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At least 145 records · Page 8

Involvement of multiple scavenger receptors in advanced glycation end product-induced vessel tube formation in endothelial cells

Highlights: • Multiple scavenger receptors contribute to AGE-induced angiogenesis. • RAGE contributes to AGE-induced angiogenesis by upregulation of scavenger receptors. • AGE activates mTOR signaling. Toxic advanced glycation end products (toxic AGEs) derived from glycolaldehyde (AGE3) have been implicated in the development of diabetic vascular complications such as retinopathy characterised by excessive angiogenesis. Different receptor types, such as receptor for AGEs (RAGE), Toll like receptor-4 and scavenger receptors, are expressed in endothelial cells and contribute to AGE-elicited alteration of cell function. In the present study, we examined the involvement of AGE-related receptors on AGE-induced angiogenesis in endothelial cells. The effects of pharmacological inhibitors or receptor neutralizing antibodies on AGE3-induced tube formation were investigated using the in vitro Matrigel tube formation assay in b.End5 cells (mouse endothelial cells). AGE3-induced signalling pathways and receptor expression changes were analysed by Western blot analysis and flow cytometry, respectively. Both FPS-ZM1, a RAGE inhibitor, and fucoidan, a ligand for scavenger receptors, suppressed AGE3-induced tube formation. Cocktails of neutralizing antibodies against the scavenger receptors CD36, CD163 and LOX-1 prevented AGE3-induced tube formation. AGE3 activated mTOR signalling, resulting in facilitation of tube formation. Activation of the AGE-RAGE pathway also led to the upregulation of scavenger receptors. Taken together, our findings suggest that the scavenger receptors CD36, CD163 and LOX-1 in conjunction with the RAGE receptor work together to mediate toxic AGE-induced facilitation of angiogenesis.

60 APPLIED LIFE SCIENCES↗

An approach for collaborative development of a federated biomedical knowledge graph-based question-answering system: Question-of-the-Month challenges

Knowledge graphs have become a common approach for knowledge representation. Yet, the application of graph methodology is elusive due to the sheer number and complexity of knowledge sources. In addition, semantic incompatibilities hinder efforts to harmonize and integrate across these diverse sources. As part of The Biomedical Translator Consortium, we have developed a knowledge graph–based question-answering system designed to augment human reasoning and accelerate translational scientific discovery: the Translator system. We have applied the Translator system to answer biomedical questions in the context of a broad array of diseases and syndromes, including Fanconi anemia, primary ciliary dyskinesia, multiple sclerosis, and others. A variety of collaborative approaches have been used to research and develop the Translator system. One recent approach involved the establishment of a monthly “Question-of-the-Month (QotM) Challenge” series. Herein, we describe the structure of the QotM Challenge; the six challenges that have been conducted to date on drug-induced liver injury, cannabidiol toxicity, coronavirus infection, diabetes, psoriatic arthritis, and -related phenotypes; the scientific insights that have been gleaned during the challenges; and the technical issues that were identified over the course of the challenges and that can now be addressed to foster further development of the prototype Translator system. We close with a discussion on Large Language Models such as ChatGPT and highlight differences between those models and the Translator system.

60 APPLIED LIFE SCIENCES↗

Dynamics-Based Peptide–MHC Binding Optimization by a Convolutional Variational Autoencoder: A Use-Case Model for CASTELO

An unsolved challenge in the development of antigen-specific immunotherapies is determining the optimal antigens to target. Comprehension of antigen–major histocompatibility complex (MHC) binding is paramount toward achieving this goal. Here, we apply CASTELO, a combined machine learning-molecular dynamics (ML-MD) approach, to identify per-residue antigen binding contributions and then design novel antigens of increased MHC-II binding affinity for a type 1 diabetes-implicated system. We build upon a small-molecule lead optimization algorithm by training a convolutional variational autoencoder (CVAE) on MD trajectories of 48 different systems across four antigens and four HLA serotypes. We develop several new machine learning metrics including a structure-based anchor residue classification model as well as cluster comparison scores. ML-MD predictions agree well with experimental binding results and free energy perturbation-predicted binding affinities. Moreover, ML-MD metrics are independent of traditional MD stability metrics such as contact area and root-mean-square fluctuations (RMSF), which do not reflect binding affinity data. Finally, our work supports the role of structure-based deep learning techniques in antigen-specific immunotherapy design.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Molecular-Level Dysregulation of Insulin Pathways and Inflammatory Processes in Peripheral Blood Mononuclear Cells by Circadian Misalignment

