CALIFORNIA STATE UNIVERSITY, NORTHRIDGE
The Evolutionarily Conserved Transcription Factor AP-1
is Essential for Transcriptional Regulation of
Small Lymphocytic Lymphoma Associated miR-155HG and miR-155GG
A thesis submitted in partial fulfillment of the requirements
For the degree of
Master of Science in Biology
By
Alina Adamian
August 2017 The thesis of Alina Adamian is approved by:
______Dr. Rheem D. Medh Date
______Dr. Virginia Vandergon Date
______Dr. Chhandak Basu Date
______Dr. Cindy S. Malone, Chair Date
California State University, Northridge
ii Acknowledgements
I would like to thank my family, friends, labmates, CSUN faculty and staff, and most especially, Jesus, my Lord and Savior, for walking with me every step of the way.
To my father, thank you for your unconditional love, unwavering support, and for raising me to be a strong independent woman who knows how to hustle.
To my mother, thank you for your sacrifices, your love, and for showing me how strong a woman can be all on her own.
To my sister, Dr. Annie Adamian, who I am so proud of, thank you for setting the bar high and for your never-ending support and encouragement!
To my mentor, best friend, professor, PI, and God sent angel, thank you for your mentorship, guidance, friendship, unconditional unwavering constant love and support, and for being the ultimate Wonder Woman who is the most caring, giving, generous woman I have ever met. Thank you for molding me into the female scientist and human being I am today. You are extraordinary!
To my best friends, Coco Chanel my sister in Christ and my darling Ely Andrea, I love you. Thank you for being the amazingly strong and smart ladies that you are and for taking this journey through academia, science and life with me. I am truly blessed to have you both in my life and I am so proud of you!
To Dr. Virginia Vandergon, thank you for the amazing conversations and life talks. Your mentorship has meant a great deal to me.
To Dr. Rheem Medh, thank you for your constant support all these years and for your loving nurturing hugs.
iii To Dr. Chhandak Basu, thank you for all the laughs teaching Recombinant DNA
Techniques together and for all your support and advice over the years. I truly appreciate you.
To my ladies of the Biology Department, Linda jan Gharakhanian, Cherie
Hawthorne, Vickie Everhart, Sarah Cohen, my laughing partner Priscilla Samaniego and my Terrie, Dr. Terri Richardson, thank you for making CSUN home.
Special thanks to:
Dr. Cindy Malone Cathy Soliva
Dr. Chhandak Basu Eric Allen
Dr. Virginia Vandergon Eliana Ochoa Bolton
Dr. Rheem Medh Lawrence Shaktah
Dr. Jessica Igoe Stephanie Kennedy
Dr. Terri Richardson Samantha Hain
Dr. Larry Allen David Kang
Priscilla Samaniego Brenda Velasco
Jacqueline Saunders Nikki Jamie Cruz
Grant Lee Weiss Lesslie Jocol
Loni Hands Gavin Long
Lynnea Waters
iv Table of Contents
Signature Page ii
Acknowledgments iii
List of Figures vi
Abstract vii
Chapter 1: Introduction 1
Chapter 2: Material and Methods 12
Chapter 3: Results Part 1 27
Chapter 4: Results Part 2 47
Chapter 5: Discussion 57
References 72
v
Figures
Figure 1: Biogenesis of microRNAs 2
Figure 2: Promoter region of miR-155HG with predicted TF binding sites 28
Figure 3: The -178/+129 promoter construct defines proximal promoter region 30
Figure 4: MEGA MSA line-up of miR-155 conserved TF binding site AP1 TF 33
Figure 5: miR-155 Promoter region AIC Model Phylogeny Tree: 35
Figure 6: The -117/+129 promoter construct shows optimal expression 37
Figure 7: miR-155- AP1mut construct harbors the AP1 binding 38
Figure 8: Promoter region of Chicken miR-155GG with AP1 TF Binding site 40
Figure 9: Expression of miR-155HG and miR-155GG in HEK cells 42
Figure 10: Expression of miR-155HG and miR-155GG in DF-1 cells 44
Figure 11: miR-155HG and miR-155GG AP1mut constructs exhibit 46 decrease in expression
Figure 12: Molecular Evolutionary Genetics Analysis: 49
Figure 13: AIC Best model fit parameters Tamura 3-parameter model. 50
Figure 14: Best model fit parameters Tamura 3-parameter model. 52
Figure 15: Best model fit parameters Tamura 3-parameter model. 54
Figure 16: Best model fit parameters Tamura 3-parameter model. 56
vi Abstract
The Evolutionarily Conserved Transcription Factor AP-1
is Essential for Transcriptional Regulation of
Small Lymphocytic Lymphoma Associated miR-155HG and miR-155GG
By
Alina Adamian
Master of Science in Biology
MicroRNAs (miRs) are small, non-coding RNAs that regulate gene expression post-transcriptionally through mRNA degradation. MiRs are categorized as either oncomiRs, a microRNA associated with cancer, as functional tumor suppressors, or as both as in the case of miR-155. MiR-155 is encoded by the gene miR-155HG on chromosome 21 and lack of expression has been associated with Mantle Cell Lymphoma
(MCL). In addition, miR-155 was found expressed in Small Lymphocytic Lymphoma
(SLL), liposarcoma and breast cancer. MiR-155 has been found to be normally expressed in B-cells. We previously found miR-155HG associated with expression in indolent SLL but not aggressive MCL. MiR-155 promotes apoptosis by targeting anti-apoptotic mRNA as well as BCL2, which is involved in regulation of the apoptosis pathway, suggesting that perhaps low or dysregulated miR-155 expression in MCL contributes to the aggressive nature of this lymphoma.
vii Here we have identified and characterized the proximal and core promoter regions of miR-155HG. Transient transfection analyses suggested the proximal promoter is located within the -117 base pairs from the TSS (Transcriptional Start Site). Several regulatory elements were predicted via transcription factor site databases within this region. One of these, AP1, is highly conserved throughout evolution. Mutagenesis analysis showed high transcriptional activity within the -117 bp region where the AP-1
TF binding site was predicted to be located at -38 bp from the TSS. Bioinformatics data suggested the AP-1 TF binding site was conserved through evolution in 11 species including 100% identity in the chicken (Gallus gallus miR-155GG). The AP-1 binding site sequence, TGA G/C TACAA, is located -40 bp from the TSS in G. gallus. Transient transfections showed equivalent transcriptional activity between miR-155HG and miR-
155GG in this region. Mutagenesis of the AP1- site in both human miR-155HG and chicken miR-155GG showed decreased levels of expression, further suggesting that AP-1 is an essential TF driving transcription of these genes. MSA alignment revealed that the
AP1 TF binding site is not conserved in Mus musculus, and as such, NIH 3T3 cells were also transfected for analysis of expression of miR-155 construct in these cells.
viii Chapter 1
Introduction
MicroRNAs (miRs) are a class of evolutionarily conserved short RNA segments that participate in the post-transcriptional regulation of gene expression by binding to the
3’ un-translated region (UTR) of target mRNAs found in the cytoplasm, resulting in degradation and translational inhibition (Basir & Khosrow, 2013). Once a gene is transcribed into an mRNA, it goes through post-transcriptional modifications, which are key factors in gene regulation, and thus, gene expression. Post-transcriptional modifications occur in between the time a gene is transcribed into an mRNA and before it is translated into a protein. These processes include 5’ capping, 3’ processing and RNA splicing. To the 5’ end of the mRNA, also called the 5’ un-translated region (UTR), 7- methylguanosine molecules are added which protect the 5’ end from being degraded by ribonucleases. The 5’ cap region has important functionality in that it not only contains binding regions for specific splicing proteins required for splicing out introns post- transcriptionally, but it also has binding sites for proteins involved in translation initiation, namely ribosomal units. Processing of the 3’ UTR involves the addition of
Adenosine purine nucleosides, creating a poly-A tail that serves as a binding site for poly-A binding proteins, providing stability and inhibiting decay of RNA molecules. The
3’ UTR contains regulatory regions, including silencer-binding regions for repressors to bind and regulate translation (Barrett, Fletcher, & Wilton, 2012), as well as regions for miRs to bind, and cause degradation. MiRs regulate gene expression by base pairing to the 3’ UTR of their target mRNAs, often causing de-adenylation of the poly (A) tail,
1 resulting in mRNA degradation and blocking of translation (Dalmay 2013). In this way, miRs regulate gene expression by blocking the translation of mRNA to protein.
The Biogenesis of MicroRNAs
Drosha, Dicer and the RISC complex
A host of proteins, enzymes and regulation are required to produce RNA molecules. For miRs, the mechanism and machinery include RNA Polymerase II, Drosha and its protein partner DiGeorge syndrome critical region gene 8 (DGCR8), Exportin-5, Dicer, the
RNA-induced silencing complex (RISC) and the Argonaute protein Ago2 (Gregory,
Jung, Diederichs, Keller, & Winter, 2009).
Figure 1: The Biogenesis of MicroRNAs: RNA Polymerase II is recruited by TFs to the coding region of gene to initiate transcription. DROSHA produces a dsRNA stem-loop that is then exported out of the nucleus by Exportin-5. DICER chops up stem-loop into duplex fragments that then bind to RISC complex and target mRNAs for degradation. Modified image (Joshi et al., 2011).
2 Transcribed in the nucleus by RNA polymerase II, primary miR (pri-miRs) transcripts of single-stranded RNA (ssRNA) are made several hundred bases in length and complimentarily fold onto themselves to form a double stranded molecule (dsRNA). This pri-miR is now a dsRNA with a hairpin loop connecting the strands (Ambros & Lee,
2001). Once pri-miR transcripts, approximately 70 base pairs in length (Förstemann et al., 2005) are produced, their stem-loops are recognized by the Drosha- DGCR8 complex which now cleaves off approximately 50 base pairs, leaving a shorter, approximately 20 bp dsRNA stem-loop, now called a pre-miR (Kim 2010).) These stem-loops are then exported by transport protein Exportin-5 to the cytoplasm where they will come in contact with Dicer (Figure 1). Dicer is a protein complex made up of helicase and RNase endonuclease III domains which work to cut dsRNA into smaller pieces, approximately
22 base pairs long (Zhang et al., 2004). Dicer recognizes the stem-loop of the miR and binds for cleavage of the loop leaving a RNA duplex that now disassociates, leaving two strands, referred to as miR-5p and miR-3p for 5’ and 3’. With the help of Dicer, the miR-
5p strand, for reasons not yet discovered, is the one that usually, but not always, binds to the RNA Induced Silencing Complex (RISC), and the miR-3p is degraded (Ambros et al.,
2003).
The RISC (RNA-Induced Silencing Complex):
The RISC complex is a multi-protein complex made of ribonucleic proteins that facilitate gene silencing, also referred to as RNA-interference, and this is where yet another protein, the Argonaute protein Ago2, comes into play. Binding of the miR-5p to the RISC complex creates a microRNA–directed RNA-induced silencing complex (miRNA–RISC) guided by the Ago2 protein. Ago2 binds with miR-5p which guides the RISC complex
3 along with Ago2 to their target mRNA where the miR-5p will complimentary base pair with the 3’ UTR (Kangsheng et al., 2017), as Ago2 cleaves the target mRNA resulting in inhibition of translation (Cai et al., 2012). MiRs bind to their target’s 3’ UTR via perfect and imperfect base pairing, resulting in one miR being able to target hundreds of target mRNAs (Papachristou et al., 2012), suggesting the high impact miRs can have on gene regulation and gene expression. The miR that is the focus of our study, miR-155HG, was found to have 388 mammalian targets (www.TargetScan.com).
