Design Rules for the Sequestration of Viruses into Polypeptide Complex Coacervates.

Encapsulation is a strategy that has been used to facilitate the delivery and increase the stability of proteins and viruses. Here, we investigate the encapsulation of viruses via complex coacervation, which is a liquid-liquid phase separation resulting from the complexation of oppositely charged polymers. In particular, we utilized polypeptide-based coacervates and explored the effects of peptide chemistry, chain length, charge patterning, and hydrophobicity to better understand the effects of the coacervating polypeptides on virus incorporation. Our study utilized two nonenveloped viruses, porcine parvovirus (PPV) and human rhinovirus (HRV). PPV has a higher charge density than HRV, and they both appear to be relatively hydrophobic. These viruses were compared to characterize how the charge, hydrophobicity, and patterning of chemistry on the surface of the virus capsid affects encapsulation. Consistent with the electrostatic nature of complex coacervation, our results suggest that electrostatic effects associated with the net charge of both the virus and polypeptide dominated the potential for incorporating the virus into a coacervate, with clustering of charges also playing a significant role. Additionally, the hydrophobicity of a virus appears to determine the degree to which increasing the hydrophobicity of the coacervating peptides can enhance virus uptake. Nonintuitive trends in uptake were observed with regard to both charge patterning and polypeptide chain length, with these parameters having a significant effect on the range of coacervate compositions over which virus incorporation was observed. These results provide insights into biophysical mechanisms, where sequence effects can control the uptake of proteins or viruses into biological condensates and provide insights for use in formulation strategies.

Empty and Full AAV Capsid Charge and Hydrophobicity Differences Measured with Single-Particle AFM.

Adeno-associated virus (AAV) is showing promise as a therapy for diseases that contain a single-gene deletion or mutation. One major scale-up challenge is the removal of empty or non-gene of interest containing AAV capsids. Analytically, the empty capsids can be separated from full capsids using anion exchange chromatography. However, when scaled up to manufacturing, the minute changes in conductivity are difficult to consistently obtain. To better understand the differences in the empty and full AAV capsids, we have developed a single-particle atomic force microscopy (AFM) method to measure the differences in the charge and hydrophobicity of AAV capsids at the single-particle level. The atomic force microscope tip was functionalized with either a charged or a hydrophobic molecule, and the adhesion force between the functionalized atomic force microscope tip and the virus was measured. We measured a change in the charge and hydrophobicity between empty and full AAV2 and AAV8 capsids. The charge and hydrophobicity differences between AAV2 and AAV8 are related to the distribution of charge on the surface and not the total charge. We propose that the presence of nucleic acids inside the capsid causes minor but measurable changes in the capsid structure that lead to measurable surface changes in charge and hydrophobicity.

Multimodal peptide ligand extracts parvovirus from interface in affinity aqueous two-phase system.

Aqueous two-phase systems (ATPS) have found various applications in bioseparations and microencapsulation. The primary goal of this technique is to partition target biomolecules in a preferred phase, rich in one of the phase-forming components. However, there is a lack of understanding of biomolecule behavior at the interface between the two phases. Biomolecule partitioning behavior is studied using tie-lines (TL), where each TL is a group of systems at thermodynamic equilibrium. Across a TL, a system can either have a bulk PEG-rich phase with citrate-rich droplets, or the opposite can occur. We found that porcine parvovirus (PPV) was recovered at a higher amount when PEG was the bulk phase and citrate was in droplets and that the salt and PEG concentrations are high. To improve the recovery, A PEG 10 kDa-peptide conjugate was formed using the multimodal WRW ligand. When WRW was present, less PPV was caught at the interface of the two-phase system, and more was recovered in the PEG-rich phase. While WRW did not significantly increase the PPV recovery in the high TL system, which was found earlier to be optimal for PPV recovery, the peptide did greatly enhance recovery at a lower TL. This lower TL has a lower viscosity and overall system PEG and citrate concentration. The results provide both a method to increase virus recovery in a lower viscosity system, as well as provide interesting thoughts into the interfacial phenomenon and how to recover virus in a phase and not at the interface.

