K Mrouj

P Singh

M Sobecki

G Dubra

Al Ghoul

A Aznar

Susana Prieto

F Bernex

Benoit Bordignon

M Pouzolles

V Zimmerman

V Dardalhon

M Villalba

L Krasinska

D Fisher

Ki-67 supports global gene expression programmes driving tumourigenesis

à la diffusion de documents scientifiques de niveau recherche, publiés ou non, émanant des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

contributes to organisation of chromatin [START_REF] Sobecki | The cell proliferation antigen Ki-67 organises heterochromatin[END_REF] , which controls gene expression and thus cellular plasticity, a characteristic of cancer cells [START_REF] Ben-Porath | An embryonic stem cell-like gene expression signature in poorly differentiated aggressive human tumors[END_REF][START_REF] Kim | A Myc network accounts for similarities between embryonic stem and cancer cell transcription programs[END_REF] . We first tested the involvement of Ki-67 in tumour initiation using an in vitro model. We transduced our previously generated Mki67 +/+ or TALENmutated Mki67 -/-3T3 fibroblasts [START_REF] Sobecki | The cell proliferation antigen Ki-67 organises heterochromatin[END_REF] with oncogenic mutant H-Ras (G12V), and assessed colony formation as an indicator of transformation. While H-Ras G12V -transduced control 3T3 cells efficiently formed colonies, Mki67 -/-3T3 cells did not, indicating that Ki-67 expression is required for transformation (Extended Data Fig. 1). We next determined whether Ki-67 knockout affects tumour initiation in vivo. We used a mouse model of colon carcinogenesis induced chemically by azoxymethane / dextran sodium sulphate (AOM-DSS) treatment [START_REF] De Robertis | The AOM/DSS murine model for the study of colon carcinogenesis: From pathways to diagnosis and therapy studies[END_REF] , and tested the effect of a germline TALEN-disruption of Ki-67 (Mki67 2nt∆/2nt∆ ) that we generated [START_REF] Sobecki | The cell proliferation antigen Ki-67 organises heterochromatin[END_REF] .

As expected, AOM-DSS efficiently induced colon tumours within 16 weeks in wild-type and Mki67 2nt∆/+ mice; however, no macroscopic lesions were observed in Mki67 2nt∆/2nt∆ mice (Fig. 1a,b). We confirmed that this was not due to an inability to induce inflammation, since DSS alone triggered similar inflammatory responses in mice of all genotypes (Extended Data Fig. 2). Furthermore, immune cell proliferation and differentiation in Mki67 2nt∆/2nt∆ mice appeared normal in response to haemolytic anaemia triggered by phenylhydrazine treatment (Extended Data Fig. 3). This suggests that Ki-67 is specifically required for initiation of tumourigenesis. To confirm this, we used a genetic model of intestinal tumourigenesis. We crossed Mki67 2nt∆/2nt∆ mice with Apc ∆14/+ mice, which rapidly develop tumours in the intestine due to loss of the second allele of the Apc tumour suppressor gene [START_REF] Colnot | Colorectal cancers in a new mouse model of familial adenomatous polyposis: influence of genetic and environmental modifiers[END_REF] . While Apc ∆14/+ Mki67 2nt∆/+ mice formed multiple intestinal tumours as expected, tumour burden was strongly reduced in Apc ∆14/+ Mki67 2nt∆/2nt∆ mice (Fig. 1c,d). These results indicate that Ki-67 is required for efficient initiation of tumourigenesis induced either by an oncogene, chemical mutagenesis or loss of a tumour suppressor.

We next asked whether Ki-67 is required for tumour growth and metastasis from already transformed cells. As a first approach, we knocked down Ki-67 by stable shRNA in a commonly used aggressive human cervical cancer cell line, HeLa S3, and grafted the resulting cells and an shRNA control line into opposing flanks of athymic nude mice. Ki-67 knockdown was maintained in vivo (Extended Data Fig. 4a,b) and, as expected, this did not affect cell proliferation (as shown by unchanged PCNA and mitotic indices; Extended data Fig. 4c,d). However, tumour growth was severely slowed (Fig. 2a) and histopathological analysis showed vast areas of necrosis and apoptosis accompanied by disorganised vascular and lymphatic networks, indicating disrupted angiogenesis (Fig. 2b,c). To ensure that phenotypes of Ki-67 downregulation were not specific to the tumour type or knockdown approach, we generated a biallelic MKI67 gene knockout (KO) by CRISPR-Cas9 in human MDA-MB-231 triple negative breast cancer cells (Extended Data Fig. 4e,f). As expected, MKI67 -/-cells proliferated normally in vitro (Extended Data Fig. 4g,h) but tumours from xenografts in nude mice grew much slower than controls, again showing normal cell proliferation but defective angiogenesis (Fig. 2d-f). Thus, in xenograft experiments, Ki-67 sustains tumour growth but not by controlling cell proliferation.

To determine effects of Ki-67 loss in a mouse model that more closely mimics human breast cancer, we used 4T1 mammary carcinoma cells. This cell line is derived from BALB/c mice, is highly tumourigenic, spontaneously metastasises to distant organs [START_REF] Dexter | Heterogeneity of tumor cells from a single mouse mammary tumor[END_REF][START_REF] Heppner | Nontransgenic models of breast cancer[END_REF] , and, when grafted in a syngeneic background, a biphasic tumour progression profile is observed due to an induced immune response [START_REF] Tao | Imagable 4T1 model for the study of late stage breast cancer[END_REF] . As expected, CRISPR-Cas9-mediated Mki67 knockout did not affect 4T1 cell proliferation rates (Extended Data Fig. 5a-d). We engrafted WT and Ki-67 knockout 4T1 cells orthotopically into mammary fat pads in both immune-proficient syngeneic BALB/c mice and immunodeficient (athymic-nude and NOD/SCID) mice, the comparison of which should allow identification of the effects of the immune system. In immunodeficient mice, tumours from Mki67 -/-4T1 cells grew significantly slower than from Ki-67-expressing 4T1 cells (Fig. 3a-c). In immune-proficient BALB/c mice, control 4T1 tumours established quickly and, as expected, initially regressed before regrowing (Fig. 3d). However, in these mice, Mki67 -/-4T1 cells formed primary tumours as efficiently as controls, but no initial regression occurred, overriding the slower growth of knockout tumours and resulting in higher final tumour burden than controls (Fig. 3d). This suggested a defective immune response in mice bearing Ki-67 knockout tumours. We analysed this by immunophenotyping of spleens and lymph nodes. The fraction of dendritic cells, B-cells and T-cells (except for T-reg) was reduced in Mki67 -/-4T1 tumour-bearing mice, as a result of a dramatic increase in cells positive for CD11b (a common myeloid marker, expressed by monocytes, neutrophils, NK cells, granulocytes, macrophages and myeloid-derived suppressor cells (MDSC)) (Extended Data Fig. 6). In agreement, immunohistological analysis revealed increased infiltration of MDSC in knockout tumours (using the MDSC marker, GR1; Fig. 3e), possibly indicating an immunosuppressive environment that protects the tumours against immune-mediated cytotoxicity.

