Dylan Duchen

Pangenome variation graphs are a powerful tool for representing genetic diversity within and across populations. For comparative and evolutionary genomic analyses leveraging these graph-based structures, it is important that graph topology reflects the underlying phylogenetic and genetic similarities of the genomes embedded within the graph. However, in metagenomic settings these approaches often produce highly fragmented multi-component graphs, hindering comparisons of genomes embedded across different components. This challenge is particularly pronounced for hypervariable viral families like Anelloviridae , whose short circular genomes frustrate existing variation graph construction methods. We present PANIMaSTA (Progressive Average Nucleotide Identity and Maximum Spanning Tree-Based Assembly), a workflow to construct minimally fragmented metagenomic pangenome sequence variation graphs through progressive assembly. The order in which the genomes are incorporated into the graph is informed by a maximum spanning tree (MST) inferred from an all-to-all genome similarity matrix comprised of pairwise Anelloviridae average nucleotide identities (ANI). Applied to over 5,200 diverse Anelloviridae genomes, we construct a sequence variation graph whose graph topology reflects the global genome similarities observed across the ANI matrix. PANIMaSTA constructs minimally fragmented metagenomic pangenome sequence variation graphs that are not achievable with existing methods suitable for similarity-aware sequence-to-graph mapping and downstream genetic analyses across highly diverse genomes.

Host genetic variation influences heterogeneity in infectious disease severity. Genome-wide association studies (GWAS) have identified 69 lead single nucleotide polymorphisms (SNPs) associated with critical COVID-19, but most lack known regulatory mechanisms. To date, the genetic cis-regulatory effects of critical COVID-19 GWAS lead SNPs have not been systematically characterized across acute illness and convalescent phases in a COVID-19 specific cohort. Here, performing severity-stratified, longitudinal cis-expression quantitative trait loci (cis-eQTL) mapping and colocalization with critical COVID-19 GWAS signals, we find that host cis-regulatory effects vary across clinical severity and disease phase. We analyzed peripheral blood mononuclear cells from 1,031 patients in the Immunophenotyping Assessment in a COVID-19 Cohort (IMPACC), a prospective multicenter study of adults hospitalized with COVID-19, profiled across 10 timepoints spanning acute illness and convalescence. We identified 23 GWAS lead SNPs that colocalized with cis-eQTLs at 26 candidate causal genes, with 16 detectable only when severity stratification and longitudinal sampling were incorporated. A colocalized, protective allele (chr19:4,717,660) at the TMIGD2 locus upregulated TMIGD2 expression exclusively during the acute phase in the prolonged-critical/fatal cohort, with no detectable effect in the rapid-recovery cohort. Our results show that host genetic effects on critical COVID-19 can be context-dependent, with cis-regulatory effects varying across clinical severity and disease phase. Severity-stratified, longitudinal cis-eQTL designs have greater sensitivity to identify candidate causal genes for critical COVID-19 GWAS associations than single-timepoint cross-sectional studies.

Oxford Nanopore technology enables cost-effective, portable, long-read analyses of pathogen genomes. Accurate detection and interpretation of small circular viral genomes, including Anelloviridae, remain challenging due to limited base-level error quantification in rolling-circle amplification (RCA)-derived datasets. Here, we characterized read-level sequencing error profiles using M13mp18, a 7.2 kb circular phage genome, subjected to 1X and 3X shearing during library preparation. M13mp18 DNA was serially diluted into pooled anellovirus-positive plasma DNA extracts. Using custom error-analysis pipelines, we quantified mismatch, insertion, and deletion rates and evaluated consensus reconstruction accuracy across simulated sequencing depths. Since metagenomic viromes contain mixtures of related genomes and uneven coverage across taxa, depth-normalized subsampling was used to assess the precision of read-level error estimates under heterogeneous coverage. Across four benchmarked datasets, per-base error rates ranged from 0.018 to 0.022 errors per aligned base. Complete M13mp18 reference reconstruction was achieved at input levels ≥ 4.6 log₁₀ copies, and consensus sequences reached 100% identity at depths ≥ 15X when sufficient reads were available. Below 4.6 log₁₀ input copies, recovery was inconsistent. These findings provide a controlled empirical characterization of read-level error behavior in RCA-derived nanopore sequencing and support the interpretation of circular DNA virome data generated in complex metagenomic backgrounds.

MHC class I polypeptide-related sequence B (MICB) is a ligand for NKG2D. We have shown NK cells are central to lung transplant acute lung injury (ALI) via NKG2D activation, and increased MICB in bronchoalveolar lavage predicts ALI severity. Separately, we found a MICB polymorphism ( MICB ^G406A ) is associated with decreased ALI risk. We hypothesized this polymorphism would protect against severe SARS-CoV-2 respiratory disease. We analyzed 1,036 patients hospitalized with SARS-CoV-2 infection from IMPACC. Associations between MICB ^G406A and outcomes were determined by linear regression or Cox proportional hazards models. We also measured immune profiles of peripheral blood and the upper and lower airway. We identified 560 major allele homozygous patients, and 426 and 50 with 1 or 2 copies of the variant allele, respectively. MICB ^G406A conferred reduced odds of severe COVID-19. MICB ^G406A homozygous participants demonstrated 34% reduced cumulative odds for mechanical ventilation or death and 43% reduced risk for mortality. Patients with MICB ^G406A variant alleles had reduced soluble inflammatory mediators and differential regulation of multiple immune pathways. These findings demonstrate a potentially novel association between increasing MICB ^G406A variant allele copies and reduced COVID-19 severity, independent of SARS-CoV-2 viral burden and humoral immunity, suggesting the NKG2D-ligand pathway as an intervention target.