In Vivo Screening Unveils Pervasive RNA-Binding Protein Dependencies in Leukemic Stem Cells and Identifies ELAVL1 as a Therapeutic Target.

Acute myeloid leukemia (AML) is fueled by leukemic stem cells (LSC) whose determinants are challenging to discern from hematopoietic stem cells (HSC) or uncover by approaches focused on general cell properties. We have identified a set of RNA-binding proteins (RBP) selectively enriched in human AML LSCs. Using an in vivo two-step CRISPR-Cas9 screen to assay stem cell functionality, we found 32 RBPs essential for LSCs in MLL-AF9;NrasG12D AML. Loss-of-function approaches targeting key hit RBP ELAVL1 compromised LSC-driven in vivo leukemic reconstitution, and selectively depleted primitive malignant versus healthy cells. Integrative multiomics revealed differentiation, splicing, and mitochondrial metabolism as key features defining the leukemic ELAVL1-mRNA interactome with mitochondrial import protein, TOMM34, being a direct ELAVL1-stabilized target whose repression impairs AML propagation. Altogether, using a stem cell-adapted in vivo CRISPR screen, this work demonstrates pervasive reliance on RBPs as regulators of LSCs and highlights their potential as therapeutic targets in AML. SIGNIFICANCE: LSC-targeted therapies remain a significant unmet need in AML. We developed a stem-cell-adapted in vivo CRISPR screen to identify key LSC drivers. We uncover widespread RNA-binding protein dependencies in LSCs, including ELAVL1, which we identify as a novel therapeutic vulnerability through its regulation of mitochondrial metabolism. This article is highlighted in the In This Issue feature, p. 171.

Fabricating Graphene Oxide/h-BN Metal Insulator Semiconductor Diodes by Nanosecond Laser Irradiation.

To employ graphene's rapid conduction in 2D devices, a heterostructure with a broad bandgap dielectric that is free of traps is required. Within this paradigm, h-BN is a good candidate because of its graphene-like structure and ultrawide bandgap. We show how to make such a heterostructure by irradiating alternating layers of a-C and a-BN film with a nanosecond excimer laser, melting and zone-refining constituent layers in the process. With Raman spectroscopy and ToF-SIMS analyses, we demonstrate this localized zone-refining into phase-pure h-BN and rGO films with distinct Raman vibrational modes and SIMS profile flattening after laser irradiation. Furthermore, in comparing laser-irradiated rGO-Si MS and rGO/h-BN/Si MIS diodes, the MIS diodes exhibit an increased turn-on voltage (4.4 V) and low leakage current. The MIS diode I-V characteristics reveal direct tunneling conduction under low bias and Fowler-Nordheim tunneling in the high-voltage regime, turning the MIS diode ON with improved rectification and current flow. This study sheds light on the nonequilibrium approaches to engineering h-BN and graphene heterostructures for ultrathin field effect transistor device development.

Square wave voltammetric approach to leptin immunosensing and optimization of driving parameters with chemometrics.

Square wave voltammetry serves as an effective analytical means to evaluate antigen-antibody coupling at the solid-liquid interface. Herein, we describe 3-aminopropyltrimethoxysilane (APTMS) induced irreversible immobilization of anti-leptin to micellar gold nanoparticles (AuNPs). Antibodies (Abs) were orthogonally loaded on micellized AuNP assemblies via amino residual groups. The ratio of bound Ab molecules was determined by the Bradford assay. The AuNP/Ab layer modified electrodes with variable antibody surface coverage (∼400 ± 55-200 ± 30 Ab/NP) were analyzed in terms of change in backward, net current (Ip) components. The rate of antigen coupling was found to be consistent with the variation in antibody density as well as the binding affinity. The lowest detection limit was observed at the femtomolar level (0.25 fM/mL) over a wide range of antigen concentration (6.2 ng/mL to 0.12 fg/mL). The variables affecting the epitope-paratope interaction were further optimized using a chemometric approach and a response surface methodology (RSM).

