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Most fungal fatty acid synthases assemble from two multidomain subunits, α and β, into a heterododecameric FAS complex. It has been recently shown that the complex assembly occurs in a cotranslational manner and is initiated by an interaction between the termini of α and β subunits. This initial engagement of subunits may be the rate-limiting phase of the assembly and subject to cellular regulation. Therefore, we hypothesized that bypassing this step by genetically fusing the subunits could be beneficial for biotechnological production of fatty acids. To test the concept, we expressed fused FAS subunits engineered for production of octanoic acid in Saccharomyces cerevisiae. Collectively, our data indicate that FAS activity is a limiting factor of fatty acid production and that FAS fusion proteins show a superior performance compared to their split counterparts. This strategy is likely a generalizable approach to optimize the production of fatty acids and derived compounds in microbial chassis organisms.
Metabolites such as lactate and free fatty acids (FFAs) abundantly occur in high concentrations in tumor and stromal cells of solid malignancies. Their known functions comprise the allocation of nutrients and intermediates for the generation of cell components, the evasion of immune destruction, the induction of vessel formation and the stimulation of cell migration in order to promote tumor growth, progression and metastasis. However, the role of metabolites as signaling molecules and the downstream mechanisms of metabolite receptor mediated signaling in tumor and stromal cells is poorly understood. Our study confirms the expression of Hydroxycarboxylic acid receptor 1 (HCA1) in solid human breast tumors and the expression of Free fatty acid receptor 4 (FFA4) in solid human colorectal tumors. In addition, the expression of HCA1 in human breast cancer cell lines as well as the expression of FFA4 in human colorectal cancer cell lines was proved. Moreover, our research reveals the expression HCA2, FFA2 and FFA4 in tumor associated macrophages (TAMs).
To test whether the loss of any of the metabolite receptors affects tumor growth and progression we utilized a syngeneic Lewis lung cancer (LLC1) tumor model, an azoxymethane (AOM) – dextran sulfate (DSS) colorectal cancer model and a Mouse mammary tumor virus Polyoma Virus middle T antigen (MMTV-PyMT) breast cancer model. The loss of HCA2 did not lead to a changed outcome compared to wild type littermates in any of the models. Likewise, the deletion of FFA4 had no influence on the LLC1 model and, surprisingly, tumor number and area in the AOM-DSS model also remained unaltered. The impact of HCA1 deficiency was investigated utilizing the MMTV-PyMT model and revealed a moderately improved tumor growth. The absence of FFA2 did not affect tumor growth in the LLC1 model but led to an increased number of colorectal tumors in the AOM-DSS model while the tumor area remained unchanged. The most compelling results were obtained upon the deletion of FFA2 in the MMTV-PyMT model. Here, we demonstrate that the loss of FFA2 significantly reduces tumor latency and also significantly improves tumor growth. Nevertheless, the formation of metastases in the LLC1 model and the MMTV-PyMT model did not show any changes upon the loss of any of the metabolite receptors.
Together, our results describe a tumor-protective effect of FFA2 with an unclear impact on metastatic processes. Considerations about putative mechanisms of short chain fatty acid (SCFA) mediated FFA2 signaling suggest potential targets for pharmacological interventions to treat mammary tumors.
Bacteria constantly attempt to hold up ion gradients across their membranes to maintain their resting potential for routine cell function, while coping with sudden environmental changes. Under abrupt hyperosmotic conditions, as faced when invading a host, most bacteria restore their turgor pressure by taking up potassium ions to prevent death by plasmolysis. Here, the potassium transporter AB, or KtrAB for short, is a key player. KtrAB consists of the membrane-embedded KtrB dimer, which includes two pores organized in tandem, and a cytoplasmic, octameric KtrA ring, which regulates these two pores. The KtrB subunits alone were suggested to function as rather non-selective ion channels translocating potassium and sodium ions. The KtrA subunits confer transport velocity, K+ selectivity as well as Na+ and nucleotide dependency to the Ktr system. The nucleotide regulation by binding to KtrA is rather well characterized. In contrast, the regulatory role of Na+ remains elusive. Controversially discussed is how selective the ion translocation by KtrB is and how KtrA affects it. Although there are several functional and structural data available of KtrAB and its homolog TrkAH, the selectivity of the ion translocation was never thoroughly addressed. The functional characterization of whether KtrAB is a selective ion channel and how selectivity is achieved is in the focus of this thesis. Since selectivity is usually defined by the ion channels’ selectivity filter contained in the pore-forming domain, a particular attention was laid on the ion-translocating subunits KtrB.
