Biology subjects

Kim, E.

Publications and source records attributed to Kim, E..

At least 127 records · Page 7Linked to original sources

bioRxiv2022

Turing Test Inspired Method for Analysis of Biases Prevalent in Artificial Intelligence-Based Medical Imaging

AO_SCPLOWBSTRACTC_SCPLOWO_ST_ABSBackgroundC_ST_ABSBecause of the growing need to provide better global healthcare, computer-based and robotic healthcare equipment that depend on artificial intelligence have seen an increase in development. In order to evaluate artificial intelligence (AI) in computer technology, the Turing test was created. For evaluating the future generation of medical diagnostics and medical robots, it remains an essential qualitative instrument. MethodWe propose a novel methodology to assess AI-based healthcare technology that provided verifiable diagnostic accuracy and statistical robustness. In order to run our test, we used a State-of-the-art AI model and compared it against radiologist for checking how generalized of the model is and if any biases are prevalent. ResultsWe achieved results that can evaluate the performance of our chosen model for this study in a clinical setting and we also applied a quantifiable methods for evaluating our modified turing test results using a meta-analytical evaluation framework. ConclusionThis test provides a translational standard for upcoming AI modalities. Our modified Turing Test is a notably strong standard to measure the actual performance of the AI model on a variety of edge cases and normal cases and also helps in detecting if the algorithm is biased towards any one type of case. This method extends the flexibility detect any prevalent biases and also classify the type of bias.

bioinformatics↗

bioRxiv2022

The Smc5/6 complex is a DNA loop extruding motor

Structural Maintenance of Chromosomes (SMC) protein complexes are essential for the spatial organization of chromosomes. While cohesin and condensin organize chromosomes by extruding DNA loops, the molecular functions of the third eukaryotic SMC complex, Smc5/6, remain largely unknown. Using single-molecule imaging, we reveal that Smc5/6 forms DNA loops by extrusion. Upon ATP-hydrolysis, Smc5/6 symmetrically reels DNA into loops at a force-dependent rate of 1 kilobase pairs per second. Smc5/6 extrudes loops in the form of a dimer, while monomeric Smc5/6 unidirectionally translocate along DNA. We also find that Nse5 and Nse6 (Nse5/6) subunits act as negative regulators of Smc5/6-mediated loop initiation and stability. Our findings reveal Smc5/6s molecular functions, and establish loop extrusion as a conserved mechanism among eukaryotic SMC complexes. One-Sentence SummarySmc5/6 is a DNA-loop-extruding motor, establishing loop extrusion as a conserved mechanism among eukaryotic SMC complexes.

biophysics↗

bioRxiv2022

Adenovirus-Vectored SARS-CoV-2 Vaccine Expressing S1-N Fusion Protein

Additional COVID-19 vaccines that are safe, easy to manufacture, and immunogenic are needed for global vaccine equity. Here, we developed a recombinant type 5 adenovirus vector encoding for the SARS-CoV-2-S1 subunit antigen and nucleocapsid as a fusion protein (Ad5.SARS-CoV-2-S1N) delivered to BALB/c mice through multiple vaccine administration routes. A single subcutaneous (S.C.) immunization with Ad5.SARS-CoV-2-S1N induced a similar humoral response, along with a significantly higher S1-specific cellular response, as a recombinant type 5 adenovirus vector encoding for S1 alone (Ad5.SARS-CoV-2-S1). Immunogenicity was improved by homologous prime boost strategies, using either S.C. or intranasal (I.N.) delivery of Ad5.SARS-CoV-2-S1N, and further improved through heterologous prime boost, with traditional intramuscular (I.M.) injection, using subunit recombinant S1 protein. Priming with low dose (1x1010 v.p.) of Ad5.SARS-CoV-2-S1N and boosting with either wildtype recombinant rS1 or B.1.351 recombinant rS1 induced a robust neutralizing response, that was sustained against immune evasive Beta and Gamma SARS-CoV-2 variants, along with a long-lived plasma cell response in the bone marrow 29 weeks post vaccination. This novel Ad5-vectored SARS-CoV-2 vaccine candidate showed promising immunogenicity in mice and supports the further development of COVID-19 based vaccines incorporating the nucleoprotein as a target antigen.

