Week 1: Principles and Practices
Class Assignment
Project Idea
Chronic wounds and surgical site infections affect millions of patients and cost heathcare systems tens of billions of dollars annually, yet closure devices often remain as passive stitches that do not actively orchestrate local immunity or regeneration [1][2].
Drug-eluting sutures have shown that suture material can safely deliver local therapeutics, but current designs provide only finite, non-adaptive release of single agents such as antibiotics or growth factors [3][4]. Cell-filled sutures packed with mesenchymal stem cells already demonstrate that viable cells can be integrated into suture structures and enhance healing, but these cells are unmodified and lack controllable, multi-functional outputs [5]. Separately, engineered combinatorial cell devices in fiber-like formats can secrete optimized cocktails of growth factors to accelerate wound and bone repair, but they are not load-bearing sutures and do not address infection or scar modulation at the incision line [6].
In a separate project, I explored how patient skin cells (such as fibroblasts) could be engineered to express a genetic circuit that could counteract the persistent inflammation of chronic wounds, sense a biomarker indicative of the end of the inflammatory wound healing phase, and then kickstart the proliferation phase sequentially.
I want to use a similar premise to propose a hollow, bioabsorbable suture that houses genetically engineered cells programmed to sense wound and infection cues to secrete combinations of pro-regenerative and antimicrobial factors over the critical healing window. This would transform sutures from a passive mechanical closure tool into an adaptive, living therapeutic that directly tackles both impaired healing and scarring in a way that current drug-eluting or cell-based sutures cannot.
Governance/Policy Goals
Enhance Biosecurity
Introducing genetically modified living materials into the body always poses the risk of unintended side effects in terms of how that newly modified
- Escape and persistence of engineered cells
- Genetically engineered cells have the potential to leak from the suture material during deegradation, which may cause the migration of these cells to other unintended areas of the body
- Unintended immune suppression hotspots
- One potential application of the seeded engineered cells is to assist in the healing of chronic wounds, which would require the secretion of anti-inflammatory genes/cytokines. In this case, it could potentially host an environment that is susceptible to tumor growth due to the prevention of the body’s natural protection mechanisms becoming temporarily reduced
Foster Lab and Patient Safety
- By preventing incident
- Informed patient consent
- Adverse events
Protect the Environment
- Wasted suture material
- As this suture material would contain a living cellular component, the wasted material would need to be properly disposed of through the right channels
- Resistance ecology
- As the suture material could aim to reduce microbial infection, this could lead to an inadvertent resistance issue through evolution (similar to antibiotic resistance) and should be thoughtfully considered
Other Considerations
- Equal access
- Not impede research
- Promote constructive applications
Potential Governance Actions
- Specialized biosafety and clinical training track for “living implant” users
- Purpose:
- Researchers and clinicians complete general biosafety and surgical training, but there is no standardized curriculum for working with engineered living impants
- Establish a dedicated training a certification program for labs and clinicians who design, manufacture, or implant living sutures, similar to specialized credentialing for radiation safety or gene therapy administration
- Design:
- Government entities would implement a standardized curriculum and requirement for all individuals working with living material users
- Universities, hospitals, and organizations could develop modules on containment of genetically engineered materials, safety functions and limitations, proper disposal methods and would need to require completion from designated users
- Assumptions:
- Assumes that the training would be taken seriously by all parties involved
- Assumes that institutions have the resources to implement this level of training
- Risks of Failures and Success:
- Training can easily devolve into people trying to just “pass a quiz”
- Small or underprivileged institutions may not be able to support the certification
- Credentials could become a bottleneck in care, limiting broader patient impact
- Mandatory standardized labeling and risk communication for living sutures
- Purpose:
- Implanted devices and sutures often have minimal patient-facing documentation and many patients do not know exactly what materials are being used
- Require clear, standardized labeling and risk summaries for any engineered-cell stuure, both on packaging for clinicians and in take-home materials for patients, similar to medication guides for high-risk drugs
- Design:
- Government entities should define a standardized material and one-page explanation that should include that the suture is living/engineered, intended benefits, key unknowns, possible risks, and recommended follow-up durations
