1H NMR characterization of complexation of Glutathione with silver and aluminum metals in aqueous solution

Metallo-elements have both pharmacological and toxic effects on plants, animals and humans. These are considered as a major public health issue worldwide. In particular, heavy metals such as silver (Ag) and aluminum (Al) are environmentally widespread, and their relative toxicity can lead to numerous pathologies such as nephropathy, cancers, vascular and skin diseases. The goal of this study was to examine the behavioral effects of Ag and Al salts (i.e. Silver nitrate and Aluminum sulfate) on glutathione (GSH), a potent oxidant in biological mixtures. We also aimed to suggest mechanisms of action of thiolate complexed to these metallo-elements in competitive studies with Ellman’s reagent (5,5’-dithiobis(2-nitrobenzoic acid aka ESSE). By proton nuclear magnetic resonance (NMR) spectroscopy, detailed titrations were carried out for these metal thiols interactions in the presence of ESSE in order to elucidate first equilibrium and possible second equilibrium. We found by 1H NMR spectroscopy that GSH binds to Ag and Al, which highlighted possible in-vivo chelation mechanisms of GSH toward these toxic metallo-elements.

Application and utility of alternative methods in isolation of pure cells from forensic biological mixtures in modern-day: a review

Development of genetic profiles from the biological mixtures has remained challenging, although modern-day technologies may help forensic scientists to attain a reliable genetic profile in the identification of the accused. In the case of rape, vaginal swab exhibits usually contain epithelial cells of victims and sperm cells of accused, such samples are more challenging when there is more than one contributor. In such cases, separation of distinct cells from a mixture that includes blood cells, epithelial cells and sperm cells for their single genetic profile is important. In the last ten decades several new techniques were developed and invented for the separation of single cell from the biological mixture that includes differential lysis, laser micro-dissection, cell sorting (FACS), sieve-based filtration, (vi) micro-fluidic devices or immunomagnetic beads cell separation of fresh samples, and the magnetic activated cell sorting (MACS). Out of them, some techniques have been commonly applied for cell separation in forensic biology. Each technique has its own limitation. Some recent studies showed, magnetic activated cell sorting (MACS), laser capture microdissection (LCM), DEPArray technology and fluorescence activated cell sorting (FACS) has proved to be effective in separation of single cell from cell mixtures. Therefore, in this review we have evaluated these four alternative methods and their potential application in the modern-day over the others for the separation of a single cell from the mixture. In this review we also discuss the advantage of these methods and their modern–day applicability and acceptance in the forensic world.

Work Category Affects the Exposure to Allergens and Endotoxins in an Animal Facility Laboratory in Italy: A Personal Air Monitoring Study

Scientists and technicians who work in contact with laboratory animals are exposed to complex biological mixtures from animals, bedding and feed. The main objective of this study was to characterize the exposures to endotoxins and animal allergens in a biomedical research institution located in Central Italy by means of air sampling in the breathing zone of the staff during daily work activities. Forty-two inhalable dust samples were collected for endotoxins and allergens analysis. Filter extracts were analyzed using a Kinetic-QCL LAL kit for endotoxins; ELISA assays were performed for Mus m 1, Rat n 1, Can f 1, Fel d 1 and Equ c 4 detection. Laboratory animal attendants (LAAs) showed endotoxin concentrations significantly higher (4.59 ng/m3) than researchers (0.57 ng/m3), researchers working only in an office (0.56 ng/m3) and technicians (0.37 ng/m3). Endotoxin concentrations exceeding the recommended occupational exposure limit proposed by the Dutch Expert Committee on Occupational Safety were found in the case of two subjects in the animal attendants category. With regards to rat and mouse allergens, a higher average dose was found for mouse than rat allergens. Also for these bio-contaminants, the LAAs are confirmed as the work category at higher risk of exposure (15.85 ng/m3), followed by technicians (10.67 ng/m3), researchers (2.73 ng/m3) and researchers in an office (0.08 ng/m3). Fel d 1 was also detected (average: 0.11 ng/m3) highlighting a passive transport between living and occupational settings. Our data could be useful to improve the control and preventive measures, ensuring lower levels of allergens and endotoxins in animal facilities.

