This page presents a timeline of our team's progress.
This page presents a timeline of our team's progress.
Nico gathered AEI instructors and assigned a collection of background reading for synthetic biology.
PET (polyethylene terephthalate) is ethylene glycol and terephthalic acid (TPA) linked by ester bonds, and makes up roughly 10% of global plastic production. Mechanical recycling downcycles the material each time it is remolded, but enzymatic recycling can be repeated indefinitely because it breaks PET all the way back down to its monomers. PETase/polyester hydrolase enzymes hydrolyze those ester bonds, cutting the chain into TPA and ethylene glycol (EG) via the intermediates MHET and BHET. Because PET is semi-crystalline, enzymes can only attack the amorphous regions easily, and PET's glass transition temperature (roughly 65–70°C) matters a great deal — near or above that point PET softens and enzymes work much faster.
A cutinase from Thermobifida fusca was the first PETase activity described, back in 2005. The turning point came in 2016, when Ideonella sakaiensis — discovered in soil at a Japanese recycling plant — was found to use PET as its sole carbon source, via PETase (PET→MHET) and MHETase (MHET→TPA+EG); it fully degraded a thin PET film in about six weeks at 30°C. By 2024, more than 99 natural PETases had been catalogued. Four engineering strategies keep recurring across the literature for improving these enzymes: increasing thermostability (e.g. added disulfide bonds), enlarging the active-site/binding pocket to accommodate bulky polymer, improving enzyme–polymer surface contact (fusing hydrophobic or binding domains), and simply speeding up catalytic turnover through computational design. Beyond breaking PET down, there's also a growing interest in upcycling the resulting monomers — turning TPA into vanillin or catechol, and EG into glycolic acid, biosurfactants, or PHA bioplastic. Industrially, Carbios in France already runs a pilot plant processing about 250 kg of PET per day with an engineered LCC enzyme, with a full-scale plant targeted for 2025–2026. Crystalline PET, enzyme long-term stability, and expanding beyond PET to other plastics remain the open challenges.
This text surveys the companies working in this space. Carbios (France) is the pioneer, using an engineered LCC cutinase to depolymerize 97% of PET in 16 hours at 60°C, with partners including L'Oréal, Nestlé, PepsiCo, and Novozymes. Samsara Eco (Australia) aims for "infinite recycling" using an enzyme library that degrades PET in minutes, and is building toward a 20,000 t/yr plant in Melbourne with Woolworths. Protein Evolution Inc. and Epoch Biodesign both use AI/generative-AI approaches to design new enzymes, focused on textiles. Ambercycle does textile-to-textile recycling. Breaking (incubated by Colossal Biosciences/Harvard Wyss) takes a very different approach, using a microbial consortium rather than isolated enzymes to attack polyolefins, which are notoriously inert. Plastic Entropy (Spain) is a rarer case — an academic spin-out using waxworm-derived enzymes to target polyethylene, which is unusually hard to degrade. Intropic Materials embeds enzymes directly inside plastic products so they only degrade in compost conditions, a "preventive" design strategy. Across the field, two broad strategies recur: closed-loop recycling (recovering monomers to make new plastic) versus biodegradation (breaking waste down to benign end products) — and the shared challenges are mixed/impure waste streams, enzyme specificity, pretreatment costs, and virgin plastic often still being cheaper.
This text reviews how machine learning is used to predict and optimize lipase enzymes — production yield, catalytic activity, stability, and substrate specificity — across algorithm types including ANNs, genetic algorithms, CNNs, deep learning, random forests, SVMs, decision trees, and KNN, each with its own accuracy/cost tradeoff. A key gap the review identifies is that very few studies use AI to redesign enzyme structure directly; most instead optimize production conditions or predict yield, partly because enzyme-activity datasets are sparse and biased toward "success" data. The review also connects to bioethics, citing the Engineering Biology Research Consortium's Statement of Ethics (environment, social protection, benefit/harm balance, fairness, open early research, and individual rights).
