The Unfolded Protein Response Is Not Necessary for the G1/S Transition, but It Is Required for Chromosome Maintenance in Saccharomyces cerevisiae

BACKGROUND: The unfolded protein response (UPR) is a eukaryotic signaling pathway, from the endoplasmic reticulum (ER) to the nucleus. Protein misfolding in the ER triggers the UPR. Accumulating evidence links the UPR in diverse aspects of cellular homeostasis. The UPR responds to the overall protein synthesis capacity and metabolic fluxes of the cell. Because the coupling of metabolism with cell division governs when cells start dividing, here we examined the role of UPR signaling in the timing of initiation of cell division and cell cycle progression, in the yeast Saccharomyces cerevisiae. METHODOLOGY/PRINCIPAL FINDINGS: We report that cells lacking the ER-resident stress sensor Ire1p, which cannot trigger the UPR, nonetheless completed the G1/S transition on time. Furthermore, loss of UPR signaling neither affected the nutrient and growth rate dependence of the G1/S transition, nor the metabolic oscillations that yeast cells display in defined steady-state conditions. Remarkably, however, loss of UPR signaling led to hypersensitivity to genotoxic stress and a ten-fold increase in chromosome loss. CONCLUSIONS/SIGNIFICANCE: Taken together, our results strongly suggest that UPR signaling is not necessary for the normal coupling of metabolism with cell division, but it has a role in genome maintenance. These results add to previous work that linked the UPR with cytokinesis in yeast. UPR signaling is conserved in all eukaryotes, and it malfunctions in a variety of diseases, including cancer. Therefore, our findings may be relevant to other systems, including humans

A New Calibrated Bayesian Internal Goodness-of-Fit Method: Sampled Posterior p-Values as Simple and General p-Values That Allow Double Use of the Data

Background: Recent approaches mixing frequentist principles with Bayesian inference propose internal goodness-of-fit (GOF) p-values that might be valuable for critical analysis of Bayesian statistical models. However, GOF p-values developed to date only have known probability distributions under restrictive conditions. As a result, no known GOF p-value has a known probability distribution for any discrepancy function. Methodology/Principal Findings: We show mathematically that a new GOF p-value, called the sampled posterior p-value (SPP), asymptotically has a uniform probability distribution whatever the discrepancy function. In a moderate finite sample context, simulations also showed that the SPP appears stable to relatively uninformative misspecifications of the prior distribution. Conclusions/Significance: These reasons, together with its numerical simplicity, make the SPP a better canonical GOF p-value than existing GOF p-values

Diagnostic delay for giant cell arteritis – a systematic review and meta-analysis

Background Giant cell arteritis (GCA), if untreated, can lead to blindness and stroke. The study’s objectives were to (1) determine a new evidence-based benchmark of the extent of diagnostic delay for GCA and (2) examine the role of GCA-specific characteristics on diagnostic delay. Methods Medical literature databases were searched from inception to November 2015. Articles were included if reporting a time-period of diagnostic delay between onset of GCA symptoms and diagnosis. Two reviewers assessed the quality of the final articles and extracted data from these. Random-effects meta-analysis was used to pool the mean time-period (95% confidence interval (CI)) between GCA symptom onset and diagnosis, and the delay observed for GCA-specific characteristics. Heterogeneity was assessed by I 2 and by 95% prediction interval (PI). Results Of 4128 articles initially identified, 16 provided data for meta-analysis. Mean diagnostic delay was 9.0 weeks (95% CI, 6.5 to 11.4) between symptom onset and GCA diagnosis (I 2 = 96.0%; P < 0.001; 95% PI, 0 to 19.2 weeks). Patients with a cranial presentation of GCA received a diagnosis after 7.7 (95% CI, 2.7 to 12.8) weeks (I 2 = 98.4%; P < 0.001; 95% PI, 0 to 27.6 weeks) and those with non-cranial GCA after 17.6 (95% CI, 9.7 to 25.5) weeks (I 2 = 96.6%; P < 0.001; 95% PI, 0 to 46.1 weeks). Conclusions The mean delay from symptom onset to GCA diagnosis was 9 weeks, or longer when cranial symptoms were absent. Our research provides an evidence-based benchmark for diagnostic delay of GCA and supports the need for improved public awareness and fast-track diagnostic pathways

A detailed Hapmap of the Sitosterolemia locus spanning 69 kb; differences between Caucasians and African-Americans

