Cultivation of Intestinal Organoids for further Stem Cell Research
By: Karina Gaardahl, Julie Eleonore Nytoft, Mariam Labrouzi, Fatima Taleb, Josephine Falkenstrøm and Nicholas Rayner Supervised by: Jesper T. Troelsen Roskilde University 5th Semester, Autumn 2016 Medicinal Biology, Bachelor in Natural Sciences
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Abstract
Throughout the years, research about how stem cells from intestines can recreate a 3- dimensional organ in vitro has been progressively developing. The organoid model system allows intestinal stem cells to self-organize, through the process of acquiring tissues of the original organ. The organoid model system has been developed to help research on diseases for toxicology and regenerative medicine. This project investigated the different developmental stages of the intestinal system as well as the assessment of the organoid model as a simulation of an in vivo intestinal system. Through the use of cDNA synthesis and qPCR, results showed signs of upregulation for the genetic markers Muc2, Defa6, Lct, Alpi and Ki67, in the course of approximately two weeks. With regards to the genetic markers Gfi1b, Pyy and Gip, results showed that there was a low expression, which can be correlated to the low amount of the two cell types, enteroendocrine and tuft cells. Through the analysis of provided EM images of intestinal organoids, the presence of goblet, enteroendocrine, enterocytes, proliferating and paneth cells was established. The organoid model may be assessed to be a viable model for the in vivo mice intestines, however the trials are still in the early stages and further testing is required. This conclusion is based on the evident results, with regards to the different cell developmental stages and differentiation in the organoid system. The model is accessible and may be easily applicable as a therapeutic, diagnostic and experimental tool.
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Table of Contents Abstract ...... 2 Table of Contents ...... 3 1. Introduction ...... 5 2. Background ...... 6 2.1. A Healthy Intestinal System ...... 6 2.2. Small intestinal signalling pathways in epithelial cells ...... 10 2.3. Types of Cells in the Small Intestine ...... 14 2.3.1. Enterocytes ...... 14 2.3.2. Enteroendocrine cells ...... 15 2.3.3. Proliferating cells ...... 15 2.3.4. Goblet Cells ...... 16 2.3.5. Paneth Cells ...... 17 2.3.6. Tuft cells ...... 18 2.3.7. Lgr5+ Stem Cells ...... 19 2.4. Theory Behind the Methods ...... 22 2.4.1. Genetic Markers for Cell Types ...... 22 2.4.2. The Organoid Model ...... 25 3. Methods ...... 32 3.1. The Preparation of Crypt Solution ...... 32 3.1.1. Isolation of Mouse Intestinal Crypts ...... 32 3.1.2. Intestinal Organoid Culture ...... 33 3.1.3. Passaging of Mouse Intestinal Organoids ...... 33 3.2. Fixation ...... 34 3.3. RNA Purification ...... 35 3.3.1. Disruption and Lysis of Organoid Cells...... 35 3.3.2. Filtration ...... 35 3.3.3. RNA Binding ...... 35 3.3.4. DNA Digestion ...... 36 3.3.5. Washing ...... 36 3.3.6. Eluting Pure RNA ...... 36 3.4. cDNA Synthesis ...... 37 3.5. qPCR: Primertest ...... 37 3.6. qPCR: Programmed Cycle Run for qPCR ...... 37 3.7. Double Delta Ct Calculations for Analysis of Fold Change ...... 38
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4. Results ...... 40 4.1 Significant Dissociation and Amplification Curves ...... 44 4.1.1. Muc2 ...... 44 4.1.2. Alpi ...... 44 4.2 qPCR Results ...... 45 4.2.1 Enterocytes ...... 45 4.2.2. Enteroendocrine Cells ...... 49 4.2.3 Proliferating Cells ...... 52 4.2.4. Goblet Cells ...... 54 4.2.5. Paneth Cells ...... 57 4.2.6. Tuft Cells ...... 59 5. Analysis of Electron Microscopy Images ...... 61 5.1. EM Images Day 2 ...... 61 5.2. EM Images Day 5 ...... 62 5.3. EM Images from Day 10 ...... 66 6. Discussion ...... 67 6.1. Reference Genes ...... 67 6.2. Significant Dissociation and Amplification Curves ...... 68 6.3. Enterocytes ...... 69 6.4. Enteroendocrine Cells ...... 69 6.5. Proliferating Cells ...... 71 6.6. Goblet Cells ...... 71 6.7. Paneth Cells ...... 72 6.8. Tuft Cells ...... 73 7. Conclusion ...... 75 8. Errors and Limitations ...... 76 9. Future Perspectives ...... 77 10. Acknowledgements ...... 77 11. Reference List ...... 78
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1. Introduction
Throughout the years, research about how stem cells from organs can recreate a 3-dimensional organ in vitro has been progressively developing. The organoid model system allows intestinal stem cells to self-organize into organoids, through the process of acquiring the tissues of the original organ.
The organoid model system has been developed to help research on diseases for toxicology and regenerative medicine. Diseases such as inflammatory bowel disease (IBD) and gastrointestinal (GI) cancers have an extremely high mortality rate, due to the lack of effective drug treatments (Fangkun et al., 2016). Several studies have been made to optimize this field of medicine by using 2-dimensional monocultures, however this model system fails to mimic cellular functions that exist in tissues (Fangkun et al., 2016). Due to the 3D organoid model system, organoids can maintain their in vivo characteristics without significant genetic or physiological changes. This can help further development of drug screening, organ transplantation and gene therapy.
This project will investigate whether different developmental stages exist in the intestinal system, and whether they are represented in the organoid model. This model allows for simulation of intestinal tissues represented by different intestinal cell types. This involves using several laboratory methods, such as isolating the mouse intestinal crypts to prepare the cells for cultivation and later using RNA purification, which allows for total RNA and DNA extraction from the cultured organoids. However, to simulate the organoid developmental stages, by looking at differential intestinal cell types, a qPCR (quantitative polymerase chain reaction) test was used. This method detects a specific DNA sequence in a sample and determines the amplification of targeted DNA using specific primers found in the different intestinal cell types.
Aim
The aim of this project is to examine whether different developmental stages in the intestinal system exist and whether they are represented in the organoid model
system.
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2. Background
2.1. A Healthy Intestinal System
The main function of the small intestine, is to absorb and digest nutrients coming from the stomach. The small intestine is split up into three segments: the duodenum, the jejunum and the ileum. In the first segment, the duodenum, the nutrients are digested by enzymes from the pancreas, acidic salt from the gallbladder and bile from the liver. Most of the digestion takes place in this segment of the small intestine.
After passing through the duodenum, the nutrients reach the jejunum, where it is either chemically digested or absorbed through the epithelial mucosa layer into the bloodstream. After the digestion in both the duodenum and jejunum, the nutrients can be absorbed in the ileum. The ileum is the longest of the three segments to maximize the absorption.
Digestion of the many different types of molecules which are to be absorbed in the small intestine, differ independently. The digestion of protein primarily takes place in the stomach by pepsin. Furthermore, the peptides are digested by trypsin and chymotrypsin in the small intestine which then can be absorbed, if the fragments are small enough. If the fragments still are too big, carboxypeptidase and aminopeptidase can further digest them. Carbohydrates are digested by amylase, which primarily happens in the mouth, though ~95% of starch is digested in the small intestine by pancreatic amylase. Triglycerides are digested by lipase coming from the pancreas. Triglycerides are broken down to one monoglyceride and two fatty acids. Because fat is water insoluble, the fats accumulate to larger fat droplets. In order for lipase to quickly digest the droplets, they need to be broken down to smaller parts to increase surface area, through a process called emulsification. After emulsification, droplets are further processed by bile salts from the liver to form micelles. Micelles are said to be a holding station for free fatty acids which are insoluble in water. The micelles can slowly release the fatty acids in to the epithelium membranes, where they are formed back to triglycerides in the smooth endoplasmic reticulum (ER) of the cells. Vitamins A, D, E and K are fat-soluble and follow the same pathway as used for absorption of triglycerides. Water-soluble vitamins are absorbed by diffusion or mediated transport. There is one exception for water soluble vitamins such as B12, which is a very large molecule. This vitamin must therefore bind to the protein intrinsic factor.
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The protein-bound B12 binds to a specific site on the epithelial cells in the lower part of the ileum. Here the B12 vitamin can be absorbed by endocytosis. It is believed that every day approximately 1500 mL of fluids is secreted from the bloodstream into the lumen of the small intestine. This happens by osmotic effect, which is acquired by transportation of mineral ions such as Na+, Cl- and HCO3-, from the intestinal epithalamium, into the lumen. Hereafter, the nutrients can be absorbed into the bloodstream by potassium ion transport, or nutrient co- transportation. Absorption of nutrients and ions results in reversion of the osmotic effect. While secreting the mineral ions, mucus is secreted.
For the small intestine to function properly, it is crucial to keep a tight regulation of secretion of digestive substances. If there is an irregularity in the homeostasis, it can lead to ulcers and inflammation. The mucus in the intestine is therefore critical for its function. The mucus is secreted from the goblet cells, and has the main function to constitute a barrier between harmful substances, and the epithelial cells. Without the mucus, digestive substances secreted to duodenum would digest the gastrointestinal tract, and pepsin from the stomach would digest the duodenum allowing ions and bacteria to move into the extracellular matrix between cells by degradation of the tight junctions.
Throughout the past decades, it has become increasingly evident that human diseases are often related to lifestyle. Reduced physical activity and the general consumption of processed foods has had severe effects on our resistance to different diseases. Research has shown that our genetic adaptations suffer under the changes in lifestyles in particularly our dietary habits during the past 100 years. (Eaton and Konner, 1985)
Many individuals of today’s society are predisposed to inflammatory, infectious, degenerative and ulcerative diseases. These predispositions can be linked to the increase in e.g. sugar consumption, the tenfold increase in sodium consumption; the fourfold increase in consumption of saturated fat and the general reduced consumption of fibres and minerals. (Bengmark, 1998; Rockey and Cello, 1993)
Prehistoric foods contained several thousand times more bacteria, particularly probiotic bacteria which we are no longer exposed to. The identification of microbes and bacteria were often linked and regarded sources of diseases and it is not until recently, that there has been an increase in the understanding of the essentiality of microflora and bacteria. The gastrointestinal tract constitutes the second largest body surface area and has been described to be somewhere
Page 7 of 81 between 250 and 400 m2 (Bengmark, 1998). Within a human lifetime, 60 tons of food (Bengmark, 1998) is passed through this canal, which constitutes an enormous threat to the digestive tract and the body as a whole. Many speculate that this may be why this organ is often affected by cancer and inflammatory diseases (Sanderson and Walker, 1993).
Due to the essential functions and challenges faced by the gastrointestinal tract, many gastrointestinal cells have a rapid turnover where most cells are replaced after three to four days (Bengmark 1998; CREAMER, SHORTER, and BAMFORTH 1961). Besides a rapid replacement of cells, secretory mechanisms help lubricate the mucosal lining and intraluminal microbial defence systems. These secretory systems are highly sensitive to foreign chemicals and once again, the modern lifestyle is taking its toll on the intestinal system. About 50% of the 2000 pharmaceutical drugs registered in Sweden have reported gastrointestinal side effects such as vomiting, diarrhoea, and obstipation (Bengmark 1998).
Through evolutionary adaptations, mammals have developed symbiotic relationships with different bacterial flora colonizing the gastrointestinal tract. It has been estimated that there are approximately 300-500 (Uhlig et al. 2003) different species of bacteria that interfere with the cells in the mucosal immune system (Hooper and Gordon 2001; Uhlig et al. 2003). These symbionts play key roles and have essential effects on immune function, processing nutrients as well as a broad range of other host activities. (Hooper and Gordon 2001)
Some of the major functions of the gut microflora include metabolic activities that result in salvage of energy and absorbable nutrients, important trophic effects on intestinal epithelia and the protection of the colonised host against invasion by pathogenic microbes (Guarner and Malagelada, 2003). The microbiotic environment is also an essential factor in terms of different pathological disorders such as colon cancer, inflammatory bowel disease and organ failures. However, the gastrointestinal bacteria are useful with regards to human health; particularly, probiotics and prebiotics are known to play key roles in the prevention of certain diseases. (Guarner and Malagelada 2003; Uhlig et al. 2003)
Probiotic bacteria are capable of controlling various enteric pathogens such as Salmonella typhimurium (Perdigon et al. 1990), Shigella (Nakaya, 1984) and Escherichia coli (Juven, Meinersmann, and Stern, 1991). They may also provide important protection against urogenital pathogens such as Gardnerella vaginalis, Candida albicans, and Chlamydia trachomatis
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(Klebanoff et al., 1991; Hillier et al., 1992). It is therefore expected that probiotic bacteria can be effective weapons within the prevention and treatment of microbial infections.
Since the mucosal immune system requires restriction of the immune response towards non- pathogenic bacteria but effective defence mechanisms towards potential pathogenic substances, it requires a highly regulated system (Mowat, 2003).
The gastrointestinal tract provides specific and distinct niches for colonization of bacteria (Fig. 1) which distributes bacterial flora based on quantitative and functional differences (Jiang, Bos, and Cebra 2001; Zoetendal et al. 2002). These structures and distributions contribute to the functional role in digestion and host defence mechanisms. There are distinct differences in the epithelial intestinal architecture as well as the density of cells associated with adaptive immune response (Uhlig et al. 2003). Examples of these cells are goblet producing cells, dendritic cells, Paneth cells, and T-lymphocytes.
Figure 1 – Different niche compartments of the gastrointestinal tract are occupied by bacteria which is illustrated in the figure above. The figure illustrates how adaptations of the different intestinal bacteria have led to colonisations in different ecological niches. As one moves through the lower gastrointestinal tract, the total bacteria load increases whereas distinct bacteria mainly colonize niches in the small intestine. Original magnification of the micrographs is ×200. (Uhlig et al. 2003)
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2.2. Small intestinal signalling pathways in epithelial cells
The gastrointestinal tract is frequently challenged by pathogens and antigens that arrive from human diet. Therefore, the intestinal epithelium, which is a single cell layer, must be capable of preventing tissue damage that can lead to a number of immune-mediated diseases, such as inflammatory bowel disease, food allergy and celiac disease (Vieira et al. 2013). The epithelial cells function as a protective barrier against external environment, and the cells support water and nutrient transport. Several types of cells can be found in the intestinal epithelium such as enterocytes, goblet cells, enteroendocrine cells, tuft cells and Paneth cells (Vieira et al. 2013) In order to maintain the morphological and functional features of the different epithelial cell types, and most importantly the regulation of intestinal epithelial cell polarity and homeostasis, various molecular pathways are involved in the process. Examples of such processes involve the Wnt, transforming growth factor-β (TGF-β)/bone morphogenetic protein (BMP), Hippo, Hedgehog and Notch pathway. More importantly, several studies about the organoid model system, has shown that the signalling pathways that are mentioned above, are responsible for organoid formation and are identical to those used during in vivo organ development, apoptosis and homeostasis (Hynds and Giangreco 2013).