immunology↗

bioRxiv2022

StandardRat: A multi-center consensus protocol to enhance functional connectivity specificity in the rat brain

Task-free functional connectivity in animal models provides an experimental framework to examine connectivity phenomena under controlled conditions and allows comparison with invasive or terminal procedures. To date, animal acquisitions are performed with varying protocols and analyses that hamper result comparison and integration. We introduce StandardRat, a consensus rat functional MRI acquisition protocol tested across 20 centers. To develop this protocol with optimized acquisition and processing parameters, we initially aggregated 65 functional imaging datasets acquired in rats from 46 centers. We developed a reproducible pipeline for the analysis of rat data acquired with diverse protocols and determined experimental and processing parameters associated with a more robust functional connectivity detection. We show that the standardized protocol enhances biologically plausible functional connectivity patterns, relative to pre-existing acquisitions. The protocol and processing pipeline described here are openly shared with the neuroimaging community to promote interoperability and cooperation towards tackling the most important challenges in neuroscience.

neuroscience↗

bioRxiv2022

RADGENNETS: DEEP LEARNING-BASED RADIOGENOMICS MODEL FOR GENE MUTATION PREDICTION IN LUNG CANCER

AO_SCPLOWBSTRACTC_SCPLOWIn this paper, we present our methodology that can be used for predicting gene mutation in patients with non-small cell lung cancer (NSCLC). There are three major types of gene mutations that a NSCLC patients gene structure can change to: epidermal growth factor receptor (EGFR), Kirsten rat sarcoma virus (KRAS), and Anaplastic lymphoma kinase (ALK). We worked with the clinical and genomics data for each patient as well CT scans. We preprocessed all of the data and then built a novel pipeline to integrate both the image and tabular data. We built a novel pipeline that used a fusion of Convolutional Neural Networks and Dense Neural Networks. Also, using a search approach, we pick an ensemble of deep learning models to classify the separate gene mutations. These models include EfficientNets, SENet, and ResNeXt WSL, among others. Our model achieved a high area under curve (AUC) score of 94% in detecting gene mutation.

cancer biology↗

bioRxiv2022

Digital data repository and automatic analysis framework for FDOPA PET neuroimaging

IntroductionFDOPA PET has been used extensively to image the human brain in many clinical disorders and has the potential to be used for patient stratification and individualized treatment. However, to reach its full and effective clinical translation, FDOPA PET requires both a robust data infrastructure and analytical protocol that are capable of ensuring high quality data and metadata, accurate biological quantification, and replicable results. In this study we evaluate a digital data repository and automated analytical framework for FDOPA PET neuroimaging that can produce an individualised quantification of dopamine synthesis capacity in the living human brain. MethodsThe imaging platform XNAT was used to store the Kings College London institutional brain FDOPA PET imaging archive, alongside individual demographics and clinical information. A fully automated analysis pipeline for imaging processing and data quantification was developed in Python and integrated in XNAT using the Docker technology. Reproducibility was assessed in test-retest datasets both in controls and patients with psychosis. The agreement between the automated analysis estimates and the results derived by the manual analysis were compared. Finally, using a sample of healthy controls (N=115), a sensitivity analysis was performed to explore the impact of experimental and demographic variables on the FDOPA PET measures. ResultsThe final data repository includes 892 FDOPA PET scans organized from 23 different studies, collected at five different imaging sites. After removing commercials studies, the infrastructure consisted of 792 FDOPA PET scans from 666 individuals (female 33.9%, healthy controls 29.1%) collected from four different imaging sites between 2004-2021. The automated analysis pipeline provided results that were in agreement with the results from the manual analysis, with a Pearsons correlation that ranged from 0.64 to 0.99 for Kicer, and from 0.79 to 1.00 for SUVR. The mean absolute difference between the two pipelines ranges from 3.4% to 9.4% for Kicer, and from 2.5% to 12.4% for SUVR. Moreover, we found good reproducibility of the data analysis by the automated pipeline (in the whole striatum for the Kicer: ICC for the controls = 0.71, ICC for the psychotic patients = 0.88). From the demographic and experimental variables assessed, gender was found to most influence striatal dopamine synthesis capacity (F = 10.7, p <0.001), with women showing greater dopamine synthesis capacity than men, while the effects of weight, age, injected radioactivity, and scanner, varied by brain region and parameter of interest. ConclusionsCombining information from different neuroimaging studies has allowed us to test comprehensively the automated pipeline for quantification of dopamine synthesis capacity using FDOPA PET data and to validate its replicability and reproducibility performances on a large sample size. This validation process is a necessary methodological step for the development of the clinical application of FDOPA PET as precision medicine biomarker. The proposed infrastructure is generalisable behind the FDOPA radiotracer.

