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All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

A Phage Foundry Framework to Systematically Develop Viral Countermeasures to Combat Antibiotic-Resistant Bacterial Pathogens

At its current rate, the rise of antimicrobial-resistant (AMR) infections is predicted to paralyze our industries and healthcare facilities while becoming the leading global cause of loss of human life. With limited new antibiotics on the horizon, we need to invest in alternative solutions. Bacteriophages (phages)–viruses targeting bacteria–offer a powerful alternative approach to tackle bacterial infections. Despite recent advances in using phages to treat recalcitrant AMR infections, the field lacks systematic development of phage therapies scalable to different applications. We propose a Phage Foundry framework to establish metrics for phage characterization and to fill the knowledge and technological gaps in phage therapeutics. Coordinated investment in AMR surveillance, sampling, characterization, and data sharing procedures will enable rational exploitation of phages for treatments. A fully realized Phage Foundry will enhance the sharing of knowledge, technology, and viral reagents in an equitable manner and will accelerate the biobased economy.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Hantavirus is Associated With Open Developed Areas and Arid Climates, Highlighting Increased Risk in the Western United States

In the United States, hantaviruses can cause hantavirus pulmonary syndrome (HPS) in humans, an acute respiratory illness with a high mortality rate. Most people contract HPS from exposure to infected rodent excrement. The interannual dynamics of hantavirus transmission are tied to both environmental and human-related factors, including changes in annual climate conditions, rodent populations, and the built environment in which humans are more likely to be exposed. Similar environmental conditions and socioeconomic factors also likely determine the long-term risk of hantavirus exposure. Here, we use ecological niche models and human cases of HPS in the U.S. from 1993 to 2022 to assess hantavirus risk using four socioeconomic variables, 17 land use variables, one variable of rodent richness, and seven climate variables to determine both the geographical locations of highest exposure risk and leading environmental predictors. We found that areas with higher relative risk tend to be where it is drier, higher social vulnerability, increased rodent richness, and more open to low levels of development—this largely mapped to the western U.S. We found evidence that fringe ecosystems may be important areas of hantavirus transmission, similar to other emerging diseases. Increased rodent richness was associated with increased hantavirus risk, warranting further investigation into how the abundance and community composition of rodents could impact long-term risk. These risk maps can help public health officials develop plans for mitigating hantavirus, especially for the most susceptible populations. They can also be used to further investigate regions estimated to be at high risk for hantavirus where disease cases have not been as common but may be underreported.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Trajectory of Growth of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) Variants in Houston, Texas, January through May 2021, Based on 12,476 Genome Sequences

Certain genetic variants of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) are of substantial concern because they may be more transmissible or detrimentally alter the pandemic course and disease features in individual patients. SARS-CoV-2 genome sequences from 12,476 patients in the Houston Methodist health care system diagnosed from January 1 through May 31, 2021 are reported here. Prevalence of the B.1.1.7 (Alpha) variant increased rapidly and caused 63% to 90% of new cases in the latter half of May. Eleven B.1.1.7 genomes had an E484K replacement in spike protein, a change also identified in other SARS-CoV-2 lineages. Compared with non–B.1.1.7-infected patients, individuals with B.1.1.7 had a significantly lower cycle threshold (a proxy for higher virus load) and significantly higher hospitalization rate. Other variants [eg, B.1.429 and B.1.427 (Epsilon), P.1 (Gamma), P.2 (Zeta), and R.1] also increased rapidly, although the magnitude was less than that in B.1.1.7. Twenty-two patients infected with B.1.617.1 (Kappa) or B.1.617.2 (Delta) variants had a high rate of hospitalization. Breakthrough cases (n = 207) in fully vaccinated patients were caused by a heterogeneous array of virus genotypes, including many not currently designated variants of interest or concern. Finally, in the aggregate, this study delineates the trajectory of SARS-CoV-2 variants circulating in a major metropolitan area, documents B.1.1.7 as the major cause of new cases in Houston, TX, and heralds the arrival of B.1.617 variants in the metroplex.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

