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At least 721 records · Page 40

Genome‐wide CRISPR‐Cas9 screen reveals a persistent null‐hyphal phenotype that maintains high carotenoid production in Yarrowia lipolytica

Abstract Yarrowia lipolytica is a metabolic engineering host of growing industrial interest due to its ability to metabolize hydrocarbons, fatty acids, glycerol, and other renewable carbon sources. This dimorphic yeast undergoes a stress‐induced transition to a multicellular hyphal state, which can negatively impact biosynthetic activity, reduce oxygen and nutrient mass transfer in cell cultures, and increase culture viscosity. Identifying mutations that prevent the formation of hyphae would help alleviate the bioprocess challenges that they create. To this end, we conducted a genome‐wide CRISPR screen to identify genetic knockouts that prevent the transition to hyphal morphology. The screen identified five mutants with a null‐hyphal phenotype— ΔRAS2 , ΔRHO5 , ΔSFL1 , ΔSNF2 , and ΔPAXIP1 . Of these hits, only ΔRAS2 suppressed hyphal formation in an engineered lycopene production strain over a multiday culture. The RAS2 knockout was also the only genetic disruption characterized that did not affect lycopene production, producing more than 5 mg L −1 OD −1 from a heterologous pathway with enhanced carbon flux through the mevalonate pathway. These data suggest that a ΔRAS2 mutant of Y. lipolytica could prove useful in engineering a metabolic engineering host of the production of carotenoids and other biochemicals.

59 BASIC BIOLOGICAL SCIENCES↗

Continuous precipitation‐filtration process for initial capture of a monoclonal antibody product using a four‐stage countercurrent hollow fiber membrane washing step

The significant increase in product titers, coupled with the growing focus on continuous bioprocessing, has renewed interest in using precipitation as a low‐cost alternative to Protein A chromatography for the primary capture of monoclonal antibody (mAb) products. In this work, a commercially relevant mAb was purified from clarified cell culture fluid using a tubular flow precipitation reactor with dewatering and washing provided by tangential flow microfiltration. The particle morphology was evaluated using an inline high‐resolution optical probe, providing quantitative data on the particle size distribution throughout the precipitation process. Data were obtained in both a lab‐built 2‐stage countercurrent washing system and a commercial countercurrent contacting skid that provided 4 stages of continuous washing. The processes were operated continuously for 2 h with overall mAb yield of 92 ± 3% and DNA removal of nearly 3 logs in the 4‐stage system. The high DNA clearance was achieved by selective redissolution of the mAb using a low pH acetate buffer. Host cell protein clearance was 0.59 ± 0.08 logs, comparable to that based on model predictions. The process mass intensity was slightly better than typical Protein A processes and could be significantly improved by preconcentration of the antibody feed material.

59 BASIC BIOLOGICAL SCIENCES↗

Mechanistic modeling of in vitro transcription incorporating effects of magnesium pyrophosphate crystallization

The in vitro transcription (IVT) reaction used in the production of messenger RNA vaccines and therapies remains poorly quantitatively understood. Mechanistic modeling of IVT could inform reaction design, scale-up, and control. In this work, we develop a mechanistic model of IVT to include nucleation and growth of magnesium pyrophosphate crystals and subsequent agglomeration of crystals and DNA. To help generalize this model to different constructs, a novel quantitative description is included for the rate of transcription as a function of target sequence length, DNA concentration, and T7 RNA polymerase concentration. The model explains previously unexplained trends in IVT data and quantitatively predicts the effect of adding the pyrophosphatase enzyme to the reaction system. The model is validated on additional literature data showing an ability to predict transcription rates as a function of RNA sequence length.

