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Summer Research Fellowship Programme of India's Science Academies

Epigenetic regulation of Histone H3 and its association with the Securin overexpression in raw Areca nut induced carcinogenesis in mammalian cells

Debarshee Sengupta

Department Of Biotechnology, Heritage Institute Of Technology, Chowbaga Road, Anandapur, Kolkata, West Bengal 700107

Prof. Anupam Chatterjee

Department Of Biotechnology & Bioinformatics, North-Eastern Hill University, Shillong, Meghalaya 793022

Abstract

Mammalian Securin which has been isolated initially from rat pituitary tumor cells as pituitary tumor transforming gene (PTTG1) is an oncogene and has been implicated in the development and progression of several malignancies. It encodes a protein which prevents separin from promoting sister chromatid separation during mitosis. Earlier higher expression of Securin, induction of precocious anaphase (premature separation of sister chromatids) and chromosomal instability have been observed to be significantly associated with an increased risk of raw areca nut (RAN) induced oral, oesophaegal and gastric cancers in both human and mouse. Thus it is been proposed that Securin level be considered as a molecular marker which can be a potential therapeutic target for many cancers. Since the mechanism of upregulation of Securin is still unclear, the present study is intended to look for epigenetic histone modifications pattern because such modifications do have profound effects on gene promoter activity. Likewise the effect of micro RNAs on epigenetics is an area that needs to be explored. Micro RNAs or miRNAs are small RNA molecules that are known to negatively control their target gene expression post transcriptionally and they've also been linked to cancer development. In our case as well, several miRNAs have been selected through in silico analysis (TargetScan, miRbase). The target for these miRNAs is 3' UTR of Securin primary transcript. Thus, it can be said that this investigation will play a pivotal role in understanding induction of carcinogenesis in mammalian cells.

Keywords: securin, raw areca nut, microRNA, epigenetic histone modifications

Abbreviations

Abbreviations
 UTR Untranslated Region
 PTTGPituitary Tumor Transforming Gene 
 miRNA/mirMicro RNA
 RAN Raw Areca Nut 
 hsa Human miRNA 

INTRODUCTION

Research over the years have shown enough evidence to implicate areca nut, as a potential carcinogen in humans. People in North-Eastern states of India consume raw areca nut (RAN) and lime which could lead to oral, oesophaegal and gastric cancers. (Singh V, et al, 2015) In Meghalaya, India, the variety of areca nut is used as raw and unprocessed form whose chemical composition and pharmacological actions have been reported. (Kurkalang S, et al, 2013) Yet very little is known about the areca nut induced carcinogenesis pathway. In our approach we're trying to device an epigenetic approach in relation with the use of selective micro RNAs. Micro RNAs are 22-25 nucleotide long non-coding RNA molecules which are encoded in the genome that can have a profound effect in controlling gene expression. More than 30% of human genes are believed to be targets of miRNAs, which signifies that miRNAs do have a comprehensive impact on transcriptomes and proteomes of eukaryotes . (Valinezhad Orang A, et al, 2014) They can bind to their target mRNAs and downregulate their stabilities. While binding to its target mRNA with full complementarity, this miRNA can lead to the degradation of the target. (Plotnikova O, et al, 2019) Micro RNAs can also bind to their targets with incomplete complementarity, often in the 3' UTR regions, and this leads to the translational suppression of their target genes by a mechanism that is yet to be completely understood. We know that each miRNA is predicted to have many targets and each mRNA may be regulated by more than one miRNA. Micro RNAs have recently been shown to be linked with cancer and they can act as tumor suppressor genes. One more important criteria for using miRNAs for our research is that they may also regulate chromatin structure by regulating key histone modifiers. So, it's clear that screening of target specific miRNAs is a necessity for this study.

Statement of the Problem

We need to find out the stable miRNA sequences that can attach to the 3' UTR of the primary Seurin transcript and degrade it.

Objectives of the Research

The current objective of my research is to look for the possible miRNAs via in silico analysis that can bind to the primary Securin transcript.

