Direct peptide profiling of lateral cell groups of the antennal lobes of Manduca sexta reveals specific composition and changes in neuropeptide expression during development

The paired antennal lobes are the first integration centers for odor information in the insect brain. In the sphinx moth Manduca sexta, like in other holometabolous insects, they are formed during metamorphosis. To further understand mechanisms involved in the formation of this particularly well investigated brain area, we performed a direct peptide profiling of a well defined cell group (the lateral cell group) of the antennal lobe throughout development by MALDI-TOF mass spectrometry. Although the majority of the about 100 obtained ion signals represent still unknown substances, this first peptidomic characterization of this cell group indicated the occurrence of 12 structurally known neuropeptides. Among these peptides are helicostatin 1, cydiastatins 2, 3, and 4, M. sexta-allatotropin (Mas-AT), M. sexta-FLRFamide (Mas-FLRFamide) I, II, and III, nonblocked Mas-FLRFamide I, and M. sexta-myoinhibitory peptides (Mas-MIPs) III, V, and VI. The identity of two of the allatostatins (cydiastatins 3 and 4) and Mas-AT were confirmed by tandem mass spectrometry (MALDI-TOF/TOF). During development of the antennal lobe, number and frequency of ion signals including those representing known peptides generally increased at the onset of glomeruli formation at pupal Stage P7/8, with cydiastatin 2, helicostatin 1, and Mas-MIP V being the exceptions. Cydiastatin 2 showed transient occurrence mainly during the period of glomerulus formation, helicostatin 1 was restricted to late pupae and adults, while Mas-MIP V occurred exclusively in adult antennal lobes. The power of the applied direct mass spectrometric profiling lies in the possibility of chemically identifying neuropeptides of a given cell population in a fast and reliable manner, at any developmental stage in single specimens. The identification of neuropeptides in the antennal lobes now allows to specifically address the function of these signaling molecules during the formation of the antennal lobe network.     

Proposed minimum reporting standards for chemical analysis

There is a general consensus that supports the need for standardized reporting of metadata or information describing large-scale metabolomics and other functional genomics data sets. Reporting of standard metadata provides a biological and empirical context for the data, facilitates experimental replication, and enables the re-interrogation and comparison of data by others. Accordingly, the Metabolomics Standards Initiative is building a general consensus concerning the minimum reporting standards for metabolomics experiments of which the Chemical Analysis Working Group (CAWG) is a member of this community effort. This article proposes the minimum reporting standards related to the chemical analysis aspects of metabolomics experiments including: sample preparation, experimental analysis, quality control, metabolite identification, and data pre-processing. These minimum standards currently focus mostly upon mass spectrometry and nuclear magnetic resonance spectroscopy due to the popularity of these techniques in metabolomics. However, additional input concerning other techniques is welcomed and can be provided via the CAWG on-line discussion forum at or . Further, community input related to this document can also be provided via this electronic forum. The contents of this paper do not necessarily reflect any position of the Government or the opinion of the Food and Drug Administration Sponsor: Metabolomics Society http://www.metabolomicssociety.org/ Reference: http://msi-workgroups.sourceforge.net/bio-metadata/reporting/pbc/ http://msi-workgroups.sourceforge.net/chemical-analysis/ Version: Revision: 5.1 Date: 09 January, 2007     

A workflow to increase the detection rate of proteins from unsequenced organisms in high-throughput proteomics experiments

We present and evaluate a strategy for the mass spectrometric identification of proteins from organisms for which no genome sequence information is available that incorporates cross-species information from sequenced organisms. The presented method combines spectrum quality scoring, de novo sequencing and error tolerant BLAST searches and is designed to decrease input data complexity. Spectral quality scoring reduces the number of investigated mass spectra without a loss of information. Stringent quality-based selection and the combination of different de novo sequencing methods substantially increase the catalog of significant peptide alignments. The de novo sequences passing a reliability filter are subsequently submitted to error tolerant BLAST searches and MS-BLAST hits are validated by a sampling technique. With the described workflow, we identified up to 20% more groups of homologous proteins in proteome analyses with organisms whose genome is not sequenced than by state-of-the-art database searches in an Arabidopsis thaliana database. We consider the novel data analysis workflow an excellent screening method to identify those proteins that evade detection in proteomics experiments as a result of database constraints.     

Deletion of complement factor H-related genes CFHR1 and CFHR3 is associated with atypical hemolytic uremic syndrome

Atypical hemolytic uremic syndrome (aHUS) is associated with defective complement regulation. Disease-associated mutations have been described in the genes encoding the complement regulators complement factor H, membrane cofactor protein, factor B, and factor I. In this study, we show in two independent cohorts of aHUS patients that deletion of two closely related genes, complement factor H-related 1 (CFHR1) and complement factor H-related 3 (CFHR3), increases the risk of aHUS. Amplification analysis and sequencing of genomic DNA of three affected individuals revealed a chromosomal deletion of approximately 84 kb in the RCA gene cluster, resulting in loss of the genes coding for CFHR1 and CFHR3, but leaving the genomic structure of factor H intact. The CFHR1 and CFHR3 genes are flanked by long homologous repeats with long interspersed nuclear elements (retrotransposons) and we suggest that nonallelic homologous recombination between these repeats results in the loss of the two genes. Impaired protection of erythrocytes from complement activation is observed in the serum of aHUS patients deficient in CFHR1 and CFHR3, thus suggesting a regulatory role for CFHR1 and CFHR3 in complement activation. The identification of CFHR1/CFHR3 deficiency in aHUS patients may lead to the design of new diagnostic approaches, such as enhanced testing for these genes.     

Disentangling conformational states of macromolecules in 3D-EM through likelihood optimization

Although three-dimensional electron microscopy (3D-EM) permits structural characterization of macromolecular assemblies in distinct functional states, the inability to classify projections from structurally heterogeneous samples has severely limited its application. We present a maximum likelihood-based classification method that does not depend on prior knowledge about the structural variability, and demonstrate its effectiveness for two macromolecular assemblies with different types of conformational variability: the Escherichia coli ribosome and Simian virus 40 (SV40) large T-antigen.     

Fully automated segmentation and morphometrical analysis of muscle fiber images.

BACKGROUND: Measurement of muscle fiber size and determination of size distribution is important in the assessment of neuromuscular disease. Fiber size estimation by simple inspection is inaccurate and subjective. Manual segmentation and measurement are time-consuming and tedious. We therefore propose an automated image analysis method for objective, reproducible, and time-saving measurement of muscle fibers in routinely hematoxylin-eosin stained cryostat sections. METHODS: The proposed segmentation technique makes use of recent advances in level set based segmentation, where classical edge based active contours are extended by region based cues, such as color and texture. Segmentation and measurement are performed fully automatically. Multiple morphometric parameters, i.e., cross sectional area, lesser diameter, and perimeter are assessed in a single pass. The performance of the computed method was compared to results obtained by manual measurement by experts. RESULTS: The correct classification rate of the computed method was high (98%). Segmentation and measurement results obtained manually or automatically did not reveal any significant differences. CONCLUSIONS: The presented region based active contour approach has been proven to accurately segment and measure muscle fibers. Complete automation minimizes user interaction, thus, batch processing, as well as objective and reproducible muscle fiber morphometry are provided.