Could Dermaseptin Analogue be a Competitive Inhibitor for ACE2 Towards Binding with Viral Spike Protein Causing COVID19?: Computational Investigation

International Journal of Peptide Research and Therapeutics - Initial phase of COVID-19 infection is associated with the binding of viral spike protein S1 receptor binding domain (RBD) with the host...     

In Silico Analysis of Prion Protein Mutants: A Comparative Study by Molecular Dynamics Approach

Polymorphisms in the human prion proteins lead to amino acid substitutions by the conversion of PrPC to PrPSc and amyloid formation, resulting in prion diseases such as familial Creutzfeldt–Jakob disease, Gerstmann–Straussler–Scheinker disease and fatal familial insomnia. Cation–π interaction is a non-covalent binding force that plays a significant role in protein stability. Here, we employ a novel approach by combining various in silico tools along with molecular dynamics simulation to provide structural and functional insight into the effect of mutation on the stability and activity of mutant prion proteins. We have investigated impressions of prevalent mutations including 1E1S, 1E1P, 1E1U, 1E1P, 1FKC and 2K1D on the human prion proteins and compared them with wild type. Structural analyses of the models were performed with the aid of molecular dynamics simulation methods. According to our results, frequently occurred mutations were observed in conserved sequences of human prion proteins and the most fluctuation values appear in the 2K1D mutant model at around helix 4 with residues ranging from 190 to 194. Our observations in this study could help to further understand the structural stability of prion proteins.     

Collagenase-3 (MMP-13) deficiency protects C57BL/6 mice from antibody-induced arthritis

Introduction

Matrix metalloproteinases (MMPs) are important in tissue remodelling. Here we investigate the role of collagenase-3 (MMP-13) in antibody-induced arthritis.

Methods

For this study we employed the K/BxN serum-induced arthritis model. Arthritis was induced in C57BL/6 wild type (WT) and MMP-13-deficient (MMP-13^–/–) mice by intraperitoneal injection of 200 μl of K/BxN serum. Arthritis was assessed by measuring the ankle swelling. During the course of the experiments, mice were sacrificed every second day for histological examination of the ankle joints. Ankle sections were evaluated histologically for infiltration of inflammatory cells, pannus tissue formation and bone/cartilage destruction. Semi-quantitative PCR was used to determine MMP-13 expression levels in ankle joints of untreated and K/BxN serum-injected mice.

Results

This study shows that MMP-13 is a regulator of inflammation. We observed increased expression of MMP-13 in ankle joints of WT mice during K/BxN serum-induced arthritis and both K/BxN serum-treated WT and MMP-13^–/– mice developed progressive arthritis with a similar onset. However, MMP-13^–/– mice showed significantly reduced disease over the whole arthritic period. Ankle joints of WT mice showed severe joint destruction with extensive inflammation and erosion of cartilage and bone. In contrast, MMP-13^–/– mice displayed significantly decreased severity of arthritis (50% to 60%) as analyzed by clinical and histological scoring methods.

Conclusions

MMP-13 deficiency acts to suppress the local inflammatory responses. Therefore, MMP-13 has a role in the pathogenesis of arthritis, suggesting MMP-13 is a potential therapeutic target.     

HIV Viremia and T-Cell Activation Differentially Affect the Performance of Glomerular Filtration Rate Equations Based on Creatinine and Cystatin C

Background

Serum creatinine and cystatin C are used as markers of glomerular filtration rate (GFR). The performance of these GFR markers relative to exogenously measured GFR (mGFR) in HIV-positive individuals is not well established.

Methods

We assessed the performance of the chronic kidney disease epidemiology collaboration equations based on serum concentrations of creatinine (eGFR_cr), cystatin C (eGFR_cys) and both biomarkers combined (eGFR_cr-cys) in 187 HIV-positive and 98 HIV-negative participants. Measured GFR was calculated by plasma iohexol clearance. Bias and accuracy were defined as the difference between eGFR and mGFR and the percentage of eGFR observations within 30% of mGFR, respectively. Activated CD4 and CD8 T-cells (CD38+ HLA-DR+) were measured by flow cytometry.