The binding sequences are to be identified and analysis of the data obtained is required.

Scope

In silico analysis of predicting binding regions or screening against a primary mRNA transcript is largely dependent on several bioinformatic tools and softwares. With time these tools have improved and have become accurate enough to be held accountable for solid research. The current research focuses on screening miRNAs and finding out their binding sequences and carry out an extensive understanding on the various parameters involoved.

LITERATURE REVIEW

Already available research in the present domain definitely throws some light on the work I've done. Securin was monitored since over-expression of this gene plays a role in carcinogenesis. Kurkalang S, et al, 2015 Histopathological preparation of stomach tissue of mice revealed that RAN + lime induced stomach cancer. There was a gradual increase in the occurence of precocious anaphases in both RAN + lime treated mouse as well as in human heavy chewers. Levels of Securin were increased in these cells during the early days of RAN + lime exposure. The levels of securin were significantly higher in the human tumor samples than their adjacent normal counterpart. Kurkalang S, et al, 2015 Thus it was proved that overexpression of Securin was associated with the increased consumption of RAN with lime and thus these parameters were considered of early diagnostic value going forward to my own research. So, since miRNAs have shown to have regulatory effect on transcription of genes, I'll be screening miRNAs keeping the Securin/PTTG1 gene as our target.

METHODOLOGY

Overview

For the process of screening of miRNA against the target securin transcript I've used a couple of open access webserver tools available in the public domain.

Firstly, I've used TargetScan, or rather TargetScanHuman 7.2 (Agarwal V, 2015 ) for finding out certain sequences of miRNA that appear to be best fit with our PTTG1 gene transcript in relation to context scores and overlaps. Then, the resulting miRNAs selected across several criterias which will be discussed later on, were then further analysed using miRbase. (Kozomara A, et al, 2019 ) Now since mammalian-specific miRNAs have far fewer conserved targets than do the more broadly conserved miRNAs (Friedman R.C, 2009 ), this tool (TargetScan) enables statistically powerful analysis of individual miRNA target sites, with the probability of preferentially conserved targeting (PCT) which is done correlating with experimental measurements of repression.

Seed Region Of MiRNA

Now in order to search for proper binding regions, we need to locate the seed region. The seed region or the seed sequence is nothing but the conserved sequence which is situated at positons 2-7 from the micro RNA's 5' end. The significance of the seed sequence lies in the fact that even though the base pairing of the mRNA and miRNA does not match exactly, the seed sequence has to be perfectly complementary. The eight base seed region mainly dominates this process. It is said that miRNAs with similar seed sequences, target similar sets of genes and consequently similar sets of pathways. There are four seed types: 8mer, 7mer-m8, 7mer-A1 and 6 mer. (Bartel, 2009) This is the most important component in identifying similar sets of micro RNAs, with increased efficiency.

Conserved And Poorly Conserved Domains

In general, the sites that match the miRNA seed, essentially which are in 3' UTRs are conserved. Targets are predcited easily by looking for the 6-8mer matches to the miRNA seed region. (Lewis GB et al., 2005) TargetScan predicts two types of 7mer sites in addition to 8mer sites.

Site types TargetScan.png
    Seed Regions 

    7mer-m8: This is an exact match to positions 2-8 of the mature miRNA (the seed + position 8)

    7mer-A1: This is an exact match to positions 2-7 of the mature miRNA (the seed) followed by an 'A'

    Now, there are several conserved and non-conserved miRNA families. So before going into the results part, we need to understand them. Broadly conserved signifies that it's conserved across most vertebrates (Supplemental table 1 of Friedman et al.), conserved means it's conserved across most mammals and poorly conserved covers the domain of other organisms. TargetScan defines site conservation by conserved branch length, with each site type having different threshold for conservation . (Friedman R.C, 2009).The different values are:

    8mer >= 0.8, 7mer-m8 >=1.3, 7mer-1A >=1.6

    Method

    First TargetScan webtool was opened and under species section, 'Human' is selected. Next, under the Human Gene Symbol section, our target gene PTTG1 was selected. Then I chose Broadly Conserved microRNA families from the drop down of step 3. This was the first step of the process, and subsequently the relevant results were obtained.