In immune-proficient mice, despite the impaired immune-response to Mki67 -/-4T1 cells and a consequently higher tumour burden, there were noticeably less metastases than from control 4T1 cells, although this failed to reach statistical significance (p = 0.13) (Fig 3f).

However, the reduction in visible metastasis from Mki67 -/-4T1 cells was highly significant in immunodeficient mice (Fig. 3g) or in immune-proficient mice injected in the tail vein to circumvent the immune-targeting of tumour cells at the primary-site (Fig. 3h). We quantified micrometastases in nude mice by dissociating lung tissue after 2 weeks and growing cells in the presence of 6-thioguanine, to which 4T1 cells are resistant [START_REF] Heppner | Nontransgenic models of breast cancer[END_REF] . The number of metastatic cells from Ki-67 knockouts was reduced nearly 100-fold (Extended Data Fig. 7). These results highlight a trade-off for cancer cells, whereby Ki-67 expression sustains tumour growth and promotes metastasis, yet also confers efficient targeting by the immune system. Since we previously found that Ki-67 knockout in mouse NIH3T3 cells or knockdown in human cancer cells does not alter cell proliferation nor induce cell death, but disrupts chromatin organisation 2 and alters gene expression, we hypothesised that the latter might explain the requirements for Ki-67 in tumourigenesis. To explore this idea we first compared transcriptomes of WT and Mki67 -/-NIH3T3 cells by RNA-seq. Consistent with roles for Ki-67 in maintaining global chromatin organisation, this revealed widespread changes in gene expression, with 2558 genes significantly deregulated in independent clones of Mki67 -/-cells (q < 0.05) (Extended Data Fig. 8a; Supplementary Table 1). Next, we investigated how transcriptomes are remodelled in 4T1 cells lacking Ki-67. In these cancer cells, Mki67 knockout caused genome-scale gene expression alterations: 4979 genes were deregulated, of which 1239 and 585 genes were >2-fold down-regulated and up-regulated, respectively (Fig. 4a; Extended Data Fig. 8b; Supplementary Table 2). There was little overlap in the deregulated genes between Mki67 -/-(epithelial) and NIH3T3 (mesenchymal) cells (Extended Data Fig. 8b; Supplementary Tables 1,2) suggesting that Ki-67 ensures gene expression programmes in different cell types by maintaining chromatin organisation rather than directly regulating specific genes. RNA-seq of early stage tumours from WT and Ki-67 mutant 4T1 cells grafted into nude mice showed that Ki-67-dependent transcriptome changes were preserved in vivo (Fig. 4b).

We performed pathway analysis of genes highly deregulated in Ki-67 knockout 4T1 cells to better understand the links between Ki-67-mediated gene expression control and tumourigenesis. We found upregulation of Notch targets and downregulation of genes involved in the inflammatory response, Wnt pathway and the EMT (Fig. 4c) which we validated by qRT-PCR (Extended Data Fig. 8c). Importantly, although the Notch pathway is oncogenic in T cell acute lymphoid leukaemia, it can act as a tumour suppressor in specific cellular contexts [START_REF] Nowell | Notch as a tumour suppressor[END_REF] , can block Wnt signaling [START_REF] Nicolas | Notch1 functions as a tumor suppressor in mouse skin[END_REF][START_REF] Devgan | p21WAF1/Cip1 is a negative transcriptional regulator of Wnt4 expression downstream of Notch1 activation[END_REF] (a driver of tumourigenesis, cell stemness and the EMT) and induce drug resistance [START_REF] Meng | Secretase Inhibitors Abrogate Oxaliplatin-Induced Activation of the Notch-1 Signaling Pathway in Colon Cancer Cells Resulting in Enhanced Chemosensitivity[END_REF] . We confirmed Notch pathway upregulation at the protein level (Fig. 4d). We further verified that Ki-67 knockout 4T1 cells had lost expression of the mesenchymal marker vimentin but upregulated E-cadherin, and had a more epithelial morphology (Fig. 4e). Downregulated genes were enriched in targets of nuclear factor erythroid 2-related factor 2 (NFE2L2), which upregulates genes in response to oxidative stress; interferon regulatory factor 8 (IRF8); polycomb-repression complex 2 (PRC2), which mediates H3K27me3 and is a well-characterised regulator of the EMT [START_REF] Malouf | Architecture of epigenetic reprogramming following Twist1mediated epithelial-mesenchymal transition[END_REF][START_REF] Tiwari | Sox4 is a master regulator of epithelial-mesenchymal transition by controlling Ezh2 expression and epigenetic reprogramming[END_REF] ; and the pluripotency factors Nanog and Sox2 (Extended Data Fig. 8d). We focused on PRC2 as we previously found 10 that in human osteosarcoma U2OS cells, Ki-67 binds to the essential PRC2 component SUZ12. To test whether the repression of the EMT in Ki-67 knockout depends on PRC2, we disrupted Suz12 or Ezh2 in WT and Mki67 -/-4T1 cells using CRISPR-Cas9. This partially rescued expression of vimentin (Extended Data Fig. 8e,f). However, it did not restore tumour growth rates nor metastasis in vivo from Mki67 -/-4T1 cells, nor affect tumourigenicity of control cells, in nude mice (Extended Data Fig. 8g). Thus, the PRC2 complex activity is restrained by Ki-67, but does not in itself have either oncogenic or tumour suppressive activity in this system. As such, the reported PRC2 roles in cancer [START_REF] Chase | Aberrations of EZH2 in Cancer[END_REF][START_REF] Bracken | Polycomb group proteins: navigators of lineage pathways led astray in cancer[END_REF] might not apply generally, and a single chromatin regulation pathway cannot account for Ki-67 roles in supporting the EMT and tumourigenesis.

