miRNA as Biomarkers in Forensic Body Fluids Identification

miRNA profiling: What does not work for blood and urine identification

Sarah S. Silva a, b, Teixeira, A.L b, MJ Carneiro de Sousa a,c and Medeiros, R.a, b

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a – ICBAS, Abel Salazar Biomedical Sciences Institute, University of Porto, 4050-313 Porto, Portugal

b – Molecular Oncology group, Portuguese Institute of Oncology, 4200-072 Porto, Portugal

c _ National Institute of Legal Medicine and Forensic Sciences, North Branch, 4050-167 Porto, Portugal


In forensics, the identification of blood, semen or vaginal secretions can represent an important support for a criminal investigation. They can be used as a source of DNA but also can hold, only by their presence, the most probative value. Through the years many methodologies were used to identify them but all presented serious drawback. Lately, mRNA surged as a potential tool for body fluid identification but their sensibility were a serious disadvantage, even more pronounced in forensic samples. Since 2009, miRNA profiling surged as a possible tool as a confirmatory test in forensics due to their tissue specific pattern of expression. Unlike mRNAs they are much more stable due to their proprieties whose makes them less prone to degradation processes.

In this report, we studied the expressional patterns of miR-127, miR-221 and RNU-48 in 50 samples of urine and blood in order to define whether or not they could be used as biomarkers for urine or blood identification.

Even though our aim was to assess whether or not our miRNAs could be considered as biomarkers, we came across 2 others interesting conclusions: the impact of RNA purity in miRNAs quantification and which miRNA cannot be used as a normalisation gene for blood and urine identification.

Key words: miRNA profiling, Forensic, Serology, body fluids, biological biomarkers

1- Introduction

Human body fluids are important components to rely on a criminal investigation [1, 2]. As a matter of fact, a complainant’s body fluids present on items belonging to a suspect – or vice versa – holds the most probative value. For example, in a case of a sexual assault in a child, where a DNA profile recovered from the child bedding and underwear coincide with his father DNA profile, can we consider his father responsible for the sexual assault? In a case like this, it is not enough to recover a DNA profile but it is also imperative to acknowledge its source. If no serological test were done, in court, the presence of DNA could be explained as a result of the presence of epithelial cells in the child clothing which is totally common when it comes from a sibling. On the other hand, if serological tests linked the DNA profile to semen it would be way more difficult to explain its presence there.

Beyond the probative value that body fluid may have in a crime scene, it is also important to acknowledge them to optimize protocols to conduct a reliable DNA profiling [3, 4]. For example, DNA extraction processes are different for blood and urine. If we conducted the protocol of blood extraction in urine samples it may result in a reduced quality of the extracted DNA e enable any conclusive DNA profile [3, 4]. There is why, body fluids identification is considered as crucial step in criminal investigation.

For some, it seems easy to identify body fluids such as blood (colour), urine (smell) or even sperm (texture) however, when dried, washed or mixed with other components their identification may not be that easy [1]. It is important to highlight that in court, there is no such thing as “It seems to be sperm because it looked like it and have the same particular texture”, it is needed an undeniable proof that it is sperm. Serological test are used in forensic biology to allow the detection and identification of body fluids in both native form or as a residue left at a crime scene. Serological tests are divided in two major fields: Presumptive and confirmatory test. Presumptive tests rely on methodologies that are sensitive and performed quickly, yet they are not specific to the body fluid. Those tests can only indicate if the fluids might be present and do not unequivocally states its presence. On the other hand, confirmatory tests are indeed specific to the body fluid we seek to identify. As presumptive tests, confirmatory testing is sensitive however, it takes a lot more time.

Idealistically, we should have a battery of confirmatory test for all important body fluids in order to reliably detect and identify them. Unfortunately, there is a large cluster of presumptive tests and far less of confirmatory ones. Moreover, till date no confirmatory test is able to reliably differentiate blood from menstrual blood which is an unquestionably important body fluid in sexual cases.

Over the last years, mRNA profiling became a target for body fluid identification due to its tissue specific patterns. Still, mRNA susceptibility to degradation by physical or chemical factors was an unquestionable drawback. In order to sidetrack this problem, miRNA surge with a real potential as a confirmatory test. MiRNAs are small non-coding RNAs with more or less than 22 nucleotides of length that, combined with the RNA-induced silencing complex, seems to regulate a major part of human gene (5 e 6 do meu artigo). Moreover, their tight relationship with Argonaute proteins, they are much less susceptive to both biotic and abiotic factors. In 2009, Hanson and colleagues were the first to introduce miRNA profiling and soon enough others followed. Those studies pointed out a large collection of miRNAs with potential as biomarker, however very few were confirmed by more than one group which revealed the lack of reproducibility of results. Moreover, when some tried to replicate the results of others, they failed.

