(4pg) Understanding methanotroph-photoautotroph synergism using an adaptable in-house bioreactor system

Biological systems that sequester greenhouse gases, like methanotrophs and algae, are showing increasing promise to aid in ameliorating climate change. Elucidating the most promising biological systems for large-scale integration for different applications requires adequate screening of different microorganisms. Screening requires ample time and scrutiny to assess the performance of biological systems both accurately and unbiasedly. Typically, screening is performed in batch with volumes less than 50mL that do not mimic large-scale operations. These trials allow the biological systems to reach the stationary phase without replenishing feed or adjusting pH, and these limited results influence the direction of posterior research. For gas-dependent biological species, batch screening is complicated by the exhaustion of headspace gas and the poor solubility of gases in aqueous media. Discerning the true cause of inhibition usually involves invasive sampling, reducing the working volume with each disturbance.

To address these issues, a fed-batch screening system (Species Screening Station (S3)) was developed to greatly expedite the screening processes [1]. Shown in Figure 1, the S3 consists of nine parallel reactors (three sets of triplicates) with working volumes of roughly 250mL that regulate six abiotic factors: temperature, agitation rate, pH, light intensity, gas feed composition, and aeration rate. The continuous feed gas relieves gas-dependent microorganisms of carbon limitations, so each species’ growth will be hindered by deficiencies in the liquid medium. In this work, different methanotrophs, algae, and cocultures of each have been screened not only to highlight the capabilities of the S3, but also to highlight promising biological systems for greenhouse gas remediation.

Before any testing, the S3 was validated by culturing Chlorella sorokiniana, a heavily-studied microalga, on the same liquid medium across all nine vessels set at the same six abiotic conditions. The tight standard deviations at each time point (<5%) and estimated maximum growth rate (0.178 ± 0.005 1/hr) validated that the vessel location does not significantly impact growth performance. With this lack of bias, three sets of triplicate biological trials can occur simultaneously, greatly reducing the amount of time required for lab-scale screening.

The first set of experiments investigated a synergistic methanotroph-photoautotrophcoculture (MPC) – Methylotuvimicrobium buryatense 5GB1 (5GB1) and Arthrospira platensis(Spirulina) – grown on defined media and synthetic biogas. Previously, this MPC exhibited accelerated growth rates and higher methane and carbon dioxide uptake rates than their respective monocultures [2]. To further validate these results, the monocultures and coculture were cultured on the S3 at the same abiotic conditions on synthetic biogas. For the 5GB1 monoculture, oxygen was also supplemented as 5GB1 is an aerobic organism. On the other hand, oxygen was not supplemented to the MPC since Spirulina provides oxygen for 5GB1. After 150 hours of screening, the biomass of the MPC exceeded that of both monocultures. Synonymous with these results, the MPC exhibited higher total nitrogen and phosphorous recovery rates (4.92 mg/L/hr and 1.60 mg/L/hr, respectively) than the monocultures (the greatest of each being 3.76 mg/L/hr from Spirulina and 1.14 mg/L/hr from 5GB1, respectively).

Beyond fundamental research, a variety of methanotroph and microalga species were screened for MPC evaluation on diluted wastewater. Both microalgae and methanotrophs have been studied separately for effective wastewater remediation [3,4]. The MPC can simultaneously remove methane and carbon dioxide from biogas emissions while valorizing eutrophication nutrients from the liquid effluent into valuable biomass [5]. The S3 was used to determine whichmethanotrophs and microalgae could best serve for dual biogas and wastewater remediation asMPC’s. Five microalgae and seven methanotrophs were screened on diluted anaerobic digestate (AD) at abiotic conditions like those at a wastewater treatment plant. Each monoculture was allowed to grow until it reached the stationary phase. The growth performance was evaluated by analyzing growth data with a hybrid Gompertz and exponential growth model. The top monocultures determined from this analysis were screened in full as MPC’s on diluted AD and synthetic biogas. The most promising MPC was Methylosarcina fibrata and Chlorella sorokiniana, which produced more than double the biomass of its monocultures, unlike the other MPC’s. In addition, the hybrid model of all monocultures and all other MPC’s had exceptional goodness-of-fit scores. The M. fibrata – C. sorokiniana coculture, however, lacked a good fit, suggesting that this MPC possessed traits that were atypical of traditional growth curves. What causes this perturbation requires further investigation, but the high biomass titer and atypical growth behavior suggest that this MPC exhibits symbiosis, making it a promising biological system for wastewater remediation.