59 BASIC BIOLOGICAL SCIENCES↗

COVID ‐19 outcomes in patients with cancer: Findings from the University of California health system database

Abstract Background The interaction between cancer diagnoses and COVID‐19 infection and outcomes is unclear. We leveraged a state‐wide, multi‐institutional database to assess cancer‐related risk factors for poor COVID‐19 outcomes. Methods We conducted a retrospective cohort study using the University of California Health COVID Research Dataset, which includes electronic health data of patients tested for severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2) at 17 California medical centers. We identified adults tested for SARS‐CoV‐2 from 2/1/2020–12/31/2020 and selected a cohort of patients with cancer. We obtained demographic, clinical, cancer type, and antineoplastic therapy data. The primary outcome was hospitalization within 30d after the first positive SARS‐CoV‐2 test. Secondary outcomes were SARS‐CoV‐2 positivity and severe COVID‐19 (intensive care, mechanical ventilation, or death within 30d after the first positive test). We used multivariable logistic regression to identify cancer‐related factors associated with outcomes. Results We identified 409,462 patients undergoing SARS‐CoV‐2 testing. Of 49,918 patients with cancer, 1781 (3.6%) tested positive. Patients with cancer were less likely to test positive (RR 0.70, 95% CI: 0.67–0.74, p < 0.001). Among the 1781 SARS‐CoV‐2‐positive patients with cancer, BCR/ABL‐negative myeloproliferative neoplasms (RR 2.15, 95% CI: 1.25–3.41, p = 0.007), venetoclax (RR 2.96, 95% CI: 1.14–5.66, p = 0.028), and methotrexate (RR 2.72, 95% CI: 1.10–5.19, p = 0.032) were associated with greater hospitalization risk. Cancer and therapy types were not associated with severe COVID‐19. Conclusions In this large, diverse cohort, cancer was associated with a decreased risk of SARS‐CoV‐2 positivity. Patients with BCR/ABL‐negative myeloproliferative neoplasm or receiving methotrexate or venetoclax may be at increased risk of hospitalization following SARS‐CoV‐2 infection. Mechanistic and comparative studies are needed to validate findings.

60 APPLIED LIFE SCIENCES↗

Urban relatives ameliorate survival disparities for genitourinary cancer in rural patients

Patients living in rural areas have worse cancer-specific outcomes. This study examines the effect of family-based social capital on genitourinary cancer survival. We hypothesized that rural patients with urban relatives have improved survival relative to rural patients without urban family. We examined rural and urban based Utah individuals diagnosed with genitourinary cancers between 1968 and 2018. Familial networks were determined using the Utah Population Database. Patients and relatives were classified as rural or urban based on 2010 rural–urban commuting area codes. Overall survival was analyzed using Cox proportional hazards models. We identified 24,746 patients with genitourinary cancer with a median follow-up of 8.72 years. Rural cancer patients without an urban relative had the worst outcomes with cancer-specific survival hazard ratios (HRs) at 5 and 10 years of 1.33 (95% CI 1.10–1.62) and 1.46 (95% CI 1.24–1.73), respectively relative to urban patients. Rural patients with urban first-degree relatives had improved survival with 5- and 10-year survival HRs of 1.21 (95% CI 1.06–1.40) and 1.16 (95% CI 1.03–1.31), respectively. Our findings suggest rural patients who have been diagnosed with a genitourinary cancer have improved survival when having relatives in urban centers relative to rural patients without urban relatives. Further research is needed to better understand the mechanisms through which having an urban family member contributes to improved cancer outcomes for rural patients. Better characterization of this affect may help inform policies to reduce urban–rural cancer disparities.

60 APPLIED LIFE SCIENCES↗

Artificial intelligence to unlock real-world evidence in clinical oncology: A primer on recent advances

Purpose: Real world evidence is crucial to understanding the diffusion of new oncologic therapies, monitoring cancer outcomes, and detecting unexpected toxicities. In practice, real world evidence is challenging to collect rapidly and comprehensively, often requiring expensive and time-consuming manual case-finding and annotation of clinical text. In this Review, we summarise recent developments in the use of artificial intelligence to collect and analyze real world evidence in oncology. Methods: We performed a narrative review of the major current trends and recent literature in artificial intelligence applications in oncology. Results: Artificial intelligence (AI) approaches are increasingly used to efficiently phenotype patients and tumors at large scale. These tools also may provide novel biological insights and improve risk prediction through multimodal integration of radiographic, pathological, and genomic datasets. Custom language processing pipelines and large language models hold great promise for clinical prediction and phenotyping. Conclusions: Despite rapid advances, continued progress in computation, generalizability, interpretability, and reliability as well as prospective validation are needed to integrate AI approaches into routine clinical care and real-time monitoring of novel therapies.

