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The identification of body fluids within a forensic setting is important as it can help to reconstruct a crime scene and show whether events happened as they were reported. In addition, knowing the type of body fluid present can be of huge benefit when looking for DNA as it can give an indication of the type of extraction method to be used. For example, different techniques are used to extract DNA from saliva compared to extraction from sperm.
Currently accepted methods of identifying body fluids involve using presumptive tests followed by confirmatory techniques. For example, the Brentamine test is used for detecting acid phosphatase in seminal fluid. However, tests such as this can only be presumptive because positive results can be given by other substances, such as vaginal acid phosphatase and some plant derivatives (Saferstein, 2011). The confirmatory test for sperm is microscopy after staining with haematoxylin and eosin. In cases of aspermic samples, the Florence test is often used for confirmatory purposes. In addition, there are a variety of presumptive tests available to test for the presence of blood, including the Kastle-Meyer (KM) test and the Leuco-Malachite Green (LMG) test. However these both produce false positives. Confirmatory tests for blood can be carried out using microscopy, spectroscopy and immunology, as well as chromatographic techniques and crystal tests such the Teichman test and Takayama test (Saferstein, 2011).
Although these techniques have a proven track record, the problem is that they each have their drawbacks. Not only are there issues with sensitivity and false positives but many of the techniques are also very time consuming. Another important disadvantage is the amount of sample that is being used. If there is only a small stain found at a crime scene, it is essential to know what it is but it is also important to preserve some of the sample. In addition previous methods of analysis may be able to identify that a sample is blood for example, but could not differentiate between menstrual blood and venous blood (Wang et al. 2012).
Micro RNA (miRNA), is a short sequence of non-coding RNA of approximately 18-25 nucleotides long (Wang et al. 2012). They attach to particular mRNAs after transcription and regulate their degradation or translational abilities. It is believed that each miRNA effects many RNA molecules and therefore contain vast amounts of cell information including tissue differentiation and development (Pritchard, Cheng & Tewari, 2012).
In recent years forensic science has developed an interest in analysing mRNA for body fluid identification. As RNA is important in cell differentiation and development, it contains information specific to different cell types. This is also true for miRNA. However, the problem relating to RNA usage is the fact that it is prone to degradation. This is aggravated by moisture, pH levels in the environment, heat and ultraviolet light, all of which limit its stability. However, because of its significantly smaller size, miRNA is much more stable and more discriminatory than mRNA (Courts & Madea, 2010). This stability means that it is more likely to be successfully retrieved from a degraded or small sample. Several investigations have been successfully performed into retrieving miRNA from aged samples and it has been reported that a time-wise degradation experiment showed that after one year in lab conditions, the levels of expression and the miRNA profiles remained constant (Zubakov et al. 2010). In addition, some cold cases may have Formalin-Fixed, Paraffin-Embedded (FFPE) samples being stored and whereas RNA is then very difficult to extract and is damaged by the processes, miRNA due to its more robust nature has proved more easily retrievable and still retains a high level of expression (Li et al. 2007).
Extraction of miRNA is often performed with chemical techniques such as chaotropic salts, followed by sold phase extraction. RNA may also be separated and sorted according to size by polyacrylamide gel. This allows small RNA strands and miRNA to be sequestered (Pritchard, Cheng & Tewari, 2012). Quantification may be carried out by methods based on reverse transcription and quantitative PCR (Omelia, Uchimoto & Williams, 2013) (Chen et al. 2005) or normalisation by spiking samples of plasma or serum (Pritchard, Cheng & Tewari, 2012).
The procedures for analysing miRNA are still under investigation with reverse transcription quantitative PCR, using Taqman being a favourite (Wang et al. 2013). Some experiments have involved microarrays (Zubakov et al. 2010)(Courts & Madea, 2011). Other potential techniques involve miRNA sequencing or Northern Blotting. Northern Blotting has been regularly used for mRNA analysis but is not particularly useful for miRNA as it cannot differentiate between the mature miRNA and its precursor (Wang et al. 2012). RNA based methods result in the detection of small RNA molecules, not just miRNA but the technique is still being investigated (Pritchard, Cheng & Tewari, 2012). Interactions between miRNAs and mRNAs have also been studied. This is done by forming covalent bonds between RNA and binding proteins through ultraviolet irradiation, followed by purification. This method is called Crosslink Immunoprecipitation (CLIP) but appears to be of more benefit in clinical terms than forensic science (Pritchard, Cheng & Tewari, 2012)(Jensen & Darnell, 2008).
