Multi-cell-line learning for the data-driven construction of mechanistic metabolic models.

Mammalian cells are commonly used as hosts in cell culture for biologics production in the pharmaceutical industry. Structured mechanistic models of metabolism have been used to capture complex cellular mechanisms that contribute to varying metabolic shifts in different cell lines. However, little research has focused on the impact of temporal changes in enzyme abundance and activity on the modeling of cell metabolism. In this work, we present a framework for constructing mechanistic models of metabolism that integrate growth-signaling control of enzyme activity and transcript dynamics. The proposed approach is applied to build models for three Chinese hamster ovary (CHO) cell lines using fed-batch culture data and time-series transcript profiles. Leveraging information from the transcriptome data, we develop a parameter estimation approach based on multi-cell-line (MCL) learning, which combines data sets from different cell lines and trains the individual cell-line models jointly to improve model accuracy. The computational results demonstrate the important role of growth signaling and transcript variability in metabolic models as well as the virtue of the MCL approach for constructing cell-line models with a limited amount of data. The resulting models exhibit a high level of accuracy in predicting distinct metabolic behaviors in the different cell lines; these models can potentially be used to accelerate the process and cell-line development for the biomanufacturing of new protein therapeutics.

Kinetic-model-based pathway optimization with application to reverse glycolysis in mammalian cells.

Over the last two decades, model-based metabolic pathway optimization tools have been developed for the design of microorganisms to produce desired metabolites. However, few have considered more complex cellular systems such as mammalian cells, which requires the use of nonlinear kinetic models to capture the effects of concentration changes and cross-regulatory interactions. In this study, we develop a new two-stage pathway optimization framework based on kinetic models that incorporate detailed kinetics and regulation information. In Stage 1, a set of optimization problems are solved to identify and rank the enzymes that contribute the most to achieving the metabolic objective. Stage 2 then determines the optimal enzyme interventions for specified desired numbers of enzyme adjustments. It also incorporates multi-scenario optimization, which allows the simultaneous consideration of multiple physiological conditions. We apply the proposed framework to find enzyme adjustments that enable a reverse glucose flow in cultured mammalian cells, thereby eliminating the need for glucose feed in the late culture stage and enhancing process robustness. The computational results demonstrate the efficacy of the proposed approach; it not only captures the important regulations and key enzymes for reverse glycolysis but also identifies differences and commonalities in the metabolic requirements for different carbon sources.

Introducing Postmetalation Metal-Organic Framework to Control Perovskite Crystal Growth for Efficient Perovskite Solar Cells.

A novel lead-containing metal-organic framework (Pb-MOF) is synthesized through postmetalation of MOF-525. Postmetalation renders lead ions bound with the organic linker of MOF-525, which can serve as nucleation points to promote perovskite crystallization. The introduction of lead postmetalated MOF-525 (Pb-MOF) as a scaffold layer between compact TiO2 (c-TiO2) layer and perovskite layer promotes perovskite crystal growth in enlarging crystal grain size with better crystallinity, hence decreasing defect sites in the perovskite layer. Postmetalation of MOF-525 with lead ions allows MAPbI3 to form a solid crystal structure to facilitate the charge separation between electron transport layer (ETL) and light-harvesting layer so as to resolve the issue of possible vacancies present in MOFs. As a result, the champion perovskite solar cell (PSC) with the introduction of Pb-MOF exhibits a power conversion efficiency (PCE) of 20.87% and better stability (86% PCE retention after 40 days), outperforming the pristine PSC (16.85% PCE, with 52% retention after 40 days) and MOF-525-introduced PSC (18.61% PCE, with 76% retention after 40 days).

Asymmetric Benzotrithiophene-Based Hole Transporting Materials Provide High-Efficiency Perovskite Solar Cells.

