Site-Specific Phosphorylation of the DNA Damage Response Mediator Rad9 by Cyclin-Dependent Kinases Regulates Activation of Checkpoint Kinase 1

The mediators of the DNA damage response (DDR) are highly phosphorylated by kinases that control cell proliferation, but little is known about the role of this regulation. Here we show that cell cycle phosphorylation of the prototypical DDR mediator Saccharomyces cerevisiae Rad9 depends on cyclin-dependent kinase (CDK) complexes. We find that a specific G2/M form of Cdc28 can phosphorylate in vitro the N-terminal region of Rad9 on nine consensus CDK phosphorylation sites. We show that the integrity of CDK consensus sites and the activity of Cdc28 are required for both the activation of the Chk1 checkpoint kinase and its interaction with Rad9. We have identified T125 and T143 as important residues in Rad9 for this Rad9/Chk1 interaction. Phosphorylation of T143 is the most important feature promoting Rad9/Chk1 interaction, while the much more abundant phosphorylation of the neighbouring T125 residue impedes the Rad9/Chk1 interaction. We suggest a novel model for Chk1 activation where Cdc28 regulates the constitutive interaction of Rad9 and Chk1. The Rad9/Chk1 complex is then recruited at sites of DNA damage where activation of Chk1 requires additional DDR–specific protein kinases.     

Identification of methylated flavonoid regioisomeric metabolites using enzymatic semisynthesis and liquid chromatography-tandem mass spectrometry

Discrimination of isomeric methylated metabolites is an important step toward identifying genes responsible for methylation, but presents substantial challenges because authentic standards are often unavailable and mass spectra of isomers have been considered indistinguishable. In this report, an approach is described for identifying methyl group positions in multiply methylated flavonoid metabolites using combinations of tandem mass spectrometry, liquid chromatography retention, and site-selective methylation by recombinant O-methyltransferases from Solanum habrochaites LA1777. The basis for observed fragment ions in tandem mass spectra of multiply methylated myricetin was further established using enzymatic incorporation of deuterium-labeled methyl groups using S-adenosylmethionine-d ₃ as precursor.     

Flow infusion electrospray ionisation mass spectrometry for high throughput,non-targeted metabolite fingerprinting: a review

Producing a comprehensive overview of the chemical content of biologically-derived material is a major challenge. Apart from ensuring adequate metabolome coverage and issues of instrument dynamic range, mass resolution and sensitivity, there are major technical difficulties associated with data pre-processing and signal identification when attempting large scale, high-throughput experimentation. To address these factors direct infusion or flow infusion electrospray mass spectrometry has been finding utility as a high throughput metabolite fingerprinting tool. With little sample pre-treatment, no chromatography and instrument cycle times of less than 5 min it is feasible to analyse more than 1,000 samples per week. Data pre-processing is limited to aligning extracted mass spectra and mass-intensity matrices are generally ready in a working day for a month’s worth of data mining and hypothesis generation. ESI-MS fingerprinting has remained rather qualitative by nature and as such ion suppression does not generally compromise data information content as originally suggested when the methodology was first introduced. This review will describe how the quality of data has improved through use of nano-flow infusion and mass-windowing approaches, particularly when using high resolution instruments. The increasingly wider availability of robust high accurate mass instruments actually promotes ESI-MS from a merely fingerprinting tool to the ranks of metabolite profiling and combined with MS/MS capabilities of hybrid instruments improved structural information is available concurrently. We summarise current applications in a wide range of fields where ESI-MS fingerprinting has proved to be an excellent tool for “first pass” metabolome analysis of complex biological samples. The final part of the review describes a typical workflow with reference to recently published data to emphasise key aspects of overall experimental design.     

Cancer cachexia’s metabolic signature in a murine model confirms a distinct entity

Despite recent consensus definitions, lack of specific biomarkers remains a hurdle towards a more accurate and efficient diagnosis of cancer cachexia, distinguishing cachexia as a separate entity from other wasting syndromes. In a previous pilot study, we have shown that cancer-cachectic mice have a unique metabolic fingerprint with distinct glucose and lipid alterations compared to healthy controls. Further metabolomics studies were carried out to investigate differences in metabolic profiles of cancer-cachectic mice to tumor-bearing non-cachectic mice, calorie-restricted mice, and surgically treated cancer-cachectic mice. CD2F1 mice were divided into: (1) Cachexia Group received cachexia-inducing C26 undifferentiated colon carcinoma cells; (2) Tumor-Burden Group received, non-cachectic, P388 lymphoma cells; (3) Caloric-Restriction Group, remaining cancer-free, but subjected to caloric-restriction; (4) Surgery Group, similar to Cachexia Group, but tumors resected mid-experiment; and (5) Control Group aged intact. Baseline, mid-experiment and final serum samples were collected for ¹H NMR spectroscopic analysis. After data reduction, unsupervised principal component analysis and orthogonal projections to latent structures analyses demonstrate that the unique metabolic fingerprint is independent of tumor-burden and distinct from profiles of caloric-restriction and aging. Hyperlipidemia, hyperglycemia, and reduced branched-chain amino acids distinguish cachexia from other groups. Furthermore, the profile of surgically treated mice differs from that of cachectic mice, reverting to a profile more congruent with healthy controls indicating cachexia is amenable to correction where surgical cure is possible. That metabolomic analysis of murine serum is able to differentiate cachexia from tumor-burden and caloric-restriction warrants similar translational investigations in patients to explore cancer cachexia’s unique biomarkers.     

