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At least 1,045 records · Page 58

Antibody dynamics to SARS‐CoV‐2 in asymptomatic COVID‐19 infections

Abstract Background The missing asymptomatic COVID‐19 infections have been overlooked because of the imperfect sensitivity of the nucleic acid testing (NAT). Globally understanding the humoral immunity in asymptomatic carriers will provide scientific knowledge for developing serological tests, improving early identification, and implementing more rational control strategies against the pandemic. Measure Utilizing both NAT and commercial kits for serum IgM and IgG antibodies, we extensively screened 11 766 epidemiologically suspected individuals on enrollment and 63 asymptomatic individuals were detected and recruited. Sixty‐three healthy individuals and 51 mild patients without any preexisting conditions were set as controls. Serum IgM and IgG profiles were further probed using a SARS‐CoV‐2 proteome microarray, and neutralizing antibody was detected by a pseudotyped virus neutralization assay system. The dynamics of antibodies were analyzed with exposure time or symptoms onset. Results A combination test of NAT and serological testing for IgM antibody discovered 55.5% of the total of 63 asymptomatic infections, which significantly raises the detection sensitivity when compared with the NAT alone (19%). Serum proteome microarray analysis demonstrated that asymptomatics mainly produced IgM and IgG antibodies against S1 and N proteins out of 20 proteins of SARS‐CoV‐2. Different from strong and persistent N‐specific antibodies, S1‐specific IgM responses, which evolved in asymptomatic individuals as early as the seventh day after exposure, peaked on days from 17 days to 25 days, and then disappeared in two months, might be used as an early diagnostic biomarker. 11.8% (6/51) mild patients and 38.1% (24/63) asymptomatic individuals did not produce neutralizing antibody. In particular, neutralizing antibody in asymptomatics gradually vanished in two months. Conclusion Our findings might have important implications for the definition of asymptomatic COVID‐19 infections, diagnosis, serological survey, public health, and immunization strategies.

Lei, Qing↗

The association between vaginal microbiota disorders and early missed abortion: A prospective study

Abstract Introduction The objective of this study was to explore the association between disordered vaginal microbiota and missed abortion to ascertain potential causes of missed abortion related to vaginal microbiology. Material and methods This study was a prospective cohort study with a comparison group (reference group). Vaginal secretions from the posterior fornix of women in the early stages of pregnancy were collected in the Xiangya Third Hospital of Central South University in Changsha, Hunan, China, from November 2018 to November 2019. A total of 54 cases of missed abortion (case group) and 50 cases of normal pregnancy requiring induced abortion (reference group) were analyzed. Bacterial DNA was extracted, hybridized with gene‐specific primers, and then detected using a bacterial chip. The composition and relative abundance of vaginal microbiota in the two groups were compared using α‐diversity analysis, β‐diversity analysis, and the linear discriminant analysis effect size method. Results The α‐diversity analysis showed that the Simpson index of the case group was lower than that of the reference group, whereas the Shannon index in the case group was higher. The relative abundance of Firmicutes in the case group (42.52%) was lower than in the reference group (51.03%, p < 0.05), as was the relative abundance of Lactobacillus (case group 16.51%, reference group 23.00%; p < 0.05). Interestingly, levels of Mycoplasma genitalium and Ureaplasma were lower in the case group ( p < 0.05). The relative abundance of Lactobacillus crispatus , Lactobacillus jensenii , and Lactobacillus gasseri was also significantly lower in the case group than in the reference group ( p < 0.05). The pathways enriched in the case group were predominantly related to metabolism, whereas the genetics‐related pathways were predominantly enriched in the reference group. Conclusions Bacteria are more diverse and unevenly distributed in patients with missed abortion. Decreases in the proportion of vaginal Lactobacillus and changes in Lactobacillus species in these patients may increase the chance of genital tract pathogenic bacterial infection. To our knowledge, our study was the first to observe that a decrease of Firmicutes levels in the vaginal microbiota might impair energy metabolism and have an association with missed abortion.

