Biology subjects

Snyder, M. P.

Publications and source records attributed to Snyder, M. P..

5 recordsLinked to original sources

bioRxiv2018

Old fibroblasts secrete inflammatory cytokines that drive variability in reprogramming efficiency and may affect wound healing between old individuals

Age-associated chronic inflammation (inflammaging) has emerged as a central hallmark of aging1-3, but its impact on specific cells is still largely unknown. Fibroblasts are present in all tissues and contribute to wound healing4-6. They are also the cell type that is mostly used for induced pluripotent stem cell (iPSC) reprogramming7 - a process that has implications for regenerative medicine and rejuvenation strategies8-17. Here we show that primary fibroblasts from old mice secrete inflammatory cytokines and that there is an increased variability in reprogramming efficiency between fibroblast cultures from old individuals. Individual-to-individual variability is emerging as a key feature of old age18-21, which could reflect distinct aging trajectories, but the underlying causes remain unknown. To identify drivers of this variability, we perform a multi-omic assessment of young and old fibroblast cultures with different reprogramming efficiency. This approach, coupled with single cell transcriptomics, reveals that old fibroblast cultures are heterogeneous and show a greater proportion of activated fibroblasts that secrete inflammatory cytokines, which correlates with reprogramming efficiency. We experimentally validate that activated fibroblasts express inflammatory cytokines in vivo and that their presence is linked to enhanced reprogramming efficiency in culture. Conditioned-media swapping experiments show that extrinsic factors secreted by activated fibroblasts are more critical than intrinsic factors for the individual-to-individual variability in reprogramming efficiency, and we identify TNF as a key inflammatory cytokine underlying this variability. Interestingly, old mice also exhibit variability in wound healing efficiency in vivo and old wounds show an increased subpopulation of activated fibroblasts with a unique TNF signature. Our study shows that a switch in fibroblast composition, and the ratio of inflammatory cytokines they secrete, drives variability in reprogramming in vitro and may influence wound healing in vivo. These findings could help identify personalized strategies to improve iPSC generation and wound healing in older individuals.

cell biology↗

bioRxiv2017

NF90/ILF3 is a transcription factor that promotes proliferation over differentiation by hierarchical regulation in K562 erythroleukemia cells

NF90 and splice variant NF110 are DNA- and RNA-binding proteins encoded by the Interleukin enhancer-binding factor 3 (ILF3) gene that regulate RNA splicing, stabilization and export. The role of NF90 in regulating transcription as a DNA-binding protein has not been comprehensively characterized. Here, ENCODE ChIP-seq identified 9,081 genomic sites specifically bound by NF90/110 in K562 cells. One third of binding sites occurred at promoters of annotated genes. NF90/110 binding colocalized with chromatin marks associated with active promoters and strong enhancers. Comparison with 150 ENCODE ChIP-seq experiments revealed that NF90 clustered with transcription factors exhibiting preference for promoters over enhancers (POLR2A, MYC, YY1). Differential gene expression analysis following shRNA knockdown of NF90 in K562 cells revealed that NF90 directly activates transcription factors that drive growth and proliferation (EGR1, MYC), while attenuating differentiation along erythroid lineage (KLF1). NF90/110 binds chromatin to hierarchically regulate transcription factors to promote proliferation and suppress differentiation.

genetics↗

bioRxiv2017

High Frequency Actionable Pathogenic Exome Mutations in an Average-Risk Cohort

Whole exome sequencing (WES) is increasingly utilized in both clinical and non-clinical settings, but little is known about the utility of WES in healthy individuals. In order to determine the frequency of both medically actionable and non-actionable but medically relevant exome findings in the general population we assessed the exomes of 70 participants who have been extensively characterized over the past several years as part of a longitudinal integrated multi-omics profiling study at Stanford University. We assessed exomes for rare likely pathogenic and pathogenic variants in genes associated with Mendelian disease in the Online Mendelian Inheritance in Man (OMIM) database. We used American College of Medical Genetics (ACMG) guidelines were used for the classification of rare sequence variants, and additionally we assessed pharmacogenetic variants. Twelve out of 70 (17%) participants had medically actionable findings in Mendelian disease genes, including 6 (9%) with mutations in genes not currently included in the ACMGs list of 59 actionable genes. This number is higher than that reported in previous studies and suggests added benefit from utilizing expanded gene lists and manual curation to assess actionable findings. A total of 60 participants (89%) had non-actionable findings identified including 57 who were found to be mutation carriers for recessive diseases and 21 who have increased Alzheimers disease risk due to heterozyg ous or homozygous APOE e4 alleles (18 participants had both). These results suggest that exome sequencing may have considerably more utility for health management in the general population than previously thought.

