Projects

Final projects:

• Individual Final Project: A Self-Lytic E. coli Chassis for Cost-Effective Biopolymer Production via Rational Circuit Design

  SECTION 1: ABSTRACT Plastic pollution is one of the biggest challenges of 21st century: We have around 7 gr of microplastics in our brains ( Nihart, A.J., Garcia, M.A., El Hayek, E. et al. Bioaccumulation of microplastics in decedent human brains. Nat Med 31, 1114–1119, 2025). Using microorganisms it is already possible to produce biodegradable plastics that do not accumulate in our bodies. The transition from petroleum-based plastics to sustainable biopolymers, such as polyhydroxyalkanoates (PHAs), is hindered by prohibitive production costs. While metabolic engineering has significantly improved cellular yields, downstream processing (DSP)—specifically cell disruption—remains a critical economic bottleneck, accounting for 30–40% of total operating expenses. Current research into continuous secretion systems shows promise for small molecules; however, biopolymers like PHAs form large, insoluble intracellular granules that are biophysically difficult to export without excessive metabolic cost.
• Group Final Project - Bacteriophage Engineering Proposal: L Protein Stabilization

  Primary Goal: Increased stability Specific Approach: Engineering DnaJ-independence by reducing chaperone-recognition signals while preserving the structural scaffold of the L protein.

  1. Computational Tools and Pipeline Justification To achieve this goal, we propose a three-step computationally efficient pipeline: Step 1: Sequence-level Mutational Scanning using ESM2 Approach: We will perform a zero-shot in silico mutational scan across the L protein sequence using the ESM2 Protein Language Model (PLM). We aim to identify exposed hydrophobic patches (typical DnaJ recognition motifs) and propose polar/hydrophilic substitutions. Why this helps: ESM2 has learned deep evolutionary constraints across millions of protein sequences. It allows us to rapidly differentiate between highly constrained residues (which are structurally vital and “untouchable”) and mutation-tolerant positions. This ensures we only disrupt chaperone-binding motifs without breaking the core evolutionary scaffold of the protein, all at a fraction of the computational cost of molecular dynamics.