Figure 2 –The molecular regulatory pathways in intestinal epithelial homeostasis. It further shows how the Wnt signalling pathway promotes the proliferation of stem cells and Paneth cell maturation. The Notch signalling aids the Wnt signalling to drive proliferation of intestinal stem cells and the regulation of undifferentiated stem cells (Vieira et al. 2013).
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Wnt/β-catenin signalling pathway
The Wnt (wingless-related integration site) is a family of different signal transducing glycoproteins acting as ligands that either send signal paracrine or autocrine, and it has various roles during intestinal homeostasis. The Wnt signalling pathway operates through the transcription co-activator β-catenin. The Wnt protein ligands bind to a G-coupled Frizzled receptor and its co-receptor either LRP6 or LRP5 (a low-density lipoprotein). This activates the transcriptional β-catenin pathway that is a key factor for controlling developmental gene expression. This process then induces a series of intracellular steps, a signalling cascade, and in the end, a response will occur changing one of a number of things: cell proliferation, apoptosis, differentiation, cell polarity, tissue homeostasis and determination of embryonic development. (Vieira et al. 2005; MacDonald, 2010)
The Wnt/β-catenin signalling pathway has three different branches of pathways that each has a function: Wnt: 3 different pathways (Rao and Kühl, 2010)
1. The canonical Wnt pathway: regulation of gene transcription, which activates target genes in the nucleus. 2. The non-canonical planar cell polarity pathway: regulation of cytoskeleton. The regulation of cytoskeleton happens when β-catenin interacts with the proteins cadherins, which is regulated by phosphorylation. 3. The non-canonical Wnt/calcium pathway: regulation of amount of calcium inside the cells. This process is dependent on G proteins.
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Figure 3 - Canonical and Non-canonical Wnt pathways (Hitt 2013). Canonical: involves the β-catenin accumulation for cell-cell attachment and gene transcription (transcriptional induction). (Rao and Kühl 2010)
Notch signalling pathway
The Notch signalling pathway regulates the cell fate decisions of proliferated cells in development and in adult life alongside the Wnt signalling (Koo and Clevers, 2014) and also negatively regulates differentiation in the secretory lineages (Jeon, 2013). The signalling occurs when the transmembrane Notch receptor is bound by ligands expressed on adjacent cells, and this results in cleavages of the receptor by y-secretase enzyme complex, where the intracellular cytoplasmic domain (NICD) of the receptor is then translocated to the nucleus and the NICD binds to a DNA-binding protein called CSL (transcription factor). This activates the Notch- responsive genes, such as Hes-1, Hes-3 and Hes-5 (Koo and Clevers, 2014; Vieira et al., 2005). These genes are vital for the differentiation of absorptive cells (enterocytes), and are expressed in proliferating crypt cells (Vieira et al., 2013; Koo & Clevers, 2014).
An example of how Notch signalling pathway controls cell fate is to look at one of the Notch genes Hes-1. The transcription factor MATH-1 is a downstream target of Hes-1 in the intestine, and its activity leads to the generation of secretory cell lineages (Vieira et al., 2013). Other transcription factors in the Notch signalling pathway, such as Gfi-1 and neurogenin-3 (Ngn-3), compete for the selection of enteroendocrine versus goblet or Paneth cell fates (Vieira et al., 2013).
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Hedgehog signalling pathway
The Hedgehog signalling pathway is important for normal embryonic development, adult tissue maintenance, renewal, and regeneration of tissue. The hedgehog signalling is activated by binding to the hedgehog ligands to the patched homolog 1 receptor (Ptch 1). When the ligands are absent the Ptch1 decreases the activity of Smo (Smoothened) protein, however when the hedgehog binding inactivates Ptch1, the SMO inhibition is released resulting in the translocation of members of the GLI family of Zn-finger transcription factors from the cytoplasm to the nucleus (Vieira et al., 2013).
Hippo signalling pathway
The main function of the Hippo signalling pathway is to control organ size by inhibiting cell proliferation and apoptosis in response to cell-cell contact (Vieira et al., 2013). The Hippo pathway plays a vital role in regulating the intestinal regeneration and tumorigenesis (Jeon et al., 2013).
The hippo signalling pathways is activated when downstream effector YAP (Yes-associated protein) and TAZ is phosphorylated by the LAT1/2 kinases where the phosphorylated YAP/TAZ will remain in the cytoplasm. When they are dephosphorylated the YAP/TAZ is translocated into the nucleus and binds to transcription factors, such as TEAD1-4, which inhibits the proliferative and anti-apoptotic function (Jeon et al., 2013).
(TGF-β)/(BMP) signalling pathway
TGF-β (transforming growth factor) signalling pathway is a family of several cytokines (Vieira et al., 2013). They regulate embryonic development, proliferation, repair of injury and cell differentiation (Vieira et al., 2013). The TGF-β signalling is activated by ligand binding to serine/threonine kinase receptors, which leads to the phosphorylation of the cytoplasmic signalling molecules Smad2 and Smad3, where they are then translocated to the nucleus (Vieira et al., 2013). The Smad proteins then interacts with transcription factors, resulting in target gene expression. The TGF-β signalling components are expressed in the differentiated compartment of the intestine. BMP (bone morphogenetic protein) signalling can block the formation of ectopic crypts, and in order for proliferation to continue the expression of BMP in the crypts will prevent the activity of BMP (Vieira et al., 2013).
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2.3. Types of Cells in the Small Intestine
2.3.1. Enterocytes
When the organism is in the absorptive stage, food is available in the intestinal lumen and the enterocytes (also called absorptive cells) are responsible for the uptake of nutrients and other substances. (Widmaier, Raff, and Strang, 2016). The vitality of the enterocytes, explains why the cell type makes up 90% of all cells found in the intestine (Umar, 2010).
The cell type is mostly found in the small intestine, since they must take up the important substances, such as: water, ions, sugars, etc. before the food reaches the colon. During the absorptive stage, the body’s energy requirement is met by the nutrients taken up by the enterocytes, which are then processed into smaller molecules and enter the bloodstream as simple monomers. From the bloodstream, the nutrients can reach all the cells in the body that require energy at a given time. (Widmaier, Raff, and Strang, 2016)
The enterocytes are very strategically placed, closest to the lumen forming the brush border with their apical membranes, so that they can come in direct contact with all the nutrients in the lumen. They are tightly packed and show large amounts of microvilli on the surface, which increases their surface area and simultaneously decreases the distance that the nutrients have to travel across, when entering the cells. (Crawley, Mooseker, and Tyska, 2014)
On figure 4 it is observed how the enterocytes are lined up closely next to each other, with tight junctions ensuring that nothing from the lumen accidently slips through to the blood stream. It can be further observe how the basolateral membrane is so close to the blood stream, from which the enterocytes can supply the blood with the water and nutrients needed in the rest of the body. The blood’s capacity of reaching all remote corners of the body is so extensive that it is capable of supplying Figure 4 - Intestinal enterocyte’s connection to blood stream and their organization: tight junctions, apical membrane and basolateral membrane (Pearson Education Inc. 2011).
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2.3.2. Enteroendocrine cells
Enteroendocrine cells make up <1% of the epithelial cell population, arranged as singular cells interspersed between non-endocrine cells throughout the intestinal tract (Buffa et al., 1978). This cell type consists of cells each responsible for carrying out a certain function, which are as follows: K cell, L cell, I cell, G cell, enterochromaffin cell, N cell and S cell. They produce gastrointestinal hormones or peptides in response to diverse stimuli. The hormones secreted from each specific cell subtype are the following: somatostatin, motilin, cholecystokinin, neurotensin, vasoactive intestinal peptide and enteroglucagon. These hormones may act as general messengers or may be transmitted to the nervous system activating nervous responses.
2.3.3. Proliferating cells
Proliferating cells can replace cells that have been lost due to injury or cell death, and are important for maintaining development as well as normal tissue homeostasis (BD Biosciences, 2015). They are also required for embryogenesis, tumorigenesis, growth and the proper function of adult tissue (DeBerardinis et al. 2008). Cell proliferation is defined by the expansion of cells as a result of cell growth and cell division. To maintain a number of cells in adult tissues and organs, proliferated cells must be balanced between the continuous divisions of single cells into two daughter cells, and cell loss through apoptosis (Cooper, 2000). Apoptosis is programmed cell death, and it is a process in which damaged and an overload of cells in the body are permanently removed. It is an ongoing process that helps maintain the balance between the continuous production of cells and cell death, to control the appropriate number of cells required for tissue homeostasis (Cooper, 2000).
There are two types of proliferated cells, the controlled and uncontrolled proliferation. The controlled cell proliferation is mentioned above and undergo cell growth normally. However, the uncontrolled proliferated cells are a hallmark of cancer. This happens when multiple mutations gather in somatic cells and removes various control mechanisms, which would normally prevent cancer cells from dividing unchecked (Cooper, 2000). This is why cell proliferation is dependent on apoptosis as it would have eliminated the cancer cells in the body.
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For growth of cells to take place, cell proliferation requires nutrients, energy and biosynthetic activity to duplicate all macromolecular components (DeBerardinis et al,. 2008). This process is regulated by the cell cycle, which is divided into three different stages to undergo division of cells. Proliferated cells are usually controlled during the first stage of interphase, which is called G1 phase and is mainly responsible for cell growth (DeBerardinis et al., 2008). Each passage through the cell cycle yields to daughter cells, and this requires a great amount of biomass (proteins, lipids and nucleic acids). In order for cells to proliferate, they have to take up an excessive amount of nutrients that guides the metabolites into pathways that is a platform for biosynthesis (DeBerardinis et al., 2008). Signals that stimulates cell proliferation also participates in the metabolic activity, which allows cells in the G0 phase (the resting phase in the cell cycle in which cells have stopped dividing) to begin to proliferate (DeBerardinis et al., 2008).
2.3.4. Goblet Cells
Throughout the length of the small and large intestine, the gastrointestinal epithelium is covered by a protective mucus gel composed of mucin glyco-proteins that are synthesized and secreted by goblet cells (Deplancke and Gaskins, 2001; Specian and Oliver, 1991). This mucus layer not only acts as a protective barrier against bacteria but also functions as lubrication and transport medium between the lumen and cells in the epithelial lining. The secretion of mucus takes place through two processes: Baseline secretion and Compound exocytosis. Baseline secretion which is also referred to as simple exocytosis, involves the release of newly synthesized mucin granules that move along the periphery of the apical granule mass. Compound exocytosis involves the accelerated secretory event, triggered by a mucin secretagogue1 causing direct release of stored mucin granules. Initially, the mucus found within the granules, are in a condensed state but when it is secreted, the mucus expands. The colon has a two-layered mucus with an inner mucus layer that is 50-200 μm thick and firmly attached to the epithelium. The outer mucus layer is easily Figure 5 - Internal structures of a Goblet Cell - Illustration from Anatomy & Physiology,Connexions
1 a substance that promotes secretion
Page 16 of 81 removed and has a less defined outer border. (Deplancke and Gaskins, 2001; Hansson, 2012).
The structural composition of goblet cells, is based on a columnar shape, having a height of four times that of their width. The cytoplasm is usually located towards the basal end of the cell body whereas the mucin granules usually accumulate near the apical surface of the cell (see Fig. 6). This gives the basal part of the cell a basophilic2 property because of nucleic acids within the nucleus. The apical plasma membrane of the goblet cell, is covered by microvilli in order to increase surface area for secretion. (Freeman, 1966)
Changes in goblet cell functions and the chemical composition of intestinal mucus can be caused by changes in the natural microbiota otherwise found in this region. Research has shown that cell dynamics and the mucus layer itself, are affected by intestinal microbes both through local release of bioactive factors or indirectly via activation of host immune cells (Deplancke and Gaskins, 2001). The secretion of mucins through the process of exocytosis, can be induced or inhibited by compounds such as hormones, inflammatory mediators such as cytokines and lipids as well as bioactive factors. These disruptive compounds may lead to pathological conditions such as chronic inflammatory diseases. (Cornick, Tawiah, and Chadee, 2015)
2.3.5. Paneth Cells
Paneth cells are placed in the small intestinal crypts of lieberkûhn, with an average of 5-12 paneth cells in each small intestinal crypt. Paneth cells are developed in the gestational age of 13.5 weeks in humans. They can live up to 20 days, which compared to other small intestinal cells is more extensive. Their characteristic feature is the granules which are visible in both fresh and fixed state. The granules are located in the upper part of the cell (Hally, 1958).
The Paneth cell is an exocrine cell and it releases granules to the lumen during digestion. The Paneth cells are also important in protection of nearby stem cells, because of their numerous prominent granules. The paneth cell’s granules can, upon cell stimulation, be released into the crypt lumen. This process is initiated, when the receptors are exposed to gram negative and gram positive bacteria or their products. The Paneth cells do not respond to fungi or protozoa. The granules called alpha-defensins consist of several proteins and peptides, including lysozyme, alpha-defensins and sPLA2. Paneth cells release their granules resulting in increased
2 base loving
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2.3.6. Tuft cells
In the intestinal epithelium, there are four overall important types of cells: enterocytes, endocrine, goblet and Paneth cells. However, in the latest years a fifth cell, the tuft cell, has been shown to be of great importance to the intestinal function which comprises 0.4% of epithelial cells (Gerbe, Legraverend, and Jay, 2012). Even though the cell type has been known to exist for many years, limited information has been discovered about their function, up until the last couple of years.
Figure 6 and Figure 7- The differentiation of small intestinal epithelial cells throughout the crypt, starting with Lgr5+ stem cells (Sato et al., 2013).
The tuft cell is not only found in the colonic and small intestinal epithelium, but throughout the whole gastrointestinal tract, as well as the airways (Westphalen et al., 2014). The cell type can have different functions depending on where it resides and is also named differently. For example when found in the airway they are known as brush cells (Westphalen et al., 2014). This project will be focusing on the small intestinal/colonic tuft cells, their differentiation from the other important intestinal cells and their importance for the intestine function. The structure is made up of many microvilli that give them a big surface area facing outwards, towards the intestinal lumen (Gerbe, et.al., 2012). Further, they are equipped with tubulovesicular
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‘’[…] “tuft” cells, […] referring to epithelial cells endowed with a unique tubulovesicular system and apical bundle of microfilaments connected to a tuft of long and thick microvilli protruding into the lumen.’’(Gerbe, Legraverend, and Jay 2012)
Out of the five different intestinal cell types, tuft cells are the only ones known to produce cyclooxygenase enzymes (COX), which is especially important in the body’s ability to induce inflammation and a sensation of pain, by producing prostaglandins, etc. (Gerbe et al., 2011). This means that the tuft cells are the only cells in the colon that induce a process to make the body aware of when it is in a state of disease and has to induce an immune response. Westphalen, et.al. established, based on previous research by Jay, et.al., that the tuft cells are dependent upon the expression of the ATHO1 transcription factor. Since the ATHO1 transcription factor is usually found to be of vital importance to intestinal secretory cells such as goblet, Paneth and endocrine cells, this would indicate that the tuft cells are of secretory cell lineage. (Westphalen et al. 2014)
One of the substance types that tuft cells are known to, not only produce, but also secrete into the lumen of the intestine, is opioids (Gerbe, Legraverend, and Jay, 2012). Opioids are the name of a class of substances resembling opium which induces pain relief and can stop diarrhoea. (Nih, 2014) The later ability being of great importance in the colon, in order for the body not to go into severe dehydration.
