Lecture — Principles & Practices

Slides will be shared after class.

Homework — Principles & Practices

Class Assignment

1. Describe a biological engineering application or tool you want to develop and why. This can tie to your eventual final project or current research.
2. Define governance/policy goals to ensure your application contributes to an ethical future (e.g., safety, equity, autonomy). Break big goals into sub‑goals.
3. Propose at least three governance actions across different actors (e.g., researchers, companies, federal agencies). For each action, consider:
   • Purpose — what changes are you proposing?
   • Design — what’s needed for it to work?
   • Assumptions — what might you have wrong?
   • Risks of failure & “success” — unintended consequences if it “works.”
4. Score each action (1–3; 1=best) against your policy goals (or a framework of your own). Use the matrix below as inspiration.
5. Prioritize one option (or a combo) and explain your trade‑offs, assumptions, and uncertainties.

Weekly Assignment

Reflect on any ethical concerns that arose this week. Propose governance actions you think are appropriate to address them. Include this on your class page for Week 1.

Before Next Class

• Open a personal Notion page (covered in Recitation) and submit the public link via this Google Form.
• Complete the Principles & Practices assignment above.

Recitation — Principles & Practices

Slides (Updated Feb 5):

• Google Slides

Recording (Updated Feb 7):

• Zoom

Lab — Pipetting

Objective

Welcome to HTGAA! This first lab introduces pipetting and serial dilutions, foundational for precise liquid handling and solution preparation. This is a one‑day lab with two mini‑protocols (mixing colors and dilutions). By the end, you’ll confidently use pipettes, prepare solutions to target concentrations, and troubleshoot common errors.

Concepts You’ll Learn

• Units & conversions
• Serial dilutions
• Pipetting proficiency

Preparation & Protocol

• Lab Prep — materials and notes (posted after lab)
• Lab Protocol — HTGAA 2025 Pipetting Lab (Google Doc)

Lab Prep Lab Protocol (Google Doc)

Inventory

• Lab Inventory (Google Sheet)

Reading & Resources — Week 1

Lab‑specific

• Unit conversion & significant figures — Crash Course
• Intro to pipetting — YouTube

Governance & ethics

• Protein Design Meets Biosecurity — Church & Baker (Science, 2024)
  Science.org
• Synthetic Genomics: Options for Governance — J. Craig Venter Institute
• US Presidential Commission on the Study of Bioethical Issues — “New Directions” report
• WHO Global guidance framework — Mitigating biorisks
• Bold Goals for U.S. Biotechnology and Biomanufacturing — White House (2023)
• National Security Commission on Emerging Biotechnology (interim) — U.S. Senate
• iGEM Safety Hub — 2020 and 2023 Responsibility
• Handbook for Community Biology Spaces — Genspace
• DIYBio Ask a Biosafety Expert — ask.diybio.org
• Rooftop Solar & the Four Levers of Social Change — Ethan Zuckerman

Lecture — DNA Read, Write, and Edit

Slides:

• George Church — Reading & Writing Life
• Joe Jacobson — Gene Synthesis

Class Recording: Zoom

Homework — DNA Read, Write, and Edit

Part 0 — Basics of Gel Electrophoresis

• Watch the week’s lecture and recitation videos. (Bootcamp is optional.)

Part 1 — Benchling & In‑silico Gel Art

Use the Gel Art: Restriction Digests and Gel Electrophoresis protocol as a guide.

1. Create a free account at benchling.com
2. Import Lambda DNA from NEB.
3. Simulate digests with enzymes: EcoRI, HindIII, BamHI, KpnI, EcoRV, SacI, SalI.
4. Design a banding pattern inspired by Paul Vanouse’s Latent Figure Protocol.

Part 2 — Wet‑lab Gel Art

Part 3 — DNA Design Challenge

• Choose a protein of interest and obtain the amino‑acid sequence (NCBI/UniProt/other).
• Reverse translate to DNA.
• Continue per recitation guidance (gRNA design, editor choice, etc.).

