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Open access publications by faculty, postdocs, and graduate students in the Department of Chemical and Biomolecular Engineering

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    Megakaryocyte membrane-wrapped nanoparticles for targeted cargo delivery to hematopoietic stem and progenitor cells
    (Bioengineering and Translational Medicine, 2022-11-29) Das, Samik; Harris, Jenna C.; Winter, Erica J.; Kao, Chen-Yuan; Day, Emily S.; Papoutsakis, Eleftherios Terry
    Hematopoietic stem and progenitor cells (HSPCs) are desirable targets for gene therapy but are notoriously difficult to target and transfect. Existing viral vector-based delivery methods are not effective in HSPCs due to their cytotoxicity, limited HSPC uptake and lack of target specificity (tropism). Poly(lactic-co-glycolic acid) (PLGA) nanoparticles (NPs) are attractive, nontoxic carriers that can encapsulate various cargo and enable its controlled release. To engineer PLGA NP tropism for HSPCs, megakaryocyte (Mk) membranes, which possess HSPC-targeting moieties, were extracted and wrapped around PLGA NPs, producing MkNPs. In vitro, fluorophore-labeled MkNPs are internalized by HSPCs within 24 h and were selectively taken up by HSPCs versus other physiologically related cell types. Using membranes from megakaryoblastic CHRF-288 cells containing the same HSPC-targeting moieties as Mks, CHRF-wrapped NPs (CHNPs) loaded with small interfering RNA facilitated efficient RNA interference upon delivery to HSPCs in vitro. HSPC targeting was conserved in vivo, as poly(ethylene glycol)–PLGA NPs wrapped in CHRF membranes specifically targeted and were taken up by murine bone marrow HSPCs following intravenous administration. These findings suggest that MkNPs and CHNPs are effective and promising vehicles for targeted cargo delivery to HSPCs.
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    Simulation of high-concentration self-interactions for monoclonal antibodies from well-behaved to poorly-behaved systems
    (AIChE Journal, 2022-11-21) Forder, James K.; Ilott, Andrew J.; Sahin, Erinc; Roberts, Christopher J.
    Attractive self-interactions of therapeutic proteins are linked to problematic solution behaviors at high protein concentrations such as reversible or irreversible aggregation, high viscosity, opalescence, phase separation, and low solubility. Prediction of attractive self-interactions early in development can improve the processes of formulation development and candidate selection. To that end, a coarse-grained model with explicit representation of charged sites was used to accurately predict a broad range of protein self-interactions at high protein concentrations (up to 160 mg/ml) for multiple monoclonal antibodies and formulations, including strong electrostatic attractions, with static light scattering measurements at low protein concentrations as the only experimental input. In addition, Mayer-weighted electrostatic energies for charged residues from these simulations can contribute to understanding of electrostatic interactions and guide the development of protein variants.
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    MIBiG 3.0: a community-driven effort to annotate experimentally validated biosynthetic gene clusters
    (Nucleic Acids Research, 0022-11-18) Terlouw, Barbara R.; Blin, Kai; Navarro-Muñoz, Jorge C.; Avalon, Nicole E.; Chevrette, Marc G.; Egbert, Susan; Lee, Sanghoon; Meijer, David; Recchia, Michael J. J.; Reitz, Zachary L.; van Santen, Jeffrey A.; Selem-Mojica, Nelly; Tørring, Thomas; Zaroubi, Liana; Alanjary, Mohammad; Aleti, Gajender; Aguilar, César; Al-Salihi, Suhad A. A.; Augustijn, Hannah E.; Avelar-Rivas, J. Abraham; Avitia-Domínguez, Luis A.; Barona-Gómez, Francisco; Bernaldo-Agüero, Jordan; Bielinski, Vincent A.; Biermann, Friederike; Booth, Thomas J.; Carrion Bravo, Victor J.; Castelo-Branco, Raquel; Chagas, Fernanda O.; Cruz-Morales, Pablo; Du, Chao; Duncan, Katherine R.; Gavriilidou, Athina; Gayrard, Damien; Gutiérrez-García, Karina; Haslinger, Kristina; Helfrich, Eric J. N.; van der Hooft, Justin J. J.; Jati, Afif P.; Kalkreuter, Edward; Kalyvas, Nikolaos; Kang, Kyo Bin; Kautsar, Satria; Kim, Wonyong; Kunjapur, Aditya M.; Li, Yong-Xin; Lin, Geng-Min; Loureiro, Catarina; Louwen, Joris J. R.; Louwen, Nico L. L.; Lund, George; Parra, Jonathan; Philmus, Benjamin; Pourmohsenin, Bita; Pronk, Lotte J. U.; Rego, Adriana; Rex, Devasahayam Arokia Balaya; Robinson, Serina; Rosas-Becerra, L. Rodrigo; Roxborough, Eve T.; Schorn, Michelle A.; Scobie, Darren J.; Singh, Kumar Saurabh; Sokolova, Nika; Tang, Xiaoyu; Udwary, Daniel; Vigneshwari, Aruna; Vind, Kristiina; Vromans, Sophie P. J. M. Vromans; Waschulin, Valentin; Williams, Sam E.; Winter, Jaclyn M.; Witte, Thomas E.; Xie, Huali; Yang, Dong; Yu, Jingwei; Zdouc, Mitja; Zhong, Zheng; Collemare, Jérôme; Linington, Roger G.; Weber, Tilmann; Medema, Marnix H.
