Biology subjects

Sealfon, S. C.

Publications and source records attributed to Sealfon, S. C..

18 recordsLinked to original sources

bioRxiv2026

Integrative Multi-omics Analysis of the Human Skeletal Muscle Response to Endurance or Resistance Exercise: Findings from the Molecular Transducers of Physical Activity Consortium (MoTrPAC)

The Molecular Transducers of Physical Activity Consortium (MoTrPAC) was established to systematically characterize the molecular basis of the health benefits of exercise. Here, we present the integrative, multi-omics response of human skeletal muscle to acute endurance (EE) and resistance (RE) exercise. Distinct temporal responses were observed, with changes in ATAC-seq, phosphoproteome, and metabolome occurring before changes in the transcriptome and proteome. These distinct temporal multi-omic dynamics were used to identify transcriptional regulatory hubs converging around MEF2A and NFIC regulation of autophagy, angiogenesis and metabolism. Further, early RE-specific phosphoproteome signatures counteracted epigenetic modifications and downregulated transcripts involved in protein turnover. Additional findings include suppression of HIPK2/3 kinase signatures linked to the acute exercise regulation of sarcomeric proteins TTN, NEB, ANKRD2 and LMOD2. Our data demonstrate distinct temporal regulation across the multi-omic landscape of human skeletal muscle, with EE and RE eliciting common and unique molecular signatures.

systems biology↗

bioRxiv2026

Exercise modulation of the alternative splicing landscape in human tissues

The diverse health benefits of exercise are associated with multi-organ molecular responses. Alternative RNA splicing (AS) is an important determinant of transcriptome and proteome diversity. We profiled the temporal effects of acute endurance and resistance exercise on the AS landscape of human skeletal muscle, adipose tissue, and blood, and studied regulatory mechanisms through integrated multi-omic analyses. We identified 5102 distinct differential AS (DAS) events, with the majority modifying protein-coding sequence (89%) and being independent of altered RNA expression (67%). Endurance and resistance exercise induced differing patterns of AS alterations with divergent temporal trajectories. We inferred the DAS-associated RNA-binding and DNA-binding proteins. In skeletal muscle, where DAS events were the most abundant, DAS genes were enriched for muscle structure- and RNA splicing-related processes, and splicing machinery components were regulated at the protein phosphorylation, RNA, and AS levels. These findings implicate AS regulation as a major mediator of the responses to exercise.

systems biology↗

bioRxiv2026

Multi-Omic, Multi-Tissue Responses to Acute Exercise in Sedentary Adults: Findings from the Molecular Transducers of Physical Activity Consortium

Regular physical activity represents one of the greatest mechanisms for maintaining human health, yet the underlying molecular transducers of these benefits remain incompletely understood. Multi-omic assays now provide new opportunities to study the coordinated molecular responses of body tissues to different exercise modalities. The Molecular Transducers of Physical Activity Consortium (MoTrPAC) was established to address this need by creating a molecular map of the response to physical activity. Described here is the first human cohort of MoTrPAC: sedentary adults enrolled prior to study suspension during the COVID-19 pandemic (N=175) randomized to either endurance or resistance exercise, or non-exercise control. From these participants, we detail their global acute molecular response in skeletal muscle, adipose tissue, and blood, integrated at multiple levels: tissue, exercise modality, timepoint, and omic category. These analyses characterize key molecular pathways, identify central regulators, and implicate novel candidate exerkines in mediating multi-organ exercise effects.

systems biology↗

bioRxiv2025

Regulation of murine follicle-stimulating hormone β subunit transcription by newly identified enhancers

Activin-class ligands of the transforming growth factor {beta} family induce follicle-stimulating hormone (FSH) production by pituitary gonadotrope cells in mice via the actions of the transcription factors SMAD3, SMAD4, and FOXL2, which bind to cis-elements in the FSH{beta} subunit (Fshb) promoter. An enhancer region for murine Fshb transcription was identified in vitro. However, deletion of the region using CRISPR-Cas9 did not affect FSH synthesis or secretion in mice. Using single-nucleus ATAC-seq of whole murine pituitaries, we identified three additional open chromatin regions upstream of Fshb exclusively in gonadotropes. These regions, as well as the Fshb gene, were fully or partially closed in gonadotropes of FSH-deficient mice with genetically or pharmacologically inactivated activin type II receptors. The initially characterized enhancer region did not significantly alter basal or activin-stimulated murine Fshb promoter-reporter activity in homologous L{beta}T2 cells. In contrast, the other three open chromatin regions enhanced basal and activin A-stimulated Fshb promoter-reporter activity in L{beta}T2 cells, with the two most distal showing the greatest effects. These two regions were open, exhibited enrichment of the enhancer mark H3K27ac, and were bound by SMAD2/3 and FOXL2 in response to activin A in L{beta}T2 cells. The most distal enhancer exhibited strong FOXL2 and weak SMAD4 binding in gel shift assays. SMAD4, but not FOXL2, directly bound the other distal enhancer. Mutation of defined FOXL2 and SMAD4 cis-elements diminished enhancer activity in reporter assays in L{beta}T2 cells. Collectively, the data indicate that there may be as many as four activin-sensitive enhancers upstream of murine Fshb.

