Immune exhaustion in chronic Chagas disease: Pro-inflammatory and immunomodulatory action of IL-27 in vitro.

In chronic Chagas disease, Trypanosoma cruzi-specific T-cell function decreases over time, and alterations in the homeostatic IL-7/IL-7R axis are evident, consistent with a process of immune exhaustion. IL-27 is an important immunoregulatory cytokine that shares T-cell signaling with IL-7 and other cytokines of the IL-12 family and might be involved in the transcriptional regulation of T-cell function. Here, we evaluated the expression and function of IL-27R in antigen-experienced T cells from subjects with chronic Chagas disease and assessed whether in vitro treatment with IL-27 and IL-7 might improve T. cruzi-specific polyfunctional T-cell responses. In vitro exposure of PBMCs to T. cruzi induced a downregulation of IL-27R in CD4+ T cells and an upregulation in CD8+ T cells in subjects without heart disease, while IL-27R expression remained unaltered in subjects with more severe clinical stages. The modulation of IL-27R was associated with functional signaling through STAT3 and STAT5 and induction of the downstream genes TBX21, EOMES and CXCL9 in response to IL-27. In vitro treatment of PBMCs with IL-27 and IL-7 improved monofunctional and polyfunctional Th1 responses, accompanied by the induction of IL-10 and Bcl-2 expression in subjects without heart disease but did not improve those in subjects with cardiomyopathy. Our findings support the process of desensitization of the IL-27/IL-27R pathway along with disease severity and that the pro-inflammatory and immunomodulatory mechanisms of IL-27 might be interconnected.

A framework for ontology-based question answering with application to parasite immunology.

BACKGROUND: Large quantities of biomedical data are being produced at a rapid pace for a variety of organisms. With ontologies proliferating, data is increasingly being stored using the RDF data model and queried using RDF based querying languages. While existing systems facilitate the querying in various ways, the scientist must map the question in his or her mind to the interface used by the systems. The field of natural language processing has long investigated the challenges of designing natural language based retrieval systems. Recent efforts seek to bring the ability to pose natural language questions to RDF data querying systems while leveraging the associated ontologies. These analyze the input question and extract triples (subject, relationship, object), if possible, mapping them to RDF triples in the data. However, in the biomedical context, relationships between entities are not always explicit in the question and these are often complex involving many intermediate concepts. RESULTS: We present a new framework, OntoNLQA, for querying RDF data annotated using ontologies which allows posing questions in natural language. OntoNLQA offers five steps in order to answer natural language questions. In comparison to previous systems, OntoNLQA differs in how some of the methods are realized. In particular, it introduces a novel approach for discovering the sophisticated semantic associations that may exist between the key terms of a natural language question, in order to build an intuitive query and retrieve precise answers. We apply this framework to the context of parasite immunology data, leading to a system called AskCuebee that allows parasitologists to pose genomic, proteomic and pathway questions in natural language related to the parasite, Trypanosoma cruzi. We separately evaluate the accuracy of each component of OntoNLQA as implemented in AskCuebee and the accuracy of the whole system. AskCuebee answers 68 % of the questions in a corpus of 125 questions, and 60 % of the questions in a new previously unseen corpus. If we allow simple corrections by the scientists, this proportion increases to 92 %. CONCLUSIONS: We introduce a novel framework for question answering and apply it to parasite immunology data. Evaluations of translating the questions to RDF triple queries by combining machine learning, lexical similarity matching with ontology classes, properties and instances for specificity, and discovering associations between them demonstrate that the approach performs well and improves on previous systems. Subsequently, OntoNLQA offers a viable framework for building question answering systems in other biomedical domains.

CRISPR-Cas9-mediated single-gene and gene family disruption in Trypanosoma cruzi.

