Prostaglandin E2 in human gingiva in health and disease and its stimulation by female sex steroids

The levels of prostaglandin E₂ were measured by means of radioimmunoassay in 12 clinically normal and 24 chronically inflamed human gingival tissue homogenates. The average values were found to be 16 and 285 pmol/gm wet weight of the normal and inflamed samples, respectively. Addition of estradiol-17β alone or a mixture of estradiol-17β and progesterone to incubation media containing normal or inflamed gingiva caused a significant increase in the synthesis of endogenous PGE₂. Increased levels of female sex steroids during pregnancy may enhance gingival inflammation.     

A new method to measure nasal impedance in spontaneously breathing adults

As an alternative to standard rhinomanometric methods, we applied forced oscillations at the mouth in five normal subjects and determined their nasal impedance with a novel method involving flow subtraction. Pressure oscillations of constant amplitude were applied at the mouth of a subject both when the nostrils were open and when they were closed with a noseclip. The airflows measured under the two conditions were subtracted to yield the oscillating nasal airflow at the imposed pressure. The resultant pressure-flow relation defined the nasal impedance of the subject. For frequencies between 3 and 15 Hz, the transnasal pressure-flow relation was well described by a linear lumped parameter model consisting of a resistive and inertial element. Nasal resistance obtained with flow subtraction did not differ significantly from control measurements obtained while the subjects performed the Valsalva maneuver. In contrast, nasal inertance obtained with flow subtraction was approximately twice that obtained with the Valsalva method. The difference between inertances may reflect structural changes in nasopharyngeal dimensions that occur with the Valsalva maneuver. We conclude that the mechanical impedance of the nasal passage may be determined during spontaneous breathing from the response to imposed forced oscillations at the mouth. The noninvasive nature of this method suggests that it may be simpler to implement than traditional rhinomanometric methods.     

Accurate prediction of kinase-substrate networks using knowledge graphs

Phosphorylation of specific substrates by protein kinases is a key control mechanism for vital cell-fate decisions and other cellular processes. However, discovering specific kinase-substrate relationships is time-consuming and often rather serendipitous. Computational predictions alleviate these challenges, but the current approaches suffer from limitations like restricted kinome coverage and inaccuracy. They also typically utilise only local features without reflecting broader interaction context. To address these limitations, we have developed an alternative predictive model. It uses statistical relational learning on top of phosphorylation networks interpreted as knowledge graphs, a simple yet robust model for representing networked knowledge. Compared to a representative selection of six existing systems, our model has the highest kinome coverage and produces biologically valid high-confidence predictions not possible with the other tools. Specifically, we have experimentally validated predictions of previously unknown phosphorylations by the LATS1, AKT1, PKA and MST2 kinases in human. Thus, our tool is useful for focusing phosphoproteomic experiments, and facilitates the discovery of new phosphorylation reactions. Our model can be accessed publicly via an easy-to-use web interface (LinkPhinder).     

Protein engineers turned evolutionists

When generating novel tailor-made proteins, protein engineers routinely apply the principles of 'Darwinian' evolution. However, laboratory evolution of proteins also has the potential to test evolutionary theories and reproduce evolutionary scenarios, thus reconstructing putative protein intermediates and providing a glimpse of 'protein fossils'. This commentary describes research at the interface of applied and fundamental molecular evolution, and provides a personal view of how synergy between fundamental and applied experiments indicates novel and more efficient ways of generating new proteins in the laboratory.     

Activity of Six Essential Oils Extracted from Tunisian Plants against Legionella pneumophila

The aim of this study was to investigate the composition of six essential oils extracted from Tunisian plants, i.e., Artemisia herba‐alba Asso , Citrus sinensis (L.) Osbeck , Juniperus phoenicea L., Rosmarinus officinalis L., Ruta graveolens L., and Thymus vulgaris L., and to evaluate their activity against Legionella pneumophila (microdilution assays). Eight Legionella pneumophila strains were studied, including the two well‐known serogroup 1 Lens and Paris strains as controls and six environmental strains isolated from Tunisian spas belonging to serogroups 1, 4, 5, 6, and 8. The essential oils were generally active against L. pneumophila. The activities of the A. herba‐alba, C. sinensis, and R. officinalis essential oils were strain‐dependent, whereas those of the J. phoenicea and T. vulgaris oils, showing the highest anti‐Legionella activities, with minimum inhibitory concentrations (MICs) lower than 0.03 and lower than or equal to 0.07 mg/ml, respectively, were independent of the strains' serogroup. Moreover, the microorganisms treated with T. vulgaris essential oil were shorter, swollen, and less electron‐dense compared to the untreated controls. Isoborneol (20.91%), (1S)‐α‐pinene (18.30%) β‐phellandrene (8.08%), α‐campholenal (7.91%), and α‐phellandrene (7.58%) were the major components isolated from the J. phoenicea oil, while carvacrol (88.50%) was the main compound of the T. vulgaris oil, followed by p‐cymene (7.86%). This study highlighted the potential interest of some essential oils extracted from Tunisian plants as biocides to prevent the Legionella risk.     

Extensive proteomic profiling of the secretome of European community acquired methicillin resistant Staphylococcus aureus clone

European community acquired methicillin resistant Staphylococcus aureus (CA-MRSA) clone remains a striking pathogenic clone spreading in European and Mediterranean countries. Since analysis of the secretome produced from this clone by proteomics could provide a comprehensive picture of both core exoproteins as well as virulence factors, we applied two proteomic approaches, pre-fractionation of proteins on SDS-PAGE followed by in-gel trypsin digestion, and in-solution trypsin-digestion followed by off-line SCX fractionation, both of which were coupled with LC-MS/MS analyses. A total of 174 distinct proteins were identified with a high-confidence. Functional classification of these identified proteins resulted in16.09% of protein synthesis, 13.79% of virulence, 6.89% of toxin, and 17.24% of unknown function. Prediction of their cellular localizations revealed 18.39% in extracellular space, 36.20% in cytoplasm, 5.17% in cytoplasmic membranes, 6.89% in cell wall, 1.14% in multiple localizations, and 32.18% in unknown localization. Among them, 52% proteins were predicted to be secreted through signal peptide-independent pathways. Most notably, the expression of some proteins such as enterotoxins U and B were identified for the first time in this clone.