Full-length human Surfactant Protein A inhibits Influenza A Virus infection of A549 lung epithelial cells: a recombinant form containing neck and lectin domains promotes infectivity

Hydrophilic lung surfactant proteins have emerged as key immunomodulators aimed at recognition and clearance of pulmonary pathogens. Surfactant protein A (SP-A) is a surfactant-associated innate immune pattern recognition molecule, which is known to interact with a variety of pathogens, and display anti-microbial effects. SP-A, being carbohydrate pattern recognition molecule, has been suggested to have a wide range of innate immune functions against pathogens. In addition, SP-A can work against respiratory pathogens, including influenza A virus (IAV). Some pandemic pH1N1 strains resist neutralization by SP-A due to differences in the N-glycosylation of viral hemagglutinin (HA). Here, we provide evidence, for the first time, that a recombinant form of human SP-A (rfhSP-A) composed of α-helical neck and carbohydrate recognition domains can actually promote the IAV replication, as observed by an upregulation of M1 expression in lung epithelial cell line, A549, when challenged with pH1N1 and H3N2 IAV subtypes. rfhSP-A (10 μg/ml) bound neuraminidase (NA) (˜60 kDa), matrix protein 1 (M1) (˜25 kDa) and M2 (˜17 kDa) in a calcium dependent manner, as revealed by far western blotting, and direct binding ELISA. However, human full length native SP-A downregulated mRNA expression levels of M1 in A549 cells challenged with IAV subtypes. Furthermore, qPCR analysis showed that transcriptional levels of TNF-α, IL-12, IL-6, IFN-α and RANTES were enhanced following rfhSP-A treatment by both IAV subtypes at 6 h post-IAV infection of A549 lung epithelial cells. In the case of full length SP-A treatment, mRNA expression levels of TNF-α, and IL-6 were downregulated during the mid-to-late stage of IAV infection of A549 cells. Multiplex cytokine/chemokine array revealed enhanced levels of both IL-6 and TNF-α due to rfhSP-A treatment in the case of both IAV subtypes tested, while no significant effect was seen in the case of IL-12. Enhancement of IAV infection of pH1N1 and H3N2 subtypes by truncated rfhSP-A, concomitant with infection inhibition by full-length SP-A, appears to suggest that a complete SP-A molecule is required for protection against IAV. This is in contrast to a recombinant form of trimeric lectin domains of human SP-D (rfhSP-D) that acts as an entry inhibitor of IAV.KACST (14-MED258-20

Photophysical properties of halide perovskite CsPb(Br1-xIx)3 thin films and nanowires

This is an accepted manuscript of an article published by Elsevier in Journal of Luminescence on 26/12/2019, available online: https://doi.org/10.1016/j.jlumin.2019.116985 The accepted version of the publication may differ from the final published version.© 2019 Thin films and nanowires based on lead halide perovskites are promising objects for the design of various optoelectronic devices as well as nano- and microlasers. One of the main advantages of such materials is their absorption and photoluminescence spectra tuning across the visible range via the change in their chemical composition, for instance, by substitution of one halide atom (Br) for another one (I) in the crystal lattice of CsPb(Br1-xIx)3. However, this approach gives materials showing unstable photoluminescence behavior caused by light-induced perovskite phase separation under high-intensity excitation at room temperature. In this work, CsPb(Br1-xIx)3 thin films and nanowires are obtained by chemical vapor anion exchange method from their CsPbBr3 counterparts fabricated by improved wet chemical methods. Spontaneous and stimulated emission from the mixed-halide and pristine bromide samples are studied. Tribromide nanowires exhibit lasing with relatively low thresholds (10–100 μJ/cm2) and high Q-factor of the laser mode up to 3500. The temperature dependence of the photoinitiated phase separation in CsPbBr1.5I1.5 samples is investigated, showing that light-induced phase instability of the mixed-halide nanowires can be suppressed at the somewhat higher temperature (250 K) than the value observed for the thin films having a similar chemical composition. The results obtained are important for the optimization of the functioning of optoelectronic devices based on considered perovskite materials.S.V.M. and A.A.Z. thank the Russian Science Foundation (grant 17-73-20336) for the financial support of study of nanostructures. S.V.M. acknowledges funding from the Ministry of Science and Higher Education of the Russian Federation (project 14.Y26.31.0010). M.V. acknowledges funding from the European Regional Development Fund according to the supported activity ‘Research Projects Implemented by World-class Researcher Groups’ under Measure No. 01.2.2-LMT-K-718, grant No. 01.2.2-LMT-K-718-01-0014. G.H. acknowledges ITMO Fellowship Program.Accepted versio

Seven Golden Rules for heuristic filtering of molecular formulas obtained by accurate mass spectrometry

