The number of people living with HIV continues to increase with the current total near 38 million, of which about 26 million are receiving antiretroviral therapy (ART). These treatment regimens are ...highly effective when properly managed, requiring routine viral load monitoring to assess successful viral suppression. Efforts to expand access by decentralizing HIV nucleic acid testing in low- and middle-income countries (LMICs) has been hampered by the cost and complexity of current tests. Sample preparation of blood samples has traditionally relied on cumbersome RNA extraction methods, and it continues to be a key bottleneck for developing low-cost POC nucleic acid tests. We present a microfluidic paper-based analytical device (μPAD) for extracting RNA and detecting HIV in serum, leveraging low-cost materials, simple buffers, and an electric field. We detect HIV virions and MS2 bacteriophage internal control in human serum using a novel lysis and RNase inactivation method, paper-based isotachophoresis (ITP) for RNA extraction, and duplexed reverse transcription recombinase polymerase amplification (RT-RPA) for nucleic acid amplification. We design a specialized ITP system to extract and concentrate RNA, while excluding harsh reagents used for lysis and RNase inactivation. We found the ITP μPAD can extract and purify 5000 HIV RNA copies per mL of serum. We then demonstrate detection of HIV virions and MS2 bacteriophage in human serum within 45-minutes.
An HIV detection assay featuring a low-cost μPAD for electrophoretic RNA extraction and rapid isothermal nucleic acid amplification.
There has been considerable recent progress in designing new proteins using deep-learning methods
. Despite this progress, a general deep-learning framework for protein design that enables solution ...of a wide range of design challenges, including de novo binder design and design of higher-order symmetric architectures, has yet to be described. Diffusion models
have had considerable success in image and language generative modelling but limited success when applied to protein modelling, probably due to the complexity of protein backbone geometry and sequence-structure relationships. Here we show that by fine-tuning the RoseTTAFold structure prediction network on protein structure denoising tasks, we obtain a generative model of protein backbones that achieves outstanding performance on unconditional and topology-constrained protein monomer design, protein binder design, symmetric oligomer design, enzyme active site scaffolding and symmetric motif scaffolding for therapeutic and metal-binding protein design. We demonstrate the power and generality of the method, called RoseTTAFold diffusion (RFdiffusion), by experimentally characterizing the structures and functions of hundreds of designed symmetric assemblies, metal-binding proteins and protein binders. The accuracy of RFdiffusion is confirmed by the cryogenic electron microscopy structure of a designed binder in complex with influenza haemagglutinin that is nearly identical to the design model. In a manner analogous to networks that produce images from user-specified inputs, RFdiffusion enables the design of diverse functional proteins from simple molecular specifications.
The binding and catalytic functions of proteins are generally mediated by a small number of functional residues held in place by the overall protein structure. Here, we describe deep learning ...approaches for scaffolding such functional sites without needing to prespecify the fold or secondary structure of the scaffold. The first approach, "constrained hallucination," optimizes sequences such that their predicted structures contain the desired functional site. The second approach, "inpainting," starts from the functional site and fills in additional sequence and structure to create a viable protein scaffold in a single forward pass through a specifically trained RoseTTAFold network. We use these two methods to design candidate immunogens, receptor traps, metalloproteins, enzymes, and protein-binding proteins and validate the designs using a combination of in silico and experimental tests.
Predicting the effects of mutations on protein function and stability is an outstanding challenge. Here, we assess the performance of a variant of RoseTTAFold jointly trained for sequence and ...structure recovery, RFjoint, for mutation effect prediction. Without any further training, we achieve comparable accuracy in predicting mutation effects for a diverse set of protein families using RFjoint to both another zero‐shot model (MSA Transformer) and a model that requires specific training on a particular protein family for mutation effect prediction (DeepSequence). Thus, although the architecture of RFjoint was developed to address the protein design problem of scaffolding functional motifs, RFjoint acquired an understanding of the mutational landscapes of proteins during model training that is equivalent to that of recently developed large protein language models. The ability to simultaneously reason over protein structure and sequence could enable even more precise mutation effect predictions following supervised training on the task. These results suggest that RFjoint has a quite broad understanding of protein sequence‐structure landscapes, and can be viewed as a joint model for protein sequence and structure which could be broadly useful for protein modeling.