Key Links

• Protocol: Gel Art — Restriction Digests & Gel Electrophoresis
• Benchling: benchling.com
• NEB Lambda DNA: neb.com
• Paul Vanouse — Latent Figure Protocol: paulvanouse.com

Recitation — DNA Read, Write, and Edit

Slides (Updated Feb 12):

• Google Slides

Recording:

• Zoom

Lab — DNA Gel Art

Objective

A focused 3‑hour lab on restriction digests and agarose gel electrophoresis. You’ll create DNA gel art while mastering core techniques that underpin verification of DNA constructs.

Concepts You’ll Learn

• Benchling tools for design
• Restriction digest setup
• Agarose gel preparation
• Gel electrophoresis execution
• DNA visualization

MIT lab timing (special for this week)

• Thu, Feb 13 — 1–4 PM ET, Building 68‑079

Prep & Protocol

Reading & Resources — Week 2

Core

• DNA Sequencing at 40: Past, Present, and Future (2017) — Shendure, Balasubramanian, Church, et al. Nature
• DNA Synthesis Technologies to Close the Gene Writing Gap (2023) — Hoose, Vellacott, Storch, et al. Nature Rev Chem
• Recombineering and MAGE (2021) — Wannier et al. Nat Rev Methods Primers
• CRISPR: A Decade of Genome Editing is Only the Beginning — Wang, Doudna, et al. Science

Databases

• GenBank overview — NCBI
• NCBI Genome — NCBI
• Ensembl — Ensembl
• UCSC Genome Browser — UCSC | Harvard GMC

Editors & Tutorials

• CRISPR/Cas9 — Addgene tutorial | Benchling guide | PAM sequences
• Base editors — Review (2018)
• Prime editing — Prime editor | primeedit.nygenome.org | guide
• TALENs — Short guide | Design resource | Directed evolution

Additional Resources

• Gel purification of DNA — Addgene
• Synthetic genomes with altered genetic codes (2020) — ScienceDirect
• DNA recorders — Nature (2021)
• Single‑molecule sensors on chips — PubMed (2022)
• Genome editors review (pre‑CRISPR era) — Trends Biotech (2013)
• Clinical trials of genome editing therapies — Nature (2020)

Lecture — Lab Automation

Homework — Lab Automation

What to do

1. Read the pre‑lab materials to understand the workflow and safety.
2. Create your protocol in the provided Colab (Python) and test in simulation.
3. Submit your completed protocol to your TA.

• Sign‑up for a robot time slot: Robot time slot form
• Submit your Colab block: Protocol submission form

Post‑Lab Questions (Mandatory)

1. Describe how you would use automation for your final project (pseudocode/scripts, fixtures or 3D‑printed holders, etc.).
2. Find and briefly describe a paper that uses Opentrons or similar tools for a novel bio application.

Recitation — Lab Automation

Slides: Google Slides
Recording: will be posted (per source).

Lab — Opentrons Art

Objective

In this two‑day lab you’ll program the Opentrons OT‑2 to deposit fluorescent E. coli on black agar plates, creating glowing bio‑art under UV light. It’s a hands‑on intro to automation + creative biotech.

Concepts You’ll Learn

• Writing Python for the Opentrons OT‑2
• Automating liquid handling steps
• Pouring black agar plates
• Handling fluorescent E. coli safely

Prep & Protocol

Reading & Resources — Week 3

Lab Automation & Opentrons

• Opentrons Lab Automation Primer — overview primer and reading list. Notion
• Opentrons Art GUI — web app & links to API/Colab resources. opentrons-art.rcdonovan.com
• Opentrons Robotics (YouTube) — channel with OT‑2 primers and demos. YouTube

Lecture — Protein Design Part I

This session introduces Protein Design foundations: what sequence/structure information is, how to find it, and how modern ML tools have changed design workflows.