2.3.7. Lgr5+ Stem Cells
The Leucin-rich repeat-containing G-protein coupled receptor 5+ (Lgr5+) pluripotent stem cells are found at the very bottom of the intestinal crypts, wedged between the Paneth cells (Barker et al., 2007). The Lgr5+ stem cells differentiate into Transit amplifying (TA) daughter cells or cycle back to Lgr5+ stem cells. The TA daughter cells can either, rapidly amplify up through the villus, and shed off at the tip, as enteroendocrine cells, tuft cells, goblet cells or enterocytes (Sato et al., 2013) or move to the crypts bottom as Paneth cells. The TA daughter cells will differentiate in one of two linage directions, the secretory linage consisting of the enteroendocrine cells and goblet cells, or the enterocyte linage which are the absorptive cells
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(see Fig. 8 right) (Radtke and Clevers, 2005), Paneth cells move down in the crypts and constitute the Lgr5+ niche. TA daughter cells have a limited self-renewal capacity. After about 3-4 division, the offspring daughter cells will differentiate into mature linage cells. The Lgr5+ stem cells has been shown to have a division rate average of one day cycling time (Barker et al., 2007).
Figure 8 – The figure to the left shows the structure of the small intestine with villus and crypt. The figure to the right shows the stem cell differentiation, and the two branches the transit amplifying cells can take, making up the secretory and enterocyte linages (Radtke & Clevers, 2005)
There has been found two types of stem cells in the small intestinal crypts, the cyclic Lgr5+ also called Lgr5 crypts base columnar cells, and +4 stem cells, which are placed at the +4 cell position from the bottom of the crypt base, just above the Paneth cells (Potten, Booth, and Pritchard, 1997). The function +4 stem cells are still not completely know (Sato et al., 2013). Each intestinal crypt contains 4-6 Lgr5+ stem cells between the Paneth cells. The Paneth cells constituted the Lgr5+ niche through cell-to-cell notch receptor contact (Sato et al., 2011). If contact is broken the organoids will initiate apoptosis. Proliferation of the crypt base by Lgr5+ cycling stem cells requires three different types of signaling pathways activated, Wnt pathway, EGF pathway and the R-spondine pathway, where the Wnt signaling pathway is the most important of the three (Sato et al., 2013).
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The Lgr5 stem cells was discovered through the use of a Lgr5+ green fluorescent protein knock in mouse crossed with a LacZ which should mark the Lgr5+cells (Barker et al., 2007). There is unfortunately to this day, still no specific gene marker for the Lgr5+ gene.
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2.4. Theory Behind the Methods
2.4.1. Genetic Markers for Cell Types
Presented below is an overview of the chosen gene-markers for each given cell type (See table 1). The descriptions were obtained from Genecards. They were chosen based on relevance, length, abundant frequency of gene expression in the small intestines and the specific cell type. In order to ensure that the gene of interest is present in the region cut by the chosen primer, the primers were designed to be intron-spanning, with the use of “UCSC Genome Browser”.
Table 1. Overview of chosen gene-markers for each given cell type. Two gene-markers were selected for each cell type excluding stem cells. Cell Type Full Gene Name Gene name
Guanine Nucleotide Exchange Factor 6 Def6
Paneth Defensin Alpha 5 Defa5
Lactase Lct
Enterocyte Alkaline Phosphatase Intestinal Alpi
Mucin 2, Oligomeric Mucus Forming Muc2
Goblet Kruppel Like Factor 4 Klf4
Gastric Inhibitory Polypeptide Gip
Enteroendocrine Peptide YY Pyy
Marker of Proliferation Ki-67 Ki-67
Proliferated Proliferating Cell Nuclear Antigen PCNA
Growth Factor Independent 1B Transcriptional Repressor Gfi1b
Tuft Doublecortin Like Kinase 1 Dclk1
Stem Leucine Rich Repeat Containing G Protein-coupled Receptor 5 Lgr5
Reference gene General Transcription Factor IIB TFIIB
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DEF6, or Guanine Nucleotide Exchange Factor 6, is highly expressed in B and T cells and is thus essential for a functional immune system, which is the role of paneth cells. Also, in cooperation with activated RAC1, it can regulate cell morphology.
DEFA5, or Defensin Alpha 5, is a member of the family Defensin, which are antimicrobial and cytotoxic peptides responsible for the defence of the host cell against foreign molecules. They are present in the granules of neutrophils and epithelia of mucosal surfaces such as the intestine; namely, in the secretory granules of paneth cells of the ileum. LGR5, or Leucine Rich Repeat Containing G Protein-Coupled Receptor 5, is a gene that encodes leucine-rich repeat-containing receptor (LGR); a member of the G protein-coupled, 7- transmembrane receptor (GPCR) superfamily. This protein is crucial in the formation and maintenance of adult intestinal stem cells during postembryonic development, and is therefore a valid marker for stem cells.
DCLK1, Doublecortin Like Kinase 1, is a gene which encodes a protein kinase and a doublecortin. It contains N-terminal doublecortin domains binding microtubules and regulating microtubule polymerization, as well as a C-terminal serine/threonine protein kinase domain which is homologous to Ca2+/calmodulin-dependent protein kinase. The protein also consists of a serine/proline-rich domain in between the doublecortin and the protein kinase domains, which mediates multiple protein-protein interactions. This is a gene marker for tuft cells.
GFI1B, or Growth Factor Independent 1B Transcriptional Repressor, is a gene that encodes a zinc-finger-containing transcriptional regulator mainly expressed in cells of the hematopoietic lineage. It forms complexes with various additional transcriptional regulatory proteins such as GATA-1, runt-related transcription factor 1 and histone deacetylases to control expression of genes involved in the development and maturation of erythrocytes and megakaryocytes. This is a gene marker for tuft cells.
PCNA (Proliferating Cell Nuclear Antigen) is a gene encoding a cofactor of DNA polymerase delta, found in the nucleus. Its conformation is a homotrimer which facilitates the progress of leading strand synthesis during DNA replication, and is therefore a valid gene marker for proliferating cells. Upon DNA damage, this protein is ubiquitinated and takes part in the RAD6-dependent DNA repair pathway.
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MKI67 (Marker Of Proliferation Ki-67) is gene that encodes a nuclear protein associated with and is required for cellular proliferation, and is therefore a suitable gene marker for characterization of proliferating cells.
PYY (Peptide YY) is a gene that encodes a member of the neuropeptide Y peptides family. The gene encodes a preproprotein which is proteolytically altered to generate two alternative peptide products different in length by three amino acids. These peptides are secreted by endocrine cells in the gut; therefore, this gene is a suitable marker for enteroendocrine cells. Binding of the encoded peptides to each of these Y receptors with different affinities, mediates regulation of pancreatic secretion, gut mobility and energy homeostasis.
Gip (Gastric Inhibitory Polypeptide) is a gene that encodes an incretin hormone in the glucagon superfamily. It is important in glucose homeostasis it stimulates insulin secretion from pancreatic beta-cells subsequent to food ingestion and nutrient absorption. This gene is a suitable gene marker for enteroendocrine cells as it stimulates the release of insulin into the bloodstream. Insulin secretion is stimulated via G protein-coupled receptor activation of adenylyl cyclase and the subsequent signal transduction pathways. It is a relatively poor inhibitor of gastric acid secretion.
ALPI (Alkaline Phosphatase, Intestinal) is one of four alkaline phosphatases which exist in the following tissues: intestinal, placental, placental-like, and liver/bone/kidney (tissue non- specific). The intestinal alkaline phosphatase gene encodes a digestive brush-border enzyme, an element of the gut mucosal defense system that functions in the detoxification of lipopolysaccharide and in the prevention of bacterial translocation. This is a gene marker for enterocytes.
LCT or lactase gene, is a gene encoding a protein which belongs to the glycosyl hydrolase 1 family. The gene encodes a preproprotein which proteolytically forms the mature enzyme that is integral to the plasma membrane and has both phlorizin hydrolase and lactase activity. Mutations in this gene are associated with congenital lactase deficiency. Polymorphisms in this gene causes lactase persistence, in which lactase activity at childhood levels continues into adulthood. This gene is a marker in characterization of enterocytes.
Muc2 is a gene that encodes a member of the mucin protein family. They are high molecular weight glycoproteins generated by many epithelial tissues and is secreted to form an insoluble
Page 24 of 81 mucous barrier that protects the gut lumen. This mucous-forming function is characteristic of goblet cells; therefore, this gene is a suitable gene-marker for the cell type.
KLF4 is a gene encoding a protein of the Kruppel family of transcription factors. The zinc- finger protein is found in the small intestine and is crucial in development of the barrier function of skin. It is understood to control the G1-to-S transition of the cell cycle following DNA damage by mediating the tumor suppressor gene p53. The protein can activate its own transcription by binding to the promoter region of its own gene and it is involved in the differentiation of epithelial cells. This gene is a marker for the characterization of goblet cells.
2.4.2. The Organoid Model
2.4.2.1. Growth Factors in Cell Media
In order to culture cells properly so they can mimic their original environment, they need a sufficient amount of nutrients required for cell growth. Which is why when cells are cultured, a media consisting of various proteins and peptides, amino acids, carbohydrates, vitamins, salts, serum (mixture of a number of proteins) fatty acids and lipids are needed for culturing the cells. However, not all cell types can grow in a serum-containing medium, there are certain cells that require specific protein growth factors in media in order to increase in size and mass and undergo cell division (Lodish et al., 2000). Growth factors are extracellular polypeptide molecules that binds to a cell-surface receptor that triggers intracellular signalling pathway leading to proliferation and differentiation (Lodish et al., 2000). Various studies have shown that because of the growth factors role in proliferation and differentiation, they have an important role in the intestinal growth as well as helping intestinal cells to repair from injury or inflammation (Rowland, Choi, and Warner, 2013).
Some of the intestinal growth factors used in media for the developing of cells are (Rowland et al., 2013; Gagne et al., 2004).
Epidermal growth factor (EGF) is a 53-amino acid peptide used for the developing of intestine. It is usually found in fluids like breast milk and saliva. This growth factor is important for intestinal epithelial cell proliferation and survival. Its receptor (EGFR) has tyrosine kinase activity and is therefore found on the basolateral surface of enterocytes.
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Heparin-binding epidermal-like growth factor (HB-EGF) is a 22-kDa glycoprotein, and is a member of the EGF family. This growth factor signals through the EGFR receptor for stimulating cellular growth and differentiation. It is also originally found in human breast milk and amniotic fluids.
Growth hormone (GH) is a 22-kDa anabolic protein and it is synthesized in the anterior pituitary. It has an important role in postnatal growth, but also in lipid and carbohydrate metabolism. GH is a type 1 cytokine receptor, and it signals tyrosine kinase JAK2 (Janus Kinase 2) pathways by binding to it. It is expressed both in various part of the small and large intestine, which implies that GH receptors influence cell growth in the intestine.
Insulin-like growth factor (IGF) is an amino acid polypeptide that is synthesized in the liver and in the gastrointestinal tract. It consists of several factors such as IGF-1 and IGF-2. Both of these growth factors are found in breast milk. They function by increasing intestinal cell proliferation and intestinal growth.
Glucagon-like peptide 2 (GLP-2) is a 33-amino acid peptide that is used for regulation of nutrients, blood flow, motility and growth in the intestine. This growth factor is secreted from enteroendocrine L cells of the distal small intestine and colon.
Keratinocyte growth factor (KGF) is a fibroblast that promotes proliferation and upregulates SI expression in fetal human small intestine explant culture, as well as stimulates growth and differentiation of epithelial cells.
Hepatocyte growth factor (HGF) is a glycoprotein. It regulates cell proliferation and survival through MET receptor tyrosine kinase.
Granulocyte colony stimulating factor (G-CSF) is a glycoprotein that is also found in amniotic fluids and human milk. This growth factor is involved in protecting the intestinal epithelium, but is mainly expressed in the regulation of neutrophil production.
Erythropoitin (Epo) is a glycoprotein and is found in breast milk. Epo receptors are found to be present on intestinal cells, and injections of Epo has shown changes in the small intestinal length as well as surface area.
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Intestinal trefoil factor (ITF) is a group of polypeptides that are secreted by mucus leading to the production of epithelial cells. ITF are seen as enterocyte protective, and promotes epithelial cell migration as well as repair of gastrointestinal damage. It also inhibits apoptosis. Some of factors from ITF are expressed in goblet cells of the small intestine and colon.
2.4.2.2. Outline of the Model
Throughout the years the stem cell field has evolved greatly in terms of the in vitro generation of complex structures (Xinaris, Brizi, and Remuzzi, 2015), and so has our understanding of stem cell niches and the role of key signalling modulators in controlling stem cell maintenance and differentiation (Fatehullah, Tan, and Barker, 2016). This has fuelled specialists to develop a model that allows stem cells from embryonic organs to reaggregate and recreate a 3- dimensional organ of the original organ system called organoids (Xinaris, Brizi, and Remuzzi, 2015).
Organoids are self-renewing and self-organizing tissues grown in vitro, that are capable of developing organotypic cultures and utilizing organ-specific functions (Fatehullah, Tan, and Barker, 2016). They are generated from progenitor cells, that are either isolated from embryos or grown from pluripotent stem cells (Xinaris, Brizi, and Remuzzi, 2015). Organoids are similar to primary tissues in their composition and structure, as they contain a population of genomically stable, self-renewing stem cells that can later differentiate progeny.
Since organoids can be grown from human stem cells it has been shown that they can self - organise and recreate original organ structures due to the dissociated cells from embryonic organs, and they can therefore give rise to modelling development and diseases for toxicology and regenerative medicine (Xinaris, Brizi, and Remuzzi, 2015).
As mentioned above, when tissues are grown in a 3D environment, embryonic stem cells self- organize into organoids and acquire the right patterning to develop into several endoderm and ectoderm-derived tissue, mimicking their in vivo counterparts (Huch and Koo, 2015). This discovery has evolved over the years, since it was missing in the traditional 2-dimensional culture system(Xinaris, Brizi, and Remuzzi, 2015). The 2D model lacked sufficient information about culture systems that would allow cell-cell and cell-matrix interactions needed for organ information (Huch and Koo 2015; Hynds and Giangreco, 2013).
