Week 1 HW: Final Project Ideas

HTBAA Homework #1

BlueRevive: Yeast-produced blue pigment for restoring used clothing

title##: ‘Week 1 HW: Final Project Ideas’

weight:## 10

Name##: Lesly Simbaña

1. What would I like to biomanufacture, and why?

I would like to produce indigoidine, a blue pigment, using engineered yeast and formulate it to restore the color of used cotton clothing. The initial product would be a pigment concentrate with a known concentration, intended for clothing repair workshops, secondhand stores, and small fashion brands. I would start with faded blue cotton T-shirts or light-colored garments that can be recolored blue.

My motivation is to reduce dependence on petrochemical colorants while helping people keep clothes in use longer. Fast fashion makes it especially relevant to consider both how colors are manufactured and how long garments remain useful. A biological pigment could address part of the manufacturing problem; restoring otherwise wearable clothing could add a benefit through longer use. Both benefits would need verification.

Indigoidine is chemically different from indigo, the familiar denim dye. Yeast production of indigoidine has already been demonstrated [1], and researchers have tested bacterially produced indigoidine on cotton [2]. Therefore, simply making blue pigment through fermentation is not the proposed innovation.

Why this matters in Ecuador

Ecuador provides a concrete setting for this idea. A USFQ case study of a textile factory followed wastewater from a Jet dyeing machine through treatment to sewer discharge and investigated whether treated water could be reused for dyeing [9]. This illustrates dyeing with liquid processing streams that require management. It does not describe every Ecuadorian workshop or establish a national practice.

In Guano, Chimborazo, a study of the Hilario factory examined polyester and polyester–cotton processing. The authors identified wet finishing as the wastewater-generating stage and described disperse dyes for polyester [7]. Fabric treatment and garment dyeing are related operations, but their recipes and water requirements are not interchangeable. My initial cotton-only pilot would require its own application tests.

How much water is involved? The Tungurahua provincial government’s territorial agenda, for the 2015–2017 planning period, reports approximately 200,000 m³/year of water use by textile dyeing factories in its industrial-water-demand section (p. 31) [6]. Converted to liters:

200,000 m³/year × 1,000 L/m³ = 200,000,000 L/year.

This is a historical provincial planning figure. The passage does not identify a precise measurement year or separate supply sources. It is not a current national total, a measured volume extracted directly from rivers, or a measure of water permanently lost. The agenda also describes industrial wastewater reaching provincial rivers with inadequate treatment [6].

A separate, measured factory example is available: Ramos et al. reported approximately 14,958 L of wastewater per operating day at Hilario, based on 2017 factory information [7]. Their calculation was:

2.77 L/s × 15 min/discharge × 60 s/min × 6 discharges/day = 14,958 L/day.

This is wastewater from one facility’s wet processing, not river withdrawal or the water needed to dye one garment. It should not be multiplied across Ecuador without representative production data.

Water quality also matters. In Pelileo, Tungurahua, Revelo et al. sampled textile wastewater from Dayantex in El Tambo. Their 2015 study reported pH values of 8–10 and an initial chemical oxygen demand of approximately 1,050 mg O₂/L [8]. Chemical oxygen demand indicates the amount of oxygen equivalent needed to chemically oxidize substances in the sample. These are historical factory-effluent measurements, not measurements of the river itself.

For broader, more recent context, INEC’s 2024 business environmental results report approximately 31 million m³ of public-network water use by manufacturing enterprises within the survey’s coverage of large and medium-sized businesses [10]. This includes manufacturing beyond textiles and is not direct river abstraction. I did not find a verified nationwide estimate specifically measuring river water withdrawn for textile dyeing. Establishing that quantity would require intake records, source information, and facility-level water balances.

These examples motivate a project that measures both freshwater demand and wastewater quality. Replacing the pigment alone will not eliminate water use, chemical auxiliaries, or treatment requirements.

Proposed innovation: selective color restoration

I propose combining yeast-produced indigoidine with a system that measures how much different areas of a garment have faded and applies a calibrated pigment dose to those areas. A color measurement would guide a programmable applicator toward an achievable blue target. The first prototype would handle large, simple faded regions; restoring complex prints would be outside its scope.

My research question is: Can selective application of yeast-produced indigoidine restore acceptable color using less pigment and freshwater than full-garment recoloring, while maintaining wash durability and fabric quality?