Results

The median mGFR was >100 ml/min/1.73 m² in both groups. All equations tended to be less accurate in HIV-positive than in HIV-negative subjects, with eGFR_cr-cys being the most accurate overall. In the HIV-positive group, eGFR_cys was significantly less accurate and more biased than eGFR_cr and eGFR_{cr_cys}. Additionally eGFR_cys bias and accuracy were strongly associated with use of antiretroviral therapy, HIV RNA suppression, and percentages of activated CD4 or CD8 T-cells. Hepatitis C seropositivity was associated with larger eGFR_cys bias in both HIV-positive and HIV-negative groups. In contrast, eGFR_cr accuracy and bias were not associated with HIV-related factors, T-cell activation, or hepatitis C.

Conclusions

The performance of eGFR_cys relative to mGFR was strongly correlated with HIV treatment factors and markers of T-cell activation, which may limit its usefulness as a GFR marker in this population.     

Mode of Action of the Antimicrobial Peptide D4E1 on Aspergillus flavus

International Journal of Peptide Research and Therapeutics - The synthetic, linear peptide, D4E1, demonstrates antimicrobial activity against a broad spectrum of organisms including the toxigenic...     

Fluxomics with Ratiometric Metabolite Dyes

Today''s major excitement in biology centers on signaling: How can a cell or organism measure the myriad of environmental cues, integrate it, and acclimate to the new conditions? Hormonal signals and second messengers are in the focus of most of these studies, e.g., regulation of glucose transporter GLUT4 cycling by insulin, or regulation of plant growth by auxin or brassinosteroids.^1–3 In comparison, we generally assume that we know almost everything about basic metabolism since it has been studied for many decades; for example we know since the early 80s that allosteric regulation by fructose-2,6-bisphophate plays an important role in regulating glycolysis in plants and animals.⁴ This may be the reason why studies of metabolism appear to be a bit out of fashion. But if we look to other organisms such as E. coli or yeast, we rapidly realize that metabolism is controlled by complex interconnected signaling networks, and that we understand little of these signaling networks in humans and plants.^5,6 As it turns out, the cell registers many metabolites, and flux through the pathways is regulated using complex signaling networks that involve calcium as well as hormones.Key Words: flux, fluxome, glucose, glutamate, phosphate, sucrose, fluorescence resonance energy transfer, biosensorOne of the reasons for the fable for hormones lies in the simple fact that it is easier to observe macroscopic changes, such as changes in the architecture of a plant than to determine metabolite levels, but also here new tools are urgently needed that allow quantification of these small molecules. Visualization of starch levels provided a significant advance, and in combination with mutant screens allowed to identify fundamental components of starch metabolism.^7–9 The biggest advance for the signaling field was the development of advanced chemical and genetically encoded calcium dyes.^10–12 No such dyes are available for hormones or metabolites, as soon as we try to determine levels of metabolites (or signaling molecules), we run into the issues of compartmentation and cellular differences in tissues. Today, the same enzymatic assays used decades ago are still widely used to determine metabolite levels. Although significant advances in chromatography and mass spectrometry based metabolite analysis have moved the study of metabolism to ‘omics’ era, compartmentalization of metabolism still presents a major challenge. Especially the large vacuoles of plant cells are a major obstacle, since even fractionation studies suffer from contamination. Moreover, with the current set of tools it is not possible to determine the dynamic changes in metabolite levels in different subcellular compartments in real time in vivo. Radiotracers have helped a lot to identify and quantify intermediates and to assemble pathways, originally using pulse labeling followed by paper chromatography. Today ¹³C-labeling is used together with mass spectrometry to obtain insights into metabolic flux control.¹³ This tool set for the first time enabled the comparison of mutants and study regulatory networks involved in sugar signaling. While significant, advances in radiotracer experiments do not provide cellular or subcellular information and only limited temporal resolution, they do provide efficient means for studying metabolite fluxes through complex and/or not well-defined pathways. Thus there is a clear need for metabolite specific dyes that can be targeted to subcellular compartments and that would enable flux measurements in response to environmental cues helping to push metabolic research back into the focus of signaling-related biology.In 2002, we developed the first prototype “metabolic dye” FRET sensor for maltose.