KtrB belongs to the superfamily of K+ transporters (SKT). Each KtrB monomer consists of four covalently attached M1-P-M2 motifs, each motif is made of two transmembrane (TM or M) helices that are connected by a pore (P) helix. The four motifs, referred to as domains D1 to D4, are arranged in a pseudo-fourfold symmetry and together form the pore for potassium ion translocation. Each pore contains two structural features thought to be involved in ion selectivity and ion gating. These are the non-canonical selectivity filter and the intramembrane loop. The selectivity filter is localized at the extracellular side of the pore and mostly shaped by the backbone carbonyl groups of the loops connecting the P and M2 helices in each domain. In KtrB, each P-loop contains only one highly conserved glycine residue instead of the classical -TVGYG- signature sequence of a K+ channel. This simple constructed selectivity filter led to the hypothesis that KtrAB would only have low ion selectivity. The intramembrane loop is formed by broken helix D3M2 and is located directly under the selectivity filter. It consists mostly of polar residues and acts as a molecular gate restricting ion fluxes. The intramembrane loop has been shown to be regulated by nucleotide binding to KtrA. Additionally, it could directly or indirectly be affected by Na+ binding. Further, the loop might even be involved in ion selectivity because it presents a physical barrier inside the pore.
To address the ion selectivity of the Ktr system, first, the ion binding specificity of KtrB was investigated. Binding affinities of different cations to KtrB were determined using isothermal titration calorimetry (ITC). For this, KtrB from Vibrio alginolyticus was heterologously produced in and purified from Escherichia coli. 12 L of culture roughly yielded 4 to 8 mg of the functional KtrB dimer in detergent solution. ITC measurements were performed in two different buffers, one choline-Cl-based and one LiCl-based buffer. No differences in the affinity between Na+ (KD = 1.8 mM), K+ (KD = 2.9 mM), Rb+ (KD = 1.9 mM) or Cs+ (KD = 1.6 mM) were detected in the choline-Cl-based buffer; only Li+ did not bind. In contrast, ITC measurements in LiCl-based buffer revealed a significant preference for K+ (KD = 91 µM) over Rb+ (KD = 2.4 mM), Cs+ (KD = 1.7 mM) and particularly Na+ (for which no binding was observed). Similarly, the presence of low millimolar NaCl concentrations in the choline-Cl-based buffer led to a decreased KD value of 260 µM. Hence, small cations, which usually are present in the natural environment, seem to modulate the selectivity filter for a better binding of K+ ions providing K+ selectivity. In fact, the low binding affinities of the other ions could indicate that they do not even bind to the selectivity filter but to the cavity. However, ITC competition experiments showed that all four ions compete for the same or overlapping binding sites, with Rb+ and Cs+ even blocking K+ binding at concentrations 10-fold above their binding affinities. Importantly, at physiological NaCl concentrations of 200 mM, the apparent binding affinity for K+ to KtrB was still 3.5 mM. This suggested that Na+ can also bind to KtrB’s selectivity filter but with a comparably low binding affinity providing an unexpectedly high preference for K+ ions.
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Mesoporous silica has emerged as an enabling formulation for poorly soluble active pharmaceutical ingredients (APIs). Unlike other formulations, mesoporous silica typically does not inhibit precipitation of supersaturated API therefore, a suitable precipitation inhibitor (PI) should be added to increase absorption from the gastrointestinal (GI) tract. However, there is limited research about optimal processes for combining PIs with silica formulations. Typically, the PI is added by simply blending the API-loaded silica mechanically with the selected PI. This has the drawback of an additional blending step and may also not be optimal with regard to release of drug and PI. By contrast, loading PI simultaneously with the API onto mesoporous silica, i.e. co-incorporation, is attractive from both a performance and practical perspective. The aim of this study was to demonstrate the utility of a co-incorporation approach for combining PIs with silica formulations, and to develop a mechanistic rationale for improvement of the performance of silica formulations using the co-incorporation approach. The results indicate that co-incorporating HPMCAS with glibenclamide onto silica significantly improved the extent and duration of drug supersaturation in single-medium and transfer dissolution experiments. Extensive spectroscopic characterization of the formulation revealed that the improved performance was related to the formation of drug-polymer interactions already in the solid state; the immobilization of API-loaded silica on HPMCAS plates, which prevents premature release and precipitation of API; and drug-polymer proximity on disintegration of the formulation, allowing for rapid onset of precipitation inhibition. The data suggests that co-incorporating the PI with the API is appealing for silica formulations from both a practical and formulation performance perspective.
Background: Physiologically-based population pharmacokinetic modeling (popPBPK) coupled with in vitro biopharmaceutics tools such as biorelevant dissolution testing can serve as a powerful tool to establish virtual bioequivalence and set clinically relevant specifications. One of several applications of popPBPK modeling is in the emerging field of virtual bioequivalence (VBE), where it can be used to streamline drug development by implementing model-informed formulation design and to inform regulatory decision-making e.g., with respect to evaluating the possibility of extending BCS-based biowaivers beyond BCS Class I and III compounds in certain cases.
