Biology subjects

Kelly, J. D.

Publications and source records attributed to Kelly, J. D..

11 recordsLinked to original sources

bioRxiv2026

Persistently activated virus-specific CD8 T cells indicate antigen-driven immune aberrations in long COVID

Long COVID (LC) affects millions of people worldwide, yet its driving mechanisms remain incompletely defined and no treatment has been approved. Persistence of SARS-CoV-2 and reactivation of herpesviruses have been implicated in LC, but direct detection of these viral antigens in blood and tissues has been challenging. T cells are exquisitely sensitive to viral antigens, survey organs throughout the body, and can be readily sampled in peripheral blood. Using high-dimensional spectral flow cytometry and single-cell sequencing approaches with multiplexed peptide/HLA tetramers, we profiled virus-specific T cells from hundreds of people with LC and recovered controls. We identified a subset of people with LC that maintained elevated activation of CD8 T cells targeting SARS-CoV-2 spike and/or lytic antigens from Epstein-Barr virus, but not other viral specificities. Spike-specific cells in LC expressed genes linked to TCR stimulation, terminal effector differentiation, and exhaustion and demonstrated reduced functionality upon cognate peptide stimulation ex vivo. Thus, T cells from a subset of people with LC are likely chronically stimulated by persistent SARS-CoV-2 antigens. These findings establish the use of T cells as biosensors of persisting antigen in LC and other disease settings and may help develop new therapeutic strategies for LC.

immunology↗

bioRxiv2026

Multiomic and Spatial Profiling of Colorectal Tissue Reveals Viral Persistence and Immune Dysregulation in Long COVID

Long COVID (LC) - a chronic condition characterized by persistent, debilitating symptoms following SARS-CoV-2 infection - has emerged as a major public health challenge. Although many interrelated mechanisms have been proposed as drivers of LC, the root causes have yet to be identified, posing significant challenges for therapeutic development. While many blood-based studies have been conducted, they have not yielded conclusive mechanistic insights into LC pathogenesis. Attention has therefore turned toward direct tissue investigation, with the gastrointestinal (GI) tract becoming a major focus due to evidence that virus or viral components can persist at this site for months to years following an episode of COVID-19. Here, we performed a high-dimensional characterization of colorectal tissue and peripheral blood in a highly characterized cohort of 44 people with LC and 13 recovered controls. We profiled SARS-CoV-2 persistence, host immune responses, and tissue inflammation using bulk and single-cell RNA sequencing, nCounter RNA probe hybridization, quantitative PCR, metagenomic next-generation sequencing, plasma proteomics, high-dimensional spectral flow cytometry, in situ-hybridization/immunohistochemistry, and single-cell digital spatial omics. Our results support a model in which LC is driven by long-term immune dysregulation and perturbations of the regulatory gut immune environment which imply ongoing viral persistence, although direct viral detection was only observed in a subset of participants. Specifically, we identify a tissue-based transcriptional environment in which SARS-CoV-2 activates innate myeloid immune signaling, driving chronic inflammation while simultaneously downregulating pathways responsible for immune-mediated clearance of infected cells, including antigen presentation, phagocytosis, cytotoxic immune cell trafficking, and granzyme production. Importantly, signatures in peripheral blood are considerably weaker than those observed in tissue. Together, these findings provide a direct biological rationale for therapeutic strategies in LC aimed at enhancing or redirecting cytotoxic immune function to overcome immune dysregulation and clear persistent viral reservoirs.

immunology↗

bioRxiv2025

Increased mannosylation of extracellular vesicles in Long COVID plasma provides a potential therapeutic target for Galanthus nivalis agglutinin (GNA) affinity resin