Humans develop immunoglobulin G (IgG) antibodies to the foods they consume. In the context of food allergy, allergen-specific IgG antibodies can sequentially class-switch to pathogenic IgE. However, the mechanism underlying the antigenicity of food proteins remains uncharacterized. Here, we identified convergent antibodies arising from different antibody gene rearrangements that bind to the immunodominant peanut allergen Ara h 2 and characterized allelic and junctional constraints on germline antibody specificity. Structurally, we found similar epitope-paratope interactions across multiple gene rearrangements. We demonstrate that these germline-encoded epitope-specific convergent antibodies to peanut occur commonly in the population because of the worldwide prevalence of the relevant gene rearrangements, allelic independence, and junctional malleability. As a result, serum IgG to this public epitope is prevalent among diverse cohorts of nonallergic peanut-consuming infants and peanut-allergic children and adults. This work demonstrates that IgG recognition of dietary antigens can be intrinsically programmed by the germline antibody repertoire.

CD16A is an activating Fc receptor on NK cells that mediates antibody-dependent cellular cytotoxicity (ADCC), a key mechanism in antiviral immunity. However, the role of NK cell–mediated ADCC in SARS-CoV-2 infection remains unclear, particularly whether it limits viral spread and disease severity or contributes to the immunopathogenesis of COVID-19. We hypothesized that the high-affinity CD16A ^V176 polymorphism influences these outcomes. Using an in vitro reporter system, we demonstrated that CD16A ^V176 is a more potent and sensitive activator than the common CD16A ^F176 allele. To assess its clinical relevance, we analyzed 1,027 patients hospitalized with COVID-19 from the Immunophenotyping Assessment in a COVID-19 cohort (IMPACC), a comprehensive longitudinal dataset with extensive transcriptomic, proteomic, and clinical data. The high-affinity CD16A ^V176 allele was associated with a significantly reduced risk of ICU admission, mechanical ventilation, and severe disease trajectories. Lower anti–SARS-CoV-2 IgG titers were correlated to CD16A ^V176 ; however, there was no difference in viral load across CD16A genotypes. Proteomic analysis revealed that participants homozygous for CD16A ^V176 had lower levels of inflammatory mediators. These findings suggest that CD16A ^V176 enhances early NK cell–mediated immune responses, limiting severe respiratory complications in COVID-19. This study identifies a protective genetic factor against severe COVID-19, informing future host-directed therapeutic strategies.

Routinely used metagenomic next-generation sequencing (mNGS) techniques often fail to detect low-level viremia (4 copies/mL) and appear biased towards viruses with linear genomes. These limitations hinder the capacity to comprehensively characterize viral infections, such as those attributed to the Anelloviridae family. These near ubiquitous non-pathogenic components of the human virome have circular single-stranded DNA genomes that vary in size from 2.0 to 3.9 kb and exhibit high genetic diversity. Hence, species identification using short reads can be challenging. Here, we introduce a rolling circle amplification (RCA)-based metagenomic sequencing protocol tailored for circular single-stranded DNA genomes, utilizing the long-read Oxford Nanopore platform. The approach was assessed by sequencing anelloviruses in plasma drawn from people who inject drugs (PWID) in two geographically distinct cohorts. We detail the methodological adjustments implemented to overcome difficulties inherent in sequencing circular genomes and describe a computational pipeline focused on anellovirus detection. We assessed our protocol across various sample dilutions and successfully differentiated anellovirus sequences in conditions simulating mixed infections. This method provides a robust framework for the comprehensive characterization of circular viruses within the human virome using the Oxford Nanopore.

Nearly 300 million individuals live with chronic hepatitis B virus (HBV) infection (CHB), for which no curative therapy is available. As viral diversity is associated with pathogenesis and immunological control of infection, improved methods to characterize this diversity could aid drug development efforts. Conventionally, viral sequencing data are mapped/aligned to a reference genome, and only the aligned sequences are retained for analysis. Thus, reference selection is critical, yet selecting the most representative reference a priori remains difficult. We investigate an alternative pangenome approach which can combine multiple reference sequences into a graph which can be used during alignment. Using simulated short-read sequencing data generated from publicly available HBV genomes and real sequencing data from an individual living with CHB, we demonstrate alignment to a phylogenetically representative ‘genome graph’ can improve alignment, avoid issues of reference ambiguity, and facilitate the construction of sample-specific consensus sequences more genetically similar to the individual’s infection. Graph-based methods can, therefore, improve efforts to characterize the genetics of viral pathogens, including HBV, and have broader implications in host-pathogen research.

Astroviral infections commonly cause acute nonbacterial gastroenteritis in children globally. However, these infections often go undiagnosed outside of research settings. There is no treatment available for astrovirus, and Astroviridae strain diversity presents a challenge to potential vaccine development. To address our hypothesis that host genetic risk factors are associated with astrovirus disease susceptibility, we performed a genome-wide association study (GWAS) of astrovirus infection in the first year of life from children enrolled in two Bangladeshi birth cohorts. We identified a novel region on chromosome 1 near the loricrin gene ( LOR ) associated with astrovirus diarrheal infection (rs75437404, meta-analysis p-value=8.82×10 ⁻⁹ , A allele OR=2.71) and on chromosome 10 near the prolactin releasing hormone receptor gene ( PRLHR ) (rs75935441, meta-analysis p-value=1.33×10 ⁻⁸ , C allele OR=4.17). The prolactin-releasing peptide has been shown to influence feeding patterns and energy balance in mice. Additionally, several SNPs in the chromosome 1 locus have previously been associated with expression of innate immune system genes PGLYRP4, S100A9 , and S100A12 . This study identified two significant host genetic regions that may influence astrovirus diarrhea susceptibility and should be considered in further studies.