1 Avenue Claude Vellefaux
- Scientific Context:
The human Major Histocompatibility Complex (MHC) is mainly composed of the genes and antigens generating the ABO blood group system and the human leukocyte antigen (HLA) proteins. The ABO system was discovered and understood more than a century ago, and blood transfusion rules that were set up at that time are still followed today to avoid life-threatening immunological adverse events and also apply to transplantation. Differences in donor/patient HLA proteins is one of the major limitations in organ transplantation due to their ubiquitous presence on cells and tissue/organs and the fact that mismatches between donor and patient antigens on the surface epitopes (binding sites) of B and T cells can trigger an immune response in the patient that can ultimately lead to the rejection of the transplanted organ. The HLA system is incredibly more complex than the ABO system, and in addition is mandatory for a proper functioning of the physiological immune response to pathogens and tumor cells. More specifically, HLA proteins serve to present small peptide fragments of “foreign proteins” to T-lymphocytes for the activation of an immune response. The HLA complex is multigenic, having up to 22 distinct proteins per individual, arising from genes identified as A, B, C for class I and DRB1, DRB3 to 5, DQB1, DQA1, DPB1 and DPA1 genes for class II, with the DQ and DP genes giving rise to heterodimeric proteins with two polymorphic chains. The HLA complex is also multiallelic, having >19,000 known genetic variants, leading to >13,000 protein variants that are potentially immunogenic for humoral response B-lymphocytes with donor-specific (DSA) antibodies and/or cellular response T-lymphocytes against “non-self” donor T-cell antigen receptors (TCRs).
Nowadays, DSAs are the main cause of transplant loss (1) due to acute and chronic rejection, because the humoral response cannot be tamed as efficiently as the T-cell response through the use of life-long immuno-suppressive pharmacological treatments initiated at time of the transplant. For example, 50% of kidneys are lost after 12 years, and 20% of recipients have DSAs at 5 years post-transplant. However, despite the potential extreme polymorphism of HLAs, less than 10% of existing alleles are commonly encountered, and it is estimated that “only” less than 1,000 epitopes exist, variously distributed in the mosaic-like HLA proteins (2). Consequently transplants are almost always performed with a significant (but not quantified) a priori level of incompatibility. Intriguingly, despite a mean and median incompatibility level broadly identical for each gene in donor/recipient pairs, the immunogenicity of these genes is different. For example DQ triggers on its own half of the DSAs encountered in the population (3-6).
The appearance of anti-HLA antibodies and their evolution may be studied in the clinical laboratory using the Luminex mean fluorescence intensity (MFI) “single antigen” flow bead assay, where a panel of around 150 common alleles per class are located on beads and incubated with recipients’ sera. This allows the detection and identification of DSA and target epitopes, as well as the estimation of DSA amount and affinity from the MFI (4-6).
The main objective of this project is to understand at the molecular level what causes the immunogenicity of HLA molecules. This will involve performing structural comparisons of previously built 3D models of HLA molecules with the >110,000 antibody MFI profiles generated per class over the past 3.5 years for the >25,000 patients followed in the laboratory (with >30,000 new profiles being added each year). For each donor/recipient pair, HLA typing is available (ranging e.g. from low resolution PCR of genomic DNA to exhaustive next-generation sequencing), and can be compared to the patient’s serum antibody profile. In this way, the overall aim is to categorize this huge database into groups of HLA reactivities, in order to identify mismatches that trigger common (or uncommon) patient sensitization at the antigen, allele, and epitope levels. To extend the resolution of the typing data, a national clinical program has been set up and is underway (PHRC ACORGHLA, 732 kEuros). This database will be extended at the national level, at least doubling the amount of information, as our INSERM laboratory manages 1/3 of the transplantation activity across the whole of France. The HLA typing data of the most informative (most and least immunogenic) donor/recipient combinations will then be compared to the 3D structural data gathered by the CAPSID team in order to “learn” relationships between patient DSA profiles and 3D HLA structures using machine learning techniques in conjunction with structural analysis tools developed by the CAPSID team (7).