There is no proven therapy for Long COVID, a post-acute illness characterized by a myriad of diverse symptoms including fatigue, dyspnea, and brain fog following SARS-CoV-2 infection. Extracellular vesicles (EVs) have been implicated in Long COVID pathogenesis by promoting viral and inflammatory signaling with their molecular cargo. In this study, we investigated whether EV abundance and glycome characteristics are altered in plasma from people with Long COVID and whether they can be targeted for removal using a glycan-binding affinity resin. Large (100-500 nm) and small (40-200 nm) EVs were isolated from plasma of participants in the post-acute phase of COVID-19 and analyzed by nanoparticle flow cytometry to measure concentration and glycan characteristics. Plasma of those with Long COVID contained elevated levels of both large and small EVs, and mannose-positive large EVs were significantly increased in comparison to recovered controls (p < 0.05). EV capture assays using Galanthus nivalis agglutinin (GNA) affinity resin demonstrated small EV removal positively correlated with mannose-positive EV abundance (r = 0.341, p < 0.05). NanoString analyses identified seven EV-associated miRNAs significantly depleted by GNA affinity resin treatment of plasma. PROGENy pathway inference of validated miRNA-mRNA interactions suggests these reductions may lead to a downregulation of JAK-STAT signaling and upregulation of Estrogen, VEGF, and PI3K pathways, resulting in a favorable rebalancing of immune and tissue-repair networks. These findings reveal specific glycome EV-miRNA cargo signatures in Long COVID and the potential clinical benefits of a lectin capture therapeutic strategy to remove these pathogenic vesicles and their inflammatory cargo.

molecular biology↗

bioRxiv2024

K-mer Genome-wide Association Study for Anthracnose and BCMV Resistance in the Andean Diversity Panel

Limited genomic resources and closely linked marker-trait associations for common beans (Phaseolus vulgaris L.) have limited breeders from fully utilizing molecular genetics technologies to maximize genetic gain. The emergence of virulent races of anthracnose (caused by Colletotrichum lindemuthianum) and Bean Common Mosaic Virus (BCMV) highlight the need for improved methods to identify and incorporate pan-genomic variation in breeding for disease resistance. We sequenced the P. vulgaris Andean Diversity Panel (ADP) and performed a genome-wide association study (GWAS) to identify associations for resistance to BCMV and eight races of anthracnose. Historical single nucleotide polymorphism (SNP)-chip and phenotypic data enabled a three-way comparison between SNP-chip, reference-based whole genome shotgun sequence (WGS)-SNP, and reference-free k-mer GWAS. Across all traits, there was excellent concordance between SNP-chip, WGS-SNP, and k-mer GWAS results--albeit at a much higher marker resolution for the WGS data sets. Significant k-mer haplotype variation revealed selection of the linked I-gene and Co-u traits in North American breeding lines and cultivars. Due to k-mer mapping criteria and the absence of target loci in the reference genome due to structural variation, only 9.1 to 47.3% of the significantly associated k-mers were mapped to the reference genome. To determine the genetic context of cis-associated k-mers, we generated whole genome assemblies of four ADP accessions and identified an expanded local repertoire of disease resistance genes associated with resistance to anthracnose and BCMV. With access to variant data in the context of a pan-genome, high resolution mapping of agronomic traits for common bean is now feasible. CORE IDEASO_LIK-mer-based GWAS offers new advantages for mapping pan-genomic variation C_LIO_LIComparison of reference-based SNP to reference-free k-mer GWAS C_LIO_LINovel discovery of cis-associated k-mers for dry bean disease resistance C_LI PLAIN LANGUAGE SUMMARYImproving disease resistance in crop species such as bean is critical. We surveyed the genomes of a diverse set of bean lines and identified sequences associated with resistance to a fungal and viral pathogen. Access to the genomes of this diversity panel of beans will permit additional discoveries on the role of structural variation in phenotypes, including disease resistance.

plant biology↗

bioRxiv2024

The effect of circulating neutralizing antibodies on the replication of SARS-CoV-2 variants following post-vaccination infections.