Circadian misalignment due to night work has been associated with elevated risk for chronic diseases. Here, we investigated the effects of circadian misalignment using shotgun protein profiling of peripheral blood mononuclear cells taken from healthy humans during a constant routine protocol, which was conducted immediately after participants had been subjected to a 3-day simulated night shift schedule or a 3-day simulated day shift schedule. By comparing proteomic profiles between the simulated shift conditions, we identified proteins and pathways that are associated with the effects of circadian misalignment, and observed that insulin regulation pathways and inflammation-related proteins displayed markedly different temporal patterns after simulated night shift. Further, by integrating the proteomic profiles with previously assessed metabolomic profiles in a network-based approach, we found key associations between circadian dysregulation of protein-level pathways and metabolites of interest in the context of chronic metabolic diseases. Overall, our results suggest that circadian misalignment is associated with a tug of war between central clock mechanisms controlling insulin secretion and peripheral clock mechanisms regulating insulin sensitivity, which may lead to adverse long-term outcomes such as diabetes and obesity. Our study provides a molecular-level mechanism linking circadian misalignment and adverse long-term health consequences of night work.

59 BASIC BIOLOGICAL SCIENCES↗

Role of Tensile Stress in DNA Nanoresonators for Epigenetic Studies

The evaluation of epigenetic features such as DNA methylation is becoming increasingly important in many biochemical processes like gene expression and transcription as well as in several diseases like schizophrenia or diabetes. Here, in this work, we report that self-assembled nanomechanical resonators entirely composed of DNA molecules can be used to explore gross changes in DNA methylation levels (0–25–50%), while careful control of tensile stress is needed to reduce the variability of resonance frequency for rigorous quantification. The effect of the tensile stress retained by the suspended DNA nanoresonators on the application of the technique is extensively explored using a combination of laser Doppler vibrometry and atomic force spectroscopy. DNA nanoresonators are real-time, label-free sensors and could avoid chemical functionalization and sample amplification. Therefore, they may represent in the future a key complementary routine tool for global DNA methylation analysis needed to evaluate the consequences of environmental stresses on the human genome.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Minimally disruptive optical control of protein tyrosine phosphatase 1B

Protein tyrosine phosphatases regulate a myriad of essential subcellular signaling events, yet they remain difficult to study in their native biophysical context. Here we develop a minimally disruptive optical approach to control protein tyrosine phosphatase 1B (PTP1B)—an important regulator of receptor tyrosine kinases and a therapeutic target for the treatment of diabetes, obesity, and cancer—and we use that approach to probe the intracellular function of this enzyme. Our conservative architecture for photocontrol, which consists of a protein-based light switch fused to an allosteric regulatory element, preserves the native structure, activity, and subcellular localization of PTP1B, affords changes in activity that match those elicited by post-translational modifications inside the cell, and permits experimental analyses of the molecular basis of optical modulation. Findings indicate, most strikingly, that small changes in the activity of PTP1B can cause large shifts in the phosphorylation states of its regulatory targets.

59 BASIC BIOLOGICAL SCIENCES↗

Structural insights on ligand recognition at the human leukotriene B4 receptor 1

The leukotriene B4 receptor 1 (BLT1) regulates the recruitment and chemotaxis of different cell types and plays a role in the pathophysiology of infectious, allergic, metabolic, and tumorigenic human diseases. Here we present a crystal structure of human BLT1 (hBLT1) in complex with a selective antagonist MK-D-046, developed for the treatment of type 2 diabetes and other inflammatory conditions. Comprehensive analysis of the structure and structure-activity relationship data, reinforced by site-directed mutagenesis and docking studies, reveals molecular determinants of ligand binding and selectivity toward different BLT receptor subtypes and across species. The structure helps to identify a putative membrane-buried ligand access channel as well as potential receptor binding modes of endogenous agonists. These structural insights of hBLT1 enrich our understanding of its ligand recognition and open up future avenues in structure-based drug design.