Sun, Dan↗

Novel CHI3L1 ‐Associated Angiogenic Phenotypes Define Glioma Microenvironments: Insights From Multi‐Omics Integration

ABSTRACT The CHI3L1 signaling pathway significantly influences glioma angiogenesis, but its role in the tumor microenvironment (TME) remains elusive. We propose a novelCHI3L1‐associated vascular phenotype classification for glioma through integrative analyses of multiple datasets with bulk and single‐cell transcriptome, genomics, digital pathology, and clinical data. We investigated the biological characteristics, genomic alterations, therapeutic vulnerabilities, and immune profiles within these phenotypes through a comprehensive multi‐omics approach. We constructed the vascular‐related risk (VR) score based onCHI3L1‐associated vascular signatures (CAVS) identified by machine learning algorithms. Utilizing unsupervised consensus clustering, gliomas were stratified into three distinct vascular phenotypes: Cluster A, marked by high vascularization and stromal activation with a relatively low levels of tumor‐infiltrating lymphocytes (TILs); Cluster B, characterized by moderate vascularization and stromal activity, coupled with a high density of TILs; and Cluster C, defined by low vascularization and sparse immune cell infiltration. We observed that the CAVS effectively indicated glioma‐associated angiogenesis and immune suppression by single‐cell RNA‐seq analysis. Moreover, the high‐VR‐score group exhibited enhanced angiogenic activity, reduced immune response, resistance to immunotherapy, and poorer clinical outcomes. The VR score independently predicted glioma prognosis and, combined with a nomogram, provided a robust clinical decision‐making tool. Potential drug prediction based on transcription factors for high‐risk patients was also performed. Our study reveals thatCHI3L1‐associated vascular phenotypes shape distinct immune landscapes in gliomas, offering insights for optimizing therapeutic strategies to improve patient outcomes.

Oncology↗

Pediatric dosing for locally acting drugs in submissions to the U.S. Food and Drug Administration between 2002 and 2020

Abstract Deriving pediatric doses for locally acting drugs (LADs) presents a unique challenge because limited systemic exposure hinders commonly used approaches such as pharmacokinetic matching to adults. This study systematically evaluated drug development practices used for pediatric dose selection of LADs approved by the U.S. Food and Drug Administration from 2002 to 2020. The three study objectives were: (1) to determine the dose selection approach for the labeled pediatric dose, (2) to examine the studied pediatric dose(s), and (3) to evaluate the characteristics of the pediatric clinical programs used to support the labeled pediatric dose. A total of 187 pediatric submissions were characterized for the labeled and studied pediatric doses of LADs. The pediatric dose was predominantly labeled as a flat dose (91%) and at a single‐dose level (67%) similar to adults. The majority (68.4%) of the submissions had the same labeled dose for pediatrics and adults. Independent pharmacodynamic/efficacy studies in pediatric patients commonly (64.2%) provided supportive evidence for the labeled pediatric dose. Inhalation, nasal, and injectable submissions had the highest number of clinical trials, lowest usage of an extrapolation of efficacy approach, and utilized diverse approaches in selecting the studied pediatric doses. This article highlights approaches for LAD dosing in pediatric patients and can be used to inform drug development of these products in the pediatric population.

Research & Experimental Medicine↗

Announcing the Biomedical Data Translator: Initial Public Release

ABSTRACT The growing availability of biomedical data offers vast potential to improve human health, but the complexity and lack of integration of these datasets often limit their utility. To address this, the Biomedical Data Translator Consortium has developed an open‐source knowledge graph–based system—Translator—designed to integrate, harmonize, and make inferences over diverse biomedical data sources. We announce here Translator's initial public release and provide an overview of its architecture, standards, user interface, and core features. Translator employs a scalable, federated, knowledge graph framework for the integration of clinical, genomic, pharmacological, and other biomedical knowledge sources, enabling query retrieval, inference, and hypothesis generation. Translator's user interface is designed to support the exploration of knowledge relationships and the generation of insights, without requiring deep technical expertise and gradually revealing more detailed evidence, provenance, and confidence information, as needed by a given user. To demonstrate Translator's application and impact, we highlight features of the user interface in the context of three real‐world use cases: suggesting potential therapeutics for patients with rare disease; explaining the mechanism of action of a pipeline drug; and screening and validating drug candidates in a model organism. We discuss strengths and limitations of reasoning within a largely federated system and the need for rich concept modeling and deep provenance tracking. Finally, we outline future directions for enhancing Translator's functionality and expanding its data sources. Translator represents a significant step forward in making complex biomedical knowledge more accessible and actionable, aiming to accelerate translational research and improve patient care.