Gene regulation:
The focus of our study is the transcriptional regulation of miR-155HG, that has been shown to target the 3’ UTR of important transcription factors as well as proteins involved in the regulation of apoptosis, programmed cell death. Gene regulation usually begins with transcription of a gene to produce an mRNA, which will then go on to produce a protein. Gene regulation requires several levels of control including chromatin structure, transcription, mRNA post-transcriptional modifications, translation, and post- translational modifications. Chromatin structure is one way a cell can control regulation of transcription even before it begins. Chromatin structure is essential in gene expression since exposure of DNA to RNA polymerase is needed for transcription of genomic regions. DNA in the nucleus is not bare, it is associated with histone proteins that form into chromatin, which represses transcription in nucleosome condensed regions by inhibiting exposure of certain regions of DNA to RNA Polymerase II. Regulation at the translational and post-translational level involve protein synthesis and modifications of proteins, respectfully. Activation and deactivation of proteins is another way that translation is regulated, mainly via phosphorylation of initiation factors. Following
4 translation, post-translational modifications such as cleavage of sites to activate a protein or give it catalytic activity to become an enzyme can occur (Di Paola et al, 2010). All of these levels of regulation are of importance and many more exist in maintaining proper cell function, including our mechanism of interest, transcriptional regulation, in particular the transcriptional regulation of miR-155HG and the post-transcriptional regulation it poses on target mRNAs.
Transcription of a gene involves an essential region of DNA, the promoter region that has unique characteristics and functions. Every eukaryotic gene has its own promoter and they play a vital role in gene regulation and maintaining homeostasis in mammalian cells by regulating transcription (Rutherford, J.C., Bird & A.J., 2004). These regions include a core promoter that has binding sites for the TATA-binding protein, basal regulatory elements, and RNA Polymerase (Cooper, 2000), as well as a proximal promoter that is located upstream of the core promoter and has its own important regions of DNA for binding of specific Transcription Factors. Within the core promoter are the binding site for RNA Polymerase and in some cases a TATA box. The core promoter is the portion of the promoter required to properly initiate transcription. Transcription begins with the recruitment of basal transcription factors (TFs) to cis-acting elements within the core promoter region, which will then recruit RNA polymerase to produce the start site of transcription (TSS). Initiation of transcription involves Transcription Factor
IID (TFIID) binding to the core promoter. TFIID, a multi-protein complex, which is encoded by the TAF13 gene in humans, is made up of the TBP (TATA-Binding Protein) as well as several TAFs (TATA-Binding Associated Factors). The binding of the TFIID complex initiates transcription. It is important to note here that RNA polymerase is not
5 the protein that drives transcription initiation, but the basal TFs that recruit RNA pol II are the responsible molecules. Promoters, as well as the TFs that bind to them, are what have shaped the evolution of gene expression and conservation of TF binding sites through evolution is a great indication of the importance of these regions of DNA
(Maston, Evans & Green, 2006).
Transcription Factors:
With approximately 1,500 TFs in every cell (Gusmão., Dieterich & Costa, 2012) and an estimated 20,000 genes in the human genome, the complexity of the components needed in various steps of transcriptional regulation is complex, necessary, and conserved through evolution (Maston, 2006). TFs are regulatory elements that have DNA-binding- domains, and they recognize specific DNA sequences. TFs initially interact with the
DNA backbone, and search the strand of DNA until they recognize a specific DNA sequencer site, usually within the first 300 base pairs upstream of the core promoter from the TSS (Buttice, Quinones, & Kurkinen, 1991). Once the TF binds to this region, a conformational change takes place - change in the tertiary structure of the protein, which will now allow it to interact with nucleotides in the backbone of the double stranded
DNA. TFs have affinity to bind to a region based on specific base and shape readouts.
Base readouts refer to recognition by TFs of bidenate hydrogen bonds within the major groove, and shape read outs refer to recognition by TFs of charges in the minor groove of the DNA helix. The bidenate hydrogen bonds in the major groove and the shape readouts in the minor groove are determined by DNA sequences in that region. These bonds and electrical charges are what entice a particular TF to its binding domain. The multiple TFs that are usually interacting with the proximal promoter are now part of the transcription
6 complex, and will interact with each other to affect RNA polymerase’s ability to transcribe the gene. These proximal promoter bound TFs now determine the level of transcription (Chi, Woo, Reinke & Valerie, 2006). As such, analysis of the promoter region of miR-155 and determination of what regions of DNA as well as what TFs are driving transcription of this gene were crucial in determining the transcriptional regulation components of miR-155.
SLL and MCL
Mantle Cell Lymphoma
Mantle cell lymphoma is a rare, B-cell non-Hodgkin’s lymphoma (NHL) which accounts for approximately 5% of all NHLs and usually affects the elderly. It is so named due to the fact that the tumor cells associated with it originally come from the mantle zone, a node located in the lymph (Cortelazzo et al., 2012). MCL is an aggressive type of cancer with patients generally not surviving past 7-8 years. MCL is usually diagnosed at a later stage when it has already spread to the bone marrow (Clement, Parker, & Salama,
2015).
Small Lymphocytic Lymphoma
Small lymphocytic lymphoma affects B cells, particularly B-lymphocytes, as does
Chronic Lymphocytic Leukemia (CLL). CLL and SLL are cancers that affect the same lymphocytes and are essentially the same disease, the only difference being where the cancer primarily occurs. When most of the cancer cells are located in the bloodstream and in the bone marrow, the disease is referred to as CLL, although the lymph nodes and spleen are often involved. When the cancer cells are located mostly in the lymph nodes, the disease is called SLL. Both types of cancers are important for study since studies have
7 shown that patients with either SLL or CLL can develop Richter’s syndrome, which is a
Non-Hodgkins Lymphoma triggered by Epstein-Barr viral infections (Tsimberidou et al.,
2009). In comparison to MCL, SLL is a more indolent, slow growing cancer, and patients diagnosed with SLL or CLL can live decades before even starting treatment. MiR-155 was found to be expressed in indolent SLL and not in aggressive MCL (Henson,
Morford, Stein, Wall, & Malone, (2011).
Purpose of project
This project aims to determine what TFs are driving transcription and therefore regulating expression of miR-155. This project involves isolating and characterizing miR-155’s core and proximal promoter region in an effort to identify TFs affecting transcription of this gene. In addition, we aim to show the evolutionary conservation of said promoter region, TF binding sites, and the product of miR-155 across species.
MiR-155HG:
MiR-155HG, an oncomiR located on chromosome 21 in humans, encodes for the stem- loop product miR-155, has an important role in the regulation of apoptosis, and has been closely associated with B cell lymphomas including, SLL/Chronic Lymphocytic
Leukemia (CLL), and Diffuse Large B Cell Lymphoma (DLBCL) (Henson et al.,
Musilova & Mraz, 2015). MiR-155 is present in normal B cells and has been shown to effect B-cell regulation by targeting the 3’ UTR of B-Cell lymphoma 2 (BCL2) and B-
Cell Lymphoma 6 (BCL6) (Musilova et al, 2015).
MIR-155 and apoptosis: MiR-155 has been found to play a key role in apoptosis, programmed cell death where loss of cell cycle regulation, DNA damage, or stresses and
8 signals from other cells induce the apoptotic pathway towards cell death (Alberts et al.,
2008). The regulation of apoptosis is an important aspect of normal cellular function, mostly regulated by the p53 protein family that includes p63 and p73. This family of proteins regulates apoptosis via induction of the Caspase-9 pathway that involves the activation of several enzymes and a DNA cleavage cascade leading to apoptosis. The p53 protein is a TF that acts as a tumor suppressor, yet, as with all genes, dysregulation can happen. In a study by Neilsen et al., mutant p53 protein was shown to up-regulate expression levels of miR-155, and both mutant p53 as well as wild-type p63 proteins were shown to regulate the transcription of the miR-155 gene miR-155HG, suggesting miR-155 plays an important role in the proper regulation of apoptosis and that dysregulation of this pathway, and miR-155, may lead to tumorogenesis.
MiR-155 and lymphomas: In a previous study by Henson et al., candidate genes were isolated based on differences in expression in MCL and SLL, and miR-155HG was found to be expressed in SLL, an indolent, slow growing lymphoma, and not expressed in aggressive MCL. Interestingly, miR-155 has been shown to be over-expressed in Diffuse
Large B-Cell Lymphoma (DLBCL), an aggressive cancer with a 40% fatality rate (Due et al., 2016), suggesting any dysregulation of miR-155 can contribute to tumorogenesis and that miR-155 is vital in keeping the balance between apoptosis and cellular proliferation.
3’ UTR Targets BLC2 and BLC6: MiR-155 plays an important role in B-cell lymphoma regulation by targeting the 3’ UTR of BCL2 B-Cell lymphoma 2 (BCL2 ) and
B-Cell Lymphoma 6 (BCL6). MiR-155 affects apoptosis by targeting the 3’ UTR of mRNA BCL2, which is involved in regulation of the apoptosis pathway (Higgs & Slack,
9 2013). The BCL-2 family of proteins help regulate the apoptosis pathway by keeping a balance between anti-apoptotic and pro-apoptotic function. BCL-2 protein family members include the BLC-2 protein along with pro and anti apoptotic activators.
Regulation involves the BLC-2 protein binding to an activator or effector protein, to either prevent or activate proteins needed in the apoptosis pathway (Strasser, Cory &
Adams, 2011). MiR-155 targets the 3’ UTR of BCL-2 that has been shown to be highly expressed in tumors. A study by Wacheck et al. showed that down-regulation of BCL2 resulted in a decrease in tumor growth, suggesting that dysregulation of miR-155 can contribute to over-expression of BCL2, inhibiting the Caspase driven apoptotic pathway and increasing tumor growth. As such, BLC2 is being used currently as a bio-marker for malignancies, since high expression of BLC2 is highly associated with tumors (Zhang et al., 2010).
BCL6: Another target of miR-155 is the 3’ UTR of BCL6, an evolutionarily conserved zinc-finger TF that moderates B cell responses to immune system molecules Interleukin-
4 (IL-4) and Interleukin-6 (IL-6). Interleukins are cytokines, messenger molecules, released by T cells of our immune system in response to various cellular needs. IL-4 is important in that is plays a vital role in T-helper 2 cell differentiation. IL-4 has been shown to regulate apoptosis by inhibiting the induction of the Caspase-3 apoptotic pathway (Lee, Kühn, Hennig, & Toborek, 2000). IL-6 cytokines are in response to inflammation, infection or foreign intruders. TF BCL6 moderates B cell immune response by regulating transcription of target genes via recruiting SMRT/histone deacetylase complex to sequence specific regions of target genes in order to inhibit transcription (Masafumi, Fukuda, Takeshi, Tokuhisa, & Takeshi, 2008). BCL6 has been
10 shown to bind to target genes involved in cytokines, chemical messengers such as IL-4 and IL-6 that trigger our immune system, as well as genes involved in cell cycle regulation and the apoptosis pathway (Masafumi et al., 2008). Chromosomal translocations that result in dysregulation of BCL6 expression are found in 40% of
DLBCL cases (Cattoretti et al., 2005). Interestingly, a study in 2000 by Capello et al. found that patients with CLL had mutations in the BCL6 gene.
Beneficial properties and Biomarkers: MiRs have been studied for their beneficial regulatory properties such as their behavior as tumor suppressors as well as their detrimental roles as oncogenes, with dysregulation in miRs observed in a variety of cancers and malignancies (Mestrovic, 2015). These characteristic properties have been proposed as good biomarkers for diagnosis of several types of cancers, with miR-155 being recognized as a prominent miR to be used as a bio-marker in several of the lymphomas aforementioned. MiRs are used as biomarkers since certain miRs have been shown to have altered profiles in the plasma of patients with cancer (Kim 2015). It is vital to study the promoter region of miR155 to determine what drives its transcriptional expression. We hypothesize that the promoter region would be found just upstream of the coding region of miRNA-155 and that TFs responsible for driving transcription of this gene would be identified within said region and control expression of this gene.
