Assessing the predictive capabilities of design heuristics and coarse-grain simulation toward understanding and optimizing site-specific covalent immobilization of ß-lactamase.

For industrial applications, covalent immobilization of enzymes provides minimum leakage, recoverability, reusability, and high stability. Yet, the suitability of a given site on the enzyme for immobilization remains a trial-and-error procedure. Here, we investigate the reliability of design heuristics and a coarse-grain molecular simulation in predicting the optimum sites for covalent immobilization of TEM-1 ß-lactamase. We utilized Escherichia coli-lysate-based cell-free protein synthesis (CFPS) to produce variants containing a site-specific incorporated unnatural amino acid with a unique moiety to facilitate site directed covalent immobilization. To constrain the number of potential immobilization sites, we investigated the predictive capability of several design heuristics. The suitability of immobilization sites was determined by analyzing expression yields, specific activity, immobilization efficiency, and stability of variants. These experimental findings are compared with coarse-grain simulation of TEM-1 domain stability and thermal stability and analyzed for a priori predictive capabilities. This work demonstrates that the design heuristics successfully identify a subset of locations for experimental validation. Specifically, the nucleotide following amber stop codon and domain stability correlate well with the expression yield and specific activity of the variants, respectively. Our approach highlights the advantages of combining coarse-grain simulation and high-throughput experimentation using CFPS to identify optimal enzyme immobilization sites.

PASTRY: A nursing-developed quality improvement initiative to combat moral distress.

BACKGROUND: High levels of moral distress in nursing professionals, of which oncology nurses are particularly prone, can negatively impact patient care, job satisfaction, and retention. AIM: "Positive Attitudes Striving to Rejuvenate You: PASTRY" was developed at a tertiary cancer center to reduce the burden of moral distress among oncology nurses. RESEARCH DESIGN: A Quality Improvement (QI) initiative was conducted using a pre- and post-intervention design, to launch PASTRY and measure its impact on moral distress of the nursing unit, using Hamric's Moral Distress Scale-Revised (MDS-R.) This program consisted of monthly 60-minute sessions allowing nurses to address morally distressing events and themes, such as clinicians giving "false hope" to patients or families. The PASTRY program sessions were led by certified clinicians utilizing strategies of discussion and mind-body practices. PARTICIPANTS: Clinical nurses working on an adult leukemia/lymphoma unit. ETHICAL CONSIDERATIONS: This was a QI initiative, participation was voluntary, MDS-R responses were collected anonymously, and the institution's Ethics Committee oversaw PASTRY's implementation. FINDINGS: While improvement in moral distress findings were not statistically significant, the qualitative and quantitative findings demonstrated consistent themes. The PASTRY program received strong support from nurses and institutional leaders, lowered the nursing unit's moral distress, led to enhanced camaraderie, and improved nurses' coping skills. DISCUSSION: Measurement of moral distress is innately challenging due to its complexity. This study reinforces oncology nurses have measurable moral distress. Interventions should be implemented for a safe and healing environment to explore morally distressing clinical experiences. Poor communication among multidisciplinary team members is associated with moral distress among nurses. Programs like PASTRY may empower nurses to build support networks for change within themselves and institutions. CONCLUSION: This QI initiative shows further research on moral distress reduction should be conducted to verify findings for statistical significance and so that institutional programs, like PASTRY, can be created.

Assessing site-specific PEGylation of TEM-1 ß-lactamase with cell-free protein synthesis and coarse-grained simulation.

PEGylation is a broadly used strategy to enhance the pharmacokinetic properties of therapeutic proteins. It is well established that the location and extent of PEGylation have a significant impact on protein properties. However, conventional PEGylation techniques have limited control over PEGylation sites. Emerging site-specific PEGylation technology provides control of PEG placement by conjugating PEG polymers via click chemistry reaction to genetically encoded non-canonical amino acids. Unfortunately, a method to rapidly determine the optimal PEGylation location has yet to be established. Here we seek to address this challenge. In this work, coarse-grained molecular dynamic simulations are paired with high-throughput experimental screening utilizing cell-free protein synthesis to investigate the effect of site-specific PEGylation on the two-state folder protein TEM-1 ß-lactamase. Specifically, the conjugation efficiency, thermal stability, and enzymatic activity are studied for the enzyme PEGylated at several different locations. The results of this analysis confirm that the physical properties of the PEGylated protein vary considerably with PEGylation site and that traditional design recommendations are insufficient to predict favorable PEGylation sites. In this study, the best predictor of the most favorable conjugation site is coarse-grained simulation. Thus, we propose a dual combinatorial screening approach in which coarse-grained molecular simulation informs site selection for high-throughput experimental verification.

Towards detection of SARS-CoV-2 RNA in human saliva: A paper-based cell-free toehold switch biosensor with a visual bioluminescent output.

