Introduction

Our project aims to engineer TfCut2 to degrade PET in cotton-PET textile waste (also called polycotton), one of the most common types of fast-fashion waste in the clothing industry. Therefore, the ultimate goal of our measurement experiments is to demonstrate and quantify the ability of our engineered TfCut2 enzymes in degrading PET in cotton-PET textile waste.

We designed 6 novel mutant enzymes through a rigorous engineering pipeline, integrating both the machine learning approach and the rational design approach with protein structures (See our modeling page for further details). After our engineering success (See our engineering page for further details), protein purity will be verified by Coomassie Blue Staining and Western Blot to confirm target protein expression. The enzyme activity verification will be conducted by para-nitrophenyl butyrate (pNPB) assay. Furthermore, when the Coomassie Blue staining results indicated enzyme impurity, we used quantitative data from the pNPB assay to standardize enzyme activity through kinetic analysis, ensuring consistent enzyme concentrations across all experiments.

UV absorbance assay was used as a quantitative assessment to detect the release of terephthalic acid (TPA) and mono 2 hydroxyethyl terephthalic acid (MHET) following PET depolymerization. When the wild type TfCut2 and six variants were applied to degrade PET or textile substrate, this method provides a rapid and direct way to measure PET degradation efficiency. For the samples that demonstrated clear degradation in UV absorbance, we performed High-Performance Liquid Chromatography (HPLC), a highly precise quantitative analysis assay. HPLC was used to accurately determine the concentrations of TPA and MHET released during PET degradation.

Additionally, when degrading different textile blends we first applied the commercial cellulase Trichoderma reesei to degrade cotton, followed by applying TfCut2 variants to degrade the PET. As a result, 3,5-Dinitrosalicylic acid (DNS) assays were performed to quantitatively evaluate cellulase efficiency in cellulose degradation.

To enhance the enzyme's ability to degrade textiles, an alkaline pretreatment method was applied to reduce the textile’s crystallinity. Then, Scanning Electron Microscopy (SEM) was used to visualize the surface morphology change, including fiber damage and structural breakdown, following pretreatment and enzymatic degradation. In addition, Fourier Transform Infrared Spectroscopy (FT-IR) was performed to analyze the relative chemical structure change. Lastly, Differential Scanning Calorimetry (DSC) was used to evaluate the crystallinity of the textile before and after pretreatment.

In the future, we aim to utilize the TPA reporter system as a cost effective measurement of TPA production.

Noted: The equipment used in our project - SEM, FT-IR, DSC and HPLC were provided and operated with the assistance of COMPEQ MANUFACTURING CO., LTD.

Coomassie Blue Staining

Background

To visualize the purification of proteins following SDS-PAGE, we employed Coomassie Brilliant Blue staining. This dye binds to basic amino acid residues through strong intermolecular forces, producing stable blue bands that are easily detectable when against a transparent background. This method is particularly useful for confirming successful protein purification, as the distinct bands correspond to both protein size and abundance, enabling direct evaluation of successful protein purification (Loh & Cao, 2008).

Experimental setup and validation

Protein purification was evaluated by SDS-PAGE followed by Coomassie Blue staining. After electrophoresis, gels were washed with ddH2O for five minutes 3 times and stained in 0.05% Coomassie Blue R250 for one hour with gentle shaking at 50 rpm.

Subsequently, gels were destained in methanol–acetic acid buffer until protein bands were visible against a clear background. TfCut2 samples and its variants were compared with a molecular weight ladder to verify expected sizes, and distinct bands were used to confirm successful purification.

Results and Discussion

Coomassie Blue staining showed major bands between the 25 kDa to 35 kDa ladder, corresponding to the predicted sizes of target protein TfCut2 and its variants (Variants 1 to 6). We used 25 mM imidazole to wash the column and subsequently eluted with 150 mM imidazole, and the sample was loaded side by side to assess protein loss during the washing step.

Coomassie Blue staining provided qualitative insight into our protein purity. The absence of bands outside of the region of 25 kDa to 35 kDa correlated with high purity. Figure 2 confirmed that non-specific proteins were removed before elution with 150 mM imidazole and successful expression for TfCut2 wild type and variants 1-3, with the bands corresponding to the expected molecular weight (Figure 2A). If the purity of protein is low (Figure 2B), employing enzyme kinetic analysis to standardize TfCut2 concentration is necessary.

