Abstract P041: Improved sensitivity of a multi-analyte early detection test based on mutation, methylation, aneuploidy, and protein biomarkers

Background: A multi-analyte blood test has the potential to maximize performance for early detection across different cancer stages and types. Improvements in early-stage cancer detection might be achieved using multi-component tests with high sensitivities and specificities. We recently performed a large feasibility study to assess the performance of 4 biomarkers (aneuploidy, methylation, mutation, and protein) for the detection of cancers from up to 15 organ sites. Specifically, a training and validation set was tested for 3 biomarkers (aneuploidy, methylation, and protein) and the performance was subsequently confirmed in an independent testing set. Methods: We have now further improved the performance of a 4-marker cancer detection blood test by fine-tuning the respective marker calling models and thresholds, exploring prostate-specific antigen (PSA) for prostate cancer detection, and developing an overarching Machine Learning (ML) cancer classifier. To improve the mutation detection, we tested (in triplicate) 200 plasma and buffy samples from young, non-cancer subjects and mutant DNA from cell lines to develop an ML-based mutation calling algorithm. This caller was validated on 186 samples and tested on an independent set of 1388 cancer and non-cancer samples. The calling of cancer-associated DNA methylation events was refined by performing training, validation, and testing across different studies. We also explored models for methylation detection based solely on distribution of methylation signal observed in non-cancer samples. Free and total PSA were investigated as markers for prostate cancer detection by including clinically relevant Gleason scores in the development of the protein-based cancer calling algorithm. Results: In the previous analysis the combination of mutation, aneuploidy, methylation, and protein biomarkers resulted in an overall sensitivity of 61.0% (95% CI: 56.9%-65.0) at a specificity of 98.2% (95% CI: 97.1 – 99.4%). We will present the added performance benefit of ML-based mutation variant calling. PSA derived features were evaluated with the goal of increasing the detectability of high-grade prostate cancers while minimizing the detection of indolent cancers. Lastly, we compared the Boolean logic-based 4-biomarker combination algorithm used in the previous analysis with an ML-based cancer classifier. The results of the modeling, applied to the testing set, will be shared. Conclusions: In summary, improvements in cancer detection performance may be achieved by optimizing each biomarker calling algorithm as well as overarching cancer classifier. When combining these improvements, we believe that a single blood test will provide robust sensitivity for the detection of several cancer types, particularly for earlier-stage disease in real world settings.

Citation Format: Vladimir Gianullin, Leonardo Hagmann, Kevin Arvai, Amira Djebbari, Christopher L. Nobles, Larson Hogstrom, Mael Manesse, Vuna Fa, Fanglei Zhuang, Xi Chen, Viatcheslav E. Katerov, Jorge Garces, Hatim T. Allawi, Abigail McElhinny, Frank Diehl, Gustavo C Cerqueira. Improved sensitivity of a multi-analyte early detection test based on mutation, methylation, aneuploidy, and protein biomarkers. [abstract]. In: Proceedings of the AACR Special Conference: Precision Prevention, Early Detection, and Interception of Cancer; 2022 Nov 17-19; Austin, TX. Philadelphia (PA): AACR; Can Prev Res 2023;16(1 Suppl): Abstract nr P041.

Abstract IA023: Improved sensitivity of a multi-analyte early detection test based on mutation, methylation, aneuploidy, and protein biomarkers

Background: A multi-analyte blood test has the potential to maximize performance for early detection across different cancer stages and types. Improvements in early-stage cancer detection might be achieved using multi-component tests with high sensitivities and specificities. We recently performed a large feasibility study to assess the performance of 4 biomarkers (aneuploidy, methylation, mutation, and protein) for the detection of cancers from up to 15 organ sites. Specifically, a training and validation set was tested for 3 biomarkers (aneuploidy, methylation, and protein) and the performance was subsequently confirmed in an independent testing set. Methods: We have now further improved the performance of a 4-marker cancer detection blood test by fine-tuning the respective marker calling models and thresholds, exploring prostate-specific antigen (PSA) for prostate cancer detection, and developing an overarching Machine Learning (ML) cancer classifier. To improve the mutation detection, we tested (in triplicate) 200 plasma and buffy samples from young, non-cancer subjects and mutant DNA from cell lines to develop an ML-based mutation calling algorithm. This caller was validated on 186 samples and tested on an independent set of 1388 cancer and non-cancer samples. The calling of cancer-associated DNA methylation events was refined by performing training, validation, and testing across different studies. We also explored models for methylation detection based solely on distribution of methylation signal observed in non-cancer samples. Free and total PSA were investigated as markers for prostate cancer detection by including clinically relevant Gleason scores in the development of the protein-based cancer calling algorithm. Results: In the previous analysis the combination of mutation, aneuploidy, methylation, and protein biomarkers resulted in an overall sensitivity of 61.0% (95% CI: 56.9%-65.0) at a specificity of 98.2% (95% CI: 97.1 – 99.4%). We will present the added performance benefit of ML-based mutation variant calling. PSA derived features were evaluated with the goal of increasing the detectability of high-grade prostate cancers while minimizing the detection of indolent cancers. Lastly, we compared the Boolean logic-based 4-biomarker combination algorithm used in the previous analysis with an ML-based cancer classifier. The results of the modeling, applied to the testing set, will be shared. Conclusions: In summary, improvements in cancer detection performance may be achieved by optimizing each biomarker calling algorithm as well as overarching cancer classifier. When combining these improvements, we believe that a single blood test will provide robust sensitivity for the detection of several cancer types, particularly for earlier-stage disease in real world settings.

