously in the review, soil samples are notorious for being contaminated with various substances such as: organic and non-organic matter, particles of clay and humic substances (Moran et al., 1993). It is therefore essential that the extraction and purification of the nucleic acids required from the sample are collected precisely using the most reliable technique to avoid any bias from contaminants within the sample. The ubiquitous RNAases are contaminants which rapidly degrade RNA. RNAases therefore need to be deactivated before RNA can be extracted from the soil sample in order for the RNA to be used for further investigation (Ogram et al., 1995; Mendum et al., 1998; Saleh-Lakha et al., 2005 and Hirsch et al., 2010). The removal of these contaminants then purifies the sample. Before the active cells in a soil sample can be analysed they need to undergo a type of cell lysis that breaks down the cell wall in order for the nucleic DNA to be extracted and analysed. Bead-beating has proven to be an effective method of disrupting cell walls; however it has been shown that this process needs to be adapted to different types of soil. An example of this is when cells from a soil sample containing a high clay particle content need to be lysed; their affinity to bind water makes it difficult for the cell walls to be broken down, so a more aggressive form of bead-beating is used. This type of methodology could be considered disadvantageous due to the time it may take to change the procedure for each individual sample, but its flexibility to suit the different soil types can be considered an advantage (Hirsch et al., 2010). A study conducted by Lerner et al. (2005) found that the Tsai and Olsen method of DNA extraction (when combined with bead-beating) worked best in comparison to four other extraction methods. The authors deducted that fewer impurities were extracted alongside the DNA, thereby making it the most appropriate method to use (Lerner et al., 2005).

Table 1. The different molecular methods used to assess soil samples (Hirsch at al., 2010).

PCR: amplification and analysis

As mentioned in the introduction, PCR is a vital and common method used in forensic analysis of biological communities. The studies conducted by Lerner et al. (2005) and Sonnenberg et al. (2007) are two examples of how effective PCR is in amplifying selective DNA and RNA regions. Specific genes within the DNA can be amplified by the use of selective primers that anneal and extend the DNA strands that undergo the amplification (Lerner et al., 2005 and Sonnenberg et al. 2007). Once the desired PCR products have been obtained and replicated from the sample, they can be subjected to DGGE and microarrays which sequence the PCR products and can be analysed to help determine the identity of the different communities present in the soil sample (Hirsch et al., 2010). The identification of these communities are based on the different nucleic acids that belong to specific microorganisms, mainly whose sequences have already been recorded and stored in electronic databases such as GenBank (Sonnenberg et al., 2007). By observing Table 1 it can be seen that PCR is often used alongside most other analysis methods even though they are performed to investigate different areas of the biological communities; such as diversity and abundance. The methods used for analysing the sequences of the microorganisms can be seen in Figure 1 and will be discussed further in the review.

DGGE and TRFLP

Figure 2. A DGGE profile showing the bacterial communities present in soil samples taken from thirteen different places (Lerner et al., 2005).The analysis of soil samples can provide information about the different types of biological communities that reside within that sample. The DGGE process enables visual patterns to be seen on a profile that shows the diversity of the microorganisms that are in the community from which the sample was taken. Hirsch et al. (2010) suggested that the bands which form at variable positions on the DGGE profile are a result of different sequencing compositions of the PCR products migrating to different sections of the gel (Hirsch et al., 2010). This theory is supported by the study carried out by Lerner et al. (2005) which collected a DGGE profile that showed the presence of bacterial communities from different soil samples - Figure 2. As seen in Figure 2, a diverse range of bacterial communities were found in each of the thirteen soil samples. The 16s rDNA was taken from each sample using the Tsai and Olsen extraction method (Tsai and Olsen, 1991) and then amplified using PCR which enabled amplicons within the 16s DNA to be replicated and then observed after undergoing DGGE. The analysis of the nucleic acid in this example has proven that it is a sufficient marker for differentiating the communities within a soil sample. Although DGGE is a useful and efficient tool for segregating data, it does have its downsides, which are: dominant species within the community could cause a bias when sampling and sometimes the bands can end up travelling to the same position (Lerner et al., 2005). Hirsch et al. (2010) also suggested that the use of TRFLP (which uses a fluorescent label to mark specific primers before PCR and then digests the products using restriction enzymes which expose the polymorphism) can be used to separate the varying species within a sample once it has been run on agar gel and subjected to gel electrophoresis. The fragment sizes can then be compared against data already collaborated on databases to identify the each species (Hirsch et al., 2010). In contrast to this statement however, is the study conducted by Hawksworth and Wiltshire (2010) which stated that the use of TRFLP is not a practical way of collecting data mainly due to rise of numerous fragments clustering together as a result of PCR inefficiency, which appear as peaks on a line graph. This is a major drawback of the process (Hawksworth and Wiltshire., 2010).

