The core exosome proteome of Trichomonas vaginalis.

BACKGROUND: Trichomonas vaginalis is parasitic protozoan that causes human urogenital infections. Accumulated reports indicated that exosomes released by this parasite play a crucial role in transmitting information and substances between cells during host-parasite interactions. Current knowledge on the protein contents in T. vaginalis exosome is mainly generated from three previous studies that used different T. vaginalis isolates as an experimental model. Whether T. vaginalis exosomes comprise a common set of proteins (core exosome proteome) is still unclear. METHODS: To explore the core exosome proteome in T. vaginalis, we used liquid chromatography-tandem mass spectrometry (LC-MS/MS) to identify the contents of sucrose ultracentrifugation-enriched exosome and supernatant fractions isolated from six isolates. RESULTS: Transmission electron microscopy (TEM) confirmed the presence of exosomes in the enriched fraction. Proteomic analysis identified a total of 1870 proteins from exosomal extracts. There were 1207 exosomal-specific proteins after excluding 436 'non-core exosomal proteins'. Among these, 72 common exosomal-specific proteins were expressed in all six isolates. Compared with three published T. vaginalis exosome proteome datasets, we identified 16 core exosomal-specific proteins. These core exosomal-specific proteins included tetraspanin (TvTSP1), the classical exosome marker, and proteins mainly involved in catalytic activity and binding such as ribosomal proteins, ras-associated binding (Rab) proteins, and heterotrimeric G proteins. CONCLUSIONS: Our study highlighted the importance of using supernatant fraction from exosomal extract as a control to eliminate 'non-core exosomal proteins'. We compiled a reference core exosome proteome of T. vaginalis, which is essential for developing a fundamental understanding of exosome-mediated cell communication and host-parasite interaction.

ProFun: A web server for functional enrichment analysis of parasitic protozoan genes.

BACKGROUND: The initial step to interpreting putative biological functions from comparative multi-omics studies usually starts from a differential expressed gene list followed by functional enrichment analysis (FEA). However, most FEA packages are designed exclusively for humans and model organisms. Although parasitic protozoan is the most important pathogen in the tropics, no FEA package is available for protozoan functional (ProFun) enrichment analysis. To speed up comparative multi-omics research on parasitic protozoans, we constructed ProFun, a web-based, user-friendly platform for the research community. METHODS: ProFun utilizes the Docker container, ShinyProxy, and R Shiny to construct a scalable web service with load-balancing infrastructure. We have integrated a series of visual analytic functions, in-house scripts, and custom-made annotation packages to create three analytical modules for 40 protozoan species: (1) Gene Overlaps; (2) Over-representation Analysis (ORA); (3) Gene Set Enrichment Analysis (GSEA). RESULTS: We have established ProFun, a web server for functional enrichment analysis of differentially expressed genes. FEA becomes as simple as pasting a list of gene IDs into the textbox of our website. Users can customize enrichment parameters and results with just one click. The intuitive web interface and publication-ready charts enable users to reveal meaningful biological events and pinpoint potential targets for further studies. CONCLUSION: ProFun is the first web application that enables gene functional enrichment analysis of parasitic protozoans. In addition to supporting FEA analysis, ProFun also allows the comparison of FEA results across complicated experimental designs. ProFun is freely available at http://dalek.cgu.edu.tw:8080/app/profun.

HeapMS: An Automatic Peak-Picking Pipeline for Targeted Proteomic Data Powered by 2D Heatmap Transformation and Convolutional Neural Networks.

