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At least 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
NASA NTRS1997

Spectral quality affects disease development of three pathogens on hydroponically grown plants

Plants were grown under light-emitting diode (LED) arrays with various spectra to determine the effects of light quality on the development of diseases caused by tomato mosaic virus (ToMV) on pepper (Capsicum annuum L.), powdery mildew [Sphaerotheca fuliginea (Schlectend:Fr.) Pollaci] on cucumber (Cucumis sativus L.), and bacterial wilt (Pseudomonas solanacearum Smith) on tomato (Lycopersicon esculentum Mill.). One LED (660) array supplied 99% red light at 660 nm (25 nm bandwidth at half-peak height) and 1% far-red light between 700 to 800 nm. A second LED (660/735) array supplied 83% red light at 660 nm and 17% far-red light at 735 nm (25 nm bandwidth at half-peak height). A third LED (660/BF) array supplied 98% red light at 660 nm, 1% blue light (BF) between 350 to 550 nm, and 1% far-red light between 700 to 800 nm. Control plants were grown under broad-spectrum metal halide (MH) lamps. Plants were grown at a mean photon flux (300 to 800 nm) of 330 micromoles m-2 s-1 under a 12-h day/night photoperiod. Spectral quality affected each pathosystem differently. In the ToMV/pepper pathosystem, disease symptoms developed slower and were less severe in plants grown under light sources that contained blue and UV-A wavelengths (MH and 660/BF treatments) compared to plants grown under light sources that lacked blue and UV-A wavelengths (660 and 660/735 LED arrays). In contrast, the number of colonies per leaf was highest and the mean colony diameters of S. fuliginea on cucumber plants were largest on leaves grown under the MH lamp (highest amount of blue and UV-A light) and least on leaves grown under the 660 LED array (no blue or UV-A light). The addition of far-red irradiation to the primary light source in the 660/735 LED array increased the colony counts per leaf in the S. fuliginea/cucumber pathosystem compared to the red-only (660) LED array. In the P. solanacearum/tomato pathosystem, disease symptoms were less severe in plants grown under the 660 LED array, but the effects of spectral quality on disease development when other wavelengths were included in the light source (MH-, 660/BF-, and 660/735-grown plants) were equivocal. These results demonstrate that spectral quality may be useful as a component of an integrated pest management program for future space-based controlled ecological life support systems.

NASA Center KSC↗
NASA NTRS2011

Climate Change, Extreme Weather Events, and Fungal Disease Emergence and Spread

Empirical evidence from multiple sources show the Earth has been warming since the late 19th century. More recently, evidence for this warming trend is strongly supported by satellite data since the late 1970s from the cryosphere, atmosphere, oceans, and land that confirms increasing temperature trends and their consequences (e.g., reduced Arctic sea ice, rising sea level, ice sheet mass loss, etc.). At the same time, satellite observations of the Sun show remarkably stable solar cycles since the late 1970s, when direct observations of the Sun's total solar irradiance began. Numerical simulation models, driven in part by assimilated satellite data, suggest that future-warming trends will lead to not only a warmer planet, but also a wetter and drier climate depending upon location in a fashion consistent with large-scale atmospheric processes. Continued global warming poses new opportunities for the emergence and spread of fungal disease, as climate systems change at regional and global scales, and as animal and plant species move into new niches. Our contribution to this proceedings is organized thus: First, we review empirical evidence for a warming Earth. Second, we show the Sun is not responsible for the observed warming. Third, we review numerical simulation modeling results that project these trends into the future, describing the projected abiotic environment of our planet in the next 40 to 50 years. Fourth, we illustrate how Rift Valley fever outbreaks have been linked to climate, enabling a better understanding of the dynamics of these diseases, and how this has led to the development of an operational predictive outbreak model for this disease in Africa. Fifth, We project how this experience may be applicable to predicting outbreaks of fungal pathogens in a warming world. Lastly, we describe an example of changing species ranges due to climate change, resulting from recent warming in the Andes and associated glacier melt that has enabled amphibians to colonize higher elevation lakes, only to be followed shortly by the emergence of fungal disease in the new habitats.

