Advancements in Rapid and Affordable Diagnostic Testing for Respiratory Infectious Diseases: Evaluation of Aptamer Beacon Technology for Rapid and Sensitive Detection of SAR-CoV-2 in Breath Condensate.

The demand for rapid and efficient diagnostic point-of-care tests for respiratory infectious diseases has become increasingly critical in the current landscape. The emphasis on accessibility has been underscored over the past year, making it crucial to have biological components that exhibit fast and accurate kinetics. The foundation for precise, swift, and effective testing relies on the availability of highly responsive biological agents. Two published aptamer DNA sequences designated Song and MSA52 and their truncated internal stem-loop structures were studied for their potential to serve as aptamer beacons for rapid COVID detection. The candidate beacons were covalently labeled with Atto 633 dye attached to their 5' ends and Iowa Black quencher attached to their 3' ends. The whole aptamer structures exhibited the greatest fluorescence signal intensities and higher fluorescence background than their truncated internal stem-loop beacon structures suggesting that the distance between fluorophores and quenchers was greater for the whole aptamer beacon candidates versus the isolated stem-loop structures. Beacon candidates were tested against two heat- or gamma radiation-killed SARS-CoV-2 Washington 1/2020 virus samples and three different COVID spike (S) proteins to test their effectiveness. Despite the higher background fluorescence, the whole aptamer beacons showed better signal-to-noise ratios and were selected for further investigation. Limit of detection (LOD) studies revealed that both the whole Song and whole MSA52 aptamer beacon candidates had a LOD of 9.61 × 103 genome equivalents in phosphate-buffered saline using the red channel of a Promega Quantus™ fluorometer which correlated well with confirmatory spectrofluorometry. Cross-reactivity studies using numerous COVID variants, related coronaviruses, and other common respiratory pathogens suggested greater COVID selectivity for the whole MSA52 versus the whole Song aptamer beacon candidate, indicating promise for specific COVID detection. Importantly, both whole aptamer beacon candidates exhibited very rapid "bind and detect" fluorescence increases within the first 1-2 min of mixing the beacons with killed SARS-CoV-2 viruses in 100 µl samples. Overall, this work illustrates the strong potential for aptamer beacons for rapid, on-site detection and presumptive diagnosis of COVID in breath condensates or other small liquid samples. This research highlights the strong potential of aptamer beacons for addressing the need for fast and convenient diagnostic tools in global health contexts, especially in resource-limited settings.

Contributions from ClpS surface residues in modulating N-terminal peptide binding and their implications for NAAB development.

Numerous technologies are currently in development for use in next-generation protein sequencing platforms. A notable published approach employs fluorescently-tagged binding proteins to identity the N-terminus of immobilized peptides, in-between rounds of digestion. This approach makes use of N-terminal amino acid binder (NAAB) proteins, which would identify amino acids by chemical and shape complementarity. One source of NAABs is the ClpS protein family, which serve to recruit proteins to bacterial proteosomes based on the identity of the N-terminal amino acid. In this study, a Thermosynechococcus vestitus (also known as Thermosynechococcus elongatus) ClpS2 protein was used as the starting point for direct evolution of an NAAB with affinity and specificity for N-terminal leucine. Enriched variants were analyzed and shown to improve the interaction between the ClpS surface and the peptide chain, without increasing promiscuity. Interestingly, interactions were found that were unanticipated which favor different charged residues located at position 5 from the N-terminus of a target peptide.

Backbone NMR assignment of the yeast expressed Fab fragment of the NISTmAb reference antibody.

The monoclonal antibody (mAb) protein class has become a primary therapeutic platform for the production of new life saving drug products. MAbs are comprised of two domains: the antigen-binding fragment (Fab) and crystallizable fragment (Fc). Despite the success in the clinic, NMR assignments of the complete Fab domain have been elusive, in part due to problems in production of properly folded, triply-labeled 2H,13C,15N Fab domain. Here, we report the successful recombinant expression of a triply-labeled Fab domain, derived from the standard IgG1κ known as NISTmAb, in yeast. Using the 2H,13C,15N Fab domain, we assigned 94% of the 1H, 13C, and 15N backbone atoms.

Correlated analytical and functional evaluation of higher order structure perturbations from oxidation of NISTmAb.