Excimer Laser Patterned Holey Graphene Oxide Films for Nonenzymatic Electrochemical Sensing.

The existence of point defects, holes, and corrugations (macroscopic defects) induces high catalytic potential in graphene and its derivatives. We report a systematic approach for microscopic and macroscopic defect density optimization in excimer laser-induced reduced graphene oxide by varying the laser energy density and pulse number to achieve a record detection limit of 7.15 nM for peroxide sensing. A quantitative estimation of point defect densities was obtained using Raman spectroscopy and confirmed with electrochemical sensing measurements. Laser annealing (LA) at 0.6 J cm-2 led to the formation of highly reduced graphene oxide (GO) by liquid-phase regrowth of molten carbon with the presence of dangling bonds, making it catalytically active. Hall-effect measurements yielded a mobility of ∼200 cm2 V-1 s-1. An additional increase in the number of pulses at 0.6 J cm-2 resulted in deoxygenation through the solid-state route, leading to the formation of holey graphene structure. The average hole size showed a hierarchical increase, with the number of pulses characterized with multiple microscopy techniques, including scanning electron microscopy, atomic force microscopy, and transmission electron microscopy. The exposure of edge sites due to high hole density after 10 pulses supported the formation of proximal diffusion layers, which led to facile mass transfer and improvement in the detection limit from 25.4 mM to 7.15 nM for peroxide sensing. However, LA at 1 J cm-2 with 1 pulse resulted in a high melt lifetime of molten carbon and the formation of GO characterized by a high resistivity of 3 × 10-2 Ω-cm, which was not ideal for sensing applications. The rapid thermal annealing technique using a batch furnace to generate holey graphene results in structure with uneven hole sizes. However, holey graphene formation using the LA technique is scalable with better control over hole size and density. This study will pave the path for cost-efficient and high-performance holey graphene sensors for advanced sensing applications.

A knowledge graph embedding based approach to predict the adverse drug reactions using a deep neural network.

Recently Artificial Intelligence(AI) has not only been used to diagnose the disease but also to cure the disease. Researchers started using AI for drug discovery. Predicting the Adverse Drug Reactions(ADRs) caused by the drug in the manufacturing stage or in the clinical trial stage is a very important problem in drug discovery. ADRs have become a major concern resulting in injuries and also becoming fatal sometimes. Drug safety has gained much importance over the years propelling to the forefront investigation of predicting the ADRs. Although prior studies have queried diverse approaches to predict ADRs, very few were found to be effective. Also, the problem of having fewer reports makes the prediction of ADRs more difficult. To tackle this problem effectively, a novel method has been proposed in this paper. The proposed method is based on Knowledge Graph(KG) embedding. Using the KG embedding, we designed and trained a custom-made Deep Neural Network(DNN) called KGDNN(Knowledge Graph DNN) for predicting the ADRs. A KG has been constructed with 6 types of entities: drugs, ADRs, target proteins, indications, pathways, and genes. Using the Node2Vec algorithm, each node has been embedded into a feature space. Using those embeddings, the ADRs are classified by the KGDNN model. The proposed method has obtained an AUROC score of 0.917 and significantly outperformed the existing methods. Two case studies on drugs causing liver injury and COVID-19 recommended drugs have been performed to illustrate the model efficacy.

Transdermal Polymeric Microneedle Sensing Platform for Fentanyl Detection in Biofluid.

Opioid drugs are extremely potent synthetic analytes, and their abuse is common around the world. Hence, a rapid and point-of-need device is necessary to assess the presence of this compound in body fluid so that a timely countermeasure can be provided to the exposed individuals. Herein, we present an attractive microneedle sensing platform for the detection of the opioid drug fentanyl in real serum samples using an electrochemical detection method. The device contained an array of pyramidal microneedle structures that were integrated with platinum (Pt) and silver (Ag) wires, each with a microcavity opening. The working sensor was modified by graphene ink and subsequently with 4 (3-Butyl-1-imidazolio)-1-butanesulfonate) ionic liquid. The microneedle sensor showed direct oxidation of fentanyl in liquid samples with a detection limit of 27.8 µM by employing a highly sensitive square-wave voltammetry technique. The resulting microneedle-based sensing platform displayed an interference-free fentanyl detection in diluted serum without conceding its sensitivity, stability, and response time. The obtained results revealed that the microneedle sensor holds considerable promise for point-of-need fentanyl detection and opens additional opportunities for detecting substances of abuse in emergencies.