For this report, we choose to test four miRNAs in both blood and urine of 50 healthy individual and study their behaviour within those body fluids.

2- Material and methods

We conducted an expression profiling of 50 healthy individuals. The case group was composed by Caucasian individuals with no major pathological condition in order to erase a variable that could alter miRNAs profiles. Peripheral venous blood (Xml) and urine were collected from each subject following the obtainment of a written informed consent from all subjects.

After collected the samples were processed. The samples were used for miRNAs extraction with GRS microRNA Kit (Grisp) according to the manufacturer’s instructions. Subsequently, miRNa priorly extracted were used as a template for cDNA synthesis using TaqMan® MicroRNA Reverse Transcription Kit (Applied Biosystems®). To quantify miRNA expression, real-time PCR assays were performed with a StepOne™ System using TaqMan®Universal Master Mix II (Applied Biosystems®). The target miRNAs were amplified by a set of designed primers for miR-127-5p, miR-221*, miR-222* and RNU48. miR-222* was used as a normalization gene miRNAs relative quantifications.

The data analysis was performed using the StepOne Software v2.2 (Applied Biosystems®).

Statistical analysis was carried out by the computer software IBM®SPSS®Statistics (Version 22.0). In order to assess any statistical alterations in our normalized miRNAs expression we used 2???Ct method and Student’s t test.

3- Results
3.1- Cycle threshold vs RNA purity

Urine samples were processed and the resulting pellet was diluted in 1ml of Tripure. Visually a wide range of pink colour was noticeable within our urine samples. Those with a deep pink were related with samples with a more substantial pellet unlike those with a less considerable pellet who presented themselves with a lighter colour. After miRNA extraction, we quantify miRNA expression of miR-222 in urine samples and perceived that only few of them were detected. Interestingly, only the ones with a lighter colour were indeed detected. This tricky situation could be explained by the ratio of absorbance at 260 nm and 280 nm which is used to assess the purity of RNA. In this case, lighter colour was also an indicator of a greater ratio, on the other hand, those with higher optical density had a very low ratio, far from the ratio of ~2.0 which is generally accepted as “pure” for RNA. In order to sidetrack this delicate situation, we choose a sample (MU26) that has an optimal 260/280nm ratio and diluted the other samples to equalize their optical density with Tripure. Posteriorly, we choose 5 samples to test and noticed a considerable decrease of Ct in the samples processed with the optimized protocol (Fig.1). The difference of Ct value is very significant, nearly 6 Ct, demonstrating that RNA purity is clearly a factor that challenge miRNA profiling. As showed, miRNA quantification goes with a low concentration or can go totally undetected when 260/280nm ratio is low however, when optimized, miRNA concentration increased significantly. As said previously, different reports indicated miRNAs as biomarkers for human body fluids identification though, when others tried to replicate them, they failed. Our results shows that for the same sample, different degrees of purity can decide whether or not a miRNA is detected, once it definitely affect their concentration. There is why, RNA purity needed to be optimal otherwise it may lead to unreliable results, which could explain, the failed attempts done by some authors when trying to replicate others results.

Figure 1 – Cycle threshold vs RNA purity. This figure presents the Ct values of miR-222 taken from 5 samples processed with both normal and optimized protocol (first and second column respectively). It is showed that the considerable fall of Ct values correlates with an increase of 260/280nm ratio.

3.2 – Normalization gene

In qRT-PCR, data normalization is imperatively required for quantification analysis [5-7]. The integration of an invariant endogenous essay, also called as reference gene, has as its main objective correct systematic technical and/or experimental errors [6, 8].

For this essay, we choose to use RNU-48 as our reference gene for the data normalization. Widely used as normalization gene, RNU-48 is expected to have a stable pattern among samples. However, within our essay the opposite transpired. As showed in figure 2, RNU-48 was the one with a major standard deviation when compared with other 3 miRNAs analyzed which make it inappropriate as an endogenous control for our essay.

Seemingly, we were not the only ones that concluded this, Sapre and colleagues also assumed that RNI-48 was inadequate as an endogenous control due to its systematic perturbation in its expression [9].

Remarkably, the unexpected miR-222 profile remained barely unaffected and presented no significant difference between urine and blood. miRNA-222 behaviour within our samples was surprising once, it is being aimed for its deregulation by many other groups. Here, it does not present any variation within samples, any variation among both body fluids, it did even remained stable within different stages of age and do not alter with gender. This particular behaviour is expected of endogenous controls. Therefore, we decided to use miR-222 as our reference gene in order to normalise our data.

3.3 – miRNAs as biomarkers

Since 2009, miRNAs has been a target for forensic researcher, especially in forensic serology. The importance of both detection and identification for body fluids in criminal investigation is undeniable. Scientifically speaking, 5 years is such a short time to develop reliable new methodologies and, as already lay out by some authors, there is still so much to do.

