Molecular Basis of the Waxy Endosperm Starch Phenotype in Broomcorn Millet (Panicum miliaceum L.)

Waxy varieties of the tetraploid cereal broomcorn millet (Panicum miliaceum L.) have endosperm starch granules lacking detectable amylose. This study investigated the basis of this phenotype using molecular and biochemical methods. Iodine staining of starch granules in 72 plants from 38 landrace accessions found 58 nonwaxy and 14 waxy phenotype plants. All waxy types were in plants from Chinese and Korean accessions, a distribution similar to that of the waxy phenotype in other cereals. Granule-bound starch synthase I (GBSSI) protein was present in the endosperm of both nonwaxy and waxy individuals, but waxy types had little or no granule-bound starch synthase activity compared with the wild types. Sequencing of the GBSSI (Waxy) gene showed that this gene is present in two different forms (L and S) in P. miliaceum, which probably represent homeologues derived from two distinct diploid ancestors. Protein products of both these forms are present in starch granules. We identified three polymorphisms in the exon sequence coding for mature GBSSI peptides. A 15-bp deletion has occurred in the S type GBSSI, resulting in the loss of five amino acids from glucosyl transferase domain 1 (GTD1). The second GBSSI type (L) shows two sequence polymorphisms. One is the insertion of an adenine residue that causes a reading frameshift, and the second causes a cysteine–tyrosine amino acid polymorphism. These mutations appear to have occurred in parallel from the ancestral allele, resulting in three GBSSI-L alleles in total. Five of the six possible genotype combinations of the S and L alleles were observed. The deletion in the GBSSI-S gene causes loss of protein activity, and there was 100% correspondence between this deletion and the waxy phenotype. The frameshift mutation in the L gene results in the loss of L-type protein from starch granules. The L isoform with the tyrosine residue is present in starch granules but is nonfunctional. This loss of function may result from the substitution of tyrosine for cysteine, although it could not be determined whether the cysteine isoform of L represents the functional type. This is the first characterization of mutations that occur in combination in a functionally polyploid species to give a fully waxy phenotype

ATAQS: A computational software tool for high throughput transition optimization and validation for selected reaction monitoring mass spectrometry

<p>Abstract</p> <p>Background</p> <p>Since its inception, proteomics has essentially operated in a discovery mode with the goal of identifying and quantifying the maximal number of proteins in a sample. Increasingly, proteomic measurements are also supporting hypothesis-driven studies, in which a predetermined set of proteins is consistently detected and quantified in multiple samples. Selected reaction monitoring (SRM) is a targeted mass spectrometric technique that supports the detection and quantification of specific proteins in complex samples at high sensitivity and reproducibility. Here, we describe ATAQS, an integrated software platform that supports all stages of targeted, SRM-based proteomics experiments including target selection, transition optimization and post acquisition data analysis. This software will significantly facilitate the use of targeted proteomic techniques and contribute to the generation of highly sensitive, reproducible and complete datasets that are particularly critical for the discovery and validation of targets in hypothesis-driven studies in systems biology.</p> <p>Result</p> <p>We introduce a new open source software pipeline, ATAQS (Automated and Targeted Analysis with Quantitative SRM), which consists of a number of modules that collectively support the SRM assay development workflow for targeted proteomic experiments (project management and generation of protein, peptide and transitions and the validation of peptide detection by SRM). ATAQS provides a flexible pipeline for end-users by allowing the workflow to start or end at any point of the pipeline, and for computational biologists, by enabling the easy extension of java algorithm classes for their own algorithm plug-in or connection via an external web site.</p> <p>This integrated system supports all steps in a SRM-based experiment and provides a user-friendly GUI that can be run by any operating system that allows the installation of the Mozilla Firefox web browser.</p> <p>Conclusions</p> <p>Targeted proteomics via SRM is a powerful new technique that enables the reproducible and accurate identification and quantification of sets of proteins of interest. ATAQS is the first open-source software that supports all steps of the targeted proteomics workflow. ATAQS also provides software API (Application Program Interface) documentation that enables the addition of new algorithms to each of the workflow steps. The software, installation guide and sample dataset can be found in <url>http://tools.proteomecenter.org/ATAQS/ATAQS.html</url></p

Calculation of partial isotope incorporation into peptides measured by mass spectrometry