Nucleotide-decorated AuNPs as probes for nucleotide-binding proteins

Gold nanoparticles (AuNPs) decorated with biologically relevant molecules have variety of applications in optical sensing of bioanalytes. Coating AuNPs with small nucleotides produces particles with high stability in water, but functionality-compatible strategies are needed to uncover the full potential of this type of conjugates. Here, we demonstrate that lipoic acid-modified dinucleotides can be used to modify AuNPs surfaces in a controllable manner to produce conjugates that are stable in aqueous buffers and biological mixtures and capable of interacting with nucleotide-binding proteins. Using this strategy we obtained AuNPs decorated with 7-methylguanosine mRNA 5’ cap analogs and showed that they bind cap-specific protein, eIF4E. AuNPs decorated with non-functional dinucleotides also interacted with eIF4E, albeit with lower affinity, suggesting that eIF4E binding to cap-decorated AuNPs is partially mediated by unspecific ionic interactions. This issue was overcome by applying lipoic-acid-Tris conjugate as a charge-neutral diluting molecule. Tris-Lipo-diluted cap-AuNPs conjugates interacted with eIF4E in fully specific manner, enabling design of functional tools. To demonstrate the potential of these conjugates in protein sensing, we designed a two-component eIF4E sensing system consisting of cap-AuNP and 4E-BP1-AuNP conjugates, wherein 4E-BP1 is a short peptide derived from 4E-BP protein that specifically binds eIF4E at a site different to that of the 5’ cap. This system facilitated controlled aggregation, in which eIF4E plays the role of the agent that crosslinks two types of AuNP, thereby inducing a naked-eye visible absorbance redshift. The reported AuNPs-nucleotide conjugation method based on lipoic acid affinity for gold, can be harnessed to obtain other types of nucleotide-functionalized AuNPs, thereby paving the way to studying other nucleotide-binding proteins.

N-Terminomics Strategies for Protease Substrates Profiling

Proteases play a central role in various biochemical pathways catalyzing and regulating key biological events. Proteases catalyze an irreversible post-translational modification called proteolysis by hydrolyzing peptide bonds in proteins. Given the destructive potential of proteolysis, protease activity is tightly regulated. Dysregulation of protease activity has been reported in numerous disease conditions, including cancers, neurodegenerative diseases, inflammatory conditions, cardiovascular diseases, and viral infections. The proteolytic profile of a cell, tissue, or organ is governed by protease activation, activity, and substrate specificity. Thus, identifying protease substrates and proteolytic events under physiological conditions can provide crucial information about how the change in protease regulation can alter the cellular proteolytic landscape. In recent years, mass spectrometry-based techniques called N-terminomics have become instrumental in identifying protease substrates from complex biological mixtures. N-terminomics employs the labeling and enrichment of native and neo-N-termini peptides, generated upon proteolysis followed by mass spectrometry analysis allowing protease substrate profiling directly from biological samples. In this review, we provide a brief overview of N-terminomics techniques, focusing on their strengths, weaknesses, limitations, and providing specific examples where they were successfully employed to identify protease substrates in vivo and under physiological conditions. In addition, we explore the current trends in the protease field and the potential for future developments.

Separation of Chromatographic Co-Eluted Compounds by Clustering and by Functional Data Analysis

Peak overlapping is a common problem in chromatography, mainly in the case of complex biological mixtures, i.e., metabolites. Due to the existence of the phenomenon of co-elution of different compounds with similar chromatographic properties, peak separation becomes challenging. In this paper, two computational methods of separating peaks, applied, for the first time, to large chromatographic datasets, are described, compared, and experimentally validated. The methods lead from raw observations to data that can form inputs for statistical analysis. First, in both methods, data are normalized by the mass of sample, the baseline is removed, retention time alignment is conducted, and detection of peaks is performed. Then, in the first method, clustering is used to separate overlapping peaks, whereas in the second method, functional principal component analysis (FPCA) is applied for the same purpose. Simulated data and experimental results are used as examples to present both methods and to compare them. Real data were obtained in a study of metabolomic changes in barley (Hordeum vulgare) leaves under drought stress. The results suggest that both methods are suitable for separation of overlapping peaks, but the additional advantage of the FPCA is the possibility to assess the variability of individual compounds present within the same peaks of different chromatograms.

