Network Analysis Reveals the Molecular Bases of Statin Pleiotropy That Vary with Genetic Background

ABSTRACT Many approved drugs are pleiotropic: for example, statins, whose main cholesterol-lowering activity is complemented by anticancer and prodiabetogenic mechanisms involving poorly characterized genetic interaction networks. We investigated these using the Saccharomyces cerevisiae genetic model, where most genetic interactions known are limited to the statin-sensitive S288C genetic background. We therefore broadened our approach by investigating gene interactions to include two statin-resistant genetic backgrounds: UWOPS87-2421 and Y55. Networks were functionally focused by selection of HMG1 and BTS1 mevalonate pathway genes for detection of genetic interactions. Networks, multilayered by genetic background, were analyzed for key genes using network centrality (degree, betweenness, and closeness), pathway enrichment, functional community modules, and Gene Ontology. Specifically, we found modification genes related to dysregulated endocytosis and autophagic cell death. To translate results to human cells, human orthologues were searched for other drug targets, thus identifying candidates for synergistic anticancer bioactivity. IMPORTANCE Atorvastatin is a highly successful drug prescribed to lower cholesterol and prevent cardiovascular disease in millions of people. Though much of its effect comes from inhibiting a key enzyme in the cholesterol biosynthetic pathway, genes in this pathway interact with genes in other pathways, resulting in 15% of patients suffering painful muscular side effects and 50% having inadequate responses. Such multigenic complexity may be unraveled using gene networks assembled from overlapping pairs of genes that complement each other. We used the unique power of yeast genetics to construct genome-wide networks specific to atorvastatin bioactivity in three genetic backgrounds to represent the genetic variation and varying response to atorvastatin in human individuals. We then used algorithms to identify key genes and their associated FDA-approved drugs in the networks, which resulted in the distinction of drugs that may synergistically enhance the known anticancer activity of atorvastatin.

concentrations selection of atorvastatin in the screening of those isolates among three S.c genetic backgrounds. Since this is the foundation of the whole paper for downstream gene screening and analysis, I suggest illustrate the process and result in detail.

Reviewer #2 (Comments for the Author):
The research presented in this manuscript is very interesting with carefully designed experiments and smooth writing style that appeals not only to specialist but to a broader readers. I have no major comments.
Staff Comments:

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Cintya and his/her colleagues provide a comprehensive analysis study of the atorvastatin pleiotropy effect through high-throughput SGA screening together with downstream gene network analysis. It is interesting in application of the S. cerevisiae genetic analysis model to investigate the potential properties of the atorvastatin.
Since atorvastatin has antifungal activity, the experimental design is reasonable using both statin-sensitive and resistant S. cerevisiae strains for a fast screen. The main concern I have in the article reading is the concentrations selection of atorvastatin in the screening of those isolates among three S.c genetic backgrounds (e.g. described in lines 137-143). Since this is the foundation of the whole paper for downstream gene screening and analysis, I suggest illustrate the process and result in detail. 9. Line 225, which is further supported by the atorvastatin hypersensitivity of the bts1∆ bre5∆ only in S288C (Fig 5). It is essential to Mark the number of degree centrality metrics in three isolates for comparation and consistency of the hypersensitivity measurement result 10. Line 242, remove the space before the bracket.
12. Line 30: Statin treatment induces the unfolded protein response. I did not see any results related to unfolded protein response (UPR) pathways in the whole article.
Indeed the relative result is from the author's previous publication (Busby et al, 2019), rearrange the sentence to clarify. On behalf of our coauthors, we are resubmitting our paper "Network analysis reveals the molecular bases of statin pleiotropy that vary with genetic background" as an Article in Microbiology Spectrum.

School of Biological Sciences
We greatly appreciate the constructive comments by the reviewers. We have taken suggestions by the two reviewers very seriously and have responded to all concerns via the completion of adjustments to the writing and figures of the manuscript. This has very much enhanced the manuscript providing further scientific validation of the pleiotropic effects of the commonly prescribed cholesterol-lowering atorvastatin.
As requested, we assented to all editorial suggestions and incorporated these (highlighted in yellow) in our resubmitted manuscript. Our detailed responses to the individual comments are below.
Thank you and the reviewers for feedback that has undoubtedly improved the manuscript. We look forward to your instructions as to how we can submit high-resolution images of our figures.   (Figs 4 and 5)." 5. Fig 4: The hmg1Δrim15Δ double mutant seems have growth defect especially in S288C background strain. I am wondering whether it is true rim15 affect the drug sensitivity of hmg1Δ.
Our response: The authors acknowledge the Reviewer's concern. While the double deletion hmg1Δ rim15Δ exerts a growth defect on its own, with a more marked effect in S288C, we believe the atorvastatin-induced lethality has to be more than simply an additive effect, especially given that the lethality observed in the treated hmg1Δ rim15Δ came from a 4 M treatment compared to 100 M for rim15Δ and 20 M for hmg1Δ.
While it is possible that this sensitivity is not unique to atorvastatin, the broad function of the RIM15 kinase may well result in hmg1Δ rim15Δ being sensitive to other compounds. Unfortunately, we do not have any data to address this possibility.  figure and figure legend has been amended to highlight the genes.
9. Line 225, which is further supported by the atorvastatin hypersensitivity of the bts1Δ bre5Δ only in S288C (Fig 5). It is essential to Mark the number of degree centrality metrics in three isolates for comparation and consistency of the hypersensitivity measurement result.
Our response: We have included the centrality metrics for S288C in the main text (Line 220). We have also added a sentence  clarifying that BRE5 was not present in the UWOPS87 and Y55 networks.
10. Line 242, remove the space before the bracket.
Our response: We have made this correction.
11. Line 247, remove (Fig 9). Thank you for addressing all the concerns raised by the reviewers.
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