Week 2 HW: dna design

BioFit — Grown-to-Shape Bacterial Cellulose Prosthetic/Orthotic Interface

Part 0 — Kernel setup

I created a Kernel repository and project folder for BioFit and used Kernel to assemble and inspect the genetic construct. I used Kernel’s sequence viewer, construct checker, codon optimization tool, sequence search/BLAST, and Biosecurity Sequence Scanner to design and quality-check the sequence. Repository: Rosalea_BioFit Construct: BioFit-Expression

Part 1 — Define the expression target

What am I trying to produce? BioFit is a biomanufacturing concept for a custom bacterial-cellulose interface for prosthetic sockets, knee braces, and potentially other orthopedic wearables. The material would be grown around a digitally fabricated 3D former based on the user’s anatomy, with the goal of producing a body-specific cellulose interface rather than manufacturing a flat sheet and subsequently cutting and forming it.

The biological output is therefore bacterial cellulose, rather than a conventional recombinant protein product. In Komagataeibacter xylinus, cellulose is synthesized extracellularly from a carbon source and assembled into a hydrated nanofibrillar network

For this DNA design, I focused on the cellulose synthase machinery, particularly the catalytic cellulose synthase subunit BcsA. Sequence The main coding sequence analyzed was BcsA / cellulose synthase catalytic subunit [UDP-forming], corresponding to UniProt P19449. The protein sequence used for the design was 754 amino acids long. The sequence corresponds to the catalytic subunit of bacterial cellulose synthase from Komagataeibacter xylinus. The P19449 annotation identifies it as the cellulose synthase catalytic subunit and the gene as bcsA. BcsA catalyzes the polymerization of UDP-glucose into cellulose. The enzyme is therefore directly relevant to the biological manufacturing goal of BioFit

Host/chassis

The biological chassis selected in my original BioFit concept was Komagataeibacter xylinus because it is a bacterial cellulose-producing organism However, Kernel currently records the expression host of the construct as Cricetulus griseus (Chinese hamster). This is an inconsistency in the current computational design. The construct also contains a bacterial promoter/RBS architecture. Therefore, the current construct should be considered a sequence-design prototype rather than a final host-matched expression design. A next iteration would need to align the Kernel expression-host setting, promoter, translation-initiation element, and backbone with the intended biological chassis. Where does the product need to go? The final bacterial cellulose is intended to be produced extracellularly by the cellulose-producing chassis. The goal of BioFit is ultimately to grow the cellulose structure around a custom 3D former rather than simply express and purify BcsA as an isolated protein. The spatial manufacturing concept therefore depends on extracellular cellulose production by the bacterial chassis.

Part 2 — Genetic parts

The resulting construct was approximately 9.3 kb in Kernel. The overall architecture is: Ptrc2 → RBS → BcsA → BcsB → BcsC → BcsD → BBa_B0015

Design rationale

The construct was designed around the cellulose synthase system rather than treating BcsA as an isolated protein because BioFit requires cellulose production as the final biological output. BcsA is particularly important because it is the catalytic subunit responsible for polymerizing UDP-glucose into cellulose. The additional Bcs components were included to represent the broader cellulose-synthesis machinery rather than relying on the catalytic subunit alone.

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Part 3 — Assemble the construct

The construct was assembled in Kernel in the following 5′→3′ order: Ptrc2 → RBS → BCSA1_KOMXY → BCSB1_KOMXY → BCSC1_KOMXY → BCSD1_KOMXY → BBa_B0015 The resulting construct is approximately 9,325 bp according to Kernel. Kernel’s construct viewer was used to inspect the sequence and confirm the order and orientation of the components. The assignment specifically requires checking the reading frame, start/stop codons, internal stops, and orientation. Construct checker Kernel initially returned several warnings, including: unequal promoter/Kozak/UTR counts, fewer polyA elements than promoters, several parts marked as “not recommended.” These warnings are important because they indicate that the construct is not perfectly matched to the expression context currently selected in Kernel. In particular, the construct uses a Ptrc2 promoter and RBS, which are characteristic of a bacterial expression architecture, while Kernel lists Cricetulus griseus as the expression host. Therefore, the warnings should not simply be ignored; they identify a host/architecture mismatch that would need to be resolved in a future design iteration.