Lastly, the S3 was slightly modified to screen a mutant of 5GB1 for its potential to remediate atmospheric concentrations of methane. M. buryatense 5GB1C (5GB1C) is a mutant of 5GB1 that lacks a plasmid to make the strain easier to genetically manipulate. Recently, this strain has demonstrated its potential for growth on methane concentrations in air as low as200ppm at working volumes of 10mL [6]. These results indicate that 5GB1C could be useful for remediating methane emissions from different agricultural sectors, such as rice fields or livestock farms [6]. The S3 was modified to determine if 5GB1C could grow on 500ppm methane at larger working volumes at different aeration rates. In one test, the S3 revealed that 5GB1C could growon 500ppm methane at aeration rates of 0.4, 0.8, and 1.6 vvm with a working volume of 260mL.In addition, exponential growth models indicated that aeration rate scaled linearly with the growth rate. This result is due to 5GB1C’s limited access to methane given the poor solubility of methane.

Teaching Statement

I wish to become a teaching faculty member for a chemical or biochemical engineering program. My teaching philosophy dually hinges upon the importance of understanding key chemical engineering concepts as well as developing the mental fortitude to tackle difficult challenges. Having researched in experimental and computational biochemical engineering, electrochemistry, and catalysis, I have a broad research background that allows me to communicate across many disciplines in the field. This broad knowledge has inspired me to initiate programs for undergraduate and graduate students to practice presenting posters and seminars. It further pushes me to extend beyond chemical engineering to develop cross-disciplined opportunities in the fields of renewable energy, decarbonization, and energy storage.

My teaching experience has granted me exposure to a wide range of students, and I have thoroughly enjoyed each teaching venture. Since I was a high-schooler, I have found that my intellect and extraverted nature have coupled well for teaching others in both STEM and non-STEM fields. While pursuing my undergraduate degree at the University of Notre Dame, I was a teaching assistant for an introductory philosophy class for five semesters. I would prepare lectures, create and grade weekly assignments, and lead discussions with my students on topics such as religion, politics, and mental health. This experience served as a foundation for my senior year when I was a tutor for Numerical and Statistical Analysis. I volunteered to be one of the course’s first tutors and convinced the professor to make this position for me. As a tutor, I held office hours, workshopped examples for in-class exercises, and facilitated lab practicums in Python.

As a graduate student at Auburn University, I served as a GTA for Computer-Aided Chemical Engineering, a junior-level course designed to combine chemical engineering core concepts with MATLAB coding. My successes as a GTA earned me the Outstanding GTA Award for the department in Fall of 2020. In addition to fulfilling my expected responsibilities and navigating Zoom classrooms, I made video lectures that highlighted core concepts and basic MATLAB coding, garnering a high attendance for office hours and interest in the coursework. In addition, I have guest lectured at both the graduate and undergraduate level for transport phenomena.

References

[1] Murphy, L, Badr, K, He, QP & Wang, J. (2022, Nov 15). Fed-Batch Screening of Methanotroph-Algae Cocultures on Anaerobic Digester Effluent for Larger-Scale Wastewater Treatment and Valorization. AIChE 2022 Annual Conference, Phoenix, AZ, USA.

[2] Badr, K, He, QP & Wang, J. (2022). Identifying interspecies interactions within a model methanotroph-photoautotroph coculture using semi-structured and structured modeling. IFAC-PapersOnLine, 55(7), 106-111. https://doi.org/10.1016/j.ifacol.2022.07.429.

[3] Mahari, WAW, Razali WAW, Manan, H, Hersi, MA, Ishak, SD, Cheah, W, Chan, DJC, Sonne, C, Show, PL & Lam SS. (2022). Recent advances on microalgae cultivation for simultaneous biomass production and removal of wastewater pollutants to achieve circular economy. Bioresource Technol, 364, 128085. https://doi.org/10.1016/j.biortech.2022.128085.

[4] AlSayed, A, Fergala, A & Eldyasti A. (2018). Sustainable biogas mitigation and value-added resources recovery using methanotrophs integrated into wastewater treatment plants. Rev Environ Sci Biotechnol, 17, 351-393. https://doi.org/10.1007/s11157-018-9464-3.

[5] Roberts, N, Hilliard, M, He, QP & Wang, J. (2020). A Microalgae-Methanotroph Coculture is a Promising Platform for Fuels and Chemical Production from Wastewater. Front Energy Res, 8, 563352. https://doi.org/10.3389/fenrg.2020.563352.

[6] He, L, Groom, JD, Wilson, EH, Fernandez, J, Konopka, MC, Beck, DAC, and Lidstrom, ME. (2023). A methanotrophic bacterium to enable methane removal from climate mitigation. PNAS, 120(35), e2310046120. https://doi.org/10.1073/pnas.2310046120.