Substrate recognition and transport mechanism of the PIN-FORMED auxin exporters.

Auxins are pivotal plant hormones that regulate plant growth and transmembrane polar auxin transport (PAT) direct patterns of development. The PIN-FORMED (PIN) family of membrane transporters mediate auxin export from the plant cell and play crucial roles in PAT. Here we describe the recently solved structures of PIN transporters, PIN1, PIN3, and PIN8, and also their mechanisms of substrate recognition and transport of auxin. We compare structures of PINs in both inward- and outward-facing conformations, as well as PINs with different binding configurations for auxin. By this comparative analysis, a model emerges for an elevator transport mechanism. Central structural elements necessary for function are identified, and we show that these are shared with other distantly related protein families.

DNA topoisomerase 2-associated proteins PATL1 and PATL2 regulate the biogenesis of hERG K+ channels.

The human ether-a-go-go-related gene (hERG) K+ channel conducts a rapidly activating delayed rectifier K+ current (IKr), which is essential for normal electrical activity of the heart. Precise regulation of hERG channel biogenesis is critical for serving its physiological functions, and deviations from the regulation result in human diseases. However, the mechanism underlying the precise regulation of hERG channel biogenesis remains elusive. Here, by using forward genetic screen, we found that PATR-1, the Caenorhabditis elegans homolog of the yeast DNA topoisomerase 2-associated protein PAT1, is a critical regulator for the biogenesis of UNC-103, the ERG K+ channel in C. elegans. A loss-of-function mutation in patr-1 down-regulates the expression level of UNC-103 proteins and suppresses the phenotypic defects resulted from a gain-of-function mutation in the unc-103 gene. Furthermore, downregulation of PATL1 and PATL2, the human homologs of PAT1, decreases protein levels and the current density of native hERG channels in SH-SY5Y cells and human-induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs). Knockdown of PATL1 and PATL2 elongates the duration of action potentials in hiPSC-CMs, suggesting that PATL1 and PATL2 affect the function of hERG channels and hence electrophysiological characteristics in the human heart. Further studies found that PATL1 and PATL2 interact with TFIIE, a general transcription factor required for forming the RNA polymerase II preinitiation complex, and dual-luciferase reporter assays indicated that PATL1 and PATL2 facilitate the transcription of hERG mRNAs. Together, our study discovers that evolutionarily conserved DNA topoisomerase 2-associated proteins regulate the biogenesis of hERG channels via a transcriptional mechanism.

PAT in the ER for Transmembrane Protein Folding.

Integral membrane proteins (IMPs) have crucial roles in many cellular processes. A novel intramembrane chaperone complex, recently elucidated by Chitwood and Hedge, provides mechanistic insight of IMP biogenesis and folding, illustrating how IMPs with multiple transmembrane domains (TMDs) are assembled within the endoplasmic reticulum (ER) membrane.

Binding of perilipin 3 to membranes containing diacylglycerol is mediated by conserved residues within its PAT domain.

Perilipins (PLINs) constitute an evolutionarily conserved family of proteins that specifically associate with the surface of lipid droplets (LDs). These proteins function in LD biogenesis and lipolysis and help to stabilize the surface of LDs. PLINs are typically composed of three different protein domains. They share an N-terminal PAT domain of unknown structure and function, a central region containing 11-mer repeats that form amphipathic helices, and a C-terminal domain that adopts a 4-helix bundle structure. How exactly these three distinct domains contribute to PLIN function remains to be determined. Here, we show that the N-terminal PAT domain of PLIN3 binds diacylglycerol (DAG), the precursor to triacylglycerol, a major storage lipid of LDs. PLIN3 and its PAT domain alone bind liposomes with micromolar affinity and PLIN3 binds artificial LDs containing low concentrations of DAG with nanomolar affinity. The PAT domain of PLIN3 is predicted to adopt an amphipathic triangular shaped structure. In silico ligand docking indicates that DAG binds to one of the highly curved regions within this domain. A conserved aspartic acid residue in the PAT domain, E86, is predicted to interact with DAG, and we found that its substitution abrogates high affinity binding of DAG as well as DAG-stimulated association with liposome and artificial LDs. These results indicate that the PAT domain of PLINs harbor specific lipid-binding properties that are important for targeting these proteins to the surface of LDs and to ER membrane domains enriched in DAG to promote LD formation.