bioengineering↗

bioRxiv2022

Brequinar and Dipyridamole in Combination Exhibits Synergistic Antiviral Activity Against SARS-CoV-2 in vitro: Rationale for a host-acting antiviral treatment strategy for COVID-19

The continued evolution of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has compromised the efficacy of currently available vaccines and monoclonal antibody (mAb)-based treatment options for COVID-19. The limited number of authorized small-molecule direct-acting antivirals present challenges with pill burden, the necessity for intravenous administration or potential drug interactions. There remains an unmet medical need for effective and convenient treatment options for SARS-CoV-2 infection. SARS-CoV-2 is an RNA virus that depends on host intracellular ribonucleotide pools for its replication. Dihydroorotate dehydrogenase (DHODH) is a ubiquitous host enzyme that is required for de novo pyrimidine synthesis. The inhibition of DHODH leads to a depletion of intracellular pyrimidines, thereby impacting viral replication in vitro. Brequinar (BRQ) is an orally available, selective, and potent low nanomolar inhibitor of human DHODH that has been shown to exhibit broad spectrum inhibition of RNA virus replication. However, host cell nucleotide salvage pathways can maintain intracellular pyrimidine levels and compensate for BRQ-mediated DHODH inhibition. In this report, we show that the combination of BRQ and the salvage pathway inhibitor dipyridamole (DPY) exhibits strong synergistic antiviral activity in vitro against SARS-CoV-2 by enhanced depletion of the cellular pyrimidine nucleotide pool. The combination of BRQ and DPY showed antiviral activity against the prototype SARS-CoV-2 as well as the Beta (B.1.351) and Delta (B.1.617.2) variants. These data support the continued evaluation of the combination of BRQ and DPY as a broad-spectrum, host-acting antiviral strategy to treat SARS-CoV-2 and potentially other RNA virus infections.

microbiology↗

bioRxiv2022

Containing Cancer with Personalized Minimum Effective Dose

Resistance to treatment is a challenge in many cancer therapies. This is partly due to the heterogeneous nature of tumors, where drug-sensitive and drug-resistant cells compete for the same resources. This competition is largely shaped by cancer treatment. The rapid reduction of drug-sensitive cell population during therapy with a maximum-tolerated dose relaxes competitive stress on the drug-resistant cell population, promoting relapse. Therefore, maintaining a high level of drug-sensitive cell population with a treatment break or lower dose can impose effective competitive stress on drug-resistant cell populations. Adaptive therapy (AT) exploits the competition between cancer cells. However, given the heterogeneous treatment response of individual patients, determining a personalized optimal treatment that can fine-tune competitive stress remains challenging. Using a deterministic model of cancer cell population competition, this study defines an effective dose window (EDW) as a range of doses that conserve sufficient sensitive cells, while maintaining the tumor volume below a threshold (e.g., initial tumor volume), to maintain a sustained competition against resistant cells. As a proof of concept, we sought to determine the EDW for a small cohort of patients with melanoma (n=8). We first fitted the model to longitudinal tumor response data from each patient. We performed structural and practical identifiability analyses to confirm the reproducibility and uniqueness of the estimated parameters. Then, we considered a subset of the cohort with uniquely identifiable parameters and estimated patient-specific EDW. We demonstrated that if the dose belongs to the EDW, the tumor volume for each patient could be indefinitely contained either using continuous or AT strategy. Using the optimal control theory, we concluded that the lower bound of the EDW approximates the minimum effective dose (MED) for containing cancer. Taken together, using tumor biomarker data, this study provides a proof of concept that there may exist a patient-specific EDW that keeps the tumor below a threshold (e.g., initial volume) by maintaining sustained competition on resistant cells.

