Publications
Dr. Chundawat’s complete list of publications is available here and at . Current h-index is 41, i10-index is 73, and total citations are 8917 (updated 2024/12). Corresponding author/s highlighted by an asterisk (*). Peer-reviewed papers are available on the publisher’s website, RUcore, and some older papers are also posted on Dr. Chundawat’s personal ResearchGate account. Original preprints are available on the bioRxiv and chemRxiv websites. Patents are available on Google Patents website.
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Authors: Ashley Dan, Bochi Liu, Urjit Patil, Bhavani Nandhini Mummidi Manuraj, Ronit Gandhi, Justin Buchel, Shishir PS Chundawat, Weihong Guo, Rohit Ramachandran
Paper Link: Link
Abstract: This study is concerned with the development of reduced order machine learning (ML) and non-ML model representations of experimental and simulated bioprocesses and their implementation in model predictive control (MPC) strategies to quantify performance accuracy and computational efficiency compared with the original models. Results showed that ML models such as Long Short-Term Memory (LSTM) networks and Artificial Neural Networks (ANNs) outperformed other reduced order models such as Kriging, Multiple Linear Regression (MLR) and Random Forest (RF) in terms of performance metrics such as R2 and RMSE for both experimental and simulated data. Experimental data were obtained from a fed-batch and perfusion-based bioprocess and an LSTM model was developed and implemented in an MPC open-loop optimal control strategy to determine optimal input trajectories to maximize key performance metrics such as product titer. For the 2 by 3 ODE simulation, results showed that an autoregressive ANN was the most accurate in terms of replicating the plant model dynamics under MPC conditions followed by the LSTM and transfer function (TF) representations, with the feedforward ANN not being able to fully capture the salient dynamics. For the 4 by 5 ODE simulation, the TF representation outperformed the feedforward ANN model which in turn was more accurate than the LSTM model. In terms of computational time, the plant model simulation time for an MPC solution is intractable for larger input-output sizes compared with the ML models. Overall, it can be seen the ML models such as ANNs and LSTMs, provide the best balance between accuracy and computational efficiency as they can capture the inherent nonlinearities of the plant model but also are not computationally intensive compared to the full plant model which are often represented by ODE and/or PDE-based differential equations. ML models such as those developed in this study demonstrate practical methods of implementing advanced process control in highly nonlinear chemical/biological processes as part of the smart manufacturing/Industry 4.0 paradigm.
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Authors: Madeline M Johnson, Antonio DeChellis, Bhargava Nemmaru, Shishir PS Chundawat, Matthew J Lang
Paper Link: Link
Abstract: Cellulose, an abundant biopolymer, has great potential to be utilized as a renewable fuel feedstock through its enzymatic degradation into soluble sugars followed by sugar fermentation into liquid biofuels. However, crystalline cellulose is highly resistant to hydrolysis, thus industrial-scale production of cellulosic biofuels has been cost-prohibitive to date. Mechanistic studies of enzymes that break down cellulose, called cellulases, are necessary to improve and adapt such biocatalysts for implementation in biofuel production processes. Thermobifida fusca Cel6B (TfCel6B) is a promising candidate for industrial use due to its thermostability and insensitivity to pH changes. However, mechanistic studies probing TfCel6B hydrolytic activity have been limited to ensemble-scale measurements. We utilized optical tweezers to perform single-molecule, nanometer-scale measurements of enzyme displacement during cellulose hydrolysis by TfCel6B. Records featured forward motility on the order of 0.17 nm s−1 interrupted by backward motions and long pauses. Processive run lengths were on the order of 5 nm in both forward and backward directions. Motility records also showed rapid bidirectional displacements greater than 5 nm. Single-enzyme velocity and bulk ensemble activity were assayed on multiple crystalline cellulose allomorphs revealing that the degree of crystallinity and hydrogen bonding have disparate effects on the single-molecule level compared to the bulk scale. Additionally, we isolated and monitored the catalytic domain of TfCel6B and observed a reduction in velocity compared to the full-length enzyme that includes the carbohydrate-binding module. Applied force has little impact on enzyme velocity yet it readily facilitates dissociation from cellulose. Preliminary measurements at elevated temperatures indicated enzyme velocity strongly increases with temperature. The unexpected motility patterns of TfCel6B are likely due to previously unknown mechanisms of processive cellulase motility implicating irregularities in cellulose substrate ultrastructure. While TfCel6B is processive, it has low motility at room temperature. Factors that most dramatically impact enzyme velocity are temperature and the presence of its native carbohydrate-binding module and linker. In contrast, substrate ultrastructure and applied force did not greatly impact velocity. These findings motivate further study of TfCel6B for its engineering and potential implementation in industrial processes.
