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At least 631 records · Page 35
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Engineered human vascular models to study endothelial dysfunction in infectious disease

Vascular involvement plays a pivotal role in the pathogenesis of numerous emerging viral threats, with climate changes amplifying the likelihood of these diseases evolving into pandemics. Establishing an infectable and physiologically relevant human in vitro model holds immense importance in comprehending the pathogenesis of these threats and devising effective countermeasures. Although in vivo models provide valuable insight into disease, their application is restricted by interspecies variations, particularly concerning pathogens exclusive to humans. Moreover, animal models often fail to replicate comorbidities prevalent in patient populations, thus limiting our understanding of disease behavior in humans. In this study, we have devised a testing platform aimed at exploring pathogen interactions with innate immunity within the vasculature, encompassing both healthy and dysfunctional endothelial conditions.

42 ENGINEERING↗
DOE OSTI2024

Live-Cell Quantum Dot-Based Tracking of Plant & Microbial Extracellular Vesicles

All cellular organisms examined to date release various types of small vesicles called extracellular vesicles (EVs). They were originally thought to be unimportant, but research into EVs as carriers of key messages for communication within large, multicellular organisms or between interacting organisms has gained interest in many different scientific areas of study. Recently, it was discovered that both plants and their pathogenic fungi generate EVs and they are important vehicles for sending plant signals to thwart invasion by fungal pathogens, and in response, fungi use EVs to help evade plant defenses. This project aimed to develop new ways to visualize EVs and their potential nucleic acid cargo isolated from the crop plant, sorghum. We adapted a click chemistry-based method for making quantum dot-based RNA sensors, which will be a useful tool for others studying small RNAs. These sensors were not used detect RNA in sorghum EVs because unlike EVs from Arabidopsis, sorghum EVs were not enriched for specific small RNAs. This interesting difference shifted the project in an exciting direction, which focused on comparing EV proteomes. Our study discovered that greater than 60% of Arabidopsis EV proteins were also found in the sorghum EV proteome, revealing a partial conservation between a eudicot and monocot plant. These studies have raised new, fundamental questions on the conserved function of EVs in plants.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Multi-omics Characterization of the Host Response to COVID-19

This project is a multi-disciplinary collaboration between investigators at PNNL with expertise in mass spectrometry (MS)-based omics technology development, omics measurement methods development and application, statistics, machine learning and integration of disparate datasets for a systems-level understanding, and expertise in pathogenic coronaviruses, and investigators at the University of Wisconsin-Madison (UW-Madison) with expertise in pathogenic respiratory viruses (e.g. influenza). The goal of this project is to obtain a comprehensive picture of the human host factors critical for the outcome of SARS-CoV-2 infection. We will generate broad untargeted multi-omics profiles using both state-of-the-art and novel instrumentation and approaches to enable the identification of the molecular mechanisms and host response pathways that impact human COVID-19 outcomes. We anticipate these results will lead to the generation of biomarker panels that are predictive of disease outcomes and mechanistic hypotheses that can be further interrogated in future studies and will provide the basis for vaccine or therapeutic development. To do so, we are obtaining and analyzing blood samples from COVID-19 patients with a range of disease outcomes that were treated at the Center Hospital of the National Center for Global Health and Medicine in Tokyo, Japan and other collaborating hospitals in our network. Specifically, this project will fund proteomics and metabolomics analyses of clinical COVID samples, machine learning-based integration of the data, and pathway-based interpretation of the data. This project was funded in June 2020. In the time span of June to September 2020, the project team developed an analytically and statistically robust analysis plan and made various preparations to facilitate sample receipt from our UW-Madison collaborators. This included blocking and randomization of sample prep orders, ordering of reagents and reference materials, and shipping of materials needed for preparation of the samples under BSL3 conditions to our collaborators at UW-Madison. As of FY21, this project has been picked up via a sponsor, the Naval Medical Research Center, which will cover the remainder of the proposed scope of work.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

Rapid T cell engineering to counter emerging threats

There is a critical need for new approaches to effectively counter emerging pathogens, especially those which do not respond to antibodies or antibiotics. T cells represent an essential element of native immune response in many of the deadliest pathogens: controlling T cell reactivity and behavior would allow for countermeasures for currently untreatable diseases from cancer to coronaviruses, especially if using a patient’s own T cells (autologous) where no host rejection will occur. However, current methods for modifying T cells, e.g., FDA-approved chimeric antigen receptor T cell (CAR) approaches, require genetic manipulation and expansion which can take weeks to generate.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