In situ Diazonium Salt Formation and Photochemical Aryl-Aryl Coupling in Continuous Flow Monitored by Inline NMR Spectroscopy.

A novel class of diazonium salts is introduced for the photochemical aryl-aryl coupling to produce (substituted) biphenyls. As common diazonium tetrafluoroborate salts fail, soluble and safe aryl diazonium trifluoroacetates are applied. In this mild synthesis route no catalysts are required to generate an aryl-radical by irradiation with UV-A light (365 nm). This reactive species undergoes direct C-H arylation at an arene, forming the product in reasonable reaction times. With the implementation of a continuous flow setup in a capillary photoreactor 13 different biphenyl derivatives are successfully synthesized. By integrating an inline 19F-NMR benchtop spectrometer, samples are reliably quantified as the fluorine-substituents act as a probe. Here, real-time NMR spectroscopy is a perfect tool to monitor the continuously operated system, which produces fine chemicals of industrial relevance even in a multigram scale.

Advanced control strategies for continuous capture of monoclonal antibodies based upon biolayer interferometry.

The semi and fully continuous production of monoclonal antibodies (mAbs) has been gaining traction as a lower cost, and efficient production of mAbs to broaden patient access. To be truly flexible and adaptive to process demands, the industry has lacked sufficient advanced control strategies. The variation of the upstream product concentration typically cannot be handled by the downstream capture step, which is configured for a constant feed concentration and fixed binding capacity. This inflexibility leads to losses of efficiency and product yield. This study shows that these challenges can be overcome by a novel advanced control strategy concept that includes dynamic control throughout a perfusion bioreactor, with cell retention by alternating tangential flow, integrated with simulated moving bed (SMB) multi-column chromatography. The automation workflow and advanced control strategy were implemented through the use of a visual programming development environment. This enabled dynamic flow control across the upstream and downstream process integrated with a dynamic column loading of the SMB. A sensor prototype, based on continuous biolayer interferometry measurements was applied to detect mAb breakthrough within the last column flow-through to manage column switching. This novel approach provided higher specificity and lower background signal compared to commonly used spectroscopy methods, resulting in an optimized resin utilization while simultaneously avoiding product loss. The dynamic loading was found to provide a twofold increase of the mAb concentration in the eluate compared to a conservative approach with a predefined recipe with similar impurity removal. This concept shows that advanced control strategies can lead to significant process efficiency and yield improvement.

Robust platform for inline Raman monitoring and control of perfusion cell culture.

Perfusion cell culture has been gaining increasing popularity for biologics manufacturing due to benefits such as smaller footprint, increased productivity, consistent product quality and manufacturing flexibility, cost savings, and so forth. Process Analytics Technologies tools are highly desirable for effective monitoring and control of long-running perfusion processes. Raman has been widely investigated for monitoring and control of traditional fed batch cell culture process. However, implementation of Raman for perfusion cell culture has been very limited mainly due to challenges with high-cell density and long running times during perfusion which cause extremely high fluorescence interference to Raman spectra and consequently it is exceedingly difficult to develop robust chemometrics models. In this work, a platform based on Raman measurement of permeate has been proposed for effective analysis of perfusion process. It has been demonstrated that this platform can effectively circumvent the fluorescence interference issue while providing rich and timely information about perfusion dynamics to enable efficient process monitoring and robust bioreactor feed control. With the highly consistent spectral data from cell-free sample matrix, development of chemometrics models can be greatly facilitated. Based on this platform, Raman models have been developed for good measurement of several analytes including glucose, lactate, glutamine, glutamate, and permeate titer. Performance of Raman models developed this way has been systematically evaluated and the models have shown good robustness against changes in perfusion scale and variations in permeate flowrate; thus models developed from small lab scale can be directly transferred for implementation in much larger scale of perfusion. With demonstrated robustness, this platform provides a reliable approach for automated glucose feed control in perfusion bioreactors. Glucose model developed from small lab scale has been successfully implemented for automated continuous glucose feed control of perfusion cell culture at much larger scale.

Bioprocess in-line monitoring and control using Raman spectroscopy and Indirect Hard Modeling (IHM).