molecular biology↗

bioRxiv2025

Consensus Pituitary Atlas, a scalable resource for annotation, novel marker discovery and analyses in pituitary gland research

Previous single-cell profiling studies of the pituitary gland have yielded minimally reproducible insights largely due to their low statistical power and methodological inconsistencies. To address this problem, we generated a uniformly pre-processed Consensus Pituitary Atlas (CPA) using all existing mouse pituitary single-cell datasets (267 biological replicates, >1.1 million high-quality cells). The CPA revealed novel cell typing and lineage markers, including low-expression transcripts that previous analyses could not detect. The scale of the CPA enabled the development of machine learning models to automate and standardize cell type annotation and doublet identification for future studies. Leveraging the curated metadata, we identified sex-biased and age-dependent gene expression patterns at cell type resolution. To identify drivers of cell fates, first we determined consensus cell communication patterns. Secondly, we used RNA-sequencing and chromatin accessibility data to identify transcription factors associated with cell fates across modalities. The epitome platform acts as an interface with the CPA, allowing streamlined user-friendly analyses. HighlightsO_LIUniform processing of 267 mouse pituitary single-cell datasets (>1.1M cells) C_LIO_LIThe statistical power enabled cell type, sex- and age-specific marker discovery C_LIO_LIMachine learning models facilitate doublet detection and cell typing in new datasets C_LIO_LIepitome platform provides programming-free data access and visualizations C_LI

bioinformatics↗

bioRxiv2024

Innate immune epigenomic landscape following controlled human influenza virus infection

Viral infections can induce changes in innate immunity that persist after virus clearance. Here, we used blood samples from a human influenza H3N2 challenge study to perform comprehensive multi-omic analyses. We detected remodeling of immune programs in innate immune cells after resolution of the infection that was proportional in magnitude to the level of prior viral load. We found changes associated with suppressed inflammation including decreased cytokine and AP-1 gene expression as well as decreased accessibility at AP-1 targets and interleukin-related gene promoter regions. We also found decreased histone deacetylase gene expression, increased MAP kinase gene expression, and increased accessibility at interferon-related gene promoter regions. Genes involved in inflammation and epigenetic-remodeling showed modulation of gene-chromatin site regulatory circuit activity. These results reveal a coordinated rewiring of the epigenetic landscape in innate immune cells induced by mild influenza virus infection.

immunology↗

bioRxiv2024

Comprehensive Guide of Epigenetics and Transcriptomics Data Quality Control

Host response to environmental exposures such as pathogens and chemicals can cause modifications to the epigenome and transcriptome. Analysis of these modifications can reveal signatures with regards to the agent and timing of exposure. Exhaustive interrogation of the cascade of the epigenome and transcriptome requires analysis of disparate datasets from multiple assay types, often at single cell resolution, from the same biospecimen. Improved signature discovery has been enabled by advancements in assaying techniques to detect RNA expression, DNA base modifications, histone modifications, and chromatin accessibility. However, there remains a paucity of rigorous quality control standards of those datasets that reflect quality assurance of the underlying assay. This guide outlines a comprehensive suite of metrics that can be used to ensure quality from 11 different epigenetics and transcriptomics assays. Recommendations on mitigation approaches to address failed metrics and poor quality data are provided. The workflow consists of assessing dataset quality and reiterating benchwork protocols for improved results to generate accurate exposure signatures.

bioinformatics↗

bioRxiv2023

Automated single-cell omics end-to-end framework with data-driven batch inference

To facilitate single-cell multi-omics analysis and improve reproducibility, we present SPEEDI (Single-cell Pipeline for End to End Data Integration), a fully automated end-to-end framework for batch inference, data integration, and cell type labeling. SPEEDI introduces data-driven batch inference and transforms the often heterogeneous data matrices obtained from different samples into a uniformly annotated and integrated dataset. Without requiring user input, it automatically selects parameters and executes pre-processing, sample integration, and cell type mapping. It can also perform downstream analyses of differential signals between treatment conditions and gene functional modules. SPEEDIs data-driven batch inference method works with widely used integration and cell-typing tools. By developing data-driven batch inference, providing full end-to-end automation, and eliminating parameter selection, SPEEDI improves reproducibility and lowers the barrier to obtaining biological insight from these valuable single-cell datasets. The SPEEDI interactive web application can be accessed at https://speedi.princeton.edu/.

