A Grid-based Method for Removing Overlaps of Dimensionality Reduction Scatterplot Layouts.

Dimensionality Reduction (DR) scatterplot layouts have become a ubiquitous visualization tool for analyzing multidimensional datasets. Despite their popularity, such scatterplots suffer from occlusion, especially when informative glyphs are used to represent data instances, potentially obfuscating critical information for the analysis under execution. Different strategies have been devised to address this issue, either producing overlap-free layouts that lack the powerful capabilities of contemporary DR techniques in uncovering interesting data patterns or eliminating overlaps as a post-processing strategy. Despite the good results of post-processing techniques, most of the best methods typically expand or distort the scatterplot area, thus reducing glyphs' size (sometimes) to unreadable dimensions, defeating the purpose of removing overlaps. This paper presents Distance Grid (DGrid), a novel post-processing strategy to remove overlaps from DR layouts that faithfully preserves the original layout's characteristics and bounds the minimum glyph sizes. We show that DGrid surpasses the state-of-the-art in overlap removal (through an extensive comparative evaluation considering multiple different metrics) while also being one of the fastest techniques, especially for large datasets. A user study with 51 participants also shows that DGrid is consistently ranked among the top techniques for preserving the original scatterplots' visual characteristics and the aesthetics of the final results.

The Flow of Trust: A Visualization Framework to Externalize, Explore, and Explain Trust in ML Applications.

We present a conceptual framework for the development of visual interactive techniques to formalize and externalize trust in machine learning (ML) workflows. Currently, trust in ML applications is an implicit process that takes place in the user's mind. As such, there is no method of feedback or communication of trust that can be acted upon. Our framework will be instrumental in developing interactive visualization approaches that will help users to efficiently and effectively build and communicate trust in ways that fit each of the ML process stages. We formulate several research questions and directions that include: 1) a typology/taxonomy of trust objects, trust issues, and possible reasons for (mis)trust; 2) formalisms to represent trust in machine-readable form; 3) means by which users can express their state of trust by interacting with a computer system (e.g., text, drawing, marking); 4) ways in which a system can facilitate users' expression and communication of the state of trust; and 5) creation of visual interactive techniques for representation and exploration of trust over all stages of an ML pipeline.

FeatureEnVi: Visual Analytics for Feature Engineering Using Stepwise Selection and Semi-Automatic Extraction Approaches.

The machine learning (ML) life cycle involves a series of iterative steps, from the effective gathering and preparation of the data-including complex feature engineering processes-to the presentation and improvement of results, with various algorithms to choose from in every step. Feature engineering in particular can be very beneficial for ML, leading to numerous improvements such as boosting the predictive results, decreasing computational times, reducing excessive noise, and increasing the transparency behind the decisions taken during the training. Despite that, while several visual analytics tools exist to monitor and control the different stages of the ML life cycle (especially those related to data and algorithms), feature engineering support remains inadequate. In this paper, we present FeatureEnVi, a visual analytics system specifically designed to assist with the feature engineering process. Our proposed system helps users to choose the most important feature, to transform the original features into powerful alternatives, and to experiment with different feature generation combinations. Additionally, data space slicing allows users to explore the impact of features on both local and global scales. FeatureEnVi utilizes multiple automatic feature selection techniques; furthermore, it visually guides users with statistical evidence about the influence of each feature (or subsets of features). The final outcome is the extraction of heavily engineered features, evaluated by multiple validation metrics. The usefulness and applicability of FeatureEnVi are demonstrated with two use cases and a case study. We also report feedback from interviews with two ML experts and a visualization researcher who assessed the effectiveness of our system.

Identification of long regulatory elements in the genome of Plasmodium falciparum and other eukaryotes.