cancer biology↗

bioRxiv2022

Individual behavioral trajectories shape whole-brain connectivity in mice

It is widely assumed that our actions shape our brains and that the resulting connections determine who we are. To test this idea in a reductionist setting, in which genes and environment are controlled, we investigated differences in neuroanatomy and structural covariance by ex vivo structural magnetic resonance imaging (MRI) in mice whose behavioral activity was continuously tracked for 3 months in a large, enriched environment. We confirmed that environmental enrichment increases mouse hippocampal volumes. Stratifying the enriched group according to individual longitudinal behavioral trajectories, however, revealed striking differences in mouse brain structural covariance in continuously highly active mice compared to those whose trajectories showed signs of habituating activity. Network-based statistics identified distinct sub-networks of murine structural covariance underlying these differences in behavioral activity. Together, these results reveal that differentiated behavioral trajectories of mice in an enriched environment are associated with differences in brain connectivity.

neuroscience↗

bioRxiv2022

Erbb4 deletion from fast-spiking interneurons causes psychosis-relevant neuroimaging phenotypes

Converging lines of evidence suggest that dysfunction of cortical parvalbumin-expressing (PV+) GABAergic interneurons is a core feature of psychosis. This dysfunction is thought to underlie neuroimaging abnormalities commonly found in patients with psychosis, particularly in the hippocampus. These include increases in resting cerebral blood flow (CBF) and levels of glutamatergic metabolites, and decreases in binding of GABAA 5 receptors and the synaptic density marker synaptic vesicle glycoprotein 2A (SV2A). However, direct links between PV+ interneuron dysfunction and these neuroimaging readouts have yet to be established. Conditional deletion of a schizophrenia susceptibility gene, the tyrosine kinase receptor Erbb4, from cortical and hippocampal PV+ interneurons leads to several synaptic, behavioral and cognitive phenotypes relevant to psychosis in mice. Here, we investigated how this PV+ interneuron disruption affects the hippocampal in vivo neuroimaging readouts in the Erbb4 model. Adult Erbb4 conditional mutant mice (Lhx6-Cre;Erbb4F/F, n=12) and their wild-type littermates (Erbb4F/F, n=12) were scanned in a 9.4T magnetic resonance scanner to quantify CBF and glutamatergic metabolite levels (glutamine, glutamate, GABA). Subsequently, we assessed GABAA receptors and SV2A density using quantitative autoradiography. Erbb4 mutant mice showed significantly elevated CBF and glutamine levels, as well as decreased SV2A density compared to wild-type littermates. No significant GABAA receptor density differences were identified. These findings demonstrate that specific disruption of cortical PV+ interneurons in mice recapitulate some of the key neuroimaging findings in psychosis patients, and link PV+ interneuron deficits to non-invasive, translational measures of brain function and neurochemistry that can be used across species.

neuroscience↗

bioRxiv2022

Post-weaning parvalbumin expression in left orbitofrontal cortex shapes sociability in female mice