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The organoid model has only recently evolved, since the earliest 3D models required a large number of starting cells and therefore could not be used for high-throughput screening, which often showed limited in vitro viability. However, many of the limitations were eliminated because the advanced 3D organoid model is built upon further studies on multipotent stem and progenitor cell isolation (Hynds and Giangreco, 2013), This has allowed aggregates of the cells to differentiate and self-organize into 3D structures that are highly reproducible (Xinaris, Brizi, and Remuzzi, 2015).
Although the 3D organoid model has various advantages in the field of medicine, it also has some limitations. To optimize the 3D organoid model researchers are trying to eliminate limitations. One of these limitations include the lack of native microenvironment, in other words, organoids lack many of the cellular inputs present in an in vivo system, and this prevents further studies about stem cells with their niches (Fatehullah, Tan, and Barker, 2016; Dedhia et al., 2016). A possible solution for this limitation could be to increase the complexity of organoids through co-culture with other cell types.
2.4.2.3. Past Issues
It is quite recent that science has found some more fitting conditions for these organoids to be able to be proliferative, looking just 10 years back, one of the most problematic issues of research on these organoids was, that organoids could not maintain life for more than just a couple of minutes. According to Bjerknes and Cheng, three largest issues of maintaining a viable environment for the organoids are: I) untransformed epithelial cells are anchorage dependant. When epithelial cultures are extracted from the donor organism, the epithelial loses contact with the basal lamina, which leads to the activation of a transduction cascade leading apoptosis. The apoptotic reaction to loss of anchorage is called anoikis. II) The understanding of the survival and growth requirements for the organoids was quite poor. III) The in vitro conditions, to match normal linage condition had still not been developed (Bjerknes and Cheng, 2006).
Due to the missing knowledge about the organoids, there has been published a lot of different protocols where minor parts are changed compared to the others. Since there is little knowledge of the survival mechanisms, scientist change the concentration of EDTA, incubation temperatures or application of shear force (Bjerknes and Cheng, 2006). Prior to year 2006
Page 28 of 81 before anoikis was understood, EDTA (standard used buffer system) was toxic for the organoids since they quickly initiated apoptosis.
According to Bjerknes and Cheng, the survival models for the organoids are based mainly on assumptions, and not empirical knowledge (Bjerknes and Cheng, 2006). In 2009, there are still no culture models that are effective for long term organoid survival (Sato et al., 2009).
Anoikis is the initiation of an apoptotic pathway, when the cells are disconnected from the basal membrane of the organism. In this case, the organoid cells are dissociated from the transmembrane heterodimeric receptor β1-intergrin. The β1 family integrins are responsible for the extracellular matrix cytoskeleton linkage and the adhesion-mediated signalling pathways, stopping the cells to induce anoikis.
2.4.2.4. Advantages
Pharmaceutical manufacturers have long been faced with the challenge of developing drugs with high effectivity and low expense. The extremely few amount of drugs that pass the tests from target identification to lead optimization for approval in reaching the market, as well as the immense expense of carrying out these tests, contribute to making drug discovery a difficult field. New approaches for epithelial translational medicine are therefore necessary. Until the 2010s, preclinical in vitro 2D cell cultures observed under the LM were utilized as the only means of investigating the quality of cell cultures in representing real tissues. Due to the 2D nature of this methodology, the lack in observational ability rendered this mode of study rather inadequate in carrying out drug-efficacy tests.
In 2010s, a novel technique called the stem cell-derived organoid model was founded (Hackney et al., 1968). This is a technique that can be utilized to develop a more accurate and personalized treatment for a specific disease at hand. In this case study, our focus is on the intestinal organoid model.
There are a few outstanding advantages of this innovative cell-based organoid model in investigating drug efficacy. First, cell-based organoid models, due to its three-dimensional nature, constitute a higher level of correspondence and accuracy in the physical, molecular and physiological properties to that of the real system. This therefore enables an increased accuracy in investigation by researchers, as though these intestinal organoids are being observed in vivo.
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Tissue cells of a specific organ of interest can thus be reproduced and observed with high representational accuracy to that of the real system. Due to the ability to carry out thorough observations through the 3D organoid model, the following features of a certain tissue can be investigated: multipotent cellular differentiation, intra and intercellular signalling and communication, as well as organisational network (Xinaris, Brizi, and Remuzzi, 2015), which are revolutionary properties crucial in the investigation of disease, previously impossible until this model was founded. Hence, this enables the observation of organ-specific functions, increasing its precision as a technique of elucidating cellular and molecular mechanisms underlying diseases and development of therapies for treatment via for example, drug discovery.
Furthermore, they are obtained from the tissue of the specific patient, which further increases the accuracy of the results obtained from this model. This precise resemblance of the organoid model to the tissue-specific cells improves the accuracy in validating lead compounds that will most likely be effective in the body of the particular patient under investigation. This would therefore lower the risk of unsuccessful treatment; in addition, this cuts back on the expense in preclinical trials (Hynds and Giangreco, 2013). This technique is thus cost-effective in terms of drug discovery compared to other models such as the less accurate 2D cell cultures.
Finally, in any given assay, researchers are continuously aiming for its high-throughput screening (HTS) capacity. Although the first organoid model founded in the 1970’s required a large number of starting cells unyielding to HTS, the stem cell-derived organoid model is subject to HTS and is thus an effective technique.
2.4.2.5. Disadvantages Organ-specific 3D cell culture models must be optimized to enable effective, reproducible and overall successful organoid formation. This includes lowering heterogeneity by accurate characterization of cell types, through setting specific gene markers and refining tissue-specific organoid growth conditions identical to the physiological environment. As human physiology undergoes dynamic homeostatic processes adjusting to its external environment, it is a common challenge to reproduce a simulation of a specific tissue in vitro which is relevant in vivo. Although these properties are difficult to achieve, overcoming these issues will ensure the ability of assessing compound efficacy and safety in an accurate high-throughput organoid assay.
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3. Methods ● Intesticult Organoid Growth Medium was prepared following the protocol in Appendix 6. 3.1. The Preparation of Crypt Solution 3.1.1. Isolation of Mouse Intestinal Crypts 500 µL Matrigel Matrix was thawed, of which 150 µL was used for each preparation (4 wells of a 24 well plate). The non-tissue culture treated 24-well plate was incubated at 37℃ for
30 minutes in order to reach the optimal conditions for our cells to grow. While the plate was incubating, two mice were sacrificed through cervical dislocation. Once the mice had been put down, 20 cm of small intestine was removed and placed in cold PBS (phosphate- buffered saline) (see Fig. 9). Figure 9 – Harvest of mouse small intestine
In order to cleanse the intestine, it was flushed with additional cold PBS by inserting a pipette tip in one end and letting the PBS move through the intestinal tract.
Once the intestines were cleansed, a longitudinal incision was made along the entire length of the small intestine. Once the small intestine was split, 1 mL of PBS was used to wash the intestines for a total of 4 times. Once the intestines were thoroughly cleansed, it was cut into 2 mm pieces and added to a conical tube containing 15 mL cold PBS. Through the use of pre- wetted pipette, the intestinal pieces were pipetted up and down 3 times and left to settle. Once they had settled, supernatant was removed.
This process was repeated 15-20 times in order to separate and remove the villi. Once the supernatant became clear it was removed, and 25 µL Gentle Cell Dissociation Reagent was added. The mixture was placed on a rocking table and incubated at room temperature for 15 minutes. Once the intestinal pieces had settled, the supernatant was removed. The intestinal pieces were once again re-suspended in cold PBS+0.1% BSA (Bovine Serum Albumin) and mixed through pipetting. The intestinal pieces were left to settle and supernatant was removed, filtering it through a 70 µm filter. The filtrate was labelled Fraction 1 and placed on ice. These
Page 32 of 81 processes were repeated for the second mouse intestines, which gave us a total of 4 fractions after the treatment. The fractions were all centrifuged for 5 minutes and the supernatant was removed, leaving a pellet. Each pellet was resuspended in 2 mL of cold PBS + 0.1% and was transferred to conical tubes. The suspension was centrifuged for 3 minutes at 2-8℃ and the supernatants poured off making them ready for the next treatment step.
3.1.2. Intestinal Organoid Culture
In order to prepare the cells for cultivation, each intestinal crypt pellet (section 3.1.1.) was resuspended in 10 mL cold (2-8℃) DMEM/F12 (Dulbecco’s Modified Eagle Medium). 1 mL of each suspension was added to the individual well and the quality of the suspensions with a microscope was assessed. The fraction from section A were collected and used for the following step. Around 50 crypts were isolated, which gave us approximately 5,000 crypts/mL (50 crypts × 100 mL = 5,000), aliquoted the crypts into 3 × 15 mL labelled conical tubes in volumes containing approximately 250 crypts per well. The well was centrifuged at 200 × g for 5 minutes at 2-8°C, and the supernatant was removed. **150 µL of complete IntestiCult™ Organoid Growth Medium (15-25°C) was added to each pellet. 150 µL of undiluted Matrigel® (matrix gel) was added to each tube, and pipetted up and down 10 times without introducing bubbles to resuspend the pellet. 50 µL was carefully pipetted to the 250-crypt suspension into the middle each wells of the pre-warmed 24-well plate. The well was incubated at 37°C for 5- 10 minutes until the matrix gel was solidified. 750 µL of the growth medium containing antibiotics (15-25°C) was pipetted into the well without disrupting the matrix gel. PBS was added to the unused wells. The plate with the lid was incubated at 37°C and 5% CO2. The culture medium was exchanged 3 times per week by removing the existing medium and replacing it with 750 µL of growth medium.
3.1.3. Passaging of Mouse Intestinal Organoids
The following materials were gathered: thawed matrix gel, growth medium at room temperature, and an untreated 24-well plate pre-warmed in a 37°C incubator. Since the medium is unnecessary for splitting the intestinal organoids, the culture media from each of the 8 wells was removed without disturbing the dome, consisting of organoids in matrix gel. 1 mL of
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Gentle Cell Dissociation Reagent was added to each well directly on the dome to facilitate detachment of the cells making up the tissue, and subsequently incubated for 1 minute at room temperature. The Gentle Cell Dissociation Reagent in each well was pipetted up and down approximately 20 times to separate the organoids. The suspension was transferred to a 15 mL conical tube, and to ensure that all the organoids were taken out of each well, they were rinsed with a further 1 mL of Gentle Cell Dissociation Reagent, respectively, and added to the same tube. These steps were carried out for each well to be passaged. To further establish the dissociation of the cells, the 15 mL tubes containing the disrupted organoids were shaken on a rocking platform at 20 rpm for 10 minutes at room temperature and centrifuged at 300 × g for 5 minutes at 2-8°C. The supernatant was then gently discarded and a pre-wetted 10 mL serological pipette - to ensure that the pellets do not stick to the tube in the process - was used to resuspend the pellets in 10 mL of cold (2-8°C) DMEM/F12. The tubes were centrifuged at 300 × g for 5 minutes at 2-8°C and the supernatant was discarded. Steps in section “**” were followed for the complete the passaging of intestinal organoids.
3.2. Fixation
For the fixation of the organoids, we used the protocol provided by Gert Helge Hansen and Lotte W. Niels-Christiansen (see Appendix 6)
The fixation was induced by using a mixture of 2% paraformaldehyde + 3% glutaraldehyde in a 0.1 M Na-phosphate buffer 7.2 pH. The paraformaldehyde makes a non-permanent fixation, dependant on temperature, where the glutaraldehyde makes a permanent fixation by creating irreversible dimer formation.
When treating the culture matrix gel, the growth medium was first gently removed by pipetting from the edge of the wells, in order to ensure that the matrix gel was not touched. After the removal of the growth medium, 2% paraformaldehyde + 3% glutaraldehyde in a 0.1M Na- phosphate buffer was added to stop cell differentiation, until the matrix gel was fully covered by the liquid (approx. 500 µL), and let it incubate for 15 minutes. After the 15 minutes, the liquid was removed in a similar way as with the growth medium, and subsequently washed three times in Na-phosphate buffer, with an incubation time of ten minutes between each wash. When done washing, approximately 500 µL of 1% paraformaldehyde in 0.1M Na-phosphate
Page 34 of 81 buffer 7.2 pH was added. The plate was sealed with parafilm and placed in a refrigerator until needed.
3.3. RNA Purification In order to obtain a total RNA and protein purification from the cultured organoids, a RNA/protein purification kit was used. Specifically, for this procedure: Nucleospin RNA/Protein by Machery-Nagel was used, with all materials and solutions supplied. For any specifications or protocol details see the 2014/rev. 09 edition of the user manual for this specific kit (see Appendix 6).
3.3.1. Disruption and Lysis of Organoid Cells To obtain sufficient amounts of RNA, the organoid cells have to be disrupted. This was done by pipetting the cells up and down several times until the organoids were dissolved into the lysis buffer. To lyse the cells, the RP1 buffer and DTT mixture were pipetted up and down, which dissolved the gel and broke the cells. The lysate mixtures were transferred to Eppendorf tubes for later use.
3.3.2. Filtration To obtain a solution free of viscous matter from e.g. the matrix gel, a filtration of the lysates was done. For this, the lysates were run through Nucleospin filters and spun for 1 minute at 11,000 × g, after which the nucleospin filter was discarded.
3.3.3. RNA Binding To make RNA bind to the column the solution obtained after filtration was mixed with 350 µL of 70% ethanol with DECP (diethylpyrocarbonate) to inactivate any RNase. The sample resuspended in ethanol was loaded onto the Nucleospin RNA/Protein column and centrifuged for 30 seconds at 11,000 × g. The flow-through was saved, as it contained proteins and miRNA. Meanwhile, the filter containing the bound RNA and DNA was placed into a new collection tube and was worked on for subsequent steps.
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3.3.4. DNA Digestion In order to make the DNA digest more efficient, salt was removed from the membranes by adding 350 µL of MDB (membrane desalting buffer) to the column and furthermore, centrifuged for 1 minute at 11000 × g. For each sample, an rDNase reaction mixture was prepared by mixing 10 µL rDNase and 90 µL rDNase reaction buffer. To the column’s center 95 µL of the rDNase reaction mixture was added and the column was incubated for 15 minutes at room temperature.
3.3.5. Washing In order to remove impurities and the DNA that had dissociated from the column after digestion, the column was washed through three times (See Table 2).
Table 2. Washing steps for removal of DNA and impurities.
First Wash Second Wash Third Wash
Washing Solution RA2 RA3 RA3
Volume Added 250 µL 600 µL 250 µL
Centrifuge 30 sec 30 sec 2 min Duration
3.3.6. Eluting Pure RNA This final step was done in order to release the final purified RNA into a tube for further processing, before using it for amplification. The column was placed in an RNase free collection tube and the RNA was eluted into this tube by adding 60 µL of RNase-free H2O and centrifuged for 1 minute at 11000 × g.
