Practical - Simulated research project Flashcards
13.1. [practical]
Question 1 (Research strategy – open question that gave you the opportunity to speculate on the topic): give a short research strategy (step-wise protocol) how you will acquire a molecular signature of idiopathic ASD using iPSC-derived brain organoids. What are the steps involved?
(1) Collection and preparation of material; fibroblast-derived iPSCs obtained from skin biopsies of four families (idiopathic ASD proband with increased head circumference; male individuals; parents not affected: likely de novo mutation) and four unaffected, first-degree male family members (Figure 1) were differentiated into organoids (Figure 3).
13.2. [practical] Question 2 (Approach):
(2) Explore molecular ASD organoid signatures at the DNA-, RNA- or protein level?
Approach at the DNA level: single-nucleotide variation (SNV) or copy number variation (CNV) microarrays; whole-genome (exome) DNA sequencing
Approach at the RNA level: mRNA expression profiling by microarrays or RNA-sequencing (RNA-seq)
Approach at the protein level: (phospho)proteomics (mass spectrometry)
Approach at the DNA level:
Identify a (deleterious) genomic variation contributing to ASD: whole-genome sequencing of fibroblasts/iPSC genomic DNAs for SNV and CNV discovery: no obvious genomic alterations (no do novo rare SNVs and/or CNVs);
Why genomic DNAs from fibroblasts, iPSCs and organoids?: any experimental manipulation (reprogramming; in vitro culturing) may introduce additional genomic variants not linked to ASD; so best choice (close to in vivo): fibroblasts.
(b) Approach at the RNA level: mRNA expression profiling by microarrays or RNA-seq (has become our choice).
(c) Approach at the (phospho)protein level: proteomics, and in particular phosphoproteomics, is not yet fully developed on a genome-wide scale (i.e. much less developed than those at the DNA- and RNA-levels) and clearly more difficult than DNA/RNA work: also: proteins display post-translational modifications; still: proteins are directly relevant for identifying and validating the molecular pathway/signature involved.
13.3. [practical] Question 3 (Brain region related to the generated organoid; regional specification):
Approach: RNA-seq of control (better than ASD) iPSC-derived organoid and compare with database transcriptomes of human brain regions (BrainSpan atlas of 16 male/female pre- and postnatal (sub)cortical human brain structures).
Result: Organoid transcriptome most similar to human dorsal telencephalon (cerebral cortex and hippocampus) transcriptomes (Figure 4).
RNA-seq advantages over microarray:
More (new?) transcript sequences identified (whole transcriptome; noncoding RNAs)
Genetic variations identified
More quantitative
Transcriptome analysis
Approach: RNA-seq of iPSC-derived organoids from four ASD/four respective fathers.
Result: Terminal differentiation day (TD) 11: 1,062 differentially expressed genes (DEGs);
TD31: 2,203 DEGs.
13.4. [practical] first next step
Validation by quantitative polymerase chain reaction (qPCR), a relatively easy, cheap and fast method. Selection of RNAs/genes to be validated: randomly select a number (10 or so) from the list of differentially expressed RNAs/genes; use same RNA samples for qPCR- as used for RNA-seq-analysis. Result:0.98 correlation coefficient; 100% concordance in direction of change (Table 1).
13.5. [practical] Question 5 (in Table 1, DLX1/2; GAD1/2; Vglut1/2: small gene families; specific mRNA quantification by qPCR: primer pairs directed towards the 3’-untranslated regions (3’ –UTRs). Why?):
Hint: members of a gene family are structurally related (at both the nucleotide and amino-acid sequence level).
Answer: gene family members are structurally related, especially in the protein-coding regions, so it is safer to design the primer pairs to a region in the mRNAs that in general is less conserved, i.e. the 3’ –UTR; exceptions to choose from in the 3’-UTR are miRNA-binding sites (they are in general well conserved).
PCR:
Traditional or Reverse Transcriptase (RT-PCR) method: final phase or end-point product detection on agarose gel and quantified by densitometric scanning
Quantitative (q) PCR
13.6. [practical] Question 6:
Potential problem with quantification by RT-PCR? How circumvented with qPCR?
.Potential problem with quantification by RT-PCR?
Answer: Plateau in the amount of PCR-product (already at 20 or 25 cycles); gives only a semi-quantitative
estimate; partial solution: use various cycle numbers or various cDNA dilutions.
How circumvented with qPCR?
Answer:
Real-time qPCR (monitor the progress of the PCR as it occurs, i.e., in real time): continuously determines the amount of PCR-product (collect data while the reaction is proceeding). Measurement is at the exponential phase of the PCR reaction (i.e., the optimal point for analyzing data).
