Genotype List String: a grammar for describing HLA and KIR genotyping results in a text string

Knowledge of an individual's human leukocyte antigen (HLA) genotype is essential for modern medical genetics, and is crucial for hematopoietic stem cell and solid-organ transplantation. However, the high levels of polymorphism known for the HLA genes make it difficult to generate an HLA genotype that unambiguously identifies the alleles that are present at a given HLA locus in an individual. For the last 20 years, the histocompatibility and immunogenetics community has recorded this HLA genotyping ambiguity using allele codes developed by the National Marrow Donor Program (NMDP). While these allele codes may have been effective for recording an HLA genotyping result when initially developed, their use today results in increased ambiguity in an HLA genotype, and they are no longer suitable in the era of rapid allele discovery and ultra-high allele polymorphism. Here, we present a text string format capable of fully representing HLA genotyping results. This Genotype List (GL) String format is an extension of a proposed standard for reporting killer-cell immunoglobulin-like receptor (KIR) genotype data that can be applied to any genetic data that use a standard nomenclature for identifying variants. The GL String format uses a hierarchical set of operators to describe the relationships between alleles, lists of possible alleles, phased alleles, genotypes, lists of possible genotypes, and multilocus unphased genotypes, without losing typing information or increasing typing ambiguity. When used in concert with appropriate tools to create, exchange, and parse these strings, we anticipate that GL Strings will replace NMDP allele codes for reporting HLA genotypes

A comparative reference study for the validation of HLA-matching algorithms in the search for allogeneic hematopoietic stem cell donors and cord blood units

The accuracy of human leukocyte antigen (HLA)-matching algorithms is a prerequisite for the correct and efficient identification of optimal unrelated donors for patients requiring hematopoietic stem cell transplantation. The goal of this World Marrow Donor Association study was to validate established matching algorithms from different international donor registries by challenging them with simulated input data and subsequently comparing the output. This experiment addressed three specific aspects of HLA matching using different data sets for tasks of increasing complexity. The first two tasks targeted the traditional matching approach identifying discrepancies between patient and donor HLA genotypes by counting antigen and allele differences. Contemporary matching procedures predicting the probability for HLA identity using haplotype frequencies were addressed by the third task. In each task, the identified disparities between the results of the participating computer programs were analyzed, classified and quantified. This study led to a deep understanding of the algorithms participating and finally produced virtually identical results. The unresolved discrepancies total to less than 1%, 4% and 2% for the three tasks and are mostly because of individual decisions in the design of the programs. Based on these findings, reference results for the three input data sets were compiled that can be used to validate future matching algorithms and thus improve the quality of the global donor search process

Rethinking Proteasome Evolution: Two Novel Bacterial Proteasomes

The proteasome is a multisubunit structure that degrades proteins. Protein degradation is an essential component of regulation because proteins can become misfolded, damaged, or unnecessary. Proteasomes and their homologues vary greatly in complexity: from HslV (heat shock locus v), which is encoded by 1 gene in bacteria, to the eukaryotic 20S proteasome, which is encoded by more than 14 genes. Despite this variation in complexity, all the proteasomes are composed of homologous subunits. We searched 238 complete bacterial genomes for structures related to the proteasome and found evidence of two novel groups of bacterial proteasomes. The first, which we name Anbu, is sparsely distributed among cyanobacteria and proteobacteria. We hypothesize that Anbu must be very ancient because of its distribution within the cyanobacteria, and that it has been lost in many more recent species. We also present evidence for a fourth type of bacterial proteasome found in a few β-proteobacteria, which we call β-proteobacteria proteasome homologue (BPH). Sequence and structural analyses show that Anbu and BPH are both distinct from known bacterial proteasomes but have homologous structures. Anbu is encoded by one gene, so we postulate a duplication of Anbu created the 20S proteasome. Anbu’s function appears to be related to transglutaminase activity, not the general stress response associated with HslV. We have found different combinations of Anbu, BPH, and HslV within these bacterial genomes, which raises questions about specialized protein degradation systems

Amyloid-Associated Nucleic Acid Hybridisation

Nucleic acids promote amyloid formation in diseases including Alzheimer's and Creutzfeldt-Jakob disease. However, it remains unclear whether the close interactions between amyloid and nucleic acid allow nucleic acid secondary structure to play a role in modulating amyloid structure and function. Here we have used a simplified system of short basic peptides with alternating hydrophobic and hydrophilic amino acid residues to study nucleic acid - amyloid interactions. Employing biophysical techniques including X-ray fibre diffraction, circular dichroism spectroscopy and electron microscopy we show that the polymerized charges of nucleic acids concentrate and enhance the formation of amyloid from short basic peptides, many of which would not otherwise form fibres. In turn, the amyloid component binds nucleic acids and promotes their hybridisation at concentrations below their solution Kd, as shown by time-resolved FRET studies. The self-reinforcing interactions between peptides and nucleic acids lead to the formation of amyloid nucleic acid (ANA) fibres whose properties are distinct from their component polymers. In addition to their importance in disease and potential in engineering, ANA fibres formed from prebiotically-produced peptides and nucleic acids may have played a role in early evolution, constituting the first entities subject to Darwinian evolution