The clinical efficacy and safety of protein-based drugs such as monoclonal antibodies (mAbs) rely on the integrity of the protein higher order structure (HOS) during product development, manufacturing, storage, and patient administration. As mAb-based drugs are becoming more prevalent in the treatment of many illnesses, the need to establish metrics for quality attributes of mAb therapeutics through high-resolution techniques is also becoming evident. To this end, here we used a forced degradation method, time-dependent oxidation by hydrogen peroxide, on the model biotherapeutic NISTmAb and evaluated the effects on HOS with orthogonal analytical methods and a functional assay. To monitor the oxidation process, the experimental workflow involved incubation of NISTmAb with hydrogen peroxide in a benchtop nuclear magnetic resonance spectrometer (NMR) that followed the reaction kinetics, in real-time through the water proton transverse relaxation rate R2(1H2O). Aliquots taken at defined time points were further analyzed by high-field 2D 1H-13C methyl correlation fingerprint spectra in parallel with other analytical techniques, including thermal unfolding, size-exclusion chromatography, and surface plasmon resonance, to assess changes in stability, heterogeneity, and binding affinities. The complementary measurement outputs from the different techniques demonstrate the utility of combining NMR with other analytical tools to monitor oxidation kinetics and extract the resulting structural changes in mAbs that are functionally relevant, allowing rigorous assessment of HOS attributes relevant to the efficacy and safety of mAb-based drug products.

Structural Fingerprinting of Antisense Oligonucleotide Therapeutics by Solution NMR Spectroscopy.

PURPOSE: Antisense oligonucleotide (ASO) therapeutics are an emerging class of biopharmaceuticals to treat and prevent diseases, particularly those involving "undruggable" protein targets. Impurities generated throughout the ASO drug manufacturing and formulation pipeline can be detrimental to drug safety and efficacy. Therefore, analytical techniques are needed to rigorously characterize these molecules for quality assurance purposes. METHODS: We demonstrate 1D and 2D nuclear magnetic resonance (NMR) spectroscopy methods that can generate high-resolution structural "fingerprints" of ASOs. RESULTS AND CONCLUSIONS: 1D 1H and 31P measurements are shown to provide rapid initial assessment of the ASO integrity. In particular, a well-resolved pair of 31P signals arising from the 5´-end of the phosphorodiamidate morpholino oligomer (PMO) are sensitive to complex formation and oligomerization state. 2D 1H-1H, 1H-13C, and 1H-15 N experiments, although less sensitive, are further shown to enable resonance assignment, which will allow the tracking of structural changes at high-resolution during the drug development and manufacturing processes. We further anticipate that the described NMR approaches will be broadly applicable to fully formulated ASO therapeutics, including modalities other than PMOs.

Selective C-Terminal Conjugation of Protease-Derived Native Peptides for Proteomic Measurements.

Bottom-up proteomic experiments often require selective conjugation or labeling of the N- and/or C-termini of peptides resulting from proteolytic digestion. For example, techniques based on surface fluorescence imaging are emerging as a promising route to high-throughput protein sequencing but require the generation of peptide surface arrays immobilized through single C-terminal point attachment while leaving the N-terminus free. While several robust approaches are available for selective N-terminal conjugation, it has proven to be much more challenging to implement methods for selective labeling or conjugation of the C-termini that can discriminate between the C-terminal carboxyl group and other carboxyl groups on aspartate and glutamate residues. Further, many approaches based on conjugation through amide bond formation require protection of the N-terminus to avoid unwanted cross-linking reactions. To overcome these challenges, herein, we describe a new strategy for single-point selective immobilization of peptides generated by protease digestion via the C-terminus. The method involves immobilization of peptides via lysine amino acids which are found naturally at the C-terminal end of cleaved peptides from digestions of certain serine endoproteinases, like LysC. This lysine and the N-terminus, the sole two primary amines in the peptide fragments, are chemically reacted with a custom phenyl isothiocyanate (EPITC) that contains an alkyne handle. Subsequent exposure of the double-modified peptides to acid selectively cleaves the N-terminal amino acid, while the modified C-terminus lysine remains unchanged. The alkyne-modified peptides with free N-termini can then be immobilized on an azide surface through standard click chemistry. Using this general approach, surface functionalization is demonstrated using a combination of X-ray photoelectron spectroscopy (XPS), ellipsometry, and atomic force microscopy (AFM).

