Combining stem cell rejuvenation and senescence targeting to synergistically extend lifespan.

Why biological age is a major risk factor for many of the most important human diseases remains mysterious. We know that as organisms age, stem cell pools are exhausted while senescent cells progressively accumulate. Independently, induction of pluripotency via expression of Yamanaka factors (Oct4, Klf4, Sox2, c-Myc; OKSM) and clearance of senescent cells have each been shown to ameliorate cellular and physiological aspects of aging, suggesting that both processes are drivers of organismal aging. But stem cell exhaustion and cellular senescence likely interact in the etiology and progression of age-dependent diseases because both undermine tissue and organ homeostasis in different if not complementary ways. Here, we combine transient cellular reprogramming (stem cell rejuvenation) with targeted removal of senescent cells to test the hypothesis that simultaneously targeting both cell-fate based aging mechanisms will maximize life and health span benefits. We find that OKSM extends lifespan and show that both interventions protect the intestinal stem cell pool, lower inflammation, activate pro-stem cell signaling pathways, and synergistically improve health and lifespan. Our findings suggest that a combination therapy, simultaneously replacing lost stem cells and removing senescent cells, shows synergistic potential for anti-aging treatments. Our finding that transient expression of both is the most effective suggests that drug-based treatments in non-genetically tractable organisms will likely be the most translatable.

A non-canonical Raf function is required for dorsal-ventral patterning during Drosophila embryogenesis.

Proper embryonic development requires directional axes to pattern cells into embryonic structures. In Drosophila, spatially discrete expression of transcription factors determines the anterior to posterior organization of the early embryo, while the Toll and TGFß signalling pathways determine the early dorsal to ventral pattern. Embryonic MAPK/ERK signaling contributes to both anterior to posterior patterning in the terminal regions and to dorsal to ventral patterning during oogenesis and embryonic stages. Here we describe a novel loss of function mutation in the Raf kinase gene, which leads to loss of ventral cell fates as seen through the loss of the ventral furrow, the absence of Dorsal/NFκB nuclear localization, the absence of mesoderm determinants Twist and Snail, and the expansion of TGFß. Gene expression analysis showed cells adopting ectodermal fates much like loss of Toll signaling. Our results combine novel mutants, live imaging, optogenetics and transcriptomics to establish a novel role for Raf, that appears to be independent of the MAPK cascade, in embryonic patterning.

The importance of considering regulatory domains in genome-wide analyses - the nearest gene is often wrong!

The expression of a large number of genes is regulated by regulatory elements that are located far away from their promoters. Identifying which gene is the target of a specific regulatory element or is affected by a non-coding mutation is often accomplished by assigning these regions to the nearest gene in the genome. However, this heuristic ignores key features of genome organisation and gene regulation; in that the genome is partitioned into regulatory domains, which at some loci directly coincide with the span of topologically associated domains (TADs), and that genes are regulated by enhancers located throughout these regions, even across intervening genes. In this review, we examine the results from genome-wide studies using chromosome conformation capture technologies and from those dissecting individual gene regulatory domains, to highlight that the phenomenon of enhancer skipping is pervasive and affects multiple types of genes. We discuss how simply assigning a genomic region of interest to its nearest gene is problematic and often leads to incorrect predictions and highlight that where possible information on both the conservation and topological organisation of the genome should be used to generate better hypotheses. The article has an associated Future Leader to Watch interview.

Wnt Signaling Rescues Amyloid Beta-Induced Gut Stem Cell Loss.

Patients with Alzheimer's disease suffer from a decrease in brain mass and a prevalence of amyloid-ß plaques. These plaques are thought to play a role in disease progression, but their exact role is not entirely established. We developed an optogenetic model to induce amyloid-ß intracellular oligomerization to model distinct disease etiologies. Here, we examine the effect of Wnt signaling on amyloid in an optogenetic, Drosophila gut stem cell model. We observe that Wnt activation rescues the detrimental effects of amyloid expression and oligomerization. We analyze the gene expression changes downstream of Wnt that contribute to this rescue and find changes in aging related genes, protein misfolding, metabolism, and inflammation. We propose that Wnt expression reduces inflammation through repression of Toll activating factors. We confirm that chronic Toll activation reduces lifespan, but a decrease in the upstream activator Persephone extends it. We propose that the protective effect observed for lithium treatment functions, at least in part, through Wnt activation and the inhibition of inflammation.

Accuracy of mutational signature software on correlated signatures.

Mutational signatures are characteristic patterns of mutations generated by exogenous mutagens or by endogenous mutational processes. Mutational signatures are important for research into DNA damage and repair, aging, cancer biology, genetic toxicology, and epidemiology. Unsupervised learning can infer mutational signatures from the somatic mutations in large numbers of tumors, and separating correlated signatures is a notable challenge for this task. To investigate which methods can best meet this challenge, we assessed 18 computational methods for inferring mutational signatures on 20 synthetic data sets that incorporated varying degrees of correlated activity of two common mutational signatures. Performance varied widely, and four methods noticeably outperformed the others: hdp (based on hierarchical Dirichlet processes), SigProExtractor (based on multiple non-negative matrix factorizations over resampled data), TCSM (based on an approach used in document topic analysis), and mutSpec.NMF (also based on non-negative matrix factorization). The results underscored the complexities of mutational signature extraction, including the importance and difficulty of determining the correct number of signatures and the importance of hyperparameters. Our findings indicate directions for improvement of the software and show a need for care when interpreting results from any of these methods, including the need for assessing sensitivity of the results to input parameters.