11 Chapter 2
Material and Methods
Boil Prep method:
Isolated colonies were picked from Luria Broth (LB) petri dishes with antibiotic ampicillin (AMP) and grown in 4 mL of LB/AMP broth overnight for 12-15 hours at 37 degrees. 1.5 mL of turbid culture were pipetted into 1.5mL Eppendorf micro- centrifuge tubes and centrifuged at 12,000 rpm for 2 minutes to obtain a pellet. The supernatant was discarded into a container of 10% bleach and 90% water, and a second aliquot of 1.5 mL of turbid culture was pipetted into the same Eppendorf tube, and again centrifuged to obtain a pellet. Supernatant was once again discarded. Using the boil buffer-lysozyme reagent made previously, 350 ul of boil buffer and lysozyme mixture was added to the sample to resuspend the pellet. Using the “racking” effect (dragging
Eppendorf tube with sample across a tube rack holder one dozen times) pellet was resuspend in the boil buffer-lysozyme solution and samples were vortexed for 30 seconds. The samples were then put into a boiling 100 C water bath for exactly 45 seconds. Samples were then centrifuged for 5 minutes at 12,000 rpm. Using a P20 pipetter cellular debris from lysed E. coli was removed from the microcentrifuge tube carefully. 40 uL of 3M NaOAC were pipetted into sample and vortexed for 10 seconds.
Then, 425 ul of 2-isopropanol was pipetted into the sample and vortexed for 10 seconds and centrifuged for 5 minutes at 12,000 rpm. Supernatant was discarded and the
Eppendorf tube was set upright on a sterile napkin and left to dry for 5-10 minutes. At the end of 10 minutes, 100 mL of dH20 was added to the tube by pipetting it carefully along the side of the tube in order to catch any DNA on the sides of the tube.
12 Cloning: miR-155HG:
Vector: pGL3 Basic vector was digested with Fermentas BglII enzyme, for 2 hours in 37
°C and heat killed for 10 minutes in an 80 °C water bath, and then phosphates groups were removed from 5’ end using Calf Intestinal Phosphatase (CIP) in preparation for blunt end ligation (see restriction digest, CIP and ligation protocols below for details). pGL3 Basic vector was also digested with Bgl II enzyme and CIPed.
DNA Insert: miR-155-Pro insert was ligated into pGL3 Basic via blunt end cloning.
MiR-155GG: pGL3 Basic reporter vector was prepped for ligation: Vector was digested with BamHI and HindIII enzymes. Vector was then CIPed in preparation for ligation (see restriction digest, CIP and ligation protocols below for details).
DNA Insert: PCR-Purified (Qiagenä PCR clean up kit) miR-155GG product was then directionally cloned into pGL3 Basic using BamH1 and HindIII.
Digests & Gel Electrophoresis
Restriction Enzymes BglII and SmaI were used to confirm orientation of miR-155-Pro in pJet cloning vector. In order to check for proper orientation of our insert, we would expect a band at 623 bp and at 230 bp. Samples were digested, heat killed, and run on a
1% Agarose gel.
Dual-Luciferase Assays:
Luminometer Monolight 2010 machine was used to collect luciferase assay data. We used the Dual-Luciferase Assay Reporter Kit as described (Promega Catalog #E1960).
Two forms of luciferase are used in this assay to gather data. The first one is the firefly
13 luciferase enzyme labeled Luciferase Assay Reagent II (LARII). The second luciferase is from an organism called Renilla reniformis, hence the name of the reagent Renilla
Luciferase. Our pGL3 Basic construct used as our negative control was measured by the assay for firefly luciferase activity (expression), as did each deletion construct. In the same manner, our internal control PRL-SV40 was measured for Renilla luciferase activity. In this way, we obtained data on dual-luciferase assay activity. Two reagents,
LARII and Stop and Glo, respectfully, are added into the luminometer apparatus which will dispense each reagent to each sample. LARII is added first, luciferase is measured, then LARII is quenched, Stop and Glo is added second and Renilla is measured. The
LARII measurement is used as a normalization ratio relative to Renilla expression.
Gel Extraction & Purification
A desired PCR band of 811 bps was gel extracted using a sterile razor. Sample was processed as per protocol (Qiagen Gel Extraction and Purification kit).
Harvest
Cells were then harvested after 48 hours (Lee 2008). 6 well plates were removed from incubator and placed in hood for harvest. Media was aspirated from each well and 1 mL of 1X Phosphate Buffer Saline (PBS) was added to each well for a quick wash. PBS was then aspirated off carefully as to not disturb the adhered cells. Then, 1 mL of 1X Passive
Lysis Buffer (PLB) was added to each well to dislodge the adherent cells. Using a rubber policemen, each well was scraped until the cells were visibly floating in PLB. The rubber policemen was washed in PBS after each well. Each sample was then pipetted into an appropriate pre-labeled 1.5 mL Eppendorf tube. 10% bleach solution was then added to each well and plates were left 24 hours in bleach before discarding into appropriate
14 hazard bins. An ice bucket filled with chunks of dry ice and 100% Ethanol was prepared.
Harvested samples were placed in a cold bath for 5 minutes and then into a 37 °C water bath for an additional 5 minutes. This process was repeated 3 times, and then samples were stored in a -20 °C freezer awaiting luciferase assays.
Ligation into pJET cloning vector
Using ThermoFisher T4 Ligase Kit, a purified Polymerase Chain Reaction (PCR) insert fragment was ligated into vector pJET with the following parameters: 5uL of PCR insert,
3 uL of vector, 1uL of T4 Ligase, 5 uL of T4 Ligase buffer and 11 uL of dH2O were added for a total reaction of 25 uL. Mixture was finger flicked to mix and placed in a 16
°C water bath overnight and electrocompetent transformed into DH5alpha cells. .
Colonies were picked and grown overnight in LB/Amp broth, 37 °C shaking incubator.
Plasmid Extraction
Plasmid extraction was performed using ThermoFisher Plasmid Extraction Kit described.
Turbid overnight cultures were obtained. 1.5 mL of culture was pipetted into eppendorf tubes and samples were centrifuged for 3 minutes at 12,000 rpm. Pellet was obtained and a second 1.5 mL of sample was pipetted into the same Eppendorf tube. Sample was once again centrifuged for 3 minutes at 12,000 rpm. Pellet was then resuspended in 260 uL of
ThermoFisher Resuspension Fluid. Microcentrifuge tube was then racked against the tube rack to resuspend the pellet. Once pellet looked visibly resuspended, 250 uL of
ThermoFisher Lysis Solution was added to each tube. Tubes were then inverted 6 times by hand to lysis the cells. Then, 350 uL of ThermoFisher Neutralization Solution was added to stop the reaction. Tubes were now inverted by hand ten times and placed into a centrifuge to spin for 5 minutes at 12,000 rpm. Using a p1000, 800 uL of supernatant was
15 pipetted out of each tube and slowly pipetted into each spin column. Spin columns were then placed into centrifuge and spun for 1 minute at 12,000 rpm. Supernatant from column was discarded and filter top was placed back into column. 500 uL of
ThermoFisher Wash Solution was then added to spin column filter and spin columns were placed in centrifuge and spun for 1 minute at 12,000 rpm. Supernatant was then discarded, and an additional 500 uL of wash solution was added and spin columns were once again spun in centrifuge for 1 minute at 12,000 rpm. Supernatant was discarded, and spin columns were spun one more time by themselves in an effort to completely remove wash solution. Spin column filters were then separated from their columns and placed into previously labeled 1.5 mL microentrifuge Eppendorf tubes. 50 uL of Thermo Fisher elution buffer was then carefully added to each tube making sure to pipette right on to p of the filter. Tubes were incubated at room temperature for 2 minutes, and then spun in centrifuge for 1 minute at 12,000 rpm. Plasmid extraction produced DNA yields of 240-
284 ng/mL upon using nano-drop machine. A mini-digest was performed which entailed using only 5 uL of sample and digesting for only 10 minutes in order to run a diagnostic gel and confirm miRNA-155-Pro insert in vector. Map was again designed, this time for pGL3 vector, and restriction enzymes Bgl II and SmaI (Fermentas) were used to confirm orientation in pGL3.
Polymerase Chain Reaction
The following PCR protocol parameters was used:
Taq PCR Master Mix 12.5 uL 2X Forward Primer 1 ul 10 uM Reverse Primer 1 uL 10 uM Template DNA (genomic DNA) 1 uL 1000 ng dH2O (autoclaved DI water) 25 uL Autoclaved distilled water
16 With a total reaction of 50 uL, PCR tubes were finger flicked to mix, and placed in thermocycler for amplification. Thermocycler parameters for 25 cycles are as follows:
95 °C 30 seconds 95 °C 1 minute 52.5 °C 1 minute 72° C 7 minutes 4° C ∞
With an optimal annealing temperature of 52.5°C, PCR product was obtained and 20 uL were run on a 0.8% agarose gel made by mixing 0.4 grams of agarose with 50 mL of 1x
TAE buffer , bringing mixture to a boil in the microwave and allowing it to cool before pouring into a gel cast tray. Generuler 1kb ladder was used and 4uL was loaded in lane 1.
Subsequent lanes were loaded with 20uL of PCR product. Gelwas run at 60 volts for 90 minutes and then Ethidium Bromide (EtBr) stained.
Primer Design: miR-155HG and miR-155GG
In order to implement isolation, characterization and analysis of the putative miR-155HG and miR-155GG promoter regions, primers were designed to amplify regions upstream of the 5’ UTR: miR-155HG: primers were designed for blunt end cloning
5’ CCCCTTGTGGCAGGGTCCGGG 3’ Forward
5’ CCTTGGTTCCCCGCGCTTGCTCTG 3’ Reverse miR-155GG: primers were designed with BamHI and HindIII restriction sites for directional cloning.
5’ GGAGATCTCTGATGCCAAGTTGTCTGAGGG 3’ Forward
5’ GGGAAGCTTGGGTCTCAAGTTGTTTGGAACGGGC 3’ Reverse
Forward and reverse primers were designed to have GC rich ends, lengths of 18-24 bps, and annealing temperatures as close to one another as possible. Primers were ordered
17 from IDT (Integrated DNA Technologies, Inc.), arrived in lyophilized form, and were
resuspended in 100 uL of H20. As to not lose any DNA that might be stuck on the cap of the tubes, primer tubes were placed in a mini centrifuge for a quick tap spin (5 seconds).
Concentration of working primers was 125 ng/uL diluted in 1X TE Buffer.
Transformation: Electroporation method:
De-salting method: Prior to electroporation, each DNA sample was de-salted using a MF-
Millipore Membrane. In a petri dish, nuclease free water was added and the membrane was placed in water to float. 5 uL of sample was pipetted onto membrane and allowed to sit for 10 minutes. Sample was then pipetted from the membrane. DH5α electrocompetent cells were used for transformation. Cells were retrieved from -80 °C freezer, allowed to thaw for 1 minute on ice, and 5 uL of DNA (200 ng/uL) were pipetted into competent cell tube. Sample was finger flicked to mix, and then immediately pipetted into a sterile, ice cold cuvette. Using an electroporator set at 2.5 kV, cells were zapped for 10 seconds. Cuvette was retrieved and immediately 500 uL of recovery media were added to cuvette. Entire mixture was then transferred to a sterile culture tube using a sterile Pasteur pipette and culture tube was placed in 37 °C shaking incubator at 250 rpm for 1 hour. 250 mLs of sample were then plated onto 2 LB/AMP agar plates and placed in
37 °C incubator overnight. Colonies were picked from plates and grown overnight in tubes with 4 mL of LB/AMP broth.