Part 4 — Optimize and quality-check

4.1 Codon optimization

I used Kernel’s Codon Optimizer on the BcsA protein sequence. Input Input type: Amino acid Protein: BcsA / cellulose synthase catalytic subunit Length: 754 aa Expression organism selected in Kernel: Cricetulus griseus (Chinese hamster) Algorithm: Simple v0.3 Restriction-enzyme constraints: None specified Motif constraints: None specified The optimizer converted the amino-acid sequence into a DNA coding sequence appropriate to the selected expression organism. Why codon optimization matters Different organisms use synonymous codons at different frequencies. Although synonymous codons encode the same amino acid, their frequencies can affect how efficiently a heterologous coding sequence is translated in a particular host. Therefore, codon optimization changes the DNA sequence while preserving the intended protein sequence. In this design, the optimization was used to produce a host-oriented DNA version of BcsA rather than simply copying the native bacterial coding sequence. The optimized sequence began with ATG and included a terminal TAA stop codon. Constraints No additional restriction-site or motif constraints were entered in the Kernel optimization interface. Therefore, the main design change was codon usage for the selected host. Important limitation: because the intended BioFit chassis from HW1 is K. xylinus, optimization for C. griseus is not necessarily the final biologically appropriate choice. A future version should optimize the sequence for the actual production chassis if the construct is intended for expression in K. xylinus. [Insert Codon Optimizer screenshot here.]

4.2 Sequence search / BLAST

I used protein BLAST to determine whether the sequence corresponded to the expected cellulose synthase protein. The query was: UniProt P19449 The BLAST result had: Query length: 754 aa Top matches: cellulose synthase catalytic subunits Query coverage: 100% E-value: 0.0 Top reported identity: approximately 96.55% Top organism: Komagataeibacter xylinus The results strongly supported that the sequence is a cellulose synthase catalytic subunit, rather than an unrelated or novel protein. The BLAST matches were also consistent with the UniProt P19449 annotation for BcsA from K. xylinus. Independent database results likewise identify P19449 as a UDP-forming cellulose synthase catalytic subunit from K. xylinus. This was an important quality-control step because it confirmed that the protein sequence used for the BioFit design matched the intended biological function. [Insert BLAST screenshot here.]

4.3 Biosecurity sequence scan

I also ran Kernel’s Biosecurity Sequence Scanner on the optimized DNA sequence. Result No flagged sequences detected. The scanner did not identify any sequences in the input that were flagged by its biosecurity screening database. This provides a computational safety check on the designed sequence. It does not demonstrate that the biological system is experimentally safe or that the entire design is risk-free; it only reports the outcome of this particular sequence-screening step. [Insert screenshot showing “No flagged sequences detected” here.]

Part 5 — From design to build

How would I build the construct? The final construct is approximately 9.3 kb, making a fragmented synthetic-DNA approach attractive for a prototype. I would use commercially synthesized DNA fragments followed by sequence-verified assembly, rather than attempting to construct the entire sequence from a large pool of short oligos manually. A practical conceptual workflow would be: Design → synthesize sequence fragments → sequence/QC fragments → assemble overlapping fragments → verify final construct For assembly, Gibson assembly is a reasonable approach because it can join overlapping DNA fragments in a single isothermal reaction using exonuclease, polymerase and ligase activities. Gibson et al. demonstrated assembly of multiple overlapping DNA molecules into much larger constructs. For a ~9.3 kb construct containing multiple functional elements, dividing the construct into several manageable synthetic fragments would also reduce the difficulty of obtaining one completely error-free long molecule. What does DNA synthesis constrain? Synthetic DNA is not perfectly error-free. Errors can arise during oligonucleotide synthesis and subsequent amplification/assembly, and the probability of obtaining an error-free product becomes more challenging as sequence length increases. Carr et al. demonstrated that error correction can substantially reduce errors in de novo DNA synthesis and showed the importance of error correction for longer synthetic targets. Their work reported an improvement to approximately one error per 10,000 bp after error depletion.