The process of peak picking and quality assessment for multiple reaction monitoring (MRM) data demands significant human effort, especially for signals with low abundance and high interference. Although multiple peak-picking software packages are available, they often fail to detect peaks with low quality and do not report cases with low confidence. Furthermore, visual examination of all chromatograms is still necessary to identify uncertain or erroneous cases. This study introduces HeapMS, a web service that uses artificial intelligence to assist with peak picking and the quality assessment of MRM chromatograms. HeapMS applies a rule-based filter to remove chromatograms with low interference and high-confidence peak boundaries detected by Skyline. Additionally, it transforms two histograms (representing light and heavy peptides) into a single encoded heatmap and performs a two-step evaluation (quality detection and peak picking) using image convolutional neural networks. HeapMS offers three categories of peak picking: uncertain peak picking that requires manual inspection, deletion peak picking that requires removal or manual re-examination, and automatic peak picking. HeapMS acquires the chromatogram and peak-picking boundaries directly from Skyline output. The output results are imported back into Skyline for further manual inspection, facilitating integration with Skyline. HeapMS offers the benefit of detecting chromatograms that should be deleted or require human inspection. Based on defined categories, it can significantly reduce human workload and provide consistent results. Furthermore, by using heatmaps instead of histograms, HeapMS can adapt to future updates in image recognition models. The HeapMS is available at: https://github.com/ccllabe/HeapMS.

Metabolomics analysis reveals changes related to pseudocyst formation induced by iron depletion in Trichomonas vaginalis.

BACKGROUND: Iron is an essential element for cellular functions, such as energy metabolism. Trichomonas vaginalis, a human urogenital tract pathogen, is capable of surviving in the environment without sufficient iron supplementation. Pseudocysts (cyst-like structures) are an environmentally tolerated stage of this parasite while encountering undesired conditions, including iron deficiency. We previously demonstrated that iron deficiency induces more active glycolysis but a drastic downregulation of hydrogenosomal energy metabolic enzymes. Therefore, the metabolic direction of the end product of glycolysis is still controversial. METHODS: In the present work, we conducted an LC‒MS-based metabolomics analysis to obtain accurate insights into the enzymatic events of T. vaginalis under iron-depleted (ID) conditions. RESULTS: First, we showed the possible digestion of glycogen, cellulose polymerization, and accumulation of raffinose family oligosaccharides (RFOs). Second, a medium-chain fatty acid (MCFA), capric acid, was elevated, whereas most detected C18 fatty acids were reduced significantly. Third, amino acids were mostly reduced, especially alanine, glutamate, and serine. Thirty-three dipeptides showed significant accumulation in ID cells, which was probably associated with the decrease in amino acids. Our results indicated that glycogen was metabolized as the carbon source, and the structural component cellulose was synthesized at same time. The decrease in C18 fatty acids implied possible incorporation in the membranous compartment for pseudocyst formation. The decrease in amino acids accompanied by an increase in dipeptides implied incomplete proteolysis. These enzymatic reactions (alanine dehydrogenase, glutamate dehydrogenase, and threonine dehydratase) were likely involved in ammonia release. CONCLUSION: These findings highlighted the possible glycogen utilization, cellulose biosynthesis, and fatty acid incorporation in pseudocyst formation as well as NO precursor ammonia production induced by iron-depleted stress.

Double-Stranded RNA Viruses Are Released From Trichomonas vaginalis Inside Small Extracellular Vesicles and Modulate the Exosomal Cargo.

Trichomonas vaginalis is a parasitic protist that infects the human urogenital tract. During the infection, trichomonads adhere to the host mucosa, acquire nutrients from the vaginal/prostate environment, and release small extracellular vesicles (sEVs) that contribute to the trichomonad adherence and modulate the host-parasite communication. Approximately 40-70% of T. vaginalis strains harbor a double-stranded RNA virus called Trichomonasvirus (TVV). Naked TVV particles have the potential to stimulate a proinflammatory response in human cells, however, the mode of TVV release from trichomonads to the environment is not clear. In this report, we showed for the first time that TVV particles are released from T. vaginalis cells within sEVs. The sEVs loaded with TVV stimulated a higher proinflammatory response of human HaCaT cells in comparison to sEVs from TVV negative parasites. Moreover, a comparison of T. vaginalis isogenic TVV plus and TVV minus clones revealed a significant impact of TVV infection on the sEV proteome and RNA cargo. Small EVs from TVV positive trichomonads contained 12 enriched and 8 unique proteins including membrane-associated BspA adhesine, and about a 2.5-fold increase in the content of small regulatory tsRNA. As T. vaginalis isolates are frequently infected with TVV, the release of TVV via sEVs to the environment represents an important factor with the potential to enhance inflammation-related pathogenesis during trichomoniasis.