Lastly, samples were labelled and put on ice until needed.
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3.4. cDNA Synthesis
To find out how much RNA was yielded, the concentrations of each RNA sample was determined using a nanodrop UV-vis spectrophotometer, before the cDNA synthesis procedure was executed.
RNA was diluted with RNAse free water to obtain a concentration of 250 ng/µl. (see Appendix 6). Random hexamer primer, which is a mixture of oligonucleotides representing all possible sequences for the gene size, was added to this solution in order to synthesize a large pool of
DNA. The solution was centrifuged and incubated at 65℃ for 5 minutes and kept on ice. The necessary amounts of 5x reaction buffer, RiboLock RNase inhibitor, dNTP mix (10 mM), M- MuLV Reverse Transcriptase (20 U/µl) and RNase free water, were mixed through centrifugation. The solution was incubated for 5 minutes at room temperature followed by incubation at 37℃ for 1 hour. The last incubation lasted for 5 minutes at 70℃. The RNA and
11 µL of the reaction master mix was distributed into PCR tubes and ran the cDNA synthesis on PCR machine Veriti 96 well Thermal Cycler.
3.5. qPCR: Primertest Primer stocks were diluted to obtain a concentration of 5 pmol/µL, and kept on ice. 1 µL of each cDNA sample for RT- (reverse transcriptase - absent) and RT+ (reverse transcriptase - present) respectively, were combined. cDNA dilutions were made in 10x, 100x and 1000x- fold. These dilutions, alongside an undiluted cDNA solution, RNase free water and RT- solutions, were plated out on a 96-well PCR plate. Each primer set was added to each of these six conditions. The PCR plate was run under the same qPCR reaction conditions as the final qPCR reactions.
3.6. qPCR: Programmed Cycle Run for qPCR Primers were diluted to obtain a concentration of 5 pmol/µL and kept on ice. 2x QuantiTect SYBR Green PCR master mix, template cDNA, primers, and RNase-free water was thawed and each individual solution was vortexed. QuantiTect SYBR Green PCR master mix, RNase free water and primers (forward and reverse) were combined to make a reaction master mix. The reaction master mix was mixed thoroughly and dispensed onto a 96 well PCR plate. cDNA
Page 37 of 81 was added to each well and a qPCR reaction was run for ROX (Rhodamine-X, which is a refernce dye used for the normalization of fluorescence intensity of qPCR dyes, such as SUBR Green) and FAM (Flourescein , is a dye used to re-emit light upon light excitation).
Note: The independent variable was the primer and as such, each plate setup was identical in terms of the placement of cDNA samples. Therefore, the results will represent the genes expressed, in the cells of a specific organoid developmental stage.
In order to dissociate the DNA and RNA hybrids, the solution in the qPCR was exposed to
95℃ for 15 minutes.
The amplification of the cDNA is done in 40 cycles consisting of the following steps:
- To enable a primer annealing, the solution was further exposed to the optimum temperature (60℃) for 30 seconds. In order to activate the polymerase and for
elongation, the condition applied to the samples was 72℃ for 30 seconds.
After the 40 cycles of the aforementioned steps, the temperature in the reaction is reduced to 55℃ from the initial temperature at 95℃. At this step, a full elongation is obtained after which gradually returns to 95℃, resulting in a dissociation curve. Since the primers and polymerases are essential in the synthesis of dsDNA, the two respective optimal temperatures are applied. The fluorescent chemical SYBR Green will settle within the double helix structure. When the dissociation temperature is met, the DNA strands will break apart and the SYBR Green is released, emitting a strong fluorescence signal. Since the temperature of dissociation indicates the length of dsDNA, this ensures that only the product of interest is present. In other words, one dissociation peek will represent one product and therefore a homogeneity of the sample is confirmed.
3.7. Double Delta Ct Calculations for Analysis of Fold Change Relative quantification was carried out to analyze the results of Real Time quantitative PCR to compare the changes in levels of gene expression over time. Double delta Ct analyses were conducted for each gene to calculate the change in gene expression, by comparison between
Page 38 of 81 the expressions of the experimental gene and the reference gene (TFIIβ). To do this, the Ct values obtained in duplicates from each day of the reference gene and experimental gene were respectively averaged, in which the reference gene average was subtracted from the experimental gene average, from each day, i.e., the ΔCTE from each respective day was calculated. The fold change or the difference in gene expression was then calculated by 2^ΔCTE-ΔCTC, which is the difference in Ct for the experimental gene compared with the control gene, that is the Ct obtained from day 2 in the first qPCR trial, and that obtained from day 3 in the second trial. The fold change value for each day was plotted against the days on a bar chart for each experimental gene. An example of the double delta Ct analysis calculations carried out for each gene, described previously, is presented below (See Table x).
The CTC (Ct Control) is necessary in order to carry out the double delta Ct analysis, as a control in which to compare the rest of the Ct values. In the first trial and the second trial, day 2 and day 3 sample values, respectively, were used as the CTC. It is expected that the fold change for day 2 and 3 in trials 1 and 2, is 1, since the exponent in the fold change calculation 2^ΔCTC- ΔCTE would cancel each other out, ending up with 2^0 which is 1.
The Ct (cycle threshold) is defined as the number of cycles required for the fluorescent signal to cross the threshold (ie exceeds background level). Ct levels are inversely proportional to the amount of target nucleic acid in the sample (ie the lower the Ct level the greater the amount of target nucleic acid in the sample)
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4. Results
The experimental setup was based on the cultivation of organoids. In order to investigate the presence of developmental stages of the different cell types, samples over a time period of 13 days were collected for analysis.
The first trial of organoid harvest involved extracting cells from days 2-6, with intervals of two days. The second trial of organoid harvest, involved extracting cells from days 1-13, with intervals of two to three days, since this allowed cells to differentiate to a detectable degree.
In order to assess the validity of the results obtained, the experiments were performed through use of two double determinations. The technological duplicates were based on two wells with the same combination of cDNA and primer. The biological double determinations were based on harvesting two organoids producing two separate samples.
Before the qPCR was run, a primer test was performed in order to validate and distinguish the optimal primers from the dysfunctional primers.
In order to establish whether the primers in use were optimal, an amplification plot was produced with dilutions of undiluted, 10-1, 10-2 and 10-3. The reference gene used for these samples, was the original reference gene RPLP0. Since this reference gene did not show results, a new reference gene was used for the rest of the experiment (TfIIβ).
From the amplification results (see Fig.10) it can be observed that the primers all showed similar curve patterns except for the three outliers that show a drastic increase in slope compared to the rest of the samples.
With regards to the samples with 10-3 dilutions showed few results, which could be due to the dilution being too extensive.
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Figure 10- Amplification plot from the primer tests
The primer Pcna amplification plot shows a tendency for the curves to overlap during cycles 34 to 40. It was therefore determined unfit for use in this experiment as an optimal primer for proliferating cells.
Figure 11 - Amplification plot for the primer Pcna
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Below is the amplification plot for the Ki67 primer recognizing the genetic marker for proliferating cells. From the plot, it can be seen that the curves and cycles are more uniform and do not overlap. It was therefore considered an optimal primer for identification of proliferating cells in the organoid model.
Figure 12 - Amplification plot for primer Ki67
Reference Gene TfIIβ
As mentioned above, the reference gene TFIIβ was used for the remaining samples. Below is an amplification plot, illustrating the result for the RT- samples. The samples should not have been amplified, since there is no reverse transcriptase. However, for this experiment we decided to proceed using this reference gene, since the amplification of the RT+ was still illustrating relevant sigmoid curves (data not shown).
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Figure 13 – Graphical representation of the Amplification curves for the RT- samples of the TFIIβ reference gene.
The UCSC genome browser cut out, represents the chosen reference gene TFIIβ, and clearly shows that the primer is not intron spanning and cuts an exon. This is an indication that the primer is not optimal, however due to the time limitations for this experiment, the primer was applied in the experiment.
Figure 14 - Illustrates the TFIIβ primers annealing position (Red arrow) on the 6th exon of the GTFIIβ locus located on chromosome 3 of the mouse genome. The results were acquired from genome browser.
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4.1 Significant Dissociation and Amplification Curves
In this section, a few significant dissociation and amplification curves are presented to illustrate examples of valid, invalid and ambiguous curves.
4.1.1. Muc2 The curves represent the fluorescence (y-axis) released from each well with cDNA, SYBR green and their corresponding primers in each cycle (x-axis).
The sigmoidal curve, shows a similar shape for the data samples, which signifies that the product which has been amplified is the same (See Fig. 15). Furthermore, an even distribution of cycle intervals can be observed with the exception of the orange and grey lines.
Figure 15 - Amplification curve of Muc2.
Figure 16 - Amplification curve of RT-
4.1.2. Alpi All RT- samples (i.e., negative controls) display fluorescence under the starting level. There is minimal amplification which is considered background noise. The left peak shows RT+ dissociation results which is present at 81℃. The right peak shows results for RT- at 83℃.
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Figure 17 - Dissociation curve for the marker Alpi.
4.2 qPCR Results
4.2.1 Enterocytes
4.2.1.1. Lct From the data results, it can be observed that the highest level of fold change was found for day 6a. The results show a level of fold change of approximately 34. Throughout the first days, there is a limited increase in level of fold change, however, all samples show fold change levels of above 1. The results for the samples for day 6b, show a fold change level of 10, being well above the previous days (6a being the exception). (See Fig. 18)
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Figure 17 - Graphical representation of the first trial of Lct, showing the fold change of genetic expression in the course of 2-6 days.
From the data, it can be observed that there is a large increase in fold change from the threshold value for day 3a (see Fig. 18). For day 3b, the fold change level is approximately 15. From day 3b to 6, there is a large decrease in fold change levels. From day 6 to 8a, there is a steady increase in fold change, which furthermore leads to a drastic increase for samples from day 8b. Samples from day 8b display the largest fold change increase, by 34. Results for day 10a and 10b show an increase in fold change levels, which drastically decrease for samples from day 13a. During the 13th days, there is an increase in fold change levels, of approximately 5.
Figure 18 – Graphical representation of the second trial of Lct, showing the fold change of genetic expression in the course of 3-13 days.
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In both the first and second trial, Lct expression is detectable between day two and day four in relatively steady levels, ranging around 2-4 fold change (excluding 3b from the second trial). For both trials from day 6 to 13 there is a significant upregulation of the Lct gene approximately ranging from low to 12-fold up-regulation (see Fig. 18).
This shows that even though there is an expression in the early development of the organoids, the abundant expression of the Lct gene, is seen in the later developmental stages.
4.2.1.2. Alpi The data above shows that the first increase in fold change is on day 2b, where it is slightly above 1.6, however the fold change decreases after 2b, but is still above the “control minimum” level of 1 by 0.1. Moving to day 6a and 6b, the fold change drastically decreases until it is approximately 0.6, but rises to a fold change of approximately 0.8 at 6b. 2a has a fold change precisely at 1. Overall, there is only an increase of fold change on day 2b, 4a and 4b, whereas day 6a and 6b has a decrease of fold change. (See Fig. 19)
Figure 19 - Graphical representation of the first trial of Alpi, showing the fold change of genetic expression in the course of 2-6 days.
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The bar charts representing the genetic expression of Alpi shows an overall fluctuating fold change pattern (See Fig. 19 and 20). From the data results, it can observed that there is a fluctuating pattern among the different samples throughout the 13 experimental days. The results from day 3b show a large increase in levels of fold change, namely an increase of approximately 3.4. During day 6 and 8, we see an increasing trend. Samples from day 8b show a drastic increase in fold change levels, in comparison to the prior day's results. The results from day 10a show a drastic decrease in levels of fold change, falling below the threshold value of 1. The results for day 10b, show higher levels of fold change, which decreases during day 13b. Generally, the data results for 3b, 8b, 10b and 13b show an increasing fold change trend up until day 8, where a decreasing trend appears.
Figure 20 - Graphical representation of the second trial of Alpi, showing the fold change of genetic expression in the course of 3-13 days.
As presented in the graphs for the Alpi gene-marker, there is a significant expression in the early development. For the first and second trial, day 2 and 3 respectively show relative expression levels. Certain outliers could be discarded, for example sample 8b, and considered biological coincidental differences found in the two different organoids harvested on the same day. On figure 19, showing the first trial of Alpi, only a small fold change is visible, the highest being 0.6-fold change. However, in the second trial, a bigger fold change is observed, if outliers are not discarded, the biggest fold change would be no less than 7 (See Fig. 20). If 8b alone is discarded as an outlier, it makes a significant difference, the fold change will be reduced to be approximately 2 at its maximum. Therefore, there are arguable grounds for dismissing any
Page 48 of 81 major outliers, that would affect the interpretation of the results obtained, as a whole. The Lct genetic marker differs in expression from Alpi, as it is slowly upregulated throughout the days in the organoid development. However, as for the second trial of Alpi and Lct, 8b is an outlier as the gene expression does not increase. Day 6 in the first trial, day 10 and 13 in the second trial show high upregulation of the Lct gene. The bar charts representing the genetic expression of Alpi show an overall steady expression level, but with different fluctuations spread throughout the data. The second trial, however, differs in that sample 8b seems to be an outlier, showing a vast difference from the other results shown in the bar charts above.
4.2.2. Enteroendocrine Cells
4.2.2.1. Gip The bars represent the abundance of gene expression displayed by the fold change (y-axis) over the progression of time shown in days (x-axis). The “a” and “b” represent duplicates of each sample day number. Samples 2a and 2b were used as controls to obtain the fold change values calculated by double delta Ct analysis as described in the beginning of this chapter. 2a has a fold change value of 1, whereas 4a, 4b, 6a and 6b yielded values consistently descend below 1; 0.89, 0.66, 0.54 and 0.23, respectively (See Fig. 21).
Figure 21 - Graphical representation of the first trial of Gip Fold Change Over Days.
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The bars represent the abundance of gene expression displayed by the fold change (y-axis) over the progression of time shown in days (x-axis). The “a” and “b” represent duplicates of each sample day number. Samples 3a and 3b were used as controls. Sample 3a has a value of 1, whereas the remaining samples yielded values below 1. Overall, it can be seen that samples 8a, 10a, 13a increase consistently, 0.037, 0.094 and 0.113, respectively. Although 8b and 10b increases at 0.016 and 0.059, 13b is 0.031 and thus drops in value. Sample 6 displays a fairly low fold change of 0.00000299 (See Fig. 22).
Figure 22- Graphical representation of the second trial of Gip Fold Change Over Days.
Thus, the sample from day 4a displays maximum fold change, i.e., the highest Gip gene expression, due to its exposure to sufficient nutrients from the still-existing media. In samples 6a and 6b, the lack of nutrients required for cells to thrive, caused the gene expression to decrease.