For complete information on the Coomassie Blue staining, please check out our Engineering and Experiments page.

Western Blot

Background

Western blotting was performed to detect and qualitatively assess the expression of our target proteins from the purified protein mixtures. We used an anti-His antibody to detect the His-tagged TfCut2 wild type (5ZOA) and six engineered variants (Mahmood & Yang, 2012).

Experimental setup and validation

After proteins were separated by SDS-PAGE, they were transferred onto PVDF membranes under an electric current in the cold transfer buffer to immobilize them on a more stable solid phase. The transfer was done by using a transfer sandwich where the gel and membrane were placed in the middle of sponge pads and filter papers to facilitate the transfer.

Membranes were then blocked with 5% skim milk in TBST for 1 hour to block the nonspecific binding of antibodies. After that, the membrane was incubated overnight at 4 °C with primary antibodies (anti-His antibody) specific to TfCut2 proteins. After several washes in TBST, membranes were incubated with Horseradish peroxidase (HRP)-conjugated secondary antibodies for 1 hour at room temperature, followed by several washes.

The proteins were detected through the reaction of HRP with chemiluminescent substrates. Luminescent signals produced were captured using an imaging system, allowing us to visualize the bands of TfCut2 proteins on the membrane.

Results and Discussion

Western blot analysis confirmed expression of the wild type TfCut2 (5ZOA) and all six engineered variants. Figures 2A and 2B showed clear bands around 35 kDa, consistent with the predicted molecular weight of TfCut2 proteins. Distinct band intensity showed differences in protein expression levels, where darker bands indicate stronger protein expression. The results confirmed the expression and molecular weight of the enzymes prior to subsequent experiments.

For complete information on the Western Blot, please check out our Engineering and Experiments page.

pNPB Assay

Background

To evaluate the enzymatic activity of TfCut2 and its engineered variants, we employed a p-nitrophenyl butyrate (pNPB) hydrolysis assay. In this colorimetric method, TfCut2 proteins cleave pNPB into p-nitrophenol (pNP) and butyrate, and the release of pNP can be quantitatively measured at 405 nm due to its strong absorbance in alkaline conditions.

Experimental setup and validation

Initial experiments were conducted in the 200 mM Tris-HCl buffer with 10 mM CaCl2 and 2 mM pNPB. However, later research found that Tris-HCl inhibited TfCut2 activity (Schmidt et al., 2016), prompting us to switch the reaction buffer to a HEPES 100 mM buffer with 10 mM CaCl₂ and 2 mM pNPB instead. Experiments were conducted under temperatures ranging from 35 °C to 70 °C and pH ranging from 6 to 9. Samples were placed in a 96-well plate, with each well containing 90 μL buffer and 10 μL TfCut2 variants at a concentration of 5 ng/μL. The first and last rows (A and H) were designated as blanks, where 10 μL Tris-HCl buffer or PBS buffers (initial experiments use Tris-HCl buffer and later experiment shift to PBS buffer) were added instead of enzymes. An ELISA plate reader was used to measure the absorbance at 405 nm.

Results and Discussion

We organized our raw data from the ELISA reader by subtracting the OD405 value from each experimental group from the blank. The data for each trial is organized into a graph formatted like Figure 2 (results for other trials)

For complete information on the pNPB assay, please check out our results and experiment page.

Enzyme Activity Standardization Using Kinetic Analysis

Background

Enzyme Kinetic Analysis is a quantitative study of how various factors, such as the concentration of the substrate and enzyme, influence the rate of an enzyme-catalyzed reaction. When Coomassie Blue staining results indicate impurity, there will be differences between total protein concentration and actual TfCut2 concentration. Therefore, we utilize enzyme kinetic analysis to standardize enzyme activity based on TfCut2’s effective concentration. This ensures that in each of the following experiments, our data and comparison between experiments are meaningful, accurate, and reproducible.

A sample enzymatic reaction is listed as follows, which S is the substrate, E is enzyme, Ef is the free enzyme, and P is the product: Let V0 be the initial reaction rate.

Since is at equilibrium, the rate determining step is and therefore Since the largest reaction rate is achieved when all enzymes are binding with the substrate. Therefore,

According to the Michaelis-Menten equation: When the concentration of substrate is large,

Since therefore

Therefore, by comparing the initial reaction rates across batches, we can determine the relative differences in active TfCut2 concentration between batches. Using this information, we can accurately dilute the enzyme stocks to a final concentration (27.8 μg/mL) for all subsequent experiments.

