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  1. Author Response:

    Reviewer #2 (Public Review):

    Chan et al set out to assess the transcriptomic (bulk and single cell), proteomic and metabolic changes that occur as primary WI38 human lung fibroblasts progress from early proliferative stages through to replicative senescence (RS) in vitro, as well as using ATAC-seq to assess changes in chromatin accessibility in senescence. The authors compare findings from RS in primary WI38 cells with immortalised cells of the same lineage expressing hTERT, cells that are quiescent through contact inhibition and cells with radiation-induced DNA damage. The data presented confirm findings in the literature from individual -omics studies; what makes this work novel and provides new insight is the combination of a range of -omics techniques, including time resolved scRNAseq, to provide deep molecular profiling across the cell lifespan. This indicates that senescence is a process of gradual onset throughout the proliferative lifecourse, and that a few key pathways are strongly associated with (and probably drive) replicative senescence, particularly a fibroblast to mesenchymal transition (FMT) akin to the epithelial-mesenchymal transition (EMT) observed in cancer development. The identification of changes that occur at different stages along the senescence trajectory is important in that it may allow tailored interventions. Moreover, their finding of nicotinamide N-methyltransferase (NNMT) upregulation in senescence provides an explanation for the greater chromatin accessibility observed in senescence as well as NAD+ depletion.

    The reliance on -omics techniques is also to some extent a weakness - no attempt is made to orthogonally validate the findings e.g. by qRT-PCR for transcripts, or western blotting for proteins identified to change on senescence. While the data on replicative senescence appear mostly robust, there are potential weaknesses in comparisons with DNA damage-induced senescence, as the early time points analysed may reflect more the acute DNA damage response rather than senescence. While it is sensible to conduct the full range of analyses on the same cell line to identify degree of concordance between gene expression control at RNA and protein levels, and correlate with metabolic consequences, there is only a cursory attempt to compare with other senescence models (a single published dataset on oxidative stress induced senescence in astrocytes) so the findings are at this stage confined to senescence in the WI38 cell line studied, though it is likely they will have much wider applicability.

    We apologize for the lack of clarity in communicating that we did in fact compare our data to a model composed of multiple replicative senescence studies from different labs and different fibroblast cell lines compiled by Judith Campisis’s lab [Hernandez-Segura et al., 2017]. This comparison is the subject of what is now manuscript Figure 1D (1C previously). We report a very high correlation (r2=0.92) between our data and a large compendium of replicative senescence data. We apologize that this was not clear and have added clarifying text.

    The comparison with oxidative stress induced senescence in astrocytes was used specifically to show that we observe similar putative regulatory TFs enriched in a senescence context far removed from replicative senescence in WI38 fibroblasts to suggest the possibility of wider applicability outside of WI-38 cells as mentioned in discussion. Although interesting and suggestive, this is outside the main thrust of the paper which was to generate a high resolution molecular description of replicative senescence in WI-38 cells.

    A larger, comprehensive analysis to determine to what extent the TFs we highlight could be master regulators of senescence across many different senescence models and tissue cell lines is useful for the field, but it is outside the scope of this paper given the size of the literature. That analysis would be a publication in its own right similar to Hernandez-Segura et. al. If the reviewer finds the astrocyte comparison misleading or unhelpful we are happy to remove.

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  2. Evaluation Summary:

    This manuscript presents a well-done integrative analysis of data from many genome-wide technologies for the study of replicative senescence, contrasting the data to non-senescence and acute senescence controls. The time-course study design and the combinatorial analyses have revealed many interesting features of senescence that were previously unknown. Data mining by scientists in the future promises to unlock other aspects of senescence biology and hence this study serves as a great resource to the community. This paper and resource will be invaluable not only for researchers specifically studying the molecular biology of cell senescence but should also be more broadly relevant for researchers studying aging, inflamm-aging, cancer, regeneration, and other fields where senescence plays a role.

    (This preprint has been reviewed by eLife. We include the public reviews from the reviewers here; the authors also receive private feedback with suggested changes to the manuscript. Reviewer #2 and Reviewer #3 agreed to share their name with the authors.)

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  3. Reviewer #1 (Public Review):

    The authors highlight a number of interesting and important findings relevant for any project related to senescence. For example, they demonstrate that a senescent signature is active in single cells regardless of the cell cycle state they are in (S, G2M, or G1), irrespective of the passage doubling levels, and after removing "bona fide" senescent and late PDL cells from the analysis. Moreover, senescence is accompanied by a) metabolic changes that include increased oxidative phosphorylation, glycolytic shunts, and fatty acid oxidation and b) proteomic changes such as increased nicotinamide N-methyltransferase (NNMT) activity, which plays roles in SAM and NAM metabolism. Finally, their pseudotime analysis shows that cell cycle genes, chromatin remodeling, and TGFB signaling with inflammation demarcate early pseudotime, intermediate pseudotime, and late pseudotime states.