Transformation: Heat-Shock protocol
DH5alpha lab-made chemically competent cells were thawed and 5 uL of insert DNA was added to comp cells. Tube was finger flicked to mix, and 500 uL of recovery media was added to cells. Cells were then put on ice for half an hour, and then put into a 42 °C
18 water bath for exactly 45 seconds, and then returned to ice bucket for 2 additional minutes. Cells were then placed in a 37 °C shaking incubator for 1 hour. After 1 hour, cells were plated onto LB/AMP agar plates and put in a 37 °C incubator overnight.
Colonies were picked from plates and grown overnight in tubes with 4 ml of LB Amp broth. Plasmid extraction followed. Transformed product was grown at 37° C for 45 minutes in recovery media, plated on LB Amp plates and left in incubator at 37° C overnight. Colonies were picked from plates and grown overnight in tubes with 4 ml of
LB Amp broth (procedure performs optimally if LB is at room temperature. Via electroporation and use of newly made electrocompetent cells, successful results were found. LB AMP plates produced only 2 colonies, yet they were viable. Colonies were picked and grown overnight in LB Amp media, 37 °C shaking.
Sequencing
Confirmation of miRNA155 promoter region in pGL3 was confirmed via Sanger cycle sequencing performed by Laragen.
Site-Directed Mutagenesis: Deletion Constructs
Deletion constructs were designed using naturally occurring restriction enzymes and site- directed mutagenesis created restriction sites (Figure 3). The -811 bp of miR-155’s promoter region was cloned into the pGL3-Basic luc reporter vector (miR155-pGL3-Pro-
811). Constructs were then designed with consideration given to predicted transcription factor binding sites and naturally occurring restriction sites. In instances where cut sites were not available, site-directed mutagenesis was utilized to change bps in order to
19 achieve a restriction enzyme cut site. Deletion constructs at sites -117, -178, 237, 436 were engineered using the following primers:
Site 1: miR155-Xho1-436
5’ -CAC TTG CTC CTC TCG AGC TCC CTG CAA GGA GAG- 3’ Forward
5’ -CTC TCC TTG CAG GGA GGT CGA GAG GAG CAA GAG -3’ Reverse
Site 2: miR155-Sac1-287
5’ - CAA GCT CTA GGT ACC AAG AAC AGG CAGG- 3’ Forward
5’-CCTG CCT GTT CTT GGT ACC TAC AGC TTC- ‘3 Reverse
Site 3: Sma1 CCC_^GGG -178
5’ -GAA CAA AGG TTG GAG CTC AAG CCT TGC GGC GCG -3’ Forward
5’ -CGC GCC GCA AGG CTT GAG CTC CAA CCT TTG TTC - 3’ Reverse
Site 4: Kpn1 GGT ACC-117
5’ –GTTTTTCAAGCTGTAGGTTC 3’ Forward
5’-TGAACACTGAGTATTGGCTGGTCG
Gallus gallus constructs were also designed to harbor the AP1 TF binding site.
Primer design for Gallus gallus miR-155GG-Pro-169:
5’ -GGAGATCCTTGGTTTTTCTCTCTCTCTCTC - 3’ Forward
5’ -GGGAAGCCATTGAGGCATCAGCAGTTG CCGC- 3’ Reverse
Primer design for Gallus gallus miR-155GG-Pro-AP1_mut:
20 5’ -GGTTAGTTATGAGgCACCTTCATGACTTATAAAGGG- 3’ Forward
5’ -CCCTTTATAAGTCATGAAGGTGCCTCATAACTAACC- 3’ Reverse
A modified PCR protocol was used for mutations. PCR was conducted using TURBO hf polymerase with the following parameters:
5 uL 10X Buffer, 1 ul template DNA (50 ng/ul), 1 uL forward primer (125 ng/ul), 1 uL reverse primer (125 ng/uL), 1 uL dNTPs, 16 uL dH20. Finger flick to mix, then add 1 uL of TURBO hf polymerase, finger flick again to mix and place in thermocycler with the following parameters:
95 °C 30 seconds 95 °C 1 minute 55 °C 1 minute 68° C 6 minutes (1 minute per kb) 4° C ∞
Tissue Culture: HEK293 T cells
HEK 293-T are human embryonic kidney cells which harbor the Large T antigen of the herpes virus (ATCC). Frozen cell line samples were obtained from the -80 freezer, thawed, and placed in a 15 mL sterile conical vial with warm Dulbecco Modified Eagle
Medium (DMEM) media with 10% FBS. Cells were then centrifuged at 300g for 5 minutes to remove freeze media from cells. Supernatant was discarded, and cell pellet was resuspended in warm DMEM with 10% FBS. Cells were then pipetted into T75 filter flasks with warmed 25 mL DMEM with 10% FBS. Cells were incubated in 37°C with
5% CO2 overnight. Cells were observed under the microscope for confluency, passaged, and 6 well plates were prepared for transfection.
21 Tissue Culture: Mouse NIH3T3 cells
Mouse NIH3T3 cells were handled as the above HEK293-T cell protocol. NIH 3T3 cells are mouse fibroblasts, which have been spontaneously immortalized.
Tissue Culture: DF-1 Chicken Fibroblasts
DF-1 CEF cell line (Chicken Embryonic Fibroblasts) was purchased from ATCC
(ATCC-CRL-12203). These are an adherent cell line from the East Lansing Line (ELL-
0). CEFs are an immortalized cell line with a patent name of DF-1, an avian cell line which has been shown to have high transfection efficiency (Lee 2008). Cell morphology expected is stated as a spindle shaped fibroblasts (Kong 2011). Cells were shipped from
ATCC frozen in complete DMEM with Dimethyl sulfoxide (DMSO). Upon receiving, cells were immediately placed into liquid nitrogen tank as directed by manufacturer. A 1 liter supply of fresh media was made: DMEM complete media with glucose and L- glutamine, 20% FBS (Fetal Bovine Serum): 13.58 grams of DMEM powder, 10 mL
Pen/Strep antibiotics, 10 mL Non-essential amino acids, 10 mL Sodium Pyruvate, 200 mL FBS, and 3.7 grams of Sodium Bicarbonate were mixed in a sterile graduated cylinder with a spin column and autoclaved dH20 was added to bring the volume up to 1 liter. Media was then vacuum filtered into sterile media bottles. Two T25 cell tissue culture flasks were filled with 10 mL of media and placed in 37 °C degree incubator to warm up so that the CEF cells would have a nice warm home to grow in. Frozen vial of cells was taken out of liquid nitogen tank and swirled for 1 minute in a 37 °C degree water bath using aseptic techniques and making sure to keep the top cap out of the water to avoid contamination. Vial was then taken to a laminar flow hood and sprayed with
70% ethanol before opening. Cells were transferred via gentle careful pipetting into a 15
22 mL sterile conical vial with pre-warmed media. Cells were spun at 200 xg for 5 minutes.
Pellet was obtained. Although the protocol stated that the supernatant should be discarded, supernatant was then transferred to a T25 cell tissue culture flask in case it still had viable cells which could be used. Once supernatant was removed from vial, fresh media was added and the cells were resuspended via the finger flick method. Media with suspended cells was then pipetted into a pre-warmed T25 flask and placed in a 37 C degree incubator with 5% CO2, and a prayer was sent to the heavens. Cells were then checked every 4 hours to make sure they did not pass >80% confluency. Six hours after plating, cells looked ~35% confluent. At 12 hours after plating, cells looked ~50% confluent. Finally, at 24 hours after plating, cells were > ~80% confluent and were ready for passaging. We now had two T25 flasks with CEF cells. One T25 flask was transferred to a ThermoScientific BioLite 100mm Tissue Culture Dish. A second T25 was transferred to a T75 cell tissue flask. DF-1 CEF have been shown to be easily trypsinized and show little susceptibility with a maximum concentration up to 0.1 g/ml (Lee 2008).
Both flasks were treated the same. At this point, a literature search provided data on the media preferences for CEF and DF-1 cells. Preferred media which allows for a 21 hour doubling time for these cells was shown to be DMEM with 1.5 grams of sodium bicarbonate and 7% FBS (Azmir 2008). Therefore, a new batch of DMEM was made to these specifications for the passaging. Media was completely removed from flasks, cells were washed with PBS to make sure all the media was removed, as any left over media will deactivate the protease. PBS was removed, and 2 mL of pre-warmed trypsin was added to the flask, enough to cover the monolayer (~2 mL). Once cells were detached from flask and resuspended in media, cells were collected via pipetting and placed into a
23 15 mL conical vial and spun at 200 xg for 5 minutes. A pellet was obtained, supernatant was discarded, and cells were resuspended in fresh media which was then pipetted into a pre-warmed T75 flask, as well as a 10 mm tissue culture dish. Flask and dish were then placed in 37 C degree incubator with 5% CO2. Cells were then monitored for appropriate confluency passage into additional T75 flasks to be able to have working stocks as well
as frozen stocks. After 24 hours, cells were confluent.
Transfections:
Transfections were conducted utilizing human HEK 293T cells (Human), NIH3T3 cells
(mouse) and DF-1 CEF (Chicken).
Transient Transfections:
6 well plates with ~30% confluency of HEK 293T cells were utilized for transfection using Promgea Dual Luciferase Assay Kit. Cells were seeded in 6-well plates with
DMEM media with 10% FBS and incubated overnight at 37 °C to allow for growth and adherence to flask. In preparation for transfection, constructs were nano-dropped for concentration, and all constructs were diluted to equal 0.6 ug/uL with our internal control construct PRL-SV40 set at 0.4 ug/uL for a total concentration of 1 ug of DNA in each well. pGL3 Basic is used here as a negative control, expressing basal transcription levels, while pGL3-SV40 is being used as a positive control, exhibiting immensely high levels of expression due to the viral promoter within. DMEM with 10% FBS was placed in a 37
°C incubator to pre-warm. 1.5 mL autoclaved Eppendorf tubes were labeled accordingly, one for each well. 140 uL of EC Buffer was added to each tube followed by 1 uL of PRL-
SV40. In addition, 1 uL of DNA was added to tube. This was then followed by 8 uL of
24 Qiagen Enhancer reagent. Tubes were then vortexed and incubated for 2 minutes at room temperature. 4 uL of Qiagen Effectene reagent was then added to each tube and again tubes were vortexed. Tubes were then left to incubate at room temperature for 10 minutes. Media was aspirated from each well and new DMEM was added to each well carefully as to not disturb the already adhered cells which we were about to transfect. An additional 1 mL of media was then added to each tube sample and then the sample was pipetted into the appropriate well. 6 well plates were then swirled to mix the media with
the newly added sample and placed in 37 °C incubator with 5 % CO2 for 48 hours undisturbed.
Data Preparation
All Dual Luciferase assay data were analyzed using Microsoft Excel. A minimum of 3 sets of replicates were used for each data set and normalization was based on firefly luciferase ratio. Student’s two sided T-test was utilized to analyze statistical significance of data sets and p values of > or < 0.05 were noted.
Bioinformatics Methods:
Programs used: ClustalW, MEGA software, Cytoscape
ClustalW:
Sequences for promoter region and miR-155 stemloop were obtained from NCBI and sequences were then aligned using ClustalW software. Sequences for promoter region were initially 1,000 bps long and were subsequently reduced to 480 bps for more concise alignment of Transcription Factor binding sites of interest.