Experimental setup and validation

To find out the relative difference of initial reaction rate between batches, we performed pNPB assay (for details on pNPB assay please check out the previous measurement page or the experiment page). We recorded the absorbance at 405 nm, which is directly proportional to product (p-nitrophenol) concentration, at every minute and found the slope of the UV absorbance vs Time graph.

We compared the R-squared value of the two variables for each time interval (for example, R-squared for 0-1 minute, 0-2 minutes, etc…). We choose the latest interval where the R-squared value, which represents the correlation between UV absorbance and time, is greater than 0.99; in other words, a linear relationship between two variables. We then calculate the slope of the graph at that interval. The slope of the two variables is directly proportional to the initial reaction rate. Technically, the slope of each point is directly proportional to the reaction rate at its corresponding moment, but since the slope is constant for the initial phase of the reaction, we can assume the linear slope is directly proportional to the initial reaction rate as well.

By taking the ratio of the slopes (current batch ÷ previous batch), we can calculate the relative enzyme concentration between batches. For example, if Batch 2 shows a slope that is 0.13 times that of Batch 1, then Batch 2 contains approximately 13% of the functional TfCut2 enzyme present in Batch 1.

We then calculate the correlation factor between batches by taking the reciprocal of the relative difference between batches.

By multiplying the correlation factor by the volume used in the previous experiments, we calculate the volume of enzyme solution needed to be added for future experiments to maintain a constant TfCut2 concentration.

Results and Discussion

Enzyme kinetic standardization revealed differences in enzyme activity between batches as the table below has shown. Correction factors used to standardize enzyme concentrations across all experiments were calculated as shown in Table 1.

This approach ensured that all downstream assays (UV absorbance assay, SEM, HPLC) were performed with comparable enzyme concentrations, making our results reproducible and meaningful across different preparations.

UV Absorbance Assay

Background

The OD260 UV absorbance test was used to directly evaluate PET depolymerization by TfCut2 and its engineered variants.

In order to obtain the optimized reaction condition, we conducted high-throughput screening on PET degradation, in which we scaled down the reaction to test the multiple conditions simultaneously. Once we obtained the optimized condition, we scaled up the reaction and performed standard PET film degradation. In addition, after confirming that our enzyme can successfully degrade PET, we test our enzyme on both pure PET textile and cotton-PET blend textile.

In all of these settings OD260 proved to be an important technique to provide a preliminary yet quantitative and informative data regarding PET degradation.

This approach was based on the bulk absorbance assay, which demonstrated that PET hydrolysis products such as TPA and MHET could be reliably detected spectrophotometrically between A240 and OD260 (Zhong-Johnson et al., 2021).

To evaluate the best detection wavelengths, we aim to find the wavelength that shows the characteristic of the TPA and shows minimal background noise.

During method development, we compared absorbance profiles of the empty 96-well UV plate, across the UV range (200–300 nm), which is the absorbance wavelength of TPA degraded product, to test for background noise. Figure 1 shows a strong absorbance peak of around 230–240 nm, indicating that this region is dominated by background signals, which makes it undesired for determining enzymatic PET hydrolysis products. By contrast, at 260 nm the baseline signal is far lower, minimizing interference while still capturing the absorbance of terephthalic acid (TPA) and MHET. This is why we chose to perform all proceeding experiments at 260 nm.

Experimental setup and validation

We first performed high-throughput PET film degradation for testing optimal conditions, in which each trial contained 96 reactions. Each reaction contained uniform pieces (0.8 × 0.25 cm) of PET film, 20 μL of enzyme at concentration of 5 μg/mL, and 180 μL of HEPES buffer supplemented with 10 mM CaCl₂. Two buffer conditions were tested sequentially: 100 mM HEPES, chosen to align with pNPB assay conditions, and 500 mM HEPES, used to replicate established PET film degradation protocols from the literature. Reactions were incubated for 48 hours across temperatures from 35–70 °C and pH values 7.0–8.5. These products were subsequently tested using UV absorbance assay. We loaded 200 μL reaction products or the no-enzyme blanks per well into the 96-well UV plate. The no-enzyme blanks were created by adding the dialysis buffer used in producing that particular batch of enzyme instead of the enzyme. For each test no-enzyme blanks were used as negative controls to account for background signals. Final data was output by subtracting each experimental groups’ absorbance with the negative control.