Tucker, Compton J.↗
NASA NTRS2011

Space Radiation Cancer, Circulatory Disease and CNS Risks for Near Earth Asteroid and Mars Missions: Uncertainty Estimates for Never-Smokers

The uncertainties in estimating the health risks from galactic cosmic rays (GCR) and solar particle events (SPE) are a major limitation to the length of space missions and the evaluation of potential risk mitigation approaches. NASA limits astronaut exposures to a 3% risk of exposure induced cancer death (REID), and protects against uncertainties in risks projections using an assessment of 95% confidence intervals after propagating the error from all model factors (environment and organ exposure, risk coefficients, dose-rate modifiers, and quality factors). Because there are potentially significant late mortality risks from diseases of the circulatory system and central nervous system (CNS) which are less well defined than cancer risks, the cancer REID limit is not necessarily conservative. In this report, we discuss estimates of lifetime risks from space radiation and new estimates of model uncertainties are described. The key updates to the NASA risk projection model are: 1) Revised values for low LET risk coefficients for tissue specific cancer incidence, with incidence rates transported to an average U.S. population to estimate the probability of Risk of Exposure Induced Cancer (REIC) and REID. 2) An analysis of smoking attributable cancer risks for never-smokers that shows significantly reduced lung cancer risk as well as overall cancer risks from radiation compared to risk estimated for the average U.S. population. 3) Derivation of track structure based quality functions depends on particle fluence, charge number, Z and kinetic energy, E. 4) The assignment of a smaller maximum in quality function for leukemia than for solid cancers. 5) The use of the ICRP tissue weights is shown to over-estimate cancer risks from SPEs by a factor of 2 or more. Summing cancer risks for each tissue is recommended as a more accurate approach to estimate SPE cancer risks. 6) Additional considerations on circulatory and CNS disease risks. Our analysis shows that an individual s history of smoking exposure has a larger impact on GCR risk estimates than amounts of radiation shielding or age at exposure (amongst adults). Risks for never-smokers compared to the average U.S. population are estimated to be reduced between 30% and 60% dependent on model assumptions. Lung cancer is the major contributor to the reduction for never-smokers, with additional contributions from circulatory diseases and cancers of the stomach, liver, bladder, oral cavity and esophagus, and leukemia. The relative contribution of CNS risks to the overall space radiation detriment is potentially increased for never-smokers such as most astronauts. Problems in estimating risks for former smokers and the influence of second-hand smoke are discussed. Compared to the LET approximation, the new track structure derived radiation quality functions lead to a reduced risk for relativistic energy particles and increased risks for intermediate energy particles. Revised estimates for the number of safe days in space at solar minimum for heavy shielding conditions are described for never-smokers and the average U.S. population. Results show that missions to near Earth asteroids (NEA) or Mars violate NASA's radiation safety standards with the current levels of uncertainties. Greater improvements in risk estimates for never-smokers are possible, and would be dependent on improved understanding of risk transfer models, and elucidating the role of space radiation on the various stages of disease formation (e.g. initiation, promotion, and progression).

Cucinotta, Francis A.↗
NASA NTRS2011

Climate Teleconnections and Recent Patterns of Human and Animal Disease Outbreaks