    With an ever-increasing amount of (meta)genomic data being deposited in sequence databases, (meta)genome mining for natural product biosynthetic pathways occupies a critical role in the discovery of novel pharmaceutical drugs, crop protection agents and biomaterials. The genes that encode these pathways are often organised into biosynthetic gene clusters (BGCs). In 2015, we defined the Minimum Information about a Biosynthetic Gene cluster (MIBiG): a standardised data format that describes the minimally required information to uniquely characterise a BGC. We simultaneously constructed an accompanying online database of BGCs, which has since been widely used by the community as a reference dataset for BGCs and was expanded to 2021 entries in 2019 (MIBiG 2.0). Here, we describe MIBiG 3.0, a database update comprising large-scale validation and re-annotation of existing entries and 661 new entries. Particular attention was paid to the annotation of compound structures and biological activities, as well as protein domain selectivities. Together, these new features keep the database up-to-date, and will provide new opportunities for the scientific community to use its freely available data, e.g. for the training of new machine learning models to predict sequence-structure-function relationships for diverse natural products. MIBiG 3.0 is accessible online at https://mibig.secondarymetabolites.org/.
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    Oxidative Functionalization of Long-Chain Liquid Alkanes by Pulsed Plasma Discharges at Atmospheric Pressure
    (ACS Sustainable Chemistry and Engineering, 2022-11-17) Nguyen, Darien K.; Dimitrakellis, Panagiotis; Talley, Michael R.; O'Dea, Robert M.; Epps, Thomas H. III; Watson, Mary P.; Vlachos, Dionisios G.
    We introduce the oxidation of long aliphatic alkanes using non-thermal, atmospheric plasma processing as an eco-friendly route for organic synthesis. A pulsed dielectric barrier discharge in He/O2 gas mixtures was employed to functionalize n-octadecane. C18 secondary alcohols and ketones were the main products, with an optimal molar yield of ∼29.2%. Prolonged treatment resulted in the formation of dialcohols, diketones, and higher molecular weight oxygenates. Lighter hydrocarbon products and decarboxylation to CO2 were also observed at longer treatment times and higher power inputs. A maximum energy yield of 5.48 × 10–8 mol/J was achieved at short treatment times and high powers, associated with higher selectivity to primary oxygenates. Direct hydroxylation of alkyl radicals, as well as disproportionation reactions, are proposed as the main pathways to alcohols and ketones. The results hold promise for functionalizing long hydrocarbon molecules at ambient conditions using catalyst-free plasma discharges.
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    Voltage Loss Diagnosis in CO2 Electrolyzers Using Five-Electrode Technique
    (ACS Energy Letters, 2022-12-09) Hansen, Kentaro U.; Cherniack, Luke H.; Jiao, Feng
    CO2 electrolysis is a promising carbon utilization technology. Currently, energetic efficiency still requires a significant improvement for commercialization. To rationally design a more efficient CO2 electrolyzer, diagnostic tools are necessary to pinpoint the source of voltage losses across the full cell at work. Here we develop a five-electrode technique to probe voltage drops at the cathode, anode, membrane, and their interfaces in a typical zero-gap cell. We show that the cathode/membrane ionic interface is the major source of overpotential, contributing 720 mV voltage loss at 600 mA cm–2. This loss can be mitigated by coating the catalyst directly onto the membrane to lower ionic resistances, reducing this voltage loss to 80 mV at the same current density. The improved design enables us to achieve a full cell performance of 3.55 V and >95% CO Faradaic efficiency at 800 mA cm–2, representing the highest performance for CO2 electrolysis with a dilute bicarbonate electrolyte. The insights provided by the five-electrode technique may guide the rational design of future membrane-based electrochemical cells.
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