Degradation products for PET film and textile also utilized UV absorbance assay to test its effectiveness. In each experiment, we added 100 μL reaction products or no-enzyme blanks per well. The reaction product consists of 500 mM HEPES buffer supplemented with 10 mM CaCl₂ and TfCut2 enzyme at a concentration of 27.8 μg/mL.

When performing UV absorbance assay for PET film and textile degradation products, we made a TPA standard curve by preparing TPA solution at defined concentrations of 25, 50, 100, 200 μg/mL in 500 mM HEPES supplemented with 10 mM CaCl₂ and measured its OD260 value. We graphed out the relationship between TPA concentration and OD260 as our standard curve.

We then utilized our standard curve to convert OD260 to its equivalent to TPA concentration in (μg/ml) and multiplied by its reaction volume and to get the total mass of TPA.

Since degrading each PET monomer will yield 1 TPA molecule, we have to calculate a weight conversion factor: Therefore,

Results and Discussion

To analyze our raw data from the ELISA reader, we subtracted the OD260 value from each experimental group from the blank. All high-throughput PET film degradation trials results are organized into 3D graphs similar to figure 3, with temperature on the x-axis, pH on the y-axis, and OD260 on the z-axis.

Our results suggest that variants 3 and 4 consistently exhibited the strongest activity, and variants 1, 2, and 5 showed similar performance with the wild type, while Variant 6 showed minimal activity.

Furthermore, drylab utilized Response Surface Methodology (RSM) to statistically optimize the conditions for degradation (temperature, pH). It utilizes experimental data and a mathematical model to identify the best possible factors for degradation with the results being 51.88 °C at pH 7.57. (For further information, please check out our modeling page)

To perform UV absorbance assay for PET degraded products, we first created the TPA standard curve (Figure 4). The standard curve shows a linear relationship between OD260 and TPA concentration as indicated by the high R² value, allowing us to use it to measure TPA concentration after enzymatic degradation of PET.

By comparing our sample’s data with the standard curve and performing the calculation previously mentioned in the experimental set up, we can yield a graph similar to Figure 5, that provides quantitative insight on our enzyme's ability to degrade PET.

However, this method is not fully accurate, as we did not consider the intermediate products like BHET and MHET. Therefore, HPLC will later be used to provide reliable numerical data on TPA and MHET concentration.

For complete information on the UV absorbance assay, please check out our results page for PET film, pure PET textile, cotton-PET blend textile, and our experiment page.

3,5-Dinitrosalicylic Acid (DNS) Assay

Background

To evaluate cellulase efficiency in degrading cotton from cotton-PET blends, we employed the 3,5-Dinitrosalicylic acid (DNS) assay, a colorimetric method for quantifying reducing sugars. In this assay, reduced sugars released from enzymatic hydrolysis react with DNS under alkaline and high temperature conditions to form a reddish-brown color (Gusakov et al., 2011). The resulting color intensity provides a quantitative measure of reducing sugar concentration, serving as a practical indicator of cotton degradation efficiency.

Experimental Setup and Validation

After allowing cellulase to degrade PET-cotton textile blend of various compositions for 96 hours (for the details check experiment page), we performed the DNS assay on sample. A glucose standard curve was prepared using solutions at concentrations of 0, 0.2, 0.4, 0.6, 0.8, and 1.0 mg/ml. We diluted all experimental samples to 1/10 of the original concentration. We then loaded both the sample and standard into each well of the PCR plate and added 25 μl DNS reagent to all wells. Then, the plate was sealed with adhesive film and heated at 100 °C for 5 minutes in a thermocycler to allow color development. Lastly, the reaction products were then diluted, and absorbance was measured at 540 nm using an ELISA plate reader to determine reducing sugar concentrations.

Results and Discussion

We analyzed our data acquired by the DNS assay to investigate cellulase degradation capacity in various compositions of PET-cotton textile blend. The glucose concentration was calculated using OD540 and compared with the standard curve.