Identification of Endosymbiotic Virus in Small Extracellular Vesicles Derived from Trichomonas vaginalis.

Accumulated evidence suggests that the endosymbiotic Trichomonasvirus (TVV) may play a role in the pathogenesis and drug susceptibility of Trichomonas vaginalis. Several reports have shown that extracellular vesicles (EVs) released from TVV-positive (TVV+) trichomonads can modulate the immune response in human vaginal epithelial cells and animal models. These results prompted us to examine whether EVs released from TVV+ isolates contained TVV. We isolated small extracellular vesicles (sEVs) from six T. vaginalis isolates that were either TVV free (ATCC 50143), harbored a single (ATCC 30236, ATCC 30238, T1), two (ATCC PRA-98), or three TVV subspecies (ATCC 50148). The presence of TVV subspecies in the six isolates was observed using reverse transcription-polymerase chain reaction (RT-PCR). Transmission electron microscopy (TEM) confirmed the presence of cup-shaped sEVs with a size range from 30-150 nm. Trichomonas vaginalis tetraspanin (TvTSP1; TVAG_019180), the classical exosome marker, was identified in all the sEV preparations. Liquid chromatography-tandem mass spectrometry (LC-MS/MS) analysis showed that all the sEVs isolated from TVV+ isolates contain viral capsid proteins derived from the same TVV subspecies in that isolate as demonstrated by RT-PCR. To provide more comprehensive information on the TVV subspecies population in other T. vaginalis isolates, we investigated the distribution of TVV subspecies in twenty-four isolates by mining the New-Generation Sequencing (NGS) RNAseq datasets. Our results should be beneficial for future studies investigating the role of TVV on the pathogenicity of T. vaginalis and the possible transmission of virus subspecies among different isolates via sEVs.

Helminth egg analysis platform (HEAP): An opened platform for microscopic helminth egg identification and quantification based on the integration of deep learning architectures.

BACKGROUND: Millions of people throughout the world suffer from parasite infections. Traditionally, technicians use manual eye inspection of microscopic specimens to perform a parasite examination. However, manual operations have limitations that hinder the ability to obtain precise egg counts and cause inefficient identification of infected parasites on co-infections. The technician requirements for handling a large number of microscopic examinations in countries that have limited medical resources are substantial. We developed the helminth egg analysis platform (HEAP) as a user-friendly microscopic helminth eggs identification and quantification platform to assist medical technicians during parasite infection examination. METHODS: Multiple deep learning strategies including SSD (Single Shot MultiBox Detector), U-net, and Faster R-CNN (Faster Region-based Convolutional Neural Network) are integrated to identify the same specimen allowing users to choose the best predictions. An image binning and egg-in-edge algorithm based on pixel density detection was developed to increase the performance. Computers with different operation systems can be gathered to lower the computation time using our easy-to-deploy software architecture. RESULTS: A user-friendly interface is provided to substantially increase the efficiency of manual validation. To adapt to low-cost computers, we architected a distributed computing structure with high flexibilities. CONCLUSIONS: HEAP serves not only as a prediction service provider but also as a parasitic egg database of microscopic helminth egg image collection, labeling data and pretrained models. All images and labeling resources are free and accessible at http://heap.cgu.edu.tw. HEAP can also be an ideal education and training resource for helminth egg examination.

Dissecting the Transcriptomes of Multiple Metronidazole-Resistant and Sensitive Trichomonas vaginalis Strains Identified Distinct Genes and Pathways Associated with Drug Resistance and Cell Death.