Gene co-expression network analysis:
24 modules of coexpressed genes (corresponding to about 17,298 genes) across ASDs and controls at TD11 and TD31 determined with network analysis software program(s), e.g. WGCNA (Weighted Gene Co-expression Network Analysis)
Modules’ eigengenes (i.e., the first principal component of theexpression profiles of themodule’s genes, representing the module by an expression value) and assess their changes over time (TD11; TD31) and across diagnosis (Figure 6)
Enriched in upregulated genes (Figure 7):
Blue module: ‘neuronal differentiation’ (Gene Ontology, GO, term)
Magenta module: ‘regulation of transcription’
Enriched in upregulated genes only at TD31:
Brown module: ‘synaptic transmission’
Functionally validate blue and brown modules
Approach: morphometric cellular analyses and immunostaining for the markers
MAP2 (microtubule-associated protein 2) for neuronal differentiation
VGAT (vesicular GABA transporter) for inhibitory neurons
VGLUT1 (vesicular glutamate transpoter-1) for excitatory neurons (Figure 8
13.7. [practical] Question 7 (Conclusion from Figure 8?):
Answer - In ASD-derived neurons:
MAP2: significant increase in neuronal maturation; in agreement with the upregulated expression of the blue module, accelerated or increased neuronal differentiation in ASD
VGAT: significant increase in inhibitory synapses
VGLUT1: no significant changes in excitatory synapses
Bias for differentiation into specific neuronal subtypes?
Approach: use telencephalic developmental transcription factors (TFs; from blue and magenta modules) as markers (Figure 9).
Result:
TBR1 (cortical excitatory neuron precursors of layer 6 neurons): not significantly different
CTIP2 (early-born layer 5 neurons): not significantly different in ASD
DLX1-2 (GABAergic inhibitory neuronal fate marker): increased significantly in ASD
GAD1/GAD67 (GABA-synthesizing enzyme): increased significantly in ASD organoids compared to those from unaffected family members
Bias for differentiation into specific neuronal subtypes?
Approach: use telencephalic developmental transcription factors (TFs; from blue and magenta modules) as markers (Figure 9).
Result:
TBR1 (cortical excitatory neuron precursors of layer 6 neurons): not significantly different
CTIP2 (early-born layer 5 neurons): not significantly different in ASD
DLX1-2 (GABAergic inhibitory neuronal fate marker): increased significantly in ASD
GAD1/GAD67 (GABA-synthesizing enzyme): increased significantly in ASD organoids compared to those from unaffected family members
13.8. [practical] Question 8 (Quantification of GAD1 and GAD2 proteins on Western blot (Figure 10)?):
Answer:
Densitometric scanning of the protein bands
Necessary: quantification relative to the bands of the housekeeping protein GAPDH
Result:
Increased protein expression of the GABAergic inhibitory interneuron marker proteins GAD1/2
Together, the cellular analyses strongly suggest an overproduction of progenitors and neurons of the GABAergic lineage as well as an altered balance between the number of excitatory and inhibitory neurons in ASD organoids (Figure 9, below, middle figure, framed
Refinement of our understanding of the functional annotations of the upregulated magenta ‘neuronal’ module.
Approach:
Investigate its (transcription-related) canonical pathway annotation
overall: magenta-module genes function in the transcriptional regulation of cell fate and cell proliferation in the forebrain
Select one of the significantly upregulated TF genes in the magenta module: TF crucial for acquisition of neural cell fates and precursor cell proliferation in the telencephalon
13.9. [practical] Question 9 (Which considerations/criteria do you propose for selection of the most attractive hub gene from Figure 11/12? Important decision – follow-up is time consuming):
Answer - FOXG1 (arrow in Figure 12):
Would be good to refine the network by extensive literature analyses as a first step in the selection of the key gene (key target) in the network/pathway; compound modulating such a key target could (eventually) result in autism drug
One of the top 100 magenta hub genes
Consistently among the top 10 upregulated genes (8.5-/13-fold expression increase at TD11 and TD31, resp.)
TF important for telencephalon development
Knock-in/-out cell/animal models available?
Loss-of-function FOXG1 mutations occur in atypical Rett syndrome patients (an ASD-related disorder) and confer a small brain size; ASDs studied here have large brain size: FOXG1 may be, at least in part, involved in brain size and social disability phenotypes
13.10. [practical] Question 10 (Approach to test the hypothesis that abnormally high levels of FOXG1 and its downstream genes could be responsible for the phenotypic abnormalities identified in neuronal cells of macrocephalic ASD patients?):
Answer:
Generate four stable iPSC lines from ASD-derived iPSC line 07-P#9 to downregulate FOXG1 (using lentiviruses carrying short hairpin RNAs – shRNAs – specifically targeting FOXG1 or a non-targeting negative control shRNA consisting of a scrambled oligonucleotide sequence)
Test whether some of the neurobiological alterations are reverted
13.11. [practical] Question 11:
How to check the degree of downregulation by shRNA (at the RNA as well as the protein level)?