The information was organized in the table below where mass before degradation (mg) represents textile weight before enzymatic treatment. Cotton mass (mg) represents mass of cotton in the textile before treatment, which can be calculated using the following equation: Reaction Volume (mL) represents the final reaction volume, which varies due to evaporation during the experiment. Glucose Mass (mg) represents total glucose released, which is calculated using the following equation: Degradation Rate (%) is calculated using this equation:

Using the DNS assay, we observed degradation rates (Figure 2) of ~61% for 35:45 blend, ~95% for 55:45 blend, and ~82% for 65:35 blend. These results confirm successful cellulase activity of degrading the cotton fraction of cotton-PET textiles, with the highest efficiency measured in the 55:45 blend. Overall, the DNS assay proved to be an effective method for quantifying cotton degradation in mixed textile.

For complete information on the DNS assay, please check out our results page and experiment page.

HPLC

Background

High-Performance Liquid Chromatography (HPLC) is a chromatographic technique to separate, identify, and quantify components in a liquid mixture. It requires a liquid mobile phase passing through a column packed with a solid stationary phase. Different compounds move at different speeds, allowing separation to occur (Schieppati et al., 2021). HPLC offers high resolution and sensitivity, quantitative accuracy, and the ability to be coupled with detectors for automated analysis. The most prominent advantage is its versatility; not only can HPLC analyze small organic molecules and ions, it can also analyze biomolecules and polymers.

In our project, HPLC quantified the amounts of terephthalic acid (TPA) and mono-(2-hydroxyethyl)-terephthalic acid (MHET) produced after degradation using our 6 variants and the wild type.

Experimental Setup and Validation

After our degradation process, we prepared our sample by transferring the supernatant of each sample into a new microtube and inactivating it with heat. After the samples cool down to room temperature, we did 2-fold dilution using DMSO then performed sonication followed by another 10-fold dilution with MeOH and filtration.

We used the Hewlett Packard HP1100 system to analyze our samples through HPLC. The separation was carried out using the Shim-Pack VP-ODS column (φ4.6 mm × 250 mm) maintained at 40 °C, with a mobile phase containing 10 mM sodium p-toluenesulfonate aqueous solution at pH 4 and methanol at a 3:1 ratio. The flow rate is controlled at 1 mL/min, with an injection volume of 5 µL. Lastly, the detection wavelength was performed at 254 nm. Our commercial TPA and MHET standards were obtained from BOC Sciences and LGC Dr Ehrenstorfer, respectively. TPA and MHET standard solutions were prepared in the concentration 2.5, 25, 50, 100, 200 and 5, 25, 50, 100, 200 µg/mL separately (Figure 2).

Results and Discussion

To analyze HPLC data, we first created the standard curve by graphing the relationship between concentration and the area below the curve (Figure 2). Each of the raw data is shown as an absorbance–time chromatogram where each of our samples is characterized as its unique curve (Figure 3). The area under the curve represents the total amount of TPA or MHET that flows out of the column. We then utilized the standard curve to convert the area under the curve into TPA and MHET concentration (Figure 4).

The calculated concentrations confirm that Variant 3 and Variant 4 are the most active enzyme variants that produce the highest concentration of TPA (12.1 μg/mL and 18.47 μg/mL, respectively) and MHET (30.36 μg/mL and 49.81 μg/mL, respectively). Variants 1 and 2 show moderate activity, only producing 4 μg/mL , 4.6 μg/mL of TPA and 9.38 μg/mL , 11.45 μg/mL of MHET. While wild type (PDB: 5ZOA) and Variant 5 produce only small amounts of products, only 2.3 μg/mL, 2.5 μg/mL in TPA and 4.97 μg/mL, 4.83 μg/mL in MHET were detected. The control (only reaction buffer without enzymes) showed no activity, validating the methodology and confirming that the TPA and MHET produced are due to the variants. Variant 6 showed no detectable activity in both data collections, indicating no product formation. Overall, the results once again suggest that variants 3 and 4 are the strongest candidates for efficient PET degradation.

For complete information on HPLC, please check out our results page for PET film, pure PET textile, cotton-PET blend textile, and our experiment page.

SEM

Background

Scanning Electron Microscopy (SEM) was employed to obtain high-resolution, three-dimensional images of textile fiber morphology. When a beam of high energy electrons interacts with the atoms in the sample, they generate signals such as backscattered electrons, secondary electrons and X-rays. These signals are collected by detectors and generated high resolution grayscale images that provide information about the surface’s topography and compositional details.

We utilized SEM to capture detailed images of textile fiber and PET film before and after pretreatment and enzymatic degradation. SEM serves as a crucial component in providing a comprehensive range of evidence for pretreatment and enzymatic degradation, as well as visual evidence to verify the quantitative results derived from DSC, FT-IR, and HPLC.