Long regulatory elements (LREs), such as CpG islands, polydA:dT tracts or AU-rich elements, are thought to play key roles in gene regulation but, as opposed to conventional binding sites of transcription factors, few methods have been proposed to formally and automatically characterize them. We present here a computational approach named DExTER (Domain Exploration To Explain gene Regulation) dedicated to the identification of candidate LREs (cLREs) and apply it to the analysis of the genomes of P. falciparum and other eukaryotes. Our analyses show that all tested genomes contain several cLREs that are somewhat conserved along evolution, and that gene expression can be predicted with surprising accuracy on the basis of these long regions only. Regulation by cLREs exhibits very different behaviours depending on species and conditions. In P. falciparum and other Apicomplexan organisms as well as in Dictyostelium discoideum, the process appears highly dynamic, with different cLREs involved at different phases of the life cycle. For multicellular organisms, the same cLREs are involved in all tissues, but a dynamic behavior is observed along embryonic development stages. In P. falciparum, whose genome is known to be strongly depleted of transcription factors, cLREs are predictive of expression with an accuracy above 70%, and our analyses show that they are associated with both transcriptional and post-transcriptional regulation signals. Moreover, we assessed the biological relevance of one LRE discovered by DExTER in P. falciparum using an in vivo reporter assay. The source code (python) of DExTER is available at https://gite.lirmm.fr/menichelli/DExTER.

PfGBP2 is a novel G-quadruplex binding protein in Plasmodium falciparum.

Guanine-quadruplexes (G4s) are non-canonical DNA structures that can regulate key biological processes such as transcription, replication and telomere maintenance in several organisms including eukaryotes, prokaryotes and viruses. Recent reports have identified the presence of G4s within the AT-rich genome of Plasmodium falciparum, the protozoan parasite causing malaria. In Plasmodium, potential G4-forming sequences (G4FS) are enriched in the telomeric and sub-telomeric regions of the genome where they are associated with telomere maintenance and recombination events within virulence genes. However, there is a little understanding about the biological role of G4s and G4-binding proteins. Here, we provide the first snapshot of G4-interactome in P. falciparum using DNA pull-down assay followed by LC-MS/MS. Interestingly, we identified ~24 potential G4-binding proteins (G4-BP) that bind to a stable G4FS (AP2_G4). Furthermore, we characterised the role of G-strand binding protein 2 (PfGBP2), a putative telomere-binding protein in P. falciparum. We validated the interaction of PfGBP2 with G4 in vitro as well as in vivo. PfGBP2 is expressed throughout the intra-erythrocytic developmental cycle and is essential for the parasites in the presence of G4-stabilising ligand, pyridostatin. Gene knockout studies showed the role of PfGBP2 in the expression of var genes. Taken together, this study suggests that PfGBP2 is a bona fide G4-binding protein, which is likely to be involved in the regulation of G4-related functions in these malarial parasites. In addition, this study sheds light on this understudied G4 biology in P. falciparum.

Toward a Quantitative Survey of Dimension Reduction Techniques.

Dimensionality reduction methods, also known as projections, are frequently used in multidimensional data exploration in machine learning, data science, and information visualization. Tens of such techniques have been proposed, aiming to address a wide set of requirements, such as ability to show the high-dimensional data structure, distance or neighborhood preservation, computational scalability, stability to data noise and/or outliers, and practical ease of use. However, it is far from clear for practitioners how to choose the best technique for a given use context. We present a survey of a wide body of projection techniques that helps answering this question. For this, we characterize the input data space, projection techniques, and the quality of projections, by several quantitative metrics. We sample these three spaces according to these metrics, aiming at good coverage with bounded effort. We describe our measurements and outline observed dependencies of the measured variables. Based on these results, we draw several conclusions that help comparing projection techniques, explain their results for different types of data, and ultimately help practitioners when choosing a projection for a given context. Our methodology, datasets, projection implementations, metrics, visualizations, and results are publicly open, so interested stakeholders can examine and/or extend this benchmark.

StackGenVis: Alignment of Data, Algorithms, and Models for Stacking Ensemble Learning Using Performance Metrics.