bioinformatics↗

bioRxiv2023

Integrated single-cell multiome analysis reveals muscle fiber-type gene regulatory circuitry modulated by endurance exercise

Endurance exercise is an important health modifier. We studied cell-type specific adaptations of human skeletal muscle to acute endurance exercise using single-nucleus (sn) multiome sequencing in human vastus lateralis samples collected before and 3.5 hours after 40 min exercise at 70% VO2max in four subjects, as well as in matched time of day samples from two supine resting circadian controls. High quality same-cell RNA-seq and ATAC-seq data were obtained from 37,154 nuclei comprising 14 cell types. Among muscle fiber types, both shared and fiber-type specific regulatory programs were identified. Single-cell circuit analysis identified distinct adaptations in fast, slow and intermediate fibers as well as LUM-expressing FAP cells, involving a total of 328 transcription factors (TFs) acting at altered accessibility sites regulating 2,025 genes. These data and circuit mapping provide single-cell insight into the processes underlying tissue and metabolic remodeling responses to exercise.

genomics↗

bioRxiv2023

Human Immune Cell Epigenomic Signatures in Response to Infectious Diseases and Chemical Exposures

The epigenomic landscape of human immune cells is dynamically shaped by both genetic factors and environmental exposures. However, the relative contributions of these elements are still not fully understood. In this study, we employed single-nucleus methylation sequencing and ATAC-seq to systematically explore how pathogen and chemical exposures, along with genetic variation, influence the immune cell epigenome. We identified distinct exposure-associated differentially methylated regions (eDMRs) corresponding to each exposure, revealing how environmental factors remodel the methylome, alter immune cell states, and affect transcription factor binding. Furthermore, we observed a significant correlation between changes in DNA methylation and chromatin accessibility, underscoring the coordinated response of the epigenome. We also uncovered genotype-associated DMRs (gDMRs), demonstrating that while eDMRs are enriched in regulatory regions, gDMRs are preferentially located in gene body marks, suggesting that exposures and genetic factors exert differential regulatory control. Notably, disease-associated SNPs were frequently colocalized with meQTLs, providing new cell-type-specific insights into the genetic basis of disease. Our findings underscore the intricate interplay between genetic and environmental factors in sculpting the immune cell epigenome, offering a deeper understanding of how immune cell function is regulated in health and disease.

genomics↗

bioRxiv2023

Multiomic identification of key transcriptional regulatory programs during endurance exercise training

Transcription factors (TFs) play a key role in regulating gene expression. We conducted an integrated analysis of chromatin accessibility, DNA methylation, mRNA expression, protein abundance and phosphorylation across eight tissues in fifty rats of equally represented sexes following endurance exercise training (EET) to identify coordinated epigenomic and transcriptional changes and determine key TFs involved. We uncovered tissue-specific EET associated changes and TF motif enrichment across differentially expressed genes (DEGs), accessible regions (DARs), and methylated regions (DMRs). We discovered distinct routes of EET-induced regulation through either epigenomic alterations providing better access for TFs to affect target genes, or via changes in TF expression or activity enabling target gene responses. We identified TF motifs enriched among correlated epigenomic and transcriptomic alterations, DEGs correlated with exercise-related phenotypic and cell type composition changes, and EET-induced activity changes of TFs whose target genes are enriched for DEGs. This analysis elucidates the unique gene regulatory mechanisms mediating diverse transcriptional responses to EET across tissues.

genomics↗

bioRxiv2021

CHARM: COVID-19 Health Action Response for Marines - association of antigen-specific interferon-gamma and IL2 responses with asymptomatic and symptomatic infections after a positive qPCR SARS-CoV-2 test

