Week 1 Homework: Microbiome-Tuned Skincare week

1. First, describe a biological engineering application or tool you want to develop and why

After the first week of the How To Grow Almost Anything course and the projects that were presented by the panel, I decided to focus on an area that has always fascinated me: skincare and cosmetics. I have personally struggled to find products that actually worked for my skin. Some creams caused dryness, others triggered breakouts, and many were ineffective despite high prices and flashy marketing. Over time, I realized that this frustration is common—most skincare follows a “one-size-fits-all” approach, categorizing skin as oily, dry, combination, or sensitive. While these categories are a helpful starting point, they fail to capture the biological complexity and uniqueness of each person’s skin.

This personal challenge led me to explore a potential solution: microbiome-tuned skincare. This approach involves designing cosmetic formulations that are personalized based on an individual’s skin microbial ecosystem. Every person’s skin hosts a complex community of microbes, including bacteria, fungi, and viruses, which together influence hydration, barrier function, inflammation, and susceptibility to conditions like acne, eczema, or premature aging. Normal skincare does not account for this complexity and treats all skin as if it reacts the same way. Microbiome-tuned skincare, by contrast, supports beneficial microbes while balancing or reducing harmful ones.

For example, some individuals naturally have low levels of certain beneficial bacteria, such as specific strains of Cutibacterium acnes, which help maintain the skin barrier and prevent infection. Prebiotic creams may promote the growth of beneficial microbes. On the other hand, individuals with higher levels of pro-inflammatory microbes could use formulas containing anti-inflammatory compounds that rebalance the microbial ecosystem without harming beneficial organisms. By analyzing a person’s skin microbiome, products can be customized for their unique needs rather than relying on generic formulations.

From a bioengineering perspective, this project combines synthetic biology, computational biology, and personalized healthcare. Skin samples can be collected to identify microbial composition, and machine learning algorithms can predict how different formulations will interact with these microbial communities. The result is a personalized skincare routine that improves hydration, reduces inflammation, supports anti-aging processes like collagen maintenance, and maintains overall skin health. This approach transforms skincare from a trial-and-error routine into a scientifically guided, individualized experience.

Beyond cosmetics, microbiome-tuned approaches have broader applications. Dermatologists could use similar strategies to treat skin conditions such as eczema, rosacea, or chronic acne with higher precision. Another example is wound care: microbiome-tuned wound treatments use microbial profiling and predictive analytics to personalize care, supporting beneficial microbes while inhibiting harmful ones. Monitoring the wound’s microbial environment over time can prevent infection, accelerate healing, and reduce reliance on antibiotics. Personally, the appeal of this project is both scientific and social: it addresses a real-life problem that I have experienced and has the potential to help others avoid ineffective treatments.

The skin is the largest organ of the human body and serves as a defensive barrier against pathogens while supporting sensory functions. Its microbiome is essential for health because it:

• Competes with harmful microbes, preventing infections
• Communicates with the immune system, regulating inflammation
• Supports barrier integrity, reducing dryness and irritation

Disruption of this microbial balance, known as dysbiosis, increases the likelihood of skin issues such as acne or eczema. Dysbiosis can result from diet, environmental factors, skincare products, or antibiotics. Regular skincare often addresses only symptoms rather than the underlying microbial imbalance. Microbiome-tuned skincare aims to restore balance and promote long-term skin health.

This strategy can be implemented using three main approaches:

1. Microbiome Sequencing: Collect skin samples and analyze microbial DNA to assess bacterial, fungal, and viral composition.
2. Machine Learning Analysis: Use computational models to predict how specific ingredients will affect microbial balance and skin health.
3. Personalized Formulation: Develop creams, serums, or cleansers specifically designed to support beneficial microbes and reduce harmful ones.

By focusing on maintaining the health of the skin ecosystem, microbiome-tuned skincare shifts the approach from reactive to proactive care.

2. Governance/Policy Goals

Because microbiome-tuned skincare directly interacts with the body, ethical considerations are critical. The main governance goals for this project are:

1. Preserving Consumer Health and Safety
   Skincare products based on microbiomes act as biological components. Poorly designed formulas may disrupt microbial balance, leading to irritation and other skin conditions. The skin microbiome is influenced by age, genetics, ethnicity or and environmental factors, so products must be tested widely and safely. Sub-goals include:

   • Standardizing validation procedures for personalized formulas
   • Monitoring long-term effects on skin health and microbial balance
   • Testing across diverse populations to ensure safety and effectiveness

2. ** Privacy and Data Security**
   Microbiome data is personal and could reveal information about health, lifestyle etc. Protecting this information is essential. Sub-goals include:

   • Anonymizing microbial data
   • Implementing strict consent procedures for users
   • Preventing misuse by third parties or commercial entities

3. Governance Actions

Action 1: Regulatory Framework for Microbiome-Based Products

• Purpose: Existing cosmetic regulations are not designed for personalized microbial interventions. A framework would define safety standards, acceptable microbial strains, and validation protocols.
• Design: Regulatory agencies (FDA, EMA) would require companies to submit microbial and clinical data for approval. Long-term monitoring ensures continued product efficacy.
• Assumptions: Regulators accept microbiome-based evidence; companies can standardize testing across populations.
• Risks of Failure & Success: Overly strict regulations could slow innovation or increase costs, while overly permissive rules may allow unsafe products to reach consumers.