Process in-line monitoring and control are crucial to optimize the productivity of bioprocesses. A frequently applied Process Analytical Technology (PAT) tool for bioprocess in-line monitoring is Raman spectroscopy. However, evaluating bioprocess Raman spectra is complex and calibrating state-of-the-art statistical evaluation models is effortful. To overcome this challenge, we developed an Indirect Hard Modeling (IHM) prediction model in a previous study. The combination of Raman spectroscopy and the IHM prediction model enables non-invasive in-line monitoring of glucose and ethanol mass fractions during yeast fermentations with significantly less calibration effort than comparable approaches based on statistical models. In this study, we advance this IHM-based approach and successfully demonstrate that the combination of Raman spectroscopy and IHM is capable of not only bioprocess monitoring but also bioprocess control. For this purpose, we used this combination's in-line information as input of a simple on-off glucose controller to control the glucose mass fraction in Saccharomyces cerevisiae fermentations. When we performed two of these fermentations with different predefined glucose set points, we achieved similar process control quality as approaches using statistical models, despite considerably smaller calibration effort. Therefore, this study reaffirms that the combination of Raman spectroscopy and IHM is a powerful PAT tool for bioprocesses.

Accelerating attribute-focused process and product development through the development and deployment of autonomous process analytical technology platform system.

Enabling real-time monitoring and control of the biomanufacturing processes through product quality insights continues to be an area of focus in the biopharmaceutical industry. The goal is to manufacture products with the desired quality attributes. To realize this rigorous attribute-focused Quality by Design approach, it is critical to support the development of processes that consistently deliver high-quality products and facilitate product commercialization. Time delays associated with offline analytical testing can limit the speed of process development. Thus, developing and deploying analytical technology is necessary to accelerate process development. In this study, we have developed the micro sequential injection process analyzer and the automatic assay preparation platform system. These innovations address the unmet need for an automatic, online, real-time sample acquisition and preparation platform system for in-process monitoring, control, and release of biopharmaceuticals. These systems can also be deployed in laboratory areas as an offline analytical system and on the manufacturing floor to enable rapid testing and release of products manufactured in a good manufacturing practice environment.

Application of PAT Probes in Aluminum Phosphate Adjuvant Manufacturing.

PURPOSE: This study is focused on monitoring process parameters and quality attributes of aluminum phosphate (AlPO4) using multiple in-line probes incorporated into an industrial-scale adjuvant suspension manufacturing unit. METHODS: The manufacturing of aluminum adjuvant suspension was monitored at manufacturing scale using conductivity, turbidity, infrared, and particle sizing and count probes to follow the continuous evolution of particle formation and size distribution, and the reaction kinetics during the synthesis of AlPO4. RESULTS: The data showed that AlPO4 forms large particles at the early stages of mixing, followed by a decrease in size and then stabilization towards the later stages of mixing and pH adjustment. The results provided a complementary view of process events and assisted in optimizing several parameters, e.g., flow rate of reactants AlCl3 and Na3PO4 solutions, mixing rate, pH, and conductivity of AlPO4, as well as adjuvant quality attribute such as particle size, thus streamlining and shortening the process development stage. CONCLUSION: The results of this study showed the usefulness of the in-line probes to automate continuous assessment of AlPO4 batch-to-batch consistency during in-house adjuvant production at the industrial scale.

Online monitoring of protein refolding in inclusion body processing using intrinsic fluorescence.

Inclusion bodies (IBs) are protein aggregates formed as a result of overexpression of recombinant protein in E. coli. The formation of IBs is a valuable strategy of recombinant protein production despite the need for additional processing steps, i.e., isolation, solubilization and refolding. Industrial process development of protein refolding is a labor-intensive task based largely on empirical approaches rather than knowledge-driven strategies. A prerequisite for knowledge-driven process development is a reliable monitoring strategy. This work explores the potential of intrinsic tryptophan and tyrosine fluorescence for real-time and in situ monitoring of protein refolding. In contrast to commonly established process analytical technology (PAT), this technique showed high sensitivity with reproducible measurements for protein concentrations down to 0.01 g L - 1 . The change of protein conformation during refolding is reflected as a shift in the position of the maxima of the tryptophan and tyrosine fluorescence spectra as well as change in the signal intensity. The shift in the peak position, expressed as average emission wavelength of a spectrum, was correlated to the amount of folding intermediates whereas the intensity integral correlates to the extent of aggregation. These correlations were implemented as an observation function into a mechanistic model. The versatility and transferability of the technique were demonstrated on the refolding of three different proteins with varying structural complexity. The technique was also successfully applied to detect the effect of additives and process mode on the refolding process efficiency. Thus, the methodology presented poses a generic and reliable PAT tool enabling real-time process monitoring of protein refolding.

