D. Brent Weatherly

CD8+ T-Cell Responses to Trypanosoma cruzi Are Highly Focused on Strain-Variant trans-Sialidase Epitopes

CD8+ T cells are crucial for control of a number of medically important protozoan parasites, including Trypanosoma cruzi, the agent of human Chagas disease. Yet, in contrast to the wealth of information from viral and bacterial infections, little is known about the antigen specificity or the general development of effector and memory T-cell responses in hosts infected with protozoans. In this study we report on a wide-scale screen for the dominant parasite peptides recognized by CD8+ T cells in T. cruzi–infected mice and humans. This analysis demonstrates that in both hosts the CD8+ T-cell response is highly focused on epitopes encoded by members of the large trans-sialidase family of genes. Responses to a restricted set of immunodominant peptides were especially pronounced in T. cruzi–infected mice, with more than 30% of the CD8+ T-cell response at the peak of infection specific for two major groups of trans-sialidase peptides. Experimental models also demonstrated that the dominance patterns vary depending on the infective strain of T. cruzi, suggesting that immune evasion may be occurring at a population rather than single-parasite level.

A Heuristic Method for Assigning a False-discovery Rate for Protein Identifications from Mascot Database Search Results

MS/MS and database searching has emerged as a valuable technology for rapidly analyzing protein expression, localization, and post-translational modifications. The probability-based search engine Mascot has found widespread use as a tool to correlate tandem mass spectra with peptides in a sequence database. Although the Mascot scoring algorithm provides a probability-based model for peptide identification, the independent peptide scores do not correlate with the significance of the proteins to which they match. Herein, we describe a heuristic method for organizing proteins identified at a specified false-discovery rate using Mascot-matched peptides. We call this method PROVALT, and it uses peptide matches from a random database to calculate false-discovery rates for protein identifications and reduces a complex list of peptide matches to a nonredundant list of homologous protein groups. This method was evaluated using Mascot-identified peptides from a Trypanosoma cruzi epimastigote whole-cell lysate, which was separated by multidimensional LC and analyzed by MS/MS. PROVALT was then compared with the two traditional methods of protein identification when using Mascot, the single peptide score and cumulative protein score methods, and was shown to be superior to both in regards to the number of proteins identified and the inclusion of lower scoring nonrandom peptide matches.

The steady-state transcriptome of the four major life-cycle stages of Trypanosoma cruzi

BackgroundChronic chagasic cardiomyopathy is a debilitating and frequently fatal outcome of human infection with the protozoan parasite, Trypanosoma cruzi. Microarray analysis of gene expression during the T. cruzi life-cycle could be a valuable means of identifying drug and vaccine targets based on their appropriate expression patterns, but results from previous microarray studies in T. cruzi and related kinetoplastid parasites have suggested that the transcript abundances of most genes in these organisms do not vary significantly between life-cycle stages.ResultsIn this study, we used whole genome, oligonucleotide microarrays to globally determine the extent to which T. cruzi regulates mRNA relative abundances over the course of its complete life-cycle. In contrast to previous microarray studies in kinetoplastids, we observed that relative transcript abundances for over 50% of the genes detected on the T. cruzi microarrays were significantly regulated during the T. cruzi life-cycle. The significant regulation of 25 of these genes was confirmed by quantitative reverse-transcriptase PCR (qRT-PCR). The T. cruzi transcriptome also mirrored published protein expression data for several functional groups. Among the differentially regulated genes were members of paralog clusters, nearly 10% of which showed divergent expression patterns between cluster members.ConclusionTaken together, these data support the conclusion that transcript abundance is an important level of gene expression regulation in T. cruzi. Thus, microarray analysis is a valuable screening tool for identifying stage-regulated T. cruzi genes and metabolic pathways.

Chromosome level assembly of the hybrid Trypanosoma cruzi genome.

BackgroundIn contrast to the essentially fully assembled genome sequences of the kinetoplastid pathogens Leishmania major and Trypanosoma brucei the assembly of the Trypanosoma cruzi genome has been hindered by its repetitive nature and the fact that the reference strain (CL Brener) is a hybrid of two distinct lineages. In this work, the majority of the contigs and scaffolds were assembled into pairs of homologous chromosomes based on predicted parental haplotype, inference from TriTryp synteny maps and the use of end sequences from T. cruzi BAC libraries.ResultsUltimately, 41 pairs of chromosomes were assembled using this approach, a number in agreement with the predicted number of T. cruzi chromosomes based upon pulse field gel analysis, with over 90% (21133 of 23216) of the genes annotated in the genome represented. The approach was substantiated through the use of Southern blot analysis to confirm the mapping of BAC clones using as probes the genes they are predicted to contain, and each chromosome construction was visually validated to ensure sufficient evidence was present to support the organization. While many members of large gene families are incorporated into the chromosome assemblies, the majority of genes excluded from the chromosomes belong to gene families, as these genes are frequently impossible to accurately position.ConclusionNow assembled, these chromosomes bring T. cruzi to the same level of organization as its kinetoplastid relatives and have been used as the basis for the T. cruzi genome in TriTrypDB, a trypanosome database of EuPathDB. In addition, they will provide the foundation for analyses such as reverse genetics, where the location of genes and their alleles and/or paralogues is necessary and comparative genome hybridization analyses (CGH), where a chromosome-level view of the genome is ideal.