Like Ki-67, the EMT is required for metastasis in some mouse cancer models [START_REF] Ye | Upholding a role for EMT in breast cancer metastasis[END_REF][START_REF] Aiello | Upholding a role for EMT in pancreatic cancer metastasis[END_REF] . The EMT is also closely associated with a stem-like state [START_REF] Mani | The epithelial-mesenchymal transition generates cells with properties of stem cells[END_REF][START_REF] Morel | Generation of breast cancer stem cells through epithelialmesenchymal transition[END_REF][START_REF] Wellner | The EMT-activator ZEB1 promotes tumorigenicity by repressing stemness-inhibiting microRNAs[END_REF] , as well as resistance to chemotherapeutic drugs [START_REF] Zheng | Epithelial-to-mesenchymal transition is dispensable for metastasis but induces chemoresistance in pancreatic cancer[END_REF] and induction of immune responses [START_REF] López-Soto | Epithelial-mesenchymal transition induces an antitumor immune response mediated by NKG2D receptor[END_REF] . We therefore next investigated the importance of Ki-67 for these three EMT-linked characteristics.

First, we analysed two indicators of tumour cell stemness: the ability to form spheroids in the absence of adhesion to a surface [START_REF] Mani | The epithelial-mesenchymal transition generates cells with properties of stem cells[END_REF][START_REF] Ishiguro | Tumor-derived spheroids: Relevance to cancer stem cells and clinical applications[END_REF] , and aldehyde dehydrogenase activity [START_REF] Ginestier | ALDH1 Is a Marker of Normal and Malignant Human Mammary Stem Cells and a Predictor of Poor Clinical Outcome[END_REF][START_REF] Huang | Aldehyde Dehydrogenase 1 Is a Marker for Normal and Malignant Human Colonic Stem Cells (SC) and Tracks SC Overpopulation during Colon Tumorigenesis[END_REF] . Both parameters were strongly reduced in Ki-67 knockout 4T1 cells (Fig. 4f,g).

Second, we noticed that 26 genes involved in drug metabolism were downregulated in Ki-67 knockout 4T1 cells, while only one was upregulated, suggesting that Ki-67 expression might determine sensitivity to chemotherapeutic drugs (Extended Data Fig. 9a,b). To test this, we performed an automated gene-drug screen using the Prestwick chemical library, composed of 1283 FDA-approved small molecules, as well as salinomycin, a positive control found to target cancer stem cells [START_REF] Gupta | Identification of selective inhibitors of cancer stem cells by highthroughput screening[END_REF] , and 6-thioguanine, which was originally used to isolate 4T1 cells [START_REF] Dexter | Heterogeneity of tumor cells from a single mouse mammary tumor[END_REF] . Control 4T1 cells were sensitive to 102 drugs at 10µM concentration, while the two Mki67 -/-clones were sensitive to 99 and 98 respectively, with 82 hits common to the three cell lines (Extended Data Fig. 9c; Supplementary Data). This suggests that Ki-67 loss does not qualitatively alter the drug-sensitivity profiles. We next determined the IC50 of 10 common hits used in cancer therapy. Importantly, Mki67 -/-cells were markedly more sensitive to all the molecules tested (Fig. 4h; Extended Data Fig. 9d).

Third, genes directing mouse major histocompatibility complex (MHC) class I-mediated antigen presentation Tap2, Psmb8 and Psmb9 were downregulated in Mki67 -/-4T1 cells (Extended Data Fig. 8c; Supplementary Table 2). Flow cytometry confirmed lower expression of the mouse MHC class I molecules H2D and H2K (Fig. 4i), providing an explanation for how Ki-67 knockout affects tumour recognition by the immune system. We obtained similar results in human MKI67 -/-MDA-MB-231 cells, implying that roles of Ki-67 in maintaining MHC expression are conserved across species (Extended Data Fig. 10).

The above results show that Ki-67 is not required for cancer cell proliferation in vivo, but supports coherent transcriptional programmes that are involved in tumour cell plasticity, drug resistance and induction of immune responses. Together, these likely account for the roles of Ki-67 in tumourigenesis revealed in this study (Fig. 4j). Clues to its biochemical mechanism of action are suggested by the fact that Ki-67 is an intrinsically disordered protein (IDP) and behaves as a surfactant for mitotic chromatin [START_REF] Cuylen | Ki-67 acts as a biological surfactant to disperse mitotic chromosomes[END_REF] . Since we previously found that heterochromatin is more dispersed in cells lacking Ki-67 (ref.

2), we propose that these properties may also allow Ki-67 to regulate interphase chromatin. Due to their conformational flexibility, IDPs can act as hubs to bind many protein partners [START_REF] Wright | Intrinsically disordered proteins in cellular signalling and regulation[END_REF] , and we previously identified many chromatin regulators interacting with Ki-67 (ref.

2). However, disrupting one such interactor, the PRC2 complex, does not restore tumourigenic capacity to Ki-67 mutant cancer cells, consistent with the idea that Ki-67 may act more globally.

While it has long been thought that global changes in nuclear structure observed in cancer cells might contribute functionally to carcinogenesis [START_REF] Zink | Nuclear structure in cancer cells[END_REF] , mechanistic insight into this question has been lacking. We speculate that the alterations of nuclear organisation seen in cancer cells may reflect their increased cellular plasticity. By binding multiple chromatin regulators and organising the transcriptome at a genome scale, Ki-67 might contribute to both nuclear structuration and cellular plasticity, thereby conferring on cancer cells the ability to adapt to their environment.

1 6-8 weeks-old female BALB/c (BALB/cOlaHsd), athymic nude (Hsd:Athymic Foxn1 nu /Foxn1 + ), and NOD.SCID (NOD.CB17-Prkdc scid /NCrHsd) mice were purchased from Envigo. C57BL/6 Apc ∆14 mice [START_REF] Colnot | Colorectal cancers in a new mouse model of familial adenomatous polyposis: influence of genetic and environmental modifiers[END_REF] were provided by Philippe Jay (IGF, Montpellier).

Methods

Cell lines and mice

Animal studies

All animal experiments were performed in accordance with international ethics standards and were subjected to approval by the Animal Experimentation Ethics Committee of Languedoc Roussillon (n°APAFIS#8637-2017012311188975v3).

Antibodies and plasmids

Antibodies: Ki-67 (clone SP6; Abcam), cyclin A2 (6E6; Novocastra), PCNA (ab18197; Abcam), β-catenin (BD610154; BD-Bioscience), Ras (G12V Mutant Specific D2H12, #14412; CST), actin (A2066; Sigma), vimentin (D21H3, #5741; CST), E-Cadherin (24E10, #3195; CST), Suz12 (D39F6, #3737; CST), H3K27me3 (#39155, Active Motif), H2D d -FITC (#553579; BD Biosciences), H2K d -PE (SF1-1.1; BD Biosciences), HLA-PE (EMR8-5; BD Biosciences).

Lentiviral Vectors used: LentiCRISPRv2 (Addgene #52961), pMD2.G (Addgene #12259), psPAX2 (Addgene #12260). pHIV-Luc-ZsGreen (Addgene #39196) was used to generate bicistronic lentivirus that expresses both Luciferase and Zsgreen.