Core resources (converted from the course page)

• RCSB PDB — archive and tools for experimentally-determined macromolecular structures, with powerful search/visualization.
• UniProt / UniProtKB — comprehensive, curated protein sequence and functional knowledgebase; tightly linked with PDB and other resources.
• Predicted structures — both resources now surface computationally predicted structures for many proteins, complementing experimental data.

(Slides and recording will be posted here when available.)

Homework — Protein Design Part I

Context (converted from the course page)

• Use RCSB PDB to explore 3D structures and annotations of your protein of interest.
• Use UniProt/UniProtKB to obtain sequence and functional information and navigate cross‑links to structural resources.
• Note that these databases increasingly include computationally predicted structures alongside experimental entries.

Recitation — Protein Design Part I

Lab — Protein Design Part I

Concepts You’ll Learn

• Protein prediction tools
• Sequence recovery models
• Generative models
• Designing toward desired physicochemical properties

Lab Protocol

The protein design lab will be entirely in‑silico; you’ll run a variety of models to test different protein designs.

Picture source: Hou, Feenstra et al., 2022 — “Ten quick tips for sequence‑based prediction of protein properties using machine learning,” PLOS Comput Biol 18(12): e1010669.

Reading & Resources — Week 4

Lecture — Protein Design Part II

Date: Tue Mar 4 (per schedule).
Slides: (will be posted when available)
Recording: Zoom

Homework — Protein Design Part II

Key Links

• Tracking sheet: Google Sheet

Part A — PepMLM peptide design (From Pranam)

1. Create a Hugging Face account → we’ll use PepMLM‑650M: model page.

   1. Generate a token: Settings → Tokens (create new).
   2. Ensure repo is ChatterjeeLab/PepMLM-650M.
   3. Open the PepMLM Colab and make a copy: Colab (linked from the model page).
   4. In Colab, choose T4 GPU, run all blocks.
   5. When prompted “Input HF token”, paste your token. When asked “Add token as git credential?”, choose No.

2. Get the amino‑acid sequence for SOD1 on UniProt (ID: P00441). Make the A4V mutation.

3. Run PepMLM inference and generate 4 peptides (length 12 aa). (2 is acceptable if time‑limited.)

4. Add a known SOD1‑binding peptide to your list: FLYRWLPSRRGG (see Genes & Development reference).
   genesdev.cshlp.org

5. Use AlphaFold‑Multimer (ColabFold notebook) to model the SOD1:peptide complex.
   Open notebook: AlphaFold‑Multimer

   • Set model_type = alphafold2_multimer_v3 — shown to recapitulate peptide‑protein binding accurately.
     Ref: Frontiers in Bioinformatics (2022)

6. After running AF‑Multimer with your 5 peptides (4 generated + 1 known), plot the ipTM scores to compare relative binding confidence.

7. Write a 1‑paragraph summary of your results.

Part B — Final Project: L‑Protein Mutants

This is computationally heavy — start early.
More details: Final Project Page (external Notion): www.notion.so

Recitation — Protein Design Part II

Date: Wed Mar 5.
Slides: MS2‑Phage homework discussion (from Notion file reference)
Recording: Zoom

Lab — Protein Design Part II

Objective

Model protein–peptide interactions by generating peptide candidates (PepMLM‑650M) and predicting complexes (AlphaFold‑Multimer). Compare ipTM scores across candidates to select promising binders.

Concepts You’ll Learn

• Protein language models for peptide design
• Multimeric structure prediction (protein–peptide)
• ipTM as a binding‑confidence heuristic
• Practical workflows in Google Colab (GPU)

Quick Links

• PepMLM‑650M (Hugging Face)
• AlphaFold‑Multimer ColabFold

Reading & Resources — Week 5

• PepMLM‑650M (protein language model) — model card
• UniProt — SOD1 (P00441) — entry
• Genes & Development (2008) — SOD1‑binding peptide reference — paper
• AlphaFold‑Multimer (ColabFold) — notebook
• Protein–peptide modeling validation — Frontiers in Bioinformatics (2022)

Lecture — Genetic Circuits Part I

Date: Tue Mar 11.