Estimating the Timing of Early Simian-Human Immunodeficiency Virus Infections: a Comparison between Poisson Fitter and BEAST

Many HIV prevention strategies are currently under consideration where it is highly informative to know the study participants’ times of infection. These can be estimated using viral sequence data sampled early in infection. However, there are several scenarios that, if not addressed, can skew timing estimates. These include multiple transmitted/founder (TF) viruses, APOBEC (apolipoprotein B mRNA editing enzyme, catalytic polypeptide-like)-mediated mutational enrichment, and recombination. Here, we suggest a pipeline to identify these problems and resolve the biases that they introduce. We then compare two modeling strategies to obtain timing estimates from sequence data. The first, Poisson Fitter (PF), is based on a Poisson model of random accumulation of mutations relative to the TF virus (or viruses) that established the infection. The second uses a coalescence-based phylogenetic strategy as implemented in BEAST. The comparison is based on timing predictions using plasma viral RNA (cDNA) sequence data from 28 simian-human immunodeficiency virus (SHIV)-infected animals for which the exact day of infection is known. In this particular setting, based on nucleotide sequences from samples obtained in early infection, the Poisson method yielded more accurate, more precise, and unbiased estimates for the time of infection than did the explored implementations of BEAST. The inference of the time of infection is a critical parameter in testing the efficacy of clinical interventions in protecting against HIV-1 infection. For example, in clinical trials evaluating the efficacy of passively delivered antibodies (Abs) for preventing infections, accurate time of infection data are essential for discerning levels of the Abs required to confer protection, given the natural Ab decay rate in the human body. In such trials, genetic sequences from early in the infection are regularly sampled from study participants, generally prior to immune selection, when the viral population is still expanding and genetic diversity is low. In this particular setting of early viral growth, the Poisson method is superior to the alternative approach based on coalescent methods. This approach can also be applied in human vaccine trials, where accurate estimates of infection times help ascertain if vaccine-elicited immune protection wanes over time.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Image-based time series analysis to establish differential disease progression for two Fusarium head blight pathogens in oat spikelets with variable resistance

Oat-based value-added products have increased their value as healthy foodstuff. Fusarium head blight (FHB) infections and the mycotoxins accumulated to the oat seeds, however, pose a challenge to oat production. The FHB infections are predicted to become more prevalent in the future changing climates and under more limited use of fungicides. Both these factors increase the pressure for breeding new resistant cultivars. Until now, however, genetic links in oats against FHB infection have been difficult to identify. Therefore, there is a great need for more effective breeding efforts, including improved phenotyping methods allowing time series analysis and the identification of molecular markers during disease progression. To these ends, dissected spikelets of several oat genotypes with different resistance profiles were studied by image-based methods during disease progression by Fusarium culmorum or F. langsethiae species. The chlorophyll fluorescence of each pixel in the spikelets was recorded after inoculation by the two Fusarium spp., and the progression of the infections was analyzed by calculating the mean maximum quantum yield of PSII (F v /F m ) values for each spikelet. The recorded values were (i) the change in the photosynthetically active area of the spikelet as percentage of its initial size, and (ii) the mean of F v /F m values of all fluorescent pixels per spikelet post inoculation, both indicative of the progression of the FHB disease. The disease progression was successfully monitored, and different stages of the infection could be defined along the time series. The data also confirmed the differential rate of disease progression by the two FHB causal agents. In addition, oat varieties with variable responses to the infections were indicated.

oats↗
DOE OSTI2022

Evaluating efficacy of indoor non-pharmaceutical interventions against COVID-19 outbreaks with a coupled spatial-SIR agent-based simulation framework