Citation Format: Vladimir Gianullin, Leonardo Hagmann, Kevin Arvai, Amira Djebbari, Christopher L. Nobles, Larson Hogstrom, Mael Manesse, Vuna Fa, Fanglei Zhuang, Xi Chen, Viatcheslav E. Katerov, Jorge Garces, Hatim T. Allawi, Abigail McElhinny, Frank Diehl, Gustavo C Cerqueira. Improved sensitivity of a multi-analyte early detection test based on mutation, methylation, aneuploidy, and protein biomarkers. [abstract]. In: Proceedings of the AACR Special Conference: Precision Prevention, Early Detection, and Interception of Cancer; 2022 Nov 17-19; Austin, TX. Philadelphia (PA): AACR; Can Prev Res 2023;16(1 Suppl): Abstract nr IA023.

Simultaneous detection of genotype and phenotype enables rapid and accurate antibiotic susceptibility determination

Multidrug resistant organisms (MDROs) are a serious threat to human health^1,2. Fast, accurate antibiotic susceptibility testing (AST) is a critical need in addressing escalating antibiotic resistance, since delays in identifying MDROs increase mortality^3,4 and use of broad-spectrum antibiotics, further selecting for resistant organisms. Yet current growth-based AST assays, such as broth microdilution⁵, require several days before informing key clinical decisions. Rapid AST would transform the care of infected patients while ensuring that our antibiotic arsenal is deployed as efficiently as possible. Growth-based assays are fundamentally constrained in speed by doubling time of the pathogen, and genotypic assays are limited by the ever-growing diversity and complexity of bacterial antibiotic resistance mechanisms. Here, we describe a rapid assay for combined Genotypic and Phenotypic AST through RNA detection, GoPhAST-R, that classifies strains with 94–99% accuracy by coupling machine learning analysis of early antibiotic-induced transcriptional changes with simultaneous detection of key genetic resistance determinants to increase accuracy of resistance detection, facilitate molecular epidemiology, and enable early detection of emerging resistance mechanisms. This two-pronged approach provides phenotypic AST 24–36 hours faster than standard workflows, with <4 hour assay time on a pilot instrument for hybridization-based multiplexed RNA detection implemented directly from positive blood cultures.

ProphET, prophage estimation tool: A stand-alone prophage sequence prediction tool with self-updating reference database

Background

Prophages play a significant role in prokaryotic evolution, often altering the function of the cell that they infect via transfer of new genes e.g., virulence or antibiotic resistance factors, inactivation of existing genes or by modifying gene expression. Recently, phage therapy has gathered renewed interest as a promising alternative to control bacterial infections. Cataloging the repertoire of prophages in large collections of species’ genomes is an important initial step in understanding their evolution and potential therapeutic utility. However, current widely-used tools for identifying prophages within bacterial genome sequences are mainly web-based, can have long response times, and do not scale to keep pace with the many thousands of genomes currently being sequenced routinely.

Methodology

In this work, we present ProphET, an easy to install prophage predictor to be used in Linux operation system, without the constraints associated with a web-based tool. ProphET predictions rely on similarity searches against a database of prophage genes, taking as input a bacterial genome sequence in FASTA format and its corresponding gene annotation in GFF. ProphET identifies prophages in three steps: similarity search, calculation of the density of prophage genes, and edge refinement. ProphET performance was evaluated and compared with other phage predictors based on a set of 54 bacterial genomes containing 267 manually annotated prophages.

Findings and conclusions

ProphET identifies prophages in bacterial genomes with high precision and offers a fast, highly scalable alternative to widely-used web-based applications for prophage detection.

Abstract 3515: Functional antigen presentation is required to interpret the tumor mutation burden (TMB) test

Therapeutic response to checkpoint inhibitors requires a prior, suppressed immune response that is released by a monoclonal antibody blocking the interaction of the checkpoint receptors with their cognate ligands. The presence of this suppressed immune response can be detected by a variety of tests including tumor mutation burden (TMB), tumor infiltrating leukocytes, T-cell receptor clonality, circulating interferons and cytokines, and upregulation of the expression of the checkpoint ligands. Today, TMB has proven to be the most predictive biomarker of response to immunotherapy.

TMB is a surrogate marker of immune response. The test works by sampling a small region of the cancer genome to estimate the number of mutations/Mb of the cancer exome. A high TMB score is associated with better response to immunotherapy because it carries more somatic mutations and a higher chance of presenting an immunogenic neoepitope that will lead to CD-8+ T-cell mediated destruction. Restriction or loss of antigen presentation caused by mutations and loss of heterozygosity (LOH) of the beta-2-microglobulin (B2M) and HLA Class I genes has been shown to be a common means of evading CD-8+ T-Cell destruction. Consequently, the outcome for high TMB tumors will be dependent on their ability to present antigens, so that the mutation count will not matter in cells that are unable to present antigens in their HLA Class I/B2M complex.

We propose that TMB should be considered together with the ability of the tumor to present these putative neoantigens. To test this hypothesis, we used the PGDx elio™ Tissue Complete test (507 genes in 1.3 Mb) to measure TMB and antigen presentation in the same assay. We tested 212 cancer patients and showed that in FFPET samples with &gt;20% tumor content, we could detect LOH of the MHC Class I and B2M genes with &gt;90% accuracy compared to whole exome data from the same sample. These data confirmed our hypothesis that it was possible to measure TMB and evaluate the genes involved in antigen presentation in the same in silico analysis of a 507 gene next-generation sequencing (NGS) panel. We are currently using this combined analysis to measure TMB and somatic alterations of the antigen presentation complex in several different cancers and to test the hypothesis that adding neoantigen presentation capability to TMB scores will significantly improve prediction of response to a variety of immunotherapies.