BACKGROUND: Structure elucidation of unknown small molecules by mass spectrometry is a challenge despite advances in instrumentation. The first crucial step is to obtain correct elemental compositions. In order to automatically constrain the thousands of possible candidate structures, rules need to be developed to select the most likely and chemically correct molecular formulas. RESULTS: An algorithm for filtering molecular formulas is derived from seven heuristic rules: (1) restrictions for the number of elements, (2) LEWIS and SENIOR chemical rules, (3) isotopic patterns, (4) hydrogen/carbon ratios, (5) element ratio of nitrogen, oxygen, phosphor, and sulphur versus carbon, (6) element ratio probabilities and (7) presence of trimethylsilylated compounds. Formulas are ranked according to their isotopic patterns and subsequently constrained by presence in public chemical databases. The seven rules were developed on 68,237 existing molecular formulas and were validated in four experiments. First, 432,968 formulas covering five million PubChem database entries were checked for consistency. Only 0.6% of these compounds did not pass all rules. Next, the rules were shown to effectively reducing the complement all eight billion theoretically possible C, H, N, S, O, P-formulas up to 2000 Da to only 623 million most probable elemental compositions. Thirdly 6,000 pharmaceutical, toxic and natural compounds were selected from DrugBank, TSCA and DNP databases. The correct formulas were retrieved as top hit at 80–99% probability when assuming data acquisition with complete resolution of unique compounds and 5% absolute isotope ratio deviation and 3 ppm mass accuracy. Last, some exemplary compounds were analyzed by Fourier transform ion cyclotron resonance mass spectrometry and by gas chromatography-time of flight mass spectrometry. In each case, the correct formula was ranked as top hit when combining the seven rules with database queries. CONCLUSION: The seven rules enable an automatic exclusion of molecular formulas which are either wrong or which contain unlikely high or low number of elements. The correct molecular formula is assigned with a probability of 98% if the formula exists in a compound database. For truly novel compounds that are not present in databases, the correct formula is found in the first three hits with a probability of 65–81%. Corresponding software and supplemental data are available for downloads from the authors' website

Barnase as a New Therapeutic Agent Triggering Apoptosis in Human Cancer Cells

RNases are currently studied as non-mutagenic alternatives to the harmful DNA-damaging anticancer drugs commonly used in clinical practice. Many mammalian RNases are not potent toxins due to the strong inhibition by ribonuclease inhibitor (RI) presented in the cytoplasm of mammalian cells.In search of new effective anticancer RNases we studied the effects of barnase, a ribonuclease from Bacillus amyloliquefaciens, on human cancer cells. We found that barnase is resistant to RI. In MTT cell viability assay, barnase was cytotoxic to human carcinoma cell lines with half-inhibitory concentrations (IC(50)) ranging from 0.2 to 13 microM and to leukemia cell lines with IC(50) values ranging from 2.4 to 82 microM. Also, we characterized the cytotoxic effects of barnase-based immunoRNase scFv 4D5-dibarnase, which consists of two barnase molecules serially fused to the single-chain variable fragment (scFv) of humanized antibody 4D5 that recognizes the extracellular domain of cancer marker HER2. The scFv 4D5-dibarnase specifically bound to HER2-positive cells and was internalized via receptor-mediated endocytosis. The intracellular localization of internalized scFv 4D5-dibarnase was determined by electronic microscopy. The cytotoxic effect of scFv 4D5-dibarnase on HER2-positive human ovarian carcinoma SKOV-3 cells (IC(50) = 1.8 nM) was three orders of magnitude greater than that of barnase alone. Both barnase and scFv 4D5-dibarnase induced apoptosis in SKOV-3 cells accompanied by internucleosomal chromatin fragmentation, membrane blebbing, the appearance of phosphatidylserine on the outer leaflet of the plasma membrane, and the activation of caspase-3.These results demonstrate that barnase is a potent toxic agent for targeting to cancer cells

The 3D OrbiSIMS—label-free metabolic imaging with subcellular lateral resolution and high mass-resolving power

We report the development of a 3D OrbiSIMS instrument for label-free biomedical imaging. It combines the high spatial resolution of secondary ion mass spectrometry (SIMS; under 200 nm for inorganic species and under 2 μm for biomolecules) with the high mass-resolving power of an Orbitrap (>240,000 at m/z 200). This allows exogenous and endogenous metabolites to be visualized in 3D with subcellular resolution. We imaged the distribution of neurotransmitters—gamma-aminobutyric acid, dopamine and serotonin—with high spectroscopic confidence in the mouse hippocampus. We also putatively annotated and mapped the subcellular localization of 29 sulfoglycosphingolipids and 45 glycerophospholipids, and we confirmed lipid identities with tandem mass spectrometry. We demonstrated single-cell metabolomic profiling using rat alveolar macrophage cells incubated with different concentrations of the drug amiodarone, and we observed that the upregulation of phospholipid species and cholesterol is correlated with the accumulation of amiodarone

Cancer Biomarker Discovery: The Entropic Hallmark

Background: It is a commonly accepted belief that cancer cells modify their transcriptional state during the progression of the disease. We propose that the progression of cancer cells towards malignant phenotypes can be efficiently tracked using high-throughput technologies that follow the gradual changes observed in the gene expression profiles by employing Shannon's mathematical theory of communication. Methods based on Information Theory can then quantify the divergence of cancer cells' transcriptional profiles from those of normally appearing cells of the originating tissues. The relevance of the proposed methods can be evaluated using microarray datasets available in the public domain but the method is in principle applicable to other high-throughput methods. Methodology/Principal Findings: Using melanoma and prostate cancer datasets we illustrate how it is possible to employ Shannon Entropy and the Jensen-Shannon divergence to trace the transcriptional changes progression of the disease. We establish how the variations of these two measures correlate with established biomarkers of cancer progression. The Information Theory measures allow us to identify novel biomarkers for both progressive and relatively more sudden transcriptional changes leading to malignant phenotypes. At the same time, the methodology was able to validate a large number of genes and processes that seem to be implicated in the progression of melanoma and prostate cancer. Conclusions/Significance: We thus present a quantitative guiding rule, a new unifying hallmark of cancer: the cancer cell's transcriptome changes lead to measurable observed transitions of Normalized Shannon Entropy values (as measured by high-throughput technologies). At the same time, tumor cells increment their divergence from the normal tissue profile increasing their disorder via creation of states that we might not directly measure. This unifying hallmark allows, via the the Jensen-Shannon divergence, to identify the arrow of time of the processes from the gene expression profiles, and helps to map the phenotypical and molecular hallmarks of specific cancer subtypes. The deep mathematical basis of the approach allows us to suggest that this principle is, hopefully, of general applicability for other diseases