Interlaboratory Studies Using the NISTmAb to Advance Biopharmaceutical Structural Analytics.

Biopharmaceuticals such as monoclonal antibodies are required to be rigorously characterized using a wide range of analytical methods. Various material properties must be characterized and well controlled to assure that clinically relevant features and critical quality attributes are maintained. A thorough understanding of analytical method performance metrics, particularly emerging methods designed to address measurement gaps, is required to assure methods are appropriate for their intended use in assuring drug safety, stability, and functional activity. To this end, a series of interlaboratory studies have been conducted using NISTmAb, a biopharmaceutical-representative and publicly available monoclonal antibody test material, to report on state-of-the-art method performance, harmonize best practices, and inform on potential gaps in the analytical measurement infrastructure. Reported here is a summary of the study designs, results, and future perspectives revealed from these interlaboratory studies which focused on primary structure, post-translational modifications, and higher order structure measurements currently employed during biopharmaceutical development.

Structural Fingerprinting of siRNA Therapeutics by Solution NMR Spectroscopy.

Nucleic acids are an increasingly popular platform for the development of biotherapeutics to treat a wide variety of illnesses, including diseases where traditional drug development efforts have failed. To date, there are 14 short oligonucleotide therapeutics and 2 messenger RNA (mRNA) vaccines approved by the U.S. Food and Drug Administration (FDA), which demonstrates the potential of nucleic acids as a platform for the development of safe and effective medicines and vaccines. Despite the increasing popularity of nucleic acid-based drugs, there has been a paucity of high-resolution structural techniques applied to rigorously characterize these molecules during drug development. Here, we present application of nuclear magnetic resonance (NMR) methods to structurally "fingerprint" short oligonucleotide therapeutics at natural isotope abundance under full formulation conditions. The NMR methods described herein leverage signals arising from the native structural features of nucleic acids, including imino, aromatic, and ribose resonances, in addition to non-native chemistries, such as 2'-fluoro (2'-F), 2'-O-methyl (2'-OMe), and phosphorothioate (PS) modifications, introduced during drug development. We demonstrate the utility of the NMR methods to structurally "fingerprint" a model short interfering RNA (siRNA) and a sample that simulated the drug product Givosiran. We anticipate broad applicability of the NMR methods to other nucleic acid-based therapeutics due to the generalized nature of the approach and ability to monitor many quality attributes simultaneously.

Real-world management of non-alcoholic steatohepatitis differs from clinical practice guideline recommendations and across regions.

BACKGROUND & AIMS: Despite availability of diagnostic and management reference guidelines outlining standard of care for patients with non-alcoholic fatty liver disease (NAFLD) and non-alcoholic steatohepatitis (NASH), national and regional guidelines are lacking, resulting in variations in patient management between regions. We retrospectively analyzed patient characteristics and management data from the Adelphi Real World NASH Disease Specific Programme™ for patients with NASH in the EU5, Canada, and the Middle East to identify gaps between real-world practice and that advocated by reference guidelines, irrespective of clinician awareness or consultation of guidelines. METHODS: We performed an analysis of physicians (hepatologists, gastroenterologists, diabetologists) and their patients diagnosed with NASH. Physicians completed patient record forms for the next 5 consulting patients, collecting information on patient care, including diagnosis and disease management. RESULTS: A total of 429 physicians provided data for 2,267 patients with NASH (EU5, n = 1,844; Canada, n = 130; Middle East, n = 293). Patient age, physician-defined fibrosis stage, comorbidities and symptoms, and diagnostic testing practices highlighted statistically significant differences across regions. Substantial disconnects between reference guidelines and real-world practice were observed. Use of liver function tests, non-invasive tests (e.g. ultrasound and transient elastography), and tests to exclude other conditions was suboptimal. Although lifestyle advice was widely provided, patients were less commonly referred to diet, exercise, and lifestyle specialists. Two-thirds of patients were receiving off-label treatment for NASH or associated underlying conditions with the aim of improving NASH, most commonly statins, metformin, and vitamin E. CONCLUSION: Real-world NASH management approaches differ across regions and from proposed standard of care represented by reference multidisciplinary guidelines. Establishment and awareness of, and adherence to regional and national guidelines may improve identification and management of patients with NASH and potentially improve outcomes in this population. LAY SUMMARY: Although reference guidelines are available to guide the management of patients with NASH, these are not widely used and there is a lack of national guidelines. Our study shows how clinical practice in the EU, Canada, and Middle East differs from proposed standard of care, particularly relating to how patients are diagnosed and treated. Wider establishment of, awareness of, and reference to guidelines may improve how physicians identify and manage patients with NASH.