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Authors: Hyun Huh, Dharanidaran Jayachandran, Junhong Sun, Mohammad Irfan, Eric Lam, Shishir PS Chundawat, Sang-Hyuk Lee
Paper Link: Link
Abstract: Plant cell walls are composed of polysaccharides among which cellulose is the most abundant component. Cellulose is processively synthesized as bundles of linear β-1,4-glucan homopolymer chains via the coordinated action of multiple enzymes in cellulose synthase complexes (CSCs) embedded within the plasma cell membrane. Plant cell walls are composed of multiple layers of cellulose fibrils that form highly intertwined extracellular matrix networks. However, it is not yet clear as to how cellulose fibrils synthesized by multiple CSCs are assembled into the intricate cellulose network deposited on plant cell surfaces. Herein, we have established an in vivo time-resolved imaging platform for visualizing cellulose during its biosynthesis and assembly into a complex fibrillar network on the surface of Arabidopsis thaliana mesophyll protoplasts as the primary cell wall regenerates. We performed total internal reflection fluorescence microscopy (TIRFM) with fluorophore-conjugated tandem carbohydrate binding modules (tdCBMs) that were engineered to specifically bind to nascent cellulose fibrils. Together with a well-controlled environment, it was possible to monitor in vivocellulose fibril synthesis dynamics in a time-resolved manner for nearly one day of continuous cell wall regeneration on protoplast cell surfaces. Our observations provide the basis for a novel model of cellulose fibril network development in protoplasts driven by complex interplay of multi-scale dynamics that include: rapid diffusion and coalescence of short nascently synthesized cellulose fibrils; processive elongation of single fibrils; and cellulose fibrillar network rearrangement during cell wall maturation. This platform is valuable for exploring mechanistic aspects of cell wall synthesis while visualizing cellulose microfibrils assembly.
Significance Statement Cellulose is a major extracellular matrix component of cells that is critical for plant development and has applications to bioenergy, agricultural food/feed, textile, and wood production. Cellulose is thought to be assembled by the closely coordinated motion of plasma membrane-embedded cellulose synthase enzyme complexes. To date, however, it has not been possible to visualize de novo plant cell wall synthesis at the single cell level with the necessary spatiotemporal resolution to derive a data-driven model of how plant cells can resynthesize and assemble cell wall after its removal. Based on our time-resolved data, we propose a new model for cellulose biosynthesis after successfully performing live protoplast time-lapse imaging to visualize for the first time the complex dynamics of de novo cellulose biosynthesis and assembly into an intertwined microfibril network.
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Authors: Bhargava Nemmaru, Jenna Douglass, John M Yarbrough, Antonio DeChellis, Srivatsan Shankar, Alina Thokkadam, Allan Wang, Shishir PS Chundawat
Paper Link: Link
Abstract: Non-productive binding of cellulolytic enzymes to various plant cell wall components, such as lignin and cellulose, necessitates high enzyme loadings to achieve efficient conversion of pretreated lignocellulosic biomass to fermentable sugars. Protein supercharging was previously employed as one of the strategies to reduce non-productive binding to biomass. However, various questions remain unanswered regarding the hydrolysis kinetics of supercharged enzymes towards pretreated biomass substrates and the role played by enzyme interactions with individual cell wall polymers such as cellulose and xylan. In this study, CBM2a (from Thermobifida fusca) fused with endocellulase Cel5A (from T. fusca) was used as the model wild-type enzyme and CBM2a was supercharged using Rosetta, to obtain eight variants with net charges spanning −14 to +6. These enzymes were recombinantly expressed in E. coli, purified from cell lysates, and their hydrolytic activities were tested against pretreated biomass substrates (AFEX and EA treated corn stover). Although the wild-type enzyme showed greater activity compared to both negatively and positively supercharged enzymes towards pretreated biomass, thermal denaturation assays identified two negatively supercharged constructs that perform better than the wild-type enzyme (∼3 to 4-fold difference in activity) upon thermal deactivation at higher temperatures. To better understand the causal factor of reduced supercharged enzyme activity towards AFEX corn stover, we performed hydrolysis assays on cellulose-I/xylan/pNPC, lignin inhibition assays, and thermal stability assays. Altogether, these assays showed that the negatively supercharged mutants were highly impacted by reduced activity towards xylan whereas the positively supercharged mutants showed dramatically reduced activity towards cellulose and xylan. It was identified that a combination of impaired cellulose binding and lower thermal stability was the cause of reduced hydrolytic activity of positively supercharged enzyme sub-group. Overall, this study demonstrated a systematic approach to investigate the behavior of supercharged enzymes and identified supercharged enzyme constructs that show superior activity at elevated temperatures. Future work will address the impact of parameters such as pH, salt concentration, and assay temperature on the hydrolytic activity and thermal stability of supercharged enzymes.
