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Drosophila melanogaster is an established model for neuroscience research with relevance in biology and medicine. Until recently, research on the Drosophila brain was hindered by the lack of a complete and uniform nomenclature. Recognizing this, Ito et al. (2014) produced an authoritative nomenclature for the adult insect brain, using Drosophila as the reference. Here, we extend this nomenclature to the adult thoracic and abdominal neuromeres, the ventral nerve cord (VNC), to provide an anatomical description of this major component of the Drosophila nervous system. The VNC is the locus for the reception and integration of sensory information and involved in generating most of the locomotor actions that underlie fly behaviors. The aim is to create a nomenclature, definitions, and spatial boundaries for the Drosophila VNC that are consistent with other insects. The work establishes an anatomical framework that provides a powerful tool for analyzing the functional organization of the VNC.

The fruit fly, Drosophila melanogaster, is an established and powerful model system for neuroscience research with wide relevance in biology and medicine. Until recently, research on the Drosophila brain was hindered by the lack of a complete and uniform nomenclature. Recognising this problem, the Insect Brain Name Working Group produced an authoritative hierarchical nomenclature system for the adult insect brain, using Drosophila melanogaster as the reference framework, with other taxa considered to ensure greater consistency and expandability (Ito et al., 2014). Here, we extend this nomenclature system to the sub-gnathal regions of the adult Drosophila nervous system, thus providing a systematic anatomical description of the ventral nervous system (VNS). This portion of the nervous system includes the thoracic and abdominal neuromeres that were not included in the original work and contains the motor circuits that play essential roles in most fly behaviours.

The fruit fly,Drosophila melanogaster, is an established and powerful model system for neuroscience research with wide relevance in biology and medicine. Until recently, research on theDrosophilabrain was hindered by the lack of a complete and uniform nomenclature. Recognising this problem, the Insect Brain Name Working Group produced an authoritative hierarchical nomenclature system for the adult insect brain, usingDrosophila melanogasteras the reference framework, with other taxa considered to ensure greater consistency and expandability (Ito et al., 2014). Here, we extend this nomenclature system to the sub-gnathal regions of the adultDrosophilanervous system, thus providing a systematic anatomical description of the ventral nervous system (VNS). This portion of the nervous system includes the thoracic and abdominal neuromeres that were not included in the original work and contains the motor circuits that play essential roles in most fly behaviours.

An analytical high-throughput method based on gas chromatography/mass spectrometry (GC/MS) was developed for fast metabolome investigation. By parallelization and partial automation the time needed for the preanalytical steps could be reduced. In addition a strong decrease of the relative standard deviation of metabolite concentrations from independent samples on the same microtiter plate from 25 to 13% was achieved. Between different plates the relative standard deviation is comparable to the one observed in standard experiments with shaking flasks. Using a fast GC the time need for the full GC/MS-based metabolome analysis could be decreased from 60 to 18 min per run, allowing the measurement of 72 single samples per day and GC/MS machine. In samples of the model organism Corynebacterium glutamicum more than 1000 peaks in the total ion current could be detected in a single fast GC/MS run of which 650 were strong enough to be quantified. Approximately 150 compounds of these were identified using our metabolite MS-library. Correlation analysis of the concentration vectors of independent wild-type samples raised under the same conditions show very high correlations of 0.99 ± 0.01 (logs). In conclusion this method allows screenings of large mutant libraries for genetically induced metabolic perturbations.