UNLABELLED: Trypanosoma cruzi is a protozoan parasite of humans and animals, affecting 10 to 20 million people and innumerable animals, primarily in the Americas. Despite being the largest cause of infection-induced heart disease worldwide, even among the neglected tropical diseases (NTDs) T. cruzi is considered one of the least well understood and understudied. The genetic complexity of T. cruzi as well as the limited set of efficient techniques for genome engineering contribute significantly to the relative lack of progress in and understanding of this pathogen. Here, we adapted the CRISPR-Cas9 system for the genetic engineering of T. cruzi, demonstrating rapid and efficient knockout of multiple endogenous genes, including essential genes. We observed that in the absence of a template, repair of the Cas9-induced double-stranded breaks (DSBs) in T. cruzi occurs exclusively by microhomology-mediated end joining (MMEJ) with various-sized deletions. When a template for DNA repair is provided, DSB repair by homologous recombination is achieved at an efficiency several orders of magnitude higher than that in the absence of CRISPR-Cas9-induced DSBs. We also demonstrate the high multiplexing capacity of CRISPR-Cas9 in T. cruzi by knocking down expression of an enzyme gene family consisting of 65 members, resulting in a significant reduction of enzymatic product with no apparent off-target mutations. Lastly, we show that Cas9 can mediate disruption of its own coding sequence, rescuing a growth defect in stable Cas9-expressing parasites. These results establish a powerful new tool for the analysis of gene functions in T. cruzi, enabling the study of essential genes and their functions and analysis of the many large families of related genes that occupy a substantial portion of the T. cruzi genome. IMPORTANCE: Trypanosoma cruzi, the causative agent of human Chagas disease, is the leading worldwide cause of infectious myocarditis. Diagnostics for the infection are relatively poor, treatment options are limited and of variable effectiveness, and suitable vaccines are nonexistent. The T. cruzi genome is replete with genes of unknown function and greatly expanded gene families with hundreds of members. The absence of facile genetic engineering tools, including RNA interference, for T. cruzi has prevented elucidation of gene and gene family function and the development of better infection prevention and control measures. In this study, we demonstrate that the CRISPR-Cas9 system is a versatile and powerful tool for genome manipulations in T. cruzi, bringing new opportunities for unraveling the functions of previously uncharacterized genes and how this human pathogen engages its large families of genes encoding surface proteins to interact with human and animal hosts.

A semantic problem solving environment for integrative parasite research: identification of intervention targets for Trypanosoma cruzi.

BACKGROUND: Research on the biology of parasites requires a sophisticated and integrated computational platform to query and analyze large volumes of data, representing both unpublished (internal) and public (external) data sources. Effective analysis of an integrated data resource using knowledge discovery tools would significantly aid biologists in conducting their research, for example, through identifying various intervention targets in parasites and in deciding the future direction of ongoing as well as planned projects. A key challenge in achieving this objective is the heterogeneity between the internal lab data, usually stored as flat files, Excel spreadsheets or custom-built databases, and the external databases. Reconciling the different forms of heterogeneity and effectively integrating data from disparate sources is a nontrivial task for biologists and requires a dedicated informatics infrastructure. Thus, we developed an integrated environment using Semantic Web technologies that may provide biologists the tools for managing and analyzing their data, without the need for acquiring in-depth computer science knowledge. METHODOLOGY/PRINCIPAL FINDINGS: We developed a semantic problem-solving environment (SPSE) that uses ontologies to integrate internal lab data with external resources in a Parasite Knowledge Base (PKB), which has the ability to query across these resources in a unified manner. The SPSE includes Web Ontology Language (OWL)-based ontologies, experimental data with its provenance information represented using the Resource Description Format (RDF), and a visual querying tool, Cuebee, that features integrated use of Web services. We demonstrate the use and benefit of SPSE using example queries for identifying gene knockout targets of Trypanosoma cruzi for vaccine development. Answers to these queries involve looking up multiple sources of data, linking them together and presenting the results. CONCLUSION/SIGNIFICANCE: The SPSE facilitates parasitologists in leveraging the growing, but disparate, parasite data resources by offering an integrative platform that utilizes Semantic Web techniques, while keeping their workload increase minimal.

A unified framework for managing provenance information in translational research.

BACKGROUND: A critical aspect of the NIH Translational Research roadmap, which seeks to accelerate the delivery of "bench-side" discoveries to patient's "bedside," is the management of the provenance metadata that keeps track of the origin and history of data resources as they traverse the path from the bench to the bedside and back. A comprehensive provenance framework is essential for researchers to verify the quality of data, reproduce scientific results published in peer-reviewed literature, validate scientific process, and associate trust value with data and results. Traditional approaches to provenance management have focused on only partial sections of the translational research life cycle and they do not incorporate "domain semantics", which is essential to support domain-specific querying and analysis by scientists. RESULTS: We identify a common set of challenges in managing provenance information across the pre-publication and post-publication phases of data in the translational research lifecycle. We define the semantic provenance framework (SPF), underpinned by the Provenir upper-level provenance ontology, to address these challenges in the four stages of provenance metadata:(a) Provenance collection - during data generation(b) Provenance representation - to support interoperability, reasoning, and incorporate domain semantics(c) Provenance storage and propagation - to allow efficient storage and seamless propagation of provenance as the data is transferred across applications(d) Provenance query - to support queries with increasing complexity over large data size and also support knowledge discovery applicationsWe apply the SPF to two exemplar translational research projects, namely the Semantic Problem Solving Environment for Trypanosoma cruzi (T.cruzi SPSE) and the Biomedical Knowledge Repository (BKR) project, to demonstrate its effectiveness. CONCLUSIONS: The SPF provides a unified framework to effectively manage provenance of translational research data during pre and post-publication phases. This framework is underpinned by an upper-level provenance ontology called Provenir that is extended to create domain-specific provenance ontologies to facilitate provenance interoperability, seamless propagation of provenance, automated querying, and analysis.