Recent clusters of outbreaks of mosquito-borne diseases (Rift Valley fever and chikungunya) in Africa and parts of the Indian Ocean islands illustrate how interannual climate variability influences the changing risk patterns of disease outbreaks. Extremes in rainfall (drought and flood) during the period 2004 - 2009 have privileged different disease vectors. Chikungunya outbreaks occurred during the severe drought from late 2004 to 2006 over coastal East Africa and the western Indian Ocean islands and in the later years India and Southeast Asia. The chikungunya pandemic was caused by a Central/East African genotype that appears to have been precipitated and then enhanced by global-scale and regional climate conditions in these regions. Outbreaks of Rift Valley fever occurred following excessive rainfall period from late 2006 to late 2007 in East Africa and Sudan, and then in 2008 - 2009 in Southern Africa. The shift in the outbreak patterns of Rift Valley fever from East Africa to Southern Africa followed a transition of the El Nino/Southern Oscillation (ENSO) phenomena from the warm El Nino phase (2006-2007) to the cold La Nina phase (2007-2009) and associated patterns of variability in the greater Indian Ocean basin that result in the displacement of the centres of above normal rainfall from Eastern to Southern Africa. Understanding the background patterns of climate variability both at global and regional scale and their impacts on ecological drivers of vector borne-diseases is critical in long-range planning of appropriate response and mitigation measures.

Anyamba, Assaf↗
NASA NTRS2015

An Overview of NASA's Risk of Cardiovascular Disease from Radiation Exposure

The association between high doses of radiation exposure and cardiovascular damage is well established. Patients that have undergone radiotherapy for primary cancers of the head and neck and mediastinal regions have shown increased risk of heart and vascular damage and long-term development of radiation-induced heart disease [1]. In addition, recent meta-analyses of epidemiological data from atomic bomb survivors and nuclear industry workers has also shown that acute and chronic radiation exposures is strongly correlated with an increased risk of circulatory disease at doses above 0.5 Sv [2]. However, these analyses are confounded for lower doses by lifestyle factors, such as drinking, smoking, and obesity. The types of radiation found in the space environment are significantly more damaging than those found on Earth and include galactic cosmic radiation (GCR), solar particle events (SPEs), and trapped protons and electrons. In addition to the low-LET data, only a few studies have examined the effects of heavy ion radiation on atherosclerosis, and at lower, space-relevant doses, the association between exposure and cardiovascular pathology is more varied and unclear. Understanding the qualitative differences in biological responses produced by GCR compared to Earth-based radiation is a major focus of space radiation research and is imperative for accurate risk assessment for long duration space missions. Other knowledge gaps for the risk of radiation-induced cardiovascular disease include the existence of a dose threshold, low dose rate effects, and potential synergies with other spaceflight stressors. The Space Radiation Program Element within NASA's Human Research Program (HRP) is managing the research and risk mitigation strategies for these knowledge gaps. In this presentation, we will review the evidence and present an overview of the HRP Risk of Cardiovascular Disease and Other Degenerative Tissue Effects from Radiation Exposure.

Patel, Zarana S.↗
NASA NTRS2022

Peru Health and Air Quality II: Leveraging Earth Observations and Health Data to Map Outbreak Risk and Inform Public Health Interventions for Zoonotic Disease Prevention

Peru's Madre de Dios region is a hotspot for dengue fever and leishmaniasis due to its tropical Amazonian climate. Though treatable, these zoonotic diseases are debilitating for under-resourced communities whose already close proximity to mosquito and sandfly vectors continues to increase via rapid urbanization and deforestation. Peru’s Ministries of Health (MINSA) and Environment (MINAM) are working to better understand the environmental factors amplifying the risk of dengue fever and leishmaniasis transmission. The first term of this project classified the land use and land cover of Madre de Dios’ 11 districts for 2010, 2015, and 2020 and identified a correlation between both diseases and urbanization. Our team expanded this analysis by creating urban-forest edge maps and incorporating climatic and topographic variables with data from Landsat 7 Enhanced Thematic Mapper Plus (ETM+), Landsat 8 Operational Land Imager (OLI), the Global Precipitation Measurement (GPM) Integrated Multi-satellitE Retrievals for GPM (IMERG), and the Shuttle Radar Topography Mission (SRTM). We determined these variables’ impacts on disease incidence by assessing existing literature and running regression models. Dengue fever correlated with urban-forest edge, urban area, slope, temperature, and precipitation. Leishmaniasis primarily correlated with forest-edge area and elevation, but lacking additional statistical significance prevented further work, a decision supported by the literature. Thus, the risk matrix and risk map which we scripted in R to visualize the risk of disease posed to districts alongside health post locations addresses only dengue fever. The results and products will inform MINSA and MINAM in public health interventions, resource distribution, and policy initiatives.