Action 2: Privacy and Data Protection

• Purpose: Protect sensitive microbiome data and prevent misuse.
• Design: Use encryption, anonymization, secure storage, and strict consent. Independent audits and international standards would guide compliance.
• Assumptions: Companies follow protocols; technology prevents unauthorized access.
• Risks of Failure & Success: Data breaches or misuse could harm consumers through discrimination. Strong protections build trust and encourage adoption of microbiome-based products.

Action 3: Incentives for Broad Access and Ethical Design

• Purpose: Ensure microbiome-tuned skincare benefits a wide population, not only wealthy consumers.
• Design: Provide grants, subsidies, and open-source tools for small companies or academic labs.
• Assumptions: Financial and technical support will broaden equitable access.
• Risks of Failure & Success: Limited funding or intellectual property disputes could restrict access. Successful implementation ensures broad social impact.

4. Governance Scoring

5. Prioritization and Recommendations

Based on the scoring, I would choose a combination of Action 1 (Regulatory Framework) and Action 2 (Privacy and Data Protection), while keeping Action 3 (Equitable Access) as a secondary focus. Regulatory oversight ensures products are safe and effective, so it is preventing disruptions to the skin microbiome. Equity initiatives are important but should follow safety and privacy considerations to ensure broad access.

Trade-offs include higher costs and slower innovation, but these are necessary to avoid harm and ensure ethical deployment. Target audiences include federal regulators (FDA, EMA), companies for privacy compliance, research institutions for open-access tools, and international bodies for cross-border standards. This combination balances safety, privacy, innovation, and societal impact, making microbiome-tuned skincare both effective and responsible.

Professor Jacobson

1. Nature’s machinery for copying DNA is called polymerase. What is the error rate of polymerase? How does this compare to the length of the human genome, and how does biology deal with that discrepancy?

Polymerase has an error rate of roughly 1 in 10⁶ bases. The human genome contains roughly 3 billion base pairs, meaning about 3,000 mistakes could occur per replication. Biology corrects these errors with proofreading, apoptosis of damaged cells, and by allowing some variation to contribute to evolution.

2. How many different ways are there to code DNA for an average human protein? Why do all these sequences not work in practice?

Theoretically, about 10¹⁵⁷ DNA sequences could encode a 330-amino-acid protein. In practice, many sequences fail due to mRNA folding, premature translation stops, and codon bias that affects efficiency.

Dr. LeProust

1. Most commonly used method for oligo synthesis

The solid-phase phosphoramidite chemical synthesis is the most used technology today for making custom DNA oligonucleotides.

2. Why is it difficult to make oligos longer than 200 nucleotides?

In addition to side reactions and chemical limitations, it is challenging due to cumulative stepwise errors and yield drops. The maximum efficiency of each addition cycle in the synthesis of phosphoramidite is approximately 99%. The likelihood of creating an accurate product decreases to a maximum of 14% over 200 bases. The increasing length of the chain in conventional porous supports can also obstruct reagent access, which reduces efficiency even more.

3. Why can’t you make a 2000 bp gene via direct oligo synthesis?

Based on the previous answer, accumulating errors make a 2000 base pair gene (4000 nucleotides) almost impossible to synthesize. It is simply not feasible.

George Church

1. [Using Google & Prof. Church’s slide #4] What are the 10 essential amino acids in all animals and how does this affect your view of the “Lysine Contingency”?

The 10 essential amino acids that animals cannot synthesize and must obtain through their diet are arginine, histidine, isoleucine, leucine, lysine, methionine, phenylalanine, threonine, tryptophan, and valine. The “Lysine Contingency” in Jurassic Park involved engineering dinosaurs to be unable to produce lysine so that, without lab-supplied supplements, they would die if they escaped. While this is a clever narrative device, it is biologically flawed because lysine is abundant in natural foods, meaning escaped dinosaurs could easily obtain it and survive. This highlights that while lysine is essential for all animals, relying on its absence as a control measure overlooks basic nutritional biology and ecosystem realities. A more effective contingency would need to target something unique to the lab environment rather than a common dietary requirement.