Retroviral vectors used: pBabe-puro (Addgene #1764), pBabe-puro H-Ras G12V (Addgene #1768). gag/pol (retroviral packaging) and Maloney (envelope) were gift from Leatitia Linares (IRCM, Montpellier). pUC57-U6-sgRNA (#51132, Addgene); Cas9-VP12 (#72247, Addgene), modified by adding T2A-GFP at the C-terminal end (gift from Edouard Bertrand, IGMM).

CRISPR/Cas9-mediated genome editing

The sgRNAs targeting mouse Mki67 exon 3 or human MKI67 exon 6 and non-targeting control sequences were previously designed [START_REF] Shalem | Genome-scale CRISPR-Cas9 knockout screening in human cells[END_REF] , and cloning of the target sequence into the LentiCRISPRV2 lentiviral vector was conducted as described [START_REF] Shalem | Genome-scale CRISPR-Cas9 knockout screening in human cells[END_REF] . Lentiviruses encoding the sgRNA targeting sequences were produced. Transduced cells (4T1 and MDA-MB-231) expressing CRISPR/Cas9 were selected using puromycin. Resistant cells were isolated and seeded as single cell clones in 96 well-plates.

For Suz12 and Ezh2 knockout, sgRNA targeting sequences [START_REF] Shalem | Genome-scale CRISPR-Cas9 knockout screening in human cells[END_REF] were synthesised with BpiI sticky ends and cloned into the pUC57-U6-sgRNA vector. Cas9-VP12-T2A-GFP and sgRNA vectors were transfected into 4T1 WT and Ki-67 -/-#2 clone using Lipofectamine 2000 (ThermoFisher). 24h post-transfection, GFP-positive cells were sorted i96-well plates by flow cytometry (FACS Aria, BD). After 10-12 days of culture, colonies were picked and screened (Cellomics, Thermo), using Suz12 or H3K9me3 antibodies. Positive knockout clones were confirmed by PCR, IF and western blotting.

AOM-DSS-induced colon carcinogenesis

Mice (Mki67 +/+ ; Mki67 +/2nt∆ & Mki67 2nt∆/2nt∆ ) were given a single intraperitoneal injection of AOM (10 mg/kg in 0.9% saline; A5486, Sigma-Aldrich), and one week later, 2% Dextran Sodium Sulfate (DSS; MP Biomedicals) was administered in the drinking water for 7 consecutive days. Mice were sacrificed at week 16-post AOM-DSS treatment and colon tissues were removed.

Colons were flushed and fixed overnight in neutral buffered formalin (10%) before paraffin embedding. Briefly, 4µm thick sections were dewaxed in xylene and rehydrated in graded alcohol baths. Slides were incubated in 3% H2O2 for 20 min and washed in PBS to quench endogenous peroxidase activity. Antigen retrieval was performed by boiling slides for 20 min in 10 mM sodium citrate buffer, pH 6.0. Nonspecific binding sites were blocked in blocking buffer (TBS, pH 7.4, 5% dried milk, 0.5% Triton X-100) for 60 min at RT. Sections were incubated with anti-β-catenin antibody diluted in blocking buffer overnight at 4°C. Envision+ (Dako) was used as a secondary reagent. Signals were developed with DAB (Sigma-Aldrich). After dehydration, sections were mounted in Pertex (Histolab) and imaged using the Nanozoomer-XR Digital slide Scanner C12000-01 (Hamamatsu).

DNA replication assay, EdU labelling

Cells were treated with 10 µM 5-ethynyl-2'-deoxyuridine (EdU; LifeTechnologies) for the indicated time, harvested, washed once with cold PBS, resuspended in 300µL cold PBS and fixed with 700µL ice-cold 100% ethanol. Click reaction was performed according to the manufacturer instructions (Click-iT™ Plus EdU Alexa Fluor™ 647 Flow Cytometry Assay Kit; Invitrogen) and cells were analysed by flow-cytometry (BD FACSCanto II). FlowJo® software was used for analysis.

Mammosphere assay

The mammosphere formation assay was performed as previously described [START_REF] Shaw | A detailed mammosphere assay protocol for the quantification of breast stem cell activity[END_REF] . Briefly, 500 cells were plated per well in a low-adherence 96-well plate coated with poly-2-hydroxyethylmethacrylate (poly-Hema). After 7 days in culture (37°C, 5% CO2), images of formed mammospheres were acquired and counted using automated high-content microscopy analysis (Cellomics, Thermo).

Aldehyde Dehydrogenase 1 (ALDH1) activity

ALDH1 enzymatic activity was determined using the ALDEFLUOR kit (Stem Cell Technologies) according to the manufacturer instructions. For each sample, half the cell/substrate mixture was treated with diethylaminobenzaldehyde (DEAB; ALDH inhibitor). ALDEFLUOR/DEAB treated cells were used to define negative gates. FACS was performed with ≥10 5 cells.

Xenografts

Animals were housed in the animal facility of IGMM and were maintained in a pathogen-free environment and fed ad libitum.

To generate primary tumours, 10 6 cells (4T1) or 3x10 6 cells (MDA-MB-231) of log-phase viable 'mouse pathogen-free' (Test: IMPACT1, Iddex) were implanted into the fourth inguinal mammary gland (in 50 µl PBS (4T1) or 200 µl PBS (MDA-MB-231)).

Primary tumour volume was measured every week by electronic calliper using the formula "p/6*S 2 (Smaller radius)*L (Larger radius)".

At the end of the experiment, following sacrifice, primary tumours were excised and fixed over-night in neutral buffered formalin (10%) before paraffin embedding (see above). IHC analysis of Ki-67 expression of the different tumour tissue sections was conducted as described above.

Visualisation of lung metastases

Dissected lungs were stained with 15% India Ink diluted in distilled water, and subsequently washed with 5 ml Fekete's solution (40 ml glacial acid acetic, 80 ml formalin, 580 ml ethanol 100%, 200 ml water). A binocular microscope connected to a digital camera was used to visualise and count the metastatic nodules.