The impact of pre-existing neutralizing antibodies (NAbs) titers on SARS-CoV-2 viral shedding dynamics in post-vaccination infection (PVI) are not well understood. We characterized viral shedding longitudinally in nasal specimens in relation to baseline (pre/peri-infection) serum neutralizing antibody titers in 125 participants infected with distinct SARS-CoV-2 variants. Among 68 participants who had received vaccinations, we quantified the effect of baseline serum NAb titers on maximum viral RNA titers and on the duration of infectivity. Baseline NAb titers were higher and efficiently targeted a broader range of variants in participants who received one or two monovalent ancestral booster vaccinations compared to those with a full primary vaccine series. In participants with Delta variant infections, baseline NAb titers targeting Delta were negatively correlated with maximum viral RNA copies. Per log10 increase in baseline NAb IC50, maximum viral load was reduced -2.43 (95% confidence interval [CI] -3.76, -1.11) log10 N copies and days of infectious viral shedding were reduced -2.79 [95% CI: -4.99, -0.60] days. By contrast, in those with Omicron infections (BA.1, BA.2, BA.4 or BA.5 lineages) baseline NAb responses against Omicron lineages did not predict viral outcomes. Our results provide robust estimates of the effect of baseline NAbs on the magnitude and duration of nasal viral replication after PVI (albeit with an unclear effect on transmission) and show how immune escape variants efficiently evade these modulating effects.

immunology↗

bioRxiv2023

Long COVID manifests with T cell dysregulation, inflammation, and an uncoordinated adaptive immune response to SARS-CoV-2

Long COVID (LC), a type of post-acute sequelae of SARS-CoV-2 infection (PASC), occurs after at least 10% of SARS-CoV-2 infections, yet its etiology remains poorly understood. Here, we used multiple "omics" assays (CyTOF, RNAseq/scRNAseq, Olink) and serology to deeply characterize both global and SARS-CoV-2-specific immunity from blood of individuals with clear LC and non-LC clinical trajectories, 8 months following infection and prior to receipt of any SARS-CoV-2 vaccine. Our analysis focused on deep phenotyping of T cells, which play important roles in immunity against SARS-CoV-2 yet may also contribute to COVID-19 pathogenesis. Our findings demonstrate that individuals with LC exhibit systemic inflammation and immune dysregulation. This is evidenced by global differences in T cell subset distribution in ways that imply ongoing immune responses, as well as by sex-specific perturbations in cytolytic subsets. Individuals with LC harbored increased frequencies of CD4+ T cells poised to migrate to inflamed tissues, and exhausted SARS-CoV-2-specific CD8+ T cells. They also harbored significantly higher levels of SARS-CoV-2 antibodies, and in contrast to non-LC individuals, exhibited a mis-coordination between their SARS-CoV-2-specific T and B cell responses. RNAseq/scRNAseq and Olink analyses similarly revealed immune dysregulatory mechanisms, along with non-immune associated perturbations, in individuals with LC. Collectively, our data suggest that proper crosstalk between the humoral and cellular arms of adaptive immunity has broken down in LC, and that this, perhaps in the context of persistent virus, leads to the immune dysregulation, inflammation, and clinical symptoms associated with this debilitating condition.

immunology↗

bioRxiv2022

Genome-wide association study of water use patterns of common bean (Phaseolus vulgaris L.) genotypes in response to drying soil

Common bean (Phaseolus vulgaris L.) is the main legume crop for direct human consumption worldwide. Among abiotic factors affecting common bean, drought is the most limiting. This study aimed at characterizing genetic variability and architecture of transpiration, stomatal regulation and whole plant water use within the Mesoamerican germplasm. A critical fraction of transpirable soil water (FTSWc) was estimated as the inflection point at which NTR starts decreasing linearly. Genome-wide association (GWA) analyses for mean NTR and FTSWc were performed. High variation on mean NTR and FTSWc was found among genotypes. Genomic signals controlling the variation of these traits were identified on Pv01 and Pv07 some located in intergenic, intronic and exonic regions. A set of novel candidate genes and putative regulatory elements located in these QTL were identified. Some of the genes have been previously reported to be involved in abiotic tolerance in model species, including some of the five transcription factors (TF) identified. Four candidate genes, one with potential water transportation activity and three TFs were validated. The gene Phvul.001G108800, an aquaporin SIP2-1 related gene, showed water channel activity through oocyte water assays. Mutant Arabidopsis thaliana (Ath) lines for the homologous genes of common bean were evaluated in transpiration experiments. Two of the three evaluated TFs, UPBEAT1 and C2H2-type ZN finger protein, were involved in the control of transpiration responses to drying soil. Our results provide evidence of novel genes to accelerate the drought tolerance improvement in the crop and study the physiological basis of drought response in plants.