60 APPLIED LIFE SCIENCES↗

Activity–Based Protein Profiling of Bile Salt Hydrolysis in the Human Gut Microbiome with Beta–Lactam or Acrylamide–Based Probes

Microbial bile salt hydrolases (BSHs) found in the intestine catalyze the deconjugation of taurine– and glycine–linked bile salts produced in the liver. The resulting bile salts are biological detergents and are critical in aiding lipophilic nutrient digestion. Therefore, the activity of BSHs in the gut microbiome is directly linked to human metabolism and overall health. Bile salt metabolism has also been associated with disease phenotypes such as liver and colorectal cancer. In order to reshape the gut microbiome to optimize bile salt metabolism, tools to characterize and quantify these processes must exist to enable a much–improved understanding of how metabolism goes awry in the face of disease, and how it can be improved through an altered lifestyle and environment. Furthermore, it is necessary to attribute metabolic activity to specific members and BSHs within the microbiome. To this end, we have developed activity–based probes with two different reactive groups to target bile salt hydrolases. Finally, these probes bind similarly to the authentic bile salt substrates, and we demonstrate enzyme labeling of active bile salt hydrolases by using purified protein, cell lysates, and in human stool.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

A Hybrid Structural Method for Investigating Low Molecular Weight Oligomeric Structures of Amyloid Beta

Spurred in part by the failure of recent therapeutics targeting amyloid β plaques in Alzheimer's Disease (AD), attention is increasingly turning to the oligomeric forms of this peptide that form early in the aggregation process. However, while numerous amyloid β fibril structures have been characterized, primarily by NMR spectroscopy and cryo-EM, obtaining structural information on the low molecular weight forms of amyloid β that presumably precede and/or seed fibril formation has proved challenging. Furthermore, these transient forms are heterogeneous, and depend heavily on experimental conditions such as buffer, temperature, concentration, and degree of quiescence during measurement. Here, we present the concept for a new approach to delineating structural features of early-stage low molecular weight amyloid β oligomers, using a solvent accessibility assay in conjunction with simultaneous fluorescence measurements.

60 APPLIED LIFE SCIENCES↗

Endogenous Production and Vibrational Analysis of Heavy-Isotope-Labeled Peptides from Cyanobacteria

Stable isotope labeling is an extremely useful tool for characterizing the structure, tracing the metabolism, and imaging the distribution of natural products in living organisms using mass-sensitive measurement techniques. In this study, a cyanobacterium was cultured in 15 N/ 13 C-enriched media to endogenously produce labeled, bioactive oligopeptides. The extent of heavy isotope incorporation in these peptides was determined with LC–MS, while the overall extent of heavy isotope incorporation in whole cells was studied with nanoSIMS and AFM-IR. Up to 98 % heavy isotope incorporation was observed in labeled cells. Three of the most abundant peptides, microcystin-LR (MCLR), cyanopeptolin-A (CYPA), and aerucyclamide-A (ACAA), were isolated and further studied with Raman and FTIR spectroscopies and DFT calculations. This revealed several IR and Raman active vibrations associated with functional groups not common in ribosomal peptides, like diene, ester, thiazole, thiazoline, and oxazoline groups, which could be suitable for future vibrational imaging studies. More broadly, this study outlines a simple and relatively inexpensive method for producing heavy-labeled natural products. Finally, manipulating the bacterial culture conditions by the addition of specific types and amounts of heavy-labeled nutrients provides an efficient means of producing heavy-labeled natural products for mass-sensitive imaging studies.