A Japanese biotech company built around a proprietary single-cell whole-genome sequencing platform that has produced the world's largest enzyme-sequence database (bit-GEM: 2+ billion genes, growing by roughly a billion a year). Combining that database with AI and robotics ("bit-QED") to engineer and evolve enzymes, bitBiome claims a 40× better hit rate for finding good enzymes and a 65%+ reduction in R&D time and cost. bitBiome identified a natural PET-degrading enzyme from soil metagenomic sequences and improved it 13× over three rounds of engineering plus an added enhancer — the modified enzyme fully degrades PET film in about 15 days without heating, active at a comparatively mild 40°C.
This text traces iGEM's origin as an MIT course in January 2003, growing into a competition from 2004 (five teams) to 250+ teams by 2016. A dedicated high-school track was added in 2011 and folded into the main competition in 2015. The paper's case study, the University of Lethbridge's citywide high-school iGEM team, follows a model of recruiting collegiate/alumni mentors, running intro workshops, and supervising lab work; surveyed students reported the program was enjoyable and challenging (88%), that it increased interest in a science career (75%), and that it built a sense of community (83%). The paper's central idea is that iGEM's modularity (BioBricks/standard parts) makes synthetic biology accessible in a "LEGO Mindstorms for biology" way, lowering the barrier for younger students.
This guidebook describes various phases: starting up (defining goals, recruiting a multidisciplinary team of 8–12), exploratory planning (project scope, modeling, documentation, fundraising), extreme execution (sustained lab work and handling failure), nearing completion (finalizing documentation, "document to win"), and the Jamboree itself and its aftermath. Its central mindset: success isn't only measured in medals, but also in publication, publicity, funding continuation, and recruiting future team members.
This text gives actionable rules for supervisors, drawn from ten years of Wageningen University's iGEM experience: assemble a complementary multidisciplinary team; fit iGEM within the curriculum; support a positive working culture; steer students toward feasible designs; coach with increasing independence as the project matures; support soft-skill development and outreach; provide infrastructure and seed funding; build and use an iGEM network; prepare students thoroughly for the Jamboree; and celebrate generously before restarting the cycle.
This is a large-scale data study (Santolini et al.) of 2,406 iGEM teams' wiki and notebook data, looking for what actually predicts success. The number of active wiki editors predicts success far better than raw team size. Advisors and instructors both help, likely via mentorship and feedback speed. Wiki engagement and more detailed wikis both correlate with success, as does a team's centrality in the inter-team collaboration network — though teams that are too tightly clustered among themselves tend to do worse. Prior participation, and especially prior success (a gold medal the year before), strongly predicts future success. Team performance scales with active editor count only up to about 12 people, then plateaus. Notably, teams that recover from an early setback tend to adopt "successful team" behaviors roughly a year before their results actually improve — organizational change precedes results.
This text introduces the culture of the 2024 Paris Jamboree (roughly 400 teams, 4,000+ attendees, 50+ countries). It argues that humor and authenticity build public trust in scientists more effectively than typical "corporate" science communication, citing research that intellectual humility builds more trust than intellectual superiority. It notes that serious science and fun coexist at the event — 2024's top prizes went to teams working on dandelion-derived rubber, a CRISPR 3D-genome-editing toolbox, and a bioengineered mosquito trap — and that the Jamboree's "Responsibility Conference" brought together the US State Department and OECD to discuss synthetic biology governance, underscoring how deeply Human Practices is built into iGEM's culture.
This text frames the "why space + synthetic biology" argument around loop-closure: recycling and reusing resources for a circular economy in space, to reduce costly resupply from Earth. It surveys opportunities including human-waste processing and reclamation (e.g. ESA's MELiSSA project), food production, soil remediation, pharmaceutical biomanufacturing, hydrogen production, and bio-concrete/myco-architecture. Its central argument is that current ISS waste handling — dry, compact, and eject to burn up — isn't sustainable for long missions, and biological recycling is the alternative. It also stresses a two-way benefit: space biotech research tends to also solve Earth problems (plastic, organic, and electronic waste recycling; drug manufacturing in remote areas; carbon capture), tying directly to the UN Sustainable Development Goals, and uses NASA's Technology Readiness Level framework to show most of these microbial technologies are still low-TRL.
