Homework Part A

1. Explain the main advantages of cell-free protein synthesis over traditional in vivo methods, specifically in terms of flexibility and control over experimental variables. Name at least two cases where cell free expression is more beneficial than cell production.

   Main advantages:

   • Flexibility and control: Cell-free systems allow precise manipulation of conditions such as pH, temperature, and reagent concentration, and enable incorporation of synthetic components like non-natural amino acids.
   • No cellular interference: There's no background expression of unwanted proteins that may interfere with the target.
   • Toxic proteins can be expressed: Toxic proteins can be produced without killing the system.
   • Portability and stability: Freeze-dried cell-free systems can be shipped and stored at room temperature, ideal for remote or space environments.

   Beneficial use cases:

   • Expression of toxic proteins, such as enzymes or toxins that would harm host cells in vivo.
   • Production in remote or extreme environments, like field hospitals or space missions, where cold-chain storage is unavailable.

2. Describe the main components of a cell-free expression system and explain the role of each component.

   1. DNA template (plasmid): Carries the gene of interest to be transcribed.
   2. RNA polymerase: Transcribes DNA into mRNA.
   3. Ribosomes and translation machinery: Translate the mRNA into protein.
   4. Amino acids and nucleotides: Building blocks for proteins and RNA.
   5. Energy source (e.g., ATP): Powers transcription, translation, and other enzymatic reactions.
   6. Cofactors and salts (e.g., Mg²⁺, K⁺): Maintain structural and catalytic conditions for enzymes and ribosomes.

3. Why is energy provision regeneration critical in cell-free systems? Describe a method you could use to ensure continuous ATP supply in your cell-free experiment.

   Why it matters:

   • Transcription and translation are ATP-intensive processes. Without live cells to regenerate ATP, reactions can stop prematurely.

   ATP regeneration method:

   • Add phosphoenolpyruvate (PEP) to the reaction. PEP can regenerate ATP from ADP using enzymatic reactions, extending the protein synthesis period.

4. Compare prokaryotic versus eukaryotic cell-free expression systems. Choose a protein to produce in each system and explain why.

   Feature	Prokaryotic (e.g., E. coli)	Eukaryotic (e.g., wheat germ, insect)
   Speed	Fast	Moderate
   Cost	Low	Higher
   Post-translational modifications	Rare	Present
   Protein complexity	Low–moderate	Moderate–high

   Example proteins:

   • Prokaryotic system: Green Fluorescent Protein (GFP) – no post-translational modifications required.
   • Eukaryotic system: Erythropoietin (EPO) – requires glycosylation for proper function, only possible in eukaryotic extracts.

5. How would you design a cell-free experiment to optimize the expression of a membrane protein? Discuss the challenges and how you would address them in your setup.

   Challenges:

   • Membrane proteins are hydrophobic and tend to aggregate without membranes.
   • No native lipid bilayer is present in cell-free systems.

   Design solutions:

   1. Add liposomes or nanodiscs to the reaction to mimic a membrane environment.
   2. Use mild detergents (e.g., digitonin) to keep membrane proteins soluble without denaturing them.
   3. Optimize expression conditions, such as magnesium concentration, temperature, and incubation time, to enhance correct folding and insertion.

6. Imagine you observe a low yield of your target protein in a cell-free system. Describe three possible reasons for this and suggest a troubleshooting strategy for each.

   • Cause: mRNA or DNA degradation.

     Fix: Use high-purity DNA and add RNase inhibitors like RNasin.

   • Cause: Inefficient transcription or translation.

     Fix: Optimize plasmid design (e.g., codon usage, ribosome binding site), and increase RNA polymerase or ribosome concentration.

   • Cause: Energy depletion.