25 MEGA software:
Sequence alignments from ClustalW were then inputed into MEGA software for analysis of evolutionary conservation. MEGA software was used to conduct phylogenetic tree analysis using model testing methods.
Cytoscape:
MiR-155 targets were obtained from miRTarBase.com, and data was inputed into
Cytoscape software. Using cluster modeling, targets were aligned based on commonality of target between organisms.
26 Chapter 3
Results Part 1
MiR-155HG: Identification of promoter region and Transcription Factors (TFs)
Identification of essential TFs that drive transcription of a gene involves characterization of a gene’s promoter region and the predicated TF binding sites that are possibly contributing to optimal gene expression. Eukaryotic promoters include core and proximal promoter regions, with the proximal promoter region harboring binding sites for important TFs. To identify the TF driving transcription of miR-155HG, the putative promoter region of miR-155HG was located in NCBI, isolated, and miR-155HG-
811/+129.
was cloned into an expression vector pGL3 Basic, a promoter-less luciferase reporter vector, for transient transfections. In addition, in silico analysis of the putative promoter region of miR-155HG using four different databases, Gene-Regulation, TFSEARCH,
Match and PROMO, was performed, and binding sites that were identified in at least three databases were marked for analysis. In total, eight TFs as well as the TATA box, located 28 bps upstream of the TSS (Transcriptional Start Site), were identified (Figure
2).
27
Figure 2: Promoter region of miR-155HG with predicted TF binding sites. Promoter region of Homo sapiens miR-155HG -811 bps upstream of TSS. TF binding sites that matched across three databases are labeled and sequences are highlighted. -117/+129 Construct designed to harbor AP1 TF binding site. -178/+129 construct designed to harbor ISGF-3 TF and AP1 TF binding site. -287/+129 construct designed to harbor IRF-1 TF, NFkB TF, ISGF-3 TF and AP1 TF, -436/+129 construct designed to harbor ELF-1 TF, IRF-1 TF, NFkB TF, ISGF-3 TF and AP1 TF binding site. -811/+129 construct harbors SP1 TF, NFkB TF, OLF-1 TF, PU.1 TF, ELF-1 TF, IRF-1 TF, NFkB TF, ISGF-3 TF and AP1 TF binding site. NCBI database was used to locate miR-155HG promoter region, TF databases were used to identify predicted TF binding sites within promoter region.
28
Transient transfection of HEK 293T cells and dual luciferase assays confirmed promoter activity of miR-155HG-811/+129 (Figure 3) and subsequent deletion constructs, using the sequence map of predicted TF binding sites, were designed and engineered (Figure
2). Four constructs, -811, -436, -287 and -178 were initially designed and tested for promoter activity. Of these constructs, -178 was the only construct that exhibited statistically significant expression of activity with a p-value of < 0.05 (Figure 3).
Constructs -286 and -436 exhibited statistically significant lower expression than the -178 construct, and expression of -286 and -436 were not statistically significant in comparison to our promoter-less control vector (Figure 3), suggesting that predicted TFs in the regions of -286 and -436 are not contributing to the optimal expression of the gene and that the statistically significant expression of -178 indicated that perhaps essential
TFs were located within this region and were needed for optimal transcription of this gene.
29 miR155HG-811/+1
Transient Transfections! miR155HG-433/+1 Expression of miR-155HG in HEK 293 T cells !
miR-155HG-178/+129! LUC 5 miR155HG-285/+1 miR-155HG-287/+129! LUC 4
miR-155HG-436/+129! LUC 3 miR-155GG-305/+1 miR-155HG! LUC 2 -811/+129!
pGL3 Basic - Control! LUC 1 miR155HG-117/+1 0 1 2 3 4 5 6 7
Fold Activity !
SP1! OLF-1! ELF-1! PU.1! NFkB! IRF-1! ISFG-3! AP-1!
Figure 3: The -178/+129 promoter construct shows optimal expression activity and defines proximal promoter region. Deletion constructs -811/+129, -436/+129, -287/+129, -178/+129 and pGL3 basic promoter-less control transiently transfected into HEK293 T cells. TFs are labeled on Y-axis with legend at bottom of graph. Expression activity for each construct displayed on x-axis showing fold activity over pGL3 basic control. Transient transfection data was evaluated for Students two-sided t-test and data showed construct -178 statistically significant higher expression than all other constructs with p-value < 0.05. Lane 1: pGL3 Basic promoter-less vector negative control. Lane 2: Construct -811/+129 harbors all 8 predicted TF binding site. Lane 3: Construct -436/+129 harbors ELF-1 TF, IRF-1 TF, NFkB TF, ISFG-3 TF and AP1 TF binding sites. Lane 4: Construct -287/+129 harbors IRF-1 TF, NFkB TF, ISFG-3 TF and AP1 TF binding site. Lane 5: Construct -178/+129 construct designed to harbor ISGF-3 and AP1 TF binding site.
30 Evolutionarily Conserved Transcription Factor Consensus Sequences
Two putative transcription factor binding sites within the essential -178 region of miR-
155HG were identified using TF prediction databases, with locations at -175 and -54. The
TF ISFG-3 binding site was predicted to be located at -175 and the TF AP1 binding site was predicted to be at -54 (Figure 2). Initial MSA analysis of miR-155 promoter regions proved futile. Approximately 1,000 bps was located for each species and although the
AP1 TF binding site was conserved in 9 species, software programs are unable to align this region (data not shown), therefore, sequences were reduced to -480 regions and these sequences were used for an MSA in MEGA software to align and identify TF binding sites. Alignment in MEGA of twenty sequences revealed 9 species with sequences that harbored AP1 TF binding sites for TGA G/C TCA and/or p-box TGAGTTCA. Of these
9, 5 were found to have 100% identity with the TGA G/C TCA AP1 TF binding site, including Human, Chimp, Chicken, Zebra Fish and Chinese Tree Shrew (Figure 4).
Although not all 9 sequences had the AP1 TF binding site, for a promoter region to have a TF binding site in common with 5 out of 9 sequences is significant, suggesting that AP1
TF is an important TF within this gene’s promoter region and possibly the TF driving optimal transcription of miR-155HG.
Phylogenetic Analysis of Evolutionary Conservation
of miR-155HG Promoter Region
MSA of miR-155 sequences across species and model testing of the promoter region of miR-155 was performed to find the best-fit model for phylogenic analysis and tree construction. The most vital information obtained from a model test is the AIC
(Akaike Information Criteria). The model test calculation of the AIC output directs us to
31 the best fit substitution model for constructing a phylogenetic tree (Table 2). A model test was performed on all twenty-one sequences across species for miR-155-Pro and our results indicated that the best model to use was JC with I and G being n/a (Table 1). This indicates that the best evolution model to use is the Jukes Cantor parameter with no values for G and I. Our “G” values are stated as 0.00. G values are Gamma Distribution values which models the non-uniformity of evolutionary rates. Our “I” values are 0.
These values are for evolutionary invariabilities among sites. Phylogenetic analysis of our
JC tree with Bootstrap parameters of 1000 indicated a confidence level of 97 for the conservation between Human and Chimp, and significant decreases in conservation for
Chicken, Zebra Fish, Mouse, Pig and Chinese Tree Shrew, with confidence levels < 70%
(Figure 5).
32
Figure 4: MEGA MSA line-up of miR-155 conserved TF binding site AP1 TF TGA G/C TCA and p-box TGAGTTCA across 20 species. AP1 TF Binding Site is Conserved in 5 species and p-box sequence is conserved in 3 species.
33
AIC Parameters: Maximum Likelihood with Jukes Cantor, 1000 Bootstrap method.
34
Figure 5: miR-155 Promoter region AIC Model Phylogeny Tree: Maximum likelihood with Juke-Cantor. Five species with conserved AP1 TF binding sites, Human, Chimp, Chicken, Zebra Fish and Pig, indicate common node with Human and Chimp having a bootstrap score of 97.
35 These data suggested that the AP1 binding site within our -178 construct was important for further analysis and thus, an additional deletion construct was engineered, -117, that now only harbored the predicted AP1 TF binding site (Figure 2).
The region spanning construct -178/+129 was predicted to have two TF binding sites,
ISFG-3 and AP1 (Figures 2), therefore, a deletion construct was designed to only harbor
AP1 TF (-117/+129 construct). Once this construct was separated into two smaller constructs; -178/+129 and -117/+129, transient transfection results indicate a statistically significant difference in expression of -117/+129 construct, which harbors the AP1 TF, and gives the highest expression, with a p-value < .05 (Figure 6). These results suggest that ISFG-3 does not contribute to the optimal expression of this gene.
36 miR155HG-811/+1
Transient Transfections! miR155HG-433/+1 Expression of miR-155HG in HEK 293 T cells !
miR-155HG-117/+129! LUC 6
miR-155HG-178/+129! LUC 5 miR155HG-285/+1 miR-155HG-287/+129! LUC 4
3 miR-155HG-436/+129! LUC miR-155GG-305/+1 2 miR-155HG! LUC -811/+129! pGL3 Basic - Control! LUC 1 miR155HG-117/+1 0 2 4 6 8 10 12 Fold Activity !
SP1! OLF-1! ELF-1! PU.1! NFkB! IRF-1! ISFG-3! AP-1!
Figure 6: The -117/+129 promoter construct shows optimal expression activity over construct -178/+129. Deletion constructs -811/+129, -436/+129, -287/+129, -178/+129, -117/+129 and pGL3 basic promoter-less control transiently transfected into HEK293 T cells. TFs are labeled on Y-axis with legend at bottom of graph. Expression activity for each construct displayed on x-axis showing fold activity over pGL3 basic control. Normalized internal control pRLSV40 luciferase reporter vector with promoter and enhancer is the +/- standard deviation of at least 4 independent transient transfections and 3 samples of DNA preps. Transient transfection data was evaluated for Students two-sided t-test and data showed construct -117 statistically significant higher expression than all other constructs including -178/+129 with p-value < 0.05. Lane 1: pGL3 Basic promoter-less vector negative control. Lane 2: Construct -811/+129 harbors all 8 predicted TF binding site. Lane 3: Construct -436/+129 harbors ELF-1 TF, IRF-1 TF, NFkB TF, ISFG-3 TF and AP1 TF binding site. Lane 4: Construct -287/+129 harbors IRF-1 TF, NFkB TF, ISFG-3 TF and AP1 TF binding site. Lane 5: Construct -178/+129 construct designed to harbor ISGF-3 and AP1 TF binding site. Lane 6: Construct -117/+129 harbors AP1 TF binding site.
37 Transient transfections results show a statistically significant difference in expression between constructs -178/+29 and -117/+129, with the latter exhibiting the higher expression p-value < .05 (Figure 6). Since construct -117 that harbors the predicted AP1
TF binding site exhibited higher expression statistically than all other constructs, we decided to mutagenize the binding site and observe if inhibition of binding could be observed with a decrease of expression. The highly conserved AP1 TF binding site was mutagenized to inhibit binding of AP1 and determine importance of this sequence.
Transient transfection results using human HEK293T cells indicated a statistically significant decrease in expression between construct -117/+129 that harbors the AP1 TF binding site and miR-155-117/+129-AP1mut that has a mutated site at TGAGGTCA, destroying AP1 binding (Buttice 1991) (Figure 7). These data suggest that AP1 TF binding is essential for optimal expression of construct -117/+129.
38 Transient Transfections! Expression of miR-155HG-AP1mut in HEK293T Cells!
miR-155HGAP1mut! LUC 3
miR-155HG-117/+129! LUC 2
1 pGL3 Basic! LUC
0 2 4 6 8 10 12
Fold Activity!