In machine learning (ML), ensemble methods-such as bagging, boosting, and stacking-are widely-established approaches that regularly achieve top-notch predictive performance. Stacking (also called "stacked generalization") is an ensemble method that combines heterogeneous base models, arranged in at least one layer, and then employs another metamodel to summarize the predictions of those models. Although it may be a highly-effective approach for increasing the predictive performance of ML, generating a stack of models from scratch can be a cumbersome trial-and-error process. This challenge stems from the enormous space of available solutions, with different sets of data instances and features that could be used for training, several algorithms to choose from, and instantiations of these algorithms using diverse parameters (i.e., models) that perform differently according to various metrics. In this work, we present a knowledge generation model, which supports ensemble learning with the use of visualization, and a visual analytics system for stacked generalization. Our system, StackGenVis, assists users in dynamically adapting performance metrics, managing data instances, selecting the most important features for a given data set, choosing a set of top-performant and diverse algorithms, and measuring the predictive performance. In consequence, our proposed tool helps users to decide between distinct models and to reduce the complexity of the resulting stack by removing overpromising and underperforming models. The applicability and effectiveness of StackGenVis are demonstrated with two use cases: a real-world healthcare data set and a collection of data related to sentiment/stance detection in texts. Finally, the tool has been evaluated through interviews with three ML experts.

Plasmodium falciparum sexual parasites regulate infected erythrocyte permeability.

To ensure the transport of nutrients necessary for their survival, Plasmodium falciparum parasites increase erythrocyte permeability to diverse solutes. These new permeation pathways (NPPs) have been extensively characterized in the pathogenic asexual parasite stages, however the existence of NPPs has never been investigated in gametocytes, the sexual stages responsible for transmission to mosquitoes. Here, we show that NPPs are still active in erythrocytes infected with immature gametocytes and that this activity declines along gametocyte maturation. Our results indicate that NPPs are regulated by cyclic AMP (cAMP) signaling cascade, and that the decrease in cAMP levels in mature stages results in a slowdown of NPP activity. We also show that NPPs facilitate the uptake of artemisinin derivatives and that phosphodiesterase (PDE) inhibitors can reactivate NPPs and increase drug uptake in mature gametocytes. These processes are predicted to play a key role in P. falciparum gametocyte biology and susceptibility to antimalarials.

Plasmodium falciparum sexual parasites develop in human erythroblasts and affect erythropoiesis.

Plasmodium falciparum gametocytes, the sexual stage responsible for malaria parasite transmission from humans to mosquitoes, are key targets for malaria elimination. Immature gametocytes develop in the human bone marrow parenchyma, where they accumulate around erythroblastic islands. Notably though, the interactions between gametocytes and this hematopoietic niche have not been investigated. Here, we identify late erythroblasts as a new host cell for P falciparum sexual stages and show that gametocytes can fully develop inside these nucleated cells in vitro and in vivo, leading to infectious mature gametocytes within reticulocytes. Strikingly, we found that infection of erythroblasts by gametocytes and parasite-derived extracellular vesicles delay erythroid differentiation, thereby allowing gametocyte maturation to coincide with the release of their host cell from the bone marrow. Taken together, our findings highlight new mechanisms that are pivotal for the maintenance of immature gametocytes in the bone marrow and provide further insights on how Plasmodium parasites interfere with erythropoiesis and contribute to anemia in malaria patients.

t-viSNE: Interactive Assessment and Interpretation of t-SNE Projections.

t-Distributed Stochastic Neighbor Embedding (t-SNE) for the visualization of multidimensional data has proven to be a popular approach, with successful applications in a wide range of domains. Despite their usefulness, t-SNE projections can be hard to interpret or even misleading, which hurts the trustworthiness of the results. Understanding the details of t-SNE itself and the reasons behind specific patterns in its output may be a daunting task, especially for non-experts in dimensionality reduction. In this article, we present t-viSNE, an interactive tool for the visual exploration of t-SNE projections that enables analysts to inspect different aspects of their accuracy and meaning, such as the effects of hyper-parameters, distance and neighborhood preservation, densities and costs of specific neighborhoods, and the correlations between dimensions and visual patterns. We propose a coherent, accessible, and well-integrated collection of different views for the visualization of t-SNE projections. The applicability and usability of t-viSNE are demonstrated through hypothetical usage scenarios with real data sets. Finally, we present the results of a user study where the tool's effectiveness was evaluated. By bringing to light information that would normally be lost after running t-SNE, we hope to support analysts in using t-SNE and making its results better understandable.