59 BASIC BIOLOGICAL SCIENCES↗

The molecular basis of Human FN3K mediated phosphorylation of glycated substrates

Abstract Glycation, a non-enzymatic post-translational modification occurring on proteins, can be actively reversed via site-specific phosphorylation of the fructose-lysine moiety by FN3K kinase, to impact the cellular function of the target protein. A regulatory axis between FN3K and glycated protein targets has been associated with conditions like diabetes and cancer. However, the molecular basis of this relationship has not been explored so far. Here, we determined a series of crystal structures of HsFN3K in the apo-state, and in complex with different nucleotide analogs together with a sugar substrate mimic to reveal the features important for its kinase activity and substrate recognition. Additionally, the dynamics in sugar substrate binding during the kinase catalytic cycle provide important mechanistic insights into HsFN3K function. Our structural work provides the molecular basis for rational small molecule design targeting FN3K.

Science & Technology - Other Topics↗

Flexible organic integrated electronics for self-powered multiplexed ocular monitoring

Smart contact lens has drawn extensive research interests due to the noninvasive real-time detection of the human body to provide biomedical information for health management. However, it has been difficult to accurately measure the physiological signals in tears, and the use of external power source has also hindered the future applications. Here, we demonstrated an organic electrochemical transistor based multiplexed sensors self-powered by the organic solar cells (OSCs). The integrated device was fabricated via simple process including solution blade-coating and thermal evaporation. OSCs were optimized to provide optimal operation voltage for the sensors that exhibit semilog-linear response to the glucose and calcium ions in tear fluids without any peripheral circuits. The sensing signals can be transmitted to the laptop wirelessly through a near filed communication unit. This integrated self-powered multiplexed sensing device will provide real-time monitoring of the biomarkers in tears, prospected to be installed on the smart contact lens for the early detection and diagnosis of diabetes.

36 MATERIALS SCIENCE↗

A proteomic meta-analysis refinement of plasma extracellular vesicles

Extracellular vesicles play major roles in cell-to-cell communication and are excellent biomarker candidates. However, studying plasma extracellular vesicles is challenging due to contaminants. Here, we performed a proteomics meta-analysis of public data to refine the plasma EV composition by separating EV proteins and contaminants into different clusters. We obtained two clusters with a total of 1717 proteins that were depleted of known contaminants and enriched in EV markers with independently validated 71% true-positive. These clusters had 133 clusters of differentiation (CD) antigens and were enriched with proteins from cell-to-cell communication and signaling. We compared our data with the proteins deposited in PeptideAtlas, making our refined EV protein list a resource for mechanistic and biomarker studies. As a use case example for this resource, we validated the type 1 diabetes biomarker proplatelet basic protein in EVs and showed that it regulates apoptosis of β cells and macrophages, two key players in the disease development. Our approach provides a refinement of the EV composition and a resource for the scientific community.

59 BASIC BIOLOGICAL SCIENCES↗

The cardiac molecular setting of metabolic syndrome in pigs reveals disease susceptibility and suggests mechanisms that exacerbate COVID-19 outcomes in patients

Abstract Although metabolic syndrome (MetS) is linked to an elevated risk of cardiovascular disease (CVD), the cardiac-specific risk mechanism is unknown. Obesity, hypertension, and diabetes (all MetS components) are the most common form of CVD and represent risk factors for worse COVID-19 outcomes compared to their non MetS peers. Here, we use obese Yorkshire pigs as a highly relevant animal model of human MetS, where pigs develop the hallmarks of human MetS and reproducibly mimics the myocardial pathophysiology in patients. Myocardium-specific mass spectroscopy-derived metabolomics, proteomics, and transcriptomics enabled the identity and quality of proteins and metabolites to be investigated in the myocardium to greater depth. Myocardium-specific deregulation of pro-inflammatory markers, propensity for arterial thrombosis, and platelet aggregation was revealed by computational analysis of differentially enriched pathways between MetS and control animals. While key components of the complement pathway and the immune response to viruses are under expressed, key N6-methyladenosin RNA methylation enzymes are largely overexpressed in MetS. Blood tests do not capture the entirety of metabolic changes that the myocardium undergoes, making this analysis of greater value than blood component analysis alone. Our findings create data associations to further characterize the MetS myocardium and disease vulnerability, emphasize the need for a multimodal therapeutic approach, and suggests a mechanism for observed worse outcomes in MetS patients with COVID-19 comorbidity.