Automated drug library screen

We performed an initial screen of all 1,280 FDA-approved drugs in the Prestwick Chemical Library (Prestwick Chemical, Illkirch-Graffenstaden, France) at 10 μM in white clear-bottom 96-well plates. Briefly, we prepared seeding solutions at a density of 2 × 10 5 cells/mL in DMEM complete medium (10%FBS), and dispensed 100 μL into 96-well plates using a Multidrop Combi Dispenser (Thermo Scientific™). Next, we prepared 1x treatment solutions of the Prestwick compounds in DMEM complete medium at a concentration of 10 μM using a Tecan EVO200 robotic liquid handling system (Tecan Trading AG). We removed medium from the pre-seeded 96-well plates and we dispensed 100 μL of 1x treatment solutions using the Tecan robot. We incubated plates at 37°C, 5% CO2 for 48 h in an automated incubator (Cytomat, Thermo Scientific™) associated with the Tecan robot. After treatment, cell survival was determined using the CellTiter-Glo® Luminescent Cell Viability Assay (Promega Corporation) in accordance with the manufacturer's instructions. Luminescence signal was automatically measured with a Tecan Infinity F500 microplate reader (Tecan Trading AG). "Hits" were identified applying the Z-score statistical method (see statistical analysis section). The same method was used for subsequent dose-response experiments on selected "hits".

Induction of anemia with PHZ

Anemia was induced in adult Mki67 2nt∆/2nt∆ mice and littermate controls (Mki67 +/2nt∆ ) by injection of 40 mg/kg phenylhydrazine (PHZ) on days 0, 1, and 3. Animals were sacrificed on day 5 and blood, spleen and bone marrow were collected. Hematocrit was measured as previously described [START_REF] Oburoglu | Glucose and glutamine metabolism regulate human hematopoietic stem cell lineage specification[END_REF] . Cell suspensions were generated and immunophenotyping performed by flow cytometry.

Immunophenotyping and flow cytometry analyses

Cells isolated from peripheral lymph nodes tumor (draining and non-draining for tumorbearing mice) as well as spleen and bone marrow, were stained with Sytox blue or Live/dead fixable viability dye (Life Technologies and eBioscience, respectively) together with the appropriate conjugated anti-CD3, CD45, CD62L, CD4, CD8, CD44, CD25, F4/80, CD19, B220, NK1.1, Gr1, CD11b, CD11c, Ter119, CD71 and Foxp3 antibodies (eBioscience/ThermoFisher or Becton Dickinson, San Diego, CA). Intracellular staining for Foxp3 was performed using the eBioscience Fixation/Permeabilization kit.

Cells were analysed on a FACS Fortessa (BD Biosciences) flow cytometer. Data analyses were performed using FlowJo Mac v.10 (Tree Star) or DIVA (Becton Dickinson) software.

Prior to intracellular cytokine stainings, cells were activated with PMA (Sigma-Aldrich; 100 ng/ml)/ Ionomycin (Sigma-Aldrich; 1ug/ml) in the presence of brefeldin A (Sigma-Aldrich; 10ug/ml) for 3.5-4h at 37 o C. Cell surface staining was performed, after which cells were fixed and permeabilised using a fixation/permeabilization kit (BD Biosciences or eBioscience) followed by intracellular cytokine staining. PCR primers used in this study.

Antibodies used for immunophenotying

(media were changed every 2 days). Cells were then fixed (4% formaldehyde) and stained with 0.5% (w/v) crystal violet to visualise the colonies formed.

RNA sequencing library prep

Total RNA was extracted using Trizol (Life Technologies) following manufacturer's instructions from wild type and two clones of 4T1 Ki-67 knockout cell lines. RNA integrity was analysed on Agilent 2100 bioanalyzer. For library preparation, cDNA synthesis was performed on rRNA-depleted samples using the TruSeq Stranded Total RNA Library Preparation (RS-122-2301). All sequencing libraries were prepared in two or three biological replicates. Indexed cDNA libraries were sequenced by MGX (Montpellier) on Illumina HiSeq2000 with a single 50 bp read and a 10 bp index read.

Sequencing of cDNA libraries and data processing

FastQC was used to perform quality control of the sequencing. Using the tool STAR 2.6.0a(2), all the reads that passed the quality control were aligned to the mouse reference genome (GRCm38.p6) and the counts per gene were quantified. The release 93 of the Ensembl mouse genome annotations were used for establishing the coordinates of each gene and their transcripts. Differential expression analysis was performed in R using the DESeq2(2) library embedded in an in-house script. After normalization of the read counts per gene, a negative binomial generalised linear model was fitted considering single factor design for assessing the differential expression between Mki67 knockout and wild-type samples. Gene set enrichment analysis of the 4T1 Mki67 -/-cell line vs WT cell line was performed using the javaGSEA(3) desktop application with a log-fold-change pre-ranked gene list.

Gene set enrichment for transcription factors.

The gene set enrichment was performed over the ENCODE and ChEA Consensus TFs from ChIP-X gene set, which contains consensus target genes for transcriptions factors present in ENCODE and ChEA databases. The p value was computed with the Fisher Exact test and then adjusted for multiple hypotesis testing in order to obtain the FDR (false discovery rate) adjusted p-value.

MHC class I expression analysis

The MHC class I expression analysis was performed as previously described [START_REF] Charni | Oxidative phosphorylation induces de novo expression of the MHC class I in tumor cells through the ERK5 pathway[END_REF] . 4T1 CTRL and Mki67 -/-cells were incubated with anti-H2D d -FITC, anti-H2K d -PE or control isotypes, and

  4T1 cells were provided by Robert Hipskind (IGMM, Montpellier); MDA-MB-231 cells were obtained from SIRIC, Montpellier. NIH 3T3, 4T1, MDA-MB-231 and S3 HeLa cells were grown in Dulbecco modified Eagle medium (DMEM -high glucose, pyruvate, GlutaMAX -Gibco® Life LifeTechnologies) supplemented with 10% foetal bovine serum (SIGMA or DUTSCHER). Cells were grown under standard conditions at 37°C in humidified incubator containing 5% CO2.

Acknowledgements

We thank D. Grimanelli for help with transcriptome analysis, and P. Jay, D. Santamaria, M.E. Hochberg and M. Serrano for comments on the manuscript. K.M and M.S. were funded by the Ligue Nationale Contre le Cancer (LNCC); P.S. and K.M. received funding from Worldwide Cancer Research (WWCR). D.F. and L.K. are Inserm employees. This work was initiated and finalised with support from the LNCC and continued with support from Worldwide Cancer Research (WWCR) and the French National Cancer Institute (INCa). The chemical library screen relied on support provided by the Programme Opérationnel FEDER-FSE 2014-2020 Languedoc Roussillon.

Data availability

All RNA-seq raw data will be deposited in GEO and will be publicly available prior to publication of the manuscript.