Experimental Setup and Validation

Our aim is to efficiently degrade PET in blended textile waste by using our TfCut2 variants. However, high crystallinity fibers hinders enzyme degradation efficiency (Qiu et al., 2024). Therefore, the primary goal for our pretreatment is to lower the crystallinity of the textile.

According to previous studies, alkaline and thermal pretreatment were used to decrease the crystallinity of cellulose fiber and polyester (Ciuffi, Fratini, & Rosi, 2024). Following their protocol, we performed pretreatment by using 15% NaOH followed by autoclaving at 127 ℃ for 15 minutes. Following the pretreatment, the textile samples were rinsed with deionized water and dried at 55 ℃ overnight. SEM was then subsequently used to analyze whether pretreatment reduced the crystallinity of 100% PET textiles and 65/35 cotton-PET blends.

In addition, SEM was also used for evaluating enzymatic degradation by comparing film surfaces with and without enzymatic degradation for both PET film, pure PET textile, and cotton-PET textile blend. (See results page for details)

SEM analysis was performed using the HITACHI SU5000. The procedure started with mounting our pretreated textiles samples securely onto the SEM stub using carbon tape. To ensure the conductivity and proper deflection of secondary electrons, the samples were coated with gold for 15 seconds. The samples were then placed into the SEM chamber under vacuum pressure of 30 Pa with 5.0 kV accelerating voltage. During imaging, the positions and magnifications were manually adjusted to obtain the best focus. Images were taken at a total of five magnifications, 500x, 2000x, 5000x, 10000x, 50000x, allowing us to obtain high resolution visualization of fiber morphology and structural changes.

Results and Discussion

SEM data consisted of images of PET film and textile at 500x and 10,000x magnification. Images of each experimental group are compared with the control group where no treatment was applied. In measuring the effects of pretreatment, we compared the pretreated 100% PET textile and the control group. As shown in Figure 1A and 1 B, under both 500x and 10,000x magnification, smooth surfaces were shown. In comparison, the pretreated fiber showed a noticeably rough surface at 500x (Figure 1C), with microcracks clearly observed at 10,000x magnification (Figure 1D). These observations indicate that 15% NaOH with autoclaving for 15 minutes pretreatment effectively disrupted the PET fiber structure. Similar analyses were performed for analyzing PET film degradation. SEM proved to be an important method to gather qualitative and visual evidence on the effect of our treatment. However, to gain quantitative data on our degradation process, we must also employ quantitative analysis, including FT-IR, DSC, and HPLC.

For complete information on SEM, please check out our results page for PET film, pure PET textile, cotton-PET blend textile.

FT-IR

Background

Fourier transform infrared spectroscopy (FT-IR) is a molecular vibrational spectroscopy technique that analyzes chemical functional groups by measuring absorbance of infrared radiation in the range of 4000 to 400 cm⁻¹, which is the absorption radiation of most organic compounds and inorganic ions (Verma, 2022).

FT-IR has been used in numerous other PET degradation experiments to track chemical bond breakdown. For example, Rostampour et al. (2024) used this technique to monitor UV-induced PET degradation by observing the decrease in the ester carbonyl peak at 1713 cm⁻¹ and the rise of the carboxylic acid peak at 1685 cm⁻¹ under varying humidity and temperature. Another study done by Ioakeimidis et al. (2016) applied the same technique to identify oxidation and hydrolysis trends to marine-weathered PET by identifying chemical deterioration of the polymer.

Similar to previous studies, we applied FT-IR to observe the composition change after 15% NaOH pretreatment (See our pretreatment page for further details). We examined whether pretreatment disrupted the ester bonds in both pure PET textiles and blended textiles. The O=C–O ester bond in PET exhibits a strong absorption at 1712 cm⁻¹ (Figure 1). When PET is degraded, cleavage of this bond alters the absorbance intensity. By observing these changes, we can evaluate the extent of ester bond cleavage and thus the degradation of PET.

In our analysis, we compared intensity and area change of this peak in untreated and pretreated samples to confirm the PET content and quantified the extent of degradation.

In addition, we also used FT-IR to check the effect of pretreatment on blended textile. By comparing the absorbance spectrum of treated textiles with the untreated group, we can observe the effectiveness of the treatment on each blend textile of various compositions.