Contagious respiratory diseases, such as COVID-19, depend on sufficiently prolonged exposures for the successful transmission of the underlying pathogen. It is important that organizations evaluate the efficacy of non-pharmaceutical interventions aimed at mitigating viral transmission among their personnel. We have developed a operational risk assessment simulation framework that couples a spatial agent-based model of movement with an agent-based SIR model to assess the relative risks of different intervention strategies. By applying our model on MIT’s Stata center, we assess the impacts of three possible dimensions of intervention: one-way vs unrestricted movement, population size allowed onsite, and frequency of leaving designated work location for breaks. We find that there is no significant impact made by one-way movement restrictions over unrestricted movement. Instead, we find that reducing the frequency at which individuals leave their workstations combined with lowering the number of individuals admitted below the current recommendations lowers the likelihood of highly connected individuals within the contact networks that emerge, which in turn lowers the overall risk of infection. We discover three classes of possible interventions based on their epidemiological effects. By assuming a direct relationship between data on secondary attack rates and transmissibility in the agent-based SIR model, we compare relative infection risk of four respiratory illnesses, MERS, SARS, COVID-19, and Measles, within the simulated area, and recommend appropriate intervention guidelines.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

A Metabolomics Assay to Diagnose Citrus Huanglongbing Disease and to Aid in Assessment of Treatments to Prevent or Cure Infection

Citrus greening disease, or Huanglongbing (HLB), has devastated citrus crops globally in recent years. The causal bacterium, ‘ Candidatus Liberibacter asiaticus’, presents a sampling issue for qPCR diagnostics and results in a high false negative rate. In this work, we compared six metabolomics assays to identify HLB-infected citrus trees from leaf tissue extracted from 30 control and 30 HLB-infected trees. A liquid chromatography-mass spectrometry-based assay was most accurate. A final partial least squares-discriminant analysis (PLS-DA) model was trained and validated on 690 leaf samples with corresponding qPCR measures from three citrus varieties (Rio Red grapefruit, Hamlin sweet orange, and Valencia sweet orange) from orchards in Florida and Texas. Trees were naturally infected with HLB transmitted by the insect vector Diaphorina citri. In a randomized validation set, the assay was 99.9% accurate to classify diseased from nondiseased samples. This model was applied to samples from trees receiving plant defense-inducer compounds or biological treatments to prevent or cure HLB infection. From two trials, HLB-related metabolite abundances and PLS-DA scores were tracked longitudinally and compared with those of control trees. We demonstrate how our assay can assess tree health and the efficacy of HLB treatments and conclude that no trialed treatment was efficacious.

Plant Sciences↗
DOE OSTI2023

Dynamic Reconfiguration of Switchgrass Proteomes in Response to Rust ( Puccinia novopanici ) Infection

Switchgrass (Panicum virgatum L.) can be infected by the rust pathogen (Puccinia novopanici) and results in lowering biomass yields and quality. Label-free quantitative proteomics was conducted on leaf extracts harvested from non-infected and infected plants from a susceptible cultivar (Summer) at 7, 11, and 18 days after inoculation (DAI) to follow the progression of disease and evaluate any plant compensatory mechanisms to infection. Some pustules were evident at 7 DAI, and their numbers increased with time. However, fungal DNA loads did not appreciably change over the course of this experiment in the infected plants. In total, 3830 proteins were identified at 1% false discovery rate, with 3632 mapped to the switchgrass proteome and 198 proteins mapped to different Puccinia proteomes. Across all comparisons, 1825 differentially accumulated switchgrass proteins were identified and subjected to a STRING analysis using Arabidopsis (A. thaliana L.) orthologs to deduce switchgrass cellular pathways impacted by rust infection. Proteins associated with plastid functions and primary metabolism were diminished in infected Summer plants at all harvest dates, whereas proteins associated with immunity, chaperone functions, and phenylpropanoid biosynthesis were significantly enriched. At 18 DAI, 1105 and 151 proteins were significantly enriched or diminished, respectively. Many of the enriched proteins were associated with mitigation of cellular stress and defense.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Cross-scale dynamics and the evolutionary emergence of infectious diseases