Competing interests

The authors declare that they have no competing interests. control or H-Ras G12V expressing retroviruses. After verification of Ras G12V expression, cells 186 were seeded at 10 5 cells/well (6 well-plate) in triplicate and allowed to grow for 2-weeks

Author


Rafael Ferreira Da Silva

Henri Casanova
email: henric@hawaii.edu

Ryan Tanaka
email: ryanyt@hawaii.edu

Frédéric Suter
email: frederic.suter@cc.in2p3.fr

Bridging Concepts and Practice in eScience via Simulation-driven Engineering

Keywords: CyberInfrastrucutre Development, Simulation Accuracy, Reproducible Research, Distributed Computing Experimental simulation

The CyberInfrastructure (CI) has been the object of intensive research and development in the last decade, resulting in a rich set of abstractions and interoperable software implementations that are used in production today for supporting ongoing and breakthrough scientific discoveries. A key challenge is the development of tools and application execution frameworks that are robust in current and emerging CI configurations, and that can anticipate the needs of upcoming CI applications. This paper presents WRENCH, a framework that enables simulationdriven engineering for evaluating and developing CI application execution frameworks. WRENCH provides a set of highlevel simulation abstractions that serve as building blocks for developing custom simulators. These abstractions rely on the scalable and accurate simulation models that are provided by the SimGrid simulation framework. Consequently, WRENCH makes it possible to build, with minimum software development effort, simulators that that can accurately and scalably simulate a wide spectrum of large and complex CI scenarios. These simulators can then be used to evaluate and/or compare alternate platform, system, and algorithm designs, so as to drive the development of CI solutions for current and emerging applications.

I. INTRODUCTION

An impediment to the advancement of CyberInfrastratructure (CI), and of distributed computing in general, is the disconnect between theoretical and practical works [START_REF] Brooker | The space between theory and practice in distributed systems[END_REF]. There are occasional success stories in which solid theoretical results provide the foundations for improved, or even near-optimal, practice. However, in the vast majority of the cases, theoreticians produce results that are never used by practitioners, and conversely practitioners use approaches that may be vastly suboptimal because they are not informed by any theory. One of the reasons for this disconnect is that theoretical work must be done using formally defined models of computation. Ideally, these models are complete enough to be relevant to practice, but simple enough that obtaining theoretical results (e.g., optimality results, complexity bounds) is tractable. As target hardware/software infrastructures and application workloads become more complex, the assumptions embedded in theoretical models often break down in practical settings. These assumptions pertain to the nature of the infrastructure and the application workload, but also to the knowledge available thereof. For instance, a theoretical framework could assume a fully-connected network with no contention and complete and accurate knowledge about the size of intermediate data files produced by an application, while in practice the network has a topology that is subject to contention and only coarse statistical characterizations of data file sizes are known. Accounting for network contention and/or stochastic data file sizes could, however, make the development of theoretical results that would be useful in practice much more challenging, if not intractable.

The above leads to a situation in which theoreticians may say "accounting for these details makes our work impossible" and practitioners may say "if your work does not account for these details then we cannot use it." It is not realistic to expect that theoreticians will somehow become able to obtain solid results when working with drastically more complex models in which all assumptions are realistic. Conversely, it is not realistic to expect that practitioners will use theoretical results hoping that these results might prove useful in spite of unrealistic assumptions. The latter is because incorporating theoretical results in software infrastructures often requires large software design/development efforts. Yet, it is not the case that theoretical work is useful only if all the underlying assumptions about the hardware/software infrastructure and application workloads are completely realistic. Unrealistic assumptions will likely cause the effectiveness of theoretical results to degrade when used in practice. However, the magnitude of these degradations may be small enough to still warrant the use of theoretical results. Or, their magnitude may be so large that new theoretical approaches are needed if practice is to be impacted. We claim that in order to bridge the theory/practice disconnect these degradations must be quantified systematically while developing theoretical results.

In this paper, we discuss our experience using simulationdriven engineering (see Figure 1) for bridging theoretical and practical aspects of CyberInfrastratructure (CI) development.

To this end, we introduce the WRENCH project [START_REF] Casanova | WRENCH: A Framework for Simulating Workflow Management Systems[END_REF], [START_REF]WRENCH Project[END_REF], a CI simulation framework that provides high-level simulation abstractions for building accurate and scalable full-fledged simulators of CI scenarios with minimal software development efforts. We then briefly describe two use cases in which WRENCH was used for implementing simulators of production application execution frameworks. These uses cases demonstrate the ease-of-development, accuracy, and scalability of simulators developed with WRENCH. They also demonstrate how simulation makes it possible to explore emerging CI capabilities. Finally, we also explain how WRENCH supports innovative avenues for CI education.

II. MOTIVATION AND BACKGROUND

Simulation-driven CI engineering is preconditioned on the ability to simulate CI execution scenarios scalably (i.e., running quickly on a standard laptop computer or small server) and accurately (i.e., representative of real-world workload executions on real-world deployments). To this end, we build on the existing SimGrid simulation framework [START_REF] Casanova | Versatile, scalable, and accurate simulation of distributed applications and platforms[END_REF], [START_REF]The SimGrid Project[END_REF]. SimGrid is open source, freely available, has been stable for many years, is actively developed, has a large user community, and has been used successfully in many distributed computing domains (cluster, peer-to-peer, grid, cloud, volunteer computing, etc.). Importantly, SimGrid has also been the object of thorough invalidation and validation studies [START_REF] Velho | On the validity of flow-level TCP network models for grid and cloud simulations[END_REF], and its simulation models have been shown to provide large accuracy and/or scalability advantages over competing simulation frameworks [START_REF] Casanova | Versatile, scalable, and accurate simulation of distributed applications and platforms[END_REF]. As a result, accurate SimGrid simulations execute in seconds or minutes on a standard laptop computer.

One significant drawback of SimGrid, especially for fullfledged CI simulations, is that its simulation abstractions are too low-level. This drawback was discussed in [START_REF] Kecskemeti | Fostering energyawareness in simulations behind scientific workflow management systems[END_REF], in which the authors conduct a critical analysis of the state-of-the-art distributed computing simulation frameworks. They observe that many popular simulation frameworks employ inaccurate simulation models, which had already been reported in [START_REF] Casanova | Versatile, scalable, and accurate simulation of distributed applications and platforms[END_REF], and acknowledge that SimGrid does provide accurate and scalable simulation capabilities. However, they also observe that using it to implement a simulator of a complex system, such as CI workloads executed on CI deployments, would be extremely labor-intensive.

