Biology subjects

Waters, K. M.

Publications and source records attributed to Waters, K. M..

5 recordsLinked to original sources

bioRxiv2024

Dysregulation of lung epithelial cell homeostasis and immunity contributes to Middle East Respiratory Syndrome coronavirus disease severity

Coronaviruses (CoV) emerge suddenly from animal reservoirs to cause novel diseases in new hosts. Discovered in 2012, Middle East respiratory syndrome coronavirus (MERS-CoV) is endemic in camels in the Middle East and is continually causing local outbreaks and epidemics. While all three newly emerging human CoV from past 20 years (SARS-CoV, SARS-CoV-2, MERS-CoV) cause respiratory disease, each CoV has unique host interactions that drive differential pathogeneses. To better understand the virus and host interactions driving lethal MERS-CoV infection, we performed a longitudinal multi-omics analysis of sublethal and lethal MERS-CoV infection in mice. Significant differences were observed in body weight loss, virus titers and acute lung injury among lethal and sub-lethal virus doses. Virus induced apoptosis of type I and II alveolar epithelial cells suggest that loss or dysregulation of these key cell populations was a major driver of severe disease. Omics analysis suggested differential pathogenesis was multi-factorial with clear differences among innate and adaptive immune pathways as well as those that regulate lung epithelial homeostasis. Infection of mice lacking functional T and B-cells showed that adaptive immunity was important in controlling viral replication but also increased pathogenesis. In summary, we provide a high-resolution host response atlas for MERS-CoV infection and disease severity. Multi-omics studies of viral pathogenesis offer a unique opportunity to not only better understand the molecular mechanisms of disease but also to identify genes and pathways that can be exploited for therapeutic intervention all of which is important for our future pandemic preparedness. ImportanceEmerging coronaviruses like SARS-CoV, SARS-CoV-2 and MERS-CoV cause a range of disease outcomes in humans from asymptomatic, moderate and severe respiratory disease which can progress to death but the factors causing these disparate outcomes remain unclear. Understanding host responses to mild and life-threatening infection provides insight into virus-host networks within and across organ systems that contribute to disease outcomes. We used multi-omics approaches to comprehensively define the host response to moderate and severe MERS-CoV infection. Severe respiratory disease was associated with dysregulation of the immune response. Key lung epithelial cell populations that are essential for lung function get infected and die. Mice lacking key immune cell populations experienced greater virus replication but decreased disease severity implicating the immune system in both protective and pathogenic roles in the response to MERS-CoV. These data could be utilized to design new therapeutic strategies targeting specific pathways that contribute to severe disease.

microbiology↗

bioRxiv2023

Expanding the access of wearable silicone wristbands in community-engaged research through best practices in data analysis and integration

Wearable silicone wristbands are a rapidly growing exposure assessment technology that offer researchers the ability to study previously inaccessible cohorts and have the potential to provide a more comprehensive picture of chemical exposure within diverse communities. However, there are no established best practices for analyzing the data within a study or across multiple studies, thereby limiting impact and access of these data for larger meta-analyses. We utilize data from three studies, from over 600 wristbands worn by participants in New York City and Eugene, Oregon, to present a first-of-its-kind manuscript detailing wristband data properties. We further discuss and provide concrete examples of key areas and considerations in common statistical modeling methods where best practices must be established to enable meta-analyses and integration of data from multiple studies. Finally, we detail important and challenging aspects of machine learning, meta-analysis, and data integration that researchers will face in order to extend beyond the limited scope of individual studies focused on specific populations.

bioinformatics↗

bioRxiv2022

Host network-based discovery of critical regulators of innate immunity, virus growth, and pathogenesis in influenza virus infection

Innate immunity is protective against viruses, but also can facilitate pathological infection responses. Despite intensive research, our understanding of the mechanisms that regulate innate immunity in virus infection remains incomplete. Systems biology-based data-driven modeling approaches hold substantial promise toward discovery of crucial innate immune signaling regulators, yet model-derived predictions are almost completely unexplored. Here, we carried out systematic experimental validation of candidate regulators predicted by a transcriptional association network model of influenza virus-infected cells. We identified dozens of novel innate immune signaling regulators with potent effects on the replication of influenza and other viruses, and importantly, we established the biological relevance of a validated regulator in vivo. Collectively, these findings aid in clarifying mechanisms of influenza virus pathogenicity and might lead to innovative approaches for treating influenza virus disease. Similar data-driven modeling strategies may be applicable for the study of other pathogen systems or immunological disorders.

