Probing interaction of atherogenic lysophosphatidylcholine with functionalized graphene nanosheets: theoretical modelling and experimental validation

FEM simulation of SARS-CoV-2 sensing in single-layer graphene-based bionanosensors

CONTEXT

Airborne pathogens, defined as microscopic organisms, pose significant health risks and can potentially cause a variety of diseases. Given their ability to spread through diverse transmission routes from infected hosts, there is a critical need for accurate monitoring of these pathogens. This study aims to develop a sensor by investigating the vibrational responses of cantilever and bridged boundary-conditioned single-layer graphene (SLG) sheets with microorganisms, specifically SARS-CoV-2, attached at various positions on the sheet. The dynamic analysis of SLG with different boundary conditions and lengths was conducted using the atomistic finite element method (AFEM). Simulations were performed to evaluate SLG's performance as a sensor for biological entities. Altering the sheet's length and the mass of the attached biological object revealed observable frequency differences. This sensor design shows promise for enhancing the detection capabilities of graphene-based technologies for viruses.

METHODS

Finite element method (FEM) analysis is employed to model the sensor's performance and optimize its design parameters. The simulation results highlight the sensor's potential for achieving high sensitivity and rapid detection of SARS-CoV-2. Bridged and cantilever boundary conditions are applied at the ends of the SLG structure by using ANSYS software. Simulations have been conducted to observe how SLG behaves when used as sensors. In armchair graphene, under both boundary conditions, an SLG (5, 5) structure with a length of 50 nm displayed the highest frequency when a SARS-CoV-2 molecule with a mass of 2.6594 × 10-18 g was attached. Conversely, the chiral SLG (17, 1) structure exhibited its lowest frequency at a length of 10 nm. This insight is crucial for grasping detection limits and how factors such as size and boundary conditions influence sensor efficacy. These biosensors hold immense promise in biological sciences and medical applications, revolutionizing patient care by enabling early detection and accurate pathogen identification in clinical settings.

Lysophosphatidylcholine induces oxidative stress and calcium-mediated cell death in human blood platelets

Platelets are essential component of circulation that plays a major role in hemostasis and thrombosis. During activation and its demise, platelets release platelet-derived microvesicles, with lysophosphatidylcholine (LPC) being a prominent component in their lipid composition. LPC, an oxidized low-density lipoprotein, is involved in cellular metabolism, but its higher level is implicated in pathologies like atherosclerosis, diabetes, and inflammatory disorders. Despite this, its impact on platelet function remains relatively unexplored. To address this, we studied LPC's effects on washed human platelets. A multimode plate reader was employed to measure reactive oxygen species and intracellular calcium using H2DCF-DA and Fluo-4-AM, respectively. Flow cytometry was utilized to measure phosphatidylserine expression, mitochondrial membrane potential (ΔΨm), and mitochondrial permeability transition pore (mPTP) formation using FITC-Annexin V, JC-1, and CoCl2/calcein-AM, respectively. Additionally, platelet morphology and its ultrastructure were observed via phase contrast and electron microscopy. Sonoclot and light transmission aggregometry were employed to examine fibrin formation and platelet aggregation, respectively. The findings demonstrate that LPC induced oxidative stress and increased intracellular calcium in platelets, resulting in increased phosphatidylserine expression and reduced ΔΨm. LPC triggered caspase-independent platelet death and mPTP opening via cytosolic and mitochondrial calcium, along with microvesiculation and reduced platelet counts. LPC increased the platelet's size, adopting a balloon-shaped morphology, causing membrane fragmentation and releasing its cellular contents, while inducing a pro-coagulant phenotype with increased fibrin formation and reduced integrin αIIbβ3 activation. Conclusively, this study reveals LPC-induced oxidative stress and calcium-mediated platelet death, necrotic in nature with pro-coagulant properties, potentially impacting inflammation and repair mechanisms during vascular injury.

Bionanosensor utilizing single-layer graphene for the detection of iridovirus

CONTEXT

Iridoviruses, a group of double-stranded DNA viruses, pose a significant threat to various aquatic animals, causing substantial economic losses in aquaculture and impacting ecosystem health. Early and accurate detection of these viruses is crucial for effective disease management and control. Conventional diagnostic methods, including polymerase chain reaction (PCR) and virus isolation, often require specialized laboratories, skilled personnel, and considerable time. This highlights the need for rapid, sensitive, and cost-effective diagnostic tools for iridovirus detection. Single-layer graphene, a two-dimensional material with unique properties like high surface area, excellent electrical conductivity, and chemical stability, has emerged as a versatile platform for biosensing applications. This paper explores the potential of employing single-layer graphene in the development of a bionanosensor for the sensitive and rapid detection of iridoviruses. The aim of the present investigation is to develop a sensor by analyzing the vibrational responses of single-layer graphene sheets (SLGS) with attached microorganisms. Graphene-based virus sensors typically rely on the interaction between the virus and the graphene surface, which lead to changes in the frequency response of graphene. This change is measured and used to detect the presence of the virus. Its high surface-to-volume ratio and sensitivity to changes in its frequency make it a highly sensitive platform for virus detection.

METHODS

We employ finite element method (FEM) analysis to model the sensor's performance and optimize its design parameters. The simulation results highlight the sensor's potential for achieving high sensitivity and rapid detection of iridovirus. Bridged and simply supported with roller support boundary conditions applied at the ends of SLG structure. Simulations have been performed to see how SLG behaves when used as sensors. A single-layer graphene armchair SLG (5,5) with 50-nm length exhibits its highest frequency vibration at 8.66 × 106 Hz, with a mass of 1.2786 Zg. In contrast, a zigzag-SLG with a (18,0) configuration has its lowest frequency vibration at 2.82 × 105 Hz. This aids in comprehending the thresholds of detection and the influence of factors such as size, and boundary conditions on sensor effectiveness. These biosensors can be especially helpful in biological sciences and the medical field since they can considerably improve the treatment of patients, cancer early diagnosis, and pathogen identification when used in clinical environments.

Nanoinformatics based insights into the interaction of blood plasma proteins with carbon based nanomaterials: Implications for biomedical applications

In the past three decades, interest in using carbon-based nanomaterials (CBNs) in biomedical application has witnessed remarkable growth. Despite the rapid advancement, the translation of laboratory experimentation to clinical applications of nanomaterials is one of the major challenges. This might be attributed to poor understanding of bio-nano interface. Arguably, the most significant barrier is the complexity that arises by interplay of several factors like properties of nanomaterial (shape, size, surface chemistry), its interaction with suspending media (surface hydration and dehydration, surface reconstruction and release of free surface energy) and the interaction with biomolecules (conformational change in biomolecules, interaction with membrane and receptor). Tailoring a nanomaterial that minimally interacts with protein and lipids in the medium while effectively acts on target site in biological milieu has been very difficult. Computational methods and artificial intelligence techniques have displayed potential in effectively addressing this problem. Through predictive modelling and deep learning, computer-based methods have demonstrated the capability to create accurate models of interactions between nanoparticles and cell membranes, as well as the uptake of nanomaterials by cells. Computer-based simulations techniques enable these computational models to forecast how making particular alterations to a material's physical and chemical properties could enhance functional aspects, such as the retention of drugs, the process of cellular uptake and biocompatibility. We review the most recent progress regarding the bio-nano interface studies between the plasma proteins and CBNs with a special focus on computational simulations based on molecular dynamics and density functional theory.