Non-equivalence of key positively charged residues of the free fatty acid 2 receptor in the recognition and function of agonist versus antagonist ligands

Short chain fatty acids (SCFAs) are produced in the gut by bacterial fermentation of poorly digested carbohydrates. A key mediator of their actions is the G protein-coupled Free Fatty Acid 2 (FFA2) receptor and this has been suggested as a therapeutic target for the treatment of both metabolic and inflammatory diseases. However, a lack of understanding of the molecular determinants dictating how ligands bind to this receptor has hindered development. We have developed a novel radiolabelled FFA2 antagonist in order to probe ligand binding to FFA2 and in combination with mutagenesis and molecular modelling studies define how agonist and antagonist ligands interact with the receptor. Although both agonist and antagonist ligands contain negatively charged carboxylates that interact with two key positively charged arginine residues in transmembrane domains V and VII of FFA2, there are clear differences in how these interactions occur. Specifically, while agonists require interaction with both arginine residues to bind the receptor, antagonists require an interaction with only one of the two. Moreover, different chemical series of antagonist interact preferentially with different arginine residues. A homology model capable of rationalizing these observations was developed and provides a tool that will be invaluable for identifying improved FFA2 agonists and antagonists to further define function and therapeutic opportunities of this receptor

CTCF sites display cell cycle-dependent dynamics in factor binding and nucleosome positioning

CCCTC-binding factor (CTCF) plays a key role in the formation of topologically associating domains (TADs) and loops in interphase. During mitosis TADs are absent, but how TAD formation is dynamically controlled during the cell cycle is not known. Several contradicting observations have been made regarding CTCF binding to mitotic chromatin using both genomics- and microscopy-based techniques. Here, we have used four different assays to address this debate. First, using 5C, we confirmed that TADs and CTCF loops are readily detected in interphase, but absent during prometaphase. Second, ATAC-seq analysis showed that CTCF sites display greatly reduced accessibility and lose the CTCF footprint in prometaphase, suggesting loss of CTCF binding and rearrangement of the nucleosomal array around the binding motif. In contrast, transcription start sites remain accessible in prometaphase, although adjacent nucleosomes can also become repositioned and occupy at least a subset of start sites during mitosis. Third, loss of site-specific CTCF binding was directly demonstrated using CUTandRUN. Histone modifications and histone variants are maintained in mitosis, suggesting a role in bookmarking of active CTCF sites. Finally, live-cell imaging, fluorescence recovery after photobleaching, and single molecule tracking showed that almost all CTCF chromatin binding is lost in prometaphase. Combined, our results demonstrate loss of CTCF binding to CTCF sites during prometaphase and rearrangement of the chromatin landscape around CTCF motifs. This, combined with loss of cohesin, would contribute to the observed loss of TADs and CTCF loops during mitosis and reveals that CTCF sites, key architectural cis-elements, display cell cycle stage-dependent dynamics in factor binding and nucleosome positioning

Predictive glycoengineering of biosimilars using a Markov chain glycosylation model

Biosimilar drugs must closely resemble the pharmacological attributes of innovator products to ensure safety and efficacy to obtain regulatory approval. Glycosylation is one critical quality attribute that must be matched, but it is inherently difficult to control due to the complexity of its biogenesis. This usually implies that costly and time-consuming experimentation is required for clone identification and optimization of biosimilar glycosylation. Here, we describe a computational method that utilizes a Markov model of glycosylation to predict optimal glycoengineering strategies to obtain a specific glycosylation profile with desired properties. The approach uses a genetic algorithm to find the required quantities to perturb glycosylation reaction rates that lead to the best possible match with a given glycosylation profile. Furthermore, the approach can be used to identify cell lines and clones that will require minimal intervention while achieving a glycoprofile that is most similar to the desired profile. Thus, this approach can facilitate biosimilar design by providing computational glycoengineering guidelines that can be generated with a minimal time and cost

Control and femtosecond time-resolved imaging of torsion in a chiral molecule

We study how the combination of long and short laser pulses, can be used to induce torsion in an axially chiral biphenyl derivative (3,5-difluoro-3',5'-dibromo-4'-cyanobiphenyl). A long, with respect to the molecular rotational periods, elliptically polarized laser pulse produces 3D alignment of the molecules, and a linearly polarized short pulse initiates torsion about the stereogenic axis. The torsional motion is monitored in real-time by measuring the dihedral angle using femtosecond time-resolved Coulomb explosion imaging. Within the first 4 picoseconds, torsion occurs with a period of 1.25 picoseconds and an amplitude of 3 degrees in excellent agreement with theoretical calculations. At larger times the quantum states of the molecules describing the torsional motion dephase and an almost isotropic distribution of the dihedral angle is measured. We demonstrate an original application of covariance analysis of two-dimensional ion images to reveal strong correlations between specific ejected ionic fragments from Coulomb explosion. This technique strengthens our interpretation of the experimental data.Comment: 11 pages, 9 figure