Methods: In this study, Naproxen, a BCS class II weak acid was chosen as the model compound. In vitro biorelevant solubility and dissolution experiments were performed and the resulting data were used as an input to the PBPK model, following a stepwise workflow for the confirmation of the biopharmaceutical parameters. The naproxen PBPK model was developed by implementing a middle-out approach and verified against clinical data obtained from the literature. Once confidence in the performance of the model was achieved, several in vivo dissolution scenarios, based on model-based analysis of the in vitro data, were used to simulate clinical trials in healthy adults. Inter-occasion variability (IOV) was also added to critical physiological parameters and mechanistically propagated through the simulations. The various trials were simulated on a “worst/best case” dissolution scenario and average bioequivalence was assessed according to Cmax, AUC and tmax.
Results: VBE results demonstrated that naproxen products with in vitro dissolution reaching 85% dissolved within 90 minutes would lie comfortably within the bioequivalence limits for Cmax and AUC. Based on the establishment of VBE, a dissolution “safe space” was designed and a clinically relevant specification for naproxen products was proposed. The interplay between formulation-related and drug-specific PK parameters (e.g., t1/2) to predict the in vivo performance was also investigated.
Conclusion: Over a wide range of values, the in vitro dissolution rate is not critical for the clinical performance of naproxen products and therefore naproxen could be eligible for BCS-based biowaivers based on in vitro dissolution under intestinal conditions. This approach may also be applicable to other poorly soluble acidic compounds with long half-lives, providing an opportunity to streamline drug development and regulatory decision-making without putting the patient at a risk.
In the context of data science, data projection and clustering are common procedures. The chosen analysis method is crucial to avoid faulty pattern recognition. It is therefore necessary to know the properties and especially the limitations of projection and clustering algorithms. This report describes a collection of datasets that are grouped together in the Fundamental Clustering and Projection Suite (FCPS). The FCPS contains 10 datasets with the names "Atom", "Chainlink", "EngyTime", "Golfball", "Hepta", "Lsun", "Target", "Tetra", "TwoDiamonds", and "WingNut". Common clustering methods occasionally identified non-existent clusters or assigned data points to the wrong clusters in the FCPS suite. Likewise, common data projection methods could only partially reproduce the data structure correctly on a two-dimensional plane. In conclusion, the FCPS dataset collection addresses general challenges for clustering and projection algorithms such as lack of linear separability, different or small inner class spacing, classes defined by data density rather than data spacing, no cluster structure at all, outliers, or classes that are in contact. This report describes a collection of datasets that are grouped together in the Fundamental Clustering and Projection Suite (FCPS). It is designed to address specific problems of structure discovery in high-dimensional spaces.
Introduction: In the development of bio-enabling formulations, innovative in vivo predictive tools to understand and predict the in vivo performance of such formulations are needed. Etravirine, a non-nucleoside reverse transcriptase inhibitor, is currently marketed as an amorphous solid dispersion (Intelence® tablets). The aims of this study were 1) to investigate and discuss the advantages of using biorelevant in vitro setups in simulating the in vivo performance of Intelence® 100 mg and 200 mg tablets, in the fed state, 2) to build a Physiologically Based Pharmacokinetic (PBPK) model by combining experimental data and literature information with the commercially available in silico software Simcyp® Simulator V17.1 (Certara UK Ltd.), and 3) to discuss the challenges when predicting the in vivo performance of an amorphous solid dispersion and identify the parameters which influence the pharmacokinetics of etravirine most.
Methods: Solubility, dissolution and transfer experiments were performed in various biorelevant media simulating the fasted and fed state environment in the gastrointestinal tract. An in silico PBPK model for healthy volunteers was developed in the Simcyp® Simulator, using in vitro results and data available from the literature as input. The impact of pre- and post-absorptive parameters on the pharmacokinetics of etravirine was investigated using simulations of various scenarios.
Results: In vitro experiments indicated a large effect of naturally occurring solubilizing agents on the solubility of etravirine. Interestingly, supersaturated concentrations of etravirine were observed over the entire duration of dissolution experiments on Intelence® tablets. Coupling the in vitro results with the PBPK model provided the opportunity to investigate two possible absorption scenarios, i.e. with or without implementation of precipitation. The results from the simulations suggested that a scenario in which etravirine does not precipitate is more representative of the in vivo data. On the post-absorptive side, it appears that the concentration dependency of the unbound fraction of etravirine in plasma has a significant effect on etravirine pharmacokinetics.
Conclusions: The present study underlines the importance of combining in vitro and in silico biopharmaceutical tools to advance our knowledge in the field of bio-enabling formulations. Future studies on other bio-enabling formulations can be used to further explore this approach to support rational formulation design as well as robust prediction of clinical outcomes.