60 APPLIED LIFE SCIENCES↗

Structure- and Interaction-Based Design of Anti-SARS-CoV-2 Aptamers

Aptamer selection against novel infections is a complicated and time-consuming approach. Synergy can be achieved by using computational methods together with experimental procedures. In this study, we aim to develop a reliable methodology for a rational aptamer in silico et vitro design. The new approach combines multiple steps: (1) Molecular design, based on screening in a DNA aptamer library and directed mutagenesis to fit the protein tertiary structure; (2) 3D molecular modeling of the target; (3) Molecular docking of an aptamer with the protein; (4) Molecular dynamics (MD) simulations of the complexes; (5) Quantum-mechanical (QM) evaluation of the interactions between aptamer and target with further analysis; (6) Experimental verification at each cycle for structure and binding affinity by using small-angle X-ray scattering, cytometry, and fluorescence polarization. By using a new iterative design procedure, structure- and interaction-based drug design (SIBDD), a highly specific aptamer to the receptor-binding domain of the SARS-CoV-2 spike protein, was developed and validated. The SIBDD approach enhances speed of the high-affinity aptamers development from scratch, using a target protein structure. The method could be used to improve existing aptamers for stronger binding. This approach brings to an advanced level the development of novel affinity probes, functional nucleic acids. It offers a blueprint for the straightforward design of targeting molecules for new pathogen agents and emerging variants.

60 APPLIED LIFE SCIENCES↗

A Quick Route to Multiple Highly Potent SARS-CoV-2 Main Protease Inhibitors**

The COVID-19 pathogen, SARS-CoV-2, requires its main protease (SC2M Pro ) to digest two of its translated long polypeptides to form a number of mature proteins that are essential for viral replication and pathogenesis. Inhibition of this vital proteolytic process is effective in preventing the virus from replicating in infected cells and therefore provides a potential COVID-19 treatment option. Guided by previous medicinal chemistry studies about SARS-CoV-1 main protease (SC1M Pro ), we have designed and synthesized a series of SC2M Pro inhibitors that contain β-(S-2-oxopyrrolidin-3-yl)-alaninal (Opal) for the formation of a reversible covalent bond with the SC2M Pro active-site cysteine C145. All inhibitors display high potency with K i values at or below 100 nM. The most potent compound, MPI3, has as a K i value of 8.3 nM. Crystallographic analyses of SC2M Pro bound to seven inhibitors indicated both formation of a covalent bond with C145 and structural rearrangement from the apoenzyme to accommodate the inhibitors. Virus inhibition assays revealed that several inhibitors have high potency in inhibiting the SARS-CoV-2-induced cytopathogenic effect in both Vero E6 and A549/ACE2 cells. Two inhibitors, MPI5 and MPI8, completely prevented the SARS-CoV-2-induced cytopathogenic effect in Vero E6 cells at 2.5-5 μM and A549/ACE2 cells at 0.16-0.31 μM. Their virus inhibition potency is much higher than that of some existing molecules that are under preclinical and clinical investigations for the treatment of COVID-19. Our study indicates that there is a large chemical space that needs to be explored for the development of SC2M Pro inhibitors with ultra-high antiviral potency.

3C-like protease↗

Floor and ceiling effects in the EORTC QLQ-C30 Physical Functioning subscale among patients with advanced or metastatic breast cancer