Trichomonas vaginalis is the causative agent of trichomoniasis, the most prevalent non-viral sexually transmitted infection worldwide. Metronidazole (MTZ) is the mainstay of anti-trichomonal chemotherapy; however, drug resistance has become an increasingly worrying issue. Additionally, the molecular events of MTZ-induced cell death in T. vaginalis remain elusive. To gain insight into the differential expression of genes related to MTZ resistance and cell death, we conducted RNA-sequencing of three paired MTZ-resistant (MTZ-R) and MTZ-sensitive (MTZ-S) T. vaginalis strains treated with or without MTZ. Comparative transcriptomes analysis identified that several putative drug-resistant genes were exclusively upregulated in different MTZ-R strains, such as ATP-binding cassette (ABC) transporters and multidrug resistance pumps. Additionally, several shared upregulated genes among all the MTZ-R transcriptomes were not previously identified in T. vaginalis, such as 5'-nucleotidase surE and Na+-driven multidrug efflux pump, which are a potential stress response protein and a multidrug and toxic compound extrusion (MATE)-like protein, respectively. Functional enrichment analysis revealed that purine and pyrimidine metabolisms were suppressed in MTZ-S parasites upon drug treatment, whereas the endoplasmic reticulum-associated degradation (ERAD) pathway, proteasome, and ubiquitin-mediated proteolysis were strikingly activated, highlighting the novel pathways responsible for drug-induced stress. Our work presents the most detailed analysis of the transcriptional changes and the regulatory networks associated with MTZ resistance and MTZ-induced signaling, providing insights into MTZ resistance and cell death mechanisms in trichomonads.

Vaginal Microbiota of the Sexually Transmitted Infections Caused by Chlamydia trachomatis and Trichomonas vaginalis in Women with Vaginitis in Taiwan.

The three most common sexually transmitted infections (STIs) are Chlamydia trachomatis (CT), Neisseria gonorrhoeae (GC) and Trichomonas vaginalis (TV). The prevalence of these STIs in Taiwan remains largely unknown and the risk of STI acquisition affected by the vaginal microbiota is also elusive. In this study, a total of 327 vaginal swabs collected from women with vaginitis were analyzed to determine the presence of STIs and the associated microorganisms by using the BD Max CT/GC/TV molecular assay, microbial cultures, and 16S rRNA sequencing. The prevalence of CT, TV, and GC was 10.8%, 2.2% and 0.6%, respectively. A culture-dependent method identified that Escherichia coli and Streptococcus agalactiae (GBS) were more likely to be associated with CT and TV infections. In CT-positive patients, the vaginal microbiota was dominated by L. iners, and the relative abundance of Gardnerella vaginalis (12.46%) was also higher than that in TV-positive patients and the non-STIs group. However, Lactobacillus spp. was significantly lower in TV-positive patients, while GBS (10.11%), Prevotella bivia (6.19%), Sneathia sanguinegens (12.75%), and Gemella asaccharolytica (5.31%) were significantly enriched. Using an in vitro co-culture assay, we demonstrated that the growth of L. iners was suppressed in the initial interaction with TV, but it may adapt and survive after longer exposure to TV. Additionally, it is noteworthy that TV was able to promote GBS growth. Our study highlights the vaginal microbiota composition associated with the common STIs and the crosstalk between TV and the associated bacteria, paving the way for future development of health interventions targeting the specific vaginal bacterial taxa to reduce the risk of common STIs.

Quantifying Dynamic Flow of Emergency Department (ED) Patient Managements: A Multistate Model Approach.