Citation Format: Gustavo C. Cerqueira, Laurel A. Keefer, Donna Nichol, Julie R. Meyer, Nicholas C. Dracopoli. Functional antigen presentation is required to interpret the tumor mutation burden (TMB) test [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 3515.

RNA-Seq Profile Reveals Th-1 and Th-17-Type of Immune Responses in Mice Infected Systemically with Aspergillus fumigatus

With the increasing numbers of immunocompromised hosts, Aspergillus fumigatus emerges as a lethal opportunistic fungal pathogen. Understanding innate and acquired immunity responses of the host is important for a better therapeutic strategy to deal with aspergillosis patients. To determine the transcriptome in the kidneys in aspergillosis, we employed RNA-Seq to obtain single 76-base reads of whole-genome transcripts of murine kidneys on a temporal basis (days 0; uninfected, 1, 2, 3 and 8) during invasive aspergillosis. A total of 6284 transcripts were downregulated, and 5602 were upregulated compared to baseline expression. Gene ontology enrichment analysis identified genes involved in innate and adaptive immune response, as well as iron binding and homeostasis, among others. Our results showed activation of pathogen recognition receptors, e.g., β-defensins, C-type lectins (e.g., dectin-1), Toll-like receptors (TLR-2, TLR-3, TLR-8, TLR-9 and TLR-13), as well as Ptx-3 and C-reactive protein among the soluble receptors. Upregulated transcripts encoding various differentiating cytokines and effector proinflammatory cytokines, as well as those encoding for chemokines and chemokine receptors, revealed Th-1 and Th-17-type immune responses. These studies form a basic dataset for experimental prioritization, including other target organs, to determine the global response of the host against Aspergillus infection.

Quantifying connectivity between local Plasmodium falciparum malaria parasite populations using identity by descent

With the rapidly increasing abundance and accessibility of genomic data, there is a growing interest in using population genetic approaches to characterize fine-scale dispersal of organisms, providing insight into biological processes across a broad range of fields including ecology, evolution and epidemiology. For sexually recombining haploid organisms such as the human malaria parasite P. falciparum, however, there have been no systematic assessments of the type of data and methods required to resolve fine scale connectivity. This analytical gap hinders the use of genomics for understanding local transmission patterns, a crucial goal for policy makers charged with eliminating this important human pathogen. Here we use data collected from four clinics with a catchment area spanning approximately 120 km of the Thai-Myanmar border to compare the ability of divergence (FST) and relatedness based on identity by descent (IBD) to resolve spatial connectivity between malaria parasites collected from proximal clinics. We found no relationship between inter-clinic distance and FST, likely due to sampling of highly related parasites within clinics, but a significant decline in IBD-based relatedness with increasing inter-clinic distance. This association was contingent upon the data set type and size. We estimated that approximately 147 single-infection whole genome sequenced parasite samples or 222 single-infection parasite samples genotyped at 93 single nucleotide polymorphisms (SNPs) were sufficient to recover a robust spatial trend estimate at this scale. In summary, surveillance efforts cannot rely on classical measures of genetic divergence to measure P. falciparum transmission on a local scale. Given adequate sampling, IBD-based relatedness provides a useful alternative, and robust trends can be obtained from parasite samples genotyped at approximately 100 SNPs.

Longitudinal genomic surveillance of Plasmodium falciparum malaria parasites reveals complex genomic architecture of emerging artemisinin resistance

Background

Artemisinin-based combination therapies are the first line of treatment for Plasmodium falciparum infections worldwide, but artemisinin resistance has risen rapidly in Southeast Asia over the past decade. Mutations in the kelch13 gene have been implicated in this resistance. We used longitudinal genomic surveillance to detect signals in kelch13 and other loci that contribute to artemisinin or partner drug resistance. We retrospectively sequenced the genomes of 194 P. falciparum isolates from five sites in Northwest Thailand, over the period of a rapid increase in the emergence of artemisinin resistance (2001–2014).

Results

We evaluate statistical metrics for temporal change in the frequency of individual SNPs, assuming that SNPs associated with resistance increase in frequency over this period. After Kelch13-C580Y, the strongest temporal change is seen at a SNP in phosphatidylinositol 4-kinase, which is involved in a pathway recently implicated in artemisinin resistance. Furthermore, other loci exhibit strong temporal signatures which warrant further investigation for involvement in artemisinin resistance evolution. Through genome-wide association analysis we identify a variant in a kelch domain-containing gene on chromosome 10 that may epistatically modulate artemisinin resistance.

Conclusions

This analysis demonstrates the potential of a longitudinal genomic surveillance approach to detect resistance-associated gene loci to improve our mechanistic understanding of how resistance develops. Evidence for additional genomic regions outside of the kelch13 locus associated with artemisinin-resistant parasites may yield new molecular markers for resistance surveillance, which may be useful in efforts to reduce the emergence or spread of artemisinin resistance in African parasite populations.

Electronic supplementary material

The online version of this article (doi:10.1186/s13059-017-1204-4) contains supplementary material, which is available to authorized users.

Comparative genomics reveals high biological diversity and specific adaptations in the industrially and medically important fungal genus Aspergillus

BACKGROUND

The fungal genus Aspergillus is of critical importance to humankind. Species include those with industrial applications, important pathogens of humans, animals and crops, a source of potent carcinogenic contaminants of food, and an important genetic model. The genome sequences of eight aspergilli have already been explored to investigate aspects of fungal biology, raising questions about evolution and specialization within this genus.

