19 research outputs found
Hydroponic isotope labeling of entire plants (HILEP) for quantitative plant proteomics
Quantitative analysis by mass spectrometry (MS) is a major challenge in
proteomics as the correlation between analyte concentration and signal
intensity is often poor due to varying ionisation efficiencies in the
presence of molecular competitors. However, relative quantitation
methods that utilise differential stable isotope labelling and mass
spectrometric detection are available. Many drawbacks inherent to
chemical labelling methods (ICAT, iTRAQ) can be overcome by
metabolic labelling with amino acids containing stable isotopes (e.g. 13C
and/or 15N) in methods such as Stable Isotope Labelling with Amino
acids in Cell culture (SILAC). SILAC has also been used for labelling of
proteins in plant cell cultures (1) but is not suitable for whole plant
labelling. Plants are usually autotrophic (fixing carbon from atmospheric
CO2) and, thus, labelling with carbon isotopes becomes impractical. In
addition, SILAC is expensive.
Recently, Arabidopsis cell cultures were labelled with 15N in a medium
containing nitrate as sole nitrogen source. This was shown to be suitable
for quantifying proteins and nitrogen-containing metabolites from this cell
culture (2,3).
Labelling whole plants, however, offers the advantage of studying
quantitatively the response to stimulation or disease of a whole multicellular
organism or multi-organism systems at the molecular level.
Furthermore, plant metabolism enables the use of inexpensive labelling
media without introducing additional stress to the organism. And finally,
hydroponics is ideal to undertake metabolic labelling under extremely
well-controlled conditions.
We demonstrate the suitability of metabolic 15N hydroponic isotope
labelling of entire plants (HILEP) for relative quantitative proteomic
analysis by mass spectrometry. To evaluate this methodology,
Arabidopsis plants were grown hydroponically in 14N and 15N media and subjected to oxidative stress
Highly accurate detection of ovarian cancer using CA125 but limited improvement with serum matrix-assisted laser desorption/ionization time-of-flight mass spectrometry profiling
Objectives: Our objective was to test the performance of CA125 in classifying serum samples from a cohort of malignant and benign ovarian cancers and age-matched healthy controls and to assess whether combining information from matrix-assisted laser desorption/ionization (MALDI) time-of-flight profiling could improve diagnostic performance.
Materials and Methods: Serum samples from women with ovarian neoplasms and healthy volunteers were subjected to CA125 assay and MALDI time-of-flight mass spectrometry (MS) profiling. Models were built from training data sets using discriminatory MALDI MS peaks in combination with CA125 values and tested their ability to classify blinded test samples. These were compared with models using CA125 threshold levels from 193 patients with ovarian cancer, 290 with benign neoplasm, and 2236 postmenopausal healthy controls.
Results: Using a CA125 cutoff of 30 U/mL, an overall sensitivity of 94.8% (96.6% specificity) was obtained when comparing malignancies versus healthy postmenopausal controls, whereas a cutoff of 65 U/mL provided a sensitivity of 83.9% (99.6% specificity). High classification accuracies were obtained for early-stage cancers (93.5% sensitivity). Reasons for high accuracies include recruitment bias, restriction to postmenopausal women, and inclusion of only primary invasive epithelial ovarian cancer cases. The combination of MS profiling information with CA125 did not significantly improve the specificity/accuracy compared with classifications on the basis of CA125 alone.