A spatially regularized detector for emergent/re-emergent disease outbreaks

Early detection of outbreaks caused by emergent pathogens, using epidemiological surveillance data i.e., daily case counts, is difficult. This is because the data tend to be noisy during the early epoch of the outbreak. In contrast, the spread-rate of the disease tends to be well-behaved, as it depends only on the mixing patterns of the population and the characteristics of the pathogen, neither of which behave erratically in space-time. In this report, we explore whether the spread-rate can be used for epidemiological surveillance, conditional on case count data. Estimating the spread-rate from case count data allows us to exploit exogenous information, e.g., incubation period distributions etc., which can considerably smooth out any erratic temporal behavior. Further, epidemiological dynamics are spatially correlated, and if case counts are available for multiple areal units e.g., counties, these correlations could potentially be used to suppress noise in the early epoch data. These exogenous information and structure are not exploited by conventional syndromic surveillance detectors to extract a well-behaved latent variable for monitoring purposes. The technical challenge lies in the estimation of the spread-rate field jointly over a collection of areal units; further, the spread-rate varies over time. We develop a method based on mean-field variational inference to approximately estimate the spread-rate field, using a Gaussian Random Field Model for spatial regularization. The method is tested on the estimation of spread-rate in the thirty-three counties of New Mexico and detect the arrival of the Fall 2020 COVID-19 wave in September 2020. We find that the method is scalable, but underestimates the uncertainty in the estimated spread-rate field. We detect the arrival of the Fall 2020 wave a week ahead of conventional syndromic surveillance algorithms, but our simplistic detection algorithm, based on simple anomaly detection, suffers from a high false positive rate, similar to conventional detectors.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Developing a Vaccine Platform for a Balanced Mucosal Immune Response (CB11446), Project Report: Year 1

Mucosal vaccines can elicit protective immune responses at the infection site of respiratory or aerosolized pathogens. Achieving balanced mucosal and systemic responses is a key challenge in the design of mucosal vaccines, especially in terms of developing a broadly applicable vaccine delivery platform amenable to a wide range of subunit vaccine antigens. The overarching goal of the project entitled “Developing a Vaccine Platform for a Balanced Mucosal Immune Response” is to develop a pathogen-agnostic vaccine platform that elicits robust and balanced mucosal immune responses upon intranasal vaccination, in the context of a nanolipoprotein particle (NLP) platform. In year one, we investigated NLP-based vaccine formulations incorporating select immune adjuvants (Monophosphoryl Lipid A (MPLA), FSL-1, L18-muramyl dipeptide (MDP), and cholesterol-tagged ODN2006 (cCpG)) along with antigens relevant to plague (LcrV), tularemia (IglC), and Ebola virus (GP). We demonstrated the ability to prepare, characterize, and quantify these formulations. We then carried out studies in vivo using a BALB/c mouse model, comparing intranasal and intramuscular administration and systematically evaluated the resulting mucosal and systemic immune responses using ELISpot and ELISAs. All proposed tasks (Table 1) were completed within the twelve-month base period, and the established go/no go metric was successfully achieved. Numerous adjuvant:LcrV:NLP formulations were found to have statistically significant increases in IgA titers in serum and/or lung upon IN administration (compared to IM administration), while also producing robust IgG responses in serum. Some formulations also showed significant IFNγ responses using restimulated splenocytes. The data collected during the base period provide valuable insights for the future design of safe and effective mucosal subunit vaccines while also highlighting areas of research that merit further investigation.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

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

Human Interferon (IFN) alpha, beta, and gamma participate in the body's natural immune response to lethal virus infection and disease.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. 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-associated 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. Transcriptomics (T) dataset downloads each have a direct relationship to a primary sample submission corresponding to a specific Human Interferon (IFN), interferon alpha (IFNα), interferon beta (IFNβ), and/or interferon gamma (IFNγ) stimulated response to an experimental virus infection treatment study. Host sample types include cerebellum ["CB", BTO:0000232], cortical neurons ["CN", BTO:0004102], cortex ["CT", BTO:0000233], dendritic cells ["DC", BTO:0002042], granule cell neurons ["GCN", BTO:0003393], lymph node ["LN", BTO:0000784], and serum ["SE", BTO:0001239] from mouse (Mus musculus) tissue collections.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