When emerging pathogens encounter new host species for which they are poorly adapted, they must evolve to escape extinction. Pathogens experience selection on traits at multiple scales, including replication rates within host individuals and transmissibility between hosts. We analyze a stochastic model linking pathogen growth and competition within individuals to transmission between individuals. Our analysis reveals a new factor, the cross-scale reproductive number of a mutant virion, that quantifies how quickly mutant strains increase in frequency when they initially appear in the infected host population. This cross-scale reproductive number combines with viral mutation rates, single-strain reproductive numbers, and transmission bottleneck width to determine the likelihood of evolutionary emergence, and whether evolution occurs swiftly or gradually within chains of transmission. We find that wider transmission bottlenecks facilitate emergence of pathogens with short-term infections, but hinder emergence of pathogens exhibiting cross-scale selective conflict and long-term infections. Furthermore, our results provide a framework to advance the integration of laboratory, clinical, and field data in the context of evolutionary theory, laying the foundation for a new generation of evidence-based risk assessment of emergence threats.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Development of a novel minigenome and recombinant VSV expressing Seoul hantavirus glycoprotein-based assays to identify anti-hantavirus therapeutics

Seoul virus (SEOV) is an emerging global health threat that can cause hemorrhagic fever with renal syndrome (HFRS), which results in case fatality rates of ~2%. There are no approved treatments for SEOV infections. We developed a cell-based assay system to identify potential antiviral compounds for SEOV and generated additional assays to characterize the mode of action of any promising antivirals. Here, to test if candidate antivirals targeted SEOV glycoprotein-mediated entry, we developed a recombinant reporter vesicular stomatitis virus expressing SEOV glycoproteins. To facilitate the identification of candidate antiviral compounds targeting viral transcription/replication, we successfully generated the first reported minigenome system for SEOV. This SEOV minigenome (SEOV-MG) screening assay will also serve as a prototype assay for discovery of small molecules inhibiting replication of other hantaviruses, including Andes and Sin Nombre viruses. Ours is a proof-of-concept study in which we tested several compounds previously reported to have activity against other negative-strand RNA viruses using our newly developed hantavirus antiviral screening systems. These systems can be used under lower biocontainment conditions than those needed for infectious viruses, and identified several compounds with robust anti-SEOV activity. Our findings have important implications for the development of anti-hantavirus therapeutics.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

iPHoP: An integrated machine learning framework to maximize host prediction for metagenome-derived viruses of archaea and bacteria

The extraordinary diversity of viruses infecting bacteria and archaea is now primarily studied through metagenomics. While metagenomes enable high-throughput exploration of the viral sequence space, metagenome-derived sequences lack key information compared to isolated viruses, in particular host association. Different computational approaches are available to predict the host(s) of uncultivated viruses based on their genome sequences, but thus far individual approaches are limited either in precision or in recall, i.e., for a number of viruses they yield erroneous predictions or no prediction at all. Here, we describe iPHoP, a two-step framework that integrates multiple methods to reliably predict host taxonomy at the genus rank for a broad range of viruses infecting bacteria and archaea, while retaining a low false discovery rate. Based on a large dataset of metagenome-derived virus genomes from the IMG/VR database, we illustrate how iPHoP can provide extensive host prediction and guide further characterization of uncultivated viruses.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

MalGen: Malware Generation with Specific Behaviors to Improve Machine Learning-based Detectors

In recent years, infections and damage caused by malware have increased at exponential rates. At the same time, machine learning (ML) techniques have shown tremendous promise in many domains, often out performing human efforts by learning from large amounts of data. Results in the open literature suggest that ML is able to provide similar results for malware detection, achieving greater than 99% classifcation accuracy [49]. However, the same detection rates when applied in deployed settings have not been achieved. Malware is distinct from many other domains in which ML has shown success in that (1) it purposefully tries to hide, leading to noisy labels and (2) often its behavior is similar to benign software only differing in intent, among other complicating factors. This report details the reasons for the diffcultly of detecting novel malware by ML methods and offers solutions to improve the detection of novel malware.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2005

A potential cause for kidney stone formation during space flights: enhanced growth of nanobacteria in microgravity