     Fix: Supplement the reaction with an energy regeneration system (e.g., phosphoenolpyruvate or creatine phosphate)

Homework Part B

1. Provide an abstract/narrative/summary for your final project.

   My final project explores the computational quantification of MSI2 isoforms in myotonic dystrophy type 1 (DM1) and assesses potential off-targets of gapmer-based therapies. DM1 is a multisystemic disorder caused by CTG repeat expansions in the DMPK gene, leading to misregulated splicing and downstream molecular effects. MSI2, a splicing regulator, has been implicated in DM1 pathology, and recent therapeutic strategies have targeted its RNA using antisense oligonucleotides like gapmers. This project leverages RNA-seq datasets from muscle biopsies of human, mouse, and cell line models, applying transcriptome assembly and isoform quantification tools to evaluate treatment outcomes and specificity. Structural modeling and sequence alignment help identify possible unintended targets. The results highlight altered MSI2 isoform expression post-treatment and predict off-target interactions. This project offers valuable insights into RNA-based therapies in neuromuscular diseases and presents a reproducible pipeline for isoform-level analysis in therapeutic contexts.

2. Provide a background and motivation section for your final project.

   a. Explain your motivation for pursuing your project

   RNA-targeted therapies are emerging as powerful tools for modulating gene expression in genetic diseases like DM1. My motivation stems from the need to understand how these therapies alter isoform profiles and whether they inadvertently affect non-target transcripts, which is critical for improving both efficacy and safety. Additionally, studying MSI2—a key splicing regulator—offers insight into DM1 pathology and the therapeutic potential of targeting RNA-binding proteins.

   b. Describing the current state of knowledge related to your project. Try to cite at least 2 peer-reviewed research papers.

   Myotonic dystrophy type 1 is characterized by the accumulation of toxic RNA foci and widespread splicing defects. MSI2 has been implicated in modulating alternative splicing events relevant to DM1 symptoms. Gapmer antisense oligonucleotides represent a promising approach to silence pathological RNA, but concerns remain regarding off-target hybridization and RNase H-mediated degradation. However, there is limited isoform-level analysis of MSI2 expression changes in response to these therapies.

   c. Describe how your project is innovative and expand upon the significance of your final project.

   This project is innovative because it focuses on isoform-specific quantification of MSI2, going beyond gene-level analysis to detect subtle therapeutic effects. It combines transcriptomics and structural bioinformatics to explore both efficacy and off-target effects of gapmer treatments—an area not thoroughly explored in current literature. The approach also provides a transferable pipeline for evaluating RNA-based interventions in other diseases.

3. Aims

   Aim 1: Quantify MSI2 isoform expression across untreated and gapmer-treated DM1 samples

   Experimental Plan:

   • Tools: Kallisto, Salmon, and StringTie for isoform quantification.
   • RNA-seq data from human, mouse, and cell lines were aligned using STAR.
   • Annotation used: GENCODE and custom transcript models (if needed).
   • Statistical analysis with DESeq2 and Sleuth.

   Results:

   • Clear differential expression of MSI2 isoforms observed post-treatment.
   • Some isoforms were significantly downregulated, aligning with the proposed mechanism of action of the gapmer.
   • Technical challenge: low coverage regions affected the quantification in certain samples.

   Aim 2: Predict and evaluate potential off-targets of gapmer treatment

   Experimental Plan:

   • Use BLAST and RNAhybrid to detect partial complementarity to other transcripts.
   • RNase H activation motifs assessed with tools like OligoWalk and mFold.
   • Structural modeling with PyMOL, Colab and RNAstructure to assess accessibility.

   Results:

   • Several potential off-targets were identified with strong thermodynamic support.
   • No major unintended targets confirmed yet, but further validation is required (e.g., qPCR or CLIP-seq).
   • Limitation: In silico predictions require biological validation.

4. Describe any unexpected challenge(s) you faced in planning or executing your final project.

   One major challenge was the inconsistency in transcript annotations across species, which required manual curation and cross-validation of MSI2 isoforms. Additionally, off-target prediction was more complex than expected due to the secondary structure of RNAs, which can obscure potential binding sites not visible through linear sequence alignment.

5. Describe the bioethical considerations involved in your project.

   Although this study is in silico, it uses publicly available data from human and animal models. Ethical considerations include proper citation and compliance with data-sharing agreements. For future experimental validation, the use of animal models and human samples must follow strict institutional and ethical guidelines (e.g., IACUC and IRB approvals). Moreover, RNA-based therapies raise ethical concerns regarding long-term off-target effects and patient safety.

6. Describe any future work