key: cord-0807226-qd8zmhxu
authors: Sanford, James A.; Nogiec, Christopher D.; Lindholm, Malene E.; Adkins, Joshua N.; Amar, David; Dasari, Surendra; Drugan, Jonelle K.; Fernández, Facundo M.; Radom-Aizik, Shlomit; Schenk, Simon; Snyder, Michael P.; Tracy, Russell P.; Vanderboom, Patrick; Trappe, Scott; Walsh, Martin J.
title: Molecular Transducers of Physical Activity Consortium (MoTrPAC): Mapping the Dynamic Responses to Exercise
date: 2020-06-19
journal: Cell Rep
DOI: 10.1016/j.celrep.2020.107863
sha: 2e4c865ce5f063c3d04f3f05475274317b7242f7
doc_id: 807226
cord_uid: qd8zmhxu

Exercise provides a robust physiological stimulus that evokes cross-talk among multiple tissues that when repeated regularly (i.e., training) improves physiological capacity, benefits numerous organ systems and decreases the risk for premature mortality. However, a gap remains in identifying the detailed molecular signals induced by exercise that benefit health and prevent disease. The Molecular Transducers of Physical Activity Consortium (MoTrPAC) was established to address this gap and generate a molecular map of exercise. Preclinical and clinical studies will examine the systemic effects of endurance and resistance exercise across a range of ages and fitness levels by molecular probing of multiple tissues before and after acute and chronic exercise. From this multi-omic and bioinformatic analysis, a molecular map of exercise will be established. Altogether, MoTrPAC will provide a public database that is expected to enhance our understanding of the health benefits of exercise and to provide insight into how activity mitigates disease.

To address whether the endogenous levels of IFNs generated by IECs controls SARS-CoV-2 179 replication and de-novo infectious virus production, we exploited our previously reported 180

IECs depleted of either the type I IFN receptor (IFNAR1) (AR-/-), the type III IFN receptor 181 (IFNLR1) (LR -/-) or depleted of both IFN receptors (dKO). To control that our cells were 182 functionally knocked-out for the type I IFN (AR-/-) and/or the type III IFN receptor (LR-/-), 183 T84 cells were treated with either IFN and the production of the IFN stimulated gene IFIT1 184 was evaluated. As expected, type I IFN receptor knock-out cells (AR-/-) only responded to 185 IFNλ, whereas type III IFN receptor knock-out cells (LR-/-) only responded to IFNβ1 (Fig.  186 S3A). The IFN receptor double knock-out cells (dKO) did not respond to either IFN (Fig. S3A) . 187 WT or IFN receptor knock-out T84 cells were infected with SARS-CoV-2 at a MOI of 0.1 (as 188 determined in T84 cells). 24 hpi, cells were immunostained using the anti-N antibody and the number of infected cells was quantified using fluorescent microscopy (Fig. 3A) . Results 190 showed that depletion of the type I IFN receptor (AR-/-) resulted in a slight increase in the 191 number of infected cells. Importantly, depletion of the type III IFN receptor (LR-/-) resulted 192 in a significant increase of cell infectivity by a factor of around seven. Similar results were 193 obtained when both the type I and the type III IFN receptors were depleted (dKO) (Fig. 3B) . 194 Interestingly, this increase in the number of infected cells upon depletion of the type III IFN 195 receptor (LR-/-) was associated with a significant increase in viral genome copy numbers 196 Interestingly, in this work expression of type III IFN was shown to be very low. This is 280 contrary to our data showing high production of type III IFN, however we have monitored IFN λ2/3 levels while this work has monitored IFNλ1 levels. Further work is necessary to 282 address if different subtypes of type III IFNs are induced by SARS-CoV-2. It is well known that 283 in vivo intestinal epithelium cells are less immunoresponsive because of the gut 284 microenvironment (e.g. microbiota and tissue specific immune cells) and as such they will 285 very likely show a severely dampened immune response allowing for an even greater SARS-286