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Asthma impacts over 300 million patients globally, with significant health implications, especially in cases of its allergic subtype. The disease is characterized by a complex ...interplay of airway inflammation and immune responses, often mediated by Th2 cell-related cytokines. In this study, we engineered lipid nanoparticles (LNPs) to specifically deliver therapeutic siRNA via the transferrin receptor to T cells. Strain-promoted azide-alkyne cycloaddition (SPAAC) was employed for the conjugation of transferrin ligands to PEGylated lipids in the LNPs, with the goal of enhancing cellular uptake and gene knockdown. The obtained LNPs exhibited characteristics that make them suitable for pulmonary delivery. Using methods such as nanoparticle tracking analysis (NTA) and enzyme-linked immunosorbent assay (ELISA), we determined the average number of transferrin molecules bound to individual LNPs. Additionally, we found that cellular uptake was ligand-dependent, achieving a GATA3 knockdown of more than 50% in relevant in vitro and ex vivo models. Notably, our findings highlight the limitations inherent to modifying the surface of LNPs, particularly with regard to their targeting capabilities. This work paves the way for future research aimed at optimizing targeted LNPs for the treatment of immunologic diseases such as allergic asthma.
In an ideal world, pharmaceutical drugs would have infinite shelf life, no susceptibility to degradation, chemical reactions or loss of efficacy. In reality, these processes occur, however, making it ...desirable to extend a drugs' shelf life. Nucleic acid-based drugs are most commonly stored as aqueous suspension where they are vulnerable to microbial growth and degradation processes. Drying procedures, such as lyophilization and spray drying, help to reduce the products' residual moisture while increasing the products' shelf life and stability. The present study was designed to evaluate 90 days of storage of spray-dried siRNA-lipid nanoparticles (LNPs) at 4 °C and 25 °C. An updated Onpattro® composition modified with a positively charged helper lipid was used as the LNP carrier system. In an attempt to further reduce the residual moisture of our previously reported formulations, all LNP samples were subjected to a secondary drying step in the spray drying tower for 20 min. The measurement of physicochemical properties of spray-dried and subsequently dried LNPs resulted in sizes of 180 nm, PDI values of 0.1-0.15 and zeta potentials of + 3 mV. Spray drying resulted in residual moisture levels of 3.6-4 % and was reduced by subsequent drying to 2.8-3.1 %. Aerodynamic properties after storage showed discrepancies depending on the storage conditions. MMADs remained at 2.8 µm when stored at 4 °C, whereas an increase to 5 µm at 25 °C was observed. Subsequent drying led to sizes of 3.6-3.8 µm, independent of the storage conditions. Spray-dried LNPs maintained bioactivity resulting in > 95 % protein downregulation and confirming the lack of cytotoxic effects in a lung adenocarcinoma cell line. Furthermore, the spray-dried and subsequently dried LNPs stored for 3 months at 4 °C and 25 °C achieved up to 50 % gene silencing of the house-keeping gene GAPDH after deposition on the mucus layer of Calu-3 cells. This study confirms the stability of spray-dried and subsequently dried LNPs over at least 90 days at 4 °C and 25 °C emphasizing the potential of dry powder inhalation of RNA-loaded LNPs as a therapy option for pulmonary diseases.
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In the field of non-viral drug delivery, polyplexes (PXs) represent an advanced investigated and highly promising tool for the delivery of nucleic acids. Upon encountering ...physiological fluids, they adsorb biological molecules to form a protein corona (PC), that influence PXs biodistribution, transfection efficiencies and targeting abilities. In an effort to understand protein – PX interactions and the effect of PX material on corona composition, we utilized cationic branched 10 kDa polyethyleneimine (b-PEI) and a hydrophobically modified nylon-3 polymer (NM0.2/CP0.8) within this study to develop appropriate methods for PC investigations. A centrifugation procedure for isolating hard corona – PX complexes (PCPXs) from soft corona proteins after incubating the PXs in fetal bovine serum (FBS) for PC formation was successfully optimized and the identification of proteins by a liquid chromatography-tandem mass spectrometry (LC-MS-MS) method clearly demonstrated that the PC composition is affected by the underlying PXs material. With regard to especially interesting functional proteins, which might be able to induce active targeting effects, several candidates could be detected on b-PEI and NM0.2/CP0.8 PXs. These results are of high interest to better understand how the design of PXs impacts the PC composition and subsequently PCPXs-cell interactions to enable precise adjustment of PXs for targeted drug delivery.