Micro simulated moving bed chromatography-mass spectrometry as a continuous on-line process analytical tool.

Continuous manufacturing is becoming increasingly important in the (bio-)pharmaceutical industry, as more product can be produced in less time and at lower costs. In this context, there is a need for powerful continuous analytical tools. Many established off-line analytical methods, such as mass spectrometry (MS), are hardly considered for process analytical technology (PAT) applications in biopharmaceutical processes, as they are limited to at-line analysis due to the required sample preparation and the associated complexity, although they would provide a suitable technique for the assessment of a wide range of quality attributes. In this study, we investigated the applicability of a recently developed micro simulated moving bed chromatography system (µSMB) for continuous on-line sample preparation for MS. As a test case, we demonstrate the continuous on-line MS measurement of a protein solution (myoglobin) containing Tris buffer, which interferes with ESI-MS measurements, by continuously exchanging this buffer with a volatile ammonium acetate buffer suitable for MS measurements. The integration of the µSMB significantly increases MS sensitivity by removing over 98% of the buffer substances. Thus, this study demonstrates the feasibility of on-line µSMB-MS, providing a versatile PAT tool by combining the detection power of MS for various product attributes with all the advantages of continuous on-line analytics.

Association study of NAFLD with pericoronary adipose tissue and pericardial adipose tissue: Diagnosis of stable CAD patients with NAFLD based on radiomic features.

BACKGROUND AND AIM: Nonalcoholic fatty liver disease (NAFLD) is prone to complicated cardiovascular disease, and we aimed to identify patients with NAFLD who are prone to developing stable coronary artery disease (CAD). METHODS AND RESULTS: We retrospectively recruited adults who underwent coronary computed tomography angiography (CTA). A total of 127 NAFLD patients and 127 non-NAFLD patients were included in this study. Clinical features and imaging parameters were analysed, mainly including pericardial adipose tissue (PAT), pericoronary adipose tissue (PCAT), and radiomic features of 6792 PCATs. The inflammatory associations of NAFLD patients with PAT and PCAT were analysed. Clinical features (model 1), CTA parameters (model 2), the radscore (model 3), and a composite model (model 4) were constructed to identify patients with NAFLD with stable CAD. The presence of NAFLD resulted in a greater inflammatory involvement in all three coronary arteries (all P < 0.01) and was associated with increased PAT volume (r = 0.178**, P < 0.05). In the presence of NAFLD, the mean CT value of the PAT was significantly correlated with the fat attenuation index (FAI) in all three vessels and had the strongest correlation with the RCA FAI (r = 0.55, p < 0.001). A total of 9 radiomic features were screened by LASSO regression to calculate radiomic scores. In the model comparison, model 4 had the best performance of all models (AUC 0.914 [0.863-0.965]) and the highest overall diagnostic value of the model (sensitivity: 0.814, specificity: 0.941). CONCLUSIONS: NAFLD correlates with PAT volume and PCAT inflammation. Furthermore, combining clinical features, CTA parameters, and radiomic scores can improve the efficiency of early diagnosis of stable CAD in patients with NAFLD.

From lab-based to in-line: Analytical tools for the characterization of whey protein denaturation and aggregation-A review.

Whey protein denaturation and aggregation have long been areas of research interest to the dairy industry, having significant implications for process performance and final product functionality and quality. As such, a significant number of analytical techniques have been developed or adapted to assess and characterize levels of whey protein denaturation and aggregation, to either maximize processing efficiency or create products with enhanced functionality (both technological and biological). This review aims to collate and critique these approaches based on their analytical principles and outline their application for the assessment of denaturation and aggregation. This review also provides insights into recent developments in process analytical technologies relating to whey protein denaturation and aggregation, whereby some of the analytical methods have been adapted to enable measurements in-line. Developments in this area will enable more live, in-process data to be generated, which will subsequently allow more adaptive processing, enabling improved product quality and processing efficiency. Along with the applicability of these techniques for the assessment of whey protein denaturation and aggregation, limitations are also presented to help assess the suitability of each analytical technique for specific areas of interest.