CoV-2 replication. 287 288 Analysis of the single-cell RNA sequencing data from the Colon Atlas revealed that only 3.8% 289 of human colon epithelial cells express very low levels of the SARS-CoV-2 receptor ACE-2 290 ( Fig. S4A-E) . This is very different to the small intestine where ACE-2 appears to be more 291 expressed (Qi et al., 2020) . This low ACE-2 level could explain why we have a small 292 percentage of infected cells in our colon organoids (Fig. 4E ). On the contrary, TMPRSS2 293 seems to be not a limiting factor in the colon ( lack of type I induction could be due to a kinetic delay of type I IFN production compared to 346 type III IFN but this will need to be carefully addressed in further experiments. Another 347 possibility is that SARS-CoV-2 encodes a specific antagonist which counteracts the 348 production of type I IFN only. However, further studies are necessary to prove this novel 349 concept. Additionally, the observation that the knock-out of the type III IFN receptor leads 350 to a much greater increase of SARS-Cov-2 infection, replication and de-novo virus 351 production compared to knock out of the type I receptor (Fig. 3A-D) in the gut is due to fecal/oral transmission or is a manifestation of virus spreading from the 361 lung to the gut. In the context of the gut we foresee that at the onset of SARS-CoV-2 362 infection, hIECs will mount an antiviral response through the type III IFN signaling pathway. 363

As immune cells participate in mounting an innate immune response, type I IFN will be 364 secreted from these cells and will be able to act on intestinal epithelial cells further 365 reinforcing their antiviral state against SARS-CoV-2. In respect to the severe pathologies 366 observed in the lung, which are believed to be caused by a cytokine storm, the findings that 367 lung epithelial cells mount a muted immune response upon SARS-CoV-2 infection suggests 368 that the cytokines are coming from an alternative source. This source could be from local 369 immune cells but also from the gastro-intestinal mucosa given the large immune response (#300-2K)) were purchased from Peprotech and and IFNλ 3 (IL-28B) was purchased from 518

BioMol. All three lambda interferons were combined and were used at a concentration of 519 100ng/mL each to make a final concentration of 300ng/mL, Pyridone 6 (Calbiochem 520 #420099-500)was used at a final concentration of 2uM. 521 522 Viral infections. All SARS-CoV-2 infections were performed the MOI indicated in the text. 523

Media was removed from cells and virus was added to cells for 1 hour at 37°C. Virus was 524 removed, cells were wash 1x with PBS and media or media containing inhibitors/cytokines 525 was added back to the cells. 526 527 2D organoid seeding. 8-well iBIDI glass bottom chambers were coated with 2.5% human 528 collagen in water for 1 h prior to organoids seeding. Organoids were collected at a ratio of 529 100 organoids/transwell. Collected organoids were spun at 450g for 5 mins and the 530 supernatant was removed. Organoids were washed 1X with cold PBS and spun at 450g for 5 531 mins. PBS was removed and organoids were digested with 0.05% Trypsin-EDTA (Life 532 technologies) for 5 mins at 37°C. Digestion was stopped by addition of serum containing 533 medium. Organoids were spun at 450g for 5 mins and the supernatant was removed and 534 organoids were re-suspended in normal growth media at a ratio of 250 µL media/well. The 535 collagen mixture was removed from the iBIDI chambers and 250 µL of organoids were 536 added to each well. 537 RNA isolation, cDNA, and qPCR. RNA was harvested from cells using RNAeasy RNA 539 extraction kit (Qiagen) as per manufactures instructions. cDNA was made using iSCRIPT 540 reverse transcriptase (BioRad) from 250 ng of total RNA as per manufactures instructions. q-541 RT-PCR was performed using iTaq SYBR green (BioRad) as per manufacturer's instructions, 542 TBP or HPRT1 were used as normalizing genes. (https://singlecell.broadinstitute.org/single_cell/study/SCP259). Expression matrices of the 586 epithelial subset of 30 samples were imported and individually analyzed using the Seurat 587 software, version 3.1.4 (https://github.com/satijalab/seurat). Quality filtering was 588 performed, and cells having fewer than 500 genes and more than 30% of UMI count 589 mapped to mitochondrial genes were discarded. Consecutively, the resulting datasets were 590 normalized, scaled and high-variance genes genes were selected. Reciprocal PCA-based data 591 integration was done to merge the samples. Afterwards, the resulting batch-corrected 592 counts were used for calculating PCA-based dimensionality reduction and unsupervised 593 Louvain clustering. Furthermore, UMAP visualization was calculated using 50 neighboring 594 points for the local approximation of the manifold structure. Cell type annotation was based 595 on the unsupervised clustering and the metadata provided by the colon atlas ( 