BACKGROUND: Sitosterolemia is an autosomal recessive disorder that maps to the sitosterolemia locus, STSL, on human chromosome 2p21. Two genes, ABCG5 and ABCG8, comprise the STSL and mutations in either cause sitosterolemia. ABCG5 and ABCG8 are thought to have evolved by gene duplication event and are arranged in a head-to-head configuration. We report here a detailed characterization of the STSL in Caucasian and African-American cohorts. METHODS: Caucasian and African-American DNA samples were genotypes for polymorphisms at the STSL locus and haplotype structures determined for this locus RESULTS: In the Caucasian population, 13 variant single nucleotide polymorphisms (SNPs) were identified and resulting in 24 different haplotypes, compared to 11 SNPs in African-Americans resulting in 40 haplotypes. Three polymorphisms in ABCG8 were unique to the Caucasian population (E238L, INT10-50 and G575R), whereas one variant (A259V) was unique to the African-American population. Allele frequencies of SNPs varied also between these populations. CONCLUSION: We confirmed that despite their close proximity to each other, significantly more variations are present in ABCG8 compared to ABCG5. Pairwise D' values showed wide ranges of variation, indicating some of the SNPs were in strong linkage disequilibrium (LD) and some were not. LD was more prevalent in Caucasians than in African-Americans, as would be expected. These data will be useful in analyzing the proposed role of STSL in processes ranging from responsiveness to cholesterol-lowering drugs to selective sterol absorption

Empirical vs Bayesian approach for estimating haplotypes from genotypes of unrelated individuals

BACKGROUND: The completion of the HapMap project has stimulated further development of haplotype-based methodologies for disease associations. A key aspect of such development is the statistical inference of individual diplotypes from unphased genotypes. Several methodologies for inferring haplotypes have been developed, but they have not been evaluated extensively to determine which method not only performs well, but also can be easily incorporated in downstream haplotype-based association analyses. In this paper, we attempt to do so. Our evaluation was carried out by comparing the two leading Bayesian methods, implemented in PHASE and HAPLOTYPER, and the two leading empirical methods, implemented in PL-EM and HPlus. We used these methods to analyze real data, namely the dense genotypes on X-chromosome of 30 European and 30 African trios provided by the International HapMap Project, and simulated genotype data. Our conclusions are based on these analyses. RESULTS: All programs performed very well on X-chromosome data, with an average similarity index of 0.99 and an average prediction rate of 0.99 for both European and African trios. On simulated data with approximation of coalescence, PHASE implementing the Bayesian method based on the coalescence approximation outperformed other programs on small sample sizes. When the sample size increased, other programs performed as well as PHASE. PL-EM and HPlus implementing empirical methods required much less running time than the programs implementing the Bayesian methods. They required only one hundredth or thousandth of the running time required by PHASE, particularly when analyzing large sample sizes and large umber of SNPs. CONCLUSION: For large sample sizes (hundreds or more), which most association studies require, the two empirical methods might be used since they infer the haplotypes as accurately as any Bayesian methods and can be incorporated easily into downstream haplotype-based analyses such as haplotype-association analyses

Native-state stability determines the extent of degradation relative to secretion of protein variants from Pichia pastoris.

We have investigated the relationship between the stability and secreted yield of a series of mutational variants of human lysozyme (HuL) in Pichia pastoris. We show that genes directly involved in the unfolded protein response (UPR), ER-associated degradation (ERAD) and ER-phagy are transcriptionally up-regulated more quickly and to higher levels in response to expression of more highly-destabilised HuL variants and those variants are secreted to lower yield. We also show that the less stable variants are retained within the cell and may also be targeted for degradation. To explore the relationship between stability and secretion further, two different single-chain-variable-fragment (scFv) antibodies were also expressed in P. pastoris, but only one of the scFvs gave rise to secreted protein. The non-secreted scFv was detected within the cell and the UPR indicators were pronounced, as they were for the poorly-secreted HuL variants. The non-secreted scFv was modified by changing either the framework regions or the linker to improve the predicted stability of the scFv and secretion was then achieved and the levels of UPR indicators were lowered Our data support the hypothesis that less stable proteins are targeted for degradation over secretion and that this accounts for the decrease in the yields observed. We discuss the secretion of proteins in relation to lysozyme amyloidosis, in particular, and optimised protein secretion, in general