The adolescent social experience is essential for the maturation of the prefrontal cortex in mammalian species. However, it still needs to be determined which cortical circuits mature with such experience and how it shapes adult social behaviors in a sex-specific manner. Here, we examined social approaching behaviors in male and female mice after post-weaning social isolation (PWSI), which deprives social experience during adolescence. We found that the PWSI, particularly isolation during late adolescence, caused an abnormal increase in social approaches (hypersociability) only in female mice. We further found that the PWSI female mice showed reduced parvalbumin (PV) expression in the left orbitofrontal cortex (OFCL). When we measured neural activity in the female OFCL, a substantial number of neurons showed higher activity when mice sniffed other mice (social sniffing) than when they sniffed an object (object sniffing). Interestingly, the PWSI significantly reduced both the number of activated neurons and the activity level during social sniffing in female mice. Similarly, the CRISPR/Cas9-mediated knock-down of PV in the OFCL during late adolescence enhanced sociability and reduced the social sniffing-induced activity in adult female mice via decreased excitability of PV+ neurons and reduced synaptic inhibition in the OFCL. Moreover, optogenetic activation of excitatory neurons or optogenetic inhibition of PV+ neurons in the OFCL enhanced sociability in female mice. Our data demonstrate that the adolescent social experience is critical for the maturation of PV+ inhibitory circuits in the OFCL; this maturation shapes female social behavior via enhancing social representation in the OFCL. Significance StatementAdolescent social isolation often changes adult social behaviors in mammals. Yet, we do not fully understand the sex-specific effects of social isolation and the brain areas and circuits that mediate such changes. Here, we found that adolescent social isolation causes three abnormal phenotypes in female but not male mice: hypersociability, decreased PV+ neurons in the OFCL, and decreased socially evoked activity in the OFCL. Moreover, PV deletion in the OFCL in vivo caused the same phenotypes in female mice by increasing excitation compared with inhibition within the OFCL. Our data suggest that adolescent social experience is required for PV maturation in the OFCL, which is critical for evoking OFCL activity that shapes social behaviors in female mice.

animal behavior and cognition↗

bioRxiv2021

Tissue Optimisation Strategies for High Quality Ex Vivo Diffusion Imaging

Ex vivo diffusion imaging can be used to study healthy and pathological tissue microstructure in the rodent brain with microscopic resolution, providing a link between in vivo MRI and ex vivo microscopy techniques. A major challenge for the successful acquisition of ex vivo diffusion imaging data however are changes in the relaxivity and diffusivity of brain tissue following perfusion fixation. In this study we address this question by examining the combined effects of tissue preparation factors that influence image quality, including tissue rehydration time, fixative concentration and contrast agent concentration. We present an optimisation strategy combining these factors to manipulate the T1 and T2 of fixed tissue and maximise signal-to-noise ratio (SNR) efficiency. Applying this strategy in the rat brain resulted in a doubling of SNR and an increase in SNR per unit time by 135% in grey matter and 88% in white matter. This enabled the acquisition of excellent quality high-resolution (78 {micro}m isotropic voxel size) diffusion data in less than 4 days, with a b-value of 4000 s/mm2, 30 diffusion directions and a field of view of 40 x 13 x 18 mm, using a 9.4 Tesla scanner with a standard 39 mm volume coil and a 660 mT/m 114 mm gradient insert. It was also possible to achieve comparable data quality for a standard resolution (150 {micro}m) diffusion dataset in 21/4 hours. In conclusion, the optimisation strategy presented here may be used to improve signal quality, increase spatial resolution and/or allow faster acquisitions in preclinical ex vivo diffusion MRI experiments.

neuroscience↗

bioRxiv2021

In vitro validation of neoantigen prediction algorithm for developing personalized cancer vaccine therapy

BackgroundThe development of personalized neoantigen-based therapeutic cancer vaccines relies on computational algorithm-based pipelines. One of the critical issues in the pipeline is obtaining higher positive predictive value (PPV) performance, i.e., how many are immunogenic when selecting the top 5 to 20 candidate neoepitopes for the vaccination. We attempted to test the PPV of a neoepitope prediction algorithm Neopepsee. MethodsSix breast cancer patients and patient-derived xenografts from three lung cancer patients and their paired peripheral blood samples were subjected to whole-exome and RNA sequencing. Neoantigen was predicted using two different algorithms (Neopepsee and pVACseq). Response of induced memory T cells to neopeptide candidates was evaluated by IFN-{gamma} Enzyme-linked immune absorbent spot (ELISpot) assays of peripheral blood mononuclear cell (PBMC) from three HLA-matched donors. Positive ELISpot response to a candidate peptide in at least 2 of 3 donor PBMC was regarded as an immunogenic response. ResultsNeopepsee predicted 159 HLA-A matched neoepitope candidates out of 898 somatic mutations in nine patients (six breast and three lung cancer patients), whereas pVACseq predicted 84 HLA-A matched candidates. A total of 26 neopeptide candidates overlapped between the two predicted candidate pools. Among the candidates, 28 (20%, 28/ 137) and 15 (20%, 15/ 75) were positive by ELISpot assay, respectively. Among 26 overlapped candidates, 20 could be tested, and 7 of them (35%) were validated by ELISpot. Neopepsee identified at least one neoepitope in 7 of 9 patients (range 0-6), compared to 6 by pVACseq (range 0-5). ConclusionAs suggested by Tumor Neoantigen Selection Alliance (TESLA), our results demonstrate low PPV of individual prediction models as well as the complementary nature of the Neopepsee and pVACseq and may help design neoepitope targeted cancer vaccines. Our data contribute a significant addition to the database of tested neoepitope candidates that can be utilized to further train and improve the prediction algorithms.