Jennifer Rogers↗
NASA NTRS2021

Impact of Recent Climate Extremes on Mosquito-borne Disease Transmission in Kenya

Climate change and variability influence temperature and rainfall, which impact vector abundance and the dynamics of vector-borne disease transmission. Climate change is projected to increase the frequency and intensity of extreme climate events. Mosquito-borne diseases, such as dengue fever, are primarily transmitted by Aedes aegypti mosquitoes. Freshwater availability and temperature affect dengue vector populations via a variety of biological processes and thus influence the ability of mosquitoes to effectively transmit disease. However, the effect of droughts, floods, heat waves, and cold waves is not well understood. Using vector, climate, and dengue disease data collected between 2013 and 2019 in Kenya, this retrospective cohort study aims to elucidate the impact of extreme rainfall and temperature on mosquito abundance and the risk of arboviral infections. To define extreme periods of rainfall and land surface temperature (LST), we calculated monthly anomalies as deviations from long-term means (1983–2019 for rainfall, 2000–2019 for LST) across four study locations in Kenya. We classified extreme climate events as the upper and lower 10% of these calculated LST or rainfall deviations. Monthly Ae. aegypti abundance was recorded in Kenya using four trapping methods. Blood samples were also collected from children with febrile illness presenting to four field sites and tested for dengue virus using an IgG enzyme-linked immunosorbent assay (ELISA) and polymerase chain reaction (PCR). We found that mosquito eggs and adults were significantly more abundant one month following an abnormally wet month. The relationship between mosquito abundance and dengue risk follows a non-linear association. Our findings suggest that early warnings and targeted interventions during periods of abnormal rainfall and temperature, especially flooding, can potentially contribute to reductions in risk of viral transmission

Aedes aegypti mosquitoes↗
NASA NTRSDate not supplied

Development of Machine Learning-Derived Microbiological and Immune Signatures: Applications in Adaptive Risk Assessment of Infectious Disease During Spaceflight

Infectious diseases represent an urgent risk for spaceflight with consequences ranging from loss in crew performance to crew incapacitation or loss of life should an outbreak occur. The resident environmental microbiome on the International Space Station has been monitored through routine surveillance over almost twenty years, beginning with culture-based microbial detection which has advanced to molecular methods in recent years. This has created a wealth of data that we have begun mining to define the microbial ecology of the ISS. Summarized here is our analysis of data from the historical microbial population defined by culture-based monitoring from the past two decades, organized by their likelihood to cause disease into clinical categories. As expected, many residents of the normal microflora in environments where people work and live were detected. However, some known pathogens were also detected. As the spaceflight environment can predispose humans to infection, crew health records were used to source additional data for the set to uncover clinical relevance. Data mining was performed on crew health records to capture adverse health events that may be related to infectious disease. Machine learning, specifically Random Forest analysis, was used to analyze the microbial and crew health datasets. The symptom categories were not explained by the ranked bacteria, due to lack of sufficient data for some categories and due to poor ranking of the pathogens for others. Poor ranking of the bacteria could be due to the clinical symptoms being linked to other disease-causing factors, such as allergy or viral infection. These findings suggest a lack of relationship between bacteria detected on surfaces in the ISS and historical health events experienced by astronauts.