The European Organization for Research and Treatment of Cancer (EORTC) Quality of Life Questionnaire Core 30 Physical Functioning subscale is a widely used patient-reported outcome measure that quantifies cancer patients' physical functioning. Strong floor/ceiling effects can affect a scale's sensitivity to change. The aim of this study was to characterize floor/ceiling effects of the physical functioning domain in patients with advanced/metastatic breast cancer enrolled in commercial clinical trials and a community-based trial. The clinical trial cohort comprised patients from 5 registrational trials submitted to the Food and Drug Administration for review (2010-2017). The community cohort comprised a subgroup of patients from the Alliance Patient Reported Outcomes to Enhance Cancer Treatment (PRO-TECT) trial. The distribution of patient responses to Physical Functioning items and the summed score were assessed at the baseline and 3-month follow-up for both cohorts. Descriptive statistics were used to determine floor/ceiling effects at the item and scale levels. The clinical trial cohort and the community cohort consisted of 2407 and 178 patients, respectively. Twenty-four percent or more of the respondents reported “not at all” for having trouble/needing help with each Physical Functioning item across both cohorts and measurement time points. Fourteen to twenty percent of the patients scored perfectly (100 of 100) on the Physical Functioning subscale summary measure (where higher scores indicated better physical functioning) across both cohorts and time points. Minor floor effects and notable ceiling effects were found at the item and scale levels of the Physical Functioning subscale, regardless of cohort, and this creates some uncertainty about its ability to detect changes in physical functioning among high-functioning patients. In conclusion, investigators may consider adding additional high-functioning items from the EORTC's item library to more accurately describe the impact of anticancer treatment on patients' physical functioning.

60 APPLIED LIFE SCIENCES↗

Quasi‐dynamic breathing model of the lung incorporating viscoelasticity of the lung tissue

Abstract We advanced a novel model to calculate viscoelastic lung compliance and airflow resistance in presence of mucus, accounting for the quasi‐linear viscoelastic stress–strain response of the parenchyma (alveoli) tissue. We adapted a continuum‐based numerical modeling approach for the lung, integrating the fluid mechanics of the airflow within individual generations of the bronchi and alveoli. The model accounts for elasticity of the deformable bronchioles, resistance to airflow due to the presence of mucus within the bronchioles, and subsequent mucus flow. Simulated quasi‐dynamic inhalation and expiration cycles were used to characterize the net compliance and resistance of the lung, considering the rheology of the mucus and viscoelastic properties of the parenchyma tissue. The structure and material properties of the lung were identified to have an important contribution to the lung compliance and airflow resistance. The secondary objective of this work was to assess whether a higher frequency and smaller volume of harmonic air flow rate compared to a normal ventilator breathing cycle enhanced mucus outflow. Results predict, lower mucus viscosity and higher excitation frequency of breathing are favorable for the flow of mucus up the bronchi tree, towards the trachea.

60 APPLIED LIFE SCIENCES↗

Mechanistic modelling of SARS-CoV-2 and other infectious diseases and the effects of therapeutics

Modern viral kinetic modeling and its application to therapeutics is a field that attracted the attention of the medical, pharmaceutical and modeling communities during the early days of the AIDS epidemic. Its successes lead to applications of modeling methods not only to HIV but a plethora of other viruses, such as hepatitis C virus (HCV), hepatitis B virus (HBV) and cytomegalovirus (CMV), which along with HIV cause chronic diseases, and viruses such as influenza, respiratory syncytial virus (RSV), West Nile virus (WNV), Zika virus, and SAR-CoV-2, which generally cause acute infections. Here we first review the historical development of mathematical models to understand HIV and HCV infections and the effects of treatment by fitting the models to clinical data. Furthermore, we then focus on recent efforts and contributions of applying these models towards understanding SARS-CoV-2 infection and highlight outstanding questions where modeling can provide crucial insights and help to optimize non-pharmaceutical and pharmaceutical interventions of the COVID-19 pandemic. The review is written from our personal perspective emphasizing the power of simple target cell limited models that provided important insights and then their evolution into more complex models that captured more of the virology and immunology. To quote Albert Einstein “Everything should be made as simple as possible, but not simpler”, and this idea underlies the modeling we describe below.