SARS-CoV-2 launches a unique transcriptional signature 607 from in vitro, ex vivo, and in vivo systems (Microbiology)

Comparative replication and immune activation profiles of SARS-610

CoV-2 and SARS-CoV in human lungs: an ex vivo study with implications for the 611 pathogenesis of COVID-19

Type I and Type III Interferons Drive Redundant Amplification Loops 614 to Induce a Transcriptional Signature in Influenza-Infected Airway Epithelia

Origin and evolution of pathogenic coronaviruses

Replication of Human Noroviruses in Stem 620 Cell-Derived Human Enteroids

Ultrastructure of the replication sites of positive-strand 622 RNA viruses

Isolation and characterization of SARS-CoV-2 from the 625 first US COVID-19 patient (Microbiology)

SARS-CoV-2 Cell Entry 628 Depends on ACE2 and TMPRSS2 and Is Blocked by a Clinically Proven Protease Inhibitor

SARS-CoV-2 productively 632 infects human gut enterocytes

Enteric involvement of severe acute respiratory syndrome-associated coronavirus 635 infection1

SARS-CoV-2 sensitive to type I interferon pretreatment

Outbreak of pneumonia of unknown etiology 639 in Wuhan, China: The mystery and the miracle

SARS-CoV-2 receptor ACE2 and TMPRSS2 642 are primarily expressed in bronchial transient secretory cells

Potent Antiviral 644 Activities of Type I Interferons to SARS-CoV-2 Infection

Seasonality of Respiratory Viral 646 Infections

Exogenous ACE2 Expression Allows Refractory Cell Lines To Support Severe Acute 649 Respiratory Syndrome Coronavirus Replication

Coronavirus Infections-More Than Just 651 the Common Cold

Type I and Type III Interferons 654 Display Different Dependency on Mitogen-Activated Protein Kinases to Mount an Antiviral 655 State in the

Differential induction of 658 interferon stimulated genes between type I and type III interferons is independent of 659 interferon receptor abundance

Single cell RNA sequencing of 13 human 664 tissues identify cell types and receptors of human coronaviruses

Intra-and Inter-cellular 668 Rewiring of the Human Colon during Ulcerative Colitis

Reovirus intermediate subviral particles constitute a 671 strategy to infect intestinal epithelial cells by exploiting TGF-β dependent pro-survival 672 signaling

Asymmetric distribution of 675 TLR3 leads to a polarized immune response in human intestinal epithelial cells

Visualization of Double-Stranded 678 RNA in Cells Supporting Hepatitis C Virus RNA Replication

Knowledge synthesis from 681 100 million biomedical documents augments the deep expression profiling of coronavirus 682 receptors

Animal Coronaviruses: A Brief Introduction

Emerging and re-emerging 686 coronaviruses in pigs

Detection of SARS-688

CoV-2 in Different Types of Clinical Specimens

Virological assessment of hospitalized 691 patients with COVID-2019

Covid-19 and the Digestive System

Single-cell RNA expression profiling of 695 ACE2, the putative receptor of Wuhan 2019-nCoV

Prolonged presence of SARS-CoV-2 viral RNA in faecal samples

Evidence for gastrointestinal 701 infection of SARS-CoV-2

Prolonged Viral Shedding in Feces of Pediatric Patients 704 with Coronavirus Disease

High 706 expression of ACE2 receptor of 2019-nCoV on the epithelial cells of oral mucosa

Characteristics of pediatric SARS-CoV-2 infection and potential evidence for 710 persistent fecal viral shedding

Interferon-λ enhances adaptive mucosal immunity by 713 boosting release of thymic stromal lymphopoietin

Single-cell RNA expression 715 profiling of ACE2, the receptor of SARS-CoV-2 (Bioinformatics)

Human intestinal tract serves as an alternative infection route for 718 Middle East respiratory syndrome coronavirus

Highlights Human intestinal epithelium cells (hIECs) can be infected by SARS-CoV-2 hIECs support SARS-CoV-2 replication and produce de-novo viruses SARS-CoV-2 infection can be controlled in hIECs by type I and III interferon eTOC Stanifer et al. find that SARS-CoV-2 could infect the human gastrointestinal tract and efficiently produce new viruses. Importantly, they find that the cytokines type I and III interferons, which are naturally made by cells in response to viral infection