In this study, we synthesized a series of small-molecule benzotrithiophenes (BTTs) and used them as hole transporting materials (HTMs) in perovskite solar cells (PSCs). The asymmetric benzo[2,1-b:-3,4-b':5,6-b″]trithiophene unit was used as the central core to which were appended various donor groups, namely, carbazole (BTT-CB), thieno thiophene (BTT-FT), triphenylamine (BTT-TPA), and bithiophene (BTT-TT). The extended aromatic core in the asymmetric BTT provided full planarity, thereby favoring intermolecular π-stacking and charge transport. The physical, optical, and electrical properties of these small-molecule HTMs are reported herein. BTT-TT displayed good crystallinity and superior hole mobility, when compared with those of the other three HTMs, and formed smooth and uniform surfaces when covering the perovskite active layer. Accordingly, among the devices prepared in this study, a PSC incorporating BTT-TT as the HTM achieved the highest power conversion efficiency (18.58%). Moreover, this BTT-TT-containing device exhibited good stability after storage for more than 700 h. Thus, asymmetric BTTs are promising candidate materials for use as small-molecule HTMs in PSCs.

Enhanced Near-Infrared Photoresponse of Inverted Perovskite Solar Cells Through Rational Design of Bulk-Heterojunction Electron-Transporting Layers.

How to extend the photoresponse of perovskite solar cells (PVSCs) to the region of near-infrared (NIR)/infrared light has become an appealing research subject in this field since it can better harness the solar irradiation. Herein, the typical fullerene electron-transporting layer (ETL) of an inverted PVSC is systematically engineered to enhance device's NIR photoresponse. A low bandgap nonfullerene acceptor (NFA) is incorporated into the fullerene ETL aiming to intercept the NIR light passing through the device. However, despite forming type II charge transfer with fullerene, the blended NFA cannot enhance the device's NIR photoresponse, as limited by the poor dissociation of photoexciton induced by NIR light. Fortunately, it can be addressed by adding a p-type polymer. The ternary bulk-heterojunction (BHJ) ETL is demonstrated to effectively enhance the device's NIR photoresponse due to the better cascade-energy-level alignment and increased hole mobility. By further optimizing the morphology of such a BHJ ETL, the derived PVSC is finally demonstrated to possess a 40% external quantum efficiency at 800 nm with photoresponse extended to the NIR region (to 950 nm), contributing ≈9% of the overall photocurrent. This study unveils an effective and simple approach for enhancing the NIR photoresponse of inverted PVSCs.

Designing Novel Poly(oxyalkylene)-Segmented Ester-Based Polymeric Dispersants for Efficient TiO2 Photoanodes of Dye-Sensitized Solar Cells.

A family of new polymeric dispersants, branched poly(oxyethylene)-segmented esters of trimellitic anhydride adduct (polyethylene glycol-trimethylolpropane-trimellitic anhydride, designated as PTT), were synthesized and utilized to homogeneously disperse TiO2 nanoparticles. The weight fraction of poly(oxyethylene)-segment in the dispersants and the molecular architecture in favoring the branched shape are two predominant factors for designing the effective dispersants. In particular, the poly(oxyethylene) block of 1000 g/mol from PEG1000 as the starting material and a total molecular weight of 12 000 g/mol have constituted the polymeric dispersants for the best performance for homogenizing TiO2 nanoparticles. The dispersant structures were characterized by using Fourier-transform infrared spectroscopy, acid value determination, and gel permeation chromatography. The TiO2 dispersibility was evaluated by dynamic light scattering and transmission electron microscopy. The synthesized dispersants were utilized to homogenize the as-prepared TiO2, further fabricated into films of photoanodes for dye-sensitized solar cells (DSSCs). The ultimate performance of DSSC was measured to be 8.17 ± 0.13% for the device efficiency (η) which was significantly higher than the conventional TiO2 photoanode at η = 7.14 ± 0.12%. The photoanode film was characterized by X-ray diffraction, Brunauer-Emmett-Teller surface area, and dye-loading amount measurements. The kinetics of photogenerated electron in the photoanode, including electron lifetime and electron transit time of the film, was studied via electrochemical impedance spectroscopy, intensity-modulated photocurrent spectroscopy, and intensity-modulated photovoltage spectroscopy.