An Indocyanine Green-Based Nanoprobe for In Vivo Detection of Cellular Senescence.

There is an urgent need to improve conventional cancer-treatments by preventing detrimental side effects, cancer recurrence and metastases. Recent studies have shown that presence of senescent cells in tissues treated with chemo- or radiotherapy can be used to predict the effectiveness of cancer treatment. However, although the accumulation of senescent cells is one of the hallmarks of cancer, surprisingly little progress has been made in development of strategies for their detection in vivo. To address a lack of detection tools, we developed a biocompatible, injectable organic nanoprobe (NanoJagg), which is selectively taken up by senescent cells and accumulates in the lysosomes. The NanoJagg probe is obtained by self-assembly of indocyanine green (ICG) dimers using a scalable manufacturing process and characterized by a unique spectral signature suitable for both photoacoustic tomography (PAT) and fluorescence imaging. In vitro, ex vivo and in vivo studies all indicate that NanoJaggs are a clinically translatable probe for detection of senescence and their PAT signal makes them suitable for longitudinal monitoring of the senescence burden in solid tumors after chemotherapy or radiotherapy.

Advances in the study of the function and mechanism of the action of flavonoids in plants under environmental stresses.

MAIN CONCLUSION: This review summarizes the anti-stress effects of flavonoids in plants and highlights its role in the regulation of polar auxin transport and free radical scavenging mechanism. As secondary metabolites widely present in plants, flavonoids play a vital function in plant growth, but also in resistance to stresses. This review introduces the classification, structure and synthetic pathways of flavonoids. The effects of flavonoids in plant stress resistance were enumerated, and the mechanism of flavonoids in plant stress resistance was discussed in detail. It is clarified that plants under stress accumulate flavonoids by regulating the expression of flavonoid synthase genes. It was also determined that the synthesized flavonoids are transported in plants through three pathways: membrane transport proteins, vesicles, and bound to glutathione S-transferase (GST). At the same time, the paper explores that flavonoids regulate polar auxin transport (PAT) by acting on the auxin export carrier PIN-FORMED (PIN) in the form of ATP-binding cassette subfamily B/P-glycoprotein (ABCB/PGP) transporter, which can help plants to respond in a more dominant form to stress. We have demonstrated that the number and location of hydroxyl groups in the structure of flavonoids can determine their free radical scavenging ability and also elucidated the mechanism by which flavonoids exert free radical removal in cells. We also identified flavonoids as signaling molecules to promote rhizobial nodulation and colonization of arbuscular mycorrhizal fungi (AMF) to enhance plant-microbial symbiosis in defense to stresses. Given all this knowledge, we can foresee that the in-depth study of flavonoids will be an essential way to reveal plant tolerance and enhance plant stress resistance.

The vascular function effects of adding exenatide or meal insulin to basal insulin therapy in early type 2 diabetes.

OBJECTIVE: Basal insulin glargine has a neutral effect on cardiovascular risk in type 2 diabetes (T2DM). In practice, basal insulin is often paired with a glucagon-like peptide-1 receptor agonist (GLP1-RA) or meal insulin; however, the cardiovascular implications of these combinations have not been fully elucidated. In this context, we sought to evaluate the vascular function effects of adding the GLP1-RA exenatide or meal insulin lispro to basal glargine therapy in early T2DM. METHODS: In this 20-week trial, adults with T2DM of < 7-years duration were randomized to 8-weeks treatment with (i) insulin glargine (Glar), (ii) glargine + thrice-daily lispro (Glar/Lispro), or (iii) glargine + twice-daily exenatide (Glar/Exenatide), followed by 12-weeks washout. At baseline, 8-weeks, and washout, fasting endothelial function was assessed with reactive hyperemia index (RHI) measurement by peripheral arterial tonometry. RESULTS: At baseline, there were no differences in blood pressure (BP), heart rate (HR) or RHI between participants randomized to Glar (n = 24), Glar/Lispro (n = 24), and Glar/Exenatide (n = 25). At 8-weeks, Glar/Exenatide decreased systolic BP (mean - 8.1 mmHg [95%CI - 13.9 to - 2.4], p = 0.008) and diastolic BP (mean - 5.1 mmHg [- 9.0 to - 1.3], p = 0.012) compared to baseline, with no significant changes in HR or RHI. Notably, baseline-adjusted RHI (mean ± SE) did not differ between the groups at 8-weeks (Glar 2.07 ± 0.10; Glar/Lispro 2.00 ± 0.10; Glar/Exenatide 1.81 ± 0.10; p = 0.19), nor did baseline-adjusted BP or HR. There were no differences between the groups in baseline-adjusted RHI, BP or HR after 12-weeks washout. CONCLUSION: Adding either exenatide or lispro to basal insulin therapy does not appear to affect fasting endothelial function in early T2DM. TRIAL REGISTRATION: ClinicalTrials.Gov NCT02194595.