Virus inactivation at moderately low pH varies with virus and buffer properties.

BACKGROUND: Virus inactivation is a critical operation in therapeutic protein manufacturing. Low pH buffers are a widely used strategy to ensure robust enveloped virus clearance. However, the choice of model virus can give varying results in viral clearance studies. Pseudorabies virus (SuHV) or herpes simplex virus-1 (HSV-1) are frequently chosen as model viruses to demonstrate the inactivation for the herpes family. RESULTS: In this study, SuHV, HSV-1, and equine arteritis virus (EAV) were used to compare the inactivation susceptibility at pH 4.0 and 4°C. SuHV and HSV-1 are from the same family, and EAV was chosen as a small, enveloped virus. Glycine, acetate, and citrate buffers at pH 4.0 and varying buffer strengths were studied. The inactivation susceptibility was found to be in the order of SuHV > HSV > EAV. The buffer effectiveness was found to be in the order of citrate > acetate > glycine. The smaller virus, EAV, remained stable and infectious in all the buffer types and compositions studied. CONCLUSION: The variation in inactivation susceptibility of herpes viruses indicated that SuHV and HSV cannot be interchangeably used as a virus model for inactivation studies. Smaller viruses might remain adventitiously infective at moderately low pH.

Enhanced Vapor Transmission Barrier Properties via Silicon-Incorporated Diamond-Like Carbon Coating.

In this study, we describe reducing the moisture vapor transmission through a commercial polymer bag material using a silicon-incorporated diamond-like carbon (Si-DLC) coating that was deposited using plasma-enhanced chemical vapor deposition. The structure of the Si-DLC coating was analyzed using scanning electron microscopy, Raman spectroscopy, X-ray photoelectron spectroscopy, energy-dispersive X-ray spectroscopy, selective area electron diffraction, and electron energy loss spectroscopy. Moisture vapor transmission rate (MVTR) testing was used to understand the moisture transmission barrier properties of Si-DLC-coated polymer bag material; the MVTR values decreased from 10.10 g/m2 24 h for the as-received polymer bag material to 6.31 g/m2 24 h for the Si-DLC-coated polymer bag material. Water stability tests were conducted to understand the resistance of the Si-DLC coatings toward moisture; the results confirmed the stability of Si-DLC coatings in contact with water up to 100 °C for 4 h. A peel-off adhesion test using scotch tape indicated that the good adhesion of the Si-DLC film to the substrate was preserved in contact with water up to 100 °C for 4 h.

Single-Particle Characterization of SARS-CoV-2 Isoelectric Point and Comparison to Variants of Interest.

SARS-CoV-2, the cause of COVID-19, is a new, highly pathogenic coronavirus, which is the third coronavirus to emerge in the past 2 decades and the first to become a global pandemic. The virus has demonstrated itself to be extremely transmissible and deadly. Recent data suggest that a targeted approach is key to mitigating infectivity. Due to the proliferation of cataloged protein and nucleic acid sequences in databases, the function of the nucleic acid, and genetic encoded proteins, we make predictions by simply aligning sequences and exploring their homology. Thus, similar amino acid sequences in a protein usually confer similar biochemical function, even from distal or unrelated organisms. To understand viral transmission and adhesion, it is key to elucidate the structural, surface, and functional properties of each viral protein. This is typically first modeled in highly pathogenic species by exploring folding, hydrophobicity, and isoelectric point (IEP). Recent evidence from viral RNA sequence modeling and protein crystals have been inadequate, which prevent full understanding of the IEP and other viral properties of SARS-CoV-2. We have thus experimentally determined the IEP of SARS-CoV-2. Our findings suggest that for enveloped viruses, such as SARS-CoV-2, estimates of IEP by the amino acid sequence alone may be unreliable. We compared the experimental IEP of SARS-CoV-2 to variants of interest (VOIs) using their amino acid sequence, thus providing a qualitative comparison of the IEP of VOIs.