BACKGROUND: Emergency department (ED) crowding and prolonged lengths of stay continue to be important medical issues. It is difficult to apply traditional methods to analyze multiple streams of the ED patient management process simultaneously. The aim of this study was to develop a statistical model to delineate the dynamic patient flow within the ED and to analyze the effects of relevant factors on different patient movement rates. METHODS: This study used a retrospective cohort available with electronic medical data. Important time points and relevant covariates of all patients between January and December 2013 were collected. A new five-state Markov model was constructed by an expert panel, including three intermediate states: triage, physician management, and observation room and two final states: admission and discharge. A day was further divided into four six-hour periods to evaluate dynamics of patient movement over time. RESULTS: A total of 149,468 patient records were analyzed with a median total length of stay being 2.12 (interquartile range = 6.51) hours. The patient movement rates between states were estimated, and the effects of the age group and triage level on these movements were also measured. Patients with lower acuity go home more quickly (relative rate (RR): 1.891, 95% CI: 1.881-1.900) but have to wait longer for physicians (RR: 0.962, 95% CI: 0.956-0.967) and admission beds (RR: 0.673, 95% CI: 0.666-0.679). While older patients were seen more quickly by physicians (RR: 1.134, 95% CI: 1.131-1.139), they spent more time waiting for the final state (for admission RR: 0.830, 95% CI: 0.821-0.839; for discharge RR: 0.773, 95% CI: 0.769-0.776). Comparing the differences in patient movement rates over a 24-hour day revealed that patients wait longer before seen by physicians during the evening and that they usually move from the ED to admission afternoon. Predictive dynamic illustrations show that six hours after the patients' entry, the probability of still in the ED system ranges from 28% in the evening to 38% in the morning. CONCLUSIONS: The five-state model well described the dynamic ED patient flow and analyzed the effects of relevant influential factors at different states. The model can be used in similar medical settings or incorporate different important covariates to develop individually tailored approaches for the improvement of efficiency within the health professions.

DeepVariant-on-Spark: Small-Scale Genome Analysis Using a Cloud-Based Computing Framework.

Although sequencing a human genome has become affordable, identifying genetic variants from whole-genome sequence data is still a hurdle for researchers without adequate computing equipment or bioinformatics support. GATK is a gold standard method for the identification of genetic variants and has been widely used in genome projects and population genetic studies for many years. This was until the Google Brain team developed a new method, DeepVariant, which utilizes deep neural networks to construct an image classification model to identify genetic variants. However, the superior accuracy of DeepVariant comes at the cost of computational intensity, largely constraining its applications. Accordingly, we present DeepVariant-on-Spark to optimize resource allocation, enable multi-GPU support, and accelerate the processing of the DeepVariant pipeline. To make DeepVariant-on-Spark more accessible to everyone, we have deployed the DeepVariant-on-Spark to the Google Cloud Platform (GCP). Users can deploy DeepVariant-on-Spark on the GCP following our instruction within 20 minutes and start to analyze at least ten whole-genome sequencing datasets using free credits provided by the GCP. DeepVaraint-on-Spark is freely available for small-scale genome analysis using a cloud-based computing framework, which is suitable for pilot testing or preliminary study, while reserving the flexibility and scalability for large-scale sequencing projects.

Protein cysteine S-nitrosylation provides reducing power by enhancing lactate dehydrogenase activity in Trichomonas vaginalis under iron deficiency.

BACKGROUND: Iron plays essential roles in the pathogenesis and proliferation of Trichomonas vaginalis, the causative agent of the most prevalent non-viral human sexually transmitted infection. We previously demonstrated that under iron deficiency, the endogenous nitric oxide (NO) is accumulated and capable of regulating the survival of T. vaginalis. Herein, we aim to explore the influence of NO on the activity of the pyruvate-reducing enzyme lactate dehydrogenase in T. vaginalis (TvLDH). METHODS: Levels of lactate and pyruvate were detected for determining glycolysis activity in T. vaginalis under iron deficiency. Quantitative PCR was performed to determine the expression of TvLDH. S-nitrosylated (SNO) proteomics was conducted to identify the NO-modified proteins. The activities of glyceraldehyde-3-phosphate dehydrogenase (TvGAPDH) and TvLDH were measured after sodium nitrate treatment. The effects of protein nitrosylation on the production of cellular reducing power were examined by measuring the amount of nicotinamide adenine dinucleotide (NAD) and the ratio of the NAD redox pair (NAD+/NADH). RESULTS: We found that although the glycolytic pathway was activated in cells under iron depletion, the level of pyruvate was decreased due to the increased level of TvLDH. By analyzing the SNO proteome of T. vaginalis upon iron deficiency, we found that TvLDH is one of the glycolytic enzymes modified by SNO. The production of pyruvate was significantly reduced after nitrate treatment, indicating that protein nitrosylation accelerated the consumption of pyruvate by increasing TvLDH activity. Nitrate treatment also induced NAD oxidation, suggesting that protein nitrosylation was the key posttranslational modification controlling cellular redox status. CONCLUSIONS: We demonstrated that NO-mediated protein nitrosylation plays pivotal roles in the regulation of glycolysis, pyruvate metabolism, and the activity of TvLDH. The recycling of oxidized NAD catalyzed by TvLDH provided the reducing power that allowed T. vaginalis to adapt to the iron-deficient environment.