    The datasets presented will be a fantastic resource to better understand the molecular choreography of cellular senescence. However, there are concerns with the robustness of the statistical analysis (e.g. apparent lack of multiple hypothesis correction, use of fold change thresholding, etc.) and a scarcity of key methodological details, which need to be corrected to determine whether discussed signatures are retained if these analytical issues are corrected.

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  4. Reviewer #2 (Public Review):

    Chan et al set out to assess the transcriptomic (bulk and single cell), proteomic and metabolic changes that occur as primary WI38 human lung fibroblasts progress from early proliferative stages through to replicative senescence (RS) in vitro, as well as using ATAC-seq to assess changes in chromatin accessibility in senescence. The authors compare findings from RS in primary WI38 cells with immortalised cells of the same lineage expressing hTERT, cells that are quiescent through contact inhibition and cells with radiation-induced DNA damage. The data presented confirm findings in the literature from individual -omics studies; what makes this work novel and provides new insight is the combination of a range of -omics techniques, including time resolved scRNAseq, to provide deep molecular profiling across the cell lifespan. This indicates that senescence is a process of gradual onset throughout the proliferative lifecourse, and that a few key pathways are strongly associated with (and probably drive) replicative senescence, particularly a fibroblast to mesenchymal transition (FMT) akin to the epithelial-mesenchymal transition (EMT) observed in cancer development. The identification of changes that occur at different stages along the senescence trajectory is important in that it may allow tailored interventions. Moreover, their finding of nicotinamide N-methyltransferase (NNMT) upregulation in senescence provides an explanation for the greater chromatin accessibility observed in senescence as well as NAD+ depletion.

    The reliance on -omics techniques is also to some extent a weakness - no attempt is made to orthogonally validate the findings e.g. by qRT-PCR for transcripts, or western blotting for proteins identified to change on senescence. While the data on replicative senescence appear mostly robust, there are potential weaknesses in comparisons with DNA damage-induced senescence, as the early time points analysed may reflect more the acute DNA damage response rather than senescence. While it is sensible to conduct the full range of analyses on the same cell line to identify degree of concordance between gene expression control at RNA and protein levels, and correlate with metabolic consequences, there is only a cursory attempt to compare with other senescence models (a single published dataset on oxidative stress induced senescence in astrocytes) so the findings are at this stage confined to senescence in the WI38 cell line studied, though it is likely they will have much wider applicability.

    The findings are important in providing a large new body of data on cell senescence and are highly relevant in geroscience to guide research into new treatments for age-related diseases that are associated with senescence, particularly fibrosis and inflammatory states, and possibly also cancer.

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  5. Reviewer #3 (Public Review):

    In this manuscript, Chan et al applied multi-omic technologies to the Hayflick replicative senescence (RS) model in WI-38 cells to reveal some key known and novel features of the senescence induction process. For example, in terms of novelty, (1) they found RS shares some molecular similarities with epithelial to mesenchymal transition (EMT) including a similar metabolomic profile, (2) that Nicotinamide N-methyltransferase (NNMT) is a potential upstream regulator of heterochromatin loss and (3) senescent WI-38 cells resemble myofibroblasts and this transition of fibroblasts to myofibroblasts is driven by TEAD1/YAP1 and TGFβ2 signaling. Known (reproduced) findings were loss of lamina-associated heterochromatin, downregulation of cell cycle genes, upregulation of senescence genes (for example SASP factors) etc. Additionally, their single-cell transcriptomic analyses reveal that senescence gene expression signatures accrue early and at all stages of cell cycle.

    The integrative analyses of transcriptomic (bulk and single-cell), proteomic, metabolomic and epigenomic analyses performed by the authors and the time-course design of the study is excellent and provides new insights into senescence biology. Particularly, the metabolic rewiring towards fatty acid oxidation and glycolytic shunts, the early upregulation of NNMT and the RS transcription factors are interesting and provide upstream mechanistic targets that can be exploited to delay senescence and its deleterious effects.

    Overall, most of the authors' claims in the manuscript are supported by strong data and sound analyses. However, this is largely an observational study with correlational analyses. Addition of some functional experiments will greatly strengthen the manuscript.

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