RNA interference (RNAi) is an efficient strategy to post‐transcriptionally silence gene expression. While all siRNA drugs on the market target the liver, the lung offers a variety of currently ...undruggable targets, which can potentially be treated with RNA therapeutics. To achieve this goal, the synthesis of poly(spermine acrylamides) (P(SpAA) is reported herein. Polymers are prepared via polymerization of N‐acryloxysuccinimide (NAS) and afterward this active ester is converted into spermine‐based pendant groups. Copolymerizations with decylacrylamide are employed to increase the hydrophobicity of the polymers. After deprotection, polymers show excellent siRNA encapsulation to obtain perfectly sized polyplexes at very low polymer/RNA ratios. In vitro 2D and 3D cell culture, ex vivo and in vivo experiments reveal superior properties of amphiphilic spermine‐copolymers with respect to delivery of siRNA to lung cells in comparison to commonly used lipid‐based transfection agents. In line with the in vitro results, siRNA delivery to human lung explants confirm more efficient gene silencing of protease‐activated receptor 2 (PAR2), a G protein‐coupled receptor involved in fibrosis. This study reveals the importance of the balance between efficient polyplex formation, cellular uptake, gene knockdown, and toxicity for efficient siRNA delivery in vitro, in vivo, and in fibrotic human lung tissue ex vivo.
Amphiphilic, cationic poly(spermine acrylamides) are synthesized via facile radical polymerization of N‐acryloxysuccinimide and N‐decylacrylamide followed by post‐polymerization functionalization with spermine. In vitro 2D and 3D cell culture, ex vivo and in vivo experiments reveal superior properties of spermine‐copolymers in delivery of siRNA to lung cells demonstrating a perfect balance between efficiency and toxicity while outperforming commonly used non‐viral transfection agents.
GATA3 gene silencing in activated T cells displays a promising option to early-on undermine pathological pathways in the disease formation of allergic asthma. The central transcription factor of T ...helper 2 (Th2) cell cytokines IL-4, IL-5, and IL-13 plays a major role in immune and inflammatory cascades underlying asthmatic processes in the airways. Pulmonary delivery of small interfering RNAs (siRNA) to induce GATA3 knockdown within disease related T cells of asthmatic lungs via RNA interference (RNAi) presents an auspicious base to realize this strategy, however, still faces some major hurdles. Main obstacles for successful siRNA delivery in general comprise stability and targeting issues, while in addition the transfection of T cells presents a particularly challenging task itself. In previous studies, we have developed and advanced an eligible siRNA delivery system composed of polyethylenimine (PEI) as polycationic carrier, transferrin (Tf) as targeting ligand and melittin (Mel) as endosomolytic agent. Resulting Tf-Mel-PEI polyplexes exhibited ideal characteristics for targeted siRNA delivery to activated T cells and achieved efficient and sequence-specific gene knockdown in vitro. In this work, the therapeutic potential of this carrier system was evaluated in an optimized cellular model displaying the activated status of asthmatic T cells. Moreover, a suitable siRNA sequence combination was found for effective gene silencing of GATA3. To confirm the translatability of our findings, Tf-Mel-PEI polyplexes were additionally tested ex vivo in activated human precision-cut lung slices (PCLS). Here, the formulation showed a safe profile as well as successful delivery to the lung epithelium with 88% GATA3 silencing in lung explants. These findings support the feasibility of Tf-Mel-PEI as siRNA delivery system for targeted gene knockdown in activated T cells as a potential novel therapy for allergic asthma.
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Many peptide hormones form an α-helix on binding their receptors
, and sensitive methods for their detection could contribute to better clinical management of disease
. De novo protein design can now ...generate binders with high affinity and specificity to structured proteins
. However, the design of interactions between proteins and short peptides with helical propensity is an unmet challenge. Here we describe parametric generation and deep learning-based methods for designing proteins to address this challenge. We show that by extending RFdiffusion
to enable binder design to flexible targets, and to refining input structure models by successive noising and denoising (partial diffusion), picomolar-affinity binders can be generated to helical peptide targets by either refining designs generated with other methods, or completely de novo starting from random noise distributions without any subsequent experimental optimization. The RFdiffusion designs enable the enrichment and subsequent detection of parathyroid hormone and glucagon by mass spectrometry, and the construction of bioluminescence-based protein biosensors. The ability to design binders to conformationally variable targets, and to optimize by partial diffusion both natural and designed proteins, should be broadly useful.