Systemic IL-12 Administration Alters Hepatic Dendritic Cell Stimulation Capabilities

The liver is an immunologically unique organ containing tolerogenic dendritic cells (DC) that maintain an immunosuppressive microenvironment. Although systemic IL-12 administration can improve responses to tumors, the effects of IL-12-based treatments on DC, in particular hepatic DC, remain incompletely understood. In this study, we demonstrate systemic IL-12 administration induces a 2–3 fold increase in conventional, but not plasmacytoid, DC subsets in the liver. Following IL-12 administration, hepatic DC became more phenotypically and functionally mature, resembling the function of splenic DC, but differed as compared to their splenic counterparts in the production of IL-12 following co-stimulation with toll-like receptor (TLR) agonists. Hepatic DCs from IL-12 treated mice acquired enhanced T cell proliferative capabilities similar to levels observed using splenic DCs. Furthermore, IL-12 administration preferentially increased hepatic T cell activation and IFNγ expression in the RENCA mouse model of renal cell carcinoma. Collectively, the data shows systemic IL-12 administration enables hepatic DCs to overcome at least some aspects of the inherently suppressive milieu of the hepatic environment that could have important implications for the design of IL-12-based immunotherapeutic strategies targeting hepatic malignancies and infections

Disruption of a mitochondrial protease machinery in Plasmodium falciparum is an intrinsic signal for parasite cell death

The ATP-dependent ClpQY protease system in Plasmodium falciparum is a prokaryotic machinery in the parasite. In the present study, we have identified the complete ClpQY system in P. falciparum and elucidated its functional importance in survival and growth of asexual stage parasites. We characterized the interaction of P. falciparum ClpQ protease (PfClpQ) and PfClpY ATPase components, and showed that a short stretch of residues at the C terminus of PfClpY has an important role in this interaction; a synthetic peptide corresponding to this region antagonizes this interaction and interferes with the functioning of this machinery in the parasite. Disruption of ClpQY function by this peptide caused hindrance in the parasite growth and maturation of asexual stages of parasites. Detailed analyses of cellular effects in these parasites showed features of apoptosis-like cell death. The peptide-treated parasites showed mitochondrial dysfunction and loss of mitochondrial membrane potential. Dysfunctioning of mitochondria initiated a cascade of reactions in parasites, including activation of VAD–FMK-binding proteases and nucleases, which resulted in apoptosis-like cell death. These results show functional importance of mitochondrial proteases in the parasite and involvement of mitochondria in programmed cell death in the malaria parasites

SDCCAG8 Interacts with RAB Effector Proteins RABEP2 and ERC1 and Is Required for Hedgehog Signaling

Recessive mutations in the SDCCAG8 gene cause a nephronophthisis-related ciliopathy with Bardet-Biedl syndrome-like features in humans. Our previous characterization of the orthologous Sdccag8gt/gt mouse model recapitulated the retinal-renal disease phenotypes and identified impaired DNA damage response signaling as an underlying disease mechanism in the kidney. However, several other phenotypic and mechanistic features of Sdccag8gt/gt mice remained unexplored. Here we show that Sdccag8gt/gt mice exhibit developmental and structural abnormalities of the skeleton and limbs, suggesting impaired Hedgehog (Hh) signaling. Indeed, cell culture studies demonstrate the requirement of SDCCAG8 for ciliogenesis and Hh signaling. Using an affinity proteomics approach, we demonstrate that SDCCAG8 interacts with proteins of the centriolar satellites (OFD1, AZI1), of the endosomal sorting complex (RABEP2, ERC1), and with non-muscle myosin motor proteins (MYH9, MYH10, MYH14) at the centrosome. Furthermore, we show that RABEP2 localization at the centrosome is regulated by SDCCAG8. siRNA mediated RABEP2 knockdown in hTERT-RPE1 cells leads to defective ciliogenesis, indicating a critical role for RABEP2 in this process. Together, this study identifies several centrosome-associated proteins as novel SDCCAG8 interaction partners, and provides new insights into the function of SDCCAG8 at this structure

Breaking point: the genesis and impact of structural variation in tumours

Somatic structural variants undoubtedly play important roles in driving tumourigenesis. This is evident despite the substantial technical challenges that remain in accurately detecting structural variants and their breakpoints in tumours and in spite of our incomplete understanding of the impact of structural variants on cellular function. Developments in these areas of research contribute to the ongoing discovery of structural variation with a clear impact on the evolution of the tumour and on the clinical importance to the patient. Recent large whole genome sequencing studies have reinforced our impression of each tumour as a unique combination of mutations but paradoxically have also discovered similar genome-wide patterns of single-nucleotide and structural variation between tumours. Statistical methods have been developed to deconvolute mutation patterns, or signatures, that recur across samples, providing information about the mutagens and repair processes that may be active in a given tumour. These signatures can guide treatment by, for example, highlighting vulnerabilities in a particular tumour to a particular chemotherapy. Thus, although the complete reconstruction of the full evolutionary trajectory of a tumour genome remains currently out of reach, valuable data are already emerging to improve the treatment of cancer