I did not identify a demonstration of this exact combination in the sources reviewed. This makes it a research opportunity, not a proven claim of worldwide novelty. A comprehensive patent and literature review would be needed before making that claim.

I would compare matched garments in three groups: untreated, fully recolored, and selectively restored. Measurements would include color uniformity, wash and rubbing durability, pigment use, freshwater input, energy, wastewater quality, and user acceptance. Environmental performance should be compared per garment meeting equivalent quality requirements. Biological origin does not automatically establish safety, biodegradability, or a lower environmental footprint.

2. What living system would I use?

I would use an engineered strain of Rhodotorula toruloides, called Rhodosporidium toruloides in the reference paper, as the manufacturing chassis [1]. This is a yeast platform with published indigoidine production, rather than unmodified baking yeast.

Inputs: glucose as the initial carbon source, a nitrogen source, mineral nutrients, water, and oxygen. I would begin with defined inputs to make results easier to interpret. Agricultural by-products could be evaluated later, without assuming that they would reproduce glucose-based performance.

Biological conversion: cellular metabolism supplies glutamine. An activated indigoidine synthetase converts two glutamine molecules into the blue pigment; an auxiliary enzyme enables synthetase activity [3]. Production would take place in an aerated bioreactor with controlled feeding and cultivation conditions.

Outputs: pigment, yeast biomass, carbon dioxide, and residual liquid. After cultivation, I would recover pigment, separate cells, and prepare a standardized formulation. I would measure how much pigment is associated with cells and how much is in the liquid instead of assuming complete secretion. The final clothing product would be designed to contain no viable production yeast.

I would not assume that the pigment dissolves in water or binds to cotton without assistance. A pigment dispersion with an appropriate binder would be compared with a reference formulation, evaluating adhesion, fabric feel, durability, and the environmental contribution of the auxiliary. Recovery and formulation are substantial development tasks.

An alternative chassis is S. cerevisiae. A published study reached 0.98 g/L in a 2-L bioreactor and showed that production depended on respiratory metabolism [3]. This supports its use as a learning platform, but its performance should not be substituted for R. toruloides data.

3. How would I use automation?

Biological prototyping. An Opentrons OT-2 liquid-handling robot would distribute media, prepare dilutions, and organize samples. Its official documentation demonstrates automated liquid transfers and serial dilution in 96-well plates [4]. Incubation and aeration would require suitable equipment; an external plate reader would analyze processed samples, with manual transfers unless additional integration were available.

I would evaluate 24 medium conditions in triplicate: 24 × 3 = 72 experimental cultures. The remaining 24 wells would hold appropriate controls and blanks. Pigment concentration would be determined from processed samples using a calibrated pigment standard, avoiding confusion between cell turbidity and pigment concentration. Promising conditions would then be checked in small bioreactors because oxygen transfer in plates differs from that in tanks.

For planning, I assume one screening round per week, including preparation, up to five days of cultivation, and analysis. Three rounds would evaluate 72 conditions and 216 experimental cultures, plus controls. This is a workflow assumption, not a guaranteed robot throughput. Automation improves repeatability and reduces repetitive labor; it does not shorten biological growth automatically.

Textile prototyping. The robot would prepare dose series for matched cotton swatches. A reflectance spectrophotometer or calibrated camera would record initial and final color. An empirical model would connect starting color, applied dose, and final appearance, selecting the lowest dose that meets quality and durability requirements.

Manufacturing. At production scale, sensors would monitor pH, temperature, and dissolved oxygen while controllers adjust feeding, aeration, and agitation. Garment treatment would use a color-measurement station and a programmable dispenser on a positioning table. Particle settling, viscosity, clogging, drying, and placement accuracy would need testing. The OT-2 would support development; bioreactors and textile equipment would manufacture and apply the product.

4. How much would I need to make, and how long would it take?

4a. A meaningful pilot scale

I define a pilot of 1,000 used cotton T-shirts weighing 0.20 kg each. I assume that retained pigment equal to 2% of dry fabric mass will achieve the target color. This is a sizing assumption, not a demonstrated dose for this formulation. I use the entire garment mass so that the calculation does not assume savings from selective restoration before testing it.

Fabric mass = 1,000 garments × 0.20 kg/garment = 200 kg.

Required retained pigment = 200 kg fabric × 0.02 kg pigment/kg fabric = 4 kg.