Advances in laser-assisted conversion of polymeric and graphitic carbon into nanodiamond films.

Nanodiamond (ND) synthesis by nanosecond laser irradiation has sparked tremendous scientific and technological interest. This review describes efforts to obtain cost-effective ND synthesis from polymers and carbon nanotubes (CNT) by the melting route. For polymers, ultraviolet (UV) irradiation triggers intricate photothermal and photochemical processes that result in photochemical degradation, subsequently generating an amorphous carbon film; this process is followed by melting and undercooling of the carbon film at rates exceeding 109K s-1. Multiple laser shots increase the absorption coefficient of PTFE, resulting in the growth of 〈110〉 oriented ND film. Multiple laser shots on CNTs result in pseudo topotactic diamond growth to form a diamond fiber. This technique is useful for fabricating 4-50 nm sized NDs. These NDs can further be employed as seed materials that are used in bulk epitaxial growth of microdiamonds using chemical vapor deposition, particularly for use with non-lattice matched substrates that formerly did not form continuous and adherent films. We also provide insights into biocompatible precursors for ND synthesis such as polybenzimidazole fiber. ND fabrication by UV irradiation of graphitic and polymeric carbon opens up a pathway for preparing selective coatings of polymer-diamond composites, doped nanodiamonds, and graphene composites for quantum computing and biomedical applications.

Osmolyte enhanced aqueous two-phase system for virus purification.

Due to the high variation in viral surface properties, a platform method for virus purification is still lacking. A potential alternative to the high-cost conventional methods is aqueous two-phase systems (ATPSs). However, optimizing virus purification in ATPS requires a large experimental design space, and the optimized systems are generally found to operate at high ATPS component concentrations. The high concentrations capitalize on hydrophobic and electrostatic interactions to obtain high viral particle yields. This study investigated using osmolytes as driving force enhancers to reduce the high concentration of ATPS components while maintaining high yields. The partitioning behavior of porcine parvovirus (PPV), a nonenveloped mammalian virus, and human immunodeficiency virus-like particle (HIV-VLP), a yeast-expressed enveloped VLP, were studied in a polyethylene glycol (PEG) 12 kDa-citrate system. The partitioning of the virus modalities was enhanced by osmoprotectants glycine and betaine, while trimethylamine N-oxide was ineffective for PPV. The increased partitioning to the PEG-rich phase pertained only to viruses, resulting in high virus purification. Recoveries were 100% for infectious PPV and 92% for the HIV-VLP, with high removal of the contaminant proteins and more than 60% DNA removal when glycine was added. The osmolyte-induced ATPS demonstrated a versatile method for virus purification, irrespective of the expression system.

Physiochemical properties of enveloped viruses and arginine dictate inactivation.

BACKGROUND: Therapeutic protein manufacturing would benefit by having an arsenal of ways to inactivate viruses. There have been many publications on the virus inactivation ability of arginine at pH 4.0, but the mechanism of this inactivation is unknown. This study explored how virus structure and solution conditions enhance virus inactivation by arginine and leads to a better understanding of the mechanism of virus inactivation by arginine. RESULTS: Large diameter viruses from the Herpesviridae family (SuHV-1, HSV-1) with loosely packed lipids were highly inactivated by arginine, whereas small diameter, enveloped viruses (equine arteritis virus (EAV) and bovine viral diarrhea virus (BVDV)) with tightly packed lipids were negligibly inactivated by arginine. To increase the inactivation of viruses resistant to arginine, arginine-derivatives and arginine peptides were tested. Derivates and peptides demonstrated that a greater capacity for clustering and added hydrophobicity enhanced virus inactivation. Dynamic light scattering (DLS) and transmission electron microscopy (TEM) detected increases in virus size after arginine exposure, supporting the mechanism of lipid expansion. CONCLUSIONS: Arginine most likely interacts with the lipid membrane to cause inactivation. This is shown by larger viruses being more sensitive to inactivation and expansion of the viral size. The enhancement of arginine inactivation when increased hydrophobic molecules are present or arginine is clustered demonstrates a potential mechanism of how arginine interacts with the lipid membrane.