60 APPLIED LIFE SCIENCES↗

The Impact of Variability in Patient Exposure During Premarket Clinical Development on Postmarket Safety Outcomes

We characterized the size of the premarket safety population for 278 small-molecule new molecular entities (NMEs) and 61 new therapeutic biologics (NTBs) approved by the US Food and Drug Administration (FDA) between October 1, 2002, and December 31, 2014, evaluating the relationship of premarket safety population size to regulatory characteristics and postmarket safety outcomes. The median size of the safety population was 1,044, and was lower for NTBs than NMEs (median: 920 vs. 1,138, P = 0.04), orphan products than nonorphan products (393 vs. 1,606, P < 0.001), and for products with fast-track designation (617 vs. 1,455, P < 0.001), priority review (630 vs. 1,735, P < 0.001), and accelerated approval (475 vs. 1,164, P < 0.001), than products without that designation. The median number of postmarket safety label updates and issues added to the label were higher with larger premarket exposure among nonorphan products, but not among orphan products. Products with accelerated approval using a surrogate end point had a higher median number of safety issues added to the label than those with full approval, but this did not vary with the size of the safety population; fast-track and priority review were not associated with the number of safety issues added to the label. Here, a smaller safety population size was associated with a longer time to first safety outcome for nonorphan products but not orphan products. For orphan and nonorphan products combined, smaller premarket safety population size is not associated with the number or timing of postmarket safety outcomes, regardless of expedited program participation.

60 APPLIED LIFE SCIENCES↗

Recommendations for Dose Selection for Adolescent Patients in Relevant Adult Oncology Clinical Trials

Our research supported the dose selection recommendations for adolescents in the US Food and Drug Administration (FDA) Guidance on Inclusion of Adolescent Patients in Adult Oncology Clinical Trials. The FDA Guidance states that for drugs administered as a flat dose in adults and data showing no clinically meaningful effect of body size on drug exposure and toxicity in adults, a minimum body weight threshold may need to be defined to prevent adolescents who have a lower body weight from exceeding adult exposures. Our review of adult population pharmacokinetic analyses of new molecular entities approved for oncology between January 2015 and March 2021 suggested that 40 kg (the approximate median body weight of a 12-year-old) is generally the lower end of the body weight range that has no clinically relevant effect on drug pharmacokinetics or safety. In conclusion, the minimum body weight threshold and selection of an appropriate dose for adolescents in relevant adult oncology clinical trials should ultimately be determined based on available data on pharmacokinetics or pharmacodynamics of the investigational drug with consideration of body size effect on drug exposure, toxicity, and efficacy data (if available), the therapeutic index of the drug, and dose- and exposure-response relationships in adults.

60 APPLIED LIFE SCIENCES↗

Calibration and Validation of a Mechanistic COVID-19 Model for Translational Quantitative Systems Pharmacology – A Proof-of-Concept Model Development for Remdesivir

With the ongoing global pandemic of coronavirus disease 2019 (COVID-19), there is an urgent need to accelerate the traditional drug development process. Many studies identified potential COVID-19 therapies based on promising nonclinical data. However, the poor translatability from nonclinical to clinical settings has led to failures of many of these drug candidates in the clinical phase. In this study, we propose a mechanism-based, quantitative framework to translate nonclinical findings to clinical outcome. Adopting a modularized approach, this framework includes an in silico disease model for COVID-19 (virus infection and human immune responses) and a pharmacological component for COVID-19 therapies. Here, the disease model was able to reproduce important longitudinal clinical data for patients with mild and severe COVID-19, including viral titer, key immunological cytokines, antibody responses, and time courses of lymphopenia. Using remdesivir as a proof-of-concept example of model development for the pharmacological component, we developed a pharmacological model that describes the conversion of intravenously administered remdesivir as a prodrug to its active metabolite nucleoside triphosphate through intracellular metabolism and connected it to the COVID-19 disease model. After being calibrated with the placebo arm data, our model was independently and quantitatively able to predict the primary endpoint (time to recovery) of the remdesivir clinical study, Adaptive Covid-19 Clinical Trial (ACTT). Our work demonstrates the possibility of quantitatively predicting clinical outcome based on nonclinical data and mechanistic understanding of the disease and provides a modularized framework to aid in candidate drug selection and clinical trial design for COVID-19 therapeutics.

60 APPLIED LIFE SCIENCES↗