Slides:

• Chris Mason — “A 500‑year plan for engineering life on Earth and beyond”
• Lisa Riedmayr — “Genetic Medicines”

Recording: Zoom

Homework — Genetic Circuits Part I

Key Link

• Gibson Assembly — Recitation/Protocol (Google Doc)

Questions

1. What are some components in the Phusion High‑Fidelity PCR Master Mix and what is their purpose?
2. What are some factors that determine primer annealing temperature during PCR?
3. There are two methods in this protocol that create linear fragments of DNA: PCR and restriction enzyme digest. Compare and contrast these two methods, including when one may be preferable.
4. Why does the PvuII digest require CutSmart buffer?
5. How can you ensure that the DNA sequences you digested and PCR‑ed will be appropriate for Gibson cloning?
6. How does the plasmid DNA enter E. coli cells during transformation?
7. Describe another assembly method in detail (e.g., Golden Gate Assembly) in 5–7 sentences with diagrams. Model this method with Benchling or a similar tool.

Recitation — Genetic Circuits Part I

Date: Wed Mar 12.
Slides: will be shared after the class.
Recording: Zoom

Lab — Gibson Assembly

Objective

Practice DNA assembly by preparing linear fragments (via PCR and/or restriction digest) and assembling them with Gibson Assembly, followed by transformation into E. coli.

Concepts You’ll Learn

• Primer design fundamentals
• PCR setup and thermocycling
• Restriction digests & buffer selection
• Gibson Assembly principles & workflow
• Transformation and selection

Protocol & Prep

• Gibson Assembly (Google Doc)
• Primer Design — Supplemental to Gibson Assembly Recitation

Reading & Resources — Week 6

• Primer Design — Supplemental to Gibson Assembly Recitation
• Introduction to Gibson Assembly — YouTube
• More from NEB — NEB: Gibson Assembly

Lecture — Genetic Circuits Part II

Date: Tue Mar 18.
Slides: will be posted after class.
Recording: Zoom

Homework — Genetic Circuits Part II

Key Link

• Week 7 — Homework & Lab Google Doc

Questions 1–3 (mandatory for all students)

1. How do endoribonucleases (ERNs) work to decrease protein levels? Name 2 differences between how ERNs work and how proteases work.
2. How does Lipofectamine 3000 work? How does DNA get into human cells and how is it expressed?
3. Explain what poly‑transfection is and why it’s useful when building neuromorphic circuits.

Questions 4–6 (added Mar 19; optional for MIT/Harvard, mandatory for Committed Listeners)

4. Genetic Toggle Switches
   • Provide a detailed explanation of the mechanism behind genetic toggle switches, including how bi‑stability is established and maintained.
   • Describe at least one induction method used to switch states, including molecular signals or environmental factors involved.
   • Note limitations. How many “switches” can we potentially chain? Is there a metabolic cost?
5. Natural Genetic Circuit Example
   • Identify and describe in detail a naturally occurring genetic circuit, emphasizing its biological function, components, and regulatory interactions.
6. Synthetic Genetic Circuit
   • Select and critically analyze a synthetic genetic circuit previously engineered by researchers (e.g., pDAWN). Provide details about its construction, components, intended function, and performance.
   • Discuss potential limitations or improvements suggested in subsequent literature or experimental data.

Recitation — Genetic Circuits Part II

Date: Wed Mar 19.
Slides: will be shared after class.
Recording: Zoom

Lab — Genetic Circuits

Objective

Translate design principles into an actionable workflow: from selecting promoters/regulators to drafting test plans for toggle switches or related motifs.