Discovery Analysis of TCGA Data Reveals Association between Germline Genotype and Survival in Ovarian Cancer Patients

Background

Ovarian cancer remains a significant public health burden, with the highest mortality rate of all the gynecological cancers. This is attributable to the late stage at which the majority of ovarian cancers are diagnosed, coupled with the low and variable response of advanced tumors to standard chemotherapies. To date, clinically useful predictors of treatment response remain lacking. Identifying the genetic determinants of ovarian cancer survival and treatment response is crucial to the development of prognostic biomarkers and personalized therapies that may improve outcomes for the late-stage patients who comprise the majority of cases.

Methods

To identify constitutional genetic variations contributing to ovarian cancer mortality, we systematically investigated associations between germline polymorphisms and ovarian cancer survival using data from The Cancer Genome Atlas Project (TCGA). Using stage-stratified Cox proportional hazards regression, we examined 650,000 SNP loci for association with survival. We additionally examined whether the association of significant SNPs with survival was modified by somatic alterations.

Results

Germline polymorphisms at rs4934282 (AGAP11/C10orf116) and rs1857623 (DNAH14) were associated with stage-adjusted survival ( = 1.12e-07 and 1.80e-07, FDR  = 1.2e-04 and 2.4e-04, respectively). A third SNP, rs4869 (C10orf116), was additionally identified as significant in the exome sequencing data; it is in near-perfect LD with rs4934282. The associations with survival remained significant when somatic alterations.

Conclusions

Discovery analysis of TCGA data reveals germline genetic variations that may play a role in ovarian cancer survival even among late-stage cases. The significant loci are located near genes previously reported as having a possible relationship to platinum and taxol response. Because the variant alleles at the significant loci are common (frequencies for rs4934282 A/C alleles = 0.54/0.46, respectively; rs1857623 A/G alleles = 0.55/0.45, respectively) and germline variants can be assayed noninvasively, our findings provide potential targets for further exploration as prognostic biomarkers and individualized therapies.     

Factors Associated with Post-Seasonal Serological Titer and Risk Factors for Infection with the Pandemic A/H1N1 Virus in the French General Population

The CoPanFlu-France cohort of households was set up in 2009 to study the risk factors for infection by the pandemic influenza virus (H1N1pdm) in the French general population. The authors developed an integrative data-driven approach to identify individual, collective and environmental factors associated with the post-seasonal serological H1N1pdm geometric mean titer, and derived a nested case-control analysis to identify risk factors for infection during the first season. This analysis included 1377 subjects (601 households). The GMT for the general population was 47.1 (95% confidence interval (CI): 45.1, 49.2). According to a multivariable analysis, pandemic vaccination, seasonal vaccination in 2009, recent history of influenza-like illness, asthma, chronic obstructive pulmonary disease, social contacts at school and use of public transports by the local population were associated with a higher GMT, whereas history of smoking was associated with a lower GMT. Additionally, young age at inclusion and risk perception of exposure to the virus at work were identified as possible risk factors, whereas presence of an air humidifier in the living room was a possible protective factor. These findings will be interpreted in light of the longitudinal analyses of this ongoing cohort.     

An Investigation of Fecal Volatile Organic Metabolites in Irritable Bowel Syndrome

Diagnosing irritable bowel syndrome (IBS) can be a challenge; many clinicians resort to invasive investigations in order to rule out other diseases and reassure their patients. Volatile organic metabolites (VOMs) are emitted from feces; understanding changes in the patterns of these VOMs could aid our understanding of the etiology of the disease and the development of biomarkers, which can assist in the diagnosis of IBS. We report the first comprehensive study of the fecal VOMs patterns in patients with diarrhea-predominant IBS (IBS-D), active Crohn''s disease (CD), ulcerative colitis (UC) and healthy controls. 30 patients with IBS-D, 62 with CD, 48 with UC and 109 healthy controls were studied. Diagnosis of IBS-D was made using the Manning criteria and all patients with CD and UC met endoscopic, histologic and/or radiologic criteria. Fecal VOMs were extracted by solid phase microextraction (SPME) and analyzed by gas chromatography-mass spectrometry (GC-MS). 240 VOMs were identified. Univariate analysis showed that esters of short chain fatty acids, cyclohexanecarboxylic acid and its ester derivatives were associated with IBS-D (p<0.05), while aldehydes were more abundant in IBD (p<0.05). A predictive model, developed by multivariate analysis, separated IBS-D from active CD, UC and healthy controls with a sensitivity of 94%, 96% and 90%; and a specificity of 82%, 80% and 80% respectively (p<0.05). The understanding of the derivation of these VOMs may cast light on the etiology of IBS-D and IBD. These data show that fecal VOMs analyses could contribute to the diagnosis of IBS-D, for which there is no laboratory test, as well as IBD.