Given the above, we need a CI simulation framework built on top of SimGrid, so that simulations can be accurate and scalable, but that exposes convenient, reusable, and high-level simulation abstractions, so that implementing simulators of CI scenarios can be done with minimal software engineering efforts. To fill this gap, the WRENCH project [START_REF]WRENCH Project[END_REF] emerged as a framework that provides accurate, scalable, and easy-to-use high-level CI abstractions for building simulators of workload executions on production CI deployments. For instance, in order to simulate the example system depicted in Figure 2, one would have to implement all communication and computing behavior of each process instantiated by the components. In SimGrid, simulating such system is labor-intensive and error-prone, requiring the development of thousands of lines of code. By contrast, WRENCH's philosophy is to expose high-level simulation abstractions to provide reusable building blocks for developing custom simulators with minimum effort. Such abstractions represent implementations of simulated CI services that assemble all software pieces (e.g., processes, communication, etc.) necessary for mimicking services behaviors. It is thus straightforward for CI developers to build WRENCH simulators for driving the development of more efficient system designs for CI software, and for CI researchers to build WRENCH simulators for driving the development of efficient algorithms that are at the core of such CI software.

III. THE WRENCH SIMULATION FRAMEWORK

WRENCH is an open-source C++ library for developing CyberInfrastructure simulators. Its set of core services are composed of two layers as follows:

• Simulation Core: All necessary simulation models and base abstractions (computing, communicating, storing), provided by SimGrid. • Simulated Core CI Services: Abstractions for simulated CI components that can be used by an application execution framework to execute computational workloads (compute services, storage services, network proximity services, data location services, etc.). The Simulated Core CI services layer provides highlevel simulation abstractions of commonplace CI services. WRENCH currently provides the following set of simulated CI services (Version 1.4 was released in April 2019):

• Compute Services: These services provide mechanisms for executing application tasks, which entail I/O and computation. These include bare-metal servers, cloud platforms, virtualized cluster platforms, and batch-scheduled clusters.

• Storage Services: These services provide mechanisms to store application files, which can then be accessed in reading/writing by the compute services when executing tasks that read/write files. • File Registry Services: These services, often known as replica catalogs, are simply databases of key-value pairs of the storage services on which replicas of files are available. They are used during application execution to decide where input files for tasks can be acquired. • Network Proximity Services: These services monitor the network and maintain a database of host-to-host network distances. This database can be queried by the CI system to make informed decisions, e.g., to pick from which Fig. 2. Example of a CI system that can be simulated using WRENCH. High-level simulation abstractions provided as WRENCH simulated core CI services can be customized and combined to build complex, heterogeneous CI systems.

storage service a file should be retrieved so as to reduce communication time. Typically, network distances are estimated based on round-trip-times between hosts. • Workflow Management Systems (WMSs): A workflow management system provides the mechanisms for executing workflow applications, including decision-making for optimizing various objectives (the most common one is to minimize workflow execution time). WRENCH does not provide a WMS implementation as part of its core components. Instead it provides abstractions for building custom WMS components.

WRENCH service implementations are all parameterizable (e.g., underlying algorithms, various overheads, message payloads, etc.), which allows developers to calibrate the instantiation of the simulated services so that they behave similarly to actual CI services of interest. The ability to define such parameterizable services is key for developing accurate CI simulators, from which research products evaluated via experimental simulation could be seamlessly integrated into actual CI platforms (see Figure 1). All aforementioned services and capabilities are made available through the WRENCH Developer API. This API is designed to ease the development of complex (simulated) systems comprised of distributed components that interact both synchronously and asynchronously, such as current and emerging CI systems.

In addition to the Developer's API, WRENCH also provides a User API, which makes it possible to build a full-fledged simulator with only a few lines of code. This API provides the mechanisms to control simulation execution (platform configuration, services instantiations, simulation launching, etc.) and analyze simulation outcomes. For an exhaustive description of the WRENCH architecture, its functionalities, and APIs, we refer the reader to the latest WRENCH research article [START_REF] Casanova | WRENCH: A Framework for Simulating Workflow Management Systems[END_REF] and the project's online documentation [START_REF]WRENCH Project[END_REF].

IV. WRENCH'S IMPACT ON CI RESEARCH, DEVELOPMENT, AND EDUCATION

Although WRENCH is a young project and its first stable release was made available just over one year ago, the framework has already impacted CI research, development, and education. In the last year, we have delivered four WRENCH's stable releases, which were downloaded over 300 times, either directly from our GitHub repository1 or via our Docker Hub repository 2 .

WRENCH has already enabled the development of two simulators of two production application execution frameworks [START_REF]The WRENCH Pegasus Simulator[END_REF], [START_REF]The WRENCH WorkQueue Simulator[END_REF] for supporting the study of energy-efficiency for I/O-intensive workflow applications [START_REF] Ferreira Da Silva | Accurately Simulating Energy Consumption of I/Ointensive Scientific Workflows[END_REF], and the study of simulation accuracy and scalability [START_REF] Casanova | WRENCH: A Framework for Simulating Workflow Management Systems[END_REF]. WRENCH has also gained overseas attention, and received contributions from users in France and Ivory Coast, who are conducting research on workflow scheduling. In the context of CI development, a WRENCH-enabled Pegasus simulator is being used to evaluate novel algorithms for energy-efficiency, workflow data footprint constraints, and cost estimation for running largescale workflows on heterogeneous computing platforms. In the context of education, we have implemented a small set of simulation-driven pedagogic modules. The modules are available on-line 3 and provide students with simulation-driven interactive learning opportunities. They target essential parallel and distributed computing learning objectives in the specific context of scientific workflow applications running on baremetal hardware resources.

A. Simulation Accuracy and Scalability

Two major concerns regarding simulation are accuracy (the ability to capture the behavior of a real-world system with as little bias as possible) and scalability (the ability to simulate large systems with as few CPU cycles and bytes of RAM as possible). By leveraging SimGrid's accurate models [START_REF] Velho | On the validity of flow-level TCP network models for grid and cloud simulations[END_REF] and their scalable implementations, WRENCH simulators can yield nearly identical behaviors when compared to actual CI systems, provided that one instantiates correctly the configurable parameters of the simulation models, a process typically referred to as "simulation calibration." The current practice of simulation calibration in our field, based on what is reported in the literature, is ad-hoc, labor-intensive, and thus often poorly realized and documented (e.g., networking research [START_REF] Velho | On the validity of flow-level TCP network models for grid and cloud simulations[END_REF], [START_REF] Andel | On the credibility of manet simulations[END_REF]). Automating such process is challenging and still an open question. As part of the WRENCH project, we are studying mechanisms to develop a solid automated calibration approach.

We have recently implemented realistic simulators of two state-of-the-art application execution frameworks, Pegasus [START_REF] Deelman | Pegasus, a workflow management system for science automation[END_REF] and WorkQueue [START_REF] Yu | Harnessing parallelism in multicore clusters with the all-pairs, wavefront, and makeflow abstractions[END_REF]. We have calibrated simulation parameters manually by analyzing and comparing simulated and real-world execution event traces. In addition to regular computing tasks, the WRENCH-enabled Pegasus simulator also accounts for "auxiliary" tasks added by the workflow system, i.e. data stage in/out, cleanup tasks, and data registration.

