Conference Agenda

Understanding pesticide flow dynamics in the vadose and saturated zones in the soil profile is crucial for protecting the environment. Although predictive computational tools have effectively modeled pesticide flow within the soil, the flow through a biobed has not been reported. Hence Hydrus, a predictive modeling tool widely used in the simulation of water, heat, and solute in a variably saturated media, will be used to simulate pesticide flow in a Biobed. The Biobed, a system that consists of biomix (2:1:1v/v mixture of straw, soil, and peat) is an effective proven technology for the treatment of pesticide residues in rinsate water. This study evaluated the effectiveness of Hydrus 1D model in simulating the flow of pesticide rinsate through biobed located at the Ian Morrison Research Farm, Carman, Manitoba. A 1D domain depth profile was set up with five observation nodes located at 10 cm, 20 cm, 30 cm, 40 cm, and 50 cm depths. The measured volumetric water content of the biobed at these depths were compared to the simulated volumetric water content. The initial hydraulic parameters θs, α, n, l, Ks, and θr were estimated by fitting the van Genuchten equation from the biomix-water characteristics curve, textural values, and bulk density. The biomix hydraulic parameters were optimized using inverse modelling methods. The measured and predicted volumetric water contents were compared and assessed using statistical analysis. The result showed high efficiency in the model performance, this showed the Hydrus 1D model of the biobed represented the field conditions well.

Bioplastics represent promising alternatives to petroleum-based plastics, yet their degradation mechanisms remain insufficiently understood. Identifying bacteria and enzymes capable of degrading bioplastics could enhance end-of-life management practices. Proteobacteria, known for their remarkable metabolic versatility, present a promising avenue for exploration. Many proteobacteria produce diverse enzymes capable of breaking down various substrates for carbon utilization. This enzymatic diversity suggests a potential capability to degrade polymers such as bioplastics, even when they are not their natural substrates. We hypothesize that Burkholderia and Stenotrophomonas species will adapt to available nutrients, activating various metabolic processes, including the degradation of medium-chain-length polyhydroxyalkanoate (mcl-PHA). Through a screening method targeting extracellular mcl-PHA depolymerases, we identified several strains, including B. gladioli, B. multivorans, B. vietnamiensis, and S. maltophilia, capable of degrading extracellular mcl-PHA. Furthermore, these strains demonstrated the ability to degrade triglycerides under similar screening conditions, suggesting either substrate promiscuity or the production of multiple degradation enzymes. To elucidate the genetic basis of this activity, we performed transposon mutagenesis on B. vietnamiensis and identified several putative genes associated with extracellular mcl-PHA degradation. These genes include triacylglycerol lipase, lipase chaperone, type II secretion system components, HTH-type transcriptional activator, and polyhydroxyalkanoate synthesis repressor. To validate these genetic elements, we will generate insertional mutants using a CRISPR-associated transposase system (CAST). CAST system, employing Tn7-like transposase subunits and a V-K CRISPR effector (Cas12k), facilitates targeted DNA integration. We have successfully adapted this system for several Burkholderia species and intend to leverage its capabilities to elucidate the genetic determinants of PHA degradation further.

Massive plastic utilization has increased plastic pollution dramatically around the world. Biodegradable polymers are now displacing recalcitrant synthetic polymers to mitigate plastic pollution. However, those biodegradable plastics are not easily degraded or composted at ambient temperatures. For example, Polylactic acids (PLA) and other biodegradable and compostable bioplastics have different chemical and physical characteristics than other organic compounds (usually food wastes) in compost systems. Specifically, biodegradation of PLA requires a temperature of 58-60 ℃. As a result, they are mostly disposed of in landfills, where they do not fully degrade, resulting in production of microplastics which contaminate soil, water, and air, and create risks to human and animal health. Our study focuses on isolating PLA-degrading microorganisms from compost (industrial and backyard), optimizing the culture conditions, and exploiting them to degrade PLA completely under environmental conditions. This study will help reduce plastic pollution by enabling 100% biodegradation of PLA.

