Structural Basis of Nucleotide Selectivity in Pyruvate Kinase

Taguchi A., Nakashima R., Nishino K. Structural Basis of Nucleotide Selectivity in Pyruvate Kinase. Journal of Molecular Biology 436, 168708 (2024); https://doi.org/10.1016/j.jmb.2024.168708.Nucleoside triphosphates are indispensable in numerous biological processes, with enzymes involved in their biogenesis playing pivotal roles in cell proliferation. Pyruvate kinase (PYK), commonly regarded as the terminal glycolytic enzyme that generates ATP in tandem with pyruvate, is also capable of synthesizing a wide range of nucleoside triphosphates from their diphosphate precursors. Despite their substrate promiscuity, some PYKs show preference towards specific nucleotides, suggesting an underlying mechanism for differentiating nucleotide bases. However, the thorough characterization of this mechanism has been hindered by the paucity of nucleotide-bound PYK structures. Here, we present crystal structures of Streptococcus pneumoniae PYK in complex with four different nucleotides. These structures facilitate direct comparison of the protein-nucleotide interactions and offer structural insights into its pronounced selectivity for GTP synthesis. Notably, this selectivity is dependent on a sequence motif in the nucleotide recognition site that is widely present among prokaryotic PYKs, particularly in Firmicutes species. We show that pneumococcal cell growth is significantly impaired when expressing a PYK variant with compromised GTP and UTP synthesis activity, underscoring the importance of PYK in maintaining nucleotide homeostasis. Our findings collectively advance our understanding of PYK biochemistry and prokaryotic metabolism

Functional and structural characterization of Streptococcus pneumoniae pyruvate kinase involved in fosfomycin resistance

Glycolysis is the primary metabolic pathway in the strictly fermentative Streptococcus pneumoniae, which is a major human pathogen associated with antibiotic resistance. Pyruvate kinase (PYK) is the last enzyme in this pathway that catalyzes the production of pyruvate from phosphoenolpyruvate (PEP) and plays a crucial role in controlling carbon flux; however, while S. pneumoniae PYK (SpPYK) is indispensable for growth, surprisingly little is known about its functional properties. Here, we report that compromising mutations in SpPYK confers resistance to the antibiotic fosfomycin, which inhibits the peptidoglycan synthesis enzyme MurA, implying a direct link between PYK and cell wall biogenesis. The crystal structures of SpPYK in the apo and ligand-bound states reveal key interactions that contribute to its conformational change as well as residues responsible for the recognition of PEP and the allosteric activator fructose 1,6-bisphosphate (FBP). Strikingly, FBP binding was observed at a location distinct from previously reported PYK effector binding sites. Furthermore, we show that SpPYK could be engineered to become more responsive to glucose 6-phosphate instead of FBP by sequence and structure-guided mutagenesis of the effector binding site. Together, our work sheds light on the regulatory mechanism of SpPYK and lays the groundwork for antibiotic development that targets this essential enzyme.Taguchi A., Nakashima R., Nishino K.. Functional and structural characterization of Streptococcus pneumoniae pyruvate kinase involved in fosfomycin resistance. Journal of Biological Chemistry 299, 104892 (2023); https://doi.org/10.1016/j.jbc.2023.104892

Rigid microenvironments promote cardiac differentiation of mouse and human embryonic stem cells.

While adult heart muscle is the least regenerative of tissues, embryonic cardiomyocytes are proliferative, with embryonic stem (ES) cells providing an endless reservoir. In addition to secreted factors and cell-cell interactions, the extracellular microenvironment has been shown to play an important role in stem cell lineage specification, and understanding how scaffold elasticity influences cardiac differentiation is crucial to cardiac tissue engineering. Though previous studies have analyzed the role of the matrix elasticity on the function of differentiated cardiomyocytes, whether it affects the induction of cardiomyocytes from pluripotent stem cells is poorly understood. Here, we examined the role of matrix rigidity on the cardiac differentiation using mouse and human ES cells. Culture on polydimethylsiloxane (PDMS) substrates of varied monomer-to-crosslinker ratios revealed that rigid extracellular matrices promote a higher yield of de novo cardiomyocytes from undifferentiated ES cells. Using an genetically modified ES system that allows us to purify differentiated cardiomyocytes by drug selection, we demonstrate that rigid environments induce higher cardiac troponin T expression, beating rate of foci, and expression ratio of adult α- to fetal β- myosin heavy chain in a purified cardiac population. M-mode and mechanical interferometry image analyses demonstrate that these ES-derived cardiomyocytes display functional maturity and synchronization of beating when co-cultured with neonatal cardiomyocytes harvested from a developing embryo. Together, these data identify matrix stiffness as an independent factor that instructs not only the maturation of the already differentiated cardiomyocytes but also the induction and proliferation of cardiomyocytes from undifferentiated progenitors. Manipulation of the stiffness will help direct the production of functional cardiomyocytes en masse from stem cells for regenerative medicine purposes

Interplay of cytokines in the pathophysiology of atopic dermatitis: insights from Murin models and human