<p>Abstract</p> <p>Background</p> <p>Stable isotope probing (SIP) technique was developed to link function, structure and activity of microbial cultures metabolizing carbon and nitrogen containing substrates to synthesize their biomass. Currently, available methods are restricted solely to the estimation of fully saturated heavy stable isotope incorporation and convenient methods with sufficient accuracy are still missing. However in order to track carbon fluxes in microbial communities new methods are required that allow the calculation of partial incorporation into biomolecules.</p> <p>Results</p> <p>In this study, we use the characteristics of the so-called 'half decimal place rule' (HDPR) in order to accurately calculate the partial¹³C incorporation in peptides from enzymatic digested proteins. Due to the clade-crossing universality of proteins within bacteria, any available high-resolution mass spectrometry generated dataset consisting of tryptically-digested peptides can be used as reference.</p> <p>We used a freely available peptide mass dataset from <it>Mycobacterium tuberculosis </it>consisting of 315,579 entries. From this the error of estimated versus known heavy stable isotope incorporation from an increasing number of randomly drawn peptide sub-samples (100 times each; no repetition) was calculated. To acquire an estimated incorporation error of less than 5 atom %, about 100 peptide masses were needed. Finally, for testing the general applicability of our method, peptide masses of tryptically digested proteins from <it>Pseudomonas putida </it>ML2 grown on labeled substrate of various known concentrations were used and¹³C isotopic incorporation was successfully predicted. An easy-to-use script <abbrgrp><abbr bid="B1">1</abbr></abbrgrp> was further developed to guide users through the calculation procedure for their own data series.</p> <p>Conclusion</p> <p>Our method is valuable for estimating¹³C incorporation into peptides/proteins accurately and with high sensitivity. Generally, our method holds promise for wider applications in qualitative and especially quantitative proteomics.</p

Distinct Cerebrospinal Fluid Proteomes Differentiate Post-Treatment Lyme Disease from Chronic Fatigue Syndrome

Neurologic Post Treatment Lyme disease (nPTLS) and Chronic Fatigue (CFS) are syndromes of unknown etiology. They share features of fatigue and cognitive dysfunction, making it difficult to differentiate them. Unresolved is whether nPTLS is a subset of CFS. Methods and Principal Findings: Pooled cerebrospinal fluid (CSF) samples from nPTLS patients, CFS patients, and healthy volunteers were comprehensively analyzed using high-resolution mass spectrometry (MS), coupled with immunoaffinity depletion methods to reduce protein-masking by abundant proteins. Individual patient and healthy control CSF samples were analyzed directly employing a MS-based label-free quantitative proteomics approach. We found that both groups, and individuals within the groups, could be distinguished from each other and normals based on their specific CSF proteins (p&0.01). CFS (n = 43) had 2,783 non-redundant proteins, nPTLS (n = 25) contained 2,768 proteins, and healthy normals had 2,630 proteins. Preliminary pathway analysis demonstrated that the data could be useful for hypothesis generation on the pathogenetic mechanisms underlying these two related syndromes. Conclusions: nPTLS and CFS have distinguishing CSF protein complements. Each condition has a number of CSF proteins that can be useful in providing candidates for future validation studies and insights on the respective mechanisms of pathogenesis. Distinguishing nPTLS and CFS permits more focused study of each condition, and can lead to novel diagnostics and therapeutic interventions

Simultaneous Quantitation of Amino Acid Mixtures using Clustering Agents

A method that uses the abundances of large clusters formed in electrospray ionization to determine the solution-phase molar fractions of amino acids in multi-component mixtures is demonstrated. For solutions containing either four or 10 amino acids, the relative abundances of protonated molecules differed from their solution-phase molar fractions by up to 30-fold and 100-fold, respectively. For the four-component mixtures, the molar fractions determined from the abundances of larger clusters consisting of 19 or more molecules were within 25% of the solution-phase molar fractions, indicating that the abundances and compositions of these clusters reflect the relative concentrations of these amino acids in solution, and that ionization and detection biases are significantly reduced. Lower accuracy was obtained for the 10-component mixtures where values determined from the cluster abundances were typically within a factor of three of their solution molar fractions. The lower accuracy of this method with the more complex mixtures may be due to specific clustering effects owing to the heterogeneity as a result of significantly different physical properties of the components, or it may be the result of lower S/N for the more heterogeneous clusters and not including the low-abundance more highly heterogeneous clusters in this analysis. Although not as accurate as using traditional standards, this clustering method may find applications when suitable standards are not readily available