Kristyn Hoffman↗
DOE OSTI2020

Methods for treating diseases related to the wnt pathway

The present invention relates to methods for treating a disease, in which the disease arises from dysregulation of the Wnt signaling pathway. In some instances, the disease can be treated by administering a Wnt pathway inhibitory compound. In other instances, the method optionally includes conducting a genome-wide screening to determine one or more genes resulting in a reduced disease state and then identifying the gene(s) as being involved in the Wnt signaling pathway.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Neuroanatomical and cognitive correlates of visual hallucinations in Parkinson’s disease and dementia with Lewy bodies: Voxel-based morphometry and neuropsychological meta-analysis

Visual hallucinations (VH) are common in Parkinson's disease and dementia with Lewy bodies, two forms of Lewy body disease (LBD), but the neural substrates and mechanisms involved are still unclear. We conducted meta-analyses of voxel-based morphometry (VBM) and neuropsychological studies investigating the neuroanatomical and cognitive correlates of VH in LBD. For VBM (12 studies), we used Seed-based d Mapping with Permutation of Subject Images (SDM-PSI), including statistical parametric maps for 50% of the studies. For neuropsychology (35 studies), we used MetaNSUE to consider non-statistically significant unreported effects. VH were associated with smaller grey matter volume in occipital, frontal, occipitotemporal, and parietal areas (peak Hedges' g -0.34 to -0.49). In patients with Parkinson's disease without dementia, VH were associated with lower verbal immediate memory performance (Hedges' g -0.52). Both results survived correction for multiple comparisons. Here, abnormalities in these brain regions might reflect dysfunctions in brain networks sustaining visuoperceptive, attention, and executive abilities, with the latter also being at the basis of poor immediate memory performance.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

Host genetics and gut microbiota composition: Baseline gut microbiota composition as a possible prognostic factor for the severity of COVID-19 in patients with familial Mediterranean fever disease

It is known that the gut microbiome of a healthy person affects the process of COVID-19 after getting infected with SARS-CoV-2 virus. It is also believed that colchicine can alleviate the severity of COVID-19. Current investigations aimed to evaluate the associations between the baseline gut microbiota composition of healthy and Familial Mediterranean fever (FMF) - carrier Armenian men populations, and the severity of the COVID-19 disease after their infection with the SARS-CoV-2. The study has a purpose of answering three core questions: i. Do the characteristics of gut microbiome of Armenians affect the course of COVID-19 severity? ii. How does the COVID-19 disease course on go for FMF patients who have been taking colchicine as a medication over the years after getting infected with SARS-CoV-2? iii. Is there an initial gut micribiota structure pattern for non-FMF and FMF patients in the cases when COVID-19 appears in mild form? The gut microbiota composition in non-FMF and FMF patients before the first infection (mild and moderate course of COVID-19) was considered. COVID-19 was diagnosed by SARS-CoV-2 nucleic acid RT-PCR in nasopharyngeal swab and/or sputum. The number of patients with male FMF with mild COVID-19 was approximately two times higher than that of non-FMF male subjects with COVID-19. In addition, an association of COVID-19 disease severity with the baseline gut Prevotella, Clostridium hiranonis, Eubacterium biforme, Veillonellaceae, Coprococcus, and Blautia diversities in the non-FMF and FMF populations were revealed by us, which can be used as risk/prognostic factor for the severity of COVID-19.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

Duration of Contagion of Foot-And-Mouth Disease Virus in Infected Live Pigs and Carcasses