RESULTS

We have generated genome sequences for ten novel, highly diverse Aspergillus species and compared these in detail to sister and more distant genera. Comparative studies of key aspects of fungal biology, including primary and secondary metabolism, stress response, biomass degradation, and signal transduction, revealed both conservation and diversity among the species. Observed genomic differences were validated with experimental studies. This revealed several highlights, such as the potential for sex in asexual species, organic acid production genes being a key feature of black aspergilli, alternative approaches for degrading plant biomass, and indications for the genetic basis of stress response. A genome-wide phylogenetic analysis demonstrated in detail the relationship of the newly genome sequenced species with other aspergilli.

CONCLUSIONS

Many aspects of biological differences between fungal species cannot be explained by current knowledge obtained from genome sequences. The comparative genomics and experimental study, presented here, allows for the first time a genus-wide view of the biological diversity of the aspergilli and in many, but not all, cases linked genome differences to phenotype. Insights gained could be exploited for biotechnological and medical applications of fungi.

Discovery of McrA, a master regulator of Aspergillus secondary metabolism

Fungal secondary metabolites (SMs) are extremely important in medicine and agriculture, but regulation of their biosynthesis is incompletely understood. We have developed a genetic screen in Aspergillus nidulans for negative regulators of fungal SM gene clusters and we have used this screen to isolate mutations that upregulate transcription of the non-ribosomal peptide synthetase gene required for nidulanin A biosynthesis. Several of these mutations are allelic and we have identified the mutant gene by genome sequencing. The gene, which we designate mcrA, is conserved but uncharacterized, and it encodes a putative transcription factor. Metabolite profiles of mcrA deletant, mcrA overexpressing, and parental strains reveal that mcrA regulates at least ten SM gene clusters. Deletion of mcrA stimulates SM production even in strains carrying a deletion of the SM regulator laeA, and deletion of mcrA homologs in Aspergillus terreus and Penicillum canescens alters the secondary metabolite profile of these organisms. Deleting mcrA in a genetic dereplication strain has allowed us to discover two novel compounds as well as an antibiotic not known to be produced by A. nidulans. Deletion of mcrA upregulates transcription of hundreds of genes including many that are involved in secondary metabolism, while downregulating a smaller number of genes.

The genomic diversification of the whole Acinetobacter genus: origins, mechanisms, and consequences

Bacterial genomics has greatly expanded our understanding of microdiversification patterns within a species, but analyses at higher taxonomical levels are necessary to understand and predict the independent rise of pathogens in a genus. We have sampled, sequenced, and assessed the diversity of genomes of validly named and tentative species of the Acinetobacter genus, a clade including major nosocomial pathogens and biotechnologically important species. We inferred a robust global phylogeny and delimited several new putative species. The genus is very ancient and extremely diverse: Genomes of highly divergent species share more orthologs than certain strains within a species. We systematically characterized elements and mechanisms driving genome diversification, such as conjugative elements, insertion sequences, and natural transformation. We found many error-prone polymerases that may play a role in resistance to toxins, antibiotics, and in the generation of genetic variation. Surprisingly, temperate phages, poorly studied in Acinetobacter, were found to account for a significant fraction of most genomes. Accordingly, many genomes encode clustered regularly interspaced short palindromic repeats (CRISPR)-Cas systems with some of the largest CRISPR-arrays found so far in bacteria. Integrons are strongly overrepresented in Acinetobacter baumannii, which correlates with its frequent resistance to antibiotics. Our data suggest that A. baumannii arose from an ancient population bottleneck followed by population expansion under strong purifying selection. The outstanding diversification of the species occurred largely by horizontal transfer, including some allelic recombination, at specific hotspots preferentially located close to the replication terminus. Our work sets a quantitative basis to understand the diversification of Acinetobacter into emerging resistant and versatile pathogens.

The Aspergillus Genome Database: multispecies curation and incorporation of RNA-Seq data to improve structural gene annotations

The Aspergillus Genome Database (AspGD; http://www.aspgd.org) is a freely available web-based resource that was designed for Aspergillus researchers and is also a valuable source of information for the entire fungal research community. In addition to being a repository and central point of access to genome, transcriptome and polymorphism data, AspGD hosts a comprehensive comparative genomics toolbox that facilitates the exploration of precomputed orthologs among the 20 currently available Aspergillus genomes. AspGD curators perform gene product annotation based on review of the literature for four key Aspergillus species: Aspergillus nidulans, Aspergillus oryzae, Aspergillus fumigatus and Aspergillus niger. We have iteratively improved the structural annotation of Aspergillus genomes through the analysis of publicly available transcription data, mostly expressed sequenced tags, as described in a previous NAR Database article (Arnaud et al. 2012). In this update, we report substantive structural annotation improvements for A. nidulans, A. oryzae and A. fumigatus genomes based on recently available RNA-Seq data. Over 26 000 loci were updated across these species; although those primarily comprise the addition and extension of untranslated regions (UTRs), the new analysis also enabled over 1000 modifications affecting the coding sequence of genes in each target genome.

The genome of Anopheles darlingi, the main neotropical malaria vector

Anopheles darlingi is the principal neotropical malaria vector, responsible for more than a million cases of malaria per year on the American continent. Anopheles darlingi diverged from the African and Asian malaria vectors ∼100 million years ago (mya) and successfully adapted to the New World environment. Here we present an annotated reference A. darlingi genome, sequenced from a wild population of males and females collected in the Brazilian Amazon. A total of 10 481 predicted protein-coding genes were annotated, 72% of which have their closest counterpart in Anopheles gambiae and 21% have highest similarity with other mosquito species. In spite of a long period of divergent evolution, conserved gene synteny was observed between A. darlingi and A. gambiae. More than 10 million single nucleotide polymorphisms and short indels with potential use as genetic markers were identified. Transposable elements correspond to 2.3% of the A. darlingi genome. Genes associated with hematophagy, immunity and insecticide resistance, directly involved in vector–human and vector–parasite interactions, were identified and discussed. This study represents the first effort to sequence the genome of a neotropical malaria vector, and opens a new window through which we can contemplate the evolutionary history of anopheline mosquitoes. It also provides valuable information that may lead to novel strategies to reduce malaria transmission on the South American continent. The A. darlingi genome is accessible at www.labinfo.lncc.br/index.php/anopheles-darlingi.