The dataset from trial two overall displays consistent fold change increase as days progress, in samples 8a and 8b, 10a and 10b as well as 13a, with values 0.037 or 0.016, 0.094 or 0.059, and 0.113, respectively (See Fig. 22). This is in accordance with cell differentiation, since the gene expression of Gip increases as time progresses. Although the majority of the samples presented, showed consistently increasing data, sample 13b had a fold change value which dropped to 0.031, that is lower than the samples prior to it. However, 13a had showed consistently increasing data following those in day 8 and 10. This result could therefore be labelled as an outlier. Sample 6 displays an unusually low fold change of 0.00000299, which is another
Page 50 of 81 outlier, as the rest of the data had consistently increased in gene expression over the course of days.
4.2.2.2. Pyy The bars represent the abundance of gene expression displayed by the fold change (y-axis) over the progression of time shown in days (x-axis). The “a” and “b” represent duplicates of each sample day number. Samples 2a and 2b were used as controls. 2a yielded a value of 1, while 4a and 6a increase from one to the other at 0.56 to 1.62, and 4b and 6b are ascending from 0.47 to 0.67.
Figure 23- Graphical representation of the first trial of Pyy Fold Change Over Days.
The bars represent the abundance of gene expression displayed by the fold change (y-axis) over the progression of time shown in days (x-axis). The “a” and “b” represent duplicates of each sample day number. Samples 3a and 3b were used as controls, which display fold change values of 1 and 2.25, respectively. Samples 6, 8b, 10a or 10b are consistently ascending at 0.34, 0.34, 0.67 or 0.96, whereas day 13b displays a lower gene expression at 0.90, than 0.67 or 0.96 from day 10 (See Fig. 24). Sample 8a has an irregularly low fold change of 0.0000093.
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Figure 24 - Graphical representation of the second trial of Pyy Fold Change Over Days.
4.2.3 Proliferating Cells
4.2.3.1. Ki67 From the graph, it can be observed that there are general small levels of fold change for samples for Ki67. The results show that the highest level of fold change is found in the samples from 6a. The data result shows that the levels of fold change for the first days, lies close to the starting level of 1. The results for the sample from day 6b, shows higher levels of fold change at approximately 1.6. (See Fig. 25)
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Figure 25- Graphical representation of the first trial for gene marker Ki67. The graph illustrates the fold change in relation to days (2-6 days).
From the data shown below, it can be observed that there are three fold change irregularities, namely the results for samples from day 3b, 8b and 13b (See Fig. 26). The data shows a fold change level of 14 for day 3b and a drastic decrease in fold change for day 6. The data results for day 8a show a small increase from day 6. The data for day 8b show a drastic increase of 16 in fold change level. The consecutive days, 10a,10b and 13a show a relatively consistent increase in fold change level. 13b shows another drastic increase with a fold change level of approximately 16.
One could argue that 3b, 8b and 13b are outliers, since they deviate from the fold change pattern of the surrounding samples. Despite the outliers, there is a gradual upregulation of the Ki67 gene expression.
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Figure 26 - Graphical representation of the second trial for gene marker Ki67, illustrating the fold change of gene expression from 3 to 13 days.
4.2.4. Goblet Cells
4.2.4.1. Muc2 In the same way as the previous results, the samples for 2a were used as starting level. It can be observed that there is a decrease of 0.3 in fold change, between samples for 2a and 2b (See Fig. 27). The samples for 4a show a high fold change, almost reaching the starting level. 4b samples show a decrease by approx. 50% with a fold change of 0.5. Samples for 6a show a fold change of around 0,8 and the consecutive samples for 6b show a drastic change in fold change. Generally, there seems to be a tendency for the samples for 2b, 4b and 6b to be lower than the results for 2a, 4a and 6a.
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Figure 27 - Graphical representation of the first trial fold change in relation to days, for the marker Muc2.
The samples 3a were used as a starting level since this measurement was the first day of the growth of the cells. 3a was therefore calculated to be 1 (See Fig. 28). The samples for 3b were lower, more specifically showed fold changes of 0.7 ±0.5. The samples taken from day 6 showed very low fold changes, at around 0.3. Samples for day 8a show a drastic increase in fold change, almost reaching the starting level value at 1. Samples for 10a, 13a and 13b are all above the starting level value whereas 10b lies well below 1.
Figure 28 - Graphical representation of the second trial fold change in relation to days for the gene marker Muc2.
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4.2.4.2. Klf4 From the graph, it can be observed that samples from day 2, namely 2b is found very close to the starting (See Fig. 29). The data for day 6b and 4a show fold change levels very close to the threshold as well, but these data lie below the threshold level of 1. The sample for day 4b shows the lowest level of fold change, being below 0.5. The highest level of fold change can be observed for sample from day 6a, reaching a fold change level of approximately 4.3.
Figure 29 - Graphical representation of the second trial for the gene marker KIf4. The graph illustrates the fold change in relation to days.
From the graph, it is observed that the highest levels of fold change are found for samples 3b and 8b (See Fig. 30). The lowest levels of fold change can be measured in samples for day 6, 8a and 10a. The starting level was established for sample 3a and used throughout the analysis. The samples for days 10 and 13 show a slightly increasing fold change trend.
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Figure 30 - Graphical representation of the second trial for the gene marker KIf4. The graph illustrates the fold change in relation to days.
4.2.5. Paneth Cells
4.2.5.1. Defa5 From the data, it can be observed that the lowest level of fold change can be found in the samples from day 6a. The level of fold change lies well below the starting level of 1 (See Fig. 31). The data for samples from day 2b are similar to the data for day 6b however, are found to be 0.6 in comparison to 0.55. The highest levels of fold change can be observed for the samples from day 4, where 4b showed fold change levels of approximately 1.6 and 4a showing fold change levels of 1.5. Generally, there is an increase in fold change levels halfway through the time and a consecutive decrease later in the development.
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Figure 31 - Graphical representation of the first trial for the gene marker Defa 5. The graph illustrates the fold change in relation to days.
The above data shows how the fold change is distributed. The results show an increase in fold change only from day 10, whereas fold change from day 3 to 8 including 10b and 13b are below the starting level of 1 (See Fig. 32). The only increase in fold change can be found in 13a and 10a. 13a has the highest fold change of 6, whereas 10a shows a fold change of approximately 2.5.
Figure 32 - Graphical representation of the second trial for the gene marker Defa 5. The graph illustrates the fold change in relation to days.
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4.2.6. Tuft Cells
4.2.6.1. Glfi1b The data results show a complete lack of fold change for the samples from day 2b and 6b. However, there is a drastic increase in fold change levels for samples from day 4a (See Fig. 33). The data from 4a show a fold change level of approximately 4.5. The results for the sample for day 4b show a lower amount of fold change. The level of fold change, decreases below the start level of 1, for the sample 6a. Generally, some or no expression is visible for the second day, increasing more than 4-fold on the fourth day and decreasing almost 5-fold between the second and the sixth day.
Figure 33 - Graphical representation of the first trial for the gene marker Glfi1b. The graph illustrates the fold change in relation to days.
From the results for the second trial run, it can be observed that none of the samples reach above the starting level value of 1 (See Fig. 34). There is no fold change up until day eight in which 8a and 10a show similar low expression levels around one. Samples from day 13a show a fold change level of 0.4 and in comparison, to samples from day 13b, there is a general decreasing trend in fold change levels.
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Figure 34 - Graphical representation of the second trial for the gene marker Glfi1b. The graph represents fold change based on qPCR results for the tuft cell genetic marker.
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5. Analysis of Electron Microscopy Images
The following images were former fixated organoid samples from mice, processed and contrived by Gert Helge Hansen and Lotte Niels-Christiansen. Their EM images will be used for cellular analysis and identification. These images will be compared with the qPCR results from the experiment.
5.1. EM Images Day 2 These structures are characterized by long cellular structures, attached to a basal membrane. The external ilium is located on the top left corner, and the internal cellular matrix is located towards the lower right area of the image. Within the internal cellular matrix, a round lighter vesicle and a basal membrane structure can be seen on the lower left corner. The darker external matter is cellular waste. Due to the presence of the microvilli, it can be assumed that the cell is an enterocyte. (See Fig. 35)
Figure 35- Microvilli of a mouse sample from day 2
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Nuclei formation can be seen on the top left corner and hormone vesicles is exhibited on the right. Although enteroendocrine cells are usually expected to be present later in the organoid development, such as on day 10, they were present in day 2 as shown here. The presence of original cells from the mouse intestine could be an explanation for why this is one of few specialized cells that are visible at this stage. (See Fig. 36)
Figure 36- An enteroendocrine cell from vertical slice.
5.2. EM Images Day 5 The golgi apparatus is present on the right, mid-center. The black coloured areas, are identified as ribosomes. The white folded structures to the right is the basolateral membrane between cells. (See Fig. 37)
Figure 37- Golgi apparatus from day 5
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The lumen is present as a circular structure and light shade in colour located in the middle. Paneth cells are shown as black circles on the right of the lumen encapsulated by a membrane. Endocrine cells are situated towards the basal membrane on the bottom. The large white rounded structure at the lower right corner shows a blurp, a cell undergoing apoptosis. The small structure protruding from the cellular structures at the lower left corner, shows an endocrine cell. (See Fig. 38)
Figure 38- Overview of an organoid on day 5.
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Two goblet cells, illustrated by lighter vesicles bound by a membrane structure are shown on the right. The brush border of the enterocytes is located in the top left corner of the image. The thread like structures at the top of the image are general membranes connecting the enterocytes. The small, circular white coloured structures, are vesicles. (See Fig. 39)
Figure 39- Goblet cells and enterocytes on day 5.
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On the right, a proliferating cell represented as larger black structures (chromosomes) can be seen. At this stage, the proliferating cell is dividing which is why the chromosomes are visible. The smaller black spots are ribosomes. (See Fig. 40)
Figure 40- Proliferating cells on day 5.
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5.3. EM Images from Day 10 A section cut of an enteroendocrine cell is illustrated. A nucleus is visible (top right corner) and the small black circles are hormone vesicles. The white linear structure towards the lower left corner, represents the basal membrane. (See Fig. 41)
.
Figure 41-From the EM image for the organoid cell structures for day 10 enteroendocrine cell.
The figure to the left, is a diagonal section of an organoid. The brush border of the enterocytes, protruding into the lumen at the bottom of the image. A multi-vesicular complex is visible in the upper left corner, shown as round dark structure containing light vesicles. (See Fig. 42)
Figure 42 - Enterocytes on day 10.
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6. Discussion
6.1. Reference Genes During the experimental process, three different types of reference genes were used. First trial was with the RPLP0 gene, which yielded non-viable results, and was therefore discarded. The RPLP0 gene was only run once in the primer trial run, to test the primers amplification efficiency. After the RPLP0 gene was discarded, the transcription factor II β(TFIIβ) gene was chosen instead. The choice was made on behalf of the reason that mammalian cells in general use this transcription factor for DNA amplification. This reference gene yielded usable results, but also non-expected results for the well samples without reverse transcriptase, which should not have happened. Since the TFIIβ primers can amplify DNA in the RT- wells, it is possible that they were able to amplify genomic DNA as well as the gene of interest. Even though there were unexpected results in the RT- samples, the results from the reference gene TFIIβ were used for the fold change calculations. This is because we expect the RT+ results to be from the organoids cDNA and not from genomic DNA.
When looking at in-silico results of the TFIIβ gene, we realised the primers are placed within exon 6 of the GTFIIβ on chromosome 3, mouse genome (GRCm 38/10mm). The placement of the forward and reverse primer will in this case only amplify approximately 7-10 nucleotides. Since the primers are only placed within an exon, we cannot be certain that the primers only amplify our chosen cDNA, but also have the ability to amplify the genomic DNA as mentioned earlier.
Due to the RT- results, we chose once more to test another gene, beta-2-microgobulin (B2m). During this test, all amplification curves yielded expected results, and all RT- gave no amplification or dissociation values, as was hoped. When calculating the fold changes, with the B2m and the TFIIβ, there are some differences in the fold changes, but the histograms follow the same curvature. We therefore still chose to use the TFIIβ gene as the reference, and compare to the B2m, if necessary. The difference between the two genes Ct values are displayed in Appendix 1, ranging from 3,38 to 0,7 cycles in difference between individual samples (sample 3aG is discarded due to a no Ct value for the TFIIβ sample). (See Appendix 1).
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6.2. Significant Dissociation and Amplification Curves
The amplification curve for the gene marker Muc2 displays a relatively exemplary sigmoidal trend, since the curves from each cycle have the same trend and only differ in its displacement to the right, which is in accordance to the number of cycles in between each sample. If the curves were found to overlap each other, it could indicate that no DNA has been amplified between the cycles, which is not shown here. When the curves differ too greatly, this could indicate that contamination could have taken place within the sample; also, not exhibited here. The grey line on the graph indicates that no amplification took place, possibly due to the lack of primers or cDNA. This is most likely because insufficient cDNA or primers would cause the inability of DNA annealing and further disable the enzymes to react to them in order to be replicated. In addition, the orange curve could also reveal that the sample contains a lower amount of cDNA since it took more cycles to reach the bottom-line threshold marker distinguishing between background noise and significant values. The lagging exponential phase, as compared to the other samples, indicates that there was not sufficient cDNA present for the primers and enzymes to amplify that specific fragment of DNA (See Fig. 15).
Besides the ideal sigmoidal amplification curve, the negative controls or no RT samples, checking for possible contamination or presence of undesired genomic DNA replication in this experiment also showed favorable results. The RT- curves were represented as plateaus, which indicate that there is no contamination and no presence of genomic DNA, which is a favorable result. This is because during cDNA synthesis, reverse transcriptase transcribes RNA to cDNA, capable of amplification in the PCR. Therefore, the absence of reverse transcriptase should disable amplification, and thus fluorescence would not be displayed. If a signal is exhibited, either contamination or genomic DNA must have been present which has undergone amplification. Due to the lack of fluorescence present far below the threshold line, it is considered background noise and not a considerable signal, which is an appropriate result as it indicates that there is no contamination and presence of genomic DNA, and therefore no amplification of undesired DNA fragments in those samples. As opposed to the RT- amplification curves, the RT- dissociation curves represent a peak for RT-, which is looks similar to the RT+ curve in amplitude. This could indicate the presence of genomic DNA, and the primer may have a target sequence that is similar to RT+ (See Fig. 16).
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6.3. Enterocytes As mentioned in the background enterocytes are important absorptive cells and make up 90% of all cells in the small intestine. The EM images of organoids, show that during the early development of the organoids, the majority of cells that are to be found are enterocytes. Furthermore, they are present in all stages of development, being present on day two, five and ten. This would give an expectation as to find the two genetic markers chosen for the enterocyte cell types Alpi and Lct, to show significant results in the qPCR reaction.
