Biology subjects

Metzner, E.

Publications and source records attributed to Metzner, E..

6 recordsLinked to original sources

bioRxiv2026

Host control and regulation of human anellovirus persistence

Anelloviruses are the most abundant and diverse eukaryotic viruses known to infect humans and can persist throughout our lifetimes. Despite their ubiquity, the host factors governing their physiologic distribution and abundance remain poorly understood. Here, we construct a viral pangenome of 2,023 strains to quantify anellovirus DNA in >1.1 million participants spanning three genetic biobanks. Genome-wide association studies identify 121 loci linked to viral persistence, predominantly via immune regulation by NF-kB signaling. Further, we associate variable anellovirus detection with conditions characterized by immune dysfunction, including lymphoid malignancies. By screening 3.2 petabases of human single-cell sequencing data, we identify myeloid progenitors in the bone marrow as a prominent site of anellovirus transcription in vivo. Finally, Perturb-seq of anellovirus proteins reveals that anellovirus ORF2, particularly from Alphatorquevirus, attenuates TNF-a-induced NF-kB signaling, connecting host genetic variation, cellular context, and viral immunomodulation to characterize the persistence of the eukaryotic human virome's most abundant component.

genetics↗

bioRxiv2026

Engineered regulatory states resolve context-dependent genetics in macular degeneration

The effects of many genes and disease-associated variants remain hidden in standard cellular models, limiting functional interpretation. Here we engineer regulatory states via CRISPR activation of transcription factors (TFs) in human RPE-1 cells, a model for age-related macular degeneration (AMD). Multiome Perturb-seq profiling of single-TF perturbations identified regulators that selectively opened chromatin at AMD GWAS variants inaccessible in resting RPE-1. Priming of partner motifs in chromatin made accessible by single-TF perturbations predicted TF pairs generating emergent transcriptional states in combinatorial Perturb-seq, providing a design principle for selecting informative interactions. Distinct TF pairs also showed variable convergence between polygenic AMD signals and Mendelian retinal disease genes, supporting an omnigenic model shaped by regulatory states. Finally, Mosaic, a chromatin-informed model of TF interaction phenotypes, nominated out-of-sample regulators, including a higher-order combination with experimentally validated emergent effects on AMD-associated programs. Engineered regulatory states thus bring hidden disease biology within experimental reach.

systems biology↗

bioRxiv2024

Comprehensive transcription factor perturbations recapitulate fibroblast transcriptional states

Cell atlas projects have nominated recurrent transcriptional states as drivers of biological processes and disease, but their origins, regulation, and properties remain unclear. To enable complementary functional studies, we developed a scalable approach for recapitulating cell states in vitro using CRISPR activation (CRISPRa) Perturb-seq. Aided by a novel multiplexing method, we activated 1,836 transcription factors in two cell types. Measuring 21,958 perturbations showed that CRISPRa activated targets within physiological ranges, that epigenetic features predicted activatable genes, and that the protospacer seed region drove an off-target effect. Perturbations recapitulated in vivo fibroblast states, including universal and inflammatory states, and identified KLF4 and KLF5 as key regulators of the universal state. Inducing the universal state suppressed disease-associated states, highlighting its therapeutic potential. Our findings cement CRISPRa as a tool for perturbing differentiated cells and indicate that in vivo states can be elicited via perturbation, enabling studies of clinically relevant states ex vivo.

systems biology↗

bioRxiv2024

Multiome Perturb-seq unlocks scalable discovery of integrated perturbation effects on the transcriptome and epigenome

Single-cell CRISPR screens link genetic perturbations to transcriptional states, but high-throughput methods connecting these induced changes to their regulatory foundations are limited. Here we introduce Multiome Perturb-seq, extending single-cell CRISPR screens to simultaneously measure perturbation-induced changes in gene expression and chromatin accessibility. We apply Multiome Perturb-seq in a CRISPRi screen of 13 chromatin remodelers in human RPE-1 cells, achieving efficient assignment of sgRNA identities to single nuclei via an improved method for capturing barcode transcripts from nuclear RNA. We organize expression and accessibility measurements into coherent programs describing the integrated effects of perturbations on cell state, finding that ARID1A and SUZ12 knockdowns induce programs enriched for developmental features. Pseudotime analysis of perturbations connects accessibility changes to changes in gene expression, highlighting the value of multimodal profiling. Overall, our method provides a scalable and simply implemented system to dissect the regulatory logic underpinning cell state.

systems biology↗

bioRxiv2022

A global view of aging and Alzheimer's pathogenesis-associated cell population dynamics and molecular signatures in the human and mouse brains

Conventional single-cell genomics approaches are limited by throughput and thus may have failed to capture aspects of the molecular signatures and dynamics of rare cell types associated with aging and diseases. Here, we developed EasySci, an extensively improved single-cell combinatorial indexing strategy, for investigating the age-dependent dynamics of transcription and chromatin accessibility across diverse brain cell types. We profiled [~]1.5 million single-cell transcriptomes and [~]400,000 single-cell chromatin accessibility profiles across mouse brains spanning different ages, genotypes, and both sexes. With a novel computational framework designed for characterizing cellular subtypes based on the expression of both genes and exons, we identified > 300 cell subtypes and deciphered their underlying molecular programs and spatial locations especially for rare cell types (e.g., pinealocytes, tanycytes). Leveraging these data, we generated a global readout of age-dependent changes at cell subtype resolution, providing insights into cell types that expand (e.g., rare astrocytes and vascular leptomeningeal cells in the olfactory bulb, reactive microglia, and oligodendrocytes) or are depleted (e.g., neuronal progenitors, neuroblasts, committed oligodendrocyte precursors) as age progresses. Furthermore, we explored cell-type-specific responses to genetic perturbations associated with Alzheimers disease (AD) and identified rare cell types depleted (e.g., mt-Cytb+, mt-Rnr2+ choroid plexus epithelial cells) or enriched (e.g., Col25a1+, Ndrg1+ interbrain and midbrain neurons) in both AD models. Key findings are consistent between males and females, validated across the transcriptome, chromatin accessibility, and spatial analyses. Finally, we profiled a total of 118,240 single-nuclei transcriptomes from twenty-four post-mortem human brain samples derived from control and AD patients, revealing highly cell-type-specific and region-specific gene expression changes associated with AD pathogenesis. Critical AD-associated gene signatures were validated in both human and mice. In summary, these data comprise a rich resource for exploring cell-type-specific dynamics and the underlying molecular mechanisms in normal and pathological mammalian aging.

genomics↗

bioRxiv2020

Advanced eMAGE for highly efficient combinatorial editing of a stable genome

Eukaryotic multiplex genome engineering (eMAGE) offers a powerful tool to generate precise combinatorial genome modifications in Saccharomyces cerevisiae. We optimize the design of synthetic oligonucleotides and enrichment of edited populations to increase editing frequencies up to 90%, reduce workflow time by 40%, and engineer a tunable mismatch repair system to lower the rate of spontaneous mutations [~]17-fold. These advances transiently evade genome maintenance to introduce multiple edits at high efficiencies in a stable genetic background, expanding utility of eMAGE in eukaryotic cells.

synthetic biology↗