Concepts You’ll Learn

• Regulatory logic & bi‑stability
• Design strategies for toggle/switch constructs
• Practical testing plans and documentation

Reading & Resources — Week 7

• Gibson Assembly Recap (protocol) — Google Doc
• pDAWN optogenetic system — Addgene
• Synthetic gene circuits review — overview (2024)

Lecture — Cell Free Systems

Date: Tue Apr 1.
Slides: (will be posted when available)
Recording: Zoom

Homework — Cell Free Systems

Part A — Questions

Key readings:

• miniPCR — DNAdots: Cell‑free technology
• ACS Synth Biol (2024)

1. Explain the main advantages of cell‑free protein synthesis over in vivo expression. Name two cases where cell‑free is preferable.
2. Describe the main components of a cell‑free expression system and the role of each.
3. Why is energy provision/regeneration critical? Propose a method to ensure a continuous ATP supply.
4. Compare prokaryotic vs eukaryotic cell‑free systems. Choose a protein for each and justify.
5. Design an experiment to optimize expression of a membrane protein; list challenges and mitigations.
6. You observe low yield; provide three plausible causes and a troubleshooting plan for each.

Part B — Individual Final Project Report

MIT/Harvard tracking

• Tracking sheet

Key ordering dates (MIT/Harvard):

• Twist — Apr 11, 2025
• Thermo Fisher — Apr 11, 2025
• AddGene plasmids — Apr 11, 2025
• NEB — May 1, 2025 (rolling)
• GeneWiz — May 1, 2025

Recitation — Cell Free Systems

Date: Wed Apr 2.
Slides: will be shared here after class.
Recording: Zoom

Lab — Cell Free Induction

Objective

Induce a reporter in a cell‑free transcription‑translation (TX‑TL) system and quantify expression changes between treatments.

Concepts You’ll Learn

• TX‑TL reaction components and setup
• Induction strategies and controls
• Fluorescence quantification & fold‑change analysis

Protocol

• Global Labs Protocol (PDF) — Cell_Free_System_Laboratory_(Global_Labs).pdf

Post‑Lab Questions (Mandatory)

1. Using your lab images (or provided images), compute fluorescence fold‑change between treatments. Discuss LacI function in the context of the circuit used.
2. What would you expect if the same induction were performed in E. coli BL21(DE3)?

Reading & Resources — Week 9

• miniPCR — DNAdots: Cell‑free technology — PDF
• Recent cell‑free system advances — ACS Synth Biol (2024)
• Example project gallery — Google Slide Deck

Lecture — Bio Production

Date: Tue Apr 8.

Slides: Will be shared after class.
Recording: Zoom

Homework — Bio Production

Part A — Lecture Questions

1. Assume that all of the molecular biology work you’d like to do could be automated. What new biological questions would you ask, or what new types of products would you make?
2. If you could make metric tons of any protein, what would you make and what positive impact could you have?

Part B — Lab‑Linked Questions

Key Link:

• HTGAA 2025 Bio Production Lab Protocol (Google Doc)

Key Papers:

• Gene expression pattern analysis of an E. coli strain with high growth and lycopene production capability (fructose carbon source)
• Improvement of biomass yield and recombinant gene expression in E. coli by using fructose as the primary carbon source (1999)

Answer the following:

1. Which genes, when transferred into E. coli, will induce production of lycopene and β‑carotene, respectively?
2. Why must plasmids transferred into E. coli contain an antibiotic resistance marker for this workflow?
3. What outcomes might we expect when we vary media, fructose, and temperature in the overnight cultures?
4. Generally describe what OD600 measures and how it should be interpreted in this experiment.
5. Identify other experimental setups where acetone could be used to separate cellular matter from a compound we intend to measure.
6. Why engineer E. coli to produce lycopene and β‑carotene when Erwinia herbicola naturally produces them?

Learning Module — Exploring Carotenoid Bioproduction (optional but encouraged)

Use this space to begin thinking through DNA design related to carotenoid pathways (targets, operon structure, promoter choices, and measurement plan).