60 APPLIED LIFE SCIENCES↗

Surface-mediated spontaneous emulsification of the acylated peptide, semaglutide

Acylated peptides composed of glucagon-like peptide-1 receptor agonists modified with a fatty acid side chain are an important class of therapeutics for type 2 diabetes and obesity but are susceptible to an unusual physical instability in the presence of hydrophobic surfaces, i.e., spontaneous emulsification, also known as ouzo formation in practice. In this work, light scattering, small-angle X-ray scattering, and circular dichroism measurements are used to characterize the physical properties of the semaglutide colloidal phase, including size distribution, shape, secondary structure, internal structure, and internal composition, as a function of solution physico-chemical conditions. The existence and size of the colloids formed are successfully predicted by a classical Rayleigh model, which identifies the parameters controlling their size and formation. Colloid formation is found to be catalyzed by hydrophobic surfaces, and formation rates are modeled as an autocatalytic reaction, enabling the formation of a master curve for various surfaces that elucidates the mechanism. Surfaces differ due to differences in surface wettability, which can be correlated with Hansen solubility parameters. This work provides insights into this unusual colloidal phenomenon and guides the peptide synthesis process and drug product formulation in the pharmaceutical industry.

59 BASIC BIOLOGICAL SCIENCES↗

Dinickel enzyme evolved to metabolize the pharmaceutical metformin and its implications for wastewater and human microbiomes

Metformin is the first-line treatment for type II diabetes patients and a pervasive pollutant with more than 180 million kg ingested globally and entering wastewater. The drug’s direct mode of action is currently unknown but is linked to effects on gut microbiomes and may involve specific gut microbial reactions to the drug. In wastewater treatment plants, metformin is known to be transformed by microbes to guanylurea, although genes encoding this metabolism had not been elucidated. In the present study, we revealed the function of two genes responsible for metformin decomposition (mfmA and mfmB) found in isolated bacteria from activated sludge. MfmA and MfmB form an active heterocomplex (MfmAB) and are members of the ureohydrolase protein superfamily with binuclear metal-dependent activity. MfmAB is nickel-dependent and catalyzes the hydrolysis of metformin to dimethylamine and guanylurea with a catalytic efficiency (k cat /K M ) of 9.6 × 10 3 M -1 s -1 and KM for metformin of 0.82 mM. MfmAB shows preferential activity for metformin, being able to discriminate other close substrates by several orders of magnitude. Crystal structures of MfmAB show coordination of binuclear nickel bound in the active site of the MfmA subunit but not MfmB subunits, indicating that MfmA is the active site for the MfmAB complex. Mutagenesis of residues conserved in the MfmA active site revealed those critical to metformin hydrolase activity and its small substrate binding pocket allowed for modeling of bound metformin. In conclusion, this study characterizes the products of the mfmAB genes identified in wastewater treatment plants on three continents, suggesting that metformin hydrolase is widespread globally in wastewater.