KBase Narrative - Draft Genome of Roseomonas Strain GC11

This narrative was used for the draft genome of a Roseomonas species Strain GC11. This genus includes 6 known species. The specimen was collected using a water grab method in Conservancy Park, a freshwater site in Belleview, KY. This species is often identified in aquatic environments and is a known pathogen to humans1. It has been reported in healthcare settings from bacteremia in the blood and has also been reported to be found in human catheters. Due to the the prevelance as a human pathogen and lack of isolation in a non-human environment this strain was of particular interest.

Cooper, Joshua [Northern Kentucky University, Depa↗
DOE OSTI2026

Beyond sequence similarity: toward function-based screening of nucleic acid synthesis

Synthetic nucleic acids are a key input to modern biotechnology, yet they represent dual-use materials that require robust screening to mitigate biosecurity risks. The prevailing screening paradigm, which identifies sequences of concern (SoCs) through sequence similarity to controlled pathogens and toxins, may not fully capture risks posed by AI tools that can decouple biomolecular function from reliance on known sequences. Rapidly advancing biodesign capabilities enable the generation of genes and proteins that might evade sequence-based detection. We highlight the critical need for function-based screening approaches that can detect sequences capable of hazardous biological functions, regardless of similarity to known SoCs. We examine the feasibility of function-based screening with an initial focus on proteins, arguing that, while protein sequence space is vast, biologically functional proteins are significantly constrained by biophysical and biochemical requirements that can be learned and modeled. We propose a concrete implementation framework organized along a continuum of complexity, starting with toxins as the most tractable targets before expanding to more complex pathogenic functions. We then discuss open challenges and describe a research and development strategy to address them.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

The multifaceted role of c-di-AMP signaling in the regulation of Porphyromonas gingivalis lipopolysaccharide structure and function

This study unveils the intricate functional association between cyclic di-3’,5’-adenylic acid (c-di-AMP) signaling, cellular bioenergetics, and the regulation of lipopolysaccharide (LPS) profile in Porphyromonas gingivalis, a Gram-negative obligate anaerobe considered as a keystone pathogen involved in the pathogenesis of chronic periodontitis. Previous research has identified variations in P. gingivalis LPS profile as a major virulence factor, yet the underlying mechanism of its modulation has remained elusive. We employed a comprehensive methodological approach, combining two mutants exhibiting varying levels of c-di-AMP compared to the wild type, alongside an optimized analytical methodology that combines conventional mass spectrometry techniques with a novel approach known as FLAT n . We demonstrate that c-di-AMP acts as a metabolic nexus, connecting bioenergetic status to nuanced shifts in fatty acid and glycosyl profiles within P. gingivalis LPS. Notably, the predicted regulator gene cdaR, serving as a potent regulator of c-di-AMP synthesis, was found essential for producing N-acetylgalactosamine and an unidentified glycolipid class associated with the LPS profile. The multifaceted roles of c-di-AMP in bacterial physiology are underscored, emphasizing its significance in orchestrating adaptive responses to stimuli. Furthermore, our findings illuminate the significance of LPS variations and c-di-AMP signaling in determining the biological activities and immunostimulatory potential of P. gingivalis LPS, promoting a pathoadaptive strategy. The study expands the understanding of c-di-AMP pathways in Gram-negative species, laying a foundation for future investigations into the mechanisms governing variations in LPS structure at the molecular level and their implications for host-pathogen interactions.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Computational tools and data integration to accelerate vaccine development: challenges, opportunities, and future directions

The development of effective vaccines is crucial for combating current and emerging pathogens. Despite significant advances in the field of vaccine development there remain numerous challenges including the lack of standardized data reporting and curation practices, making it difficult to determine correlates of protection from experimental and clinical studies. Significant gaps in data and knowledge integration can hinder vaccine development which relies on a comprehensive understanding of the interplay between pathogens and the host immune system. In this review, we explore the current landscape of vaccine development, highlighting the computational challenges, limitations, and opportunities associated with integrating diverse data types for leveraging artificial intelligence (AI) and machine learning (ML) techniques in vaccine design. We discuss the role of natural language processing, semantic integration, and causal inference in extracting valuable insights from published literature and unstructured data sources, as well as the computational modeling of immune responses. Furthermore, we highlight specific challenges associated with uncertainty quantification in vaccine development and emphasize the importance of establishing standardized data formats and ontologies to facilitate the integration and analysis of heterogeneous data. Through data harmonization and integration, the development of safe and effective vaccines can be accelerated to improve public health outcomes. Looking to the future, we highlight the need for collaborative efforts among researchers, data scientists, and public health experts to realize the full potential of AI-assisted vaccine design and streamline the vaccine development process.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