Research & Experimental Medicine↗

Activated KCNQ1 channel promotes fibrogenic response in hereditary gingival fibromatosis via clustering and activation of Ras

Abstract Background and Objective Activated potassium channels were found to be strongly correlated with gingival overgrowth (GO) phenotype as we reviewed syndromic hereditary gingival fibromatosis (HGF). Nevertheless, the functional roles of potassium channels in gingival fibrosis or gingival overgrowth remained uncovered. The aim of the present study was to explore the pathogenic role of aberrantly activated potassium channel in Hereditary Gingival Fibromatosis (HGF). Methods Gingival tissues were collected from 9 HGF patients and 15 normal controls. Expression of KCNQ1 was detected by immunohistochemistry. Gingival fibroblasts were isolated, and outward K + currents were detected by whole‐cell patch‐clamp analysis, transmembrane potential was determined by flow cytometry. Normal human gingival fibroblasts (NHGFs) were transfected with KCNQ1 adenovirus or treated with KCNQ1 selective agonist ML277 and antagonist chromanol 293B. Accumulation of Extracellular Matrix (ECM) was measured by Western blotting and Sircol Soluble Collagen Assay. Content of secreted TGF‐β1 was measured by ELISA. Active RAS pull‐down assay and cell immunofluorescence were utilized to verify RAS activation. Results KCNQ1 was upregulated in gingival tissues derived from HGF patients and HGF gingival fibroblasts presented increased outward K + currents than NHGFs. Overexpression of KCNQ1, or KCNQ1 agonist ML277, promoted fibrotic responses of NHGFs. TGF‐β1 and KCNQ1 channels formed a positive feed‐back loop. ML277 generated lateral clustering and activation of Ras on plasma membrane, followed by augmented MAPK/AP‐1 signaling pathway output. JNK or ERK1/2 inhibitors suppressed ML277‐induced AP‐1 and ECM upregulation. Conclusion Activation of KCNQ1 potassium channel promoted fibrogenic responses in NHGFs via Ras/MAPK/AP‐1 signaling.

Gao, Qian↗

Neighborhood sociome factors and pediatric asthma exacerbations: Protective role of tree crown density and importance of pharmacy access in Chicago's south side

Abstract Background Pediatric asthma exacerbations remain a critical public health concern, particularly in historically underserved urban settings. Objective This study investigates sociome factors—the social context of disease—associated with asthma exacerbations among children living in Chicago's South Side, leveraging clinical and publicly available generalizable census tract‐level datasets from agencies including ChiVes, the City of Chicago Data Portal, EPA, Census Bureau, HUD, NOAA, and more. The aim is to uncover novel hypotheses for potential new interventions. Methods A generalized linear model assessed associations with the outcome of asthma exacerbations while accounting for clustering at the patient level. Predictors included all variables from the Sociome Data Commons, including social, environmental, behavioral, economic, housing, and school variables. Results Predictors of decreased risk included patient age (+4.8 years, −22%), tree crown density (+6% coverage, −17%), parks per acre (+0.41, −8%), and labor market engagement (+0.8 points, −9%). Conversely, predictors of increased risk included increased distance to the nearest pharmacy (+0.28 miles, +12%), limited English skills (+2.3%, +10%), higher inequality (+0.08 points, +8%), and visits in the Spring (+11%) and Fall (+20%). Conclusion The results suggest that tree crown density, a novel finding in the context of asthma exacerbations, may play a protective role. Limited access to health care facilities such as pharmacies continues to complicate care. Clinical Implications These findings provide hypotheses for future interventions for long‐standing asthma disparities.