This text proposes building space habitats out of biologically produced materials rather than materials shipped from Earth. It tests common bioplastics — agarose (water-soluble, brittle when dry), PLA (the most widely produced bioplastic, UV-resistant, low degradation), and PHA (a bacterial fermentation product, UV-stable but more biodegradable than PLA) — against the properties a habitat material needs: blocking UV, transmitting visible light for photosynthesis inside, and holding a pressure difference against the thin Martian atmosphere. As proof of concept, the authors grew eukaryotic green algae inside a 3D-printed PLA bioplastic habitat under a Mars-like 600 Pa CO₂ atmosphere. The paper's larger claim — that habitats made from the products of biology itself are scalable and sustainable — complements this team's own PET-to-habitat/PHA storyline directly.
Four documents specific to enzyme engineering strategies for PET breakdown (two further documents in this folder duplicated root-folder papers already covered above).
This text covers engineering of all three enzyme classes in the PET breakdown pathway — PET hydrolases (PETases), BHET hydrolases, and MHET hydrolases — and lists the industrially desired properties for any of them: high catalytic activity, high substrate/product tolerance, high thermostability, high expression/solubility, and acidic pH tolerance. Four engineering approaches recur: rational design (targeted mutations from known structure), semi-rational design (mutating residues near active-site hotspots, screening small-to-moderate libraries), directed evolution/high-throughput screening (large random-mutagenesis libraries), and the newer computational design approach that increasingly pairs with AI/ML to predict good variants before any lab testing happens. A key insight: MHET/BHET hydrolase engineering lags well behind PETase engineering, since most past effort has focused on PETases specifically. Mechanical recycling is still more efficient for clean PET, but colored, thermoformed, or textile PET often can't be mechanically recycled at all — which is exactly where enzymatic recycling earns its keep.
This text describes a scaffolded enzyme complex combining a chimeric Ideonella sakaiensis PETase (PET→BHET/MHET), a chimeric Candida antarctica lipase B (MHET→TPA), and a carbohydrate/cellulose-binding module on a scaffolding protein that anchors the whole complex tightly to the PET surface. The assembled complex reached 6.5× higher hydrolysis efficiency on highly crystalline PET and 8.0× higher on real waste PET, compared to free, unlinked enzymes. The core idea — pairing enzymes that act at sequential steps on a shared physical scaffold, rather than using them separately in solution — is the same "proximity effect" logic used in natural cellulosomes.
Cellulosomes are natural multi-enzyme complexes from anaerobic bacteria such as Clostridium thermocellum that are extremely efficient at degrading cellulose: a scaffoldin protein with nine cohesin domains plus a cellulose-binding module, with each cellulase enzyme carrying a matching dockerin that binds a cohesin, anchored to the cell surface by a further anchoring protein — up to 63 enzymes in one complex. Two mechanisms explain the efficiency gain from clustering: the proximity effect (intermediate products get handed directly to the next enzyme) and the targeting effect (the binding module keeps the whole assembly anchored to the substrate). The authors engineered Kluyveromyces marxianus yeast to display this complex and achieved the highest-ever reported ethanol yields from any engineered yeast cellulosome to date.
This is bitBiome's own primary research paper, discovering a novel PET hydrolase (bbPET0069) from a soil bacterial genome sequence via their single-cell sequencing database. Structurally it's a cutinase-like Type I PETase, but unusually lacks the disulfide bonds most engineered PETases rely on for stability. The enzyme showed strong synergy with CALB (the same two-enzyme logic as the Korea University paper above); combining 3D structural modeling, a protein language model, and three rounds of directed evolution produced a 12.6-fold increase in PET degradation activity with CALB present, reaching up to 95.5% conversion of PET to terephthalic acid. The paper cites the global context directly: roughly 460 million tonnes of plastic are produced annually, and only about 9% is recycled.
Six reference works on ethics, bioethics, and biosecurity — the summary below focuses on each book's core framework and structure rather than every case study inside it.