With regards to the Lct gene, the data showed that there was an abundant expression of the Lct gene later in the developmental stages of the organoid.
This is in accordance with what is expected, as the older the organoid becomes, the more of a complex biological system it will become. Therefore, the expression levels of more specialized metabolites, such as lactase, will be higher. In terms of the results for the gene Alpi, there was an overall trend where the qPCR showed that the Alpi expression is relatively even throughout the whole lifespan of the organoids. The Alpi expression and thus the presence of enterocytes in the organoid system throughout the development, is more or less steady. In accordance to the theoretical background of the enterocytes, the enterocytes are the majority of cells found in the intestines and constitutes the apical membrane structure, it is expected to see them throughout the whole organoid development. This is supported by the EM images (see Fig. 35,39 and 42 for respectively day 2, 5 and 10), seen for the early stages where the presence of enterocytes is presented. The qPCR results for both Lct and Alpi, show some expression early in the developmental stages, however the most prominent results are as mentioned, in the later stages of development.
6.4. Enteroendocrine Cells
The enteroendocrine cells only make up 1% of the epithelial cells in the intestines (Buffa et al. 1978). Since the results from the qPCR show that the overall expression of the two genetic markers Pyy and Gip is very low, it is an indication of the fact that the cells are limited throughout the whole development of the organoid.
The gene Gip, showed that the fold change values seen in trial one, proportional to gene expression, have decreased as days progressed from 4 to 6, which illustrates an inaccuracy since the expression of Gip was expected to increase as time passed and cells underwent
Page 69 of 81 differentiation (See Fig. 21). This can be accounted for by the observation under the light microscope of the cells after day 4 displays black dots which indicate cell death (See Appendix 4), in the first trial due to the inability to renew the media after every third day. However, as the theory of the cell’s nature and the results compared, show that the limited number of cells (as mentioned previously) that are detectable is a valid observation.
The fluctuation in data values for the gene Gip, may be due to the levels of cDNA being very low, this represented by the low amount of enteroendocrine cells present in the system.
In terms of the gene Pyy, the dataset from trial one exhibited an overall increase in fold change from day 4 to 6. This is consistent with successful cell differentiation (See Fig. 23). At day 2 we see a relative number of gene expression, which may indicate that there are original endocrine cells present in the sample. Once the samples reach day 4, there is a decrease in fold change which indicates that the original cells may begin to die. For the samples for day 6, there is a drastic increase in fold change which may indicate that newly produced endocrine cells may have grown in the organoid model. This result was anticipated since endocrine cells are highly specialized and measurable amounts are not expected until the model is fully developed (day 6-10). Furthermore, the endocrine cells only represent 1% of all intestinal cells (Buffa et al., 1978). This implicates that there is not a sufficient amount of endocrine cells for detectable gene expression, until later in the organoid development.
The pattern described for trial 1 also applies for trial 2, with regards to the presence of original cells and the production of new cells in an increasing fashion, throughout the experiment. However, sample 8a has an irregularly low fold change of 0.0000093, which can be considered an outlier caused by errors such as pipetting, which would cause insufficient cDNA into the well. In contrast, sample 8b displays consistency with the rest of the data.
In comparison to the EM images, it can be observed that the presence of enteroendocrine cells can be located throughout all developmental stages (see Fig. 36, 38 and 41, respectively, for days 2, 5 and 10). However, the number of enteroendocrine cells present for day 2 was low (only 1 cell was visible) in comparison to the number of enteroendocrine cells on day 5 and 10.
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6.5. Proliferating Cells
As it has been mentioned before, the Ki67 gene marker is associated with cell proliferation and is present during all the stages of the cell cycle. Proliferated cells replace injured or dead cells, as the organoid gets larger, the more cells there will be, and therefore more cells will undergo apoptosis and will need to be replaced. Both graphs show that Ki67 is present in all stages of development of the organoids. However, as the days go by the number of proliferated cells increases, especially in the second trial (See Fig. 26). Since 3b was one of the controls used to compare with the Ct values of the other samples, we can see an upregulation of proliferated cells for 8b and 13b, meaning that in these days’ cells have been replaced with new cells. In terms of the EM images, the presence of very few proliferating cells is observed (one proliferating cell is visible). This can be due to the fact that there is a very small chance of fixating the organoid for EM during the time in which the cell proliferation is visible (visible during meiosis). (See Fig. 40)
One may assume that there is a higher number of proliferating cells for larger organisms, and as such, the number of proliferating cells will depend on the species. It can furthermore be assumed that due to the size of the organoid system (relatively small) in comparison to the intestinal system of a mouse or human, less proliferating cells would be required for substitution of cells undergoing apoptosis. The results obtained from the second trial in the qPCR, also illustrate that the further in the organoid development the more proliferating cells will be present. This is consistent with the theory that the larger the organoid is in cellular mass, the more proliferating cells will be required for substitution of the apoptotic cells.
6.6. Goblet Cells The results for Muc2, show a trend in trial one, having a lower fold change number in comparison to the results for the second trial (See Fig. 27). The results indicate that there is a consistent level of gene expression representing steady amounts of goblet cells throughout the experiment.
During the second trial, it can be observed that from day 3 to day 6 there is a decrease in expression, which could be the result of original goblet cells dying.
From day 6 and onwards, there is a general increase in fold change which could be due to the growth of new goblet cells in the organoid model. The slight decrease in fold change on day
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13, could be a result of cells dying since the organoids were dissociating towards the end of their lifecycle.
With regards to the gene Klf4, the results in trial one shows that the fold change levels are relatively similar, with the exception of samples for day 6a. This could indicate relative amounts of goblet cells present during the first 4 days. At day 6, there is a drastic increase in fold change which indicates that there are four times the amount of goblet cells on day 6 compared to day 2.
The results from trial two, show a high level of fold change for samples 3b and 8b which could indicate higher levels of goblet cell growth. One could argue that 3b and 8b should be considered outliers since they show very high results in terms of fold change compared to the surrounding samples. From day 10 and onwards, a steady increase in fold change can be seen. This may be the result of the organoid model maturing, and furthermore allowing goblet cells to thrive. Since goblet cells are responsible for the production of mucins, and the formation of mucus in the intestines, it can be assumed that they should be present throughout all stages of the organoid development. However, the bigger the surface area of the intestines, the more mucus is required and furthermore, a higher amount of goblet cells are needed. In other words, the organoid model represents a smaller system during the first developmental days and as such, less goblet cells will be present. During the later developmental stages of the organoid model, the surface area increases and therefore the requirement for goblet cells increases as well. The presence of goblet cells can be observed at day five on the EM image (See Fig. 39).
6.7. Paneth Cells
The paneth cells produce antimicrobial substances that are used for protection of the stem cells. The paneth cells make up the stem cell niche, found in the bottom of the crypt from where all cells differentiate. It could therefore be expected that the paneth cells should be present throughout the entire organoid development. However, as more crypts develop, the more stem cell niches are required, and therefore more paneth cells are expected to appear.
In the first trial for Defa5, there is a significant expression of the gene marker from day 2 to day 4, and a decrease on day 6 (See Fig. 31). This may be a result of an increase in paneth cell growth since the organoid model is getting more developed and mature. The fold change is
Page 72 of 81 almost the same in day 2 and 6 which could be due to the overall organoid death, observed from day 6 and onwards (resulting in the termination of the first trial).
For the second trial, the graph shows that there is a low but somewhat consistent expression from day 3 to 8. This correlates well with the expectations with regards to fewer crypt numbers in relation to paneth cell numbers. From day 10 and onwards, there is a general decrease (if 13a is disregarded) in fold change which could be the result of the cells dieing. One could also hypothesize that the decrease in paneth cells from day 10 indicates a lack of growth factors. Since the paneth cell is the stem cell niche and therefore propagates the development of all other cell types, the death of paneth cells would therefore lead to the failure of the whole organoid system.
The EM images show that paneth cells were not developed in the early stages, but start appearing on day 5 (See Fig. 38) and day 10. The presence of paneth cells on day 5, are supported by the theory and the results for the qPCR during days 4-13.
6.8. Tuft Cells
The Gfi1b tuft cell genetic marker, shows irregular results in the qPCR amplification for the first trial. If the samples 2b and 6b do not show any amplification, they are regarded as having undetectable amplification levels and the tuft cell presence would only be on day four in the first trial. This could be explained by the fact that the tuft cells are not expected until later on in the organoid development since they are a cell type connecting the intestinal system and the nervous system. A possible explanation as to why the cell type would disappear at day six, could be because of the organoids dissociating at this stage in the first trial. This could be a results of the media not having been changed often enough which consequently affected the system, failing due to a lack of nutrients and an change in pH.
When considering the second trial in comparison to the first trial, the days that show high expression in one sample show no expression in the other. This could be due to one of two things; either the samples differ in expression as of biological chance of difference or the samples were not distributed evenly. However, since samples from the same day that differ, have been regarded as differences in biological circumstances in the two different organoids, the samples with no expression in the later development will be considered outliers.
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The second trial of the Gfi1b tuft cell marker differs from the other trials presented so far, in terms of it not showing sufficient expression levels on the first days. It is therefore not possible to make the calculations from which the graphs are based on, with the third day as the starting point in the fold change. The first day where expression is observed for this trial is the eighth day and this is therefore regarded as the starting point “1” and the rest calculated accordingly. Day eight and ten show somewhat similar expression levels, however still generally low and with no samples above one. This indicates that the tuft cells show limited presence in the organoid system which correlates with the 0.4% found in intestines (found later in the organoid development). There is limited expression on day thirteen, below 0.4-fold change compared the 1.0 fold change starting point. This means that there is a downregulation of the Gfi1b at day thirteen (See Fig. 34).
Overall the highest tuft cell expression is seen in the first trial on day four at a fold change of approximately 4.5. Both trials indicate that compared to the other cell types included in this project, the tuft cell shows low expression and only later in the organoid development (after day four in the first trial and not before day eight in the second trial). Since the tuft cell is a cell type that is not currently well studied and understood, it is difficult to state whether the results found are in accordance with what is expected. The EM images that have been analyzed during this project cannot supply anything to support or disapprove the data obtained on the tuft cells, as the morphology of the cell type is not available and it is therefore not possible to characterize the tuft cell microscopically. Despite of the lack of data to validate the findings, the presence of tuft cells in the organoid system is only an argument for the success and possibility of the organoid model’s representation of the small intestine.
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7. Conclusion
Through the experiment, developmental stages in the small intestine and the ability of the organoid model to simulate a “real life” or in vivo intestine were investigated. Through the research, it was found that the genetic markers Muc2, Defa6, Lct, Alpi and Ki67 showed signs of upregulation and thereby evidence that may indicate that different developmental stages can be found in the intestinal model. With regards to the genetic markers Gfi1b, Pyy and Gip, results showed that there were low expressions, which can be correlated to the low amount of the two cell types, enteroendocrine (1%) and tuft cells (0.4%). However, these genetic markers still illustrate a change in expression during the developmental stages.
Seen on the EM images, the presence of goblet, enteroendocrine, enterocytes, proliferating and paneth cells was established. Since different amounts of cells are observed on day 2, 5 and 10 this furthermore confirms that there are different developmental stages in the organoid system.
The two organoids, harvested for the same day, may have differed in size and surface area, thereby affecting the amounts of different cells as well as the maturation level of the system. This may explain why the two biological duplicates differed in levels of expression. In relation to the size of the organoid models, it was observed that the larger the system gets, the more difficult it will become for the model to sustain itself. Furthermore, the larger the system, the higher the requirement for all the cell types, including paneth cells. In other words, the organoid system is dependent on the stem cell niches to provide the model with newly differentiated cells. As such, when paneth cells die, it may cause the entire organoid system to collapse.
In conclusion, the organoid model may be assessed to be a viable model for the in vivo mice intestines. This conclusion is based on the evident results, with regards to the different cell developmental stages and differentiation in the organoid system. The model is accessible and may be easily applicable as a therapeutic, diagnostic and experimental tool.
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8. Errors and Limitations
As with any scientific research, there are errors and limitations which may have had an influence on the accuracy and reliability of the results that were obtained. Firstly, the reference gene TfI1b used in this experiment was not intron-spanning, which could have caused unforeseen issues.
Secondly, the stem cell gene-marker LGR5 yielded no fluorescence on the amplification curve in the primer test, which was supposed to display a signal to indicate replication of the gene. However, the absence of amplification curves indicates that the LGR5 primers were not functional.
Thirdly, as explained in the discussion (See section 6.8), there was contamination of samples in the negative controls or RT- samples, indicated by the signals presented on the amplification curves in the primer test. This could possibly be explained by a pipetting error in which an RT+ sample was possibly, accidentally added to the combined RT- solution, and therefore yielding amplification in terms of fluorescence. This can be a decent explanation, since the replication of RNA samples without reverse transcriptase is not possible, due to the absence of cDNA.
Fourthly, to reduce pipetting errors, master mixes were used. However, in a few of the samples, the solutions were pipetted directly into the 96 well plate, reducing the amount of primer added, to 0.5 µL. This increased the risk of error, however, there were no obvious effects of pipetting errors on the results.
Additionally, there may have been false amplification signals or fluorescence, since the primers can target other sequences than the ones present in the given cell types in the intestinal system. For an example, the negative control or RT- sample of Alpi showed amplification on the qPCR. This may have been due to the limitation in specificity between the primer and cDNA, amplifying genomic DNA and displaying false signal and presence of a specific cell type.
Furthermore, day 8 and onwards in the second trial set displayed cell death through the microscope. However, since our amplification and dissociation curves do not seem to be affected by this and show fine results, this most likely did not have a large impact, and thus is not a considerable error in our experiment.
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9. Future Perspectives
In order to improve the experimental setup and the general project, one may consider to change the following aspects. Future reproduction of this experiment should include more replications of the experiment and should be carried out including additional cell markers, in order to investigate the presence of tuft cells in depth. In order to more carefully investigate the developmental stages, smaller intervals of extracting organoids should be done as well as the renewal of media every second day must be followed.
Finally, EM for more samples should be obtained, in order to improve the quality of the results to accompany the qPCR results, which may overall contribute to a more complete analysis of the presence of the various cell types on different days. Carrying out an immuno-gold labelling test would allow us to further analyse and detect cell types that are not detectable at the EM level such as tuft and stem cells.
10. Acknowledgements
The experimental study was performed at Roskilde University and was part of the 5th semester’s project within medicinal biology. We wish to thank our supervisor Jesper T. Troelsen as well as our laboratory technician Helle Jensen, for providing the necessary guidance and aid in the laboratory processes. Finally, we wish to thank Gert Helge Hansen and Lotte W. Niels-Christiansen at the Panum Institute, for providing, interpreting as well as analyzing EM images.