Allergy↗

PpIX‐enabled fluorescence‐based detection and photodynamic priming of platinum‐resistant ovarian cancer cells under fluid shear stress

Over 75% percent of ovarian cancer patients are diagnosed with advanced-stage disease characterized by unresectable intraperitoneal dissemination and the presence of ascites, or excessive fluid build-up within the abdomen. Conventional treatments include cytoreductive surgery followed by multi-line platinum and taxane chemotherapy regimens. Despite an initial response to treatment, over 75% of patients with advanced-stage ovarian cancer will relapse and succumb to platinum-resistant disease. Recent evidence suggests that fluid shear stress (FSS), which results from the movement of fluid such as ascites, induces epithelial-to-mesenchymal transition and confers resistance to carboplatin in ovarian cancer cells. This study demonstrates, for the first time, that FSS-induced platinum resistance correlates with increased cellular protoporphyrin IX (PpIX), the penultimate downstream product of heme biosynthesis, the production of which can be enhanced using the clinically approved pro-drug aminolevulinic acid (ALA). These data suggest that, with further investigation, PpIX could serve as a fluorescence-based biomarker of FSS-induced platinum resistance. Additionally, this study investigates the efficacy of PpIX-enabled photodynamic therapy (PDT) and the secretion of extracellular vesicles under static and FSS conditions in Caov-3 and NIH:OVCAR-3 cells, two representative cell lines for high-grade serous ovarian carcinoma (HGSOC), the most lethal form of the disease. FSS induces resistance to ALA-PpIX-mediated PDT, along with a significant increase in the number of EVs. Finally, the ability of PpIX-mediated photodynamic priming (PDP) to enhance carboplatin efficacy under FSS conditions is quantified. These preliminary findings in monolayer cultures necessitate additional studies to determine the feasibility of PpIX as a fluorescence-based indicator, and mediator of PDP, to target chemoresistance in the context of FSS.

59 BASIC BIOLOGICAL SCIENCES↗

Pressured cytotoxic T cell epitope strength among SARS-CoV-2 variants correlates with COVID-19 severity

Heterogeneity in susceptibility among individuals to COVID-19 has been evident through the pandemic worldwide. Cytotoxic T lymphocyte (CTL) responses generated against pathogens in certain individuals are known to impose selection pressure on the pathogen, thus driving emergence of new variants. In this study, we probe the role played by host genetic heterogeneity in terms of HLA-genotypes in determining differential COVID-19 severity in patients. We use bioinformatic tools for CTL epitope prediction to identify epitopes under immune pressure. Using HLA-genotype data of COVID-19 patients from a local cohort, we observe that the recognition of pressured epitopes from the parent strain Wuhan-Hu-1 correlates with COVID-19 severity. We also identify and rank list HLA-alleles and epitopes that offer protectivity against severe disease in infected individuals. Finally, we shortlist a set of 6 pressured and protective epitopes that represent regions in the viral proteome that are under high immune pressure across SARS-CoV-2 variants. In conclusion, identification of such epitopes, defined by the distribution of HLA-genotypes among members of a population, could potentially aid in prediction of indigenous variants of SARS-CoV-2 and other pathogens.

60 APPLIED LIFE SCIENCES↗

Feasibility of Vascular Parameter Estimation for Assessing Hypertensive Pregnancy Disorders

Abstract Hypertensive pregnancy disorders (HPDs), such as pre-eclampsia, are leading sources of both maternal and fetal morbidity in pregnancy. Noninvasive imaging, such as ultrasound (US) and magnetic resonance imaging (MRI), is an important tool for predicting and monitoring these high risk pregnancies. While imaging can measure hemodynamic parameters, such as uterine artery pulsatility and resistivity indices (PI and RI), the interpretation of such metrics for disease assessment relies on ad hoc standards, which provide limited insight to the physical mechanisms underlying the emergence of hypertensive pregnancy disorders. To provide meaningful interpretation of measured hemodynamic data in patients, advances in computational fluid dynamics can be brought to bear. In this work, we develop a patient-specific computational framework that combines Bayesian inference with a reduced-order fluid dynamics model to infer parameters, such as vascular resistance, compliance, and vessel cross-sectional area, known to be related to the development of hypertension. The proposed framework enables the prediction of hemodynamic quantities of interest, such as pressure and velocity, directly from sparse and noisy MRI measurements. We illustrate the effectiveness of this approach in two systemic arterial network geometries: an aorta with branching carotid artery and a maternal pelvic arterial network. For both cases, the model can reconstruct the provided measurements and infer parameters of interest. In the case of the maternal pelvic arteries, the model can make a distinction between the pregnancies destined to develop hypertension and those that remain normotensive, expressed through the value range of the predicted absolute pressure.

