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STEM CELLS (Discuss how the cellular microenvironment/niche influences…

- - - - Stimulatory (permissive) or inhibitory (restrictive) signals
      - Example: Paneth cells in the intestinal crypts to regulate Lgr5+ stem cells
      - Example: MSCs regulating HSC differentiation and proliferation
        
        Growth factors
        
        Anti-inflammatory cytokines
        
        Anti-fibrosis
      - Example: Liver stem cells --> Cholangiocytes (differentiation promoted by TGF-beta) and Hepatocytes (differentiation promoted by Notch signalling and ECM proteins)
  - - - Tissue of origin
      - Genetic background
      - Differentiation protocols
      - Nomenclature
      - Transcriptional noise, inter-clonal variation
      - Characterisation/definition
        
        Some researchers simply use plastic adherence as marker for MSC
        
        Current guidelines: 3 requirements
        
        Plastic adherence
        
        Differentiation into adipocytes, chondrocytes and osteoblasts
        
        Markers: CD105+, CD90+, CD73+
      - Effective extrinsic signals
  - - - NOT HAVING A GOOD NICHE - FBR
        
        Adsorbs layer of denatured proteins
        
        Nts and macrophages aggregates around denatured proteins
        
        Forms multinucleated giant cells
        
        Release of cytokines recruits fibroblasts
        
        Collagenous fibrosis, formation of acellular collagenous bag
      - Vasculature
        
        In vivo bioreactors: angiogenesis by planting a blood vessel in bioreactor surgically
        
        Signalling molecules, e.g. VEGF - consider release kinetics
    - - Bioreactors that e.g. facilitating stretching for myocytes
      - Stiffness
      - Porosity for delivery of soluble factors
    - - Layer by layer technique regulates release of heparin and bFGF
      - Sandwiching protects from degradation of soluble factors
      - Inkjetting technology and thermally induced phase separation
        
        Modulates rate of delivery/release kinetics
        
        Spheres made at varying levels of porosity and cross-linker levels as well as capping layers
        
        bFGF vs alpha MSH
        
        bFGF is bigger than alpha MSH
        
        Crosslinking influences bFGF
        
        No of capping layers influences aMSH
- - - - FACS
        
        Lgr5+ Gut crypt stem cells
        
        Axin2 + alveolar epithelial cells
        
        CD34+ HSCs
        
        CD73+, CD90+, CD105+ MSC, negative for myeloid and lymphoid markers
      - Surrogate clonogenic assays
        
        Will a single stem cell differentiate into multiple cell types or a homogeneous population? Characterising potential
        
        Different colony characteristics (e.g. BFU, CFU) correlated with certain potentials
        
        Surrogate = modelling in vivo
    - - Animal model
        
        Congenic mouse model
        
        Non-competitive re-population assay
        
        Competitive repopulation assay
        
        Competitor is a standard, or radioprotector
        
        K/O or pertubation model
        
        Repopulate with stem cells to see how well stem cells can repair
        
        Lineage tracing!
- - - - Knockouts
        
        Working out contribution of gene to disease
      - Insert disease polymorphism into healthy individual
      - Insert reporter gene
        
        Lineage tracing
      - Example: Parkinson's Disease
        
        K/O of LRRK2 and SCNA to work out contribution of these polymorphism to disease
        
        Insert LRRK2 and SCNA into normal background to observe contribution to disease and whether there are other precipitating factors
        
        Insert LRRK2 OR SCNA separately - are these polymorphisms alone enough to produce diseased phenotype
      - Emphasis now on using well defined singular genetic background to study individual genes as opposed to inconsistency
      - Characterisation of differentiation protocols e.g. dopaminergic neuron development - k/o of different genes and observing effect on development of neurons in specialised areas of the brain
    - - Examples
        
        Luciferase (bio luminescent)
        
        Pros:High through put screening of small molecular drugs
        
        Con: needs a substrate
        
        Fluorescent proteins (GFP, mCherry)
        
        Pros: no substrate required
        
        Cons: can be weakly or unpredictably expressed
        
        beta-lactamase
        
        Pros: good for live cell imaging
      - Why are reporters used?
        
        Guide in vitro control of stem cell differentiation
        
        Observing drug efficacy
        
        Lineage tracing
        
        Allows straightforward readout of complex models
  - - - Examples
        
        Schizophrenic patient iPSCs
        
        Model Schizophrenia
        
        Test drug efficacy in improving neuronal connectivity - done using rabies model looking at synaptic integrity
        
        Rhett's syndrome
        
        Alzheimer's
      - Limitations
        
        Polygenic diseases
        
        Low penetrance and late onset
        
        Alzheimers
        
        PSEN1, PSEN2, APP - highly penetrant/causative but <5% have this gene
        
        APOE4 and TREM2 - intermediately penetrant/medium risk
        
        BIN1 - low penetrance but high frequency in population
        
        Used GWAS to identify these but can use k/o studies to investigate contribution further
        
        Parkinsons
        
        Poorly replicated microenvironment
        
        Inconsistent genetic backgrounds
        
        Epigenetics disregarded
      - Why are they used?
        
        Animal models are less predictive
        
        Grown efficiently with robust differentiation protocols
        
        Consistency
        
        Ease of genetic manipulation
    - - Major issue in drugs is cardiotoxicity
        
        due to amine groups
        
        Dog models have poor predictive capacity (50%) whereas iPSC models have predictive capacity that is 95% accurate
      - Current approach is reductionist
        
        Using biologically irrelevant immortalised cells (transfected with receptor or interest that they're trying to target) - not reflective of normal biology
        
        over expression of target can lead to signalling artefacts (noise)
      - using enzymatic reporters to quantify gene expression
        
        e.g. inducing Lmx1a expression through use of different kinase inhibitors using luciferase (sensitive plate based assay)
      - Organoids vs intermediate systems (combining cells) vs individual cells
        
        Organoids
        
        Cons: Only epithelial cells, cannot be replicated well --> therefore not suitable for drug testing (can't test multiple drugs on one organoid), not suitable for high throughput screening
        
        Pros: 3D structure, multiple cell types
        
        Intermediate systems
        
        Lack of 3D structure
        
        Poorly replicates micro environment
      - iPSCs or ESCs allow for better lead selection and phenotypic screening
    - - Specific to individual as opposed to generalised disease model