Plasma Proteomic Variables Related to COVID-19 Severity: An Untargeted nLC-MS/MS Investigation

Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) infection leads to a wide range of clinical manifestations and determines the need for personalized and precision medicine. To better understand the biological determinants of this heterogeneity, we explored the plasma proteome of 43 COVID-19 patients with different outcomes by an untargeted liquid chromatography-mass spectrometry approach. The comparison between asymptomatic or pauci-symptomatic subjects (MILDs), and hospitalised patients in need of oxygen support therapy (SEVEREs) highlighted 29 proteins emerged as differentially expressed: 12 overexpressed in MILDs and 17 in SEVEREs. Moreover, a supervised analysis based on a decision-tree recognised three proteins (Fetuin-A, Ig lambda-2chain-C-region, Vitronectin) that are able to robustly discriminate between the two classes independently from the infection stage. In silico functional annotation of the 29 deregulated proteins pinpointed several functions possibly related to the severity; no pathway was associated exclusively to MILDs, while several only to SEVEREs, and some associated to both MILDs and SEVEREs; SARS-CoV-2 signalling pathway was significantly enriched by proteins up-expressed in SEVEREs (SAA1/2, CRP, HP, LRG1) and in MILDs (GSN, HRG). In conclusion, our analysis could provide key information for 'proteomically' defining possible upstream mechanisms and mediators triggering or limiting the domino effect of the immune-related response and characterizing severe exacerbations

Recent approaches to novel antibacterials designed after LPS structure and biochemistry

Lipopolysaccharides (LPSs), which constitute the lipid portion of the outer leaflet of Gram-negative bacteria, are essential for growth, and are responsible for a variety of biological effects associated with Gram-negative sepsis. LPSs are amphiphilic molecules comprising three regions: lipid A, the core region, and a polysaccharide portion; the lipid A was proven to represent the toxic principle of endotoxic active lipopolysaccharides. In addition, it is known that the minimal conserved structure of LPS is the lipophylic oligoasaccharidic structure containing Kdo residues linked to the-LipA moiety. Thus, the design and development of novel antibacterial drugs can focus on different aspects, related to the biosynthesis and chemical features of LPS: 1) Inhibitors of lipid A biosynthesis 2) Inhibitors of Kdo biosynthesis. Both Kdo and Lipid A are needed for the construction of the minimum structural element Kdo2-LipidA, needed for bacterial survival. Any inhibitors acting on the biogenetic pathway of this molecule can act as antibacterial. 3) Antagonists of the interaction between endotoxins and the host receptors: LPS is recognised by the CD14 and the Toll-like receptor (TLR)- 4/MD2 complex, where Lipid A is the crucial moiety in the interaction. Any drug acting as an antagonist of this process can have antisepsis potential. Considerable efforts have been made in this direction to identify natural or synthetic molecules able to interfere with the interaction between LPS and inflammatory cells. This review will highlight recent efforts in the design and biological activity of enzyme inhibitors and antagonist acting on the 3 key aspects outlined above. © 2012 Bentham Science Publishers

Synthesis and characterization of a paramagnetic sialic acid conjugate as probe for magnetic resonance applications

11 páginas, 8 figuras, 4 tablas, 3 esquemas -- PAGS nros. 21-31Magnetic Resonance Imaging (MRI) using paramagnetic systems as contrast agents is receiving increased attention as diagnostic tool in the clinic. At the same time, NMR of paramagnetic systems can also be applied in biochemical fields; for example, the use of Paramagnetic Relaxation Enhancement (PRE) allows structure refinement and the analysis of transient dynamic processes involved in macromolecular complex formation. Herein we report the synthesis and computational characterization of a new DOTA-like sialic acid conjugate, which can be used both in MRI and PRE applications when coordinated to a suitable paramagnetic metalWe gratefully acknowledge financial supports from the University of Milano-Bicocca (FAR2008) and computational facilities from CILEA (Consorzio Interuniversitario Lomabardo per l’Elaborazione Automatica), Programma Operativo Regione Lombardia Ob. 3 Fondo Sociale Europeo 2000–2006, Sovvenzione Globale Progetto Ingenio A0001127/2007 and Consorzio Interuniversitario Nazionale ‘Metodologie e Processi Innovativi di Sintesi’ (C.I.N.M.P.I.S.).Peer reviewe