immunology↗

bioRxiv2021

Clonal hematopoiesis in individuals with ANKRD26 or ETV6 germline mutations

Currently, there are at least a dozen recognized hereditary hematopoietic malignancies (HHMs), some of which phenocopy others. Among these, three HHMs driven by germline mutations in ANKRD26, ETV6, or RUNX1 share a phenotype of thrombocytopenia, qualitative platelet defects, and an increased lifetime risk of hematopoietic malignancies (HMs). Prior work has demonstrated that RUNX1 germline mutation carriers experience an elevated lifetime risk (66%) for developing clonal hematopoiesis (CH) prior to age 50. Germline mutations in ANKRD26 or ETV6 phenocopy RUNX1 germline mutations, but no studies have focused on the risk of CH in individuals with germline mutations in ANKRD26 or ETV6. To determine the prevalence of CH in individuals with germline mutations in ANKRD26 or ETV6, we performed next generation sequencing on hematopoietic tissue from twelve individuals with either germline ANKRD26 or germline ETV6 mutations. Each patient had thrombocytopenia but had not developed HMs. Among the seven individuals with germline ANKRD26 mutations, one patient had a CH clone driven by a somatic SF3B1 mutation (p.Lys700Glu). This mutation increased from a variant allele frequency (VAF) of 9.4% at age 56 to 17.4% at age 60. None of the germline ETV6 mutation carriers had evidence of CH at the limits of detection of the NGS assay (5% VAF). Unlike individuals with germline mutations in RUNX1, no individuals under the age of 50 with germline mutations in ANKRD26 or ETV6 had detectable CH. This work demonstrates that ANKRD26 germline mutation carriers, but not ETV6 mutation carriers, experience elevated risk for CH.

genetics↗

bioRxiv2021

Suppressed prefrontal neuronal firing variability and impaired social representation in IRSp53-mutant mice

Social deficit is a major feature of neuropsychiatric disorders, including autism spectrum disorders, schizophrenia, and attention-deficit/hyperactivity disorder, but its neural mechanisms remain unclear. Here, we examined neuronal discharge characteristics in the medial prefrontal cortex (mPFC) of IRSp53-mutant mice, which show social deficits, during social approach. IRSp53-mutant excitatory mPFC neurons displayed an increase in baseline neuronal firing and decreases in variability and dynamic range of firing rates and burst firing during social and non-social target approaches compared to wild-type controls. As a consequence, their firing activity was less differential between social and non-social targets. In addition, there was a decrease in the proportion of excitatory mPFC neurons encoding social information but not that of those encoding non-social information. These results suggest that insufficient neuronal activity dynamics may underlie impaired cortical encoding of social information and social behaviors in IRSp53-mutant mice.

neuroscience↗

bioRxiv2021

Dopamine depletion can be predicted by the aperiodic component of subthalamic local field potentials

Electrophysiological biomarkers reflecting the pathological activities in the basal ganglia are essential to gain an etiological understanding of Parkinsons disease (PD) and develop a method of diagnosing and treating the disease. Previous studies that explored electrophysiological biomarkers in PD have focused mainly on oscillatory or periodic activities such as beta and gamma oscillations. Emerging evidence has suggested that the nonoscillatory, aperiodic component reflects the firing rate and synaptic current changes corresponding to cognitive and pathological states. Nevertheless, it has never been thoroughly examined whether the aperiodic component can be used as a biomarker that reflects pathological activities in the basal ganglia in PD. In this study, we examined the parameters of the aperiodic component and tested its practicality as an electrophysiological biomarker of pathological activity in PD. We found that a set of aperiodic parameters, aperiodic offset and exponent, were significantly decreased by the nigrostriatal lesion. To further prove the usefulness of the parameters as biomarkers, acute levodopa treatment reverted the aperiodic offset. We then compared the aperiodic parameters with a previously established periodic biomarker of PD, beta frequency oscillation. We found a significantly low negative correlation with beta power. We showed that the performance of the machine learning-based prediction of pathological activities in the basal ganglia can be improved by using the lowly correlated parameters, beta power and aperiodic component. We suggest that the aperiodic component will provide a more sensitive measurement to early diagnosis PD and have the potential to use as the feedback parameter for the adaptive deep brain stimulation.