In the first study examining miRNA potential, nine miRNAs were described as showing recognisable differences which allowed for body fluid identification. This was done using 50 picograms of RNA using quantitative PCR. It also showed that differentiation for seminal fluid also included aspermic samples, meaning that only the one test would be necessary for identification. The markers used for semen identification were miR135b and miR10b. Another advantage of the technique was that it allowed the distinction between menstrual and venous blood by using the markers miR451 and miR412 (Hanson, Lubenow & Ballantyne, 2009).
Possible miRNAs have been earmarked by further research and by using different techniques. By using microarray another 14 possible markers were found. However, it was also discovered that there were differences in the results depending on whether microarray or reverse transcription PCR was used but this was largely dependent on the body fluid in question. For example, by microarray the marker miR-891a appeared to very prevalent in vaginal secretions. However, according to the quantitative PCR method, it only appeared to be present in seminal fluid (Zubakov et al. 2010). The differences in results between the studies of Hanson et al. and Zubakov et al., have been explained as being a consequence of approaching the procedure with different methodologies and because of the small size of sample used. However, it has also been pointed out that because miRNA is not exclusive to any one type of tissue or body fluid, it means that different groups of markers can be used for identification. Again, the choice of markers will be dependent on the methodology used but this highlights the need for standardization and validation of methods (Courts & Madea, 2010). New miRNA markers and techniques are still under investigation.
There are several problems related to using miRNA. Firstly, the mature miRNA used for body fluid identification originates from a much longer primary strand (pri-RNA) which may contain several thousand nucleotides. This undergoes cleavage into precursor miRNA (pre-miRNA) of approximately 70-100 nucleotides and then into the mature 18-25 nucleotide strands. This means that analytical techniques need to be able to differentiate between the types of miRNA. In addition, the lengths of the strands tend to vary and some sequences may only be one nucleotide different to others, making them difficult to isolate. These differences are often related to modifications designed to enhance functionality and stability. Also because of their small size, traditional primers cannot anneal to the strands. This becomes more difficult as there are no particular sequences which allow for binding and features such as a poly 'A' tail do not occur (Pritchard, Cheng & Tewari, 2012). This situation can be remedied by stem-loop techniques (Chen et al. 2005). In addition, the short length of the miRNA containing differing nucleotides means that the annealing temperatures required can vary enormously thus making it difficult to copy large quantities. The use of stem-loop technology can also help with this (Pritchard, Cheng & Tewari, 2012).
The stem-loop reverse transcriptase and real-time PCR process with Taqman. Taken from Chen et al. 2005
The stem-loop process works by having special primers which bind to the miRNA and loop round to allow reverse transcription to take place. This then undergoes PCR with the TaqMan probe and its linked dyes for quantification. It also uses a tailed primer which adds extra nucleotides to balance the temperature required (Chen et al. 2005).
Another solution to the various annealing temperatures is to use Locked Nucleic Acids (LNAs) (Pritchard, Cheng & Tewari, 2012). LNAs are designed to maintain a locked conformation, by applying a methylene bridge. This conformation increases their affinity for binding and makes the oligonucleotide more stable, even at higher temperatures (Vester & Wengel, 2004).
A locked nucleic acid. Taken from Vester & Wengel, 2004.
Real-time quantitative polymerase chain reaction (RTQ-PCR) has become an effective method of choice and an accepted method of validation which has been used in a number of studies, including that by Zubakov et al. 2010 and Courts & Madea, 2011. However, it has been pointed out that results from this technique are not completely accurate. Instead there is a degree of variability and subsequent reports are often biased towards effective results (Nelson et al. 2008). This does not mean that the technique should not be used but that there should be an awareness of its limitations.
