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In silico Derivation of HLA-Specific Alloreactivity Potential from Whole Exome Sequencing of Stem-Cell Transplant Donors and Recipients: Understanding the Quantitative Immunobiology of Allogeneic Transplantation.

Jameson-Lee M, Koparde V, Griffith P, Scalora AF, Sampson JK, Khalid H, Sheth NU, Batalo M, Serrano MG, Roberts CH, Hess ML, Buck GA, Neale MC, Manjili MH, Toor AA - Front Immunol (2014)

Bottom Line: All the possible nonameric peptides incorporating the variant amino acid resulting from these SNPs were interrogated in silico for their likelihood to be presented by the HLA class I molecules using the Immune Epitope Database stabilized matrix method (SMM) and NetMHCpan algorithms.A similar library of presented peptides was identified when the data were interrogated using the NetMHCpan algorithm.The bioinformatic algorithm presented here demonstrates that there may be a high level of mHA variation in HLA-matched individuals, constituting a HLA-specific alloreactivity potential.

View Article: PubMed Central - PubMed

Affiliation: Stem Cell Transplant Program, Massey Cancer Center, Virginia Commonwealth University , Richmond, VA , USA.

ABSTRACT
Donor T-cell mediated graft versus host (GVH) effects may result from the aggregate alloreactivity to minor histocompatibility antigens (mHA) presented by the human leukocyte antigen (HLA) molecules in each donor-recipient pair undergoing stem-cell transplantation (SCT). Whole exome sequencing has previously demonstrated a large number of non-synonymous single nucleotide polymorphisms (SNP) present in HLA-matched recipients of SCT donors (GVH direction). The nucleotide sequence flanking each of these SNPs was obtained and the amino acid sequence determined. All the possible nonameric peptides incorporating the variant amino acid resulting from these SNPs were interrogated in silico for their likelihood to be presented by the HLA class I molecules using the Immune Epitope Database stabilized matrix method (SMM) and NetMHCpan algorithms. The SMM algorithm predicted that a median of 18,396 peptides weakly bound HLA class I molecules in individual SCT recipients, and 2,254 peptides displayed strong binding. A similar library of presented peptides was identified when the data were interrogated using the NetMHCpan algorithm. The bioinformatic algorithm presented here demonstrates that there may be a high level of mHA variation in HLA-matched individuals, constituting a HLA-specific alloreactivity potential.

No MeSH data available.


Related in: MedlinePlus

Bioinformatics workflow for calculating HLA-specific alloreactivity potential in individual DRP. Starting with donor and recipient whole exome sequence data, non-synonymous SNP with a GVH vector (nsSNPGVH) were identified, and peptide fragments generated using the ANNOVAR software package. These peptides, together with HLA data (Table 1) were then analyzed with IEDB SMM and NetMHCpan algorithms separately. Individual DRP binding data were then analyzed and candidate mHAs cataloged.
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Figure 1: Bioinformatics workflow for calculating HLA-specific alloreactivity potential in individual DRP. Starting with donor and recipient whole exome sequence data, non-synonymous SNP with a GVH vector (nsSNPGVH) were identified, and peptide fragments generated using the ANNOVAR software package. These peptides, together with HLA data (Table 1) were then analyzed with IEDB SMM and NetMHCpan algorithms separately. Individual DRP binding data were then analyzed and candidate mHAs cataloged.

Mentions: To derive the amino acid sequence of the oligopeptides, i.e., potential mHA, resulting from these nsSNPs and their binding affinity to the relevant HLA in each DRP, a bioinformatics pipeline was developed. This pipeline has the following components: (1) determine nsSNPGVH between the exomes of transplant donors and recipients; (2) generate putative immunogenic peptides in silico from these genomic differences; and (3) analyze the binding affinity of these polymorphic peptides to the HLA in that individual (Figure 1). This third step estimates the likelihood of these peptides to be presented by the six patient-specific HLA class I molecules to determine candidate mHA. A complete description of this bioinformatic pipeline follows.