Answer:
qPCR analyses at TD11 (Figure 13): two FOXG1-targeting shRNAs (shRNA-2 and 3) downregulate FOXG1 mRNA expression; FOXG1-targeting shRNA-1 does not result in FOXG1 downregulation
immunostaining for FOXG1 (Figure 14): shRNA-2 and -3 downregulate also at the protein level
Why don’t we use just one but rather three shRNAs targeting FOXG1?
Answer:
The effectiveness of mRNA downregulation by shRNAs is difficult to predict: use three different shRNAs, each directed towards a specific region within FOXG1 mRNA (in general, one needs at least two working shRNAs for a proper downregulation study)
13.12. [practical] Question 12 (Approach to prove that FOXG1 causes the overproduction of GABAergic interneurons observed
In the ASD-derived organoids?):
Answer:
AnalyzeGABAergic marker expression following FOXG1 downregulation
qPCR: downregulation of GABAergic markers DLX1, DLX2, and GAD1, but not the dorsal forebrain marker PAX6 (Figure 15)
Immunostaining: The normal levels of GABAergic neuronal differentiation (DLX1-2- and GAD1-positive cells) are restored (Figure 16; shRNA-3; overproduction with shRNA-C)
No or minor effects on the transcript/protein expression levels of dorsal forebrain markers (such as PAX6), or on TFs directing cortical excitatory neuron differentiation (such as TBR1) (Figures 15 and 16)
Thus:
FOXG1 is involved, at least in part, in causing the overproduction of neurons of the GABAergic lineage found in ASD proband-derived organoids
The early increase in proliferation of GABAergic neuronal progenitor cells gives rise to an increased proportion of mature GABAergic interneurons
FOXG1 RNAi restores both these early and late effects to levels comparable to those found in unaffected family members
Upregulated FOXG1 expression in ASD neural cells is driving an early proliferative effect in neuronal precursor cells of the GABAergic lineage
FOXGI is part of the molecular signature of idiopathic ASD
Highlights
iPSC-derived telencephalic organoids reflect human midfetal telencephalic development
Inhibitory neurons are overproduced in organoids from patients with idiopathic ASD
Overproduction of inhibitory neurons is caused by increased FOXG1 gene expression
13.13. [practical] Question 13 (Major overall flaw/shortcoming of our study?):
Hint: Type of differentiated iPSCs used to obtain brain organoids and the complexity of the brain.
Answer:
Organoids used here: radial glia, intermediate progenitors and neurons; the length of the time of differentiation was relatively short (maximum of 31 days of terminal differentiation, TD31), which limits the diversity of brain cell types generated
Brain: more cell types (e.g. oligodendrocytes, microglia and astrocytes; not co-developing alongside the neuronal ones and are therefore not represented in the organoids)
Thus: organoid recapitulates only a subset of brain components and thus of cell-to-cell signaling processes
13.14. [practical] conclusions?
iPSC-derived cortical organoids recapitulating human telencephalic development
Genome-wide transcriptome analysis in four families affected by idiopathic ASD
Affected individuals do not share any obvious underlying genomic alterations (heterogeneity in genotypes)
All individuals express a phenotypic trait that confers increased symptom severity, namely macrocephaly
Identification of perturbations in coherent programs of mRNA expression: upregulation of cell proliferation, unbalanced GABAergic inhibitory neuron differentiation, exuberant synaptic development and a generalized increase in proliferative potential
In accord with earlier hypotheses stating that abnormal control of cell proliferation, overproduction of neurons, increased spine densities, and an imbalance between glutamate and GABA neurons might contribute to the ASD phenotype, including its accelerated brain growth
A shared pathophysiological mechanism may exist for idiopathic ASD
Dysregulated gene expression in iPSC-derived organoids, and FOXGI in particular, could be used as a potential biomarker of severe ASD
Deletions and missense mutations in the FOXGI gene have been associated with an atypical Rett syndrome (a rare form of autism that affects only girls) and small brain size, suggesting that deviations in its expression levels during brain development, in excess and defects, cause opposite modulation in brain growth but a similarly disabling outcome, characterized by intellectual disability and ASD-like symptoms
Directly studying neurodevelopmental processes in patents with neuropsychiatric disorders that have heterogeneous etiologies can open inroads into diagnosis and therapy