Transcript expression analysis of putative Trypanosoma brucei GPI-anchored surface proteins during development in the tsetse and mammalian hosts

Human African Trypanosomiasis is a devastating disease caused by the parasite Trypanosoma brucei. Trypanosomes live extracellularly in both the tsetse fly and the mammal. Trypanosome surface proteins can directly interact with the host environment, allowing parasites to effectively establish and maintain infections. Glycosylphosphatidylinositol (GPI) anchoring is a common posttranslational modification associated with eukaryotic surface proteins. In T. brucei, three GPI-anchored major surface proteins have been identified: variant surface glycoproteins (VSGs), procyclic acidic repetitive protein (PARP or procyclins), and brucei alanine rich proteins (BARP). The objective of this study was to select genes encoding predicted GPI-anchored proteins with unknown function(s) from the T. brucei genome and characterize the expression profile of a subset during cyclical development in the tsetse and mammalian hosts. An initial in silico screen of putative T. brucei proteins by Big PI algorithm identified 163 predicted GPI-anchored proteins, 106 of which had no known functions. Application of a second GPI-anchor prediction algorithm (FragAnchor), signal peptide and trans-membrane domain prediction software resulted in the identification of 25 putative hypothetical proteins. Eighty-one gene products with hypothetical functions were analyzed for stage-regulated expression using semi-quantitative RT-PCR. The expression of most of these genes were found to be upregulated in trypanosomes infecting tsetse salivary gland and proventriculus tissues, and 38% were specifically expressed only by parasites infecting salivary gland tissues. Transcripts for all of the genes specifically expressed in salivary glands were also detected in mammalian infective metacyclic trypomastigotes, suggesting a possible role for these putative proteins in invasion and/or establishment processes in the mammalian host. These results represent the first large-scale report of the differential expression of unknown genes encoding predicted T. brucei surface proteins during the complete developmental cycle. This knowledge may form the foundation for the development of future novel transmission blocking strategies against metacyclic parasites.

Human African Trypanosomiasis (HAT) is a fatal disease caused by African trypanosomes and transmitted by an infected tsetse fly. Presently, there are no vaccines to prevent mammalian infections. Proteins expressed on the trypanosome surface can influence the host environment and allow for their transmission. Potentially accessible to the adaptive immune systems of vertebrate hosts, these proteins could serve as future vaccine targets. Identification and characterization of these currently unknown proteins can help us develop strategies to alter the host environment, making it inhospitable for the parasite, thereby reducing disease transmission. While there is extensive knowledge about trypanosome development in the mammalian host, less is known about the molecular events in the tsetse fly, particularly the salivary gland stages. We used an in silico approach to identify putative surface proteins from the known genome sequence of Trypanosoma brucei, and we describe the stage specific expression of these genes during development in the tsetse fly and mammalian host. Our findings show that a majority of unknown transcripts encoding predicted surface proteins are expressed by the parasites infecting tsetse salivary glands. These data will help focus future investigations into transmission-blocking approaches targeting the expressed antigens of trypanosomes infecting tsetse salivary glands.

DIVERGENOME: a bioinformatics platform to assist population genetics and genetic epidemiology studies

Large-scale genomics initiatives such as the HapMap project and the 1000-genomes rely on powerful bioinformatics support to assist data production and analysis. Contrastingly, few bioinformatics platforms oriented to smaller research groups exist to store, handle, share, and integrate data from different sources, as well as to assist these scientists to perform their analyses efficiently. We developed such a bioinformatics platform, DIVERGENOME, to assist population genetics and genetic epidemiology studies performed by small- to medium-sized research groups. The platform is composed of two integrated components, a relational database (DIVERGENOMEdb), and a set of tools to convert data formats as required by popular software in population genetics and genetic epidemiology (DIVERGENOMEtools). In DIVERGENOMEdb, information on genotypes, polymorphism, laboratory protocols, individuals, populations, and phenotypes is organized in projects. These can be queried according to permissions. Here, we validated DIVERGENOME through a use case regarding the analysis of SLC2A4 genetic diversity in human populations. DIVERGENOME, with its intuitive Web interface and automatic data loading capability, facilitates its use by individuals without bioinformatics background, allowing complex queries to be easily interrogated and straightforward data format conversions (not available in similar platforms). DIVERGENOME is open source, freely available, and can be accessed online (pggenetica.icb.ufmg.br/divergenome) or hosted locally.

The Aspergillus Genome Database (AspGD): recent developments in comprehensive multispecies curation, comparative genomics and community resources

The Aspergillus Genome Database (AspGD; http://www.aspgd.org) is a freely available, web-based resource for researchers studying fungi of the genus Aspergillus, which includes organisms of clinical, agricultural and industrial importance. AspGD curators have now completed comprehensive review of the entire published literature about Aspergillus nidulans and Aspergillus fumigatus, and this annotation is provided with streamlined, ortholog-based navigation of the multispecies information. AspGD facilitates comparative genomics by providing a full-featured genomics viewer, as well as matched and standardized sets of genomic information for the sequenced aspergilli. AspGD also provides resources to foster interaction and dissemination of community information and resources. We welcome and encourage feedback at aspergillus-curator@lists.stanford.edu.