microbiology↗

bioRxiv2018

Combination attenuation offers strategy for live-attenuated coronavirus vaccines

With an ongoing threat posed by circulating zoonotic strains, new strategies are required to prepare for the next emergent coronavirus (CoV). Previously, groups had targeted conserved coronavirus proteins as a strategy to generate live-attenuated vaccine strains against current and future CoVs. With this in mind, we explored whether manipulation of CoV NSP16, a conserved 2O methyltransferase (MTase), could provide a broad attenuation platform against future emergent strains. Using the SARS-CoV mouse model, a NSP16 mutant vaccine was evaluated for protection from heterologous challenge, efficacy in the aging host, and potential for reversion to pathogenesis. Despite some success, concerns for virulence in the aged and potential for reversion makes targeting NSP16 alone an untenable approach. However, combining a 2O MTase mutation with a previously described CoV fidelity mutant produced a vaccine strain capable of protection from heterologous virus challenge, efficacy in aged mice, and no evidence for reversion. Together, the results indicate that targeting the CoV 2O MTase in parallel with other conserved attenuating mutations may provide a platform strategy for rapidly generating live-attenuated coronavirus vaccines.\n\nSignificanceEmergent coronaviruses remain a significant threat to global public health and rapid response vaccine platforms are needed to stem future outbreaks. However, failure of many previous CoV vaccine formulations has clearly highlighted the need to test efficacy under different conditions and especially in vulnerable populations like the aged and immune-compromised. This study illustrates that despite success in young models, the NSP16 mutant carries too much risk for pathogenesis and reversion in vulnerable models to be used as a stand-alone vaccine strategy. Importantly, the NSP16 mutation can be paired with other attenuating approaches to provide robust protection from heterologous challenge and in vulnerable populations. Coupled with increased safety and reduced pathogenesis, the study highlights the potential for NSP16 attenuation as a major component of future live-attenuated coronavirus vaccines.

microbiology↗

bioRxiv2017

MERS-CoV NSP16 necessary for IFN resistance and viral pathogenesis

Coronaviruses encode a mix of highly conserved and novel genes as well as genetic elements necessary for infection and pathogenesis, raising the possibility for common targets for attenuation and therapeutic design. In this study, we focus on the highly conserved nonstructural protein (NSP) 16, a viral 2O methyl-transferase (MTase) that encodes critical functions in immune modulation and infection. Using reverse genetics, we disrupted a key motif in the conserved KDKE motif of MERS NSP16 (D130A) and evaluated the effect on viral infection and pathogenesis. While the absence of 2O MTase activity had only marginal impact on propagation and replication in Vero cells, the MERS dNSP16 mutant demonstrated significant attenuation relative to control both in primary human airway cultures and in vivo. Further examination indicated the MERS dNSP16 mutant had a type I IFN based attenuation and was partially restored in the absence of IFIT molecules. Importantly, the robust attenuation permitted use of MERS dNSP16 as a live attenuated vaccine platform protecting from challenge with a mouse adapted MERS-CoV strain. These studies demonstrate the importance of the conserved 2O MTase activity for CoV pathogenesis and highlight NSP16 as a conserved universal target for rapid live attenuated vaccine design in an expanding CoV outbreak setting.\n\nSignificanceCoronavirus emergence in both human and livestock represents a significant threat to global public health, as evidenced by the sudden emergence of SARS-CoV, MERS-CoV, PEDV and swine delta coronavirus in the 21st century. These studies describe an approach that effectively targets the highly conserved 2O methyl-transferase activity of coronaviruses for attenuation. With clear understanding of the IFN/IFIT based mechanism, NSP16 mutants provide a suitable target for a live attenuated vaccine platform as well as therapeutic development for both current and future emergent CoV strains. Importantly, other approaches targeting other conserved pan-coronavirus functions have not yet proven effective against MERS-CoV, illustrating the broad applicability of targeting viral 2O MTase function across coronaviruses.

microbiology↗