Multiple Statistical Analysis Techniques Corroborate Intratumor Heterogeneity in Imaging Mass Spectrometry Datasets of Myxofibrosarcoma

MALDI mass spectrometry can generate profiles that contain hundreds of biomolecular ions directly from tissue. Spatially-correlated analysis, MALDI imaging MS, can simultaneously reveal how each of these biomolecular ions varies in clinical tissue samples. The use of statistical data analysis tools to identify regions containing correlated mass spectrometry profiles is referred to as imaging MS-based molecular histology because of its ability to annotate tissues solely on the basis of the imaging MS data. Several reports have indicated that imaging MS-based molecular histology may be able to complement established histological and histochemical techniques by distinguishing between pathologies with overlapping/identical morphologies and revealing biomolecular intratumor heterogeneity. A data analysis pipeline that identifies regions of imaging MS datasets with correlated mass spectrometry profiles could lead to the development of novel methods for improved diagnosis (differentiating subgroups within distinct histological groups) and annotating the spatio-chemical makeup of tumors. Here it is demonstrated that highlighting the regions within imaging MS datasets whose mass spectrometry profiles were found to be correlated by five independent multivariate methods provides a consistently accurate summary of the spatio-chemical heterogeneity. The corroboration provided by using multiple multivariate methods, efficiently applied in an automated routine, provides assurance that the identified regions are indeed characterized by distinct mass spectrometry profiles, a crucial requirement for its development as a complementary histological tool. When simultaneously applied to imaging MS datasets from multiple patient samples of intermediate-grade myxofibrosarcoma, a heterogeneous soft tissue sarcoma, nodules with mass spectrometry profiles found to be distinct by five different multivariate methods were detected within morphologically identical regions of all patient tissue samples. To aid the further development of imaging MS based molecular histology as a complementary histological tool the Matlab code of the agreement analysis, instructions and a reduced dataset are included as supporting information

Chronic Oral Infection with Porphyromonas gingivalis Accelerates Atheroma Formation by Shifting the Lipid Profile

BACKGROUND: Recent studies have suggested that periodontal disease increases the risk of atherothrombotic disease. Atherosclerosis has been characterized as a chronic inflammatory response to cholesterol deposition in the arteries. Although several studies have suggested that certain periodontopathic bacteria accelerate atherogenesis in apolipoprotein E-deficient mice, the mechanistic link between cholesterol accumulation and periodontal infection-induced inflammation is largely unknown. METHODOLOGY/PRINCIPAL FINDINGS: We orally infected C57BL/6 and C57BL/6.KOR-Apoe(shl) (B6.Apoeshl) mice with Porphyromonas gingivalis, which is a representative periodontopathic bacterium, and evaluated atherogenesis, gene expression in the aorta and liver and systemic inflammatory and lipid profiles in the blood. Furthermore, the effect of lipopolysaccharide (LPS) from P. gingivalis on cholesterol transport and the related gene expression was examined in peritoneal macrophages. Alveolar bone resorption and elevation of systemic inflammatory responses were induced in both strains. Despite early changes in the expression of key genes involved in cholesterol turnover, such as liver X receptor and ATP-binding cassette A1, serum lipid profiles did not change with short-term infection. Long-term infection was associated with a reduction in serum high-density lipoprotein (HDL) cholesterol but not with the development of atherosclerotic lesions in wild-type mice. In B6.Apoeshl mice, long-term infection resulted in the elevation of very low-density lipoprotein (VLDL), LDL and total cholesterols in addition to the reduction of HDL cholesterol. This shift in the lipid profile was concomitant with a significant increase in atherosclerotic lesions. Stimulation with P. gingivalis LPS induced the change of cholesterol transport via targeting the expression of LDL receptor-related genes and resulted in the disturbance of regulatory mechanisms of the cholesterol level in macrophages. CONCLUSIONS/SIGNIFICANCE: Periodontal infection itself does not cause atherosclerosis, but it accelerates it by inducing systemic inflammation and deteriorating lipid metabolism, particularly when underlying hyperlidemia or susceptibility to hyperlipidemia exists, and it may contribute to the development of coronary heart disease