New resources for functional analysis of omics data for the genus Aspergillus

Background

Detailed and comprehensive genome annotation can be considered a prerequisite for effective analysis and interpretation of omics data. As such, Gene Ontology (GO) annotation has become a well accepted framework for functional annotation. The genus Aspergillus comprises fungal species that are important model organisms, plant and human pathogens as well as industrial workhorses. However, GO annotation based on both computational predictions and extended manual curation has so far only been available for one of its species, namely A. nidulans.

Results

Based on protein homology, we mapped 97% of the 3,498 GO annotated A. nidulans genes to at least one of seven other Aspergillus species: A. niger, A. fumigatus, A. flavus, A. clavatus, A. terreus, A. oryzae and Neosartorya fischeri. GO annotation files compatible with diverse publicly available tools have been generated and deposited online. To further improve their accessibility, we developed a web application for GO enrichment analysis named FetGOat and integrated GO annotations for all Aspergillus species with public genome sequences. Both the annotation files and the web application FetGOat are accessible via the Broad Institute's website (http://www.broadinstitute.org/fetgoat/index.html). To demonstrate the value of those new resources for functional analysis of omics data for the genus Aspergillus, we performed two case studies analyzing microarray data recently published for A. nidulans, A. niger and A. oryzae.

Conclusions

We mapped A. nidulans GO annotation to seven other Aspergilli. By depositing the newly mapped GO annotation online as well as integrating it into the web tool FetGOat, we provide new, valuable and easily accessible resources for omics data analysis and interpretation for the genus Aspergillus. Furthermore, we have given a general example of how a well annotated genome can help improving GO annotation of related species to subsequently facilitate the interpretation of omics data.

Identification of Schistosoma mansoni microRNAs

Background

MicroRNAs (miRNAs) constitute a class of single-stranded RNAs which play a crucial role in regulating development and controlling gene expression by targeting mRNAs and triggering either translation repression or messenger RNA (mRNA) degradation. miRNAs are widespread in eukaryotes and to date over 14,000 miRNAs have been identified by computational and experimental approaches. Several miRNAs are highly conserved across species. In Schistosoma, the full set of miRNAs and their expression patterns during development remain poorly understood. Here we report on the development and implementation of a homology-based detection strategy to search for miRNA genes in Schistosoma mansoni. In addition, we report results on the experimental detection of miRNAs by means of cDNA cloning and sequencing of size-fractionated RNA samples.

Results

Homology search using the high-throughput pipeline was performed with all known miRNAs in miRBase. A total of 6,211 mature miRNAs were used as reference sequences and 110 unique S. mansoni sequences were returned by BLASTn analysis. The existing mature miRNAs that produced these hits are reported, as well as the locations of the homologous sequences in the S. mansoni genome. All BLAST hits aligned with at least 95% of the miRNA sequence, resulting in alignment lengths of 19-24 nt. Following several filtering steps, 15 potential miRNA candidates were identified using this approach. By sequencing small RNA cDNA libraries from adult worm pairs, we identified 211 novel miRNA candidates in the S. mansoni genome. Northern blot analysis was used to detect the expression of the 30 most frequent sequenced miRNAs and to compare the expression level of these miRNAs between the lung stage schistosomula and adult worm stages. Expression of 11 novel miRNAs was confirmed by northern blot analysis and some presented a stage-regulated expression pattern. Three miRNAs previously identified from S. japonicum were also present in S. mansoni.

Conclusion

Evidence for the presence of miRNAs in S. mansoni is presented. The number of miRNAs detected by homology-based computational methods in S. mansoni is limited due to the lack of close relatives in the miRNA repository. In spite of this, the computational approach described here can likely be applied to the identification of pre-miRNA hairpins in other organisms. Construction and analysis of a small RNA library led to the experimental identification of 14 novel miRNAs from S. mansoni through a combination of molecular cloning, DNA sequencing and expression studies. Our results significantly expand the set of known miRNAs in multicellular parasites and provide a basis for understanding the structural and functional evolution of miRNAs in these metazoan parasites.

The genome of the blood fluke Schistosoma mansoni

Schistosoma mansoni is responsible for the neglected tropical disease schistosomiasis that affects 210 million people in 76 countries. We report here analysis of the 363 megabase nuclear genome of the blood fluke. It encodes at least 11,809 genes, with an unusual intron size distribution, and novel families of micro-exon genes that undergo frequent alternate splicing. As the first sequenced flatworm, and a representative of the lophotrochozoa, it offers insights into early events in the evolution of the animals, including the development of a body pattern with bilateral symmetry, and the development of tissues into organs. Our analysis has been informed by the need to find new drug targets. The deficits in lipid metabolism that make schistosomes dependent on the host are revealed, while the identification of membrane receptors, ion channels and more than 300 proteases, provide new insights into the biology of the life cycle and novel targets. Bioinformatics approaches have identified metabolic chokepoints while a chemogenomic screen has pinpointed schistosome proteins for which existing drugs may be active. The information generated provides an invaluable resource for the research community to develop much needed new control tools for the treatment and eradication of this important and neglected disease.