^14,15 A similar glucose sensor was recently employed for measuring tracer-independent transport of glucose across the ER membrane of liver cells.¹⁶ After resolving some issues such as low signal-to-noise and gene silencing in plants, we are now able to compare glucose levels between cells in an intact root in real time.¹⁷ The parallel development of sucrose and phosphate sensors complements the set of tools, in future experiments providing a comparison of sucrose, phosphate and glucose fluxes in intact tissues with both temporal (below seconds) and spatial resolution (cellular and subcellular).^18,19The first experiments already led to a big surprise: glucose supplied to the root is rapidly taken up and is rapidly metabolized.¹⁷ Roots expressing the highest affinity sensor FLIPglu170n responded to glucose perfusion suggesting that the steady state glucose level in the root is less than 100 nM, the estimated detection limit for this sensor in these first experiments. The first experiments were limited by the mixing kinetics in the bath used for perfusion, while improvement of the chamber now allow for faster for glucose exchange. We estimate that glucose levels fall from a steady state level of approximately 5 mM in the cytosol when perfused with 5 mM glucose to below 100 nM in about three minutes. For the sensor with an affinity of 600 µM the rate of glucose accumulation, which is composed of the various rates that affect the steady state in the cytosol such as metabolism, compartmentation and transport across the plasma membrane, is in the range of 527 ± 77 µM glucose/min and that for glucose removal is 317 ± 37 (Fig. 1; Chaudhuri B, Frommer WB, unpublished). Questions that arise are: Which transport systems drive uptake? How much does the vacuole contribute to the observed flux and steady state levels? Is the capacity of hexokinase at levels below its K_m still sufficient to phosphorylate glucose efficient enough to pull glucose below 100 nM or does hexokinase have different properties in vivo compared to what we know from the purified enzyme? Are there different transporters and enzymes contributing to flux in the low (1–10 mM) and the ultrahigh affinity (low µM) phases? Are there spatial differences in the root? Why do roots take up glucose so efficiently in the first place? The combination of the sensors with information from the expression-LEDs from Birnbaum and Benfey²⁰ and specific knock-out mutants should help answering some of these questions.Open in a separate windowFigure 1Quantitative analysis of glucose flux from an Arabidopsis root expressing FLIPglu-600µΔ13, a FRET sensor for glucose with an affinity of 600 µM. The root of a 10 day-old seedling was placed into a perfusion chamber and perfused with hydroponic medium with or without 5 mM glucose. eCFP was excited and emission was recorded for eCFP and eYFP every 10 seconds (essentially as decsribed in ref. 17). The emission intensities for a region-of-interest were averaged and the emission ratio was determined at the two wavelengths for each image of a time series and plotted on the Y-axis against time on the X-axis. Addition of glucose is indicated.Another big surprise is the dramatic gradient of glucose across the plasma membrane, which has important implications for our understanding of transport processes across the plasma membrane as well as the intracellular membranes.¹⁷ Information about the gradients is relevant in the context of apo- and symplasmic unloading routes in roots²¹ and the contribution of proton-coupled transporters in cellular export.²² It will thus be interesting to follow the extracellular levels using surface-anchored sensors. Now that besides high sensitivity glucose FLIPs¹⁷ we also generated nanosensors for sucrose¹⁹ and phosphate,¹⁸ complementing the similar tool sets for calcium²³ and pH,²⁴ it is possible to compare multiple parameters and to follow flux at different levels and to calibrate against other influences.The improvements of the signal-to-noise ratio of the FRET-based metabolite sensors²⁵ makes the FLIPs a standard tool for every lab interested in measuring ion-, sugar- or amino acid flux in living cells. Since the nanosensors are genetically encoded, they can be used to characterize intracellular fluxes^16,26 in any organism for which transformation protocols have been established. The existing sets of sensors are simple to use, constructs are available through Addgene and Arabidopsis lines from the Arabidopsis Stock Center. Detailed instructions for imaging can be found at: http://carnegiedpb.stanford.edu/research/frommer/research_frommer_protocols.php. These tools will hopefully become a standard system not only for physiological analyses, but in addition provide a new way for high throughput fluxomics studies.