Experimental Setup and Validation

All spectra were recorded using a Fourier Transform Infrared (FT-IR) spectrometer using ATR-FTIR (Attenuated Total Reflectance Fourier Transform Infrared) mode. Samples were placed in the path of emitted IR beams. FT-IR spectra were collected from control groups and experimental groups. Spectra were collected across a wavelength range of 4000 to 500 cm⁻¹., covering the mid-IR region. Key absorption peaks identified are the O=C–O ester bond in PET at 1712 cm⁻¹ and the benzene ring C-H at 724 cm⁻¹ and glycosidic bond at 1159 cm⁻¹, 1117 cm⁻¹, 1054 cm⁻¹, 1028 cm⁻¹, and 995 cm⁻¹. Data are compared between the untreated control from the database and experimental groups.

Results and Discussion

Figure 1 shows the control spectrum of pure PET, pure cotton, and comparison between pretreated and untreated samples. By comparing the controlled FT-IR spectrogram with each of our samples, we can calculate the relative change of chemical composition of the sample using the formula

For example, Figure 2 corresponds to approximately 13% degradation rate of PET ester bonds, confirming that the pretreatment partially hydrolyzes PET linkage. Therefore, FT-IR experiment provides important insights on the effectiveness of our pretreatment.

For complete information on FT-IR, please check out our results page.

DSC

Background

We utilized heat-flux Differential scanning calorimetry (DSC) to measure the crystallinity changes in pretreated textile samples compared to untreated controls. The samples were subjected to a precisely controlled heat program. The heat flow of samples undergoing melting and crystallization was recorded, providing data on the temperature that transition occurs and energy involved in each of those transititions. By quantifying the crystallinity of the pretreated PET textile, we were able to assess the effectiveness of pretreatment and enhance enzymatic degradation efficiently.

Experimental Setup and Validation

100% PET textiles and fibers were pretreated with alkaline-thermal under different conditions: 15% NaOH with autoclaving at 127 °C for 15 and 30 minutes or 15% NaOH at 80 °C for 4, 8, and 20 hours. Each sample was then sent for DSC analysis.

DSC analysis measures the onset temperature (Tₒ), which marks the point where the curve first departs from the baseline. It indicates the start of a measurable thermal event like melting or crystallization.

The endothermic peak drops below the base line and indicates melting, which is when the crystallites begin to break down. The area under the endothermic peak gives the enthalpy of fusion ΔHm On the other hand, an exothermic peak indicates crystallization, and the area under it indicates the enthalpy of crystallization ΔHc. These two variable can be compared to the enthalpy of fusion theoretical value for 100% crystalline PET ΔHf which is equal to 140 J/g, to calculate the sample’s crystallinity using the formula: However, an exothermic peak has not been observed during the heating process. Therefore, we employed the formula:

Results and Discussion

By incorporating the crystallinity formulas mentioned above, DSC analysis showed the disruption of crystalline region in PET fiber after pretreatment with 15% NaOH at 80 °C for 4 hr and 8 hr as indicated by the absence of ΔHc and two distinct ΔHm peaks in DSC (Figure 1). The values ΔHc and ΔHm were provided by the DSC software, which we used in the crystallinity formula. Therefore, we added up the two areas of the curve and compared them with ΔHf. The degree of crystallinity was calculated to be 11.7% for 4 hr incubation (Figure 1A) and 5.6% for 8 hr incubation (Figure 1B), compared to a crystallinity of 36.5% in control samples. This suggests that our pretreatment successfully breaks down crystalline formations within PET fibers, allowing improved enzymatic degradation efficiency.

DSC provided data in supporting how textile crystallinity was lowered, allowing us to validate our pretreatment effectiveness and optimize experiment conditions.

For complete information on DSC, please check out our results page.

Future Work

TPA Reporter System

We initially planned to incorporate a TPA reporter system to serve as a cost effective and accessible method to assess PET degradation. This system would utilize a synthetic biology approach that integrates a promoter, three transporter proteins, and a regulator protein to detect TPA. In this design, the presence of TPA would induce the expression of colorimetric genes. (For details check our engineering page).

This approach not only addresses the high expense for performing HPLC, but also allows us to directly measure TPA without being distorted by MHET and BHET like in UV absorbance.

However, due to time constraints and multiple setbacks during the cloning process (See engineering page for details), we could not complete this complex system. Future work will focus on completing and optimizing this TPA reporter system to be used as an effective quantification tool.