Figure 7: miR-155-AP1mut construct exhibits decrease in expression as compared to -117/+129 that harbors the AP1 binding site with p-value < 0.05. Deletion constructs -117/+129, miR-155-AP1mut and pGL3 basic promoter-less control transiently transfected into HEK293 T cells. TFs are labeled on Y-axis with legend at bottom of graph. Expression activity for each construct displayed on x-axis showing fold activity over pGL3 basic control. Normalized internal control pRLSV40 luciferase reporter vector with promoter and enhancer is the +/- standard deviation of at least 4 independent transfections and 3 samples of DNA preps. Transient transfection data was evaluated for students two-sided t-test and data showed construct miR-155-AP1mut with a statistically significant decrease in expression activity over construct -117 with p-value < 0.05. Lane 1: pGL3 Basic promoter-less vector negative control. Lane 2: Construct -117/+129 harbors AP1 TF binding site. Lane 3: miR=155HG-AP1mut binding site.
Since the MSA of miR-155 across 20 species indicated an AP1 TF binding site among 9 species, with G. gallus (chicken) as one of the top 5 among Human, Chimp, Chicken,
Zebra fish and Chinese tree shrew that exhibited 100% identity in comparison to human
39 (Figure 4), we isolated and analyzed the putative promoter of the Chicken miR-155 (miR-
155GG) TF binding sites (Figure 8).
Figure 8: Promoter region of Chicken miR-155GG with AP1 TF Binding site and TATA box identified using NCBI and TF Database search. NCBI database was used to locate miR-155GG promoter region, TF databases were used to identify predicted TF binding sites within promoter region. Promoter region of Gallus gallus miR-155GG-169 construct with AP1 TF binding site and TATA box labeled and highlighted.
40 A consensus TATA box with 100% identity to the human was also observed (Figure 4).
The putative promoter region of miR-155GG (chicken) was engineered, construct miR-
155GG -169/+114, and transient transfections into human HEK 293T cells and DF-1 chicken fibroblast cells were performed (Figures 9). Transient transfection data was obtained for expression of miR-155HG -117/+129 and miR-155GG -169/+114 constructs in HEK293T cells. For the human miR-155HG 117/+129 construct that has the AP1 TF binding site intact shows statistically significant levels of expression with a p-value < .05 as compared to our pGL3 Basic control (Figures 6 and 7). Our chicken miR-155GG promoter construct also gave comparable expression in HEK 293T cells as compared to the miR-155HG -117/+129 construct, both of which harbor the AP1 TF binding site
(Figure 9). These data confirm promoter activity for miR-155GG -169/+114 construct in human HEK 293T cells.
41 Transient Transfections! SYMBOL PREDICTED Expression of miR-155HG and miR-155GG in HEK 293T cells! TF FACTOR
SP1
miR-155HG-117/+129 LUC 4 OLF-1 miR-155-117/+1! LUC miR-155-175/+1! LUC ELF-1 3 miR-155GGmiR155GG-169/+114 -169/+1! LUC LUC miR-155-287/+1! LUC PU.1 miR-155HG 2 miR-155HG-436/+1! LUC LUC -811/+129 miR-155HG! NFKB -811/+1 ! LUC pGL3 Basic! LUC 1 pGL3 Basic! LUC IRF-1 0 2 4 6 8 10 12 miR-155 -811/+1 ISGF-3 Fold Activity! miR-155HG AP1 C-JUN TTATGAGTCACAAGTGAGTTATAAAAGGGT SP1! OLF-1! ELF-1! PU.1! NFkB! IRF-1! ISFG-3! AP-1!
miR-155 -811/+1 miR-155 -811/+1 miR-155GG
TTATGAGTCACCTTCATGACTTATAAAGGGT Figure 9: Expression of constructs miR-155HG-117/+129 and miR-155GG-169/+114 in HEK293T cells exhibit statistically significant higher expression as compared to pGL3 Basic control and miR-155HG-811/+129 construct with p-value < 0.05. Deletion constructs miR-155-811/+129, miR-155GG-169/+114, miR-155HG-117/+129 and pGL3 basic promoter-less control transiently transfected into HEK293 T cells. TFs are labeled on Y-axis with legend at bottom of graph. Expression activity for each construct displayed on x-axis showing fold activity over pGL3 basic control. Normalized internal control pRLSV40 luciferase reporter vector with promoter and enhancer is the +/- standard deviation of at least 4 independent transfections and 3 samples of DNA preps. Transient transfection data was evaluated for Students two-sided t-test and data showed construct -117 and -169 show statistically significant higher expression than all other constructs with p-value < 0.05. Lane 1: pGL3 Basic promoter-less vector negative control. Lane 2: Construct -811/+129 harbors all 8 predicted TF binding sites. Lane 3: Chicken construct -169/+114 harbors AP1 TF binding sites. Lane 4: Construct -117/+129 harbors AP1 TF binding sites.
42 AP1 TF was found via bioinformatics MEGA alignment and has 100% identity between human and chicken within the miR-155 promoter regions, therefore, to analyze expression levels of said construct in chickens, DF-1 chicken fibroblast cells were transiently transfected with miR-155HG -117/+129 and miR-155GG 169/+114. The promoter activities of miR-155HG -117/+129 and miR-155GG 169/+114 constructs in
DF-1 chicken fibroblast cells indicate that both chicken and human promoter constructs exhibit comparable expression levels, both are statistically significantly above the pGL3
Basic control with a p-value < .05 (Figure 10).
43 Transient Transfections!
Expression of miR-155HG and miR-155GG ! in DF-1 Chicken Fibroblast cells!
miR-155HG-117/+129 LUC 4
miR155GG-169/+114 LUC 3 LUC LUC LUC miR-155HG LUC 2 -811/+129
pGL3 Basic! LUC 1
0 2 4 6 8 10 12
SP1! OLF-1! ELF-1! PU.1! NFkB! IRF-1! ISFG-3! AP-1!
Figure 10: Expression of constructs miR-155HG-117/+129 and miR-155GG- 169/+114 in DF-1 chicken fibroblast cells exhibit statistically significant higher expression as compared to pGL3 Basic control and miR-155HG-811/+129 construct with p-value < 0.05. Deletion constructs miR-155-811/+129, miR-155GG-169/+114 (pink), miR-155HG- 117/+129 and pGL3 basic promoter-less control transiently transfected into DF-1 chicken fibroblast cells. TFs are labeled on Y-axis with legend at bottom of graph. Expression activity for each construct displayed on x-axis showing fold activity over pGL3 basic control. Transient transfection data was evaluated for students two-sided t-test and data showed construct -117 and -169 show statistically significant higher expression than all other constructs with p-value < 0.05. Lane 1: pGL3 Basic promoter-less vector negative control. Lane 2: Construct -811/+129 harbors all 8 predicted TF binding sites. Lane 3: Chicken construct -169/+114 harbors AP1 TF binding sites. Lane 4: Construct -117/+129 harbors AP1 TF binding sites.
44 As in the human miR-155-117/+129-AP1mut construct, the chicken miR-155GG
169/+114 AP1 TF binding site was mutagenized. Transient transfections of HEK293T cells indicated a statistically significant decrease in expression between the chicken miR-
155GG 169/+114 and the chicken miR-155GG 169/+114AP1mut that has a mutated site at TGAGGTCA (Figure 11A). These data are similar in decrease of expression as the human miR-155-117/+129 construct to the human miR-155-117/+129-AP1mut construct
(Figures 11A). These data suggest that the miR-155GG chicken construct -169/+114 also has an AP1 TF binding site that is essential for optimal expression of the chicken miR-
155GG 169/+114 promoter.
DF-1 chicken fibroblast cells were transiently transfected with human miR-155-
117/+129, human miR-155-117/+129-AP1mut, chicken miR-155GG 169/+114, and chicken miR-155GG 169/+114AP1mut constructs (Figure 11B). Transfections in both cell lines produced similar results between constructs with AP1 TF binding site intact and constructs with AP1 TF binding site mutated with p-values < .05.
45 Transient Transfections of miR-155HG-117/+129AP1mut! & miR-155GG-169/+114AP1mut in 3 cell lines !
A! B!
C!
SP1! OLF-1! ELF-1! PU.1! NFkB! IRF-1! ISFG-3! AP-1!
Figure 11: miR-155HG-AP1mut and miR-155GG-AP1mut constructs exhibit decrease in expression as compared to -117/+129 and -169/+114 that harbors the AP1 binding sites with p-value < 0.05 in all three cell lines 11A-C. Deletion constructs -169/+114 and -117/+129, miR-155GG-AP1mut and miR-155HG-AP1mut and pGL3 basic promoter-less control transiently transfected into HEK293 T cells (A), DF-1 Chicken fibroblast cells (B) and mouse NIH 3T3 cells (C). TFs are labeled on Y-axis with legend at bottom of graph. Expression activity for each construct displayed on x-axis showing fold activity over pGL3 basic control. Transient transfection data was evaluated for students two-sided t-test and data showed construct miR-155-AP1muts with a statistically significant decrease in expression activity over constructs -169 and -117 with p-value < 0.05. Lane 1: pGL3 Basic promoterless vector negative control. Lane 2: Construct -169/+114GG construct with AP1 TF binding site. Lane 3: Construct miR-155GG-169/+114-AP1mut binding site. Lane 4: Construct -117/+129HG construct with AP1 TF binding site. Lane 5: Construct miR-155HG-117/+129-AP1mut binding site.
46 Interestingly, the MSA of the AP1 TF binding site conservation across species indicated that miR-155 for Mus musculus (mouse) does not have the predicted AP1 TF consensus binding site (Figure 4). All constructs were transiently transfectioned into mouse NIH
3T3 cells and similar results were obtained as we saw in the human HEK293 T cells and the chicken DF-1 fibroblast cells (data not shown). Transient transfections of constructs into NIH 3T3 mouse cells exhibited a statistically significant difference in higher expression in construct -117/+129 as compared to pGL3 Basic control with p-values <
.05 (data not shown). Subsequently, constructs miR-155HG-117/+129-AP1mut and miR-
155GG-169/+114-AP1mut were transfected into mouse NIH 3T3 cells and a statistically significant decrease in expression was observed similar to the decrease in expression observed in the HEK293 T cells and DF-1 chicken fibroblast cells (Figure 11C).
Expression differentiation was statistically significant with p-values < .05.
47 Results Part 2
miR-155 Stem-loop product
Conservation of miR-155 Stem-loop and Targets
Analysis of the evolutionary conservation of the MiR-155-5p stem-loop across species was performed and included analysis of nucleotide mutations, transversions and transitions illustrated in phylogeny trees. A MEGA alignment illustrates that conservation of RNA along the sequence is found in three regions with high similarity amongst twenty- seven species (Figure 12). Using the MEGA software, our model test suggested the best-fit tree for our alignment as a Tamura 3-parameter G+I. Our best-fit tree suggests the highest conservation among species between the Zebra Fish and Channel catfish with a confidence score of 99.
Conservation of miR-155 stem-loop sequence as well as mRNA targets were obtained using NCBI, Genecards, TargetScan, miRTarBase, MEGA and Cytoscape softwares and databases. MiRTarBase database was used to acquire miR-155-5p and miR-155-3p stem-loops for 27 species (Supplemental Figure 1). Sequences were then transferred to MEGA software for alignment and conservation data. Data was then used in conjunction with MEGA parameters to obtain an MSA as well as distances matrices, model testing, and phylogeny. Although MEGA software uses ClustalW parameters for its alignments, manual alignments were necessary as well. mRNA targets were obtained using miRTarBase and were compared between five species; human, mouse, rat, chicken, and dog (Supplemental Figure 2A). mRNA target data was then extrapolated into
Cytoscape software in order to align mRNA targets in common (data not shown).