Data-driven modeling of incursions of high-consequence, transboundary pathogens of animals is a critical component of veterinary preparedness. However, simplifying assumptions and excessive use of proxy measures to compensate for gaps in available data may compromise modeled outcomes. The current investigation was prospectively designed to address two major gaps in current knowledge of foot-and-mouth disease virus (FMDV) pathogenesis in pigs: the end (duration) of the infectious period and the viability of FMDV in decaying carcasses. By serial exposure of sentinel groups of pigs to the same group of donor pigs infected by FMDV A24 Cruzeiro, it was demonstrated that infected pigs transmitted disease at 10 days post infection (dpi), but not at 15 dpi. Assuming a latent period of 1 day, this would result in a conservative estimate of an infectious duration of 9 days, which is considerably longer than suggested by a previous report from an experiment performed in cattle. Airborne contagion was diminished within two days of removal of infected pigs from isolation rooms. FMDV in muscle was inactivated within 7 days in carcasses stored at 4°C. By contrast, FMDV infectivity in vesicle epithelium harvested from intact carcasses stored under similar conditions remained remarkably high until the study termination at 11 weeks post mortem. The output from this study consists of experimentally determined data on contagion associated with FMDV-infected pigs. This information may be utilized to update parameterization of models used for foot-and-mouth disease outbreak simulations involving areas of substantial pig production.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Differential contagiousness of respiratory disease across the United States

The initial contagiousness of a communicable disease within a given population is quantified by the basic reproduction number, $R_0$. This number depends on both pathogen and population properties. On the basis of compartmental models that reproduce Coronavirus Disease 2019 (COVID-19) surveillance data, we used Bayesian inference and the next-generation matrix approach to estimate region-specific $R_0$ values for 280 of 384 metropolitan statistical areas (MSAs) in the United States (US), which account for 95% of the US population living in urban areas and 82% of the total population. We focused on MSA populations after finding that these populations were more uniformly impacted by COVID-19 than state populations. Our maximum a posteriori (MAP) estimates for $R_0$ range from 1.9 to 7.7 and quantify the relative susceptibilities of regional populations to spread of respiratory diseases.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Effect of disease progression on the podocyte cell cycle in Alport Syndrome

Progression of glomerulosclerosis is associated with loss of podocytes with subsequent glomerular tuft instability. It is thought that a diminished number of podocytes may be able to preserve tuft stability through cell hypertrophy associated with cell cycle reentry. At the same time, reentry into the cell cycle risks podocyte detachment if podocytes cross the G1/S checkpoint and undergo abortive cytokinesis. In order to study cell cycle dynamics during chronic kidney disease (CKD) development, we used a FUCCI model (fluorescence ubiquitination-based cell cycle indicator) of mice with X-linked Alport Syndrome. This model exhibits progressive CKD and expresses fluorescent reporters of cell cycle stage exclusively in podocytes. With the development of CKD, an increasing fraction of podocytes in vivo were found to be in G1 or later cell cycle stages. Podocytes in G1 and G2 were hypertrophic. Heterozygous female mice, with milder manifestations of CKD, showed G1 fraction numbers intermediate between wild-type and male Alport mice. Proteomic analysis of podocytes in different cell cycle phases showed differences in cytoskeleton reorganization and metabolic processes between G0 and G1 in disease. Additionally, in vitro experiments confirmed that damaged podocytes reentered the cell cycle comparable to podocytes in vivo. Importantly, we confirmed the upregulation of PDlim2, a highly expressed protein in podocytes in G1, in a patient with Alport Syndrome, confirming our proteomics data in the human setting. Thus, our data showed that in the Alport model of progressive CKD, podocyte cell cycle distribution is altered, suggesting that cell cycle manipulation approaches may have a role in the treatment of various progressive glomerular diseases characterized by podocytopenia.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

J-domain proteins interaction with neurodegenerative disease-related proteins

HSP70 chaperones, J-domain proteins (JDPs) and nucleotide exchange factors (NEF) form functional networks that have the ability to prevent and reverse the aggregation of proteins associated with neurodegenerative diseases. JDPs can interact with specific substrate proteins, hold them in a refolding-competent conformation and target them to specific HSP70 chaperones for remodeling. Thereby, JDPs select specific substrates and constitute an attractive target for pharmacological intervention of neurodegenerative diseases. This, under the condition that the exact mechanism of JDPs interaction with specific substrates is unveiled. In this review, we provide an overview of the structural and functional variety of JDPs that interact with neurodegenerative disease-associated proteins and we highlight those studies that identified specific residues, domains or regions of JDPs that are crucial for substrate binding.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