BACKGROUND: Although some information is available regarding the cellular/molecular changes in immune system exposed to microgravity, little is known about the reasons of the increase in the kidney stone formation in astronauts during and/or after long duration missions at zero gravity (0 g). In our earlier studies, we have assessed a unique agent, nanobacteria (NB), in kidney stones and hypothesized that NB have an active role in calcium phosphate-carbonate deposition in kidney. In this research we studied effect of microgravity on multiplication and calcification of NB in vitro. METHODS: We examined NB cultures in High Aspect Rotating Vessels (HARVs) designed at the NASA's Johnson Space Center, which are designed to stimulate some aspects of microgravity. Multiplication rate and calcium phosphate composition of those NB were compared with NB cultured on stationary and shaker flasks. Collected aliquots of the cultures from different incubation periods were analyzed using spectrophotometer, SEM, TEM, EDX, and x-ray diffraction techniques. RESULTS: The results showed that NB multiplied 4.6x faster in HARVs compared to stationary cultures, and 3.2x faster than shaker flask conditions. X-ray diffraction and EDX analysis showed that the degree of apatite crystal formation and the properties of the apatite depend on the specific culture conditions used. CONCLUSION: We now report an increased multiplication rate of NB in microgravity-simulated conditions. Thus, NB infection may have a potential role in kidney stone formation in crew members during space flights. For further proof to this hypothesis, screening of the NB antigen and antibody level in flight crew before and after flight would be necessary.

Weightlessness↗
DOE OSTI2021

PNNL DataHub Project: Omics Lethal Human Viruses Project Profiling of the Host Response to Ebola Virus Infection, Processed Experimental Dataset Catalog

Ebola virus (EBOV) is high risk biological agent, classified as a Category A priority pathogen (Flaviviridae) by the National Institute of Allergy and Infectious Diseases (NIAID), known to cause hemorrhagic fever with high mortality rates in humans. Lethal host-pathogen invasion mechanisms and the cellular intricacies behind these fatal infections still remain unclear. The NIAID Modeling Host Responses to Understand Severe Human Virus Infections Research Program project (2013-2018) aimed to develop an improved comprehensive understanding of the host response to a suite of viruses causing lethal infections leveraging a systems biology approach. Herein, PNNL sub-projects provide a never before released comprehensive infectious disease collection of primary and secondary transformation multi-Omics data profiling a series of priority pathogen primary experimental studies for enhanced open-access to viral Omics datasets and project lifecycle metadata. Secondary host-pathogen viral dataset downloads contain one or more statistically processed (normalization data transformation) quantitative dataset collections resulting in qualitative expression analyses of primary host-pathogen experimental study designs. Leveraging unique high-resolution Omics capabilities for proteomics (P), metabolomics (M), lipidomics (L), and transcriptomics (T) dataset downloads each have a direct relationship to a primary sample submission corresponding to a specific Ebola virus [NCBITAXON:186536] (Zaire/Makona or Zaire/Mayinga) experimental infection study. Human host samples types include peripheral blood mononuclear cells isolated from blood plasma ["PBMC", BTO:0001025], human hepatoma carcinoma cells ["HUH", BTO:0001950], human umbilical vein endothelial cells ["HUVEC", BTO:0001949], immortalized human hepatocyte cells ["IHH", BTO:0006147], and human histiocytic lymphoma cells ["U937", BTO:0001412].