Proteomic signatures of metronidazole-resistant Trichomonas vaginalis reveal novel proteins associated with drug resistance.

BACKGROUND: Trichomoniasis is the most common non-viral sexually transmitted disease caused by the protozoan parasite Trichomonas vaginalis. Metronidazole (MTZ) is a widely used drug for the treatment of trichomoniasis; however, increased resistance of the parasite to MTZ has emerged as a highly problematic public health issue. METHODS: We conducted iTRAQ-based analysis to profile the proteomes of MTZ-sensitive (MTZ-S) and MTZ-resistant (MTZ-R) parasites. STRING and gene set enrichment analysis (GESA) were utilized to explore the protein-protein interaction networks and enriched pathways of the differentially expressed proteins, respectively. Proteins potentially related to MTZ resistance were selected for functional validation. RESULTS: A total of 3123 proteins were identified from the MTZ-S and MTZ-R proteomes in response to drug treatment. Among the identified proteins, 304 proteins were differentially expressed in the MTZ-R proteome, including 228 upregulated and 76 downregulated proteins. GSEA showed that the amino acid-related metabolism, including arginine, proline, alanine, aspartate, and glutamate are the most upregulated pathways in the MTZ-R proteome, whereas oxidative phosphorylation is the most downregulated pathway. Ten proteins categorized into the gene set of oxidative phosphorylation were ATP synthase subunit-related proteins. Drug resistance was further examined in MTZ-S parasites pretreated with the ATP synthase inhibitors oligomycin and bafilomycin A1, showing enhanced MTZ resistance and potential roles of ATP synthase in drug susceptibility. CONCLUSIONS: We provide novel insights into previously unidentified proteins associated with MTZ resistance, paving the way for future development of new drugs against MTZ-refractory trichomoniasis.

Pathogenic Protist Transmembranome database (PPTdb): a web-based platform for searching and analysis of protist transmembrane proteins.

BACKGROUND: Pathogenic protist membrane transporter proteins play important roles not only in exchanging molecules into and out of cells but also in acquiring nutrients and biosynthetic compounds from their hosts. Currently, there is no centralized protist membrane transporter database published, which makes system-wide comparisons and studies of host-pathogen membranomes difficult to achieve. RESULTS: We analyzed over one million protein sequences from 139 protists with full or partial genome sequences. Putative transmembrane proteins were annotated by primary sequence alignments, conserved secondary structural elements, and functional domains. We have constructed the PPTdb (Pathogenic Protist Transmembranome database), a comprehensive membrane transporter protein portal for pathogenic protists and their human hosts. The PPTdb is a web-based database with a user-friendly searching and data querying interface, including hierarchical transporter classification (TC) numbers, protein sequences, functional annotations, conserved functional domains, batch sequence retrieving and downloads. The PPTdb also serves as an analytical platform to provide useful comparison/mining tools, including transmembrane ability evaluation, annotation of unknown proteins, informative visualization charts, and iterative functional mining of host-pathogen transporter proteins. CONCLUSIONS: The PPTdb collected putative protist transporter proteins and offers a user-friendly data retrieving interface. Moreover, a pairwise functional comparison ability can provide useful information for identifying functional uniqueness of each protist. Finally, the host and non-host protein similarity search can fulfill the needs of comprehensive studies of protists and their hosts. The PPTdb is freely accessible at http://pptdb.cgu.edu.tw .

