Identification of high-risk amino-acid substitutions in hematopoietic cell transplantation: a challenging task.

Allogeneic hematopoietic cell transplantation (HCT) offers the potential to cure hematologic malignancies. In the absence of an HLA-matched donor, HLA mismatched unrelated donors may be used, although risks of GvHD and treatment-related mortality (TRM) are higher. Identification and avoidance of amino-acid substitution and position types (AASPT) conferring higher risks of TRM and GvHD would potentially improve the success of transplantation from single HLA mismatched unrelated donors. Using random forest and logistic regression analyses, we identified 19 AASPT associated with greater risks for at least one adverse transplant outcome: grade III-IV acute GvHD, TRM, lower disease-free survival or worse overall survival relative to HLA-matched unrelated donors and to other AASPT. When tested in an independent validation cohort of 3530 patients, none of the AASPT from the training set were validated as high risk, however. Review of the literature shows that failure to validate original observations is the rule and not the exception in immunobiology and emphasizes the importance of independent validation before clinical application. Our current data do not support avoiding any specific class I AASPT for unrelated donors. Additional studies should be performed to fully understand the role of AASPT in HCT outcomes.

The Human Proteome Organization Chromosome 6 Consortium: integrating chromosome-centric and biology/disease driven strategies.

The Human Proteome Project (HPP) is designed to generate a comprehensive map of the protein-based molecular architecture of the human body, to provide a resource to help elucidate biological and molecular function, and to advance diagnosis and treatment of diseases. Within this framework, the chromosome-based HPP (C-HPP) has allocated responsibility for mapping individual chromosomes by country or region, while the biology/disease HPP (B/D-HPP) coordinates these teams in cross-functional disease-based groups. Chromosome 6 (Ch6) provides an excellent model for integration of these two tasks. This metacentric chromosome has a complement of 1002-1034 genes that code for known, novel or putative proteins. Ch6 is functionally associated with more than 120 major human diseases, many with high population prevalence, devastating clinical impact and profound societal consequences. The unique combination of genomic, proteomic, metabolomic, phenomic and health services data being drawn together within the Ch6 program has enormous potential to advance personalized medicine by promoting robust biomarkers, subunit vaccines and new drug targets. The strong liaison between the clinical and laboratory teams, and the structured framework for technology transfer and health policy decisions within Canada will increase the speed and efficacy of this transition, and the value of this translational research. BIOLOGICAL SIGNIFICANCE: Canada has been selected to play a leading role in the international Human Proteome Project, the global counterpart of the Human Genome Project designed to understand the structure and function of the human proteome in health and disease. Canada will lead an international team focusing on chromosome 6, which is functionally associated with more than 120 major human diseases, including immune and inflammatory disorders affecting the brain, skeletal system, heart and blood vessels, lungs, kidney, liver, gastrointestinal tract and endocrine system. Many of these chronic and persistent diseases have a high population prevalence, devastating clinical impact and profound societal consequences. As a result, they impose a multi-billion dollar economic burden on Canada and on all advanced societies through direct costs of patient care, the loss of health and productivity, and extensive caregiver burden. There is no definitive treatment at the present time for any of these disorders. The manuscript outlines the research which will involve a systematic assessment of all chromosome 6 genes, development of a knowledge base, and development of assays and reagents for all chromosome 6 proteins. We feel that the informatic infrastructure and MRM assays developed will place the chromosome 6 consortium in an excellent position to be a leading player in this major international research initiative. This article is part of a Special Issue: Can Proteomics Fill the Gap Between Genomics and Phenotypes?

Identification by random forest method of HLA class I amino acid substitutions associated with lower survival at day 100 in unrelated donor hematopoietic cell transplantation.

The identification of important amino acid substitutions associated with low survival in hematopoietic cell transplantation (HCT) is hampered by the large number of observed substitutions compared with the small number of patients available for analysis. Random forest analysis is designed to address these limitations. We studied 2107 HCT recipients with good or intermediate risk hematological malignancies to identify HLA class I amino acid substitutions associated with reduced survival at day 100 post transplant. Random forest analysis and traditional univariate and multivariate analyses were used. Random forest analysis identified amino acid substitutions in 33 positions that were associated with reduced 100 day survival, including HLA-A 9, 43, 62, 63, 76, 77, 95, 97, 114, 116, 152, 156, 166 and 167; HLA-B 97, 109, 116 and 156; and HLA-C 6, 9, 11, 14, 21, 66, 77, 80, 95, 97, 99, 116, 156, 163 and 173. In all 13 had been previously reported by other investigators using classical biostatistical approaches. Using the same data set, traditional multivariate logistic regression identified only five amino acid substitutions associated with lower day 100 survival. Random forest analysis is a novel statistical methodology for analysis of HLA mismatching and outcome studies, capable of identifying important amino acid substitutions missed by other methods.

Crystal structure of fatty acid/phospholipid synthesis protein PlsX from Enterococcus faecalis.

PlsX is a key enzyme that coordinates the production of fatty acids and membrane phospholipids. The plsX gene is co-localized with a bacterial fab gene cluster which encodes several key fatty acid biosynthetic enzymes. The protein is a member of a large, conserved protein family (Pfam02504) found exclusively in bacteria. The PlsX sequence homologues include both phosphate acetyltransferases and phosphate butaryltransferases that catalyze the transfer of an acetyl or butaryl group to orthophosphate. We have determined the crystal structure of PlsX from the human pathogen Enterococcus faecalis. PlsX is a alpha/beta/alpha sandwich that resembles a Rossmann fold and forms a dimer. A putative catalytic site has been identified within a deep groove on the interface between monomers. This site showed strong surface similarity to epimerases and reductases. It was recently proposed that PlsX is a phosphate acyltransferase that catalyzes the formation of acyl-phosphate from the acyl-acyl carrier protein; however the specific biochemical function of the PlsX protein awaits further experimental scrutiny.

Topology independent protein structural alignment.

BACKGROUND: Identifying structurally similar proteins with different chain topologies can aid studies in homology modeling, protein folding, protein design, and protein evolution. These include circular permuted protein structures, and the more general cases of non-cyclic permutations between similar structures, which are related by non-topological rearrangement beyond circular permutation. We present a method based on an approximation algorithm that finds sequence-order independent structural alignments that are close to optimal. We formulate the structural alignment problem as a special case of the maximum-weight independent set problem, and solve this computationally intensive problem approximately by iteratively solving relaxations of a corresponding integer programming problem. The resulting structural alignment is sequence order independent. Our method is also insensitive to insertions, deletions, and gaps. RESULTS: Using a novel similarity score and a statistical model for significance p-value, we are able to discover previously unknown circular permuted proteins between nucleoplasmin-core protein and auxin binding protein, between aspartate rasemase and 3-dehydrogenate dehydralase, as well as between migration inhibition factor and arginine repressor which involves an additional strand-swapping. We also report the finding of non-cyclic permuted protein structures existing in nature between AML1/core binding factor and ribofalvin synthase. Our method can be used for large scale alignment of protein structures regardless of the topology. CONCLUSION: The approximation algorithm introduced in this work can find good solutions for the problem of protein structure alignment. Furthermore, this algorithm can detect topological differences between two spatially similar protein structures. The alignment between MIF and the arginine repressor demonstrates our algorithm's ability to detect structural similarities even when spatial rearrangement of structural units has occurred. The effectiveness of our method is also demonstrated by the discovery of previously unknown circular permutations. In addition, we report in this study the finding of a naturally occurring non-cyclic permuted protein between AML1/Core Binding Factor chain F and riboflavin synthase chain A.