Prediction of adverse drug reactions using drug convolutional neural networks.

Prediction of Adverse Drug Reactions (ADRs) has been an important aspect of Pharmacovigilance because of its impact in the pharma industry. The standard process of introduction of a new drug into a market involves a lot of clinical trials and tests. This is a tedious and time consuming process and also involves a lot of monetary resources. The faster approval of a drug helps the patients who are in need of the drug. The in silico prediction of Adverse Drug Reactions can help speed up the aforementioned process. The challenges involved are lack of negative data present and predicting ADR from just the chemical structure. Although many models are already available to predict ADR, most of the models use biological activities identifiers, chemical and physical properties in addition to chemical structures of the drugs. But for most of the new drugs to be tested, only chemical structures will be available. The performance of the existing models predicting ADR only using chemical structures is not efficient. Therefore, an efficient prediction of ADRs from just the chemical structure has been proposed in this paper. The proposed method involves a separate model for each ADR, making it a binary classification problem. This paper presents a novel CNN model called Drug Convolutional Neural Network (DCNN) to predict ADRs using chemical structures of the drugs. The performance is measured using the metrics such as Accuracy, Recall, Precision, Specificity, F1 score, AUROC and MCC. The results obtained by the proposed DCNN model outperform the competing models on the SIDER4.1 database in terms of all the metrics. A case study has been performed on a COVID-19 recommended drugs, where the proposed model predicted the ADRs that are well aligned with the observations made by medical professionals using conventional methods.

Thermostabilization of viruses via complex coacervation.

Widespread vaccine coverage for viral diseases could save the lives of millions of people each year. For viral vaccines to be effective, they must be transported and stored in a narrow temperature range of 2-8 °C. If temperatures are not maintained, the vaccine may lose its potency and would no longer be effective in fighting disease; this is called the cold storage problem. Finding a way to thermally stabilize a virus and end the need to transport and store vaccines at refrigeration temperatures will increase access to life-saving vaccines. We explore the use of polymer-rich complex coacervates to stabilize viruses. We have developed a method of encapsulating virus particles in liquid complex coacervates that relies on the electrostatic interaction of viruses with polypeptides. In particular, we tested the incorporation of two model viruses; a non-enveloped porcine parvovirus (PPV) and an enveloped bovine viral diarrhea virus (BVDV) into coacervates formed from poly(lysine) and poly(glutamate). We identified optimal conditions (i.e., the relative amount of the two polypeptides) for virus encapsulation, and trends in this composition matched differences in the isoelectric point of the two viruses. Furthermore, we were able to achieve a ∼103-104-fold concentration of virus into the coacervate phase, such that the level of virus remaining in the bulk solution approached our limit of detection. Lastly, we demonstrated a significant enhancement of the stability of non-enveloped PPV during an accelerated aging study at 60 °C over the course of a week. Our results suggest the potential for using coacervation to aid in the purification and formulation of both enveloped and non-enveloped viruses, and that coacervate-based formulations could help limit the need for cold storage throughout the transportation and storage of vaccines based on non-enveloped viruses.

Changes in Membrane Dielectric Properties of Porcine Kidney Cells Provide Insight into the Antiviral Activity of Glycine.