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11. Reference List Barker, Nick, Johan H van Es, Jeroen Kuipers, Pekka Kujala, Maaike van den Born, Miranda Cozijnsen, Andrea Haegebarth, et al. 2007. “Identification of Stem Cells in Small Intestine and Colon by Marker Gene Lgr5.” Nature 449 (7165): 1003–7. doi:10.1038/nature06196. Bengmark, S. 1998. “Ecological Control of the Gastrointestinal Tract. The Role of Probiotic Flora.” Gut 42 (1). BMJ Publishing Group Ltd and British Society of Gastroenterology: 2–7. doi:10.1136/GUT.42.1.2. Bjerknes, Matthew, and Hazel Cheng. 2006. “Intestinal Epithelial Stem Cells and Progenitors.” Methods in Enzymology 419 (2000): 337–83. doi:10.1016/S0076-6879(06)19014-X. Buffa, R, C Capella, P Fontana, L Usellini, and E Solcia. 1978. “Types of Endocrine Cells in the Human Colon and Rectum.” Cell and Tissue Research 192 (2): 227–40. http://www.ncbi.nlm.nih.gov/pubmed/699014. Charles L. Bevins and Nita H. Salczman. 2011. “Box 2 : Paneth Cells, Antimicrobial Peptides and Maintenance of Intestinal Homeostasis : Nature Reviews Microbiology.” http://www.nature.com/nrmicro/journal/v9/n5/box/nrmicro2546_BX2.html. Cornick, Steve, Adelaide Tawiah, and Kris Chadee. 2015. “Roles and Regulation of the Mucus Barrier in the Gut.” Tissue Barriers 3 (1–2). Taylor & Francis: e982426. doi:10.4161/21688370.2014.982426. Crawley, Scott W, Mark S Mooseker, and Matthew J Tyska. 2014. “Shaping the Intestinal Brush Border.” The Journal of Cell Biology 207 (4): 441–51. doi:10.1083/jcb.201407015. CREAMER, B, R G SHORTER, and J BAMFORTH. 1961. “The Turnover and Shedding of Epithelial Cells. I. The Turnover in the Gastro-Intestinal Tract.” Gut 2 (2). BMJ Publishing Group Ltd and British Society of Gastroenterology: 110–18. doi:10.1136/GUT.2.2.110. DeBerardinis, Ralph J, Julian J Lum, Georgia Hatzivassiliou, Craig B Thompson, S. Adhikary, M. Eilers, D. Astuti, et al. 2008. “The Biology of Cancer: Metabolic Reprogramming Fuels Cell Growth and Proliferation.” Cell Metabolism 7 (1). Elsevier: 11–20. doi:10.1016/j.cmet.2007.10.002. Dedhia, Priya H., Nina Bertaux-Skeirik, Yana Zavros, and Jason R. Spence. 2016. “Organoid Models of Human Gastrointestinal Development and Disease.” Gastroenterology 150 (5): 1098–1112. doi:10.1053/j.gastro.2015.12.042. Deplancke, B, and H R Gaskins. 2001. “Microbial Modulation of Innate Defense: Goblet Cells and the Intestinal Mucus Layer.” The American Journal of Clinical Nutrition 73 (6). American Society for Nutrition: 1131S–1141S. http://www.ncbi.nlm.nih.gov/pubmed/11393191. Eaton, S B, and M Konner. 1985. “Paleolithic Nutrition. A Consideration of Its Nature and Current Implications.” The New England Journal of Medicine 312 (5): 283–89. doi:10.1056/NEJM198501313120505. Fatehullah, Aliya, Si Hui Tan, and Nick Barker. 2016. “Organoids as an in Vitro Model of Human Development and Disease.” Nature Cell Biology 18 (3). Nature Research: 246–54. doi:10.1038/ncb3312. Freeman, James A. 1966. “Goblet Cell Fine Structure.” The Anatomical Record 154 (1). Wiley Subscription Services, Inc., A Wiley Company: 121–47. doi:10.1002/ar.1091540111. Gagne, David, Anders Bondo Dydensborg, Inga C Teller, Isabelle Degongre, Jin Q Cheng, Naoya Fujita, Takashi Tsuruo, Karine Valle, and Pierre H Vachon. 2004. “Human Intestinal Epithelial Cell Survival and Anoikis” 279 (42): 44113–22. doi:10.1074/jbc.M405323200.
Page 78 of 81
Gerbe, François, Johan H van Es, Leila Makrini, Bénédicte Brulin, Georg Mellitzer, Sylvie Robine, Béatrice Romagnolo, et al. 2011. “Distinct ATOH1 and Neurog3 Requirements Define Tuft Cells as a New Secretory Cell Type in the Intestinal Epithelium.” The Journal of Cell Biology 192 (5): 767–80. doi:10.1083/jcb.201010127. Gerbe, François, Catherine Legraverend, and Philippe Jay. 2012. “The Intestinal Epithelium Tuft Cells: Specification and Function.” Cellular and Molecular Life Sciences : CMLS 69 (17): 2907– 17. doi:10.1007/s00018-012-0984-7. Guarner, Francisco, and Juan-R Malagelada. 2003. “Gut Flora in Health and Disease.” Lancet (London, England) 361 (9356): 512–19. doi:10.1016/S0140-6736(03)12489-0. Hackney, J D, R F Bils, Y Takahashi, D E Rounds, and C R Collier. 1968. “Organotypic Culture of Mammalian Lung--Studies on Morphology, Ultrastructure, and Surfactant.” Aspen Emphysema Conference 9: 13–34. http://www.ncbi.nlm.nih.gov/pubmed/4881137. HALLY, A D. 1958. “The Fine Structure of the Paneth Cell.” Journal of Anatomy 92 (2). Wiley- Blackwell: 268–77. http://www.ncbi.nlm.nih.gov/pubmed/13525239. Hansson, Gunnar C. 2012. “Role of Mucus Layers in Gut Infection and Inflammation.” Current Opinion in Microbiology 15 (1). NIH Public Access: 57–62. doi:10.1016/j.mib.2011.11.002. Hillier, S L, M A Krohn, S J Klebanoff, and D A Eschenbach. 1992. “The Relationship of Hydrogen Peroxide-Producing Lactobacilli to Bacterial Vaginosis and Genital Microflora in Pregnant Women.” Obstetrics and Gynecology 79 (3): 369–73. http://www.ncbi.nlm.nih.gov/pubmed/1738516. Hitt, Emma. 2013. “Wnt Signaling Inhibition: Will Decades of Effort Be Fruitful at Last?” OncLive. http://www.onclive.com/publications/oncology-live/2012/december-2012/wnt-signaling- inhibition-will-decades-of-effort-be-fruitful-at-last. Hooper, L V, and J I Gordon. 2001. “Commensal Host-Bacterial Relationships in the Gut.” Science (New York, N.Y.) 292 (5519): 1115–18. http://www.ncbi.nlm.nih.gov/pubmed/11352068. Huch, Meritxell, and Bon-Kyoung Koo. 2015. “Modeling Mouse and Human Development Using Organoid Cultures.” Development 142 (18). Hynds, Robert E, and Adam Giangreco. 2013. “Concise Review: The Relevance of Human Stem Cell-Derived Organoid Models for Epithelial Translational Medicine.” Stem Cells (Dayton, Ohio) 31 (3). Europe PMC Funders: 417–22. doi:10.1002/stem.1290. Jeon, Min Kyung, Christina Klaus, Elke Kaemmerer, and Nikolaus Gassler. 2013. “Intestinal Barrier: Molecular Pathways and Modifiers.” World Journal of Gastrointestinal Pathophysiology 4 (4). Baishideng Publishing Group Inc: 94–99. doi:10.4291/wjgp.v4.i4.94. Jiang, H Q, N A Bos, and J J Cebra. 2001. “Timing, Localization, and Persistence of Colonization by Segmented Filamentous Bacteria in the Neonatal Mouse Gut Depend on Immune Status of Mothers and Pups.” Infection and Immunity 69 (6): 3611–17. doi:10.1128/IAI.69.6.3611- 3617.2001. Juven, B J, R J Meinersmann, and N J Stern. 1991. “Antagonistic Effects of Lactobacilli and Pediococci to Control Intestinal Colonization by Human Enteropathogens in Live Poultry.” The Journal of Applied Bacteriology 70 (2): 95–103. http://www.ncbi.nlm.nih.gov/pubmed/2019552. Klebanoff, S J, S L Hillier, D A Eschenbach, and A M Waltersdorph. 1991. “Control of the Microbial Flora of the Vagina by H2O2-Generating Lactobacilli.” The Journal of Infectious Diseases 164 (1): 94–100. http://www.ncbi.nlm.nih.gov/pubmed/1647428. Koo, Bon Kyoung, and Hans Clevers. 2014. “Stem Cells Marked by the R-Spondin Receptor LGR5.” Gastroenterology 147 (2). Elsevier, Inc: 289–302. doi:10.1053/j.gastro.2014.05.007.
Page 79 of 81
Lodish H, Baltimore D, Berk A, Zipursky. 2000. “Apoptosis, Cell Cycle, and Cell Proliferation Tools for Assessing Cell Events Life, Death, and Cell Proliferation.” Mowat, Allan McI. 2003. “Anatomical Basis of Tolerance and Immunity to Intestinal Antigens.” Nature Reviews. Immunology 3 (4): 331–41. doi:10.1038/nri1057. NAKAYA, Rintaro. 1984. “Role of Bifidobacterium in Enteric Infection.” Bifidobacteria and Microflora 3 (1). Japan Bifidus Foundation: 3–9. doi:10.12938/bifidus1982.3.1_3. Perdigon, Gabriela, Susana Alvarez, Maria E. Nader De Macias, Maria E. Roux, and Aida Pesce de Ruiz Holgado. 1990. “The Oral Administration of Lactic Acid Bacteria Increase the Mucosal Intestinal Immunity in Response to Enteropathogens.” Journal of Food Protection 53 (number 5). International Association for Food Protection: 404–10. Potten, C S, C Booth, and D M Pritchard. 1997. “The Intestinal Epithelial Stem Cell: The Mucosal Governor.” International Journal of Experimental Pathology 78 (4): 219–43. doi:10.1046/j.1365-2613.1997.280362.x. Radtke, F., and Hans Clevers. 2005. “Self-Renewal and Cancer of the Gut: Two Sides of a Coin.” Science 307 (5717): 1904–9. doi:10.1126/science.1104815. Rao, Tata Purushothama, and Michael Kühl. 2010. “An Updated Overview on Wnt Signaling Pathways: A Prelude for More.” Circulation Research 106 (12): 1798–1806. doi:10.1161/CIRCRESAHA.110.219840. Rockey, Don C., and John P. Cello. 1993. “Evaluation of the Gastrointestinal Tract in Patients with Iron-Deficiency Anemia.” New England Journal of Medicine 329 (23): 1691–95. doi:10.1056/NEJM199312023292303. Rowland, Kathryn J, Pamela M Choi, and Brad W Warner. 2013. “The Role of Growth Factors in Intestinal Regeneration and Repair in Necrotizing Enterocolitis.” Seminars in Pediatric Surgery 22 (2). NIH Public Access: 101–11. doi:10.1053/j.sempedsurg.2013.01.007. Sanderson, I R, and W A Walker. 1993. “Uptake and Transport of Macromolecules by the Intestine: Possible Role in Clinical Disorders (an Update).” Gastroenterology 104 (2): 622–39. http://www.ncbi.nlm.nih.gov/pubmed/8425707. Sato, Toshiro, Hans Clevers, L. G. van der Flier, H. Clevers, H. Cheng, C. P. Leblond, N. Barker, et al. 2013. “Growing Self-Organizing Mini-Guts from a Single Intestinal Stem Cell: Mechanism and Applications.” Science 340 (6137): 241–60. doi:10.1126/science.1234852. Sato, Toshiro, Johan H van Es, Hugo J Snippert, Daniel E Stange, Robert G Vries, Maaike van den Born, Nick Barker, Noah F Shroyer, Marc van de Wetering, and Hans Clevers. 2011. “Paneth Cells Constitute the Niche for Lgr5 Stem Cells in Intestinal Crypts.” Nature 469 (7330). Nature Publishing Group: 415–18. doi:10.1038/nature09637. Sato, Toshiro, Robert G Vries, Hugo J Snippert, Marc van de Wetering, Nick Barker, Daniel E Stange, Johan H van Es, et al. 2009. “Single Lgr5 Stem Cells Build Crypt-Villus Structures in Vitro without a Mesenchymal Niche.” Nature 459 (7244). Nature Publishing Group: 262–65. doi:10.1038/nature07935. Specian, R D, and M G Oliver. 1991. “Functional Biology of Intestinal Goblet Cells.” The American Journal of Physiology 260 (2 Pt 1): C183-93. http://www.ncbi.nlm.nih.gov/pubmed/1996606. Uhlig, Holm H, Fiona Powrie, LV Hooper, JI Gordon, F Guarner, JR Malagelada, F Shanahan, et al. 2003. “Dendritic Cells and the Intestinal Bacterial Flora: A Role for Localized Mucosal Immune Responses.” The Journal of Clinical Investigation 112 (5). American Society for Clinical Investigation: 648–51. doi:10.1172/JCI19545. Umar, Shahid. 2010. “Intestinal Stem Cells.” Current Gastroenterology Reports 12 (5): 340–48.
Page 80 of 81
doi:10.1007/s11894-010-0130-3. Vieira, Gabriella Cunha, S Chockalingam, Zsombor Melegh, Sally Malik, Marianna Szemes, Ji Hyun Park, Abderrahmane Kaidi, et al. 2005. “LGR5 Regulates pro-Survival MEK / ERK and Wnt / β-Catenin Signalling in Neuroblastoma Proliferative” 6 (37). Westphalen, C Benedikt, Samuel Asfaha, Yoku Hayakawa, Yoshihiro Takemoto, Dana J Lukin, Andreas H Nuber, Anna Brandtner, et al. 2014. “Long-Lived Intestinal Tuft Cells Serve as Colon Cancer-Initiating Cells.” The Journal of Clinical Investigation 124 (3): 1283–95. doi:10.1172/JCI73434. Widmaier, Eric P., Hershel Raff, and Kevin T. Strang. 2016. Vander’s Human Physiology : The Mechanisms of Body Function. Xinaris, Christodoulos, Valerio Brizi, and Giuseppe Remuzzi. 2015. “Organoid Models and Applications in Biomedical Research.” Nephron 130 (3): 191–99. doi:10.1159/000433566. Zoetendal, Erwin G, Atte von Wright, Terttu Vilpponen-Salmela, Kaouther Ben-Amor, Antoon D L Akkermans, and Willem M de Vos. 2002. “Mucosa-Associated Bacteria in the Human Gastrointestinal Tract Are Uniformly Distributed along the Colon and Differ from the Community Recovered from Feces.” Applied and Environmental Microbiology 68 (7). American Society for Microbiology: 3401–7. doi:10.1128/AEM.68.7.3401-3407.2002.
Page 81 of 81