Real-time detection of mAb aggregates in an integrated downstream process.

The implementation of continuous processing in the biopharmaceutical industry is hindered by the scarcity of process analytical technologies (PAT). To monitor and control a continuous process, PAT tools will be crucial to measure real-time product quality attributes such as protein aggregation. Miniaturizing these analytical techniques can increase measurement speed and enable faster decision-making. A fluorescent dye (FD)-based miniaturized sensor has previously been developed: a zigzag microchannel which mixes two streams under 30 s. Bis-ANS and CCVJ, two established FDs, were employed in this micromixer to detect aggregation of the biopharmaceutical monoclonal antibody (mAb). Both FDs were able to robustly detect aggregation levels starting at 2.5%. However, the real-time measurement provided by the microfluidic sensor still needs to be implemented and assessed in an integrated continuous downstream process. In this work, the micromixer is implemented in a lab-scale integrated system for the purification of mAbs, established in an ÄKTA™ unit. A viral inactivation and two polishing steps were reproduced, sending a sample of the product pool after each phase directly to the microfluidic sensor for aggregate detection. An additional UV sensor was connected after the micromixer and an increase in its signal would indicate that aggregates were present in the sample. The at-line miniaturized PAT tool provides a fast aggregation measurement, under 10 min, enabling better process understanding and control.

Advances in bioreactor control for production of biotherapeutic products.

Advanced control strategies are well established in chemical, pharmaceutical, and food processing industries. Over the past decade, the application of these strategies is being explored for control of bioreactors for manufacturing of biotherapeutics. Most of the industrial bioreactor control strategies apply classical control techniques, with the control system designed for the facility at hand. However, with the recent progress in sensors, machinery, and industrial internet of things, and advancements in deeper understanding of the biological processes, coupled with the requirement of flexible production, the need to develop a robust and advanced process control system that can ease process intensification has emerged. This has further fuelled the development of advanced monitoring approaches, modeling techniques, process analytical technologies, and soft sensors. It is seen that proper application of these concepts can significantly improve bioreactor process performance, productivity, and reproducibility. This review is on the recent advancements in bioreactor control and its related aspects along with the associated challenges. This study also offers an insight into the future prospects for development of control strategies that can be designed for industrial-scale production of biotherapeutic products.

Bioprocess in-line monitoring using Raman spectroscopy and Indirect Hard Modeling (IHM): A simple calibration yields a robust model.

To increase the process productivity and product quality of bioprocesses, the in-line monitoring of critical process parameters is highly important. For monitoring substrate, metabolite, and product concentrations, Raman spectroscopy is a commonly used Process Analytical Technology (PAT) tool that can be applied in-situ and non-invasively. However, evaluating bioprocess Raman spectra with a robust state-of-the-art statistical model requires effortful model calibration. In the present study, we in-line monitored a glucose to ethanol fermentation by Saccharomyces cerevisiae (S. cerevisiae) using Raman spectroscopy in combination with the physics-based Indirect Hard Modeling (IHM) and showed successfully that IHM is an alternative to statistical models with significantly lower calibration effort. The IHM prediction model was developed and calibrated with only 16 Raman spectra in total, which did not include any process spectra. Nevertheless, IHM's root mean square errors of prediction (RMSEPs) for glucose (3.68 g/L) and ethanol (1.69 g/L) were comparable to the prediction quality of similar studies that used statistical models calibrated with several calibration batches. Despite our simple calibration, we succeeded in developing a robust model for evaluating bioprocess Raman spectra.