High Throughput Selection of Effective Serodiagnostics for Trypanosoma cruzi infection

Background Diagnosis of Trypanosoma cruzi infection by direct pathogen detection is complicated by the low parasite burden in subjects persistently infected with this agent of human Chagas disease. Determination of infection status by serological analysis has also been faulty, largely due to the lack of well-characterized parasite reagents for the detection of anti-parasite antibodies. Methods In this study, we screened more than 400 recombinant proteins of T. cruzi, including randomly selected and those known to be highly expressed in the parasite stages present in mammalian hosts, for the ability to detect anti-parasite antibodies in the sera of subjects with confirmed or suspected T. cruzi infection. Findings A set of 16 protein groups were identified and incorporated into a multiplex bead array format which detected 100% of >100 confirmed positive sera and also documented consistent, strong and broad responses in samples undetected or discordant using conventional serologic tests. Each serum had a distinct but highly stable reaction pattern. This diagnostic panel was also useful for monitoring drug treatment efficacy in chronic Chagas disease. Conclusions These results substantially extend the variety and quality of diagnostic targets for Chagas disease and offer a useful tool for determining treatment success or failure.

Widespread, focal copy number variations (CNV) and whole chromosome aneuploidies in Trypanosoma cruzi strains revealed by array comparative genomic hybridization

BackgroundTrypanosoma cruzi is a protozoan parasite and the etiologic agent of Chagas disease, an important public health problem in Latin America. T. cruzi is diploid, almost exclusively asexual, and displays an extraordinarily diverse population structure both genetically and phenotypically. Yet, to date the genotypic diversity of T. cruzi and its relationship, if any, to biological diversity have not been studied at the whole genome level.ResultsIn this study, we used whole genome oligonucleotide tiling arrays to compare gene content in biologically disparate T. cruzi strains by comparative genomic hybridization (CGH). We observed that T. cruzi strains display widespread and focal copy number variations (CNV) and a substantially greater level of diversity than can be adequately defined by the current genetic typing methods. As expected, CNV were particularly frequent in gene family-rich regions containing mucins and trans-sialidases but were also evident in core genes. Gene groups that showed little variation in copy numbers among the strains tested included those encoding protein kinases and ribosomal proteins, suggesting these loci were less permissive to CNV. Moreover, frequent variation in chromosome copy numbers were observed, and chromosome-specific CNV signatures were shared by genetically divergent T. cruzi strains.ConclusionsThe large number of CNV, over 4,000, reported here uphold at a whole genome level the long held paradigm of extraordinary genome plasticity among T. cruzi strains. Moreover, the fact that these heritable markers do not parse T. cruzi strains along the same lines as traditional typing methods is strongly suggestive of genetic exchange playing a major role in T. cruzi population structure and biology.

HLA Class I-T cell epitopes from trans-sialidase proteins reveal functionally distinct subsets of CD8+ T cells in chronic Chagas disease.

Background Previously, we identified a set of HLA-A020.1-restricted trans-sialidase peptides as targets of CD8+ T cell responses in HLA-A0201+ individuals chronically infected by T. cruzi. Methods and Findings Herein, we report the identification of peptides encoded by the same trans-sialidase gene family that bind alleles representative of the 6 most common class I HLA-supertypes. Based on a combination of bioinformatic predictions and HLA-supertype considerations, a total of 1001 epitopes predicted to bind to HLA A01, A02, A03, A24, B7 and B44 supertypes was selected. Ninety-six supertype-binder epitopes encoded by multiple trans-sialidase genes were tested for the ability to stimulate a recall CD8+ T cell response in the peripheral blood from subjects with chronic T. cruzi infection regardless the HLA haplotype. An overall hierarchy of antigenicity was apparent, with the A02 supertype peptides being the most frequently recognized in the Chagas disease population followed by the A03 and the A24 supertype epitopes. CD8+ T cell responses to promiscuous epitopes revealed that the CD8+ T cell compartment specific for T. cruzi displays a functional profile with T cells secreting interferon-γ alone as the predominant pattern and very low prevalence of single IL-2-secreting or dual IFN-γ/IL-2 secreting T cells denoting a lack of polyfunctional cytokine responses in chronic T. cruzi infection. Conclusions This study identifies a set of T. cruzi peptides that should prove useful for monitoring immune competence and changes in infection and disease status in individuals with chronic Chagas disease.