Towards structure-focused glycoproteomics

Facilitated by advances in the separation sciences, mass spectrometry and informatics, glycoproteomics, the analysis of intact glycopeptides at scale, has recently matured enabling new insights into the complex glycoproteome. While diverse quantitative glycoproteomics strategies capable of mapping monosaccharide compositions of N- and O-linked glycans to discrete sites of proteins within complex biological mixtures with considerable sensitivity, quantitative accuracy and coverage have become available, developments supporting the advancement of structure-focused glycoproteomics, a recognised frontier in the field, have emerged. Technologies capable of providing site-specific information of the glycan fine structures in a glycoproteome-wide context are indeed necessary to address many pending questions in glycobiology. In this review, we firstly survey the latest glycoproteomics studies published in 2018–2020, their approaches and their findings, and then summarise important technological innovations in structure-focused glycoproteomics. Our review illustrates that while the O-glycoproteome remains comparably under-explored despite the emergence of new O-glycan-selective mucinases and other innovative tools aiding O-glycoproteome profiling, quantitative glycoproteomics is increasingly used to profile the N-glycoproteome to tackle diverse biological questions. Excitingly, new strategies compatible with structure-focused glycoproteomics including novel chemoenzymatic labelling, enrichment, separation, and mass spectrometry-based detection methods are rapidly emerging revealing glycan fine structural details including bisecting GlcNAcylation, core and antenna fucosylation, and sialyl-linkage information with protein site resolution. Glycoproteomics has clearly become a mainstay within the glycosciences that continues to reach a broader community. It transpires that structure-focused glycoproteomics holds a considerable potential to aid our understanding of systems glycobiology and unlock secrets of the glycoproteome in the immediate future.

Laser synthesis of nanomaterials to create a new family of electrochemical microbiosensors

A brief review of modern methods for creating materials for enzymeless microbiosensors intended for express analysis of the content of components of biological fluids, including human blood, has been made. New directions of the synthesis of such materials have been described: laser ablation (PLD) and laser-induced deposition (LCLD). The comparison of laser methods for the synthesis of materials of non-enzymatic microbiosensors with the known methods for creating nanostructured materials has been carried out. Using bimetallic LCLD microtracks as an example, the mechanism of enhancing the electrochemical response of the sensor to the content of glucose and hydrogen peroxide in complex organic and biological mixtures has been shown. It is associated with the creation of nano- and microstructured materials with a highly developed surface, on which there are extended boundaries of the interphase contact zones. This creates numerous activated acid-base centers. They facilitate the transfer of charge from the oxidizing agent to the reducing agent in the solution in contact with the sensor surface. A comparison of the sensory properties of microcomposite bimetallic deposits synthesized by the laser method and their analogs synthesized by traditional methods has been carried out. The advantages of laser methods for the synthesis of microcomposite sensor-active materials are discussed: the miniature size of the sensors, the possibility of using inexpensive metals instead of precious ones, the environmental friendliness of the methods, and the absence of the need to pre-activate the surface

Model of the Fractionation Process of Three- and Four-Component Biological Mixtures in the Gravity Field

The publication describes a simplified method of evaluation of basic parameters of the fractionation process in the gravity field of three- and four-component biological mixtures having physical parame-ters similar to peripheral blood. The description of the method contains the balance of masses and forc-es imposing independent movement of microparticles of different shape in the base fluid matrix. It was also assumed that the biological mixture as an uncompressible quasi-homogeneous liquid can be de-scribed using the basic laws of hydrodynamics. The presented method of evaluation of basic parame-ters of the fractionation process, in relation to complex biological mixtures, together with calculation examples, is a prelude to the extended peripheral blood test within the sedimentation rate of erythro-cytes OB (ESR). Keywords: fractionation of biological mixtures, sedimentation of blood components, mixture fractionation process model, a peripheral blood OB test, fractionation in the gravity field.

MSstatsTMT: Statistical Detection of Differentially Abundant Proteins in Experiments with Isobaric Labeling and Multiple Mixtures

Tandem mass tag (TMT) is a multiplexing technology widely-used in proteomic research. It enables relative quantification of proteins from multiple biological samples in a single MS run with high efficiency and high throughput. However, experiments often require more biological replicates or conditions than can be accommodated by a single run, and involve multiple TMT mixtures and multiple runs. Such larger-scale experiments combine sources of biological and technical variation in patterns that are complex, unique to TMT-based workflows, and challenging for the downstream statistical analysis. These patterns cannot be adequately characterized by statistical methods designed for other technologies, such as label-free proteomics or transcriptomics. This manuscript proposes a general statistical approach for relative protein quantification in MS- based experiments with TMT labeling. It is applicable to experiments with multiple conditions, multiple biological replicate runs and multiple technical replicate runs, and unbalanced designs. It is based on a flexible family of linear mixed-effects models that handle complex patterns of technical artifacts and missing values. The approach is implemented in MSstatsTMT, a freely available open-source R/Bioconductor package compatible with data processing tools such as Proteome Discoverer, MaxQuant, OpenMS, and SpectroMine. Evaluation on a controlled mixture, simulated datasets, and three biological investigations with diverse designs demonstrated that MSstatsTMT balanced the sensitivity and the specificity of detecting differentially abundant proteins, in large-scale experiments with multiple biological mixtures.