The use of microarrays allows for larger quantities of miRNAs to be studied. This often involves marking the strands with a fluorescently labelled nucleotide on the 3' end. Depending on how the technique is performed, it may be necessary to remove the phosphate on the 5' end which is a result of the endonuclease Dicer. If the dephosphorylation is not carried out then it may link with the 3' ligase (Pritchard, Cheng & Tewari, 2012). However, studies have shown that the use of some ligases and polymerase molecules can lead to a sequence bias and makes random labelling very difficult. These problems can also affect the comparison of results from different size samples and therefore highlight the importance of comparing analogous experiments (Nelson et al. 2008). The sequence bias can be restricted by using alternative chemical techniques but all labelling will tend to add to background noise (Pritchard, Cheng & Tewari, 2012). Another microarray technique into miRNA analysis is the nanostring nCounter system, which uses sequence specific dye labelled probe pairs and microscopic imaging but is less prone to bias (Malkov et al. 2009). However, in general, microarrays are a cheaper option but tend to be less specific and have a limited quantification ability in comparison to other techniques (Pritchard, Cheng & Tewari, 2012).
MiRNA sequencing is another useful technique which has the advantage of being able to distinguish between strands which vary by one nucleotide. It begins with reverse transcription to a cDNA library. Ligation is used to add adaptors and then the cDNA is immobilised, either on beads or a solid surface. The disadvantage of this method is that small strands of RNA are also picked up, not just the miRNA. It also has a tendency to bias towards particular miRNAs over others (Pritchard, Cheng & Tewari, 2012).
An interesting new study has been undertaken to determine whether it would be possible to undertake miRNA extraction in 'cold cases' where DNA had already been extracted. The results showed that miRNA was present in higher quantities where DNA extraction had been performed than through mRNA extraction procedures. It was surmised that the miRNA withstood the purification processes because of it high stability, which mRNA would not but this does not explain why the DNA procedure should produce a greater yield. The study looked at identification of blood and saliva samples but further research is required (Omelia, Uchimoto & Williams, 2013). An investigation into simultaneous miRNA and DNA analysis has been undertaken and the results have demonstrated that in addition to a full profile from the DNA, specific markers for saliva and additional specific markers for blood have also been identified (van der Meer, Uchimoto & Williams, 2012). This paper is due to be published later this year (Omelia, Uchimoto & Williams, 2013).
Further problems can occur because none of the miRNAs contain information for only one cell or body fluid type. So they are not exclusive. This means that for sample identification, several markers are needed to be present in conjunction with each other. It cannot be performed accurately based on an individual marker (Hanson, Lubenow & Ballantyne, 2009). The choice of markers is assessed based on abundance and detection rates. The markers which show a greater variance of abundance in some body fluids compared to others and which are more easily detectable are chosen. A popular method of analysing the data has been to produce graphs based on the cycle threshold values (Ct). In addition, the âˆ†Ct values, which are the differences between the Ct and the normalised value using a standard, have been used to make two dimensional scatter plots thus enabling easier visualisation. Through this technique, distinct clumping patterns of particular miRNAs can be detected and show notable differences according to the body fluid being analysed (Hanson, Lubenow & Ballantyne, 2009). As previously commented, variations in marker specificity and abundance also seem to vary according to the methodology used.
There also needs to be an awareness of added difficulties presented in different body fluid types, for example the effects of RNAse in blood plasma which lower the levels (Pritchard, Cheng & Tewari, 2012). It has even been mentioned that further investigation is needed to examine the effects of disease and illness, in order to identify any differences in the miRNAs and their abundance or specificity resulting from variations in the human condition. For example, it is not yet known how much the B cells contribute to miR16 expression in blood. Therefore, it is not known, without specific testing, whether individuals with chronic lymphoctic leukemia would produce blood samples that could be identifiable as blood through miRNA expression (Hanson, Lubenow & Ballantyne, 2009). Although this may only affect a small number of crime scene samples, it could reflect in some and therefore an awareness of the possibility is important.
The benefit of being able to identify the type of body fluid present at a crime scene by using a small proportion of the sample is evident. Zubakov demonstrated that the extreme sensitivity of the qPCR procedure and high copy number of miRNA, meant that quantities of 0.1pg of RNA could be used to distinguish relevant miRNA (Courts & Madea, 2010). These advantages and continued research show this to be a promising area for further investigation.