Genomic organization and expression profile of the mucin-associated surface protein (masp) family of the human pathogen Trypanosoma cruzi

A novel large multigene family was recently identified in the human pathogen Trypanosoma cruzi, causative agent of Chagas disease, and corresponds to ∼6% of the parasite diploid genome. The predicted gene products, mucin-associated surface proteins (MASPs), are characterized by highly conserved N- and C-terminal domains and a strikingly variable and repetitive central region. We report here an analysis of the genomic organization and expression profile of masp genes. Masps are not randomly distributed throughout the genome but instead are clustered with genes encoding mucin and other surface protein families. Masp transcripts vary in size, are preferentially expressed during the trypomastigote stage and contain highly conserved 5′ and 3′ untranslated regions. A sequence analysis of a trypomastigote cDNA library reveals the expression of multiple masp variants with a bias towards a particular masp subgroup. Immunofluorescence assays using antibodies generated against a MASP peptide reveals that the expression of particular MASPs at the cell membrane is limited to subsets of the parasite population. Western blots of phosphatidylinositol-specific phospholipase C (PI-PLC)-treated parasites suggest that MASP may be GPI-anchored and shed into the medium culture, thus contributing to the large repertoire of parasite polypeptides that are exposed to the host immune system.

Schistosoma mansoni: Microarray analysis of gene expression induced by host sex

Schistosoma mansoni is a digenetic trematode and a human parasite responsible for high social and economic impact. Although some authors have studied the effect of host hormones on parasites, not much is known about the effects of host sex on gene expression in Schistosomes. In order to study gene transcripts associated with the host sex, we compared the gene expression profiles of both male and female unisexual adult S. mansoni parasites raised on either male or female hosts, using DNA microarrays. Our results show that host sex caused differential expression of at least 11 genes in female parasites and of 134 in male parasites. Of the differentially expressed genes in female worms, 10 were preferentially expressed in female worms from male mice, while of the 134 differentially expressed genes in male parasites, 79 (59%) were preferentially expressed in worms from female mice. Further investigation of the role of each of those genes will help understand better their importance in the pathogenesis of Schistosomiasis.

Sequences involved in mRNA processing in Trypanosoma cruzi

Gene expression in Trypanosomatids requires processing of polycistronic transcripts to generate monocistronic mRNAs by cleavage events that are coupled to the addition of a Spliced Leader sequence (SL) at the 5'-end and a poly(A) tail at the 3'-end of each mRNA. Here we investigate the sequence requirements involved in Trypanosoma cruzi mRNA processing by mapping all available expressed sequence tags and cDNAs containing poly(A) tail and/or SL to genomic intergenic regions. Amongst other parameters, we determined that the median lengths of 5' untranslated region (UTR) and 3'UTR sequences are 35 and 264 nucleotides, respectively; and that the median distance between SL addition sites and a polypyrimidine motif is 18 nucleotides, whereas the median distance between poly(A) addition sites and the closest polypyrimidine-rich sequence is 40 nucleotides.

Sequence diversity and evolution of multigene families in Trypanosoma cruzi

Several copies of genes belonging to three multigene families present in the genome of Trypanosoma cruzi were sequenced and comparatively analyzed across six different strains of the parasite belonging to the T. cruzi I lineage (Colombiana, Silvio X10 and Dm28c), the T. cruzi II lineage (Esmeraldo and JG) and a hybrid strain (CL Brener). For all three gene families analyzed, our results support the division in T. cruzi I and II lineages. Furthermore, in agreement with its hybrid nature, sequences derived from the CL Brener clone clustered together with T. cruzi II sequences as well as with a third group of sequences. Paralogous sequences encoding Amastin, an amastigote surface glycoprotein and TcAG48, an antigenic RNA binding protein, which are clustered in the parasite genome, present higher intragenomic variability in T. cruzi II and CL Brener strains, when compared to T. cruzi I strains. Paralogous sequences derived from the TcADC gene family, which encode various isoforms of adenylyl cyclases and are dispersed throughout the T. cruzi genome, exhibit similar degree of variability in all strains, except in the CL Brener strain, in which the sequences were more divergent. Several factors including mutation rates and gene conversion mechanisms, acting differently within the T. cruzi population, may contribute to create such distinct levels of sequence diversity in multigene families that are clustered in the T. cruzi genome.

Microarray analysis of gene expression induced by sexual contact in Schistosoma mansoni

Background

The parasitic trematode Schistosoma mansoni is one of the major causative agents of Schistosomiasis, a disease that affects approximately 200 million people, mostly in developing countries. Since much of the pathology is associated with eggs laid by the female worm, understanding the mechanisms involved in oogenesis and sexual maturation is an important step towards the discovery of new targets for effective drug therapy. It is known that the adult female worm only develops fully in the presence of a male worm and that the rates of oviposition and maturation of eggs are significantly increased by mating. In order to study gene transcripts associated with sexual maturation and oviposition, we compared the gene expression profiles of sexually mature and immature parasites using DNA microarrays.

Results

For each experiment, three amplified RNA microarray hybridizations and their dye swaps were analyzed. Our results show that 265 transcripts are differentially expressed in adult females and 53 in adult males when mature and immature worms are compared. Of the genes differentially expressed, 55% are expressed at higher levels in paired females while the remaining 45% are more expressed in unpaired ones and 56.6% are expressed at higher levels in paired male worms while the remaining 43.4% are more expressed in immature parasites. Real-time RT-PCR analysis validated the microarray results. Several new maturation associated transcripts were identified. Genes that were up-regulated in single-sex females were mostly related to energy generation (i.e. carbohydrate and protein metabolism, generation of precursor metabolites and energy, cellular catabolism, and organelle organization and biogenesis) while genes that were down-regulated related to RNA metabolism, reactive oxygen species metabolism, electron transport, organelle organization and biogenesis and protein biosynthesis.

Conclusion

Our results confirm previous observations related to gene expression induced by sexual maturation in female schistosome worms. They also increase the list of S. mansoni maturation associated transcripts considerably, therefore opening new and exciting avenues for the study of the conjugal biology and development of new drugs against schistosomes.

