Mechanistic target of rapamycin (mTOR) pathway in Sertoli cells regulates age-dependent changes in sperm DNA methylation.

Over the past several decades, a trend toward delayed childbirth has led to increases in parental age at the time of conception. Sperm epigenome undergoes age-dependent changes increasing risks of adverse conditions in offspring conceived by fathers of advanced age. The mechanism(s) linking paternal age with epigenetic changes in sperm remain unknown. The sperm epigenome is shaped in a compartment protected by the blood-testes barrier (BTB) known to deteriorate with age. Permeability of the BTB is regulated by the balance of two mTOR complexes in Sertoli cells where mTOR complex 1 (mTORC1) promotes the opening of the BTB and mTOR complex 2 (mTORC2) promotes its integrity. We hypothesized that this balance is also responsible for age-dependent changes in the sperm epigenome. To test this hypothesis, we analyzed reproductive outcomes, including sperm DNA methylation in transgenic mice with Sertoli cell-specific suppression of mTORC1 (Rptor KO) or mTORC2 (Rictor KO). mTORC2 suppression accelerated aging of the sperm DNA methylome and resulted in a reproductive phenotype concordant with older age, including decreased testes weight and sperm counts, and increased percent of morphologically abnormal spermatozoa and mitochondrial DNA copy number. Suppression of mTORC1 resulted in the shift of DNA methylome in sperm opposite to the shift associated with physiological aging - sperm DNA methylome rejuvenation and mild changes in sperm parameters. These results demonstrate for the first time that the balance of mTOR complexes in Sertoli cells regulates the rate of sperm epigenetic aging. Thus, mTOR pathway in Sertoli cells may be used as a novel target of therapeutic interventions to rejuvenate the sperm epigenome in advanced-age fathers.

Taurine linked with healthy aging.

Reversing age-associated taurine loss improves mouse longevity and monkey health.

Velcrin-induced selective cleavage of tRNALeu(TAA) by SLFN12 causes cancer cell death.

Velcrin compounds kill cancer cells expressing high levels of phosphodiesterase 3A (PDE3A) and Schlafen family member 12 (SLFN12) by inducing complex formation between these two proteins, but the mechanism of cancer cell killing by the PDE3A-SLFN12 complex is not fully understood. Here, we report that the physiological substrate of SLFN12 RNase is tRNALeu(TAA). SLFN12 selectively digests tRNALeu(TAA), and velcrin treatment promotes the cleavage of tRNALeu(TAA) by inducing PDE3A-SLFN12 complex formation in vitro. We found that distinct sequences in the variable loop and acceptor stem of tRNALeu(TAA) are required for substrate digestion. Velcrin treatment of sensitive cells results in downregulation of tRNALeu(TAA), ribosome pausing at Leu-TTA codons and global inhibition of protein synthesis. Velcrin-induced cleavage of tRNALeu(TAA) by SLFN12 and the concomitant global inhibition of protein synthesis thus define a new mechanism of apoptosis initiation.

Structure of PDE3A-SLFN12 complex reveals requirements for activation of SLFN12 RNase.

DNMDP and related compounds, or velcrins, induce complex formation between the phosphodiesterase PDE3A and the SLFN12 protein, leading to a cytotoxic response in cancer cells that express elevated levels of both proteins. The mechanisms by which velcrins induce complex formation, and how the PDE3A-SLFN12 complex causes cancer cell death, are not fully understood. Here, we show that PDE3A and SLFN12 form a heterotetramer stabilized by binding of DNMDP. Interactions between the C-terminal alpha helix of SLFN12 and residues near the active site of PDE3A are required for complex formation, and are further stabilized by interactions between SLFN12 and DNMDP. Moreover, we demonstrate that SLFN12 is an RNase, that PDE3A binding increases SLFN12 RNase activity, and that SLFN12 RNase activity is required for DNMDP response. This new mechanistic understanding will facilitate development of velcrin compounds into new cancer therapies.

Unbiased approach for the identification of molecular mechanisms sensitive to chemical exposures.

Targeted methods that dominated toxicological research until recently did not allow for screening of all molecular changes involved in toxic response. Therefore, it is difficult to infer if all major mechanisms of toxicity have already been discovered, or if some of them are still overlooked. We used data on 591,084 unique chemical-gene interactions to identify genes and molecular pathways most sensitive to chemical exposures. The list of identified pathways did not change significantly when analyses were done on different subsets of data with non-overlapping lists of chemical compounds indicative that our dataset is saturated enough to provide unbiased results. One of the most important findings of this study is that almost every known molecular mechanism may be affected by chemical exposures. Predictably, xenobiotic metabolism pathways, and mechanisms of cellular response to stress and damage were among the most sensitive. Additionally, we identified highly sensitive molecular pathways, which are not widely recognized as major targets of toxicants, including lipid metabolism pathways, longevity regulation cascade, and cytokine-mediated signaling. These mechanisms are relevant to significant public health problems, such as aging, cancer, metabolic and autoimmune disease. Thus, public health field will benefit from future focus of toxicological research on identified sensitive mechanisms.

Data on chemical-gene interactions and biological categories enriched with genes sensitive to chemical exposures.

A dataset of chemical-gene interactions was created by extracting data from the Comparative Toxicogenomics Database (CTD) with the following filtering criteria: data was extracted only from experiments that used human, rat, or mouse cells/tissues and used high-throughput approaches for gene expression analysis. Genes not present in genomes of all three species were filtered out. The resulting dataset included 591,084 chemical-gene interaction. All chemical compounds in the database were annotated for their major uses. For every gene in the database number of chemical-gene interactions was calculated and used as a metric of gene sensitivity to a variety of chemical exposures. The lists of genes with corresponding numbers of chemical-gene interactions were used in gene-set enrichment analysis (GSEA) to identify potential sensitivity to chemical exposures of molecular pathways in Hallmark, KEGG and Reactome collections. Thus, data presented here represent unbiased and searchable datasets of sensitivity of genes and molecular pathways to a broad range of chemical exposures. As such the data can be used for a diverse range of toxicological and regulatory applications. Approach for the identification of molecular mechanisms sensitive to chemical exposures may inform regulatory toxicology about best toxicity testing strategies. Analysis of sensitivity of genes and molecular pathways to chemical exposures based on these datasets was published in Chemosphere (Suvorov et al., 2021) [1].