scholarly journals Novel Observations Concerning Differentiation of Bloodstream-Form Trypanosomes to the Form That Is Adapted for Growth in Tsetse Flies

mSphere ◽  
2018 ◽  
Vol 3 (5) ◽  
Author(s):  
Christine Clayton
Keyword(s):  
Cold Shock ◽  
Tricarboxylic Acid ◽  
Bloodstream Form ◽  
Tsetse Flies ◽  
Data Sets ◽  
Glucose Medium ◽  
Transcriptome Data ◽  
Procyclic Form ◽  
Link Type ◽  
Highly Efficient

ABSTRACT Salivarian trypanosomes grow in mammals, where they depend on glucose, and as procyclic forms in tsetse flies, where they metabolize proline. Differentiation of bloodstream forms to nongrowing stumpy forms, and to procyclic forms, has been studied extensively, but reconciling the results is tricky because investigators have used parasites with various differentiation competences and different media for procyclic-form culture. Standard protocols include lowering the temperature to 27°C, adding a tricarboxylic acid, and transferring the parasites to high-proline medium, often including glucose. A 20°C cold shock enhanced efficiency. Y. Qiu, J. E. Milanes, J. A. Jones, R. E. Noorai, et al. (mSphere 3:e00366-18, 2018, https://doi.org/10.1128/mSphere.00366-18) studied this systematically, and their results call long-established protocols into question. Importantly, highly efficient differentiation was observed after cold shock and transfer to no-glucose medium without tricarboxylic acid; in contrast, glucose made differentiation tricarboxylic acid dependent and inhibited procyclic growth. New transcriptome data for stumpy and procyclic forms will enable informative comparisons with biochemical observations and with other RNA and protein data sets.

scholarly journals Glucose Signaling Is Important for Nutrient Adaptation during Differentiation of Pleomorphic African Trypanosomes

mSphere ◽  
2018 ◽  
Vol 3 (5) ◽  
Author(s):  
Yijian Qiu ◽  
Jillian E. Milanes ◽  
Jessica A. Jones ◽  
Rooksana E. Noorai ◽  
Vijay Shankar ◽  
...  
Keyword(s):  
Life Cycle ◽  
Glucose Sensing ◽  
Negative Regulator ◽  
Bloodstream Form ◽  
Tsetse Flies ◽  
Insect Vector ◽  
Rapid Reduction ◽  
African Trypanosomes ◽  
Procyclic Form ◽  
African Trypanosome

ABSTRACT The African trypanosome has evolved mechanisms to adapt to changes in nutrient availability that occur during its life cycle. During transition from mammalian blood to insect vector gut, parasites experience a rapid reduction in environmental glucose. Here we describe how pleomorphic parasites respond to glucose depletion with a focus on parasite changes in energy metabolism and growth. Long slender bloodstream form parasites were rapidly killed as glucose concentrations fell, while short stumpy bloodstream form parasites persisted to differentiate into the insect-stage procyclic form parasite. The rate of differentiation was lower than that triggered by other cues but reached physiological rates when combined with cold shock. Both differentiation and growth of resulting procyclic form parasites were inhibited by glucose and nonmetabolizable glucose analogs, and these parasites were found to have upregulated amino acid metabolic pathway component gene expression. In summary, glucose transitions from the primary metabolite of the blood-stage infection to a negative regulator of cell development and growth in the insect vector, suggesting that the hexose is not only a key metabolic agent but also an important signaling molecule. IMPORTANCE As the African trypanosome Trypanosoma brucei completes its life cycle, it encounters many different environments. Adaptation to these environments includes modulation of metabolic pathways to parallel the availability of nutrients. Here, we describe how the blood-dwelling life cycle stages of the African trypanosome, which consume glucose to meet their nutritional needs, respond differently to culture in the near absence of glucose. The proliferative long slender parasites rapidly die, while the nondividing short stumpy parasite remains viable and undergoes differentiation to the next life cycle stage, the procyclic form parasite. Interestingly, a sugar analog that cannot be used as an energy source inhibited the process. Furthermore, the growth of procyclic form parasite that resulted from the event was inhibited by glucose, a behavior that is similar to that of parasites isolated from tsetse flies. Our findings suggest that glucose sensing serves as an important modulator of nutrient adaptation in the parasite.

scholarly journals Glucose signaling is important for nutrient adaptation during differentiation of pleomorphic African trypanosomes

2018 ◽  
Author(s):  
Yijian Qiu ◽  
Jillian E. Milanes ◽  
Jessica A. Jones ◽  
Rooksana E. Noorai ◽  
Vijay Shankar ◽  
...  
Keyword(s):  
Glucose Sensing ◽  
Negative Regulator ◽  
Bloodstream Form ◽  
Tsetse Flies ◽  
Insect Vector ◽  
Dependent Manner ◽  
Concentration Dependent Manner ◽  
African Trypanosomes ◽  
Procyclic Form ◽  
African Trypanosome