Recitation — Bio Production

Date: Wed Apr 9.
Slides: 2025: Lycopene & β‑Carotene Bioproduction
Recording: Zoom

Lab — DNA Design

1) DNA Design

1.1 Benchling Documentation

• Workspace reference — include links or screenshots of your Benchling workspace.
• Plasmid maps & features — promoters, CDS, antibiotic markers, restriction sites.
• Rationale — explain element choices (host compatibility, reporter/assay match).

1.2 FASTA Files

• Submission‑ready sequences for each designed construct.
• Verify correctness via in‑silico digest or alignment.

1.3 Provider Requirements (e.g., Twist)

• Order summary — list fragments/constructs, lengths, GC content, constraints.
• Checklist — avoid problematic repeats/hairpins; remove restricted sites; check stop codons/frames.

2) Detailed Protocol

2.1 DNA Assembly and Cloning

1. Overview — choose Gibson, Golden Gate, or restriction‑ligation as appropriate.
2. Linearization/fragment prep — digest or PCR; purify.
3. Assembly reaction — follow kit‑specific conditions (e.g., Gibson 50 °C for 15–60 min; Golden Gate cyclical 37 °C/16 °C).
4. Transformation — competent cells; plate on appropriate antibiotic.
5. Colony screening — colony PCR or miniprep → verification.

2.2 Reagents & Materials

• Assembly mixes (e.g., NEB Gibson/Golden Gate).
• Competent cells (e.g., DH5α, TOP10).
• LB‑Agar + antibiotic (Amp, Kan, etc.).
• Primers — 20–30 bp overlaps for Gibson or type IIS flanks for Golden Gate.

2.3 Useful Databases

• RCSB PDB
• UniProt

Reading & Resources — Week 10

• Bio Production lab protocol — Google Doc
• Lycopene via fructose — Biotechnol Lett (2016)
• Fructose improves yield & expression — Biotechnol Prog (1999)
• Protein expression in E. coli — Frontiers in Microbiology (2021)

Lecture — Building Genomes

Recording: Zoom

Homework — Building Genomes

Use this week to deepen your strain design plans and connect them to next week’s imaging/measurement workflows.

Recitation — Building Genomes

Recording: Zoom

Lab — Bio Production (Beta‑Carotene & Lycopene)

Objective

Work with E. coli carrying pAC‑LYC (lycopene) and pAC‑BETA (beta‑carotene) to optimize pigment production by tuning media, temperature, and carbon source.

Concepts You’ll Learn

• Fundamentals of bioproduction
• Tuning environmental factors to optimize production
• Measuring OD600 and absorbance spectra
• Handling cultures, plasmid systems, and acetone extraction

Key Plasmids

• pAC‑LYC (Addgene #53270)
• pAC‑BETA (Addgene #53272)

Workflow (2 Days)

• Day 1: Set up overnight cultures; vary LB vs 2YT, 37 °C vs 30 °C, and ± fructose.
• Day 2: Measure OD600; extract pigments with acetone; record absorbance spectra for lycopene vs β‑carotene.

References

• High growth & lycopene production (fructose)

Reading & Resources — Week 11

• pAC‑LYC — Addgene
• pAC‑BETA — Addgene
• Bioproduction with fructose — Biotechnol Lett (2016)
• OD600 & absorbance basics — ThermoFisher protocol

Lecture — Imaging and Measurement

Date: Tue Apr 22.

Slides: Lecture Slides
Recording: Class Recording

Homework — Imaging and Measurement

Final Project Homework

• Identify at least one aspect of your project you will measure (e.g., protein mass/sequence, biomarker presence/quantity).
• Describe all elements you will measure and how you will perform these measurements.
• Specify the technologies you will use (e.g., gel electrophoresis, DNA sequencing, mass spectrometry).

Waters Homework

1. Molecular weight — intact protein measurement.
2. Primary amino acid sequence — peptide map.
3. (Optional) Protein structure/shape — native vs denatured protein measurement.

Recitation — Imaging and Measurement

Date: Wed Apr 23.

Slides: Recitation Slides
Recording: Recitation Recording

Lab — Imaging & Measurement

Objective

Connect measurement to design by acquiring and interpreting LC‑MS data.