Proteomic Signatures of Antimicrobial Resistance in Yersinia pestis and Francisella tularensis

Antimicrobial resistance (AMR) is a well-recognized, widespread, and growing issue of concern. With increasing incidence of AMR, the ability to respond quickly to infection with or exposure to an AMR pathogen is critical. Approaches that could accurately and more quickly identify whether a pathogen is AMR also are needed to more rapidly respond to existing and emerging biological threats. We examined proteins associated with paired AMR and antimicrobial susceptible (AMS) strains of Yersinia pestis and Francisella tularensis, causative agents of the diseases plague and tularemia, respectively, to identify whether potential existed to use proteins as signatures of AMR. We found that protein expression was significantly impacted by AMR status. Antimicrobial resistance-conferring proteins were expressed even in the absence of antibiotics in growth media, and the abundance of 10–20% of cellular proteins beyond those that directly confer AMR also were significantly changed in both Y. pestis and F. tularensis. Most strikingly, the abundance of proteins involved in specific metabolic pathways and biological functions was altered in all AMR strains examined, independent of species, resistance mechanism, and affected cellular antimicrobial target. We have identified features that distinguish between AMR and AMS strains, including a subset of features shared across species with different resistance mechanisms, which suggest shared biological signatures of resistance. These features could form the basis of novel approaches to identify AMR phenotypes in unknown strains.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Case report: Fatal Legionella infection diagnosed via by metagenomic next-generation sequencing in a patient with chronic myeloid leukemia

Legionella is an aerobic, gram-negative, intracellular pathogen and is an important cause of community-acquired pneumonia. Legionella pneumophila is the most common causative agent of Legionella pneumonia. Clinical diagnosis of Legionella pneumonia is challenging due to the lack of specific clinical manifestations and the low positive rates of conventional pathogen detection methods. In this study, we report a case of a patient with chronic myeloid leukemia who developed rigors and high fever after chemotherapy and immunotherapy. Chest computed tomography revealed consolidation in the left lower lobe of the lung and ground-glass opacities in both lower lobes. Multiple blood cultures showed Escherichia coli , Staphylococcus aureus , Bacillus licheniformis , and positive results in the β-D-glucan test (G test). The patient was treated with various sensitive antimicrobial agents, including meropenem plus fluconazole, meropenem plus carpofungin, and vancomycin. Unfortunately, the patient’s condition gradually worsened and eventually resulted in death. On the following day of death, metagenomic next-generation sequencing (mNGS) of 1whole blood revealed L. pneumophila pneumonia with concurrent bloodstream infection (blood mNGS reads 114,302). These findings suggest that when conventional empirical antimicrobial therapy proves ineffective for critically ill patients with pneumonia, the possibility of combined Legionella infection must be considered, and mNGS can provide a diagnostic tool in such cases.

Bu, Chunhong↗
DOE OSTI2023

Comparative transcriptome analysis of rainbow trout gonadal cells (RTG-2) infected with U and J genogroup infectious hematopoietic necrosis virus

Infectious hematopoietic necrosis virus (IHNV) is the causative pathogen of infectious hematopoietic necrosis, outbreaks of which are responsible for significant losses in rainbow trout aquaculture. Strains of IHNV isolated worldwide have been classified into five major genogroups, J, E, L, M, and U. To date, comparative transcriptomic analysis has only been conducted individually for the J and M genogroups. In this study, we compared the transcriptome profiles in U genogroup and J genogroup IHNV-infected RTG-2 cells with mock-infected RTG-2 cells. The RNA-seq results revealed 17,064 new genes, of which 7,390 genes were functionally annotated. Differentially expressed gene (DEG) analysis between U and J IHNV-infected cells revealed 2,238 DEGs, including 1,011 downregulated genes and 1,227 upregulated genes. Among the 2,238 DEGs, 345 new genes were discovered. The DEGs related to immune responses, cellular signal transduction, and viral diseases were further analyzed. RT-qPCR validation confirmed that the changes in expression of the immune response-related genes trpm2 , sting , itgb7 , ripk2 , and irf1 , cellular signal transduction-related genes irl , cacnb2 , bmp2l , gadd45α , and plk2 , and viral disease-related genes mlf1, mtor, armc5 , pik3r1 , and c-myc were consistent with the results of transcriptome analysis. Taken together, our findings provide a comprehensive transcriptional analysis of the differential virulence of the U and J genogroups of IHNV, and shed new light on the pathogenic mechanisms of IHNV strains.