I assume 80% retention after application, finishing, and initial washing, and 80% recovery of the pigment produced during separation and formulation. These are different efficiencies and must be measured separately.

Recovered pigment needed = 4 kg / 0.80 = 5 kg.

Pigment that the yeast must produce = 5 kg / 0.80 = 6.25 kg.

Therefore, the manufacturing target is 6.25 kg of pigment in the culture, yielding 5 kg of usable pigment and approximately 4 kg retained in clothing. These masses refer to active pigment, not total broth or formulation mass.

4b. Culture volume and manufacturing time

As a feasibility reference, Wehrs et al. reported 86.3 ± 7.4 g/L with glucose in a high-gravity fed-batch process and 2.9 ± 0.8 g/L with sorghum hydrolysate in batch cultivation, using 2-L bioreactors [1]. These are different process conditions. Neither figure validates large-scale performance for my project.

For planning, I assume a target of 10 g/L after five days using glucose. This titer–time combination is an unvalidated engineering target at the proposed scale, not a published result.

Required culture volume = 6,250 g / (10 g/L) = 625 L.

I would provisionally select a reactor capable of a final working volume of 800 L, for example a nominal 1,000-L tank if its design allows adequate space for aeration and foam.

Pigment produced per batch = 800 L × 10 g/L = 8 kg.

Recovered pigment per batch = 8 kg × 0.80 = 6.4 kg.

Pigment retained in garments = 6.4 kg × 0.80 = 5.12 kg.

One batch would exceed the 4-kg retained-pigment target, providing some margin without guaranteeing protection against failed batches.

Assumed average cultivation productivity = 10 g/L / 120 h = 0.083 g/(L·h).

Starting with an available strain and established process, I budget one day for inoculum and preparation, five days for cultivation, and two days for recovery, formulation, and basic quality control: approximately eight days to obtain pigment. One additional day for cleaning gives an approximately nine-day reactor cycle under sequential scheduling.

Assuming a garment-treatment capacity of 200 T-shirts/day, application would take 1,000/200 = five working days. Without overlapping production and application, the total is approximately 13 days to finish applying the formulation. Final quality-release testing could add time. These equipment capacities and durations are planning assumptions.

This estimate excludes strain construction, formulation development, and equipment validation. The initial screening alone takes three weeks under the proposed schedule; full development could require months or longer.

Sensitivity to uncertain assumptions:

• At 3 g/L, the required cumulative culture volume is 6,250/3 = 2,083 L: three 800-L batches. Assuming eight days of processing per batch and one cleaning day between batches gives approximately 26 days through processing of the third batch. This holds batch duration constant only for the scenario calculation.

• At 50% textile retention and 80% recovery, the culture must produce 4/(0.50 × 0.80) = 10 kg: two batches at 10 g/L.

• If the retained-pigment dose must be 4% rather than 2%, culture production must reach 12.5 kg: also two batches at 10 g/L.

Textile performance can therefore be as important as yeast productivity.

4c. How I would measure water savings

The Ecuadorian figures provide context, not a baseline for these cotton T-shirts. The 800-L culture volume is also not the process’s total water footprint. I would meter freshwater used for medium preparation, cleaning, pigment recovery, formulation, application, and rinsing, as well as record internal reuse and wastewater discharge.

Freshwater savings per accepted garment = freshwater input per accepted garment for full recoloring − freshwater input per accepted garment for selective restoration.

Both routes would include the same accounting boundary, including pigment manufacture. I would report L/accepted garment and L/kg of accepted fabric, together with wastewater volume and pollutant load. No numerical water-saving claim is justified before these measurements.

5. What do I not know yet?

1. Fixation, stability, and suitability for clothing. Will the formulation produce an acceptable blue on used cotton, withstand washing and rubbing, preserve fabric feel, and be suitable for skin contact? I would compare formulations and measure color, transfer to other fabrics, fiber damage, residual chemicals, and storage stability. A 2026 study found substantial pigment loss during storage of extracts from another producer [5]. That identifies a concern but does not predict the durability of this yeast-derived formulation on clothing.

2. Productivity and recovery at scale. Can the process reach 10 g/L in five days at an 800-L working volume and recover 80% of pigment? I would measure titer, productivity, substrate consumption, oxygen demand, pigment distribution, and recovery losses at successive scales. Extraction energy, solvents, and equipment costs could determine feasibility.