    Next, taking the results of our first step, we handpicked certain microRNAs based on their context scores and conserved branch lengths, which will be elaborated in the results section, and found out individual binding sequences, taking into account their probability of preferential conservation. These miRNAs were then subjected to sequencing using miRbase (Kozomara A, 2014), to find out other related properties.

    RESULTS AND DISCUSSION

    TargetScan analysis was done along with sequence identification with miRbase and miRDB.

    The conserved miRNA sites that were obtained from the first step of the process from TargetScan are:

    miRNA data
    miRNA Site TypePosition on PTTG1 3' UTRContext ++ Score Conserved Branch Length 
    hsa-mir-655-3p8mer 32-39 -0.722.667 
     hsa-mir-374c-5p8mer 32-39-0.71 2.667

    Because of similar scores and site of binding, I selected hsa-mir-655-3p which has a higher negative context++ score. Upon clicking on the view table of miRNAs link on the left corner of the results page, we get the miRNA families conserved only among mammals sorted based on their cumulative weightage score:

    miRNA families conserved among mammals
    miRNA family Conserved Sites  Poorly Conserved Sites Position on PTTG1 3' UTRConserved Branch Length Cumulative weighted context++ score 
    mir-655-3p 8mer  -32-39  2.667 -0.72
    mir-186-5p  -  8mer46-53  0.364 -0.59
    mir-329-3p/362-3p -7mer-A1  23-29 0.847 -0.33 

    Now, context score is a sequence based score for individual target sites that is calculated by TargetScan. (Grimson A et al., 2007) Targets with lowest context plus scores are generally considered to be the most representative ones. (Garcia DM et al., 2011) It is been used for the analysis of preferentially conserved miRNA-pairing motifs within 3' UTRs.

    Again, TargetScan conserved branch length score is that it represents the sum of phylogenetic branch length between species that contains a site. (Friedman R.C, 2009) This will be elaborated more later on.

    Now, for our Human PTTG1 gene (ENST00000352433.5), it has a 3' UTR length of 63 as predicted by TargetScan:

    All miRNAs image.jpg
      miRNA families conserved among mammals

      As we can see that miR-655-3p binds to the positions 32-39 of the PTTG1 3' UTR, while miR-186-5p binds to the sequences 46-53 and finally miR-329-3p/362-3p binds to the 23-29 sequences of the PTTG1 3' UTR.

      seed key.png
        Seed type key

        Each colour code for the miRNAs represent their seed type, as already mentioned in the earlier table. What TargetScan or such similar tools do is, they calculate probabilities. There is always a range of probabilities for even something like miRNA target prediction. The true value lies in the range between higher and lower probabilities for the same set of colour markers.

        mir-655-3p.PNG
          miR-655-3p
          Capture of miR-186-5p.PNG
            miR-186-5p
            329-3p 362-3p.PNG
              miR-329-3p/362-3p

              As we can see that miR-655-3p is highly conserved across most species, i.e the sequence is the same throughout, till Opossum, while the other two are poorly conserved, conserved only till Chimp. This justifies the fact why miR-655-3p has a conserved branch length score as high as 2.667.

              These miRNA sequences are then extracted via the miRbase link available also on the TargetScan result page. The sequences as provided by miRbase and verified by TargetScan are as follows:

              1. hsa-mir-655-3p (MIMAT0003331): 5' AUAAUACAUGGUUAACCUCUUU 3'

              Binding sequence 655-3p refined 2.png
                Binding Sequence of mir-655-3p to PTTG1 3' UTR

                2. hsa-mir-186-5p (MIMA0000456): 5' CAAAGAAUUCUCCUUUUGGGCU 3'

                Binding sequence 186-5p.PNG
                  Binding Sequence of mir-186-5p to PTTG1 3' UTR