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

BACKGROUND: Trypanosoma 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. RESULTS: In 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. CONCLUSIONS: The 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.

Epigenetic regulation of transcription and virulence in Trypanosoma cruzi by O-linked thymine glucosylation of DNA.

Unlike other eukaryotes, the protein-coding genes of Trypanosoma cruzi are arranged in large polycistronic gene clusters transcribed by polymerase II (Pol II). Thus, it is thought that trypanosomes rely solely on posttranscriptional processes to regulate gene expression. Here, we show that the glucosylated thymine DNA base (ß-d-glucosyl-hydroxymethyluracil or base J) is present within sequences flanking the polycistronic units (PTUs) in T. cruzi. The loss of base J at sites of transcription initiation, via deletion of the two enzymes that regulate base J synthesis (JBP1 and JBP2), correlates with an increased rate of Pol II transcription and subsequent genome-wide increase in gene expression. The affected genes include virulence genes, and the resulting parasites are defective in host cell invasion and egress. These studies indicate that base J is an epigenetic factor regulating Pol II transcription initiation in kinetoplastids and provides the first biological role of the only hypermodified DNA base in eukaryotes.

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

BACKGROUND: Chronic 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. RESULTS: In 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. CONCLUSION: Taken 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.

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.

Glycoproteomics of Trypanosoma cruzi trypomastigotes using subcellular fractionation, lectin affinity, and stable isotope labeling.

Herein we detail the first glycoproteomic analysis of a human pathogen. We describe an approach that enables the identification of organelle and cell surface N-linked glycoproteins from Trypanosoma cruzi, the causative agent of Chagas' disease. This approach is based on a subcellular fractionation protocol to produce fractions enriched in either organelle or plasma membrane/cytoplasmic proteins. Through lectin affinity capture of the glycopeptides from each subcellular fraction and stable isotope labeling of the glycan attachment sites with H(2)18O, we unambiguously identified 36 glycosylation sites on 35 glycopeptides which mapped to 29 glycoproteins. We also present the first expression evidence for 11 T. cruzi specific glycoproteins and provide experimental data indicating that the mucin associated surface protein family (MASP) and dispersed gene family (DGF-1) are post-translationally modified by N-linked glycans.

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.

Microarray profiling of gene expression during trypomastigote to amastigote transition in Trypanosoma cruzi.

Trypanosoma cruzi, the causative agent of Chagas disease, remains a significant public health concern throughout South and Central America. Although much is known about immune control of T. cruzi and in particular the importance of recognition of parasite-infected cells, relatively little is known about the target antigens of these protective immune responses. For instance, few of the genes expressed in the intracellular amastigote stage have been identified. To gain insight into the molecular events, at the level of mRNA abundance, involved in this critical point in the parasite life-cycle, we used DNA microarrays of 4400 sequences from T. cruzi ORF-selected and random, genomic sequencing libraries to determine relative mRNA abundances in trypomastigotes and developing amastigotes. Results from six hybridizations using independently generated parasite samples consistently identified 60 probes that detected genes upregulated within 2h after extracellular trypomastigotes were induced, in vitro, to differentiate into amastigotes. Sequence analysis from these 60 probes identified 14 known and 25 novel T. cruzi genes. The general direction of regulation was confirmed by quantitative RT-PCR for seven of the array-identified, amastigote upregulated, known genes. This work demonstrates the feasibility of computational and microarray approaches to gene discovery in T. cruzi, an organism for which a fully assembled and annotated genome sequence is not yet available and in which control of transcription initiation is believed to be absent. Moreover, this work is the first report of amastigote up regulation for 38 genes, thus expanding considerably the pool of genes known to be upregulated in this important yet poorly-studied stage of the T. cruzi life-cycle.

Microarray analysis of neural stem cell differentiation in the striatum of the fetal rat.

1. Gene expression profiles in neural stem cell differentiation in vitro were determined by cDNA microarray analysis. 2. Total RNA was extracted and reverse transcripted into cDNA from differentiated and undifferentiated neural stem cells. The 33P labeled cDNA was hybridized with a cDNA microarray consisting of 14,000 human genes. 3. The results showed that a total of 1406 genes were differentially expressed, of which 148 genes exhibited more than twofold differences. Some genes were obviously activated while others were strongly repressed. These changes in gene expression suggest that differentiation is regulated by different genes at different expressional levels. By biological classification, the differentially expressed genes were divided into four functional categories: molecular function, biological process, cellular component, and new functional genes or ESTs. 4. These findings will be a valuable contribution for gene expression profiling and elucidation of neural stem cell differentiation mechanisms.