The pathogenesis of atopic dermatitis (AD) is understood to be crucially influenced by three main factors: dysregulation of the immune response, barrier dysfunction, and pruritus. In the lesional skin of AD, various innate immune cells, including Th2 cells, type 2 innate lymphoid cells (ILC2s), and basophils, produce Th2 cytokines [interleukin (IL)-4, IL-5, IL-13, IL-31]. Alarmins such as TSLP, IL-25, and IL-33 are also produced by epidermal keratinocytes, amplifying type 2 inflammation. In the chronic phase, not only Th2 cells but also Th22 and Th17 cells increase in number, leading to suppression of filaggrin expression by IL-4, IL-13, and IL-22, which further deteriorates the epidermal barrier function. Dupilumab, which targets IL-4 and IL-13, has shown efficacy in treating moderate to severe AD. Nemolizumab, targeting IL-31RA, effectively reduces pruritus in AD patients. In addition, clinical trials with fezakinumab, targeting IL-22, have demonstrated promising results, particularly in severe AD cases. Conversely, in murine models of AD, several cytokines, initially regarded as promising therapeutic targets, have not demonstrated sufficient efficacy in clinical trials. IL-33 has been identified as a potent activator of immune cells, exacerbating AD in murine models and correlating with disease severity in human patients. However, treatments targeting IL-33 have not shown sufficient efficacy in clinical trials. Similarly, thymic stromal lymphopoietin (TSLP), integral to type 2 immune responses, induces dermatitis in animal models and is elevated in human AD, yet clinical treatments like tezepelumab exhibit limited efficacy. Therapies targeting IL-1α, IL-5, and IL-17 also failed to achieve sufficient efficacy in clinical trials. It has become clear that for treating AD, IL-4, IL-13, and IL-31 are relevant therapeutic targets during the acute phase, while IL-22 emerges as a target in more severe cases. This delineation underscores the necessity of considering distinct pathophysiological aspects and therapeutic targets in AD between mouse models and humans. Consequently, this review delineates the distinct roles of cytokines in the pathogenesis of AD, juxtaposing their significance in human AD from clinical trials against insights gleaned from AD mouse models. This approach will improve our understanding of interspecies variation and facilitate a deeper insight into the pathogenesis of AD in humans

エジプト紅海沿岸のマングローブ林の林分構造

Established mangrove forests along the coastal area of the Arabian Peninsula and African side of the Red Sea are uniquely different from mangrove forests in other parts of the world because of their low biodiversity and harsh habitat of arid and highly saline conditions. Therefore mangrove forests in this area appear in patchy and scattered patterns at mouths of wadi or in sheltered lagoons with rare and irregular flooding. Most of them are pure forests of Avicennia marina, occasionally mixed with Rhizophora mucronata in the southern part of the Red Sea. In this study, we analyze the forest structure of A. marina and discuss the regeneration strategy and the forest dynamics of this unique mangrove species. Three experimental plots of 1000 to 2000 trees/ha were selected from north to south along the Red Sea coast. The highest tree size (6.8m) suggested severe effects of the high salinity of the Red Sea (3.2 to 4.9%) on tree growth. Dense mantle vegetation had developed at the forest edge facing the open sea to protect the forest interior against strong waves and wind. Tree growth was also prevented by severe drought on the landside edge of the forest. All the forests had a dense seedling bank throughout the forest floor, with a very high rate of turnover and regeneration, which seldom occurred in other forests

Automatic evaluation of atlantoaxial subluxation in rheumatoid arthritis by a deep learning model

Background: This work aims to develop a deep learning model, assessing atlantoaxial subluxation (AAS) in rheumatoid arthritis (RA), which can often be ambiguous in clinical practice. Methods: We collected 4691 X-ray images of the cervical spine of the 906 patients with RA. Among these images, 3480 were used for training the deep learning model, 803 were used for validating the model during the training process, and the remaining 408 were used for testing the performance of the trained model. The two-dimensional key points’ detection model of Deep High-Resolution Representation Learning for Human Pose Estimation was adopted as the base convolutional neural network model. The model inferred four coordinates to calculate the atlantodental interval (ADI) and space available for the spinal cord (SAC). Finally, these values were compared with those by clinicians to evaluate the performance of the model. Results: Among the 408 cervical images for testing the performance, the trained model correctly identified the four coordinates in 99.5% of the dataset. The values of ADI and SAC were positively correlated among the model and two clinicians. The sensitivity of AAS diagnosis with ADI or SAC by the model was 0.86 and 0.97 respectively. The specificity of that was 0.57 and 0.5 respectively. Conclusions: We present the development of a deep learning model for the evaluation of cervical lesions of patients with RA. The model was demonstrably shown to be useful for quantitative evaluation.Okita Y., Hirano T., Wang B., et al. Automatic evaluation of atlantoaxial subluxation in rheumatoid arthritis by a deep learning model. Arthritis Research and Therapy 25, 181 (2023); 10.1186/s13075-023-03172-x

Quantification of Hepatic Iron Concentration in Chronic Viral Hepatitis: Usefulness of T2-weighted Single-Shot Spin-Echo Echo-Planar MR Imaging

Objective: To investigate the usefulness of single-shot spin-echo echo-planar imaging (SSEPI) sequence for quantifying mild degree of hepatic iron stores in patients with viral hepatitis. Methods: This retrospective study included 34 patients with chronic viral hepatitis/cirrhosis who had undergone histological investigation and magnetic resonance imaging with T2-weighted gradient-recalled echo sequence (T2-GRE) and diffusion-weighted SSEPI sequence with b-factors of 0 s/mm 2 (T2-EPI), 500 s/mm 2 (DW-EPI-500), and 1000 s/mm 2 (DW-EPI-1000). The correlation between the liver-to-muscle signal intensity ratio, which was generated by regions of interest placed in the liver and paraspinous muscles of each sequence image, and the hepatic iron concentration (mmol/g dry liver), which was assessed by spectrophotometry, was analyzed by linear regression using a spline model. Akaike information criterion (AIC) was used to select the optimal model. Results: Mean 6 standard deviation of the hepatic iron concentration quantified by spectrophotometry was 24.6616.