Figure 3 shows real-world and simulated ECDFs for sample runs of two real-world scientific applications with task completion date ECDFs. We observe that the simulated ECDFs ("wrench") track the real-world ECDFs ("pegasus" and "workqueue") closely. Therefore, we argue that research products prototyped in the simulators (e.g., envisioned enhancements to a target CI systems) that lead to good results in simulation will also, when implemented back into actual software (e.g., the actual target CI systems), lead to good results in practice. Although our simulation results yield good accuracy, we underline that such accuracy may decrease when simulating a different platforms, unless a recalibration of the simulator is performed. However, we would expect that many components of the simulation would not need recalibration (e.g., those simulation parameters that correspond to the behavior/implementation of the CI software being simulated, such as message sizes, timeout threshold, various delay values).

Detailed evaluation of WRENCH-enabled simulator's accuracy can be found in [START_REF] Casanova | WRENCH: A Framework for Simulating Workflow Management Systems[END_REF]. In that study, we have also evaluated simulation scalability. For this purpose, we have conducted simulation runs with workloads comprising 10K+ jobs running in a simulated cloud platform. Experimental results show that such large-scale, complex simulations ran under 13 minutes on a standard laptop computer. As a result, large numbers of large-scale simulations can be executed so as to identify performance, scalability, and correctness issues in the research products before production-level efforts and resources are committed to the implementation of the research product in actual production software.

All these simulators were implemented using often less 700 lines of code (including code for parsing simulatorspecific configuration files), whereas if using SimGrid directly it would require thousands of lines of code. For example, in [START_REF] Chai | Modeling distributed platforms from application traces for realistic file transfer simulation[END_REF] a specific simulator of a simple fork-join workflow was implemented directly on top of SimGrid for studying the impact of file transfers on performance. This simulator consists of more than a thousand lines of code and only offers a minuscule fraction of the simulation capabilities provided by WRENCH. Most of the simulator's code pertains to the implementation of control message exchanges between the different processes involved in the simulated system and to the different interaction loops of these processes. Implementing these message exchanges and interactions is a tedious and error-prone process when using the low-level SimGrid API (and very few users would commit to the required effort). By contrast, WRENCH completely hides the implementation of these necessary aspects of a distributed system simulator, which are implemented inside the WRENCH core. Instead, it exposes to users a higher level and user-friendly interface.

B. Energy-aware Computing

In a recent work [START_REF] Ferreira Da Silva | Accurately Simulating Energy Consumption of I/Ointensive Scientific Workflows[END_REF], we have leveraged the WRENCHenabled Pegasus simulator to investigate the impact of resource utilization and I/O operations on the energy usage, as well as the impact of executing multiple tasks concurrently on multisocket, multi-core compute nodes. Our simulator allowed us to draw direct comparisons between real-world and modeled power and energy consumption. Figure 4 shows the simulated power and energy consumption measurements as well as with the traditional model (from the literature). We find that our model has high accuracy when compared to real-world executions. Furthermore, our model improves accuracy by about two orders of magnitude when compared to the traditional models used in the energy-efficient scheduling literature.

C. Pedagogic Modules

To support simulation-driven computing education, we have implemented a few simulation-driven pedagogic modules supported by WRENCH-based simulators. All these simulators were implemented using often less than one hundred lines of code. Modules are packaged as Docker containers that expose q q q q q q q q q q q q 140 160 180 200 q estimation real wrench q q q q q q q q q q q q 0.1 0.2 an interactive Web application through which students can perform various hands-on activities. Each activity entails running, through the Web application, a simulator with different input parameters. Students run these simulations to explore different execution options for different application and/or platform configuration scenarios. Students are presented with simulation output that includes visualizations of the simulated execution, such as resource utilization metrics, event timelines, and interactive Gantt charts (see Figure 5). Students must analyze this output and draw a range of conclusions that lead them to achieve a well-defined set of learning objectives. These modules have already been used in the classroom, in an undergraduate course at the University of Hawai'i in Spring 2019 [START_REF] Tanaka | Teaching Parallel and Distributed Computing Concepts in Simulation with WRENCH[END_REF].

V. CONCLUSION

In this paper, we have introduced WRENCH, a framework for enabling simulation-driven engineering for evaluating and developing CI application execution frameworks. We have reported on how WRENCH has aided to bridge concepts and practice in eScience via simulation. We have described the overall framework capabilities and available services, and briefly exposed WRENCH's impact on (i) research and development, through the implementation of two state-of-the-art application execution frameworks and a case study on energyefficiency; and (ii) education, via the development of online self-contained pedagogic modules.

Although relying on simulation is key for advancing stateof-the-art CI software, attempting to do so from scratch, i.e., implementing a full-fledged simulation based on base models of the infrastructure and application workloads is not worthwhile. It is too labor-intensive and in practice results in the implementer opting for simplifications that translate in loss of simulation accuracy. Instead, relying on simulation frameworks, such as SimGrid and WRENCH, allows users to focus on their own research, development, and/or teaching interests while keeping the gap between concepts and practice as narrow as possible.

An interesting future direction is that of automated simulation calibration. The "simulation calibration" question is crucial to establishing a solid simulation-driven experimental science approach for CI research, development, and education. Yet this question is poorly understood and current calibration practices are both inadequate and labor-intensive. This issue is not confined to WRENCH, but is faced by all distributed system simulators. An additional challenge is that of the data necessary for performing calibration is often not available to the community-e.g., execution and performance traces are scarce and fragmented.

Fig. 1 .

 1 Fig. 1. Simulation-driven engineering life cycle.

Fig. 3 .

 3 Fig.3. Empirical cumulative distribution function of task completion times for sample real-world ("pegasus" and "workqueue") and simulated ("wrench") executions.

Fig. 4 .

 4 Fig.4. Comparison of power (left) and energy (right) consumption measurements for a real-world application ("real") using a well-known model from the literature ("estimation") and our WRENCH model ("wrench").

Fig. 5 .

 5 Fig. 5. Gantt chart of simulated workload task executions for a scientific workflow running on a distributed platform.

https://github.com/wrench-project/wrench

https://hub.docker.com/r/wrenchproject/wrench

http://wrench-project.org/wrench-pedagogic-modules

ACKNOWLEDGMENTS

This work is funded by NSF contracts #1642369 and #1642335; by CNRS under grant #PICS07239; and partly funded by NSF contracts #1923539 and #1923621: "Cyber-Training: Implementation: Small: Integrating core CI literacy and skills into university curricula via simulation-driven activities". We thank Martin Quinson, Arnaud Legrand, and Pierre-Franc ¸ois Dutot for their valuable help.