Highly conserved s2m element of SARS-CoV-2 dimerizes via a kissing complex and interacts with host miRNA-1307-3p.

The ongoing COVID-19 pandemic highlights the necessity for a more fundamental understanding of the coronavirus life cycle. The causative agent of the disease, SARS-CoV-2, is being studied extensively from a structural standpoint in order to gain insight into key molecular mechanisms required for its survival. Contained within the untranslated regions of the SARS-CoV-2 genome are various conserved stem-loop elements that are believed to function in RNA replication, viral protein translation, and discontinuous transcription. While the majority of these regions are variable in sequence, a 41-nucleotide s2m element within the genome 3' untranslated region is highly conserved among coronaviruses and three other viral families. In this study, we demonstrate that the SARS-CoV-2 s2m element dimerizes by forming an intermediate homodimeric kissing complex structure that is subsequently converted to a thermodynamically stable duplex conformation. This process is aided by the viral nucleocapsid protein, potentially indicating a role in mediating genome dimerization. Furthermore, we demonstrate that the s2m element interacts with multiple copies of host cellular microRNA (miRNA) 1307-3p. Taken together, our results highlight the potential significance of the dimer structures formed by the s2m element in key biological processes and implicate the motif as a possible therapeutic drug target for COVID-19 and other coronavirus-related diseases.

The emerging landscape of single-molecule protein sequencing technologies.

Single-cell profiling methods have had a profound impact on the understanding of cellular heterogeneity. While genomes and transcriptomes can be explored at the single-cell level, single-cell profiling of proteomes is not yet established. Here we describe new single-molecule protein sequencing and identification technologies alongside innovations in mass spectrometry that will eventually enable broad sequence coverage in single-cell profiling. These technologies will in turn facilitate biological discovery and open new avenues for ultrasensitive disease diagnostics.

Principal Component Analysis of 1D 1H Diffusion Edited NMR Spectra of Protein Therapeutics.

The one-dimensional (1D) diffusion edited proton NMR method, Protein Fingerprint by Lineshape Enhancement (PROFILE) has been demonstrated to be suitable for higher order structure (HOS) characterization of protein therapeutics including monoclonal antibodies. Recent reports in the literature have demonstrated its advantages for HOS characterization over traditional methods such as circular dichroism and Fourier-transform infrared spectroscopy. Previously, we have demonstrated that the PROFILE method is complementary with high resolution 2D methyl correlated NMR methods and how both may be deployed as a multi-modal platform to further the utility of NMR for HOS characterization. A major limitation of the PROFILE method remains its need for high signal to noise data due to its reliance on convolution difference processing and linear correlation metrics to assess spectral similarity. Here we present an alternative method for analyzing 1D diffusion edited spectra, which overcomes this limitation by using nonlinear iterative partial least squares (NIPALS) principal component analysis, and which we dub PROtein Fingerprint Observed Using NIPALS Decomposition (PROFOUND). We demonstrate that results from the PROFOUND method are robust with respect to instrument, operator and in the presence of high experimental noise and how it may be employed to provide quantitative assessment of spectral similarity.

Grand Challenges in Pharmaceutical Research Series: Ridding the Cold Chain for Biologics.

Biologics are complex pharmaceuticals that include formulated proteins, plasma products, vaccines, cell and gene therapy products, and biological tissues. These products are fragile and typically require cold chain for their delivery and storage. Delivering biologics, while maintaining the cold chain, whether standard (2°C to 8°C) or deepfreeze (as cold as -70°C), requires extensive infrastructure that is expensive to build and maintain. This poses a huge challenge to equitable healthcare delivery, especially during a global pandemic. Even when the infrastructure is in place, breaches of the cold chain are common. Such breaches may damage the product, making therapeutics and vaccines ineffective or even harmful. Rather than strengthening the cold chain through building more infrastructure and imposing more stringent guidelines, we suggest that money and effort are best spent on making the cold chain unnecessary for biologics delivery and storage. To meet this grand challenge in pharmaceutical research, we highlight areas where innovations are needed in the design, formulation and biomanufacturing of biologics, including point-of-care manufacturing and inspection. These technological innovations would rely on fundamental advances in our understanding of biomolecules and cells.