neuroscience↗

bioRxiv2021

The Xenopus Phenotype Ontology: bridging model organism phenotype data to human health and development.

BackgroundOntologies of precisely defined, controlled vocabularies are essential to curate the results of biological experiments such that the data are machine searchable, can be computationally analyzed, and are interoperable across the biomedical research continuum. There is also an increasing need for methods to interrelate phenotypic data easily and accurately from experiments in animal models with human development and disease. ResultsHere we present the Xenopus Phenotype Ontology (XPO) to annotate phenotypic data from experiments in Xenopus, one of the major vertebrate model organisms used to study gene function in development and disease. The XPO implements design patterns from the Unified Phenotype Ontology (uPheno), and the principles outlined by the Open Biological and Biomedical Ontologies (OBO Foundry) to maximize interoperability with other species and facilitate ongoing ontology management. Constructed in Web Ontology Language (OWL) the XPO combines the existing uPheno library of ontology design patterns with additional terms from the Xenopus Anatomy Ontology (XAO), the Phenotype and Trait Ontology (PATO) and the Gene Ontology (GO). The integration of these different ontologies into the XPO enables rich phenotypic curation, whilst the uPheno bridging axioms allows phenotypic data from Xenopus experiments to be related to phenotype data from other model organisms and human disease. Moreover, the simple post-composed uPheno design patterns facilitate ongoing XPO development as the generation of new terms and classes of terms can be substantially automated. ConclusionsThe XPO serves as an example of current best practices to help overcome many of the inherent challenges in harmonizing phenotype data between different species. The XPO currently consists of approximately 22,000 terms and is being used to curate phenotypes by Xenbase, the Xenopus Model Organism Knowledgebase, forming a standardized corpus of genotype-phenotype data that can be directly related to other uPheno compliant resources.

bioinformatics↗

bioRxiv2021

Caspase-4/11 exacerbates disease severity in SARS-CoV-2 infection by promoting inflammation and thrombosis

SARS-CoV-2 is a worldwide health concern, and new treatment strategies are needed 1. Targeting inflammatory innate immunity pathways holds therapeutic promise, but effective molecular targets remain elusive. Here, we show that human caspase-4 (CASP4), and its mouse homologue, caspase-11 (CASP11), are upregulated in SARS-CoV-2 infections, and that CASP4 expression correlates with severity of SARS-CoV-2 infection in humans. SARS-CoV-2-infected Casp11-/- mice were protected from severe weight loss and lung pathology, including blood vessel damage, compared to wild-type (WT) and gasdermin-D knock out (Gsdmd-/-) mice. GSDMD is a downstream effector of CASP11 and CASP1. Notably, viral titers were similar in the three genotypes. Global transcriptomics of SARS-CoV-2-infected WT, Casp11-/- and Gsdmd-/- lungs identified restrained expression of inflammatory molecules and altered neutrophil gene signatures in Casp11-/- mice. We confirmed that protein levels of inflammatory mediators IL-1{beta}, IL6, and CXCL1, and neutrophil functions, were reduced in Casp11-/- lungs. Additionally, Casp11-/- lungs accumulated less von Willebrand factor, a marker for endothelial damage, but expressed more Kruppel-Like Factor 2, a transcription factor that maintains vascular integrity. Overall, our results demonstrate that CASP4/11, promotes detrimental SARS-CoV-2-associated inflammation and coagulopathy, largely independently of GSDMD, identifying CASP4/11 as a promising drug target for treatment and prevention of severe COVID-19.

immunology↗