Refsgaardmaher9812

obial community structures and diversity at concentrations currently present in the environment, with unknown consequences for the ecosystem. The experimental set-up presented here emphasizes the interest of using natural communities to increase the ecological realism of ecotoxicological studies and to detect potential toxic effects on non-target species.A novel severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) emerged in China in December 2019, causing an ongoing, rapidly spreading global pandemic. Worldwide, vaccination is now expected to provide containment of the novel virus, resulting in an antibody-mediated immunity. To verify this, serological antibody assays qualitatively as well as quantitatively depicting the amount of generated antibodies are of great importance. Currently available test methods are either laboratory based or do not have the ability to indicate an estimation about the immune response. To overcome this, a novel and rapid serological magnetic immunodetection (MID) point-of-care (PoC) assay was developed, with sensitivity and specificity comparable to laboratory-based DiaSorin Liaison SARS-CoV-2 S1/S2 IgG assay. To specifically enrich human antibodies against SARS-CoV-2 in immunofiltration columns (IFCs) from patient sera, a SARS-CoV-2 S1 antigen was transiently produced in plants, purified and immobilized on the IFC. Then, an IgG-specific secondary antibody could bind to the retained antibodies, which was finally labeled using superparamagnetic nanoparticles. Based on frequency magnetic mixing technology (FMMD), the magnetic particles enriched in IFC were detected using a portable FMMD device. The obtained measurement signal correlates with the amount of SARS-CoV-2-specific antibodies in the sera, which could be demonstrated by titer determination. In this study, a MID-based assay could be developed, giving qualitative as well as semiquantitative results of SARS-CoV-2-specific antibody levels in patient's sera within 21 min of assay time with a sensitivity of 97% and a specificity of 92%, based on the analysis of 170 sera from hospitalized patients that were tested using an Food and Drug Administration (FDA)-certified chemiluminescence assay.Phialophora verrucosa is a dematiaceous fungus that causes mainly chromoblastomycosis, but also disseminated infections such as phaeohyphomycosis and mycetoma. These diseases are extremely hard to treat and often refractory to current antifungal therapies. In this work, we have evaluated the effect of 1,10-phenanthroline-5,6-dione (phendione) and its metal-based complexes, [Ag (phendione)2]ClO4 and [Cu(phendione)3](ClO4)2.4H2O, against P. verrucosa, focusing on (i) conidial viability when combined with amphotericin B (AmB); (ii) biofilm formation and disarticulation events; (iii) in vitro interaction with human macrophages; and (iv) in vivo infection of Galleria mellonella larvae. The combination of AmB with each of the test compounds promoted the additive inhibition of P. verrucosa growth, as judged by the checkerboard assay. During the biofilm formation process over polystyrene surface, sub-minimum inhibitory concentrations (MIC) of phendione and its silver(I) and copper(II) complexes were able to reduce biomass and extracellular matrix production. Moreover, a mature biofilm treated with high concentrations of the test compounds diminished biofilm viability in a concentration-dependent manner. Pre-treatment of conidial cells with the test compounds did not alter the percentage of infected THP-1 macrophages; however, [Ag(phendione)2]ClO4 caused a significant reduction in the number of intracellular fungal cells compared to the untreated system. In addition, the killing process was significantly enhanced by post-treatment of infected macrophages with the test compounds. P. verrucosa induced a typically cell density-dependent effect on G. mellonella larvae death after 7 days of infection. Blasticidin S Interestingly, exposure to the silver(I) complex protected the larvae from P. verrucosa infection. Collectively, the results corroborate the promising therapeutic potential of phendione-based drugs against fungal infections, including those caused by P. verrucosa.Flavivirus replication occurs in membranous replication compartments, also known as replication organelles (ROs) derived from the host ER membrane. Our previous study showed that the non-structural (NS) protein 1 (NS1) is the essential factor for RO creation by hydrophobic insertion into the ER membrane. Here, we found that the association of NS1 with the membrane can be facilitated by the electrostatic interaction between NS1 and negatively charged lipids. NS1 binds to a series of negatively charged lipids, including PI4P, and a positively charged residue, R31, located on the membrane-binding face of NS1, plays important roles in this interaction. The NS1 R31E mutation significantly impairs NS1 association with negatively charged membrane and its ER remodeling ability in the cells. To interfere with the electrostatic interaction between NS1 and negatively charged lipids, intracellular phosphatidylinositol phosphates (PIPs) level was downregulated by the overexpression of Sac1 or treatment with PI3K and PI4K inhibitors to attenuate flavivirus replication. Our findings emphasize the importance of electrostatic interaction between NS1 and negatively charged lipids in flavivirus RO formation.

The fungi ITS sequence length dissimilarity, non-specific amplicons, including chimaera formed during Polymerase Chain Reaction (PCR), added to sequencing errors, create bias during similarity clustering and abundance estimation in the downstream analysis. To overcome these challenges, we present a novel approach, Hierarchical Clustering with Kraken (HCK), to classify ITS1 amplicons and Abundance-Base Alternative Approach (ABAA) pipeline to detect and filter non-specific amplicons in fungi metabarcoding sequencing datasets.

We compared the performances of both pipelines against QIIME, KRAKEN, and DADA2 using publicly available fungi ITS mock community datasets and using BLASTn as a reference. We calculated the Precision, Recall, F-score using the True-Positive, False-positive, and False-negative estimation. Alpha diversity (Chao1 and Shannon metrics) was also used to evaluate the diversity estimation of our method.

The analysis shows that ABAA reduced the number of false-positive with all metabarcoding methods tested, and HCK increases precision and recall.