This text teaches "principlism," derived from a shared "common morality" across cultures. Its four principles — respect for autonomy (the basis of informed consent), nonmaleficence ("do no harm"), beneficence (an obligation to actively contribute to others' welfare), and justice (fair distribution of benefits, risks, and costs) — are meant to be balanced case by case rather than ranked. The authors explicitly push back on the common criticism that their framework over-privileges autonomy as an "American individualism" bias, arguing all four principles carry real weight.
This text surveys particular moral principles (autonomy, nonmaleficence, beneficence, utility, justice) and the major moral theories relevant to bioethics debates — utilitarianism, Kantian ethics, principlism, natural law theory, Rawls' contract theory, virtue ethics, ethics of care, feminist ethics, and casuistry. Its most relevant chapters for a synthetic biology project are on human research ethics and genetic choices, which cover historical research-ethics failures (Tuskegee, Willowbrook, human radiation experiments) that motivated today's IRB/informed-consent requirements.
This text gives short essays, such as "Seven Threats to Ethics," which works through ideas that make people doubt ethics is possible at all — the death of God, relativism, evolutionary "selfish gene" arguments, determinism, and the unreasonable demands of some moral theories — arguing that none of them actually destroys the possibility of ethics. Blackburn's recurring theme is that ethics functions like an "ethical climate," a largely invisible set of norms shaping what a society finds acceptable, and that this climate can go badly wrong — his central historical example being the climate that enabled Nazi Germany.
This is a core "dual-use research of concern" (DURC) governance text. Its central concept is dual use: technology with legitimate civilian or scientific benefit that could also be misused for harm. After building an analytic framework across its first four chapters — including a practical "Decision Framework" for assessing how much oversight a given dual-use technology needs — the bulk of the book applies that framework to case studies, including synthetic biology with standard parts, which maps directly onto iGEM/BioBricks. Its key takeaway is that dual-use risk isn't a fixed property of a technology; it depends on context and accessibility, and governance should be proportionate and technology-specific rather than a blanket restriction.
This is a modern, post-COVID biosecurity governance reference. It contrasts top-down (state/international regulation) with bottom-up "grassroots" governance — including the role of education and outreach, directly relevant to a Human Practices program. It distinguishes biosafety (protecting people/environment from unintentional exposure) from biosecurity (preventing deliberate misuse), a line synthetic biology tends to blur. It also covers cyberbiosecurity (securing DNA synthesis order screening and digital sequence data), information hazards (how publishing certain synbio information can itself create risk), and practical governance tools like DNA-synthesis screening guidance and early-warning "tripwires." A soil-habitat chapter considers the biosecurity and ecological implications of releasing engineered organisms into soil, which is directly relevant if this project involves any environmental release.
This text examines "appeals to nature" as a contested argument against synthetic biology, asks whether synthetic organisms can hold intrinsic value or any moral status at all, and connects those philosophical questions to real policy questions about how synthetic biology is culturally received and discussed (including critiques of "playing God" framing). Its key argument, worth being able to articulate both ways, is the "unnaturalness" objection — that engineering life is inherently wrong because it isn't natural — versus the counterargument that humans have always modified nature through agriculture and selective breeding, so synthetic biology may be a difference of degree rather than of kind.
This is a standard undergraduate primer on molecular biology techniques, moving from historical context through core molecular biology tools, cloning and PCR methodology, and into applications like genomics, medical/forensic uses, and transgenic organisms. Its clearest vocabulary distinction is between molecular cloning (copying a DNA fragment into a vector) and organism cloning (creating a genetically identical organism) — explicitly separated as "two sorts of cloning."
This is an actual MIT high-school/early-college synthetic biology curriculum. Its foundational chapters introduce the abstraction hierarchy (parts→devices→systems) for managing biological complexity and the role of standardization in DNA assembly, before moving into hands-on labs built around the design-build-test cycle — engineering bacteria to produce a banana scent, comparing predicted versus measured genetic outcomes, modeling "bacterial photography," comparing chassis strains, and using redundancy to manage unreliable biological performance. The abstraction hierarchy is the central organizing idea here, and it's the same concept underlying BioBricks and the iGEM parts registry.