3. A real advantage over full recoloring. Does selective restoration reduce freshwater and pigment demand while producing clothing people want to wear again? I would compare the three garment groups, recording accepted and rejected pieces, retreatment, resource use, wastewater quality, cost, and user acceptance. For an Ecuadorian pilot, I would also document the water supplier or intake source and the receiving wastewater system before making any claim about river protection.

References

[1] Wehrs, M., et al. (2019). Sustainable bioproduction of the blue pigment indigoidine: Expanding the range of heterologous products in R. toruloides to include non-ribosomal peptides. Green Chemistry, 21, 3394–3406. https://doi.org/10.1039/C9GC00920E

[2] Ghiffary, M. R., Prabowo, C. P. S., Sharma, K., Yan, Y., Lee, S. Y., & Kim, H. U. (2021). High-Level Production of the Natural Blue Pigment Indigoidine from Metabolically Engineered Corynebacterium glutamicum for Sustainable Fabric Dyes. ACS Sustainable Chemistry & Engineering, 9(19), 6613–6622. https://doi.org/10.1021/acssuschemeng.0c09341

[3] Wehrs, M., et al. (2018). Production efficiency of the bacterial non-ribosomal peptide indigoidine relies on the respiratory metabolic state in S. cerevisiae. Microbial Cell Factories, 17, 193. https://doi.org/10.1186/s12934-018-1045-1

[4] Opentrons. (n.d.). Python API: Tutorial. Official technical documentation. https://docs.opentrons.com/python-api/tutorial/

[5] Production and extraction of a natural blue colorant from Streptomyces lavendulae: Insights into indigoidine stability and its potential use in sustainable dyeing. (2026). Biocatalysis and Agricultural Biotechnology. https://doi.org/10.1016/j.biteb.2026.102715

[6] Gobierno Provincial de Tungurahua. (n.d.). Tungurahua desde la visión territorial: Agenda [2015–2017 planning period], p. 31, sections 1.1.7.3–1.1.7.5. https://www.tungurahua.gob.ec/images/archivos/transparencia/2017/AgendaTerritorialTungurahua2016.pdf

[7] Ramos, K., Parada, M., & Godoy, S. (2018). Evaluación y diseño de un sistema de tratamiento de agua residual para la fábrica textil Hilario [Evaluation and design of a wastewater treatment system for the Hilario textile factory]. Perfiles, 1(19). https://doi.org/10.47187/perf.v1i19.13

[8] Revelo, A., Proaño, D., & Banchón, C. (2015). Biocoagulación de aguas residuales de industria textilera mediante extractos de Caesalpinia spinosa [Textile wastewater biocoagulation using Caesalpinia spinosa extracts]. Enfoque UTE, 6(1). https://doi.org/10.29019/enfoqueute.v6n1.50

[9] Llive Carrillo, W. R. (2012). Análisis y evaluación de una planta de tratamiento de aguas residuales de una industria textil [Analysis and evaluation of a textile industry’s wastewater treatment plant] [Chemical engineering undergraduate thesis, Universidad San Francisco de Quito]. https://repositorio.usfq.edu.ec/handle/23000/1968

[10] Instituto Nacional de Estadística y Censos (INEC). (2026, March 31). Principales resultados del Módulo de Información Económica Ambiental en Empresas 2024, p. 22. https://www.ecuadorencifras.gob.ec/documentos/web-inec/Encuestas_Ambientales/EMPRESAS/2024/MIEAE_2024_PPT.pdf

AI use disclosure

AI client: OpenAI Codex. Date: September 21, 2026. AI assisted with searching and assessing sources, framing the proposed innovation, and checking arithmetic. No experiments were performed.

User prompt 1, translated from Spanish: “Please see the attached document where are my responses about my homework about biomanufacturing, there are some phrases in spanish and english that need to be checked. Let my explain my idea in general, so you can have context about it . My idea is for yeast to produce colorants to replace colorants used in the fashion industry because of fast fashion. There is already a startup in Germany doing this. Please confirm that I have written well and the ideas are well connected and understanding if not let me know where I have to check. Also check citation if well written. ”

User prompt 2, translated from Spanish: “The assignment must be in English, there are some words that I need to translate into English, please translate that. Also, Can you add some context about Ecuador, how garments are dyed, and how much river water is used in Ecuador? Find reliable bibliography supporting this and cite them, but first let me give the link to confirm that the links and information are correct and realiable.

Final Project