Concepts You’ll Learn

• Sample prep for intact mass vs peptide mapping
• Fundamentals of LC‑MS instrumentation & readouts
• Native vs denatured protein measurements
• Basic analysis and documentation

Reading & Resources — Week 12

• Immerse Cambridge (Waters) — About the lab
• Mass spectrometry overview (Proteomics) — Thermo Fisher
• Peptide mapping by LC/MS — Agilent (PDF)
• Intro to LC‑MS (lecture notes) — UCL (PDF)

Lecture — Frugal Science, Microbiome

Recording: Zoom

Homework — Frugal Science, Microbiome

Suggestion: Draft a resource‑aware protocol for a measurement or assay relevant to your final project (cost, accessibility, robustness).

Recitation — Frugal Science, Microbiome

Recording: Zoom

Lab — Makeup / Final Projects

Objective

Allocate bench time to complete experiments needed for your final project milestone(s).

Concepts You’ll Practice

• Resource‑aware experimental design (frugal science mindset)
• Measurement planning (microbiome & general wet‑lab workflows)
• Documentation and sample tracking

Recommendations

• Bring a clear checklist of experiments, materials, and expected outcomes.
• Coordinate with instructors on space/equipment.
• Log instrument settings, reagents, and environmental conditions.

Reading & Resources — Week 13

• Paperfuge & frugal science — Manu Prakash et al. (Nature Biomed Eng, 2017)
• Microbiome experimental design primer — Microbiome study design (Nat Rev Microbiol, 2018)
• Low‑cost field diagnostics overview — Ann. Rev. Biomed. Eng. (2021)

Lecture — Bio Design, Living Materials

Date: Tue May 6.

Slides: will be shared here after class.
Recording: Zoom

Homework — Week 14

Key Link

• Final Project Information

Recitation — Bio Design, Living Materials

Date: Wed May 7.

Slides: will be shared after class.
Recording: Zoom

Lab — Capstone Work Session

Objective

Allocate bench time to complete any remaining experiments and finalize documentation for presentations.

Concepts You’ll Practice

• Connecting measurements to design decisions
• Imaging or assays for key results
• Clear documentation (figures, captions, protocol notes)

Reading & Resources — Week 14

• Final project information — local page (converted content; link resolves once that section is built)
• Course Logistics — MIT/Harvard times & nodes

BioClub Tokyo (Japan)

Node links:

• Node Home
• BioClub Zoom

Students:

• Abhilaya Makkuva
• Ada Yazan
• Alireza Hekmati
• Anandita Amalia
• Aprajita Shukla
• Arisa Tani
• Aryan Choudhary
• Azmine Toushik Wasi
• Chairunnisa Amanda
• Dr. Data Cheuk Kwong Ng
• Elif Dilan Gündüz
• Eskalalita Mutamassika Dini
• Farhani Syafwani
• Hansen Jonathan
• Kavya Sreekanth
• Malika Tulenbergenova
• Md Rasel Uddin
• Muhammad Samudra Ilham
• Nina Kurowska
• Robina Nematullah Khan
• Rushda Parveen
• Syed Tauheed Ahmad
• Yash Sawant

Cellsius (San Francisco, US)

Node links:

• Node Home

Students:

• Matthew Berkshire (Chicago, USA)
• Etai Sapoznik (San Francisco, USA)
• Jenny Wang (Vancouver, Canada)
• Divya Srinivasan (Berkeley, USA)
• Heike Rapp (San Francisco, CA)

Designer Cells Lab at Yonsei University (Incheon, South Korea)

Node links:

• Node Home

Students:

• Ahmad Hader (Amman, Jordan)
• Xavier Rios (Sucre, Bolivia)
• Yousif Graytee (Baghdad, Iraq)
• Hyunseo Kwon (Incheon, Korea)
• Anastasia Arkhipenkova

Genspace (New York, US)

Node links:

• Node Home

Students:

• Anastasia Bernaz (Abbotsford, Canada)
• Amparo Saavedra (Santiago, Chile)
• Amy Chien (NYC, USA)
• César Rubio (Santiago, Chile)
• Chien Lu (Jersey City, US)
• David Chau (New York, USA)
• Oscar Schrag (Brooklyn, USA)
• Nikhil Kumar (NYC, USA)
• Patrik Artell (Lidingö, Sweden)
• Sohum Patnaik (NYC, USA)
• Tanisha Shaw (NYC, USA)
• Teddy Toussaint
• William Eliot (NYC, USA)
• Yehuda Binik (NYC, USA)

Lifefabs Institute (London, UK)

Node links:

• Node Home

Students:

• Adelina Krusteva (London, UK)
• Alejandro Mena (Toledo, Spain)
• António Couto (Lisboa, Portugal)
• Asma Khalil (Abu Dhabi, UAE)
• Auda Sakho (London, UK)
• Ava Chan (Oxford, UK)
• Beatriz Mesquita (Lisbon, Portugal)
• Cale Harrison (London, UK)
• Chloe Lee (London, UK)
• Cindy Orbegoso (Cambridge, UK)
• Defne Karagul (London, UK)
• Eduardo Goicoechea (Leamington Spa, UK)
• Esraa Alkhalil (Daraa, Syria)
• Federico Brunello (Naples, Italy)
• Folasewa Abdulsalam (Ramat‑Gan, Israel)
• Hana Urukalovic (London, UK)
• Holly Adams (Barcelona, Spain)
• Irendra Wijewardana (Utrecht, Netherlands)
• Kourosh Afshinjoo (Tehran, Iran)
• László Cseresznyés (Lisbon, Portugal)
• Mehmet Erkan Ozseyhan (Bursa, Türkiye)
• Mikhail Bagirov (Maastricht, Netherlands)
• Muhamad Muhamad Alkriz (Aleppo, Syria)
• Paula Rojas (Bogotá, Colombia)
• Richard Machoka (Nairobi, Kenya)
• Taline Frantz (Lisboa, Portugal)

Ottawa Bio Science (ON, Canada)

Node links:

• Node Home

Students:

• Alexander Proaño
• Berenice Ferruzca (Queretaro, MX)
• David J. Castillo (CDMX)
• Ethan Itovitch (Montreal, Canada)
• Kate Melanson (Ottawa, Canada)
• Mariana Valdez (Puebla, Mexico)
• Paul Romero (Quito, Ecuador)
• Toma (Teimurazi) Goch (Magdeburg, Germany)
• Valeria Rodriguez (Munich, Germany)

SynBioGenetics USFQ (Quito, Ecuador)

Node links:

• Node Home

Students:

• Alison Cabrera (Quito, Ecuador)
• Alonso Reyes‑Calderon (Lima, Peru)
• Anahi Nacato (Quito, Ecuador)
• Damaris Ganchozo (Guayaquil, Ecuador)
• David Vaca (Quito, Ecuador)
• Eduarda Pérez (Quito, Ecuador)
• Elvio Rodríguez Araya (Rosario, Argentina)
• Isabella Ortega (Quito, Ecuador)
• Jorge Moreano (Quito, Ecuador)
• Kelly Zúñiga Vera (Quito, Ecuador)
• María J. Méndez (Cali, Colombia)
• Melany Jumbo (Quito, Ecuador)
• Rodrigo Tamayo (Santiago, Chile)
• Vanessa Romero (Quito, Ecuador)
• Yasmine Yaakoubi (Tunis, Tunisia)

Victoria Makerspace (BC, Canada)

Node links:

• Node Home

Students:

• Elizabeth Vink (San Diego, USA)
• Marlene Taja (SLP, Mexico)
• Gustavo Muro Marchani (Calgary, Canada)
• Andrea Tambo (La Paz, Bolivia)
• Piyush Acharya (Bellevue, USA)