plant biology↗

bioRxiv2022

Markers of Fungal Translocation Are Elevated During Post-Acute Sequelae of SARS-CoV-2 Infection and Induce NF-κB Triggered Inflammation.

Long COVID, a type of Post-Acute Sequelae of SARS CoV-2 infection (PASC), has been associated with sustained elevated levels of immune activation and inflammation. However, the pathophysiological mechanisms that drive this inflammation remain unknown. Inflammation during acute Coronavirus Disease 2019 (COVID-19) could be exacerbated by microbial translocation (from the gut and/or lung) to the blood. Whether microbial translocation contributes to inflammation during PASC is unknown. We found higher levels of fungal translocation - measured as {beta}-glucan, a fungal cell wall polysaccharide - in the plasma of individuals experiencing PASC compared to those without PASC or SARS-CoV-2 negative controls. The higher {beta}-glucan correlated with higher levels of markers of inflammation and elevated levels of host metabolites involved in activating N-Methyl-D-aspartate receptors (such as metabolites within the tryptophan catabolism pathway) with established neuro-toxic properties. Mechanistically, {beta}-glucan can directly induce inflammation by binding to myeloid cells (via the Dectin-1 receptor) and activating Syk/NF-{kappa}B signaling. Using an in vitro Dectin-1/NF-{kappa}B reporter model, we found that plasma from individuals experiencing PASC induced higher NF-{kappa}B signaling compared to plasma from SARS-CoV-2 negative controls. This higher NF-{kappa}B signaling was abrogated by the Syk inhibitor Piceatannol. These data suggest a potential targetable mechanism linking fungal translocation and inflammation during PASC.

microbiology↗

bioRxiv2021

Integrated plasma proteomic and single-cell immune signaling network signatures demarcate mild, moderate, and severe COVID-19

The biological determinants of the wide spectrum of COVID-19 clinical manifestations are not fully understood. Here, over 1400 plasma proteins and 2600 single-cell immune features comprising cell phenotype, basal signaling activity, and signaling responses to inflammatory ligands were assessed in peripheral blood from patients with mild, moderate, and severe COVID-19, at the time of diagnosis. Using an integrated computational approach to analyze the combined plasma and single-cell proteomic data, we identified and independently validated a multivariate model classifying COVID-19 severity (multi-class AUCtraining = 0.799, p-value = 4.2e-6; multi-class AUCvalidation = 0.773, p-value = 7.7e-6). Features of this high-dimensional model recapitulated recent COVID-19 related observations of immune perturbations, and revealed novel biological signatures of severity, including the mobilization of elements of the renin-angiotensin system and primary hemostasis, as well as dysregulation of JAK/STAT, MAPK/mTOR, and NF-{kappa}B immune signaling networks. These results provide a set of early determinants of COVID-19 severity that may point to therapeutic targets for the prevention of COVID-19 progression. SummaryFeyaerts et al. demonstrate that an integrated analysis of plasma and single-cell proteomics differentiates COVID-19 severity and reveals severity-specific biological signatures associated with the dysregulation of the JAK/STAT, MAPK/mTOR, and NF-{kappa}B immune signaling networks and the mobilization of the renin-angiotensin and hemostasis systems.

