SummaryDrosophila melanogaster has emerged as an important model system for the study of both stem cell biology and aging. Much is known about how molecular signals from the somatic niche regulate adult stem cells in the germline, and a variety of environmental factors as well as single point mutations have been shown to affect lifespan. Relatively little is known, however, about how aging affects specific populations of cells, particularly adult stem cells that may be susceptible to aging-related damage. Here we show that male germline stem cells (GSCs) are lost from the stem cell niche during aging, but are efficiently replaced to maintain overall stem cell number. We also find that the division rate of GSCs slows significantly during aging, and that this slowing correlates with a reduction in the number of somatic hub cells that contribute to the stem cell niche. Interestingly, slowing of stem cell division rate was not observed in long-lived methuselah mutant flies. We finally investigated whether two mechanisms that are thought to be used in other adult stem cell types to minimize the effects of aging were operative in this system. First, in many adult tissues stem cells exhibit markedly fewer cell cycles relative to transit-amplifying cells, presumably protecting the stem cell pool from replication-associated damage. Second, at any given time not all stem cells actively cycle, leading to 'clonal succession' from the reserve pool of initially quiescent stem cells. We find that neither of these mechanisms is used in Drosophila male GSCs.
Genes interact in networks to orchestrate cellular processes. Analysis of these networks provides insights into gene interactions and functions. Here, we took advantage of normal variation in human gene expression to infer gene networks, which we constructed using correlations in expression levels of more than 8.5 million gene pairs in immortalized B cells from three independent samples. The resulting networks allowed us to identify biological processes and gene functions. Among the biological pathways, we found processes such as translation and glycolysis that co-occur in the same subnetworks. We predicted the functions of poorly characterized genes, including CHCHD2 and TMEM111, and provided experimental evidence that TMEM111 is part of the endoplasmic reticulum-associated secretory pathway. We also found that IFIH1, a susceptibility gene of type 1 diabetes, interacts with YES1, which plays a role in glucose transport. Furthermore, genes that predispose to the same diseases are clustered nonrandomly in the coexpression network, suggesting that networks can provide candidate genes that influence disease susceptibility. Therefore, our analysis of gene coexpression networks offers information on the role of human genes in normal and disease processes.
The accumulation of unfolded or misfolded proteins in the endoplasmic reticulum (ER) results in the condition called "ER stress," which induces the unfolded protein response (UPR), a complex cellular process that includes changes in expression of many genes. Failure to restore homeostasis in the ER is associated with human diseases. To identify the underlying changes in gene expression in response to ER stress, we induced ER stress in human B cells and then measured gene expression at ten time points. We followed up those results by studying cells from 60 unrelated people. We rediscovered genes that were known to play a role in the ER-stress response and uncovered several thousand genes that are not known to be involved. Two of these are VLDLR and INHBE, which showed significant increase in expression after ER stress in B cells and in primary fibroblasts. To study the links between UPR and disease susceptibility, we identified ER-stress-responsive genes that are associated with human diseases and assessed individual differences in the ER-stress response. Many of the UPR genes are associated with Mendelian disorders, such as Wolfram syndrome, and complex diseases, including amyotrophic lateral sclerosis and diabetes. Data from two independent samples showed extensive individual variability in ER-stress response. Additional analyses with monozygotic twins revealed significant correlations within twin pairs in their responses to ER stress, thus showing evidence for heritable variation among individuals. These results have implications for basic understanding of ER function and its role in disease susceptibility.
Objective. Although oral methotrexate (MTX) remains the anchor drug for rheumatoid arthritis (RA), up to 50% of patients do not achieve a clinically adequate outcome. In addition, there is a lack of prognostic tools for treatment response prior to drug initiation. This study was undertaken to investigate whether interindividual differences in the human gut microbiome can aid in the prediction of MTX efficacy in new-onset RA.Methods. We performed 16S ribosomal RNA gene and shotgun metagenomic sequencing on the baseline gut microbiomes of drug-naive patients with new-onset RA (n = 26). Results were validated in an additional independent cohort (n = 21). To gain insight into potential microbial mechanisms, we conducted ex vivo experiments coupled with metabolomics analysis to evaluate the association between microbiome-driven MTX depletion and clinical response.Results. Our analysis revealed significant associations of the abundance of gut bacterial taxa and their genes with future clinical response (q < 0.05), including orthologs related to purine and MTX metabolism. Machine learning techniques were applied to the metagenomic data, resulting in a microbiome-based model that predicted lack of response to MTX in an independent group of patients. Finally, MTX levels remaining after ex vivo incubation with distal gut samples from pretreatment RA patients significantly correlated with the magnitude of future clinical response, suggesting a possible direct effect of the gut microbiome on MTX metabolism and treatment outcomes.Conclusion. Taken together, these findings are the first step toward predicting lack of response to oral MTX in patients with new-onset RA and support the value of the gut microbiome as a possible prognostic tool and as a potential target in RA therapeutics.
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