genomics↗

bioRxiv2017

Static And Dynamic DNA Loops Form AP-1 Bound Activation Hubs During Macrophage Development

The three-dimensional arrangement of the human genome comprises a complex network of structural and regulatory chromatin loops important for coordinating changes in transcription during human development. To better understand the mechanisms underlying context-specific 3D chromatin structure and transcription during cellular differentiation, we generated comprehensive in situ Hi-C maps of DNA loops during human monocyte-to-macrophage differentiation. We demonstrate that dynamic looping events are regulatory rather than structural in nature and uncover widespread coordination of dynamic enhancer activity at preformed and acquired DNA loops. Enhancer-bound loop formation and enhancer-activation of preformed loops represent two distinct modes of regulation that together form multi-loop activation hubs at key macrophage genes. Activation hubs connect 3.4 enhancers per promoter and exhibit a strong enrichment for Activator Protein 1 (AP-1) binding events, suggesting multi-loop activation hubs driven by cell-type specific transcription factors may represent an important class of regulatory chromatin structures for the spatiotemporal control of transcription.\n\nHIGHLIGHTSO_LIHigh resolution and high sensitivity of loop detection via deeply sequenced in situ Hi-C experiments during monocyte to macrophage differentiation (> 10 billion total reads)\nC_LIO_LIMulti-loop interaction communities identified surrounding key macrophage genes.\nC_LIO_LIMulti-loop communities connect dynamic enhancers through both static and newly acquired DNA loops, forming hubs of activation\nC_LIO_LIMacrophage activation hubs are enriched for AP-1 bound long-range enhancer interactions, suggesting cell-type specific TFs drive changes in 3D structure and transcription through regulatory DNA loops\nC_LI

genomics↗

bioRxiv2017

Index Switching Causes "Spreading-Of-Signal" Among Multiplexed Samples In Illumina HiSeq 4000 DNA Sequencing

Illumina-based next generation sequencing (NGS) has accelerated biomedical discovery through its ability to generate thousands of gigabases of sequencing output per run at a fraction of the time and cost of conventional technologies. The process typically involves four basic steps: library preparation, cluster generation, sequencing, and data analysis. In 2015, a new chemistry of cluster generation was introduced in the newer Illumina machines (HiSeq 3000/4000/X Ten) called exclusion amplification (ExAmp), which was a fundamental shift from the earlier method of random cluster generation by bridge amplification on a non-patterned flow cell. The ExAmp chemistry, in conjunction with patterned flow cells containing nanowells at fixed locations, increases cluster density on the flow cell, thereby reducing the cost per run. It also increases sequence read quality, especially for longer read lengths (up to 150 base pairs). This advance has been widely adopted for genome sequencing because greater sequencing depth can be achieved for lower cost without compromising the quality of longer reads. We show that this promising chemistry is problematic, however, when multiplexing samples. We discovered that up to 5-10% of sequencing reads (or signals) are incorrectly assigned from a given sample to other samples in a multiplexed pool. We provide evidence that this \"spreading-of-signals\" arises from low levels of free index primers present in the pool. These index primers can prime pooled library fragments at random via complementary 3 ends, and get extended by DNA polymerase, creating a new library molecule with a new index before binding to the patterned flow cell to generate a cluster for sequencing. This causes the resulting read from that cluster to be assigned to a different sample, causing the spread of signals within multiplexed samples. We show that low levels of free index primers persist after the most common library purification procedure recommended by Illumina, and that the amount of signal spreading among samples is proportional to the level of free index primer present in the library pool. This artifact causes homogenization and misclassification of cells in single cell RNA-seq experiments. Therefore, all data generated in this way must now be carefully re-examined to ensure that \"spreading-of-signals\" has not compromised data analysis and conclusions. Re-sequencing samples using an older technology that uses conventional bridge amplification for cluster generation, or improved library cleanup strategies to remove free index primers, can minimize or eliminate this signal spreading artifact.

molecular biology↗