immunology↗

bioRxiv2018

Real-time projections of epidemic transmission and estimation of vaccination impact during an Ebola virus disease outbreak in the Eastern region of the Democratic Republic of Congo

BackgroundAs of October 12, 2018, 211 cases of Ebola virus disease (EVD) were reported in North Kivu Province, Democratic Republic of Congo. Since the beginning of October the outbreak has largely shifted into regions in which active armed conflict is occurring, and in which EVD cases and their contacts are difficult for health workers to reach. We used available data on the current outbreak with case-count time series from prior outbreaks to project the short-term and long-term course of the outbreak.\n\nMethodsFor short and long term projections we modeled Ebola virus transmission using a stochastic branching process that assumes gradually quenching transmission estimated from past EVD outbreaks, with outbreak trajectories conditioned on agreement with the course of the current outbreak, and with multiple levels of vaccination coverage. We used a negative binomial autoregression for short-term projections, a Theil-Sen regression model for final sizes, and a baseline minimum-information projection using Gotts law to construct an ensemble of forecasts to be compared and recorded for future evaluation against final outcomes. From August 20 to October 13, short-term model projections were validated against actual case counts.\n\nResultsDuring validation of short-term projections, from one week to four weeks, we found models consistently scored higher on shorter-term forecasts. Based on case counts as of October 13, the stochastic model projected a median case count of 226 cases by October 27 (95% prediction interval: 205-268) and 245 cases by November 10 (95% prediction interval: 208-315), while the auto-regression model projects median case counts of 240 (95% prediction interval: 215-307) and 259 (95% prediction interval: 216-395) cases for those dates, respectively. Projected median final counts range from 274 to 421. Except for Gotts law, the projected probability of an outbreak comparable to 2013-2016 is exceedingly small. The stochastic model estimates that vaccine coverage in this outbreak is lower than reported in its trial setting in Sierra Leone.\n\nConclusionsBased on our projections we believe that the epidemic had not yet peaked at the time of these estimates, though a trajectory on the scale of the West African outbreak is exceedingly improbable. Validating our models in real time allowed us to generate more accurate short-term forecasts, and this process may provide a useful roadmap for real-time short-term forecasting. We estimate that transmission rates are higher than would be seen under target levels of 62% coverage due to contact tracing and vaccination, and this model estimate may offer a surrogate indicator for the outbreak response challenges.

epidemiology↗

bioRxiv2018

Early projections of Ebola outbreak size and duration with and without vaccine use in Equateur, Democratic Republic of Congo, as of May 21, 2018

BackgroundAs of May 27, 2018, 54 cases of Ebola virus disease (EVD) were reported in Equateur Province, Democratic Republic of Congo. We used reported case counts and time series from prior outbreaks to estimate the current outbreak size and duration with and without vaccine use.\n\nMethodsWe modeled Ebola virus transmission using a stochastic branching process model with a negative binomial distribution, using both estimates of reproduction number R declining from supercritical to subcritical derived from past Ebola outbreaks, as well as a particle filtering method to generate a probabilistic projection of the future course of the outbreak conditioned on its reported trajectory to date; modeled using 0%, 44%, and 62% estimates of vaccination coverage. Additionally, we used the time series for 18 prior Ebola outbreaks from 1976 to 2016 to parameterize a regression model predicting the outbreak size from the number of observed cases from April 4 to May 27.\n\nResultsWith the stochastic transmission model, we projected a median outbreak size of 78 EVD cases (95% credible interval: 52, 125.4), 86 cases (95% credible interval: 53, 174.3), and 91 cases (95% credible interval: 52, 843.5), using 62%, 44%, and 0% estimates of vaccination coverage. With the regression model, we estimated a median size of 85.0 cases (95% prediction interval: 53.5, 216.6).\n\nConclusionsThis outbreak has the potential to be the largest outbreak in DRC since 2007. Vaccines are projected to limit outbreak size and duration but are only part of prevention, control, and care strategies.

epidemiology↗