                  3. hsa-mir-329-3p (MIMAT0001629): 5' AACACACCUGGUUAACCUCUUU 3'

                  Binding 329 3p 362 3p.PNG
                    Binding Sequence of mir-329-3p/362-3p to PTTG1 3' UTR

                    CONCLUSION AND RECOMMENDATIONS

                    Conclusion

                    Few things that have unraveled through this endeavour are that the above three micro RNAs (hsa-mir-655-3p, hsa-mir-186-5p and hsa-mir-329-3p), obtained by in-silico analysis can be designed and tested in wet lab to actually analyse their ability to post-transcriptionally regulate the Securin mRNA transcript and actually degrade it. Among them, hsa-miR-655-3p, as found to be highly conserved can also prove fruitful in mouse model testing as well. This can serve as a novel method of understanding the process of induction of carcinogenesis in mammalian cells due to Securin overexpression.

                    REFERENCES

                    Kurkalang S, Banerjee A, Ghosal N, Dkhar H, and Chatterjee A. Induction of chromosome instability and stomach cancer by altering the expression pattern of mitotic expression genes in mice exposed to areca-nut. BMC Cancer. 13:315-321. 2013

                    Kurkalang S, Banerjee A, Dkhar H, Nongrum HB, Ganguly B, Islam M, Rangad GM and Chatterjee A. Precocious anaphase and expression of securine and p53 genes as candidate biomarkers for the early detection in areca nut induced carcinogenesis. Mutagenesis. 30:381-389. 2015.

                    Singh V, Singh L C, Singh AP, Sharma J, Borthakur BB, Debnath A et al. Status of epigenetic chromatin modification enzymes and esophageal squamous cell carcinoma risk in northeasten Indian population. Am J Cancer Res. 5:979-99. 2015.

                    Valinezhad Orang A, Safaralizadeh R and Kazemzadeh-Bavili M. (2014). Mechanisms of miRNA-mediated gene regulation from common downregulation to mRNA-specific upregulation. International Journal Of Genomics, 2014, 1-15. doi: 10.1155/2014/970607

                    Plotnikova O, Baranova A and Skoblov M (2019). Comprehensive analysis of human microRNA-mRNA interactome. Front. Genet. 10:933. doi: 10.3389/fgene.2019.00933

                    Agarwal V, Bell G.W, Nam J-W and Bartel D.P. (2015). Predicting effective microRNA target sites in mammalian mRNAs. eLife, 4. doi: 10.7554/elife.05005

                    Friedman R.C, Farh K.K, Burge C.B, Bartel D.P. Most mammalian mRNAs are conserved targets of microRNAs. Genome Research, 19:92-105 (2009). doi: 10.1101/gr.082701.108

                    Kozomara A, Birgaoanu M, Griffiths-Jones S. miRbase: from microRNA sequences to function. Nucleic Acids Res 2019 47:D155-D162. doi: 10.1093/nar/gky1141

                    Kozomara A, Griffiths-Jones S. miRbase: annotating high confidence microRNAs using deep sequencing data. Nucleic Acids Res 2014 42:D68-D73. doi: 10.1093/nar/gkt1181

                    Grimson A, Farh KK, Johnston WK, Garrette-Engele P, Lim LP, Bartel DP. MicroRNA Targeting specificity in mammals: Determinants beyond Seed Pairing. Molecular Cell, 27:91-105(2007).

                    Garcia DM, Baek D, Shin C, Bell GW, Grimson A, Bartel DP. Weak Seed-Pairing Stability And High Target-Site Abundance Decrease the Proficiency of Isy-6, and Other miRNAs. Nat Struct Mol Biol., 18:1139-1146 (2011).

                    Lewis BP, Burge CB, Bartel DP. Conserved seed pairing, often flanked by adenosines, indicates that thousands of human genes are microRNA targets. Cell. 2005 Jan 14; 120(1):15-20.