Zhao, Jing-Zhuang↗
DOE OSTI2023

Identification of Colletotrichum aenigma as the new causal agent of leaf blight disease on Aucuba japonica Thunb., and screenings of effective fungicides for its sustainable management

Aucuba japonica Thunb is an evergreen woody ornamental plant with significant economic and ecological values. It also produces aucubin, showing a variety of biological activities. It is widely planted in the southwest region of China, including karst landscape areas in Guizhou Province. In January 2022, a serious leaf blight disease was observed on the leaves of A. japonica in the outdoor gardens of Guizhou University, Guiyang, Guizhou, China. The causal agent was identified as Colletotrichum aenigma through amplification and sequencing of the internal transcribed spacer (ITS) region, translation of the chitin synthase ( CHS ) and actin ( ACT ) genes, and morphological characterizations. Koch’s postulates were confirmed by its pathogenicity on healthy leaves, including re-isolation and identification. To our knowledge, this is the first report of C. aenigma causing leaf blight on A. japonica worldwide. To identify pathogen characteristics that could be utilized for future disease management, the effects of temperature and light on mycelial growth, conidia production, and conidial germination, and the effects of humidity on conidial germination were studied. Optimal temperatures for mycelial growth of C. aenigma BY827 were 25–30°C, while 15°C and 35°C were favorable for conidia production. Concurrently, alternating 10-h light and 14-h dark, proved to be beneficial for mycelial growth and conidial germination. Additionally, conidial germination was enhanced at 90% humidity. In vitro screenings of ten chemical pesticides to assess their efficacy in suppressing C. aenigma representative strain BY827. Among them, difenoconazole showed the best inhibition rate, with an EC 50 (concentration for 50% of maximal effect) value of 0.0148 μg/ml. Subsequently, field experiment results showed that difenoconazole had the highest control efficiency on A. japonica leaf blight (the decreasing rate of disease incidence and decreasing rate of disease index were 44.60 and 47.75%, respectively). Interestingly, we discovered that C. aenigma BY827 may develop resistance to mancozeb, which is not reported yet among Colletotrichum spp. strains. In conclusion, our study provided new insights into the causal agent of A. japonica leaf blight, and the effective fungicides evaluated provided an important basis and potential resource for the sustainable control of A. japonica leaf blight caused by C. aenigma in the field.

Fan, Ruidong↗
DOE OSTI2024

Genomic and phenotypic characterization of multidrug-resistant Salmonella enterica serovar Reading isolates involved in a turkey-associated foodborne outbreak