CoMutPlotter: a web tool for visual summary of mutations in cancer cohorts.

BACKGROUND: CoMut plot is widely used in cancer research publications as a visual summary of mutational landscapes in cancer cohorts. This summary plot can inspect gene mutation rate and sample mutation burden with their relevant clinical details, which is a common first step for analyzing the recurrence and co-occurrence of gene mutations across samples. The cBioPortal and iCoMut are two web-based tools that allow users to create intricate visualizations from pre-loaded TCGA and ICGC data. For custom data analysis, only limited command-line packages are available now, making the production of CoMut plots difficult to achieve, especially for researchers without advanced bioinformatics skills. To address the needs for custom data and TCGA/ICGC data comparison, we have created CoMutPlotter, a web-based tool for the production of publication-quality graphs in an easy-of-use and automatic manner. RESULTS: We introduce a web-based tool named CoMutPlotter to lower the barriers between complex cancer genomic data and researchers, providing intuitive access to mutational profiles from TCGA/ICGC projects as well as custom cohort studies. A wide variety of file formats are supported by CoMutPlotter to translate cancer mutation profiles into biological insights and clinical applications, which include Mutation Annotation Format (MAF), Tab-separated values (TSV) and Variant Call Format (VCF) files. CONCLUSIONS: In summary, CoMutPlotter is the first tool of its kind that supports VCF file, the most widely used file format, as its input material. CoMutPlotter also provides the most-wanted function for comparing mutation patterns between custom cohort and TCGA/ICGC project. Contributions of COSMIC mutational signatures in individual samples are also included in the summary plot, which is a unique feature of our tool. CoMutPlotter is freely available at http://tardis.cgu.edu.tw/comutplotter .

Metabolic reprogramming of hydrogenosomal amino acids in Trichomonas vaginalis under glucose restriction.

BACKGROUND: Glucose is the major energy source that is converted to pyruvate for ATP generation in the trichomonad hydrogenosome. Under glucose restriction (GR), the regulation of amino acids metabolism is crucial for trichomonad growth and survival. RNA-sequencing (RNA-seq) analysis has been used to identify differentially expressed genes in Trichomonas vaginalis under GR, leading to significant advances in understanding adaptive responses of amino acid metabolism to GR. However, the levels of amino acid metabolites modulated by GR are unknown in T. vaginalis. METHODS: Herein, we describe a comprehensive metabolomic analysis of amino acid metabolites in the hydrogenosome using liquid chromatography Fourier transform ion cyclotron resonance mass spectrometry (LC-FT MS). The relative abundance of 17 hydrogenosomal amino acids was analyzed under GR and high-glucose (HG) conditions. RESULTS: Levels of most amino acids were higher in GR culture. Arginine was not detectable in either HG or GR cultures; however, its metabolic end-product proline was slightly increased under GR, suggesting that the arginine dihydrolase pathway was more activated by GR. Additionally, methionine catabolism was less stimulated under GR because of greater methionine accumulation. Furthermore, branched chain amino acids (BCAA), including leucine, isoleucine and valine, as well as phenylalanine and alanine, markedly accumulated under GR, indicating that glutamate-related metabolic pathways were remarkably enhanced in this setting. Our metabolomic analysis combined with previous RNA-seq data confirm the existence of several amino acid metabolic pathways in the hydrogenosome and highlight their potentially important roles in T. vaginalis under glucose deprivation.

Potential role of autophagy in proteolysis in Trichomonas vaginalis.