                    David P. Bartel, MicroRNAs: Target Recognition and Regulatory Functions, Cell, Volume 136, Issue 2, 2009, Pages 215-233.

                    ACKNOWLEDGEMENTS

                    I express my sincere gratitude to my guide, Prof. Anupam Chatterjee, Department Of Biotechnology and Bioinformatics, North-Eastern Hill University Shillong, for giving me the opportunity to explore various dimensions of the topic, despite certain limitations we faced in conducting this fellowship online. I would also like to thank Prof. Dipankar Chaudhuri, Department Of Biotechnology, Heritage Institute Of Technology Kolkata, for his valuable technical inputs throughout the course of this fellowship.

                    Lastly, I'm grateful to the Indian Academy Of Sciences for offering me this fellowship. It has been a great learning experience for me, something that'll contribute immensely to my own knowledge and understanding.

                    References

                    • Singh V, Singh L C, Singh AP, Sharma J, Borthakur BB, Debnath A et al. Status of epigenetic chromatin modification enzymes and esophageal squamous cell carcinoma risk in northeasten Indian population. Am J Cancer Res. 5:979-99. 2015.

                    • Kurkalang S, Banerjee A, Ghosal N, Dkhar H, and Chatterjee A. Induction of chromosome instability and stomach cancer by altering the expression pattern of mitotic expression genes in mice exposed to areca-nut. BMC Cancer. 13:315-321. 2013

                    • Valinezhad Orang A, Safaralizadeh R and Kazemzadeh-Bavili M. (2014). Mechanisms of miRNA-mediated gene regulation from common downregulation to mRNA-specific upregulation. International Journal Of Genomics, 2014, 1-15. doi: 10.1155/2014/970607

                    • Plotnikova O, Baranova A and Skoblov M (2019). Comprehensive analysis of human microRNA-mRNA interactome. Front. Genet. 10:933. doi: 10.3389/fgene.2019.00933

                    • Kurkalang S, Banerjee A, Dkhar H, Nongrum HB, Ganguly B, Islam M, Rangad GM and Chatterjee A. Precocious anaphase and expression of securine and p53 genes as candidate biomarkers for the early detection in areca nut induced carcinogenesis. Mutagenesis. 30:381-389. 2015.

                    • Agarwal V, Bell G.W, Nam J-W and Bartel D.P. (2015). Predicting effective microRNA target sites in mammalian mRNAs. eLife, 4. doi: 10.7554/elife.05005

                    • Kozomara A, Birgaoanu M, Griffiths-Jones S. miRbase: from microRNA sequences to function. Nucleic Acids Res 2019 47:D155-D162. doi: 10.1093/nar/gky1141

                    • Friedman R.C, Farh K.K, Burge C.B, Bartel D.P. Most mammalian mRNAs are conserved targets of microRNAs. Genome Research, 19:92-105 (2009). doi: 10.1101/gr.082701.108

                    • Kozomara A, Griffiths-Jones S. miRbase: annotating high confidence microRNAs using deep sequencing data. Nucleic Acids Res 2014 42:D68-D73. doi: 10.1093/nar/gkt1181

                    Source

                    • Fig 1: TargetScan
                    • Table 1: TargetScanHuman 7.2
                    • Table 2: TargetScanHuman 7.2
                    • Fig 2: TargetScanHuman 7.2 predicted targeting of Human PTTG1
                    • Fig 3: TargetScanHuman 7.2 predicted targeting of Human PTTG1
                    • Fig 4: TargetScanHuman 7.2 predicted targeting of Human PTTG1
                    • Fig 5: TargetScanHuman 7.2 predicted targeting of Human PTTG1
                    • Fig 6: TargetScanHuman 7.2 predicted targeting of Human PTTG1
                    • Fig 7: TargetScanHuman 7.2 predicted targeting of Human PTTG1
                    • Fig 8: TargetScanHuman 7.2 predicted targeting of Human PTTG1
                    • Fig 9: TargetScanHuman 7.2 predicted targeting of Human PTTG1
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