Principal component analysis for automated classification of 2D spectra and interferograms of protein therapeutics: influence of noise, reconstruction details, and data preparation.

Protein therapeutics have numerous critical quality attributes (CQA) that must be evaluated to ensure safety and efficacy, including the requirement to adopt and retain the correct three-dimensional fold without forming unintended aggregates. Therefore, the ability to monitor protein higher order structure (HOS) can be valuable throughout the lifecycle of a protein therapeutic, from development to manufacture. 2D NMR has been introduced as a robust and precise tool to assess the HOS of a protein biotherapeutic. A common use case is to decide whether two groups of spectra are substantially different, as an indicator of difference in HOS. We demonstrate a quantitative use of principal component analysis (PCA) scores to perform this decision-making, and demonstrate the effect of acquisition and processing details on class separation using samples of NISTmAb monoclonal antibody Reference Material subjected to two different oxidative stress protocols. The work introduces an approach to computing similarity from PCA scores based upon the technique of histogram intersection, a method originally developed for retrieval of images from large databases. Results show that class separation can be robust with respect to random noise, reconstruction method, and analysis region selection. By contrast, details such as baseline distortion can have a pronounced effect, and so must be controlled carefully. Since the classification approach can be performed without the need to identify peaks, results suggest that it is possible to use even more efficient measurement strategies that do not produce spectra that can be analyzed visually, but nevertheless allow useful decision-making that is objective and automated.

Leveraging nature's biomolecular designs in next-generation protein sequencing reagent development.

Next-generation approaches for protein sequencing are now emerging that could have the potential to revolutionize the field in proteomics. One such sequencing method involves fluorescence-based imaging of immobilized peptides in which the N-terminal amino acid of a polypeptide is readout sequentially by a series of fluorescently labeled biomolecules. When selectively bound to a specific N-terminal amino acid, the NAAB (N-terminal amino acid binder) affinity reagent identifies the amino acid through its associated fluorescence tag. A key technical challenge in implementing this fluoro-sequencing approach is the need to develop NAAB affinity reagents with the high affinity and selectivity for specific N-terminal amino acids required for this biotechnology application. One approach to develop such a NAAB affinity reagent is to leverage naturally occurring biomolecules that bind amino acids and/or peptides. Here, we describe several candidate biomolecules that could be considered for this purpose and discuss the potential for developability of each. Key points • Next-generation sequencing methods are emerging that could revolutionize proteomics. • Sequential readout of N-terminal amino acids by fluorescent-tagged affinity reagents. • Native peptide/amino acid binders can be engineered into affinity reagents. • Protein size and structure contribute to feasibility of reagent developability.

Assessment of the Higher-Order Structure of Formulated Monoclonal Antibody Therapeutics by 2D Methyl Correlated NMR and Principal Component Analysis.

Characterization of the higher-order structure (HOS) of protein therapeutics, and in particular of monoclonal antibodies, by 2D 1 H-13 C methyl correlated NMR has been demonstrated as precise and robust. Such characterization can be greatly enhanced when collections of spectra are analyzed using multivariate approaches such as principal component analysis (PCA), allowing for the detection and identification of small structural differences in drug substance that may otherwise fall below the limit of detection of conventional spectral analysis. A major limitation to this approach is the presence of aliphatic signals from formulation or excipient components, which result in spectral interference with the protein signal of interest; however, the recently described Selective Excipient Reduction and Removal (SIERRA) filter greatly reduces this issue. Here we will outline how basic 2D 1 H-13 C methyl-correlated NMR may be combined with the SIERRA approach to collect 'clean' NMR spectra of formulated monoclonal antibody therapeutics (i.e., drug substance spectra free of interfering component signals), and how series of such spectra may be used for HOS characterization by direct PCA of the series spectral matrix. © 2020 U.S. Government. Basic Protocol 1: NMR data acquisition Basic Protocol 2: Full spectral matrix data processing and analysis Support Protocol: Data visualization and cluster analysis.