BACKGROUND: Autophagy has been shown to be involved in the pathogenesis of several protists, offering prospects for the developments of new drugs targeting autophagy. However, there is no evidence illustrating functional autophagy in the deep-branching trichomonads. The human parasitic protist Trichomonas vaginalis has been predicted to possess reduced autophagic machinery, with only autophagy-related protein 8 (Atg8) conjugation system required for autophagosome formation. METHODS: The recombinant protein of TvAtg8 (rTvAtg8) and the polyclonal antibody against rTvAtg8 were generated. The expression and localization of TvAtg8 was monitored upon autophagy induction by glucose restriction (GR) compared with glucose-rich cultivation. The role of TvAtg8 in proteolysis was clarified. RESULTS: Here, we report that T. vaginalis Atg8 (TvAtg8) is upregulated and conjugated to autophagosome-like vesicles upon autophagy induction by GR. Moreover, we investigate, for the first time, the role of autophagy in T. vaginalis. Proteasome inhibition (PI)-induced autophagy compensates for the removal of polyubiquitinated proteins under glucose-rich condition. GR-induced autophagy is a major proteolytic system in T. vaginalis. These results suggest that autophagy is vital for proteolysis in T. vaginalis with an impaired ubiquitin-proteasome system or under glucose-limited environment. CONCLUSION: Our findings unveiled previously unidentified functions of autophagy in proteostasis in trichomonads, advancing our understanding of this highly conserved process in the ancient eukaryote.

Large-Scale Proteomic Identification of Targets of Cellular miR-197 Downregulated by Enterovirus A71.

MicroRNAs are noncoding RNA species comprising 18-23 nucleotides that regulate host-virus interaction networks. Here, we show that enterovirus A71 infection in human rhabdomyosarcoma (RD) is regulated by miR-197 expression. Transfection of miR-197 mimic into RD cells inhibited virus replication by interfering with the viral RNA synthesis. We employed a combination of mass-spectrometry-based quantitative proteomics with the stable isotope labeling with amino acids in cell culture (SILAC) approach for the identification of the miR-197 target genes in RD cells and to investigate the differential expression of the prospective target proteins. A total of 1822 proteins were repeatedly identified in miR-197-transfected RD cells, 106 of which were predicted to have seed sites by TargetScan. Notably, seven of eight selected genes potentially related to viral replication and immune response were validated as direct miR-197 targets, using a luciferase 3'-untranslated region (UTR) reporter assay. The expression levels of three selected endogenous molecules (ITGAV, ETF1, and MAP2K1/MEK1) were significantly reduced when RD cells were transfected with a miR-197 mimic. Our results provide a comprehensive database of miR-197 targets, which might provide better insights into the understanding of host-virus interaction.

A Transcriptome Study of Progeroid Neurocutaneous Syndrome Reveals POSTN As a New Element in Proline Metabolic Disorder.

Aging is a complex biological process. A study of pyrroline-5-carboxylate reductase 1 (PYCR1) deficiency, which causes a progeroid syndrome, may not only shed light on its genetic contribution to autosomal recessive cutis laxa (ARCL) but also help elucidate the functional mechanisms associated with aging. In this study, we used RNA-Seq technology to examine gene expression changes in primary skin fibroblasts from healthy controls and patients with PYCR1 mutations. Approximately 22 and 32 candidate genes were found to be up- and downregulated, respectively, in fibroblasts from patients. Among the downregulated candidates in fibroblasts with PYCR1 mutations, a strong reduction in the expression of 17 genes (53.1%) which protein products are localized in the extracellular space was detected. These proteins included several important ECM components, periostin (POSTN), elastin (ELN), and decorin (DCN); genetic mutations in these proteins are associated with different phenotypes of aging, such as cutis laxa and joint and dermal manifestations. The differential expression of ten selected extracellular space genes was further validated using quantitative RT-PCR. Ingenuity Pathway Analysis revealed that some of the affected genes may be associated with cardiovascular system development and function, dermatological diseases and conditions, and cardiovascular disease. POSTN, one of the most downregulated gene candidates in affected individuals, is a matricellular protein with pivotal functions in heart valvulogenesis, skin wound healing, and brain development. Perturbation of PYCR1 expression revealed that it is positively correlated with the POSTN levels. Taken together, POSTN might be one of the key molecules that deserves further investigation for its role in this progeroid neurocutaneous syndrome.