Plasmodium falciparum gametocyte-infected erythrocytes do not adhere to human primary erythroblasts.

Plasmodium falciparum gametocytes, the sexual stages responsible for malaria parasite transmission, develop in the human bone marrow parenchyma in proximity to the erythroblastic islands. Yet, mechanisms underlying gametocytes interactions with these islands are unknown. Here, we have investigated whether gametocyte-infected erythrocytes (GIE) adhere to erythroid precursors, and whether a putative adhesion may be mediated by a mechanism similar to the adhesion of erythrocytes infected with P. falciparum asexual stages to uninfected erythrocytes. Cell-cell adhesion assays with human primary erythroblasts or erythroid cell lines revealed that immature GIE do not specifically adhere to erythroid precursors. To determine whether adhesion may be dependent on binding of STEVOR proteins to Glycophorin C on the surface of erythroid cells, we used clonal lines and transgenic parasites that overexpress specific STEVOR proteins known to bind to Glycophorin C in asexual stages. Our results indicate that GIE overexpressing STEVOR do not specifically adhere to erythroblasts, in agreement with our observation that the STEVOR adhesive domain is not exposed at the surface of GIE.

An ApiAP2 member regulates expression of clonally variant genes of the human malaria parasite Plasmodium falciparum.

Variegated surface antigen expression is key to chronic infection and pathogenesis of the human malaria parasite Plasmodium falciparum. This protozoan parasite expresses distinct surface molecules that are encoded by clonally variant gene families such as var, rif and stevor. The molecular mechanisms governing activation of individual members remain ill-defined. To investigate the molecular events of the initial transcriptional activation process we focused on a member of the apicomplexan ApiAP2 transcription factor family predicted to bind to the 5' upstream regions of the var gene family, AP2-exp (PF3D7_1466400). Viable AP2-exp mutant parasites rely on expressing no less than a short truncated protein including the N-terminal AP2 DNA-binding domain. RNA-seq analysis in mutant parasites revealed transcriptional changes in a subset of exported proteins encoded by clonally variant gene families. Upregulation of RIFINs and STEVORs was validated at the protein levels. In addition, morphological alterations were observed on the surface of the host cells infected by the mutants. This work points to a complex regulatory network of clonally variant gene families in which transcription of a subset of members is regulated by the same transcription factor. In addition, we highlight the importance of the non-DNA binding AP2 domain in functional gene regulation.

Exonuclease-mediated degradation of nascent RNA silences genes linked to severe malaria.

Antigenic variation of the Plasmodium falciparum multicopy var gene family enables parasite evasion of immune destruction by host antibodies. Expression of a particular var subgroup, termed upsA, is linked to the obstruction of blood vessels in the brain and to the pathogenesis of human cerebral malaria. The mechanism determining upsA activation remains unknown. Here we show that an entirely new type of gene silencing mechanism involving an exonuclease-mediated degradation of nascent RNA controls the silencing of genes linked to severe malaria. We identify a novel chromatin-associated exoribonuclease, termed PfRNase II, that controls the silencing of upsA var genes by marking their transcription start site and intron-promoter regions leading to short-lived cryptic RNA. Parasites carrying a deficient PfRNase II gene produce full-length upsA var transcripts and intron-derived antisense long non-coding RNA. The presence of stable upsA var transcripts overcomes monoallelic expression, resulting in the simultaneous expression of both upsA and upsC type PfEMP1 proteins on the surface of individual infected red blood cells. In addition, we observe an inverse relationship between transcript levels of PfRNase II and upsA-type var genes in parasites from severe malaria patients, implying a crucial role of PfRNase II in severe malaria. Our results uncover a previously unknown type of post-transcriptional gene silencing mechanism in malaria parasites with repercussions for other organisms. Additionally, the identification of RNase II as a parasite protein controlling the expression of virulence genes involved in pathogenesis in patients with severe malaria may provide new strategies for reducing malaria mortality.

Strand-specific RNA-Seq reveals widespread and developmentally regulated transcription of natural antisense transcripts in Plasmodium falciparum.