48 Bioinformatics data was obtained on the product of miR-155HG, the miR-155 stem-loop.
Sequences for 27 species were obtained from NCBI and aligned in MEGA to show high conservation of stem-loop across species (Figure 12).
Figure 12: Molecular Evolutionary Genetics Analysis: MEGA software line up of conserved miR-155 stem-loop across 27 species.
Model Testing: Model testing for miR-155 stem-loop was performed using MEGA software. AIC resulted indicated the best model for the 27 sequences of miR-155 stem- loop to be Tamura3-parameter: T92+G+I Tree.
49
Figure 13: AIC Best model fit parameters Tamura 3-parameter model. Model Test Output: T92+G+I Tree with bootstrap parameters of 1,000.
50
Maximum Likelihood Parameters:
51
Figure 14: Best model fit parameters Tamura 3-parameter model. Model Test Output: T92+G+I Tree with bootstrap parameters of 500.
52
53
Figure 15: Best model fit parameters Tamura 3-parameter model. Model Test Output: T92+G+I Tree with bootstrap parameters of 1,500.
54
Table 4
55
Figure 16: Best model fit parameters Tamura 3-parameter model.
Model Test Output: T92+G+I Tree with bootstrap parameters of 2,000.
56 Discussion
Gene regulation is key for normal development of an organism, cellular differentiation, proliferation, and cell death. Regulation of gene expression, whether at the transcriptional or post-transcriptional level, is heavily regulated by Transcription
Factors (TFs) generally found in the core promoter region within the first 300 bps upstream of the TSS. Proximal promoter regions harbor vital TF binding sites and identification and conservation of these sites are imperative for the optimal regulation of a gene. MiR-155 was found to have differential expression in two types of lymphomas
(Henson et al., 2011), and identifying the TFs driving optimal transcription of this gene is of importance. TF databases were used to obtain predicted TF binding sites within the promoter region of miR-155HG and bioinformatics analysis conducted on the promoter region for miR-155HG found dozens of TFs located with the -811/+129 promoter region, however, only 8 of these TFs were found to overlap in the four databases utilized; SP1,
NFkB, OLF-1, PU.1, ELF-1, IRF-1, ISGF-3, and AP1.
Deletion constructs designed to have TFs within their prospective regions were utilized for transient transfections of three different cell lines; HEK 293T cells, DF-1 chicken fibroblast cells, and NIH 3T3 mouse cells.
Transient transfections of miR-155HG in HEK 293T cells: Data from transient transfections of miR-155 -811/+129 construct, as well as subsequent constructs -
436/+129, and -287/+129 did not show statistically significant differential of expression among constructs in HEK 293T cells (Figure 3), which was surprising since there are so many notable TFs within each of these constructs. Most of these TFs have been found to
57 be involved in either apoptosis or cellular differentiation, including NFkB, PU.1 and
AP1.
NF-kB: Constructs -811/+129, -436/+129 and -287/+129 all have the predicted NFkB TF binding site, as well as numerous others, within the particular region of the promoter, yet all of these constructs did not show statistically significant differences in gene expression as compared to the -178/+129 construct that has the predicted ISFG-3 and AP1 TF binding sites within the region of the promoter (Figure 3). Nuclear factor kappa-light- chain-enhancer of activated B cells (NF-kB) is a complex of proteins found in the cytoplasm of all animal cells in an inactive form. NF-kB is activated via its interaction with phosphorylated NF-kappa-B inhibitor (I-kappa-B) and in response to apoptotic stimuli, cytokines, and interleukins, proteins made by leukocytes in response to immune function of cells. Interestingly, in a study by Catz et al., the promoter region of BCL-2, a target of miR-155’s stem loop product, was shown to be transcriptionally regulated by
NF-kB, suggesting NF-kB’s role in the regulation of apoptosis by the regulation of BCL-
2 gene expression. However, in our study, no differential expression was observed that was statistically significant, suggesting other predicted TFs within miR-155’s promoter region may be responsible for driving transcription of this gene and thus regulating gene expression.
PU.1: TF PU.1 is yet another TF that is predicted to have binding sites within our constructs -811/+129, -436/+129, -286/+129, all of which, as aforementioned, did not show statistically significant differential gene expression (Figures 3 & 6). Encoded by the
SPI1 proto-oncogene, PU.1 is a Hematopoietic TF (HTF) that regulates the development and differentiation of myeloid cells. Myloid cells include monocytes, megakaryocytes,
58 macrophages, neutrophils, basophils, eosinophils, erythrocytes and dendritic cells. In a study by Koschmieder et al., knock-out mice showed that any alteration in HTF expression, whether from translocation, transitions or other mutations, can result in fatal leukemia. PU.1 TF targets include Macrophage Colony-Stimulating Factor 1 Receptor
(M-CSFR), Granulocyte macrophage colony-stimulating factor receptor (GM-CSFR), and Granulocyte Colony Stimulating Factor (G-CSFR), all genes involved in the regulation and production of white cells such as granulocytes and macrophages
(Genecards). MiR-155 is involved in the differentiation of myeloid cells, and interestingly, a study in 2015 by Gerloff et al. showed that miR-155 targets PU.1, a TF, as we mentioned previously, that is involved in myeloid TF development and differentiation. This study also found that both knock-down of miR-155 or overexpression of PU.1 TF inhibited cell proliferation and in induced cell death in leukemia (Gerloff et al., 2015). In our study, our -811/+129 construct harbors all 8 TFs, and luc assay data does not show statistically significant differential expression between our -811/+129 construct and our -436/+129 construct which was designed to exclude the predicted binding sites for TFs SP1, NF-1, OLF-1 and PU.1. In addition, no statistically significant difference in expression was observed in between construct -811/+129 and construct-285/+129 that have the TF binding sites for ISGF-3, IRF-1 and NFkB, with binding site for IRF-1 are predicted to have binding sites for the same region. IRF-1 is a
TF involved in the regulation and activation of transcription in interferon genes
(Genecards).
59 Construct -178/+129, however, did show statistically significant differential gene expression as compared to all other constructs including pGL3 Basic and full construct -
811/+129, with data showing higher expression of -117/+129 with a p-value of < 0.05, suggesting this region was possibly of importance. Construct -178/+129 was then analyzed via bioinformatics and it was revealed that two TF binding sites were predicted at -54 and -175 of miR-155HG’s promoter region, ISFG-3 and AP1. Bioinformatics data also revealed via an MSA (Figure 4), that 9 out of 20 species contained the AP1 TF binding sites within their promoter regions, and thus, an additional construct was designed, -117/+129, that solely contained the AP1 TF. Transient transfections in HEK
293T cells of additional deletion construct -117/+129, which contained the AP1 TF binding site, showed statistically significant differential gene expression as compared to all other constructs (Figure 6) including construct -178/+129, which contained the AP1 as well as the ISFG-3 TF binding site, suggesting not only that AP1 TF plays an essential role in driving the optimal transcription of miR-155HG, but further suggests that ISFG-3 is a possible inhibitor of gene transcription in the promoter region of miR-155HG and thus, possibly plays a role in the regulation of expression levels of this gene.
Transcription factor Interferon-Stimulated Gene factor-3 (ISFG3) is a transcription factor that is ligand-dependent. ISFG-3 is activated upon receiving signals from interferons and thus exports out of the nucleus to bind to a segment of DNA recognized as its binding site
(Platanias, 2005). Literature on ISFG-3 is quite sparse, and we would suggest that future direction in exploring the role of ISFG-3 in this promoter region entail engineering a construct which would only harbor the ISFG-3 TF binding site and compare transient transfections of constructs with solely AP1 TF and solely ISFG-3 TF, in an effort to
60 establish if indeed ISFG-3 plays a role as an inhibitor of transcription and thus gene expression.
Mutation of miR-155HG AP1 TF binding site: Promoter region in construct -117/+129 was predicted to have an AP1 TF binding site TGA C/G TCA, and thus mutation of this site was required to show a change/decrease in expression when the site is mutated, to suggest that AP1 TF is indeed the TF that drives optimal transcription of miR-155HG.
Published literature by Buttice et al. showed that for the AP1 TF binding site to be inhibited, specific nucleotides within the AP1 TF binding site TGA C/G TCA needed to be mutated. The authors showed that in 7 constructs, each with a sequential single base pair mutation, that the single base pair mutation of the second Thymine to a Guanine exhibited inhibition of AP1 TF binding in quadruplicate transfections with two separate
DNA samples. Thus, site-directed mutagenesis primers were engineered to mutate the second thymine in the predicted AP1 TF binding site and T was replaced with a G.
Transient transfections with construct designed to mutate AP1 TF binding site at TGA
C/G GCA revealed a statistically significant decrease in expression over the -117/+129 construct with a p-value of < 0.05 (Figure 7) suggesting that the AP1 TF binding site is of importance in the transcriptional regulation of this gene.
Transient Transfections of miR-155GG chicken promoter in HEK 293 T cells:
Interestingly, bioinformatics analysis on these TFs conserved across species revealed that
9 species had the AP1 TF binding site conserved within their core promoter region with 5 of these species (Human, Chimp, Chicken, Zebra Fish and Chinese Tree Shrew) having
100% identity of the AP1 TF binding site TGA G/C TCA. Of these, G. gallus, with its
100% identity in AP1 TF binding site as well as an appropriate TATA box, was chosen
61 for analysis (Figure 8). The promoter region of chicken miR-155GG was analyzed and a -
120/+114 region that harbored the AP1 TF binding site was isolated for amplification.
This construct was specifically designed to contain the predicted AP1 TF binding site and exclude all other predicted TF binding sites. Primers designed for this region failed to amplify, and thus, primers were redesigned to amplify the -169/+114 region of miR-
155GG and this was then cloned into an expression vector. Human miR-155HG construct
-117/+129 and chicken miR-155GG construct -169/+114 were then used for transient transfections into HEK 293T cells. Data revealed differential gene expression between -
117/+129 and -169/+114 versus our promoterless vector pGL3 Basic, with statistically significant higher gene expression among our miR-155 constructs and pGL2 Basic, giving p values < 0.05 (Figure 9).
Transient Transfections of human miR-155HG and miR-155GG chicken promoter in DF-1 Chicken Fibroblast cells:
To ascertain data on expression of chicken miR-155GG constructs in chicken cells, DF-1 chicken fibroblast cells were transiently transfected with human and chicken miR-155 constructs (Figure 10). Since human construct -117/+129 was the only construct that had exhibited statistically significant higher expression as compared to all other constructs, said construct was used along with chicken miR-155GG construct -169/+114 so that expression levels could also be compared between the two in addition to pGL3 Basic.
Transient transfections of human miR-155 construct -117/+129 and chicken miR-155 -
169/+129 revealed statistically significant higher expressions levels as compared to the pGL3 Basic promoterless vector, with p values < 0.05, and expression levels of human miR-155 construct and chicken miR-155 construct were comparable (Figure 10). In
62 addition, common patterns of gene expression can be observed between miR-155 constructs in HEK 293T cells as compared to DF-1 fibroblast cells, with both constructs,
-117/+129 and -169/+114 displaying statistically significant higher expression as compared to all other constructs that contain their various prospective TF binding sites, arguably confirming that not only are the regions of -117/+129 and -169/+114 indeed regions of miR-155’s core promoter region, but that they also quite possibly contain the predicted AP1 TF binding sites.