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Authors: Dharanidaran Jayachandran, Amar Parvate, Jory T Brookreson, James E Evans, Shishir PS Chundawat
Paper Link: Link
Abstract: Polysaccharides are a major class of natural polymers found abundantly across all major life forms and play a critical role as structural, metabolic, or functional components in biomolecular processes. Some polysaccharides like cellulose and hyaluronan are synthesized by membrane-bound family-2 glycosyltransferases (GTs). Despite the fact that the GT-2 family has the maximum number of deposited sequences, the biochemistry of GT-2 family enzymes is still poorly understood due to difficulties associated with GT membrane protein expression, purification, and reconstitution in lipid carriers. Here, we chose Populus tremula x tremuloides cellulose synthase 8 (PttCesA8) and Streptococcus equisimilishyaluronan synthase (SeHas) as putative family-2-GTs to be expressed in a wheat-germ-based cell-free expression (CFE) system as proteoliposomes. The cell-free products were obtained as reconstituted liposomes directly from CFE reactions at high yields and short processing times compared to other approaches. GT enzymes expression was confirmed using SDS-PAGE and immunoblotting, and the integration of GTs in lipid layers was observed using cryogenic electron microscopy. Both GTs tested were catalytically active when incubated with their respective substrates and cofactors. The Michalis-Menten kinetic constants, Km for PttCesA8, was 295.8 µM, and SeHas was 321.51 µM (toward UDP N-Acetyl Glucosamine) and 207.88 µM (toward UDP Glucuronic Acid), respectively. UDP was found to actively inhibit both these GTs with apparent inhibition constants of 10.08 µM and 24.38 µM. Mutation of specific conserved residues in structure-deficit SeHas confirmed the importance of lysine-139, glutamine-248, and threonine-283 residues in hyaluronan biosynthesis. In summary, wheat-germ-based CFE can be used to express functionally active and liposome-reconstituted family-2 GTs at high yields with relative ease to enable classical enzymology assays and will also enable more detailed structural studies in the near future.
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Authors: Antonio DeChellis, Bhargava Nemmaru, Deanne Sammond, Jenna Douglass, Nivedita Patil, Olivia Reste, Shishir PS Chundawat
Paper Link: Link
Abstract: Lignocellulosic biomass recalcitrance to enzymatic degradation necessitates high enzyme loadings, incurring large processing costs for the production of industrial-scale biofuels or biochemicals. Manipulating surface charge interactions to minimize nonproductive interactions between cellulolytic enzymes and plant cell wall components (e.g., lignin or cellulose) via protein supercharging has been hypothesized to improve biomass biodegradability but with limited demonstrated success to date. Here, we characterize the effect of introducing non-natural enzyme surface mutations and net charge on cellulosic biomass hydrolysis activity by designing a library of supercharged family-5 endoglucanase Cel5A and its native family-2a carbohydrate binding module (CBM) originally belonging to an industrially relevant thermophilic microbe, Thermobifida fusca. A combinatorial library of 33 mutant constructs containing different CBM and Cel5A designs spanning a net charge range of −52 to 37 was computationally designed using Rosetta macromolecular modeling software. Activity for all mutants was rapidly characterized as soluble cell lysates, and promising mutants (containing mutations on the CBM, Cel5A catalytic domain, or both CBM and Cel5A domains) were then purified and systematically characterized. Surprisingly, often endocellulases with mutations on the CBM domain alone resulted in improved activity on cellulosic biomass, with three top-performing supercharged CBM mutants exhibiting between 2- and 5-fold increase in activity, compared to native enzyme, on both pretreated biomass enriched in lignin (i.e., corn stover) and isolated crystalline/amorphous cellulose. Furthermore, we were able to clearly demonstrate that endocellulase net charge can be selectively fine-tuned using a protein supercharging protocol for targeting distinct substrates and maximizing biocatalytic activity. Additionally, several supercharged CBM-containing endocellulases exhibited a 5–10 °C increase in optimal hydrolysis temperature, compared to native enzyme, which enabled further increase in hydrolytic yield at higher operational reaction temperatures. This study demonstrates the first successful implementation of enzyme supercharging of cellulolytic enzymes to increase hydrolytic activity toward complex lignocellulosic biomass-derived substrates.
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Authors: Khovesh Ramdin, Markus Hackl, Shishir PS Chundawat
Paper Link: Link
Abstract: The analysis of particles bound to surfaces by tethers can facilitate understanding of biophysical phenomena (e.g., DNA–protein or protein–ligand interactions and DNA extensibility). Modeling such systems theoretically aids in understanding experimentally observed motions, and the limitations of such models can provide insight into modeling complex systems. The simulation of tethered particle motion (TPM) allows for analysis of complex behaviors exhibited by such systems; however, this type of experiment is rarely taught in undergraduate science classes. We have developed a MATLAB simulation package intended to be used in academic contexts to concisely model and graphically represent the behavior of different tether–particle systems. We show how analysis of the simulation results can be used in biophysical research using single-molecule force spectroscopy (SMFS). Students in physics, engineering, and chemistry will be able to make connections with principles embedded in the field of study and understand how those principles can be used to create meaningful conclusions in a multidisciplinary context. The simulation package can model any given tether–particle system and allows the user to generate a parameter space with static and dynamic model components. Our simulation was successfully able to recreate generally observed experimental trends by using acoustic force spectroscopy (AFS). Further, the simulation was validated through consideration of the conservation of energy of the tether–bead system, trend analyses, and comparison of particle positional data from actual TPM in silico experiments conducted to simulate data with a parameter space similar to the AFS experimental setup. Overall, our TPM simulator and graphical user interface is primarily for demonstrating behaviors characteristic to TPM in a classroom setting but can serve as a template for researchers to set up TPM simulations to mimic a specific SMFS experimental setup.