The ability to monitor the status and progression of viral infections is important for development and screening of new antiviral drugs. Previous research illustrated that the osmolyte glycine (Gly) reduced porcine parvovirus (PPV) infection in porcine kidney (PK-13) cells by stabilizing the capsid protein and preventing virus capsid assembly into viable virus particles. Dielectrophoresis (DEP) was examined herein as a noninvasive, electric field- and frequency-dependent tool for real-time monitoring of PK-13 cell responses to obtain information about membrane barrier functionality and polarization. DEP responses of PK-13 cells were compared to those of PPV-infected cells in the absence and presence of the osmolyte glycine. With infection progression, PK-13 DEP spectra shifted toward lower frequencies, reducing crossover frequencies (fCO). The spherical single-shell model was used to extract PK-13 cell dielectric properties. Upon PPV infection, specific membrane capacitance increased over the time progression of virus attachment, penetration, and capsid protein production and assembly. Following glycine treatment, the DEP spectra displayed attenuated fCO and specific membrane capacitance values shifted back toward uninfected PK-13 cell values. These results suggest that DEP can be used to noninvasively monitor the viral infection cycle and screen antiviral compounds. DEP can augment traditional tools by elucidating membrane polarization changes related to drug mechanisms that interrupt the virus infection cycle.

Virus Isoelectric Point Determination Using Single-Particle Chemical Force Microscopy.

Virus colloidal behavior is governed by the interaction of the viral surface and the surrounding environment. One method to characterize the virus surface charge is the isoelectric point (pI). Traditional determination of virus pI has focused on the bulk characterization of a viral solution. However, virus capsids are extremely heterogeneous, and a single-particle method may give more information on the range of surface charge observed across a population. One method to measure the virus pI is chemical force microscopy (CFM). CFM is a single-particle technique that measures the adhesion force of a functionalized atomic force microscope (AFM) probe and, in this case, a virus covalently bound to a surface. Non-enveloped porcine parvovirus (PPV) and enveloped bovine viral diarrhea virus (BVDV) were used to demonstrate the use of CFM for viral particles with different surface properties. We have validated the CFM to determine the pI of PPV to be 4.8-5.1, which has a known pI value of 5.0 in the literature, and to predict the unknown pI of BVDV to be 4.3-4.5. Bulk measurements, ζ-potential, and aqueous two-phase system (ATPS) cross-partitioning methods were also used to validate the new CFM method for the virus pI. Most methods were in good agreement. CFM can detect the surface charge of viral capsids at a single-particle level and enable the comparison of surface charge between different types of viruses.

Tie line framework to optimize non-enveloped virus recovery in aqueous two-phase systems.

Viral particle purification is a challenge due to the complexity of the broth, the particle size, and the need to maintain virus activity. Aqueous two-phase systems (ATPSs) are a viable alternative for the currently used and expensive downstream processes. This work investigated the purification of two non-enveloped viruses, porcine parvovirus (PPV), and human rhinovirus (HRV) at various ATPS tie lines. A polyethylene glycol (PEG) 12 kDa-citrate system at pH 7 was used to study the behavior of the partitioning on three different thermodynamic tie line lengths (TLLs). It was experimentally determined that increasing the TLL, and therefore increasing the hydrophobic and electrostatic driving forces within the ATPS, facilitated higher virus recoveries in the PEG-rich phase. A maximum of 79% recovery of infectious PPV was found at TLL 36 w/w% and tie line (TL) ratio 0.1. Increased loading of PPV was studied to observe the change in the partitioning behavior and similar trends were observed for all the TLs. Most contaminants remained in the citrate-rich phase at all the chosen TLLs, demonstrating purification of the virus from protein contaminants. Moderate DNA removal was also measured. Net neutral charged HRV was studied to demonstrate the effects of driving forces on neutrally charged viruses. HRV recovery trends remained similar to PPV on each TLL studied, but the values were lower than PPV. Recovery of viral particles in the PEG-rich phase of the PEG-citrate system utilized the difference in the surface hydrophobicity between virus and proteins and showed a direct dependence on the surface charge of each studied virus. The preferential partitioning of the relatively hydrophobic viral particles in the PEG-rich phase supports the hypothesis that both hydrophobic and electrostatic forces govern the purification of viruses in ATPS.