- Medical professionals should ensure that patients receive and acknowledge these materials during consent and discharge
- Assumptions:
- Assumes patients will read and understand the materials
- Assumes that clinicians will consistently use and explain documents instead of just handing them over
- Assumes that simple language used for materials can convey the complex biological concepts utilized
- Risks of Failures and Success:
- Overly technical language may confuse or scare patients without helping them to make an informed decision
- If the material emphasizes uncertainty too strongly, clinicians may avoid using the sutures due to patient refusal or anxieties, even when risk-benefit is favorable in high-need cases
- Open safety data and pre-registration for living-suture research
- Purpose:
- Clinical trials are often pre-registered, but preclinical work, especially in industry, can remain proprietary and negative results are frequently unpublished
- Require prospective registration and open reporting of both clinical and key preclinical studies involving engineered-cell sutures, including negative or inconclusive safety findings
- Design:
- Academic and industrial labs should register protocols in public or semi-public databases and post summaries of the key findings, including failures
- Government or regulatory safety boards should aggregate data and identify patterns which can be communicated to different programs and companies
- Assumptions:
- Assumes companies will accept some loss of competitive secrecy for safety transparency
- Assumes public reporting can be done in ways that protect intellectual property while still being meaningful
- Risks of Failures and Success:
- Compliance may be partial, some negative preclinical findings could stay hidden in internal reports
- Low-quality data could mislead more than inform
- Highly publicized early safety issues, even if fixable, could dissolve public trust in otherwise promising tools
Governance Actions vs Policy Goals
| Researchers | Medical professionals | Government Entities (Ex: FDA) | Patients | |
|---|---|---|---|---|
| Enhance Biosecurity | ||||
| • Escape and persistence of engineered cells | 3 | 1 | 2 | n/a |
| • Unintended immune suppression hotspots | 1 | 3 | 2 | n/a |
| Foster Lab and Patient Safety | ||||
| • By preventing incident | 3 | 2 | 1 | 4 |
| • Informed patient consent | 4 | 1 | 2 | 3 |
| • Adverse events | 3 | 2 | 1 | 4 |
| Protect the environment | ||||
| • Wasted suture material | 3 | 2 | 1 | 4 |
| • Resistance ecology | 3 | 2 | 1 | 4 |
| Other considerations | ||||
| • Equal access | 3 | 2 | 1 | n/a |
| • Not impede research | 2 | 1 | 2 | |
| • Promote constructive applications | 1 | 2 | 3 | 4 |
- 1= most responsibility, 4=least responsibility
Lecture 2 Preparation Questions
Questions from Professor Jacobson
- The error rate for DNAP is 106 (about 1 in 1 million). Since the human genome is roughly 3.2 x 109 bp, this means that there would be around 3,200 errors each time a genome copy is made. However, nature is able to combat these errors due to its error correction mechanisms, such as the MutS repair system.
- If we assume that an average human protein has 375 amino acids [7], and there are about three codons that code each amino acid, then there are roughly 10180 ways to code for the average human protein. However, some of these codings could be invalid if they don’t have a proper start codon, if they have unstable mRNA, or if they produce a misfolded protein.
Questions from Dr. LeProust
- Currently, the method typically used for oligo synthesis is solid-phase phosphoramidite chemistry, where the 5’ end of the previous nucleotide is protected and as phosphoramidites are added (modified versions of each nucleotide), the 5’ end is exposed, allowing the next base to couple, and then the resulting 5’ end is protected once again while an oxidizing solution stabilizes the bond that was just formed, repeating the process until one obtains the desired oligonucleotide [8].
- Oligos longer than 200bp are typically too difficult to synthesize due to an accumulation of impurities that significantly decreases the yield [9].
- Coding a gene over 2000bp by oligo synthesis would also be difficult due to exponentially decreasing yields over a certain threshold and difficulty with purifying the final product.
Questions from George Church
In response to question #2
- The NA:NA code relies on pairing G to C and pairing A with T (or U in RNA). This then is translated in the AA:NA code as a three bp long codon that translates to one of the twenty amino acid, and this ultimately results in amino acids that can be coded by multiple codon sequences. In order to create an AA:AA code, which would represent protein-protein interactions, I would anticipate the need to consider 3D structure as well as properties of each of the AAs. For example, a positively charged amino acid, like histamine, would ultimately pair best with a negatively charged amino acid, such as glutamic acid. Since there are multiple amino acids with these properties, the code would not have a singular outcome, like NA:NA, but this code could then be further optimized through the 3D structure complemtarity [10][11].