Here, we choose 4 miRNAs and decided to study their expression level in urine and blood samples. As stated earlier, we choose miR-222 as our endogenous control for our data normalisation due to its behaviour within our samples. As showed in figure 4, we can state that all miRNAs considered have different expressional patterns and all of them probabilistically significant (P<0,05). In table 1, we assess the fold change within our body fluids and concluded that miR-221 is 4,86 times overexpressed in blood when compared to urine while miR-221 is a little bit more – 5,39 times.

RNU-48 is the one with a major difference between urine and blood. The one used numerous times as an endogenous control is upregulated about 141 times more in blood than in urine supporting our decision to not use it to normalize our data.

Till now, a minor number of miRNAs have been acknowledged as tissue specific – at least reliably. By definition, miRNAs are considered tissue specific when they’re found with high abundance in a specific tissue while it has low or non-existent expression in others. That differential profile patterns would allow body fluids reliable identification and serve as a significant confirmatory test. Considering our results, we can conclude that miR-127, miR-221 and RNU-48 are not suitable for neither blood nor urine identification. Despite a significant difference of expression, they do not present the expected expressional patterns to be considered as a good biomarker.

Table 1 – miRNA detection in both urine and blood samples and its corresponding fold change within the body fluids.

As we stated within our introduction, the miRNAs considered as biomarkers for body fluid identification in other reports have been difficult to replicate. We believe that those difficulties are linked to several factors as environmental factors, methodologies, age, gender, pathologies among several others. We know that miRNAs expression levels do alter with both biotic and abiotic factors, there is why we try to minimize the impact of those within our samples excluding, as example, acute pathological conditions. Despite considering that miR-127, miR-221 and RNU-48 are unsuitable for urine and blood identification, we wanted to study their expressional behavior within samples with different stages of age and gender. Figure 4A displays an overview of their relative quantification within female and male samples. Within blood, we did not notice any significant alteration in their expression (P>0,05). On the other hand, in urine, RNU-48 presented itself with a significant overexpression in females (P<0,05). Once again, this overexpression is another drawback to the use of RNU-48 as endogenous control.

When it comes to age, we divided our 50 samples in 3 categories: 20-40, 41-60 and over 60 years old. As it is shown in figure 4B, the relative quantification we achieved demonstrated no significant change in their expression profile (P>0,05).

4 – Conclusion and future perspectives

More than just a source of DNA, body fluids sole presence can have the most probative value. Hanson and colleagues introduced miRNA profiling as a reliable tool to identify body fluids such as blood, menstrual blood, semen, vaginal secretion and urine due to their tissue-specific pattern and stability when conditioned by degradation processes.

Here we focused our attention in four miRNAs: miR-127, miR-221, miR-222 and RNU-48. Soon enough miRNAs purity struck our attention when we notice that low value of 260/280nm ratio was associated with a poor degree of detection. When we upgraded our protocol the consequence reflected in a considerable decrease of the samples threshold.

It would be irrefutably helpful to understand what threshold could affect miRNA profiling once, as it was shown, miRNA purity do affect considerably their quantification. It could even convey wrong outcomes once even miRNAs with high concentration within body fluids can appear with low concentration or totally inexistent.

Our second result emphasised the importance of a normalisation gene. At first, we choose to use RNU-48 as our endogenous control but its behaviour within blood and urine make us reconsider our decision. RNU-48 is usually used as a reference gene due to its stable behaviour within samples however, our essay showed otherwise. Within the 4 miRNAs testes, RNU-48 was the one with a more pronounced variability within samples, which is opposed of what would be expected of a normalisation gene. Unexpectedly, miR-222 presented itself with the lowest standard deviation between blood and urine. Furthermore, we studied its expression levels and compared them within age and gender and concluded that no significant alteration was noticeable (P<0,05). That behaviour is by designation, the definition of normalisation genes. There is why we decided to switch our choice of normalisation genes and use miR-222 instead of RNU-48.

As stated earlier, normalisation genes are indispensable to validate qRT-PCR results however, till date, no normalisation gene is universally acknowledged. This problem is reflected in our case, where one of the most used normalisation gene proved to be unsuitable for urine and blood miRNA analysis. This subject is a very sensitive point in miRNA profiling. There is why it is imperative to focus our future line of work towards finding a reliable normalisation gene before anything else.

Our main goal was to define whether or not miR-127, miR-221 or RNU-48 could have the potential to be considered as biomarkers for body fluids identification. In this case, we could establish that all four have different expressional patterns in urine and blood (fig.5) however, to be considered as biomarker it would expected a major difference within body fluids which do not happen with our miRNAs considered for this essay. There is why we conclude that none of this miRNAs have the potential to be considered as a biomarker for body fluid identification.

Conflict of interest


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