A semi-quantitative GeLC-MS analysis of temporal proteome expression in the emerging nosocomial pathogen Ochrobactrum anthropi

BackgroundThe α-Proteobacteria are capable of interaction with eukaryotic cells, with some members, such as Ochrobactrum anthropi, capable of acting as human pathogens. O. anthropi has been the cause of a growing number of hospital-acquired infections; however, little is known about its growth, physiology and metabolism. We used proteomics to investigate how protein expression of this organism changes with time during growth.ResultsThis first gel-based liquid chromatography-mass spectrometry (GeLC-MS) temporal proteomic analysis of O. anthropi led to the positive identification of 131 proteins. These were functionally classified and physiochemically characterized. Utilizing the emPAI protocol to estimate protein abundance, we assigned molar concentrations to all proteins, and thus were able to identify 19 with significant changes in their expression. Pathway reconstruction led to the identification of a variety of central metabolic pathways, including nucleotide biosynthesis, fatty acid anabolism, glycolysis, TCA cycle and amino acid metabolism. In late phase growth we identified a number of gene products under the control of the oxyR regulon, which is induced in response to oxidative stress and whose protein products have been linked with pathogen survival in response to host immunity reactions.ConclusionThis study identified distinct proteomic profiles associated with specific growth points for O. anthropi, while the use of emPAI allowed semi-quantitative analyses of protein expression. It was possible to reconstruct central metabolic pathways and infer unique functional and adaptive processes associated with specific growth phases, thereby resulting in a deeper understanding of the physiology and metabolism of this emerging pathogenic bacterium.

Interleukin-1-induced changes in the glioblastoma secretome suggest its role in tumor progression

UNLABELLED The tumor microenvironment including glial cells and their inflammatory products regulates brain tumor development and progression. We have previously established that human glioma cells are exquisitely sensitive to IL-1 stimulation leading us to undertake a comparative analysis of the secretome of unstimulated and cytokine (IL-1)-stimulated glioblastoma cells. We performed label-free quantitative proteomic analysis and detected 190 proteins which included cytokines, chemokines, growth factors, proteases, cell adhesion molecules, extracellular matrix (ECM) and related proteins. Measuring area under the curve (AUC) of peptides for quantitation, the IL-1-induced secretome contained 13 upregulated and 5 downregulated extracellular proteins (p<0.05) compared to controls. Of these, IL-8, CCL2, TNC, Gal-1 and PTX3 were validated as upregulated and SERPINE1, STC2, CTGF and COL4A2 were validated as downregulated factors by immunochemical methods. A major representation of the ECM and related proteins in the glioblastoma secretome and their modulation by IL-1 suggested that IL-1 induces its effect in part by altering TGFβ expression, activity and signaling. These findings enhance our understanding of IL-1-induced modulation of glioma microenvironment, with implications for increased tumor invasion, migration and angiogenesis. They further provide novel targets for the glioblastoma intervention. BIOLOGICAL SIGNIFICANCE Present study is on an unbiased screening of the glioblastoma secretome stimulated by IL-1 which triggers neuroinflammatory cascades in the central nervous system. Network of secreted proteins were shown to be regulated revealing their possible contribution to glioma progression. Label free quantitative proteomics has provided unique novel targets for potential glioblastoma intervention.

Dyn-MPI: Supporting MPI on Non Dedicated Clusters

Distributing data is a fundamental problem in implementing efficient distributed-memory parallel programs. The problem becomes more difficult in environments where the participating nodes are not dedicated to a parallel application. We are investigating the data distribution problem in non dedicated environments in the context of explicit message-passing programs. To address this problem, we have designed and implemented an extension to MPI called Dynamic MPI (Dyn-MPI). The key component of Dyn-MPI is its run-time system, which efficiently and automatically redistributes data on the fly when there are changes in the application or the underlying environment. Dyn-MPI supports efficient memory allocation, precise measurement of system load and computation time, and node removal. Performance results show that programs that use Dyn-MPI execute efficiently in non dedicated environments, including up to almost a three-fold improvement compared to programs that do not redistribute data and a 25% improvement over standard adaptive load balancing techniques.