59 BASIC BIOLOGICAL SCIENCES↗

Mortality among workers at the Los Alamos National Laboratory, 1943–2017

During World War II (WWII), the Manhattan Engineering District established a secret laboratory in the mountains of northern New Mexico. The mission was to design, construct and test the first atomic weapon, nicknamed ‘The Gadget’ that was detonated at the TRINITY site in Alamogordo, NM. After WWII, nuclear weapons research continued, and the laboratory became the Los Alamos National Laboratory (LANL). The mortality experience of 26,328 workers first employed between 1943 and 1980 at LANL was determined through 2017. Included were 6157 contract workers employed by the ZIA Company. Organ dose estimates for each worker considered all sources of exposure, notably photons, neutrons, tritium, 238Pu and 239Pu. Vital status determination included searches within the National Death Index, Social Security Administration and New Mexico State Mortality Files. Standardized Mortality Ratios (SMR) and Cox regression models were used in the analyses. Most workers (55%) were hired before 1960, 38% had a college degree, 25% were female, 81% white, 13% Hispanic and 60% had died. Vital status was complete, with only 0.1% lost to follow-up. The mean dose to the lung for the 17,053 workers monitored for radiation was 28.6 weighted-mGy (maximum 16.8 weighted-Gy) assuming a Dose Weighting Factor of 20 for alpha particle dose to lung. The Excess Relative Risk (ERR) at 100 weighted-mGy was 0.01 (95%CI -0.02, 0.03; n = 839) for lung cancer. The ERR at 100 mGy was -0.43 (95%CI -1.11, 0.24; n = 160) for leukemia other than chronic lymphocytic leukemia (CLL), -0.06 (95%CI -0.16, 0.04; n = 3043) for ischemic heart disease (IHD), and 0.29 (95%CI 0.02, 0.55; n = 106) for esophageal cancer. Among the 6499 workers with measurable intakes of plutonium, an increase in bone cancer (SMR 2.44; 95%CI 0.98, 5.03; n = 7) was related to dose. The SMR for berylliosis was significantly high, based on 4 deaths. SMRs for Hispanic workers were significantly high for cancers of the stomach and liver, cirrhosis of the liver, nonmalignant kidney disease and diabetes, but the excesses were not related to radiation dose. There was little evidence that radiation increased the risk of lung cancer or leukemia. Esophageal cancer was associated with radiation, and plutonium intakes were linked to an increase of bone cancer. IHD was not associated with radiation dose. More precise evaluations will await the pooled analysis of workers with similar exposures such as at Rocky Flats, Savannah River and Hanford.

63 RADIATION, THERMAL, AND OTHER ENVIRON. POLLUTAN↗

Machine Learning in Infectious Disease for Risk Factor Identification and Hypothesis Generation: Proof of Concept Using Invasive Candidiasis

Machine learning (ML) models can handle large data sets without assuming underlying relationships and can be useful for evaluating disease characteristics, yet they are more commonly used for predicting individual disease risk than for identifying factors at the population level. We offer a proof of concept applying random forest (RF) algorithms to Candida-positive hospital encounters in an electronic health record database of patients in the United States. Candida-positive encounters were extracted from the Cerner HealthFacts database; invasive infections were laboratory-positive sterile site Candida infections. Features included demographics, admission source, care setting, physician specialty, diagnostic and procedure codes, and medications received before the first positive Candida culture. We used RF to assess risk factors for 3 outcomes: any invasive candidiasis (IC) vs non-IC, within-species IC vs non-IC (eg, invasive C. glabrata vs noninvasive C. glabrata), and between-species IC (eg, invasive C. glabrata vs all other IC). Fourteen of 169 (8%) variables were consistently identified as important features in the ML models. When evaluating within-species IC, for example, invasive C. glabrata vs non-invasive C. glabrata, we identified known features like central venous catheters, intensive care unit stay, and gastrointestinal operations. In contrast, important variables for invasive C. glabrata vs all other IC included renal disease and medications like diabetes therapeutics, cholesterol medications, and antiarrhythmics. Known and novel risk factors for IC were identified using ML, demonstrating the hypothesis-generating utility of this approach for infectious disease conditions about which less is known, specifically at the species level or for rarer diseases.