BACKGROUND: Advances in high-throughput sequencing have led to the discovery of widespread transcription of natural antisense transcripts (NATs) in a large number of organisms, where these transcripts have been shown to play important roles in the regulation of gene expression. Likewise, the existence of NATs has been observed in Plasmodium but our understanding towards their genome-wide distribution remains incomplete due to the limited depth and uncertainties in the level of strand specificity of previous datasets. RESULTS: To gain insights into the genome-wide distribution of NATs in P. falciparum, we performed RNA-ligation based strand-specific RNA sequencing at unprecedented depth. Our data indicate that 78.3% of the genome is transcribed during blood-stage development. Moreover, our analysis reveals significant levels of antisense transcription from at least 24% of protein-coding genes and that while expression levels of NATs change during the intraerythrocytic developmental cycle (IDC), they do not correlate with the corresponding mRNA levels. Interestingly, antisense transcription is not evenly distributed across coding regions (CDSs) but strongly clustered towards the 3'-end of CDSs. Furthermore, for a significant subset of NATs, transcript levels correlate with mRNA levels of neighboring genes.Finally, we were able to identify the polyadenylation sites (PASs) for a subset of NATs, demonstrating that at least some NATs are polyadenylated. We also mapped the PASs of 3443 coding genes, yielding an average 3' untranslated region length of 523 bp. CONCLUSIONS: Our strand-specific analysis of the P. falciparum transcriptome expands and strengthens the existing body of evidence that antisense transcription is a substantial phenomenon in P. falciparum. For a subset of neighboring genes we find that sense and antisense transcript levels are intricately linked while other NATs appear to be regulated independently of mRNA transcription. Our deep strand-specific dataset will provide a valuable resource for the precise determination of expression levels as it separates sense from antisense transcript levels, which we find to often significantly differ. In addition, the extensive novel data on 3' UTR length will allow others to perform searches for regulatory motifs in the UTRs and help understand post-translational regulation in P. falciparum.

Differential expression profiles in the midgut of Triatoma infestans infected with Trypanosoma cruzi.

Chagas disease, or American trypanosomiasis, is a parasitic disease caused by the protozoan Trypanosoma cruzi and is transmitted by insects from the Triatominae subfamily. To identify components involved in the protozoan-vector relationship, we constructed and analyzed cDNA libraries from RNA isolated from the midguts of uninfected and T. cruzi-infected Triatoma infestans, which are major vectors of Chagas disease. We generated approximately 440 high-quality Expressed Sequence Tags (ESTs) from each T. infestans midgut cDNA library. The sequences were grouped in 380 clusters, representing an average length of 664.78 base pairs (bp). Many clusters were not classified functionally, representing unknown transcripts. Several transcripts involved in different processes (e.g., detoxification) showed differential expression in response to T. cruzi infection. Lysozyme, cathepsin D, a nitrophorin-like protein and a putative 14 kDa protein were significantly upregulated upon infection, whereas thioredoxin reductase was downregulated. In addition, we identified several transcripts related to metabolic processes or immunity with unchanged expressions, including infestin, lipocalins and defensins. We also detected ESTs encoding juvenile hormone binding protein (JHBP), which seems to be involved in insect development and could be a target in control strategies for the vector. This work demonstrates differential gene expression upon T. cruzi infection in the midgut of T. infestans. These data expand the current knowledge regarding vector-parasite interactions for Chagas disease.

Differential infectivity by the oral route of Trypanosoma cruzi lineages derived from Y strain.