The COVID-19 pandemic has illustrated the global demand for rapid, low-cost, widely distributable and point-of-care nucleic acid diagnostic technologies. Such technologies could help disrupt transmission, sustain economies and preserve health and lives during widespread infection. In contrast, conventional nucleic acid diagnostic procedures require trained personnel, complex laboratories, expensive equipment, and protracted processing times. In this work, lyophilized cell-free protein synthesis (CFPS) and toehold switch riboregulators are employed to develop a promising paper-based nucleic acid diagnostic platform activated simply by the addition of saliva. First, to facilitate distribution and deployment, an economical paper support matrix is identified and a mass-producible test cassette designed with integral saliva sample receptacles. Next, CFPS is optimized in the presence of saliva using murine RNase inhibitor. Finally, original toehold switch riboregulators are engineered to express the bioluminescent reporter NanoLuc in response to SARS-CoV-2 RNA sequences present in saliva samples. The biosensor generates a visible signal in as few as seven minutes following administration of 15 µL saliva enriched with high concentrations of SARS-CoV-2 RNA sequences. The estimated cost of this test is less than 0.50 USD, which could make this platform readily accessible to both the developed and developing world. While additional research is needed to decrease the limit of detection, this work represents important progress toward developing a diagnostic technology that is rapid, low-cost, distributable and deployable at the point-of-care by a layperson.

Mechanistic discoveries and simulation-guided assay optimization of portable hormone biosensors with cell-free protein synthesis.

Nuclear receptors (NRs) influence nearly every system of the body and our lives depend on correct NR signaling. Thus, a key environmental and pharmaceutical quest is to identify and detect chemicals which interact with nuclear hormone receptors, including endocrine disrupting chemicals (EDCs), therapeutic receptor modulators, and natural hormones. Previously reported biosensors of nuclear hormone receptor ligands facilitated rapid detection of NR ligands using cell-free protein synthesis (CFPS). In this work, the advantages of CFPS are further leveraged and combined with kinetic analysis, autoradiography, and western blot to elucidate the molecular mechanism of this biosensor. Additionally, mathematical simulations of enzyme kinetics are used to optimize the biosensor assay, ultimately lengthening its readable window by five-fold and improving sensor signal strength by two-fold. This approach enabled the creation of an on-demand thyroid hormone biosensor with an observable color-change readout. This mathematical and experimental approach provides insight for engineering rapid and field-deployable CFPS biosensors and promises to improve methods for detecting natural hormones, therapeutic receptor modulators, and EDCs.

Persistence of SARS CoV-2 S1 Protein in CD16+ Monocytes in Post-Acute Sequelae of COVID-19 (PASC) Up to 15 Months Post-Infection

The recent COVID-19 pandemic is a treatment challenge in the acute infection stage but the recognition of chronic COVID-19 symptoms termed post-acute sequelae SARS-CoV-2 infection (PASC) may affect up to 30% of all infected individuals. The underlying mechanism and source of this distinct immunologic condition three months or more after initial infection remains elusive. Here, we investigated the presence of SARS-CoV-2 S1 protein in 46 individuals. We analyzed T-cell, B-cell, and monocytic subsets in both severe COVID-19 patients and in patients with post-acute sequelae of COVID-19 (PASC). The levels of both intermediate (CD14+, CD16+) and non-classical monocyte (CD14Lo, CD16+) were significantly elevated in PASC patients up to 15 months post-acute infection compared to healthy controls (P=0.002 and P=0.01, respectively). A statistically significant number of non-classical monocytes contained SARS-CoV-2 S1 protein in both severe (P=0.004) and PASC patients (P=0.02) out to 15 months post-infection. Non-classical monocytes were sorted from PASC patients using flow cytometric sorting and the SARS-CoV-2 S1 protein was confirmed by mass spectrometry. Cells from 4 out of 11 severe COVID-19 patients and 1 out of 26 PASC patients contained ddPCR+ peripheral blood mononuclear cells, however, only fragmented SARS-CoV-2 RNA was found in PASC patients. No full length sequences were identified, and no sequences that could account for the observed S1 protein were identified in any patient. Non-classical monocytes are capable of causing inflammation throughout the body in response to fractalkine/CX3CL1 and RANTES/CCR5.

Coarse-grained simulation of PEGylated and tethered protein devices at all experimentally accessible surface residues on ß-lactamase for stability analysis and comparison.