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

ASFV Gene A151R Is Involved in the Process of Virulence in Domestic Swine

African swine fever virus (ASFV) is the etiological agent of a swine pandemic affecting a large geographical area extending from Central Europe to Asia. The viral disease was also recently identified in the Dominican Republic and Haiti. ASFV is a structurally complex virus with a large dsDNA genome that encodes for more than 150 genes. Most of these genes have not been experimentally characterized. One of these genes, A151R, encodes for a nonstructural protein and has been reported to be required for the replication of a Vero-cell-adapted ASFV strain. Here, we evaluated the role of the A151R gene in the context of the highly virulent field isolate Georgia 2010 (ASFV-G) during virus replication in swine macrophage cell cultures and during experimental infection in swine. We show that the recombinant virus ASFV-G-ΔA151R, harboring a deletion of the A151R gene, replicated in swine macrophage cultures as efficiently as the parental virus ASFV-G, indicating that the A151R gene is not required for ASFV replication in swine macrophages. Interestingly, experimental infection of domestic pigs demonstrated that ASFV-G-ΔA151R had a decreased replication rate and produced a drastic reduction in virus virulence. Animals were intramuscularly inoculated with 102 HAD50 of ASFV-G-ΔA151R and compared with pigs receiving a similar dose of virulent ASFV-G. All ASFV-G-infected pigs developed an acute lethal form of the disease, while those inoculated with ASFV-G-ΔA151R remained healthy during the 28-day observational period, with the exception of only one showing a protracted, but fatal, form of the disease. All ASFV-G-ΔA151R surviving animals presented protracted viremias with lower virus titers than those detected in ASFV-G-infected animals. In addition, three out of the four animals surviving the infection with ASFV-G-ΔA151R were protected against the challenge with the virulent parental virus ASFV-G. This is the first report indicating that the ASFV A151R gene is involved in virus virulence in domestic swine, suggesting that its deletion may be used to increase the safety profile of currently experimental vaccines.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Omics Lethal Human Viruses Project Profiling of the Host Response to MERS-CoV Infection, Processed Experimental Dataset Catalog

Middle East Respiratory Syndrome coronavirus (MERS-CoV) is classified as a Category C priority pathogen (Coronaviridae) by the National Institute of Allergy and Infectious Diseases (NIAID), and is known to cause severe respiratory disease with high mortality rates in humans. Lethal host-pathogen invasion mechanisms and the cellular intricacies behind these fatal infections still remain unclear. The NIAID Modeling Host Responses to Understand Severe Human Virus Infections Research Program project (2013-2018) aimed to develop an improved comprehensive understanding of the host response to a suite of viruses causing lethal infections leveraging a systems biology approach. Herein, PNNL sub-projects provide a never before released comprehensive infectious disease collection of primary and secondary transformation multi-Omics data profiling a series of priority pathogen primary experimental studies for enhanced open-access to viral Omics datasets and project lifecycle metadata. Secondary host-pathogen viral dataset downloads contain one or more statistically processed (normalization data transformation) quantitative dataset collections resulting in qualitative expression analyses of primary host-pathogen experimental study designs. Leveraging unique high-resolution Omics capabilities for proteomics (P), metabolomics (M), lipidomics (L), and transcriptomics (T) dataset downloads each have a direct relationship to a primary sample submission corresponding to a specific MERS-CoV [NCBITAXON:1335626] experimental infection study. Host sample types include human lung adenocarcinoma cells ["Calu-3", BTO:0002750], human bronchial epithelial cells ["Calu-3 clone 2B4"; BTO:0002022], primary human fibroblasts ["FB"; BTO:0000452], primary human airway epithelial cells ["HAE"; BTO:0005571], human microvascular endothelial cells ["HMVE"; BTO:0003123], and whole mouse lung [BTO:0000763] tissue collections.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

PNNL DataHub Project: Omics Lethal Human Viruses Project Profiling of the Host Response to Influenza A Virus Infection, Processed Experimental Dataset Catalog

Influenza A virus (IAV) is a high risk biological agent, classified as a Category C priority pathogen (Orthomyxoviridae) by the National Institute of Allergy and Infectious Diseases (NIAID), and is known to cause severe respiratory disease with high mortality rates in humans. Lethal host-pathogen invasion mechanisms and the cellular intricacies behind these fatal infections still remain unclear. The NIAID Modeling Host Responses to Understand Severe Human Virus Infections Research Program project (2013-2018) aimed to develop an improved comprehensive understanding of the host response to a suite of viruses causing lethal infections leveraging a systems biology approach. Herein, PNNL sub-projects provide a never before released comprehensive infectious disease collection of primary and secondary transformation multi-Omics data profiling a series of priority pathogen primary experimental studies for enhanced open-access to viral Omics datasets and project lifecycle metadata. Secondary host-pathogen viral dataset downloads contain one or more statistically processed (normalization data transformation) quantitative dataset collections resulting in qualitative expression analyses of primary host-pathogen experimental study designs. Leveraging unique high-resolution Omics capabilities for proteomics (P), metabolomics (M), lipidomics (L), and transcriptomics (T) dataset downloads each have a direct relationship to a primary sample submission corresponding to a specific Influenza A virus [NCBITAXON:11320] experimental infection study. Host sample types include human lung adenocarcinoma cells ["Calu-3", BTO:0002750] and whole mouse lung [BTO:0000763] tissue collections.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Defining Lipidomic Responses to Coronavirus Infection