FiCoS: A fine-grained and coarse-grained GPU-powered deterministic simulator for biochemical networks

Mathematical models of biochemical networks can largely facilitate the comprehension of the mechanisms at the basis of cellular processes, as well as the formulation of hypotheses that can be tested by means of targeted laboratory experiments. However, two issues might hamper the achievement of fruitful outcomes. On the one hand, detailed mechanistic models can involve hundreds or thousands of molecular species and their intermediate complexes, as well as hundreds or thousands of chemical reactions, a situation generally occurring in rule-based modeling. On the other hand, the computational analysis of a model typically requires the execution of a large number of simulations for its calibration or to test the effect of perturbations. As a consequence, the computational capabilities of modern Central Processing Units can be easily overtaken, possibly making the modeling of biochemical networks a worthless or ineffective effort. To the aim of overcoming the limitations of the current state-of-the-art simulation approaches, we present in this paper FiCoS, a novel “black-box” deterministic simulator that effectively realizes both a fine-grained and a coarse-grained parallelization on Graphics Processing Units. In particular, FiCoS exploits two different integration methods, namely, the Dormand–Prince and the Radau IIA, to efficiently solve both non-stiff and stiff systems of coupled Ordinary Differential Equations. We tested the performance of FiCoS against different deterministic simulators, by considering models of increasing size and by running analyses with increasing computational demands. FiCoS was able to dramatically speedup the computations up to 855×, showing to be a promising solution for the simulation and analysis of large-scale models of complex biological processes

Paving the path toward multi-omics approaches in the diagnostic challenges faced in thyroid pathology

Introduction: Despite advancements in diagnostic methods, the classification of indeterminate thyroid nodules still poses diagnostic challenges not only in pre-surgical evaluation but even after histological evaluation of surgical specimens. Proteomics, aided by mass spectrometry and integrated with artificial intelligence and machine learning algorithms, shows great promise in identifying diagnostic markers for thyroid lesions. Areas covered: This review provides in-depth exploration of how proteomics has contributed to the understanding of thyroid pathology. It discusses the technical advancements related to immunohistochemistry, genetic and proteomic techniques, such as mass spectrometry, which have greatly improved sensitivity and spatial resolution up to single-cell level. These improvements allowed the identification of specific protein signatures associated with different types of thyroid lesions. Expert commentary: Among all the proteomics approaches, spatial proteomics stands out due to its unique ability to capture the spatial context of proteins in both cytological and tissue thyroid samples. The integration of multi-layers of molecular information combining spatial proteomics, genomics, immunohistochemistry or metabolomics and the implementation of artificial intelligence and machine learning approaches, represent hugely promising steps forward toward the possibility to uncover intricate relationships and interactions among various molecular components, providing a complete picture of the biological landscape whilst fostering thyroid nodule diagnosis

Synthesis and characterization of a paramagnetic sialic acid conjugate as probe for magnetic resonance applications

11 páginas, 8 figuras, 4 tablas, 3 esquemas -- PAGS nros. 21-31Magnetic Resonance Imaging (MRI) using paramagnetic systems as contrast agents is receiving increased attention as diagnostic tool in the clinic. At the same time, NMR of paramagnetic systems can also be applied in biochemical fields; for example, the use of Paramagnetic Relaxation Enhancement (PRE) allows structure refinement and the analysis of transient dynamic processes involved in macromolecular complex formation. Herein we report the synthesis and computational characterization of a new DOTA-like sialic acid conjugate, which can be used both in MRI and PRE applications when coordinated to a suitable paramagnetic metalWe gratefully acknowledge financial supports from the University of Milano-Bicocca (FAR2008) and computational facilities from CILEA (Consorzio Interuniversitario Lomabardo per l’Elaborazione Automatica), Programma Operativo Regione Lombardia Ob. 3 Fondo Sociale Europeo 2000–2006, Sovvenzione Globale Progetto Ingenio A0001127/2007 and Consorzio Interuniversitario Nazionale ‘Metodologie e Processi Innovativi di Sintesi’ (C.I.N.M.P.I.S.).Peer reviewe

Smart biomaterials: The contribution of glycoscience

Examples of material functionalisation ("biodecoration") with signalling and relevant glycidic scaffolds will be outlined. Recent research concerning the development of smart biomaterials for Tissue Engineering (TE) applications will be considered. © The Royal Society of Chemistry 2012