Biophysics↗

JAK inhibition reduces SARS-CoV-2 liver infectivity and modulates inflammatory responses to reduce morbidity and mortality

Using AI, we identified baricitinib as having antiviral and anticytokine efficacy. We now show a 71% (95% CI 0.15 to 0.58) mortality benefit in 83 patients with moderate-severe SARS-CoV-2 pneumonia with few drug-induced adverse events, including a large elderly cohort (median age, 81 years). An additional 48 cases with mild-moderate pneumonia recovered uneventfully. Using organotypic 3D cultures of primary human liver cells, we demonstrate that interferon-α2 increases ACE2 expression and SARS-CoV-2 infectivity in parenchymal cells by greater than fivefold. RNA-seq reveals gene response signatures associated with platelet activation, fully inhibited by baricitinib. Using viral load quantifications and superresolution microscopy, we found that baricitinib exerts activity rapidly through the inhibition of host proteins (numb-associated kinases), uniquely among antivirals. This reveals mechanistic actions of a Janus kinase-1/2 inhibitor targeting viral entry, replication, and the cytokine storm and is associated with beneficial outcomes including in severely ill elderly patients, data that incentivize further randomized controlled trials.

59 BASIC BIOLOGICAL SCIENCES↗

CDK4/6 inhibition enhances SHP2 inhibitor efficacy and is dependent upon RB function in malignant peripheral nerve sheath tumors

Malignant peripheral nerve sheath tumors (MPNSTs) are highly aggressive soft tissue sarcomas with limited treatment options, and new effective therapeutic strategies are desperately needed. We observe antiproliferative potency of genetic depletion of PTPN11 or pharmacological inhibition using the SHP2 inhibitor (SHP2i) TNO155. Our studies into the signaling response to SHP2i reveal that resistance to TNO155 is partially mediated by reduced RB function, and we therefore test the addition of a CDK4/6 inhibitor (CDK4/6i) to enhance RB activity and improve TNO155 efficacy. In combination, TNO155 attenuates the adaptive response to CDK4/6i, potentiates its antiproliferative effects, and converges on enhancement of RB activity, with greater suppression of cell cycle and inhibitor-of-apoptosis proteins, leading to deeper and more durable antitumor activity in in vitro and in vivo patient-derived models of MPNST, relative to either single agent. Overall, our study provides timely evidence to support the clinical advancement of this combination strategy in patients with MPNST and other tumors driven by loss of NF1.

60 APPLIED LIFE SCIENCES↗

In vitro selection and analysis of SARS-CoV-2 nirmatrelvir resistance mutations contributing to clinical virus resistance surveillance

To facilitate the detection and management of potential clinical antiviral resistance, in vitro selection of drug-resistant severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) against the virus M pro inhibitor nirmatrelvir (Paxlovid active component) was conducted. Six M pro mutation patterns containing T304I alone or in combination with T21I, L50F, T135I, S144A, or A173V emerged, with A173V+T304I and T21I+S144A+T304I mutations showing >20-fold resistance each. Biochemical analyses indicated inhibition constant shifts aligned to antiviral results, with S144A and A173V each markedly reducing nirmatrelvir inhibition and M pro activity. SARS-CoV-2 surveillance revealed that in vitro resistance–associated mutations from our studies and those reported in the literature were rarely detected in the Global Initiative on Sharing All Influenza Data database. In the Paxlovid Evaluation of Protease Inhibition for COVID-19 in High-Risk Patients trial, E166V was the only emergent resistance mutation, observed in three Paxlovid-treated patients, none of whom experienced COVID-19–related hospitalization or death.