Analysing nucleic acids The use of 16s rDNA in bacteria was mentioned previously in the review, but why is rDNA so useful in allowing us to discover, compare and identify different species within a soil sample community? The LSU is a section of rDNA that contains the divergent regions D1-D2. Sonnenberg et al. (2007) conducted an experiment that provided evidence to support the theory that this particular site in rDNA can be used as a suitable marker for the identification of species and taxa. Although the experiment was conducted on animals, it can be hypothesised that the same result would occur if a different eukaryote was used, for example fungi. The use of the BLAST + MEGAN classification method and GenBank allowed information regarding the LSU rDNA sequences to be obtained, however a more recent study by authors Porter and Golding (2012) indicated that although BLAST + MEGAN doesn't provide the measure of confidence for a classification it does produce the lowest amount of error (Sonnenberg et al., 2007 and Porter and Golding, 2012). Many evaluations have been undertaken in regards to the phylogeny of fungi over the years to determine which method can accurately identify and distinguish the fungal taxa within a biological community. Porter and Golding (2012) used SAP and NBC along with BLAST + MEGAN to determine if specific regions within the LSU of fungi could distinguish between the different taxa and species of communities within a soil sample. The authors learnt that they needed to identify the correct primers that were to be used in the taxa identification so that the most informative region within the rDNA was targeted. This then allowed them to identify the primer binding sites in the rDNA on the basis of information about sequence similarity available on the BioPearl database. The results that the authors collected suggested that the NBC method would be best suited to collect and assign the taxonomic data extracted from the LSU rDNA of fungi. NBC combined with MEGAN produces sequence comparison results at a rapid rate; however they also found that SAP would be an equally suitable method of calculating taxonomy if practical time wasn't of the essence (Porter and Golding, 2012). Although studies have been carried out to categorise taxonomic and species data concerning fungi based on their rDNA, most methods are not considered to be sufficient enough to be used in processing legal evidence. Gaps in these studies have led to an indication that almost 20% of sequence data stored in GenBank is incorrect, meaning certain fungal strains may be wrongly identified resulting in inaccurate data being published (Nilsson et al., 2006).

Conclusion

The use of molecular techniques for analysing communities present in a soil sample is an extremely useful tool to have. Methods such as DGGE combined with PCR produce data that can be stored in electronic databases for comparison against newer studies that are continuously being conducted. It has been established that particular regions within the LSU rDNA of eukaryotes anneal to specific primers which once bound can be amplified in order for further analysis to be carried out on them. Techniques such as BLAST + MEGAN, NBC and SAP can then be applied to these samples to identify, categorise and differentiate the individual species that were present in the original sample. The sequence information gained from these discriminating methods can also indicate the taxa within the sample population. There are many interesting opportunities that have yet to be acted upon in respect to bacterial identification from soil samples. I believe it would be advantageous to personally test out the DGGE method to see if there is any correlation between the profiles of bacteria present in an urban soil sample in comparison to a soil sample taken from the countryside.

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