Highly pathogenic human coronavirus infection can cause a severe atypical, rapid onset pneumonia with a mortality rate of up to 10% for severe acute respiratory syndrome coronavirus 1 (SARS-CoV 1), 35% for Middle East respiratory syndrome coronavirus (MERS-CoV), or 1% for severe acute respiratory syndrome coronavirus 2 (SARS-CoV 2 causative agent of COVID 19). While medical countermeasures successfully controlled the worldwide SARS-CoV epidemic, the MERS-CoV epidemic is still ongoing and continues to be a concern for travelers in the Middle East and the multi-year SARS-CoV 2 pandemic underscore the importance of defining biomarkers that are diagnostic and/or predictive of severe disease outcomes for respiratory viruses. Systems biology approaches provide global snapshots of infection induced changes in host cells/tissues and provide extremely rich datasets for understanding host pathogen interactions. Metabolites, especially lipids, are critical for viral replication but less is understood about infection induced changes to lipids due to limits in lipid species detection and identification. To characterize how individual lipid species and proteins with lipid associated functions contribute to highly pathogenic human coronavirus replication and disease severity, existing datasets were probed to determine cell type specific lipid responses to MERS-CoV infection and verification studies were performed to determine if modification of the host lipid signature (by inhibiting enzymatic functions that produce specific lipid species) can perturb CoV replication in human lung cells. MERS-CoV infects human lung epithelial, endothelial and fibroblast cells. All three cell types were infected with MERS-CoV and samples collected to analyze lipids, proteins, metabolites, and transcripts from 12 to 48 hours post infection. Time matched mock-infected cells were collected in parallel for each cell type. Following sample and statistical analysis, functional enrichment and bioinformatic analysis was performed to identify differentially expressed lipids and proteins. Two lipid species were found to be significantly upregulated following MERS-CoV infection, ceramides, and triacylglycerol both of which are indicative of cells undergoing apoptotic cell death. In contrast, sphingomyelins (lipid molecules that can serve as a precursor for one pathway for ceramide synthesis) had significantly decreased expression in MERS-CoV infected cells. An inhibitor of acid sphingomyelinase (that converts sphingomyelin to ceramides and phosphorylcholine) reduced MERS-CoV replication suggesting that production of ceramides is key for successful viral replication and transmission. Acyl-CoA-synthetase 3 (ACSL3), the only protein whose function is lipid associated and had increased differential expression in our dataset, regulates the synthesis of triacylglycerol (increased expression). Inhibitors that directly block ACSL3 (Triacsin C) but not steps later in the triacylglycerol synthesis pathway (Etomoxir) inhibit MERS-CoV replication suggesting that triacylglycerol production and/or ACSL3 activity is also key for viral replication. ACSL3 expression is also upregulated in lung cancer cells and is predicted to promote continued cell viability which would also enhance viral replication. The differentially expressed lipid and lipid-associated protein species identified in our studies suggest that MERS-CoV infection is activating cellular death pathways to limit the number of cells that become infected but also stimulating the production of lipid-associated enzymes that can prolong host cell viability and the amount of time progeny virions can be produced and released. As the inhibitors that worked against MERS-CoV infection were also efficacious against SARS-CoV 2 infection, countermeasures that target these host pathways may provide novel ways to block highly pathogenic human coronavirus infection and/or prevent severe disease outcomes.

59 BASIC BIOLOGICAL SCIENCES↗