60 APPLIED LIFE SCIENCES↗

A novel conjugative transposon carrying an autonomously amplified plasmid

Tetracyclines serve as broad-spectrum antibiotics to treat bacterial infections. The discovery of new tetracycline resistance genes has led to new questions about the underlying mechanisms of resistance, gene transfer, and their relevance to human health. We tracked changes in the abundance of a 55-kbp conjugative transposon (CTn214) carrying tetQ, a tetracycline resistance gene, within a Bacteroides fragilis metagenome-assembled genome derived from shotgun sequencing of microbial DNA extracted from the ileal pouch of a patient with ulcerative colitis. The mapping of metagenomic reads to CTn214 revealed the multi-copy nature of a 17,044-nt region containing tetQ in samples collected during inflammation and uninflamed visits. B. fragilis cultivars isolated from the same patient during periods of inflammation harbored CTn214 integrated into the chromosome or both a circular, multi-copy, extrachromosomal region of the CTn214 containing tetQ and the corresponding integrated form. The tetracycline-dependent mechanism for the transmission of CTn214 is nearly identical to a common conjugative transposon found in the genome of B. fragilis (CTnDOT), but the autonomously amplified nature of a circular 17,044-nt region of CTn214 that codes for tetQ and the integration of the same sequence in the linear chromosome within the same cell is a novel observation. Genome and transcriptome sequencing of B. fragilis cultivars grown under different concentrations of tetracycline and ciprofloxacin indicates that tetQ in strains containing the circular form remains actively expressed regardless of treatment, while the expression of tetQ in strains containing the linear form increases only in the presence of tetracycline.

59 BASIC BIOLOGICAL SCIENCES↗

Genetic Predictive Factors for Nonsusceptible Phenotypes and Multidrug Resistance in Expanded-Spectrum Cephalosporin-Resistant Uropathogenic Escherichia coli from a Multicenter Cohort: Insights into the Phenotypic and Genetic Basis of Coresistance

Antimicrobial resistance in urinary tract infections (UTIs) is a major public health concern. This study aims to characterize the phenotypic and genetic basis of multidrug resistance (MDR) among expanded-spectrum cephalosporin-resistant (ESCR) uropathogenic Escherichia coli (UPEC) causing UTIs in California patient populations. Between February and October 2019, 577 ESCR UPEC isolates were collected from patients at 6 clinical laboratory sites across California. Lineage and antibiotic resistance genes were determined by analysis of whole-genome sequence data. The lineages ST131, ST1193, ST648, and ST69 were predominant, representing 46%, 5.5%, 4.5%, and 4.5% of the collection, respectively. Overall, 527 (91%) isolates had an expanded-spectrum β-lactamase (ESBL) phenotype, with bla CTX-M-15 , bla CTX-M-27 , bla CTX-M-55 , and bla CTX-M-14 being the most prevalent ESBL genes. In the 50 non-ESBL phenotype isolates, 40 (62%) contained bla CMY-2 , which was the predominant plasmid-mediated AmpC (pAmpC) gene. Narrow-spectrum β-lactamases, bla TEM-1B and bla OXA-1 , were also found in 44.9% and 32.1% of isolates, respectively. Among ESCR UPEC isolates, isolates with an ESBL phenotype had a 1.7-times-greater likelihood of being MDR than non-ESBL phenotype isolates (P < 0.001). The cooccurrence of bla CTX-M-15 , bla OXA-1 , and aac(6')-Ib-cr within ESCR UPEC isolates was strongly correlated. Cooccurrence of bla CTX-M-15 , bla OXA-1 , and aac(6')-Ib-cr was associated with an increased risk of nonsusceptibility to piperacillin-tazobactam, cefepime, fluoroquinolones, and amikacin as well as MDR. Multivariate regression revealed the presence of bla CTX-M-55 , bla TEM-1B , and the ST131 genotype as predictors of MDR.