In silico Derivation of HLA-Specific Alloreactivity Potential from Whole Exome Sequencing of Stem-Cell Transplant Donors and Recipients: Understanding the Quantitative Immunobiology of Allogeneic Transplantation.

Jameson-Lee M, Koparde V, Griffith P, Scalora AF, Sampson JK, Khalid H, Sheth NU, Batalo M, Serrano MG, Roberts CH, Hess ML, Buck GA, Neale MC, Manjili MH, Toor AA - Front Immunol (2014)

Bioinformatics workflow for calculating HLA-specific alloreactivity potential in individual DRP. Starting with donor and recipient whole exome sequence data, non-synonymous SNP with a GVH vector (nsSNPGVH) were identified, and peptide fragments generated using the ANNOVAR software package. These peptides, together with HLA data (Table 1) were then analyzed with IEDB SMM and NetMHCpan algorithms separately. Individual DRP binding data were then analyzed and candidate mHAs cataloged.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4222229&req=5

Figure 1: Bioinformatics workflow for calculating HLA-specific alloreactivity potential in individual DRP. Starting with donor and recipient whole exome sequence data, non-synonymous SNP with a GVH vector (nsSNPGVH) were identified, and peptide fragments generated using the ANNOVAR software package. These peptides, together with HLA data (Table 1) were then analyzed with IEDB SMM and NetMHCpan algorithms separately. Individual DRP binding data were then analyzed and candidate mHAs cataloged.
Mentions: To derive the amino acid sequence of the oligopeptides, i.e., potential mHA, resulting from these nsSNPs and their binding affinity to the relevant HLA in each DRP, a bioinformatics pipeline was developed. This pipeline has the following components: (1) determine nsSNPGVH between the exomes of transplant donors and recipients; (2) generate putative immunogenic peptides in silico from these genomic differences; and (3) analyze the binding affinity of these polymorphic peptides to the HLA in that individual (Figure 1). This third step estimates the likelihood of these peptides to be presented by the six patient-specific HLA class I molecules to determine candidate mHA. A complete description of this bioinformatic pipeline follows.

Bottom Line: All the possible nonameric peptides incorporating the variant amino acid resulting from these SNPs were interrogated in silico for their likelihood to be presented by the HLA class I molecules using the Immune Epitope Database stabilized matrix method (SMM) and NetMHCpan algorithms.A similar library of presented peptides was identified when the data were interrogated using the NetMHCpan algorithm.The bioinformatic algorithm presented here demonstrates that there may be a high level of mHA variation in HLA-matched individuals, constituting a HLA-specific alloreactivity potential.

View Article: PubMed Central - PubMed

Affiliation: Stem Cell Transplant Program, Massey Cancer Center, Virginia Commonwealth University , Richmond, VA , USA.

ABSTRACT
Donor T-cell mediated graft versus host (GVH) effects may result from the aggregate alloreactivity to minor histocompatibility antigens (mHA) presented by the human leukocyte antigen (HLA) molecules in each donor-recipient pair undergoing stem-cell transplantation (SCT). Whole exome sequencing has previously demonstrated a large number of non-synonymous single nucleotide polymorphisms (SNP) present in HLA-matched recipients of SCT donors (GVH direction). The nucleotide sequence flanking each of these SNPs was obtained and the amino acid sequence determined. All the possible nonameric peptides incorporating the variant amino acid resulting from these SNPs were interrogated in silico for their likelihood to be presented by the HLA class I molecules using the Immune Epitope Database stabilized matrix method (SMM) and NetMHCpan algorithms. The SMM algorithm predicted that a median of 18,396 peptides weakly bound HLA class I molecules in individual SCT recipients, and 2,254 peptides displayed strong binding. A similar library of presented peptides was identified when the data were interrogated using the NetMHCpan algorithm. The bioinformatic algorithm presented here demonstrates that there may be a high level of mHA variation in HLA-matched individuals, constituting a HLA-specific alloreactivity potential.

No MeSH data available.


Related in: MedlinePlus