Status of Intraductal Therapy for Ductal Carcinoma in Situ

The intraductal approach is particularly appealing in the setting of ductal carcinoma in situ (DCIS), a preinvasive breast neoplasm that is thought to be entirely intraductal in its extent. Based on an emerging understanding of the anatomy of the ductal system as well as novel techniques to leverage the access accorded by the intraductal approach, researchers are actively exploring how ductal lavage, ductoscopy, and intraductal infusion of therapeutic agents may enhance breast cancer treatment. Both cytologic and molecular diagnostics continue to improve, and work is ongoing to identify the most effective diagnostic biomarkers for DCIS and cancer, although optimal targeting of the diseased duct remains an important consideration. Ductoscopy holds potential in detection of occult intraductal lesions, and ductoscopically guided lumpectomy could increase the likelihood of a more comprehensive surgical excision. Exciting pilot studies are in progress to determine the safety and feasibility of intraductal chemotherapy infusion. These studies are an important starting point for future investigations of intraductal ablative therapy for DCIS, because as our knowledge and techniques evolve, it is likely that DCIS may be the target most amenable to treatment by intraductal therapy. If such studies are successful, these approaches will allow an important and meaningful transformation in treatment options for women diagnosed with DCIS

Tolerability of breast ductal lavage in women from families at high genetic risk of breast cancer

<p>Abstract</p> <p>Background</p> <p>Ductal lavage (DL) has been proposed as a minimally-invasive, well-tolerated tool for obtaining breast epithelial cells for cytological evaluation of breast cancer risk. We report DL tolerability in <it>BRCA1/2 </it>mutation-positive and -negative women from an IRB-approved research study.</p> <p>Methods</p> <p>165 <it>BRCA1/2 </it>mutation-positive, 26 mutation-negative and 3 mutation unknown women underwent mammography, breast MRI and DL. Psychological well-being and perceptions of pain were obtained before and after DL, and compared with pain experienced during other screening procedures.</p> <p>Results</p> <p>The average <b><it>anticipated </it></b>and <b><it>experienced </it></b>discomfort rating for DL, 47 and 48 (0–100), were significantly higher (<it>p </it>< 0.01) than the <b><it>anticipated </it></b>and <b><it>experienced </it></b>discomfort of mammogram (38 and 34), MRI (36 and 25) or nipple aspiration (42 and 27). Women with greater pre-existing emotional distress experienced more DL-related discomfort than they anticipated. Women reporting DL-related pain as worse than expected were nearly three times more likely to refuse subsequent DL than those reporting it as the same or better than expected. Twenty-five percent of participants refused repeat DL at first annual follow-up.</p> <p>Conclusion</p> <p>DL was anticipated to be and experienced as <b>more </b>uncomfortable than other procedures used in breast cancer screening. Higher underlying psychological distress was associated with decreased DL tolerability.</p

Metabolic Network Topology Reveals Transcriptional Regulatory Signatures of Type 2 Diabetes

Type 2 diabetes mellitus (T2DM) is a disorder characterized by both insulin resistance and impaired insulin secretion. Recent transcriptomics studies related to T2DM have revealed changes in expression of a large number of metabolic genes in a variety of tissues. Identification of the molecular mechanisms underlying these transcriptional changes and their impact on the cellular metabolic phenotype is a challenging task due to the complexity of transcriptional regulation and the highly interconnected nature of the metabolic network. In this study we integrate skeletal muscle gene expression datasets with human metabolic network reconstructions to identify key metabolic regulatory features of T2DM. These features include reporter metabolites—metabolites with significant collective transcriptional response in the associated enzyme-coding genes, and transcription factors with significant enrichment of binding sites in the promoter regions of these genes. In addition to metabolites from TCA cycle, oxidative phosphorylation, and lipid metabolism (known to be associated with T2DM), we identified several reporter metabolites representing novel biomarker candidates. For example, the highly connected metabolites NAD+/NADH and ATP/ADP were also identified as reporter metabolites that are potentially contributing to the widespread gene expression changes observed in T2DM. An algorithm based on the analysis of the promoter regions of the genes associated with reporter metabolites revealed a transcription factor regulatory network connecting several parts of metabolism. The identified transcription factors include members of the CREB, NRF1 and PPAR family, among others, and represent regulatory targets for further experimental analysis. Overall, our results provide a holistic picture of key metabolic and regulatory nodes potentially involved in the pathogenesis of T2DM