PEGylated and surface-tethered proteins are used in a variety of biotechnological applications, but traditional methods offer little control over the placement of the functionalization sites on the protein. Fortunately, recent experimental methods functionalize the protein at any location on the amino acid sequence, so the question becomes one of selecting the site that will result in the best protein function. This work shows how molecular simulation can be used to screen potential attachment sites for surface tethering or PEGylation. Previous simulation work has shown promise in this regard for a model protein, but these studies are limited to screening only a few of the surface-accessible sites or only considered surface tethering or PEGylation separately rather than their combined effects. This work is done to overcome these limitations by screening all surface-accessible functionalization sites on a protein of industrial and therapeutic importance (TEM-1) and to evaluate the effects of tethering and PEGylation simultaneously in an effort to create a more accurate screen. The results show that functionalization site effectiveness appears to be a function of super-secondary and tertiary structures rather than the primary structure, as is often currently assumed. Moreover, sites in the middle of secondary structure elements, and not only those in loops regions, are shown to be good options for functionalization-a fact not appreciated in current practice. Taken as a whole, the results show how rigorous molecular simulation can be done to identify candidate amino acids for functionalization on a protein to facilitate the rational design of protein devices.

Immune-Based Prediction of COVID-19 Severity and Chronicity Decoded Using Machine Learning

Individuals with systemic symptoms long after COVID-19 has cleared represent approximately ~10% of all COVID-19 infected individuals. Here we present a bioinformatics approach to predict and model the phases of COVID so that effective treatment strategies can be devised and monitored. We investigated 144 individuals including normal individuals and patients spanning the COVID-19 disease continuum. We collected plasma and isolated PBMCs from 29 normal individuals, 26 individuals with mild-moderate COVID-19, 25 individuals with severe COVID-19, and 64 individuals with Chronic COVID-19 symptoms. Immune subset profiling and a 14-plex cytokine panel were run on all patients. Data was analyzed using machine learning methods to predict and distinguish the groups from each other.Using a multi-class deep neural network classifier to better fit our prediction model, we recapitulated a 100% precision, 100% recall and F1 score of 1 on the test set. Moreover, a first score specific for the chronic COVID-19 patients was defined as S1 = (IFN-{gamma} + IL-2)/ CCL4-MIP-1{beta}. Second, a score specific for the severe COVID-19 patients was defined as S2 = (10*IL-10 + IL-6) - (IL-2 + IL-8). Severe cases are characterized by excessive inflammation and dysregulated T cell activation, recruitment, and counteracting activities. While chronic patients are characterized by a profile able to induce the activation of effector T cells with pro-inflammatory properties and the capacity of generating an effective immune response to eliminate the virus but without the proper recruitment signals to attract activated T cells. SummaryImmunologic Modeling of Severity and Chronicity of COVID-19

Thermostable lyoprotectant-enhanced cell-free protein synthesis for on-demand endotoxin-free therapeutic production.

Cell-free protein synthesis has emerged as a promising platform for the production of therapeutic proteins due to its inherently open reaction environment, flexible reaction conditions and rapid protein synthesis capabilities. In recent years, lyophilized cell-free systems have widened the application space of cell-free technology by improving reagent stability outside of cold-chain storage. Current embodiments of the system, however, demonstrate poor stability at elevated temperatures. Lyoprotectants have long been recognized for the ability to preserve the activity of biological molecules during drying processes, but the application of this technology to lyophilized cell-free systems has been limited and has failed to address the negative effects that such lyoprotectants may have on cell-free systems. Here, several lyoprotected, lyophilized cell-free protein synthesis systems are demonstrated using antiplasticized sugar glasses as lyoprotectants, showing significant improvement over standard lyophilized systems or trehalose-preserved systems. Furthermore, we demonstrate for the first time, preservation and therapeutic expression, specifically of FDA-approved crisantaspase, from a truly single-pot lyophilized, endotoxin-free, cell-free protein synthesis system, exemplifying the potential for on-site therapeutic synthesis.

Streamlining the preparation of "endotoxin-free" ClearColi cell extract with autoinduction media for cell-free protein synthesis of the therapeutic protein crisantaspase.

An "endotoxin-free" E. coli-based cell-free protein synthesis system has been reported to produce therapeutic proteins rapidly and on-demand. However, preparation of the most complex CFPS reagent - the cell extract - remains time-consuming and labor-intensive because of the relatively slow growth kinetics of the endotoxin-free ClearColiTMBL21(DE3) strain. Here we report a streamlined procedure for preparing E. coli cell extract from ClearColi™ using auto-induction media. In this work, the term auto-induction describes cell culture media which eliminates the need for manual induction of protein expression. Culturing Clearcoli™ cells in autoinduction media significantly reduces the hands-on time required during extract preparation, and the resulting "endotoxin-free" cell extract maintained the same cell-free protein synthesis capability as extract produced with traditional induction as demonstrated by the high-yield expression of crisantaspase, an FDA approved leukemia therapeutic. It is anticipated that this work will lower the barrier for researchers to enter the field and use this technology as the method to produce endotoxin-free E. coli-based extract for CFPS.