Deciphering ApoE Genotype-Driven Proteomic and Lipidomic Alterations in Alzheimer’s Disease Across Distinct Brain Regions

Alzheimer’s disease (AD) is a neurodegenerative disease with a complex etiology influenced by confounding factors such as genetic polymorphisms, age, sex, and race. Traditionally, AD research has not prioritized these influences, resulting in dramatically skewed cohorts such as three times the number of Apolipoprotein E (APOE) e4-allele carriers in AD relative to healthy cohorts. Thus, the resulting molecular changes of AD have previously been complicated by the influence of apolipoprotein E disparities. To explore how apolipoprotein E polymorphism influences AD progression, 62 post-mortem patients consisting of 33 Alzheimer’s disease (AD) and 29 controls (Ctrl) were studied to balance the number of e4-allele carriers and facilitate a molecular comparison of the apolipoprotein E genotype. Lipid and protein perturbations were assessed across AD diagnosed brains compared to Ctrl brains, e4 allele carriers (APOE4+ for those carrying 1 or 2 e4s and APOE4- for non-e4 carriers), and differences in e3e3 and e3e4 Ctrl brains across two brain regions (frontal cortex (FCX) and cerebellum (CBM)). In conclusion, the region-specific influences of apolipoprotein E on AD mechanisms showcased mitochondrial dysfunction and cell proteostasis at the core of AD pathophysiology in the post-mortem brains, indicating these two processes may be influenced by genotypic differences and brain morphology.

Alzheimer’s disease↗
DOE OSTI2021

Cryo-EM structures of the ABCA4 importer reveal mechanisms underlying substrate binding and Stargardt disease

ABCA4 is an ATP-binding cassette (ABC) transporter that flips N-retinylidene-phosphatidylethanolamine (N-Ret-PE) from the lumen to the cytoplasmic leaflet of photoreceptor membranes. Loss-of-function mutations cause Stargardt disease (STGD1), a macular dystrophy associated with severe vision loss. To define the mechanisms underlying substrate binding and STGD1, we determine the cryo-EM structure of ABCA4 in its substrate-free and bound states. The two structures are similar and delineate an elongated protein with the two transmembrane domains (TMD) forming an outward facing conformation, extended and twisted exocytoplasmic domains (ECD), and closely opposed nucleotide binding domains. N-Ret-PE is wedged between the two TMDs and a loop from ECD1 within the lumen leaflet consistent with a lateral access mechanism and is stabilized through hydrophobic and ionic interactions with residues from the TMDs and ECDs. Our studies provide a framework for further elucidating the molecular mechanism associated with lipid transport and disease and developing promising disease interventions.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Modelling kidney disease using ontology: insights from the Kidney Precision Medicine Project

An important need exists to better understand and stratify kidney disease according to its underlying pathophysiology in order to develop more precise and effective therapeutic agents. National collaborative efforts such as the Kidney Precision Medicine Project are working towards this goal through the collection and integration of large, disparate clinical, biological and imaging data from patients with kidney disease. Ontologies are powerful tools that facilitate these efforts by enabling researchers to organize and make sense of different data elements and the relationships between them. Ontologies are critical to support the types of big data analysis necessary for kidney precision medicine, where heterogeneous clinical, imaging and biopsy data from diverse sources must be combined to define a patient’s phenotype. Here, the development of two new ontologies — the Kidney Tissue Atlas Ontology and the Ontology of Precision Medicine and Investigation — will support the creation of the Kidney Tissue Atlas, which aims to provide a comprehensive molecular, cellular and anatomical map of the kidney. These ontologies will improve the annotation of kidney-relevant data, and eventually lead to new definitions of kidney disease in support of precision medicine.

60 APPLIED LIFE SCIENCES↗