Conclusions: We report unexpectedly good performance of serum CA125 using threshold classification in discriminating healthy controls and women with benign masses from those with invasive ovarian cancer. This highlights the dependence of diagnostic tests on the characteristics of the study population and the crucial need for authors to provide sufficient relevant details to allow comparison. Our study also shows that MS profiling information adds little to diagnostic accuracy. This finding is in contrast with other reports and shows the limitations of serum MS profiling for biomarker discovery and as a diagnostic too
Trans-ancestry meta-analyses identify rare and common variants associated with blood pressure and hypertension
High blood pressure is a major risk factor for cardiovascular disease and premature death. However, there is limited knowledge on specific causal genes and pathways. To better understand the genetics of blood pressure, we genotyped 242,296 rare, low-frequency and common genetic variants in up to ~192,000 individuals, and used ~155,063 samples for independent replication. We identified 31 novel blood pressure or hypertension associated genetic regions in the general population, including three rare missense variants in RBM47, COL21A1 and RRAS with larger effects (>1.5mmHg/allele) than common variants. Multiple rare, nonsense and missense variant associations were found in A2ML1 and a low-frequency nonsense variant in ENPEP was identified. Our data extend the spectrum of allelic variation underlying blood pressure traits and hypertension, provide new insights into the pathophysiology of hypertension and indicate new targets for clinical intervention
MS-based clinical proteomics: biomarker discovery in men’s cancer
Importance of biomarker discovery in men’s cancer diagnosis and prognosis
Each year around 10,000 men in the UK die as a result of prostate cancer (PCa) making it the 3rd most common
cancer behind lung and breast cancer; worldwide more than 670,000 men are diagnosed every year with the
disease [1]. Current methods of diagnosis of PCa mainly rely on the detection of elevated prostate-specific
antigen (PSA) levels in serum and/or physical examination by a doctor for the detection of an abnormal prostate.
PSA is a glycoprotein produced almost exclusively by the epithelial cells of the prostate gland [2]. Its role is not
fully understood, although it is known that it forms part of the ejaculate and its function is to solubilise the sperm
to give them the mobility to swim. Raised PSA levels in serum are thought to be due to both an increased
production of PSA from the proliferated prostate cells, and a diminished architecture of affected cells, allowing an
easier distribution of PSA into the wider circulatory system
First-dimension separation with the MicroRotoforTM cell prior to SDS-PAGE and LC-MS/MS analysis
Free-flow isoelectric focusing (IEF) is a gel-free method for separating proteins based on their isoelectric point (pl) in a liquid environment and in the presence of carrier ampholytes. this method has been used with the RotoforTM cell at the preparative scale to fractionate proteins from samples containing several hundred milligrams of protein; see the refeences listed in Bio-Rad bulletin 3152. the MicroRotofor cell applies the same method to much sl=maller protein samples without dilution, separating and recoverng milligram quantities of protein in a total volume of about 2 ml
Comparison of bottom-up protein identification methods
With the rapid development of proteomics, a number of different methods appeared for the basic task of protein identification. We made a simple comparison between a common liquid chromatography-tandem mass spectrometry (LC-MS/MS) workflow using an ion trap mass spectrometer and a combined LC-MS and LC-MS/MS method using Fourier transform ion cyclotron resonance (FTICR) mass spectrometry and accurate peptide masses.
To compare the two methods for protein identification, we grew and extracted proteins from E. coli using established protocols. Cystines were reduced and alkylated, and proteins digested by trypsin. The resulting peptide mixtures were separated by reversed-phase liquid chromatography using a 4 h gradient from 0 to 50% acetonitrile over a C18 reversed-phase column. The LC separation was coupled on-line to either a Bruker Esquire HCT ion trap or a Bruker 7 tesla APEX-Qe Qh-FTICR hybrid mass spectrometer.
Data-dependent Qh-FTICR-MS/MS spectra were acquired using the quadrupole mass filter and collisionally induced dissociation into the external hexapole trap. Proteins were in both schemes identified by Mascot MS/MS ion searches and the peptides identified from these proteins in the FTICR MS/MS data were used for automatic internal calibration of the FTICR-MS data, together with ambient polydimethylcyclosiloxane ions
Genome expansion and gene loss in powdery mildew fungi reveal tradeoffs in extreme parasitism
Powdery mildews are phytopathogens whose growth and reproduction are entirely dependent
on living plant cells. The molecular basis of this life-style, obligate biotrophy, remains unknown. We
present the genome analysis of barley powdery mildew, Blumeria graminis f.sp. hordei (Blumeria), as well
as a comparison with the analysis of two powdery mildews pathogenic on dicotyledonous plants. These
genomes display massive retrotransposon proliferation, genome-size expansion, and gene losses. The
missing genes encode enzymes of primary and secondary metabolism, carbohydrate-active enzymes, and
transporters, probably reflecting their redundancy in an exclusively biotrophic life-style. Among the 248
candidate effectors of pathogenesis identified in the Blumeria genome, very few (less than 10) define a
core set conserved in all three mildews, suggesting thatmost effectors represent species-specific adaptations