SARS-CoV-2 T cell responses are associated with COVID-19 recovery, and Class I- and Class II-restricted epitopes have been identified in the spike (S), nucleocapsid (N) and membrane (M) proteins and others. This prospective COVID-19 Health Action Response for Marines (CHARM) study enabled assessment of T cell responses in symptomatic and asymptomatic SARS-CoV-2 infected participants. At enrollment all participants were negative by qPCR; follow-up occurred biweekly and then bimonthly for the next 6 weeks. Study participants who tested positive by qPCR SARS-CoV-2 test were asked to enroll in an immune response sub-study. FluoroSpot interferon-gamma (IFN-{gamma}) and IL2 responses following qPCR-confirmed infection at enrollment (day 0), day 7 and 14 and more than 28 days later were measured using pools of 17mer peptides covering S, N, and M proteins, or CD4+CD8 peptide pools containing predicted epitopes from multiple SARS-CoV-2 antigens. Among 124 asymptomatic and 105 symptomatic participants, SARS-CoV-2 infection generated IFN-{gamma} responses to the S, N and M proteins that persisted longer in asymptomatic cases. IFN-{gamma} responses were significantly (p=0.001) more frequent to the N pool (51.4%) than the M pool (18.9%) among asymptomatic subjects; however, the difference was not statistically significant (p=0.06) for symptomatic subjects (N pool: 44.4%; M pool: 25.9%). In asymptomatic participants IFN-{gamma} responders to the CD4+CD8 pool responded more frequently to the S pool (55.6%) and N pool (57.1%), than the M pool (7.1%), but symptomatic participants, IFN-{gamma} responses were more frequent to the S pool (75.0%) than N pool (33.3%) and M pool (33.3%). The frequencies of IFN-{gamma} responses to the S and N+M pools peaked 7 days after the positive qPCR test among asymptomatic (S pool: 22.2%; N+M pool: 28.7%) and symptomatic (S pool: 15.3%; N+M pool 21.9%) participants and dropped by >28 days. Magnitudes of post-infection IFN-{gamma} and IL2 responses to the N+M pool were significantly correlated with IFN-{gamma} and IL2 responses to the N and M pools. These data further support the central role of Th1-biased cell mediated immunity IFN-{gamma} and IL2 responses, particularly to the N protein, in controlling COVID-19 symptoms, and justify T cell-based COVID-19 vaccines that include the N and S proteins.

immunology↗

bioRxiv2021

Single nucleus pituitary transcriptomic and epigenetic landscape reveals human stem cell heterogeneity with diverse regulatory mechanisms

Despite their importance in tissue homeostasis and renewal, human pituitary stem cells (PSCs) are incompletely characterized. We describe a human single nucleus (sn) RNAseq and ATACseq resource from pediatric, adult, and aged pituitaries (snpituitaryatlas.princeton.edu) and characterize cell type-specific gene expression and chromatin accessibility programs for all major pituitary cell lineages. We identify uncommitted PSCs, committing progenitor cells, and sex differences. Pseudotime trajectory analysis indicates that early life PSCs are distinct from the other age groups. Linear modeling of same-cell multiome data identifies regulatory domain accessibility sites and transcription factors (TFs) that are significantly associated with gene expression in PSCs compared to other cell types and within PSCs. Modeling the heterogeneous expression of two markers for committing cell lineages among PSCs shows significant correlation with regulatory domain accessibility for GATA3, but with TF expression for POMC. These findings characterize human stem cell lineages and reveal diverse mechanisms regulating key PSC genes.

cell biology↗

bioRxiv2021

Comparing host module activation patterns and temporal dynamics in infection by influenza H1N1 viruses

Influenza is a serious global health threat that shows varying pathogenicity among different virus strains. Understanding similarities and differences among activated functional pathways in the host responses can help elucidate therapeutic targets responsible for pathogenesis. To compare the types and timing of functional modules activated in host cells by four influenza viruses of varying pathogenicity, we developed a new DYNAmic MOdule (DYNAMO) method that addresses the need to compare functional module utilization over time. This integrative approach overlays whole genome time series expression data onto an immune-specific functional network, and extracts conserved modules exhibiting either different temporal patterns or overall transcriptional activity. We identified a common core response to influenza virus infection that is temporally shifted for different viruses. We also identified differentially regulated functional modules that reveal unique elements of responses to different virus strains. Our work highlights the usefulness of combining time series gene expression data with a functional interaction map to capture temporal dynamics of the same cellular pathways under different conditions. Our results help elucidate conservation of the immune response both globally and at a granular level, and provide mechanistic insight into the differences in the host response to infection by influenza strains of varying pathogenicity.

bioinformatics↗

bioRxiv2021

mRNA-1273 efficacy in a severe COVID-19 model: attenuated activation of pulmonary immune cells after challenge