BACKGROUND: Diversity of T. cruzi strains is a central problem in Chagas disease research because of its correlation with the wide range of clinical manifestations and the biogeographical parasite distribution. The role played by parasite microdiversity in Chagas disease epidemiology is still debatable. Also awaits clarification whether such diversity is associated with the outcome of oral T. cruzi infection, responsible for frequent outbreaks of acute Chagas disease. METHODS AND FINDINGS: We addressed the impact of microdiversity in oral T. cruzi infection, by comparative analysis of two strains, Y30 and Y82, both derived from Y strain, a widely used experimental model. Network genealogies of four nuclear genes (SSU rDNA, actin, DHFR-TS, EF1α) revealed that Y30 is closely related to Discrete Typing Unit TcII while Y82 is more closely related to TcVI, a group containing hybrid strains. Nevertheless, excepting one A-G transition at position 1463, Y30 and Y82 SSU rDNAs were identical. Y82 strain, expressing the surface molecule gp82, infected mice orally more efficiently than Y30, which expresses a related gp30 molecule. Both molecules are involved in lysosome exocytosis-dependent host cell invasion, but exhibit differential gastric mucin-binding capacity, a property critical for parasite migration toward the gastric mucosal epithelium. Upon oral infection of mice, the number of Y30 and Y82 parasites in gastric epithelial cells differed widely. CONCLUSIONS: We conclude that metacyclic forms of gp82-expressing Y82 strain, closely related to TcVI, are better adapted than Y30 strain (TcII) to traverse the stomach mucous layer and establish oral route infection. The efficiency to infect target cell is the same because gp82 and gp30 strains have similar invasion-promoting properties. Unknown is whether differences in Y30 and Y82 are natural parasite adaptations or a product of lab-induced evolution by differential selection along the 60 years elapsed since the Y strain isolation.

Tigutcystatin, a cysteine protease inhibitor from Triatoma infestans midgut expressed in response to Trypanosoma cruzi.

The insect Triatoma infestans is a vector of Trypanosoma cruzi, the etiological agent of Chagas disease. A cDNA library was constructed from T. infestans anterior midgut, and 244 clones were sequenced. Among the EST sequences, an open reading frame (ORF) with homology to a cystatin type 2 precursor was identified. Then, a 288-bp cDNA fragment encoding mature cystatin (lacking signal peptide) named Tigutcystatin was cloned fused to a N-terminal His tag in pET-14b vector, and the protein expressed in Escherichia coli strain Rosetta gami. Tigutcystatin purified and cleaved by thrombin to remove His tag presented molecular mass of 11 kDa and 10,137 Da by SDS-PAGE and MALDI-TOF mass spectrometry, respectively. Purified Tigutcystatin was shown to be a tight inhibitor towards cruzain, a T. cruzi cathepsin L-like enzyme (K(i)=3.29 nM) and human cathepsin L (K(i)=3.78 nM). Tissue specific expression analysis showed that Tigutcystatin was mostly expressed in anterior midgut, although amplification in small intestine was also detected by semi quantitative RT-PCR. qReal time PCR confirmed that Tigutcystatin mRNA is significantly up-regulated in anterior midgut when T. infestans is infected with T. cruzi. Together, these results indicate that Tigutcystatin may be involved in modulation of T. cruzi in intestinal tract by inhibiting parasite cysteine proteases, which represent the virulence factors of this protozoan.

A cyclopalladated complex interacts with mitochondrial membrane thiol-groups and induces the apoptotic intrinsic pathway in murine and cisplatin-resistant human tumor cells.

BACKGROUND: Systemic therapy for cancer metastatic lesions is difficult and generally renders a poor clinical response. Structural analogs of cisplatin, the most widely used synthetic metal complexes, show toxic side-effects and tumor cell resistance. Recently, palladium complexes with increased stability are being investigated to circumvent these limitations, and a biphosphinic cyclopalladated complex {Pd(2) [S((-))C(2), N-dmpa](2) (µ-dppe)Cl(2)} named C7a efficiently controls the subcutaneous development of B16F10-Nex2 murine melanoma in syngeneic mice. Presently, we investigated the melanoma cell killing mechanism induced by C7a, and extended preclinical studies. METHODS: B16F10-Nex2 cells were treated in vitro with C7a in the presence/absence of DTT, and several parameters related to apoptosis induction were evaluated. Preclinical studies were performed, and mice were endovenously inoculated with B16F10-Nex2 cells, intraperitoneally treated with C7a, and lung metastatic nodules were counted. The cytotoxic effects and the respiratory metabolism were also determined in human tumor cell lines treated in vitro with C7a. RESULTS: Cyclopalladated complex interacts with thiol groups on the mitochondrial membrane proteins, causes dissipation of the mitochondrial membrane potential, and induces Bax translocation from the cytosol to mitochondria, colocalizing with a mitochondrial tracker. C7a also induced an increase in cytosolic calcium concentration, mainly from intracellular compartments, and a significant decrease in the ATP levels. Activation of effector caspases, chromatin condensation and DNA degradation, suggested that C7a activates the apoptotic intrinsic pathway in murine melanoma cells. In the preclinical studies, the C7a complex protected against murine metastatic melanoma and induced death in several human tumor cell lineages in vitro, including cisplatin-resistant ones. The mitochondria-dependent cell death was also induced by C7a in human tumor cells. CONCLUSIONS: The cyclopalladated C7a complex is an effective chemotherapeutic anticancer compound against primary and metastatic murine and human tumors, including cisplatin-resistant cells, inducing apoptotic cell death via the intrinsic pathway.

