Trypanosoma brucei: a model micro-organism to study eukaryotic phospholipid biosynthesis

Although the protozoan parasite, Trypanosoma brucei, can acquire lipids from its environment, recent reports have shown that it is also capable of de novo synthesis of all major phospholipids. Here we provide an overview of the biosynthetic pathways involved in phospholipid formation in T. brucei and highlight differences to corresponding pathways in other eukaryotes, with the aim of promoting trypanosomes as an attractive model organism to study lipid biosynthesis. We show that de novo synthesis of phosphatidylethanolamine involving CDP-activated intermediates is essential in T. brucei and that a reduction in its cellular content affects mitochondrial morphology and ultrastructure. In addition, we highlight that reduced levels of phosphatidylcholine inhibit nuclear division, suggesting a role for phosphatidylcholine formation in the control of cell division. Furthermore, we discuss possible routes leading to phosphatidylserine and cardiolipin formation in T. brucei and review the biosynthesis of phosphatidylinositol, which seems to take place in two separate compartments. Finally, we emphasize that T. brucei represents the only eukaryote so far that synthesizes all three sphingophospholipid classes, sphingomyelin, inositolphosphorylceramide and ethanolaminephosphorylceramide, and that their production is developmentally regulated.

A Drosophila XPD model links cell cycle coordination with neuro-development and suggests links to cancer

XPD functions in transcription, DNA repair and in cell cycle control. Mutations in human XPD (also known as ERCC2) mainly cause three clinical phenotypes: xeroderma pigmentosum (XP), Cockayne syndrome (XP/CS) and trichothiodystrophy (TTD), and only XP patients have a high predisposition to developing cancer. Hence, we developed a fly model to obtain novel insights into the defects caused by individual hypomorphic alleles identified in human XP-D patients. This model revealed that the mutations that displayed the greatest in vivo UV sensitivity in Drosophila did not correlate with those that led to tumor formation in humans. Immunoprecipitations followed by targeted quantitative MS/MS analysis showed how different xpd mutations affected the formation or stability of different transcription factor IIH (TFIIH) subcomplexes. The XP mutants most clearly linked to high cancer risk, Xpd R683W and R601L, showed a reduced interaction with the core TFIIH and also an abnormal interaction with the Cdk-activating kinase (CAK) complex. Interestingly, these two XP alleles additionally displayed high levels of chromatin loss and free centrosomes during the rapid nuclear division phase of the Drosophila embryo. Finally, the xpd mutations showing defects in the coordination of cell cycle timing during the Drosophila embryonic divisions correlated with those human mutations that cause the neurodevelopmental abnormalities and developmental growth defects observed in XP/CS and TTD patients.

Automatic Segmentation of the Eye in 3D Magnetic Resonance Imaging: A novel Statistical Shape Model for treatment planning of Retinoblastoma

Purpose: Proper delineation of ocular anatomy in 3D imaging is a big challenge, particularly when developing treatment plans for ocular diseases. Magnetic Resonance Imaging (MRI) is nowadays utilized in clinical practice for the diagnosis confirmation and treatment planning of retinoblastoma in infants, where it serves as a source of information, complementary to the Fundus or Ultrasound imaging. Here we present a framework to fully automatically segment the eye anatomy in the MRI based on 3D Active Shape Models (ASM), we validate the results and present a proof of concept to automatically segment pathological eyes. Material and Methods: Manual and automatic segmentation were performed on 24 images of healthy children eyes (3.29±2.15 years). Imaging was performed using a 3T MRI scanner. The ASM comprises the lens, the vitreous humor, the sclera and the cornea. The model was fitted by first automatically detecting the position of the eye center, the lens and the optic nerve, then aligning the model and fitting it to the patient. We validated our segmentation method using a leave-one-out cross validation. The segmentation results were evaluated by measuring the overlap using the Dice Similarity Coefficient (DSC) and the mean distance error. Results: We obtained a DSC of 94.90±2.12% for the sclera and the cornea, 94.72±1.89% for the vitreous humor and 85.16±4.91% for the lens. The mean distance error was 0.26±0.09mm. The entire process took 14s on average per eye. Conclusion: We provide a reliable and accurate tool that enables clinicians to automatically segment the sclera, the cornea, the vitreous humor and the lens using MRI. We additionally present a proof of concept for fully automatically segmenting pathological eyes. This tool reduces the time needed for eye shape delineation and thus can help clinicians when planning eye treatment and confirming the extent of the tumor.