The mRNA-1273 vaccine was recently determined to be effective against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) from interim Phase 3 results. Human studies, however, cannot provide the controlled response to infection and complex immunological insight that are only possible with preclinical studies. Hamsters are the only model that reliably exhibit more severe SARS-CoV-2 disease similar to hospitalized patients, making them pertinent for vaccine evaluation. We demonstrate that prime or prime-boost administration of mRNA-1273 in hamsters elicited robust neutralizing antibodies, ameliorated weight loss, suppressed SARS-CoV-2 replication in the airways, and better protected against disease at the highest prime-boost dose. Unlike in mice and non-human primates, mRNA-1273- mediated immunity was non-sterilizing and coincided with an anamnestic response. Single-cell RNA sequencing of lung tissue permitted high resolution analysis which is not possible in vaccinated humans. mRNA-1273 prevented inflammatory cell infiltration and the reduction of lymphocyte proportions, but enabled antiviral responses conducive to lung homeostasis. Surprisingly, infection triggered transcriptome programs in some types of immune cells from vaccinated hamsters that were shared, albeit attenuated, with mock-vaccinated hamsters. Our results support the use of mRNA-1273 in a two-dose schedule and provides insight into the potential responses within the lungs of vaccinated humans who are exposed to SARS-CoV-2.

immunology↗

bioRxiv2020

Single nucleus multi-omics regulatory atlas of the murine pituitary

The pituitary regulates growth, reproduction and other endocrine systems. To investigate transcriptional network epigenetic mechanisms, we generated paired single nucleus (sn) transcriptome and chromatin accessibility profiles in single mouse pituitaries and genome-wide sn methylation datasets. Our analysis provided insight into cell type epigenetics, regulatory circuit and gene control mechanisms. Latent variable pathway analysis detected corresponding transcriptome and chromatin accessibility programs showing both inter-sexual and inter-individual variation. Multi-omics analysis of gene regulatory networks identified cell type-specific regulons whose composition and function were shaped by the promoter accessibility state of target genes. Co-accessibility analysis comprehensively identified putative cis-regulatory regions, including a domain 17kb upstream of Fshb that overlapped the fertility-linked rs11031006 human polymorphism. In vitro CRISPR-deletion at this locus increased Fshb levels, supporting this domains inferred regulatory role. The sn pituitary multi-omics atlas (snpituitaryatlas.princeton.edu) is a public resource for elucidating cell type-specific gene regulatory mechanisms and principles of transcription circuit control.

cell biology↗

bioRxiv2019

Deciphering the combinatorial interaction landscape

From cellular activation to drug combinations, the control of biological systems involves multiple stimuli that can elicit complex nonlinear interactions. To elucidate the functions and logic of stimulus interactions, we developed SAIL (Synergistic/Antagonistic Interaction Learner). SAIL uses a machine learning classifier trained to categorize interactions across a complete taxonomy of possible combinatorial effects. The strategy resolves the most informative interactions, and helps infer their functions and regulatory mechanisms. SAIL-predicted interaction mechanisms controlling key immune functions were experimentally validated. SAIL can integrate results from multiple datasets to derive general properties of how cells respond to multiple stimuli. Using public immunological datasets, we assembled a fine-grained landscape of [~]30000 interactions. Analysis of the landscape shows the context-dependent functions of individual modulators, and reveals a probabilistic algebra that links the separate and combined stimulus effects. SAIL is available through a user friendly interface to resolve the effect of stimulus and drug combinations.

bioinformatics↗

bioRxiv2017

High resolution annotation of Zebrafish transcriptome using long-read sequencing

With the emergence of zebrafish as an important model organism, a concerted effort has been made to study its transcriptome. This effort is limited, however, by gaps in zebrafish annotation, which are especially pronounced concerning transcripts dynamically expressed during zygotic genome activation (ZGA). To date, short read sequencing has been the principal technology for zebrafish transcriptome annotation. In part because these sequence reads are too short for assembly methods to resolve the full complexity of the transcriptome, the current annotation is rudimentary. By providing direct observation of full-length transcripts, recently refined long-read sequencing platforms can dramatically improve annotation coverage and accuracy. Here, we leveraged the SMRT platform to study transcriptome of zebrafish embryos before and after ZGA. Our analysis revealed additional novelty and complexity in the zebrafish transcriptome, identifying 2748 high confidence novel transcripts that originated from previously unannotated loci and 1835 high confidence new isoforms in previously annotated genes. We validated these findings using a suite of computational approaches including structural prediction, sequence homology and functional conservation analyses, as well as by confirmatory transcript quantification with short-read sequencing data. Our analyses provided insight into new homologs and paralogs of functionally important proteins and non-coding RNAs, isoform switching occurrences and different classes of novel splicing events. Several novel isoforms representing distinct splicing events were validated through PCR experiments, including the discovery and validation of a novel 8 kb transcript spanning multiple miR-430 elements, an important driver of early development. Our study provides a significantly improved zebrafish transcriptome annotation resource.

bioinformatics↗