60 APPLIED LIFE SCIENCES↗

PDB‐101: Molecular Explorations through Biology and Medicine

PDB‐101 is an online portal for teachers, students, and the general public to promote exploration of the structural biology of proteins and nucleic acids ( pdb101.rcsb.org ). Learning about the diverse shapes and functions of these biological macromolecules helps to understand all aspects of biomedicine and agriculture, from protein synthesis to health and disease to biological energy. Why PDB‐101? Researchers around the world are studying these molecules at the atomic level. These 3D structures are freely available at the Protein Data Bank (PDB), the central storehouse of biomolecular structures. This website builds introductory materials to help beginners get started in the basics of biomolecular structure and function (“101”, as in an entry level course) as well as resources for extended learning. Since 2011, PDB‐101 has been developed by the RCSB PDB , a global resource for the advancement of research and education in biology and medicine. Along with our Worldwide PDB collaborators, RCSB PDB curates, annotates, and makes publicly available the PDB data deposited by scientists around the globe. The RCSB PDB then provides a window to these data through a rich online resource with powerful searching, reporting, and visualization tools for researchers. This information is then streamlined for students and teachers at PDB‐101. Features include the ongoing Molecule of the Month series, educational materials such as paper models, posters, molecular animations, educational curricula and more. The section “Guide to Understanding PDB Data” is a primer for detailed PDB‐specific information: PDB Data, Visualizing Structures, Reading Coordinate Files, scientific methods for structure determination, and more. PDB‐101 also runs annual Video Challenges for high school students. Participants create short videos that tell molecular stories that connect structural biology and medicine. Previous topics have included HIV/AIDS, diabetes, and antimicrobial resistance. The 2022 challenge will focus on Molecular Mechanisms of Cancer. PDB‐101 activities are evaluated using user surveys, feedback from in‐person activities, and website analytics. In 2020, PDB‐101 hosted >850,000 users and >2.6 million page views.

Zardecki, Christine↗

Longitudinal Surveillance for Chronic Health Conditions in Former United States Department of Energy Site Workers

The aim of the study was to determine (1) the rate at which rescreening former Department of Energy site workers identifies noncommunicable chronic diseases and (2) the development of comorbid conditions. Incidence and prevalence of hypertension, diabetes, reduced kidney function, and peripheral neuropathy at both initial and return screenings were calculated. Risk ratio of chronic disease development at return screening based on the presence of other conditions at initial screening were estimated with generalized linear regression. Prevalence of reduced kidney function was 19% at initial examination and 30% at return examination. The screening program was responsible for identifying 81% of reduced kidney function cases. Similar findings were present for the other chronic conditions examined. As a result, former worker health surveillance programs help identify significant health conditions among DOE workers, subcontractors, and visitors. Longitudinal screening of participants detects additional chronic conditions.

59 BASIC BIOLOGICAL SCIENCES↗

cotH Genes Are Necessary for Normal Spore Formation and Virulence in Mucor lusitanicus

Mucormycosis is an invasive fungal infection caused by certain members of the fungal order of Mucorales. The species most frequently identified as the etiological agents of mucormycosis belong to the genera Rhizopus , Lichtheimia , and Mucor . The frequency of systemic mucormycosis has been increasing, mainly because of increasing numbers of susceptible patients. Furthermore, Mucorales display intrinsic resistance to the majority of routinely used antifungal agents (e.g., echinocandins and short-tailed azoles), which limits the number of possible therapeutic options. All the above-mentioned issues urge the improvement of molecular identification methods and the discovery of new antifungal targets and strategies. Spore coat proteins (CotH) constitute a kinase family present in many pathogenic bacteria and fungi and participate in the spore formation in these organisms. Moreover, some of them can act as virulence factors being receptors of the human GRP78 protein during Rhizopus delemar-induced mucormycosis. We identified 17 cotH -like genes in the Mucor lusitanicus genome database. Successful disruption of five cotH genes in Mucor was performed using the CRISPR-Cas9 system. The CotH3 and CotH4 proteins play a role in adaptation to different temperatures as well as in developing the cell wall structure. We also show CotH4 protein is involved in spore wall formation by affecting the total chitin content and, thus, the composition of the spore wall. The role of CotH3 and CotH4 proteins in virulence was confirmed in two invertebrate models and a diabetic ketoacidosis (DKA) mouse model.

59 BASIC BIOLOGICAL SCIENCES↗