Trypanosoma cruzi mitochondrial maxicircles display species- and strain-specific variation and a conserved element in the non-coding region

BACKGROUND

The mitochondrial DNA of kinetoplastid flagellates is distinctive in the eukaryotic world due to its massive size, complex form and large sequence content. Comprised of catenated maxicircles that contain rRNA and protein-coding genes and thousands of heterogeneous minicircles encoding small guide RNAs, the kinetoplast network has evolved along with an extreme form of mRNA processing in the form of uridine insertion and deletion RNA editing. Many maxicircle-encoded mRNAs cannot be translated without this post-transcriptional sequence modification.

RESULTS

We present the complete sequence and annotation of the Trypanosoma cruzi maxicircles for the CL Brener and Esmeraldo strains. Gene order is syntenic with Trypanosoma brucei and Leishmania tarentolae maxicircles. The non-coding components have strain-specific repetitive regions and a variable region that is unique for each strain with the exception of a conserved sequence element that may serve as an origin of replication, but shows no sequence identity with L. tarentolae or T. brucei. Alternative assemblies of the variable region demonstrate intra-strain heterogeneity of the maxicircle population. The extent of mRNA editing required for particular genes approximates that seen in T. brucei. Extensively edited genes were more divergent among the genera than non-edited and rRNA genes. Esmeraldo contains a unique 236-bp deletion that removes the 5'-ends of ND4 and CR4 and the intergenic region. Esmeraldo shows additional insertions and deletions outside of areas edited in other species in ND5, MURF1, and MURF2, while CL Brener has a distinct insertion in MURF2.

CONCLUSION

The CL Brener and Esmeraldo maxicircles represent two of three previously defined maxicircle clades and promise utility as taxonomic markers. Restoration of the disrupted reading frames might be accomplished by strain-specific RNA editing. Elements in the non-coding region may be important for replication, transcription, and anchoring of the maxicircle within the kinetoplast network.

Analysis of expressed sequence tags from Trypanosoma cruzi amastigotes

A total of 880 expressed sequence tags (EST) originated from clones randomly selected from a Trypanosoma cruzi amastigote cDNA library have been analyzed. Of these, 40% (355 ESTs) have been identified by similarity to sequences in public databases and classified according to functional categorization of their putative products. About 11% of the mRNAs expressed in amastigotes are related to the translational machinery, and a large number of them (9% of the total number of clones in the library) encode ribosomal proteins. A comparative analysis with a previous study, where clones from the same library were selected using sera from patients with Chagas disease, revealed that ribosomal proteins also represent the largest class of antigen coding genes expressed in amastigotes (54% of all immunoselected clones). However, although more than thirty classes of ribosomal proteins were identified by EST analysis, the results of the immunoscreening indicated that only a particular subset of them contains major antigenic determinants recognized by antibodies from Chagas disease patients.

The genome sequence of Trypanosoma cruzi, etiologic agent of Chagas disease

Whole-genome sequencing of the protozoan pathogen Trypanosoma cruzi revealed that the diploid genome contains a predicted 22,570 proteins encoded by genes, of which 12,570 represent allelic pairs. Over 50% of the genome consists of repeated sequences, such as retrotransposons and genes for large families of surface molecules, which include trans-sialidases, mucins, gp63s, and a large novel family (>1300 copies) of mucin-associated surface protein (MASP) genes. Analyses of the T. cruzi, T. brucei, and Leishmania major (Tritryp) genomes imply differences from other eukaryotes in DNA repair and initiation of replication and reflect their unusual mitochondrial DNA. Although the Tritryp lack several classes of signaling molecules, their kinomes contain a large and diverse set of protein kinases and phosphatases; their size and diversity imply previously unknown interactions and regulatory processes, which may be targets for intervention.

Comparative genomics of trypanosomatid parasitic protozoa

A comparison of gene content and genome architecture of Trypanosoma brucei, Trypanosoma cruzi, and Leishmania major, three related pathogens with different life cycles and disease pathology, revealed a conserved core proteome of about 6200 genes in large syntenic polycistronic gene clusters. Many species-specific genes, especially large surface antigen families, occur at nonsyntenic chromosome-internal and subtelomeric regions. Retroelements, structural RNAs, and gene family expansion are often associated with syntenic discontinuities that-along with gene divergence, acquisition and loss, and rearrangement within the syntenic regions-have shaped the genomes of each parasite. Contrary to recent reports, our analyses reveal no evidence that these species are descended from an ancestor that contained a photosynthetic endosymbiont.

Identification and characterization of a novel mouse gene encoding a Ras-associated guanine nucleotide exchange factor: expression in macrophages and myocarditis elicited by Trypanosoma cruzi parasites

The ability of Trypanosoma cruzi to activate macrophages is, at least in part, attributed to the glycosylphosphatidylinositol-anchored mucin-like glycoproteins (GPI-mucins) expressed in the surface of the trypomastigote stage of the parasite. The differential display reverse transcriptase-polymerase chain reaction and the reverse Northern blot were used to study modulation of gene expression in murine macrophages exposed to GPI-mucins and in cardiac tissues from mice infected with T. cruzi. Among several cDNAs that were more abundant in lanes corresponding to macrophages stimulated with GPI-mucins as compared with resting cells, we confirmed the differential expression of A1, interleukin-18, and GPIgamma4. Some of these genes were also shown to have enhanced expression in the cardiac tissue (DAP-12, A1, and GPIgamma4) from infected animals. The expression of GPIgamma4 was also enhanced in human monocytes stimulated with GPI-mucins or bacterial lipopolysaccharides. The complete sequence of the GPIgamma4 transcript and its gene including the 5' upstream region was defined. GPIgamma4 was encoded by a novel, single copy gene present in mouse as well as human genomes and showed conserved homology to different members of the guanine nucleotide exchange factor family.