Comparative Analysis of One-Dimensional Protein Fingerprint by Line Shape Enhancement and Two-Dimensional 1H,13C Methyl NMR Methods for Characterization of the Higher Order Structure of IgG1 Monoclonal Antibodies.

The use of NMR spectroscopy has emerged as a premier tool to characterize the higher order structure of protein therapeutics and in particular IgG1 monoclonal antibodies (mAbs). Due to their large size, traditional 1H-15N correlation experiments have proven exceedingly difficult to implement on mAbs, and a number of alternative techniques have been proposed, including the one-dimensional (1D) 1H protein fingerprint by line shape enhancement (PROFILE) method and the two-dimensional (2D) 1H-13C methyl correlation-based approach. Both 1D and 2D approaches have relative strengths and weaknesses, related to the inherent sensitivity and resolution of the respective methods. To further increase the utility of NMR to the biopharmaceutical community, harmonized criteria for decision making in employing 1D and 2D approaches for mAb characterization are warranted. To this end, we have conducted an interlaboratory comparative study of the 1D PROFILE and 2D methyl methods on several mAbs samples to determine the degree to which each method is suited to detect spectral difference between the samples and the degree to which results from each correlate with one another. Results from the study demonstrate both methods provide statistical data highly comparable to one another and that each method is capable of complementing the limitations commonly associated with the other, thus providing a better overall picture of higher order structure.

Best Practices in Utilization of 2D-NMR Spectral Data as the Input for Chemometric Analysis in Biopharmaceutical Applications.

Quality attributes (QAs) are measureable parameters of a biologic that impact product safety and efficacy and are essential characteristics that are linked to positive patient health outcomes. One QA, higher order structure (HOS), is directly coupled to the function of protein biologics, and deviations in this QA may cause adverse effects. To address the critical need for HOS assessment, methods for analyzing structural fingerprints from 2D nuclear magnetic resonance spectroscopy (2D-NMR) spectra have been established for drug substances as large as monoclonal antibody therapeutics. Here, chemometric analyses have been applied to 2D 1H,13C-methyl NMR correlation spectra of the IgG1κ NIST monoclonal antibody (NISTmAb), recorded at natural isotopic abundance, to benchmark the performance and robustness of the methods. In particular, a variety of possible spectral input schemes (e.g., chemical shift, peak intensity, and total spectral matrix) into chemometric algorithms are examined using two case studies: (1) a large global 2D-NMR interlaboratory study and (2) a blended series of enzymatically glycan-remodeled NISTmAb isoforms. These case studies demonstrate that the performance of chemometric algorithms using either peak positions or total spectral matrix as the input will depend on the study design and likely be product-specific. In general, peak positions are found to be a more robust spectral parameter for input into chemometric algorithms, whereas the total spectral matrix approach lends itself to easier automation and requires less user intervention. Analysis with different input data also shows differences in sensitivity to certain changes in HOS, highlighting that product knowledge will further guide appropriate method selection based on the fit-for-purpose application in the context of biopharmaceutical development, production, and quality control.

Chemometric Outlier Classification of 2D-NMR Spectra to Enable Higher Order Structure Characterization of Protein Therapeutics.

Protein therapeutics are vitally important clinically and commercially, with monoclonal antibody (mAb) therapeutic sales alone accounting for $115 billion in revenue for 2018.[1] In order for these therapeutics to be safe and efficacious, their protein components must maintain their high order structure (HOS), which includes retaining their three-dimensional fold and not forming aggregates. As demonstrated in the recent NISTmAb Interlaboratory nuclear magnetic resonance (NMR) Study[2], NMR spectroscopy is a robust and precise approach to address this HOS measurement need. Using the NISTmAb study data, we benchmark a procedure for automated outlier detection used to identify spectra that are not of sufficient quality for further automated analysis. When applied to a diverse collection of all 252 1H,13C gHSQC spectra from the study, a recursive version of the automated procedure performed comparably to visual analysis, and identified three outlier cases that were missed by the human analyst. In total, this method represents a distinct advance in chemometric detection of outliers due to variation in both measurement and sample.