59 BASIC BIOLOGICAL SCIENCES↗

Genomic analysis and identification of a novel superantigen, SargEY, in Staphylococcus argenteus isolated from atopic dermatitis lesions

During surveillance of Staphylococcus aureus in lesions from patients with atopic dermatitis (AD), we isolated Staphylococcus argenteus, a species registered in 2011 as a new member of the genus Staphylococcus and previously considered a lineage of S. aureus. Genome sequence comparisons between S. argenteus isolates and representative S. aureus clinical isolates from various origins revealed that the S. argenteus genome from AD patients closely resembles that of S. aureus causing skin infections. We previously reported that 17%–22% of S. aureus isolated from skin infections produce staphylococcal enterotoxin Y (SEY), which predominantly induces T-cell proliferation via the T-cell receptor (TCR) Vα pathway. Complete genome sequencing of S. argenteus isolates revealed a gene encoding a protein similar to superantigen SEY, designated as SargEY, on its chromosome. Population structure analysis of S. argenteus revealed that these isolates are ST2250 lineage, which was the only lineage positive for the SEY-like gene among S. argenteus. Recombinant SargEY demonstrated immunological cross-reactivity with anti-SEY serum. SargEY could induce proliferation of human CD4 + and CD8 + T cells, as well as production of TNF-α and IFN-γ. SargEY showed emetic activity in a marmoset monkey model. S arg EY and SET (a phylogenetically close but uncharacterized SE) revealed their dependency on TCR Vα in inducing human T-cell proliferation. Additionally, TCR sequencing revealed other previously undescribed Vα repertoires induced by SEH. S arg EY and SEY may play roles in exacerbating the respective toxin-producing strains in AD.

59 BASIC BIOLOGICAL SCIENCES↗

A bacterial sensor taxonomy across earth ecosystems for machine learning applications

Microbial communities have evolved to colonize all ecosystems of the planet, from the deep sea to the human gut. Microbes survive by sensing, responding, and adapting to immediate environmental cues. This process is driven by signal transduction proteins such as histidine kinases, which use their sensing domains to bind or otherwise detect environmental cues and “transduce” signals to adjust internal processes. We hypothesized that an ecosystem’s unique stimuli leave a sensor “fingerprint,” able to identify and shed insight on ecosystem conditions. To test this, we collected 20,712 publicly available metagenomes from Host-associated, Environmental, and Engineered ecosystems across the globe. We extracted and clustered the collection’s nearly 18M unique sensory domains into 113,712 similar groupings with MMseqs2. We built gradient-boosted decision tree machine learning models and found we could classify the ecosystem type (accuracy: 87%) and predict the levels of different physical parameters (R2 score: 83%) using the sensor cluster abundance as features. Feature importance enables identification of the most predictive sensors to differentiate between ecosystems which can lead to mechanistic interpretations if the sensor domains are well annotated. To demonstrate this, a machine learning model was trained to predict patient’s disease state and used to identify domains related to oxygen sensing present in a healthy gut but missing in patients with abnormal conditions. Moreover, since 98.7% of identified sensor domains are uncharacterized, importance ranking can be used to prioritize sensors to determine what ecosystem function they may be sensing. Furthermore, these new predictive sensors can function as targets for novel sensor engineering with applications in biotechnology, ecosystem maintenance, and medicine.

97 MATHEMATICS AND COMPUTING↗

Serodominant SARS-CoV-2 Nucleocapsid Peptides Map to Unstructured Protein Regions

The SARS-CoV-2 nucleocapsid (N) protein is highly immunogenic, and anti-N antibodies are commonly used as markers for prior infection. While several studies have examined or predicted the antigenic regions of N, these have lacked consensus and structural context. Using COVID-19 patient sera to probe an overlapping peptide array, we identified six public and four private epitope regions across N, some of which are unique to this study. We further report the first deposited X-ray structure of the stable dimerization domain at 2.05 Å as similar to all other reported structures. Structural mapping revealed that most epitopes are derived from surface-exposed loops on the stable domains or from the unstructured linker regions. An antibody response to an epitope in the stable RNA binding domain was found more frequently in sera from patients requiring intensive care. Since emerging amino acid variations in N map to immunogenic peptides, N protein variation could impact detection of seroconversion for variants of concern.

60 APPLIED LIFE SCIENCES↗