This is a computational counterpart to the wet-lab books — how synthetic biology gets designed in silico before any lab work happens. Organized around component design, circuit design, circuit analysis/simulation, and DNA assembly automation, mirroring the same CAD→simulate→optimize→build pipeline used in electronics engineering, complicated in biology by the stochastic, noisy behavior of biological systems compared to deterministic circuits.
This is a "just the essentials" reference in the collection, written by long-time Imperial College iGEM supervisors specifically with students in mind. Its nine chapters move from basic biology and engineering concepts through the parts/devices/systems abstraction hierarchy and modeling, into a dedicated iGEM chapter and a closing chapter on the societal impact of synthetic biology.
This text is useful for Human Practices framing. It contrasts two strategies for "making life": a top-down "À la Frankenstein" approach that starts from existing complex life and strips it down (e.g. genome minimization), against a bottom-up "À la Werker" approach that builds a living system upward from non-living chemical components (e.g. protocells). Later chapters cover real case studies (engineered artemisinin precursor, synthetic chromosomes) and a dedicated chapter on the iGEM competition itself, "from BioBrick to Jamboree."
This is a broad, practical handbook moving from standardizing biology (DNA assembly standards, measurement) through engineering with legacy chassis organisms (bacteria, yeast, microalgae, mammalian cells, plants) to constructing genuinely new biology (semi-synthetic minimal cells, expanded genetic codes). Its introduction makes a historical point worth remembering: synthetic biology, like molecular biology before it, largely emerged from non-biologists — physicists and computer scientists — bringing engineering perspectives to biology.
This is a lab-protocols book, covering 27 chapters across gene circuits and biochemical pathways, genome editing (notably CRISPR-Cas12a-based tools), genome-scale computing and machine-learning-based design, and molecular assembly methods including cell-free synthesis and optogenetic control. CRISPR-Cas systems are the clear recurring tool across chapters, and machine learning is now integrated directly into circuit design and gene-essentiality prediction — the same AI trend seen in the PET-enzyme-engineering papers above.
This text is focused on integrating synthetic biology with "big data" — genomics, transcriptomics, proteomics, and interactomics — across topics from targeted therapies and microbiome engineering to computational multi-level modeling. Quorum sensing (bacterial cell-to-cell communication via signaling molecules) is worth knowing well here, since it's widely repurposed as an engineering tool for coordinating populations of engineered cells.
This covers DNA synthesis and genome engineering, control of protein expression, spatial engineering, early therapeutic applications (including CAR T-cell engineering), and — notably — a dedicated part on the societal ramifications of synthetic biology. That final part surveys public perception across the US and Europe and compares historical technology "frames": genetic engineering as "technology as conflict," nanotechnology as "technology as progress," IT as "technology as gadget" — and asks which frame synthetic biology will inherit. It champions Responsible Research and Innovation (RRI) as the way forward.
This text's chapters on Technical Issues, Development Issues, and Safety Issues are written specifically around the real challenges iGEM teams face, making it a strong first stop for any "how do successful iGEM teams handle X" question.
This text has six parts spanning biological basis, modeling, modular parts and circuits, synthetic genomes, disease/therapeutics, and industrial chemicals production. Best used as a reference or glossary source when the deepest or most technical explanation of a specific sub-topic is needed, rather than read narratively front to back.
This is a journal article documenting a real case study of a Delft University iGEM team's own Human Practices process, for a bacteriophage-based project called PHOCUS. It shows how the team integrated Responsible Research and Innovation (via the classic "AIRR" framework — Anticipation, Inclusion, Reflexivity, Responsiveness) with Safe by Design, building safety directly into the technology rather than adding safeguards afterward — concretely, using physical encapsulation to contain their engineered bacteriophage and prevent off-target infection. The authors are honest that applying RRI/Safe by Design doesn't guarantee a project is fully safe, or that future governance will be future-proof; it's a structured process for thinking about risk, not a guarantee of eliminating it. It's a strong template for structuring this team's own Human Practices write-up.