Polyethylene terephthalate (PET), a widely used synthetic polymer, is found in various products, from beverage bottles to textile fibers. Concerns about its long-term impact on humans have prompted research into mitigating its accumulation. After discovery of the efficient enzyme “PETase” from Ideonella sakaiensis in 2016, tremendous research was focused on application of the wild-type or engineered forms. Previously, we developed a hybrid construct fusing the signal peptide of a membrane-anchored Escherichia coli lipoprotein to express and deliver PETase to the outer membrane, aiming to streamline the soluble production and purification processes. However, traditional plasmid-based techniques utilized in this approach are susceptible to genetic instability and depends on the addition of inducers and antibiotics, which pose challenges for industrial scalability and application. To address these problems, we employed a “CRISPR-assisted transposition” approach to integrate a DNA payload containing the LPP-PETase gene cassette, under control of constitutive promoter, to develop a cell surface-displayed PETase capable of serving as a whole-cell biocatalyst. Stable expression and proper localization of the membrane anchored PETase were confirmed and evaluated via enzyme kinetic analysis and Western Blotting. Enzyme kinetic parameters were calculated utilizing a chromogenic substrate, and high-performance liquid chromatography quantification of Bis(2-Hydroxyethyl) terephthalate (BHET, PET derivative) hydrolysis. Our findings illustrate that the engineered whole-cell biocatalyst can present continuous functional PETase activity under controlled culture conditions. Genetically engineered "plastic-consuming" bacteria in fermenters, with plastic-degrading enzymes on their cell surfaces, offer a viable waste plastic disposal strategy. This closed, biosafe system converts plastic into valuable biomass sustainably.

LDPE is highly recalcitrant to natural biodegradation processes, and is among the most abundant plastic wastes in the environment. The high degree of crystallinity is thought to play a significant role in the resistance of LDPE to biodegradation. We previously identified three species of bacteria, Cupriavidus necator H16, Pseudomonas putida LS46, and Pseudomonas chlororaphis PA2361, with the ability to utilize untreated LDPE as a sole carbon source. Here we report changes in the molecular structure of LDPE after incubation with these bacteria. The changes in polymer structure were analyzed using Time-domain Nuclear Magnetic Resonance, High-Temperature Size-Exclusion Chromatography, Differential Scanning Calorimetry, X-Ray Diffraction, and Gas Chromatography. Overall, limited degradation of the LDPE powder was seen to occur in first 30 days of incubation with the bacteria. Residual LDPE from bacterial cultures showed a significant decrease in the percentage of amorphous regions (from > 47% to 40%), while the percentage of crystalline regions remained constant. The weight-average molecular numbers (Mw) and number-average molecular numbers (Mn) increased, while the polydispersity ratios decreased, indicating that branches of the LDPE with lower molecular weight were preferentially degraded. The limited degradation of LDPE was confirmed to occur in the low molecular weight branches, while the main branch remained untouched. LDPE hydrolysis products were detected in the supernatant with the majority being linear alkanes (heptane and undecane). The study is the first to report the connection between the structure of LDPE, and the degradability of the polymer, and explains the resistance of LDPE to complete biodegradation.

This study utilized vermicompost for the remediation of contaminated soils in Nigeria. Two soil washing methods adopted were batch and column processes. Characterization of the Vermicompost and crude oil contaminated soil were performed before and after the soil washing using Fourier transform infrared (FTIR), scanning electron microscopy (SEM), X-ray fluorescence (XRF), X-ray diffraction (XRD) and Atomic adsorption spectrometry (AAS). The optimization of the washing parameters, using response surface methodology (RSM) based on Box-Behnken Design was performed on the response from the laboratory experimental data. Artificial Neural Network (ANN) and Adaptive neuro fuzzy inference system (ANFIS) were used in modelling the removal efficiency of the process. The result showed removal efficiency of 97.8% for batch process remediation and 72.44% for column process. Optimization of the experimental factors gave optimal removal efficiency of 98.9% at absorbent dosage of 34.53 grams, adsorbate concentration of 69.11 (g/ml), contact time of 25.96 (min), and pH value of 7.71, respectively. Removal efficiency obtained from the multilevel general factorial design experiment ranged from 56% to 92% for column process remediation. The coefficient of determination (R^2) for ANN was (0.9974) and (0.9852) for batch and column process, respectively. The RSM coefficient of determination (R^2) for batch and column processes was (0.9712) and (0.9614), which also demonstrates agreement between observed and predicted. The coefficient of determination for the ANFIS model were (0.7115) and (0.9978) for the batch and column processes respectively. Machine learning models (ANN and ANFIS) accurately predict removal of crude oil from contaminated soil using vermicompost