Salmonella is a global bacterial foodborne pathogen associated with a variety of contaminated food products. Poultry products are a common source of Salmonella -associated foodborne illness, and an estimated 7% of human illnesses in the United States are attributed to turkey products. From November 2017 to March 2019, the Centers for Disease Control and Prevention reported a turkey-associated outbreak of multidrug-resistant (MDR; resistant to ≥3 antimicrobial classes) Salmonella enterica serovar Reading ( S . Reading) linked to 358 human infections in 42 US states and Canada. Since S . Reading was seldom linked to human illness prior to this outbreak, the current study compared genomic sequences of S . Reading isolates prior to the outbreak (pre-outbreak) to isolates identified during the outbreak period, focusing on genes that were different between the two groups but common within a group. Following whole-genome sequence analysis of five pre-outbreak and five outbreak-associated turkey/turkey product isolates of S . Reading, 37 genes located within two distinct chromosomal regions were identified only in the pre-outbreak isolates: (1) an ~5 kb region containing four protein-coding genes including uidA which encodes beta-glucuronidase, pgdA encoding peptidoglycan deacetylase, and two hypothetical proteins and (2) an ~28 kb region comprised of 32 phage-like genes and the xerC gene, which encodes tyrosine recombinase (frequently associated with phage genes). The five outbreak isolates also had a deletional event within the cirA gene, introducing a translational frame shift and premature stop codon. The cirA gene encodes a protein with dual receptor functions: a siderophore receptor for transport of dihydroxybenzoylserine as well as a colicin Ia/b receptor. Significant differences for the identified genetic variations were also detected in 75 S . Reading human isolates. Of the 41 S . Reading isolates collected before or in 2017, 81 and 90% of the isolates contained the uidA and pgdA genes, respectively, but only 24% of the isolates collected after 2017 harbored the uidA and pgdA genes. The truncation event within the cirA gene was also significantly higher in isolates collected after 2017 (74%) compared to before or in 2017 (5%). Phenotypic analysis of the S . Reading isolates for colicin and cefiderocol sensitivities (CirA) and β-methyl-D-glucuronic acid utilization (UidA and accessory proteins) supported the genomic data. Overall, a similar genome reduction pattern was generally observed in both the turkey and human isolates of S . Reading during the outbreak period, and the genetic differences were present in genes that could potentially promote pathogen dissemination due to variation in Salmonella colonization, fitness, and/or virulence.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Impact of intense sanitization procedures on bacterial communities recovered from floor drains in pork processing plants

Pork processing plants in the United States (US) cease operations for 24–48 h every six or twelve months to perform intense sanitization (IS) using fogging, foaming, and further antimicrobial treatments to disrupt natural biofilms that may harbor pathogens and spoilage organisms. The impact such treatments have on short-term changes in environmental microorganisms is not well understood, nor is the rate at which bacterial communities return. Swab samples were collected from floor drains to provide representative environmental microorganisms at two US pork processing plants before, during, and after an IS procedure. Samples were collected from four coolers where finished carcasses were chilled and from four locations near cutting tables. Each sample was characterized by total mesophile count (TMC), total psychrophile count (TPC), and other indicator bacteria; their biofilm-forming ability, tolerance of the formed biofilm to a quaternary ammonium compound (300 ppm, QAC), and ability to protect co-inoculated Salmonella enterica. In addition, bacterial community composition was determined using shotgun metagenomic sequencing. IS procedures disrupted bacteria present but to different extents depending on the plant and the area of the plant. IS reduced TPC and TMC, by up to 1.5 Log 10 CFU only to return to pre-IS levels within 2–3 days. The impact of IS on microorganisms in coolers was varied, with reductions of 2–4 Log 10 , and required 2 to 4 weeks to return to pre-IS levels. The results near fabrication lines were mixed, with little to no significant changes at one plant, while at the other, two processing lines showed 4 to 6 Log 10 reductions. Resistance to QAC and the protection of Salmonella by the biofilms varied between plants and between areas of the plants as well. Community profiling of bacteria at the genus level showed that IS reduced species diversity and the disruption led to new community compositions that in some cases did not return to the pre-IS state even after 15 to 16 weeks. The results found here reveal the impact of using IS to disrupt the presence of pathogen or spoilage microorganisms in US pork processing facilities may not have the intended effect.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Non-Thermal Plasma as a Novel Strategy for Treating or Preventing Viral Infection and Associated Disease

Pathogenic viruses cause many human, animal, and plant diseases that are associated with substantial morbidity, mortality and socio-economic impact. Although effective strategies for combatting virus transmission and associated disease are available, global outbreaks of viral pathogens such as the virus responsible for the COVID-19 pandemic demonstrate that there is still a critical need for new approaches that can be used to interrupt the chain of viral infection and mitigate virus-associated pathogenesis. Recent studies point to non-thermal plasma (NTP), a partly ionized gas comprised of a complex mixture of reactive oxygen and nitrogen species along with physical effectors, as the potential foundation for new antiviral approaches. A more thorough understanding of the antiviral properties and safety of NTP has stimulated explorations of NTP as the basis for treatments of viral diseases. The recently described immunomodulatory properties of NTP are also being evaluated for potential use in immunotherapies of viral diseases as well as in antiviral vaccination strategies. In this review, we present the current state-of-the-art in addition to compelling arguments that NTP merits further exploration for use in the prevention and management of viral infections and associated diseases.

60 APPLIED LIFE SCIENCES↗