Mutation of miR-155GG AP1 TF binding site: Promoter region of chicken miR-
155GG construct -169/+114 was predicted to have an AP1 TF binding site TGA C/G
TCA, so as was with the human construct, mutation of this site was required to show a change/decrease in expression when the site is mutated, to suggest that AP1 TF is indeed present in the chicken’s promoter region and that it may then possibly play a role in the transcriptional regulation of this gene. Site-directed mutagenesis primers were engineered to mutate the second thymine in the predicted AP1 TF binding site and T was replaced with a G. Transient transfections with construct designed to mutate AP1 TF binding site at TGA C/G GCA revealed a statistically significant decrease in expression over the -
117/+129 construct with a p-value of < 0.05 (Figure 7) suggesting that the AP1 TF binding site is of importance in the transcriptional regulation of this gene.
Constructs chicken miR-155GG-AP1mut as well as human miR-155HG-AP1mut did indeed exhibit significant decreases in expression as compared to our miR-155 constructs that still contained the predicted AP1 TF binding sites, with p values < 0.05 (Figure 11).
Expression of miR-155HG-AP1mut and miR-155GG-AP1mut constructs in all three cell lines indicate statistically significant differences in expression from the constructs with
63 the AP1 TF and a statistically significant decrease in expression from the constructs with
AP1 TF binding site mutations with p-values < .05 (Figure 11).
Transient Transfections of miR-155HG and miR-155GG in NIH 3T3 cells: An MSA alignment indicated AP1 TF binding site was absent in Mus musculus, therefore, NIH
3T3 cells were used for additional transient transfections in order to observe binding, if any, of AP1 TF with our miR-155HG and miR-155GG constructs in a cell line that does not have the AP1 TF binding site with the promoter region of miR-155. Both human and chicken constructs were transiently transfected into NIH 3T3 mouse cells and data indicated statistically significant higher levels of expression between miR-155 constructs as compared to promoterless vector pGL3 Basic (data not shown).
Transient Transfections of miR-155HG and miR-155GG AP1mut constructs in NIH
3T3 cells: miR-155HGAP1mut an miR-155GGAP1mut constructs were transiently transected in NIH 3T3 cells along with human construct -117/+129 and chicken -
169/+114. Data indicated that our AP1-mut constructs had statistically significant lower levels of expression as compared to the constructs that had the predicted AP1 TF binding site, with p-values < 0.05. These data suggest AP1 TF binding site is essential for the transcription of human miR-155HG and that the binding site is located at -54 bp upstream of TSS. In addition, these data suggest that AP1 TF binding site is located at –52 bp upstream of the TSS in chicken miR-155GG. Studies on identification of transcription factor binding sites in promoter regions have shown that essential TFs driving transcription of genes are generally located within the -300 bp region upstream of TSS.
These data fall in line with the general consensus that TFs driving transcription are generally, yet not always, located in the approximate 300 bps upstream of the TSS. A
64 study in 1993 by T Matsusaka et. al identified NFkB as the TF driving transcription of the IL6 gene with the location of the TF at ~ 150 bps from the TSS. DNA foot-printing studies in HeLA cells conducted by Dynan and Tijan showed that the TF regulating transcription of the SV40 promoter, SP1, was found ~70-110 bps from TSS, yet a study in 2015 by Saunders et al. found that the TF driving transcription of the Slit 2 gene was located at -420 bps from the TSS, indicating that core promoter regions do not have uniformity amongst different genes, and thus identifying particular TFs driving transcription of a promoter does at times require for the entire promoter region of a gene to be analyzed, if one is to sufficiently and adequately identify the TF responsible for driving transcription of a gene.
AP1 TF is conserved in evolution in at least 9 species. Of the species that did not harbor the AP1 TF binding site, we suggest that evolutionary pressures, translocations and mutations could possibly have altered this binding site and thus it has been lost throughout time.
AP1: The Transcription Factor AP-1, located within the -117 upstream of the TSS. AP1 is encoded by the JUN gene, and functions to regulate several cellular processes including apoptosis, cell differentiation and proliferation, much like the regulation put forth by miR-155 (Ameyar, Wisniewska, & Weitzman, 2003). TF AP-1 is of the JUN family which comprises the c-FOS and b-JUN binds to the motif 5'-TGA C/G TCA-3' as well as p-Box 5’-TGAGTTCA-3’, yet with lower affinity (Knudsen 1993). Of the 21 species’ genomes found on NCBI that encode for miR-155, 11 species were found to have binding sites for TF AP1 which include 5’-TGA G/C TCA-3’ sites as well as p-box
65 5’-TGAGTTCA-3’ sites, suggesting the importance of the AP1 TF binding site and its regulation on this gene. Additional TFs contributing to the transcriptional regulation of this gene included NFkB, with a binding site of 5’ -CAGGAGGAAA-3’, with two species, Homo sapiens and Chimp, having the binding site within the promoter region of miR-155HG, as well as TF PU.1 with a binding site of 5’-TTCCTCTCTT-3’, with two species, Homo sapiens and Chimp, having conservation of PU.1 binding site.
AP1 TF has been found to regulate apoptosis and cell cycle regulation and proliferation with its regulation on numerous proteins of vital biological processing importance, such as Cyclin D, p21, FL1 and Fas (Shen et al., 2008). AP1 TF is an important TF in the regulation of apoptosis with regulation on proteins such as p53, FasL and Bc13. AP1 TF has also been shown to be the TF regulating transcription of important genes that help CD 4 T cells decide their fate. CD4 T cells can either differentiate into T helper cells, cells of our immune system that help combat infections from pathogens and other foreign molecules, or they can differentiate into Tregs that are regulator T cells that help with maintaining homeostasis in our immune system and prevent auto-immune disease. Interestingly, Tregs display the FOXP3 biomarker (Idris et al., 2015), a target of miR-155 stem-loop. FOXP3, is itself a TF that has been shown to play a role in the transcription of over 1,100 genes as well the regulation of T cell development (Young et al., 2007).
AP1 has also been found to play a role in the inhibition of follicular B cell differentiation. B cells are vital to our immune system in that they differentiate into plasma cells that harbor antibodies. When B cells are triggered to proliferate due to an immune system response, AP1 has been shown to become up-regulated resulting in
66 activation triggered apoptosis to regulate immune system over response (Grotsch et al.,
2014).
Model testing and Tree Construction: miR-155HG Promoter Region:
MiR-155HG promoter region was aligned in MEGA along with an additional 19 miR-
155 sequences across species to observe conservation, if any, of promoter regions and TF binding sites. To visually observe conservation, MEGA software was used to generate model test results for use in building phylogenic trees as well as distance matrices. Over time, certain species have had insertions or deletions in their DNA sequences, and these changes can be observed when manually attempting to align the sequences against each other. MEGA dataset alignment is shuffled and trees are generated until a positive score is achieved by the algorithm. Bootstrap values are considered “confident” when greater than 70%. For miR-155’s promoter region, a -480 bp region was used for analysis across species and sequences for all 20 species were aligned in MEGA software for analysis.
A model test was performed on all twenty sequences across species for miR-155
Promoter region and model testing output results were that the best-fit model for the -480 bp upstream of TSS for each species was a Jukes Cantor. The Jukes Cantor method, the method selected for our best fit for miR-155HG promoter, is based on the assumption that in a DNA sequence, all four nucleotides A,C, T,G all occur at the same equal frequency. This then infers that all four nucleotides would have equal rates of substitution as well. Jukes Cantor maximum likelihood tree indicated a 97 bootstrap confidence level between human and chimp, the sequence alignment did not account for the 100% identity
67 in AP1 TF conservation among the 5 species due to the high variability spanning the length of the -480 region of miR-155’s promoter.
Model testing and Tree Construction: miR-155 Stem-loop:
For our stem-loop product, MSA of our twenty-seven sequences was performed using
MEGA software. A model test was performed on all twenty-seven sequences across species for miR-155 and or results indicated that the best model to use was T92+G+I.
This indicates that the best evolution model to use is the Tamura 3-parameter. Our “G” values are stated as .29. Our parameters for our model tree’s boot strapping were set at
1000. The Maximum Likelihood tree for miR-155’s stem-loop is consistent with what we would expect to find in the clustering of organisms, such as the primates. Distance matrices, substitution models and phylogeny databases were used to analyze evolutionary history, mutations, substitutions, transversions and transitions of miR-155 across species
(data not shown).
Stem loop MSAs for phylogenetic analysis were more prudent for the stem-loop product of miR-155HG in comparison to miR-155’s promoter region, simply due to the fact that the length of the stem loops are immensely shorter. MiR-155’s stem loop sequence is less than 70 bps, which allows for an easier alignment among species as compared to the initial 1,000 bp or subsequent even shorter 480 bps of the promoter region alignments. Stem loop alignments illustrated high conservation among 27 species, and interestingly, sea squirt was the only species among the 27 to have an additional
68 segment of DNA within its stem loop sequence, suggesting a possible segment that may have been lost throughout evolution.
Our data suggests that AP1 is the TF driving transcription of this gene, and that the evolutionarily conserved miR-155 stem-loop product is posing post-transcriptional regulation of 388 target mRNAs (data not shown). Analysis of conservation is vital in the study of microRNAs. MicroRNAs do not perfectly base pair with their intended targets, enabling them to straddle numerous mRNAs as targets. These conserved regions thus allow researchers to study the mechanism of targeting by miR-155 across species since conservation amongst species, as we have demonstrated, is high.
MiR-155 has been associated with several types of cancers, including aggressive lymphomas. Studying the mechanism in which this gene is regulated and dysregulated will assist in targeting of regulatory elements to be used as tools for therapies.
Post-transcriptional regulation plays a dynamic role in gene expression and any modification in expression levels of miRs can have significant consequences. As modifiers of gene expression, any elevated or down-regulated levels of expression of miR-155 could affect the production of mRNAs, most notably mRNAs that code for either proteins involved in the apoptotic process and regulation and mRNAs that code for tumor suppressors.
Limitations of this study can contribute to future direction, in that these data can be used to further build upon. Although these data highly suggest that AP1 is located at the predicted binding site, a chromatin immune precipitation assay would heighten the confidence level of our findings. ChIP assays are designed to display interactions
69 between DNA and proteins, in this case, the predicted segment of DNA that AP1 TF binds to, and the AP1 TF protein. These data can then be utilized to then move forward and possibly collect data on transient transfections of B-cells, and preferably, SLL and
MCL cells.
Here we have identified a vital and evolutionarily conserved TF driving transcription of miR-155HG. Our study will provide new insight for how the regulation of lymphoma-associated gene is controlled, and may increase the knowledge of how gene expression of miRs is controlled in general. Enhanced understanding from our studies should provide information for why certain cancers are very aggressive and others are less aggressive, and therefore have a higher long-term survival rate. Identification of the proteins involved in driving optimal transcription of a gene and how it is expressed will allow for knowledge into such mechanisms and allow for greater understanding of diseases which are brought about due to dysregulation of such mechanisms and proteins involved.
MicroRNAs play a vital role in gene regulation, in that they post-transcriptionally regulate gene expression by binding to the 3’ UTRs of target mRNAs resulting in degradation of mRNA and inhibition of translation. MiR-155 is one of the most notable of miRs to emerge due to its association in the dysregulation in cancer. We have shown the transcriptional regulation of miR-155HG and the post-transcriptional modifications its product miR-155 bestows upon its targets to inhibit translation. Analysis of evolutionary conservation of miR-55 is potentially transformative in that it will permit us to understand regulation, expression and targeting of miR-155 and contribute further to the knowledge into this vital and recent line of study into MicroRNAs. Given that miRs
70 pose such a great effect on the translation of mRNA, it could be argued that although
TFs, as we have shown, play a role in the regulation of gene expression, miRs are truly the more powerful molecules that regulate gene expression.
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