Open positions at CBIB

Postdoc : Investigating White Matter Tract invasion by single-cell sequencing data analysis

Starting date: Jan 2020
Location: Bordeaux, France
Laboratory: Bordeaux Bioinformatics Center (CBiB) 
Address: CBiB 146 Rue Léo Saignat 33076 Bordeaux Cedex

Description :

A post-doctoral position (12 months, extendable) is available in the Bioinformatics team at the IBGC, UMR 5095 CNRS to work with Dr. Macha Nikolski and Dr. Thomas Daubon. The research project consists in developing methods and analyzing human and culture samples by single cell RNA sequencing for understanding invasion processes in glioblastoma.


Glioblastoma (GBM) is the most deadly type of human cancer. Most patients diagnosed with this grade IV malignant glioma survive for about 15 months. Even with optimal treatment, the estimated recurrence rate is more than 90%. Recurrence is mostly caused by the regrowth of highly invasive cells that spread from the tumor bulk and are therefore not removed by resection. A large number of GBM cells are invading around the tumor core. Invasion on blood vessels is a well-described phenomenon, but a majority of cells invade along white matter tracts. This latter mode, also known as perineuronal satellitosis, is not well described in the literature (observed by Scherrer in 1950). Furthermore, the molecular relationship between glioma and white matter tracts remains largely unknown. Recent publications described neurogliomal synapses in glioblastoma (Venkataramani et al, Nature), in pediatric glioma (Venkatesh et al, Nature), or in cerebral metastasis (Zeng et al, Nature), which interconnects the neuronal network to the cancer network. Glutamate influx via NMDAR induces calcium flux into the glioma network, and by consequence, tumor cells are invading the surrounding tissues. Single-cell transcriptomics was performed in the publications related to glioma, and massive amount of data was generated in Venkataramani et al.


By using these data, the candidate will develop a methodology for integrating these already acquired datasets for deciphering molecular and metabolic pathways, used for increasing invasion. Indeed, due to differences in experimental platforms and biological sample batches, the integration of multiple scRNA-seq datasets remains challenging.


These bioinformatics analyses will be extended by integrating newly acquired data, generated by the team of Thomas Daubon (IBGC, UMR 5095 CNRS) for several glioblastoma models in co-culture with neurons or white matter tracts in acute brain slices. Bulk and single-cell transcriptomics will help to elucidate the invasive mechanisms in play.

Skills needed :

  • PhD degree in bioinformatics, high level engineer or equivalent
  • Dedicated, pro-active and with a personal fit into the team
  • Good communication skills that allow productive interactions with biologists and clinicians (e.g. discussing models / analyses choices)
  • Programming skills (R, Python) in Unix environment are essential
  • Prior experience in NGS data analysis is essential, experience in sc-RNAseq data analysis would be a plus
  • Ability to communicate in both spoken and written English
  • Autonomous and rigorous with a critical mind

CONTACTS:

Macha Nikolski - macha.nikolski@u-bordeaux.fr 

Thomas Daubon - thomas.daubon@u-bordeaux.fr

 

Internship : Evolution of pulmonary microbiote and mycobiote in patients with mucoviscidosis treated by LUMACAFTOR / IVACAFTOR

Starting date: Jan 2020
Location: Bordeaux, France
Laboratory: Bordeaux Bioinformatics Center (CBiB) 
Address: CBiB 146 Rue Léo Saignat 33076 Bordeaux Cedex

Description:

Cystic fibrosis is the most common serious genetic disease and affects nearly 7000 people in France. It is the consequence of mutations of the CFTR gene, coding for a protein involved in the fluid-electrolyte balance of secretions. The most common mutation is the DeltaF508 mutation (40% of patients in the homozygous state and 60% in the heterozygous state). Mutated, the CFTR protein will be responsible for an accumulation of dehydrated and viscous secretions in the organs, including the lungs. Disturbances of the bacterial and fungal microbiota (mycobiota) occur throughout the disease and are accompanied by chronic colonization with different pathogens. Chronic colonization with Pseudomonas aeruginosa marks, in particular, an evolutionary turn of the disease and is associated with a deterioration of the respiratory function. In recent years, protein therapies have developed, directly targeting defects in the CFTR protein. However, the impact of this treatment on the pulmonary microbiota and mycobiota has not yet been studied. Our hypothesis is that the restoration, even partial, of the functionality of the CFTR protein under lumacaftor / ivacaftor allows an improvement of the hydration of the secretion and the mucociliary clearance; and should result in reduction / eradication of specific bacterial and / or fungal pathogens (such as P. aeruginosa, A. fumigatus, Candida albicans, ...).

The project proposal for a Master 2 internship aims at developing, under the supervision of  bioinformaticians and clinicians approaches for the analysis of microbiome and mycobiome data collected from pulmonary samples. The main objective of this observational study of CF patients under the LUMACAFTOR-IVACAFTOR treatment is to show that even partial changes in the hydration of pulmonary secretions (mucus) promote a change in pulmonary microbiota and mycobiota, which could then to approach the characteristics of the microbiota "healthy type" (with in particular a decrease of specific pathogens cited previously. Furthermore, analytical approaches will be developed: (i) to study the effect at 6 months of treatment with lumacaftor / ivacaftor on pulmonary inflammation (evaluated by the measurement of pulmonary calprotectin); (ii) to study the co-evolution under lumacaftor / ivacaftor of inflammation and microbiota (bacterial and fungal) at the pulmonary level;(iii) to study the evolution over time of bacterial and fungal microbial community (alpha and betadiversity); Analysis of bacteria / fungi / clinical data networks and comparison of different bacterial and fungal assignment pipelines (cf Pauvert et al., Fungal Ecology, 2019), will also be included.

 

Skills needed :

The expected MSc candidate will justify training in bioinformatics and be familiar with a Linux environment. The development will be mainly in R for the statistical parts and visualizations, and Python and Bash for the workflow part. Knowledge of the main types of genomic and genetic data would be desirable. The candidate will benefit from an interdisciplinary environment, including biologists, clinicians, computer scientists and bioinformaticians.

CONTACTS:

Macha Nikolski - macha.nikolski@u-bordeaux.fr

Benjamin Dartigues- benjamin.dartigues@u-bordeaux.fr

Laurence Delhaes - laurence.delhaes@gmail.com 

Raphael Enaud - raphael_enaud@yahoo.fr