The project will primarily focus on B-cell epitopes as tangible immune response data is available in the form of exhaustive serum antibody profiles. But because the structural regions involved in antibody response are also recognized by TCRs, these will also be considered. Indeed, in the presence of a HLA mismatch, donor HLA can give rise to peptides presentable by the recipient’s HLA. Thus a potential future extension of the project is to identify, and perhaps even design, possible peptide HLA inhibitors. In any case, the final objective of the present project is to define which HLA incompatibilities need to be avoided, and which might be permitted, due to their high and low immunogenic potential, in order to extend organ function duration. This objective is becoming increasingly urgent in the context of an aging population where more transplants are required but fewer suitable donors are available.
The successful candidate will be based primarily at the Saint-Louis Hospital/INSERM U976 in Paris, and will visit the Inria Nancy centre on a regular basis.
1- Lefaucheur C, Loupy A. Antibody-Mediated Rejection of Solid-Organ Allografts. N Engl J Med. 2018 Dec 27;379(26):2580-2582.
2- Tambur, A.R., and Claas, F.H. 2015. HLA epitopes as viewed by antibodies: what is it all about? Am J Transplant 15:1148-1154.
3- Cross, A.R., Lion, J., Loiseau, P., Charron, D., Taupin, J.L., Glotz, D., and Mooney, N. 2016. Donor Specific Antibodies are not only directed against HLA-DR: Minding your Ps and Qs. Hum Immunol.
4- Wiebe, C., Pochinco, D., Blydt-Hansen, T.D., Ho, J., Birk, P.E., Karpinski, M., Goldberg, A., Storsley, L.J., Gibson, I.W., Rush, D.N., et al. 2013. Class II HLA epitope matching-A strategy to minimize de novo donor-specific antibody development and improve outcomes. Am J Transplant 13:3114-3122.
5- McCaughan JA, Battle RK, Singh SKS, Tikkanen JM, Moayedi Y, Ross HJ, Singer LG, Keshavjee S, Tinckam KJ. Identification of risk epitope mismatches associated with de novo donor-specific HLA antibody development in cardiothoracic transplantation. Am J Transplant. 2018 Dec;18(12):2924-2933.
6- Snanoudj R, Kamar N, Cassuto E, Caillard S, Metzger M, Merville P, Thierry A, Jollet I, Grimbert P, Anglicheau D, Hazzan M, Choukroun G, Hurault De Ligny B, Janbon B, Vuiblet V, Devys A, Le Meur Y, Delahousse M, Morelon E, Bailly E, Girerd S, Amokrane K, Legendre C, Hertig A, Rondeau E, Taupin JL. Epitope load identifies kidney transplant recipients at risk of allosensitization following minimization of immunosuppression. Kidney Int. 2019 in press.
7- Ritchie, D.W. 2016. Calculating and scoring high quality multiple flexible protein structure alignments. Bioinformatics 32:2650-2658.
- Skills and profile:
Required qualification: Candidates must have a masters degree in computing science, mathematics, or one of the physical sciences. Good programming skills in at least one procedural language such as Python, C, or C++ will be essential. A strong interest in immunology and structural biology would also be highly desirable.
- How to Apply:
The required documents for applying are the following :
- a motivation letter;
- your degree certificates and transcripts for Bachelor and Master (or the last 5 years if not applicable).
- Master thesis (or equivalent) if it is already completed, or a description of the work in progress, otherwise;
- all your publications, if any (it is not expected that you have any).
- At least one recommendation letter from the person who supervises(d) your Master thesis (or research project or internship); you can also send at most two other recommendation letters.
The recommendation letter(s) should be sent directly by their author to the prospective PhD advisor.
All the documents should be sent in at most 2 pdf files; one file should contain the publications, if any, the other file should contain all the other documents. These two files should be sent to your prospective PhD advisor (in addition to the application on the web).
Partial reimbursement of public transport costs
Social security coverage
1982€ gross/month for 1st and 2nd year. 2085€ gross/month for 3rd year.
Monthly salary after taxes: around 1596,05€ for 1st and 2nd year. 1678,99€ for 3rd year. (medical insurance included).