Gcn1 and actin binding to Yih1: implications for activation of the eIF2 kinase GCN2.

Yeast Yih1 protein and its mammalian ortholog IMPACT, abundant in neurons, are inhibitors of Gcn2, a kinase involved in amino acid homeostasis, stress response, and memory formation. Like Gcn2, Yih1/IMPACT harbors an N-terminal RWD domain that mediates binding to the Gcn2 activator Gcn1. Yih1 competes with Gcn2 for Gcn1 binding, thus inhibiting Gcn2. Yih1 also binds G-actin. Here, we show that Yih1-actin interaction is independent of Gcn1 and that Yih1-Gcn1 binding does not require actin. The Yih1 RWD (residues 1-132) was sufficient for Gcn2 inhibition and Gcn1 binding, but not for actin binding, showing that actin binding is dispensable for inhibiting Gcn2. Actin binding required Yih1 residues 68-258, encompassing part of the RWD and the C-terminal "ancient domain"; however, residues Asp-102 and Glu-106 in helix3 of the RWD were essential for Gcn1 binding and Gcn2 inhibition but dispensable for actin binding. Thus, the Gcn1- and actin-binding sites overlap in the RWD but have distinct binding determinants. Unexpectedly, Yih1 segment 68-258 was defective for inhibiting Gcn2 even though it binds Gcn1 at higher levels than does full-length Yih1. This and other results suggest that Yih1 binds with different requirements to distinct populations of Gcn1 molecules, and its ability to disrupt Gcn1-Gcn2 complexes is dependent on a complete RWD and hindered by actin binding. Modeling of the ancient domain on the bacterial protein YigZ showed peculiarities to the eukaryotic and prokaryotic lineages, suggesting binding sites for conserved cellular components. Our results support a role for Yih1 in a cross-talk between the cytoskeleton and translation.

Role of GP82 in the selective binding to gastric mucin during oral infection with Trypanosoma cruzi.

Oral infection by Trypanosoma cruzi has been the primary cause of recent outbreaks of acute Chagas' diseases. This route of infection may involve selective binding of the metacyclic trypomastigote surface molecule gp82 to gastric mucin as a first step towards invasion of the gastric mucosal epithelium and subsequent systemic infection. Here we addressed that question by performing in vitro and in vivo experiments. A recombinant protein containing the complete gp82 sequence (J18), a construct lacking the gp82 central domain (J18*), and 20-mer synthetic peptides based on the gp82 central domain, were used for gastric mucin binding and HeLa cell invasion assays, or for in vivo experiments. Metacyclic trypomastigotes and J18 bound to gastric mucin whereas J18* failed to bind. Parasite or J18 binding to submaxillary mucin was negligible. HeLa cell invasion by metacyclic forms was not affected by gastric mucin but was inhibited in the presence of submaxillary mucin. Of peptides tested for inhibition of J18 binding to gastric mucin, the inhibitory peptide p7 markedly reduced parasite invasion of HeLa cells in the presence of gastric mucin. Peptide p7*, with the same composition as p7 but with a scrambled sequence, had no effect. Mice fed with peptide p7 before oral infection with metacyclic forms developed lower parasitemias than mice fed with peptide p7*. Our results indicate that selective binding of gp82 to gastric mucin may direct T. cruzi metacyclic trypomastigotes to stomach mucosal epithelium in oral infection.