AbstractThe African trypanosome has evolved mechanisms to adapt to changes in nutrient availability that occur during its lifecycle. During transition from mammalian blood to insect vector gut, parasites experience a rapid reduction in environmental glucose. Here we describe how pleomorphic parasites respond to glucose depletion with a focus on parasite changes in energy metabolism and growth. Long slender bloodstream form parasites are rapidly killed as glucose concentrations fall, while the short stumpy bloodstream form parasites persist to differentiate into the insect stage procyclic form parasite. The rate of differentiation was slower than that triggered by other cues but reached physiological rates when combined with cold shock. Both differentiation and growth of resulting procyclic form parasites were inhibited by glucose and its non-metabolizable analogs in a concentration dependent manner. Procyclic form parasites differentiated from short stumpy form parasites in glucose depleted medium significantly upregulated gene expression of amino acid metabolic pathway components when compared to procyclic forms generated by cis-aconitate treatment. Additionally, growth of these parasite was inhibited by the presence of either glucose or 6-deoxyglucose. In summary, glucose transitions from the primary metabolite of the blood stage infection to a negative regulator of cell development and growth in the insect vector, suggesting that the hexose is not only a key metabolic agent but is also an important signaling molecule.Author SummaryAs the African trypanosome, Trypanosoma brucei, completes its lifecycle, it encounters many different environments. Adaptation to these environments includes modulation of metabolic pathways to parallel the availability of nutrients. Here, we describe how the blood-dwelling lifecycle stages of the African trypanosome, which consume glucose to meet their nutritional needs, respond differently to culture in the near absence of glucose. The proliferative long slender parasites rapidly die, while the non-dividing short stumpy remains viable and undergoes differentiation to the next lifecycle stage, the procyclic form parasite. Interestingly a sugar analog that cannot be used as an energy source inhibited the process. Furthermore, the growth of procyclic form parasite that resulted from the event was inhibited by glucose, a behavior that is similar to that of parasites isolated from tsetse flies. Our findings suggest that glucose sensing serves as an important modulator of nutrient adaptation in the parasite.

scholarly journals Effects of sevoflurane anesthesia and abdominal surgery on the systemic metabolome: a prospective observational study

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Yiyong Wei ◽  
Donghang Zhang ◽  
Jin Liu ◽  
Mengchan Ou ◽  
Peng Liang ◽  
...  
Keyword(s):  
Abdominal Surgery ◽  
General Anesthesia ◽  
Tricarboxylic Acid Cycle ◽  
Tricarboxylic Acid ◽  
Metabolic Changes ◽  
Sevoflurane Anesthesia ◽  
Glutamate Metabolism ◽  
Acid Cycle ◽  
Link Type ◽  
The Mean

Abstract Background Metabolic status can be impacted by general anesthesia and surgery. However, the exact effects of general anesthesia and surgery on systemic metabolome remain unclear, which might contribute to postoperative outcomes. Methods Five hundred patients who underwent abdominal surgery were included. General anesthesia was mainly maintained with sevoflurane. The end-tidal sevoflurane concentration (ETsevo) was adjusted to maintain BIS (Bispectral index) value between 40 and 60. The mean ETsevo from 20 min after endotracheal intubation to 2 h after the beginning of surgery was calculated for each patient. The patients were further divided into low ETsevo group (mean − SD) and high ETsevo group (mean + SD) to investigate the possible metabolic changes relevant to the amount of sevoflurane exposure. Results The mean ETsevo of the 500 patients was 1.60% ± 0.34%. Patients with low ETsevo (n = 55) and high ETsevo (n = 59) were selected for metabolomic analysis (1.06% ± 0.13% vs. 2.17% ± 0.16%, P < 0.001). Sevoflurane and abdominal surgery disturbed the tricarboxylic acid cycle as identified by increased citrate and cis-aconitate levels and impacted glycometabolism as identified by increased sucrose and D-glucose levels in these 114 patients. Glutamate metabolism was also impacted by sevoflurane and abdominal surgery in all the patients. In the patients with high ETsevo, levels of L-glutamine, pyroglutamic acid, sphinganine and L-selenocysteine after sevoflurane anesthesia and abdominal surgery were significantly higher than those of the patients with low ETsevo, suggesting that these metabolic changes might be relevant to the amount of sevoflurane exposure. Conclusions Sevoflurane anesthesia and abdominal surgery can impact principal metabolic pathways in clinical patients including tricarboxylic acid cycle, glycometabolism and glutamate metabolism. This study may provide a resource data for future studies about metabolism relevant to general anaesthesia and surgeries. Trial registration www.chictr.org.cn. identifier: ChiCTR1800014327.

scholarly journals Optimizing viral genome subsampling by genetic diversity and temporal distribution (TARDiS) for Phylogenetics

2021 ◽  
Author(s):  
Simone Marini ◽  
Carla Mavian ◽  
Alberto Riva ◽  
Marco Salemi ◽  
Brittany Rife Magalis
Keyword(s):  
Genetic Algorithm ◽  
Genetic Diversity ◽  
Viral Genome ◽  
Temporal Distribution ◽  
Data Sets ◽  
Link Type

AbstractTARDiS for Philogenetics is a novel tool for optimal genetic sub-sampling. It optimizes both genetic diversity and temporal distribution through a genetic algorithm. TARDiS, along with example data sets and a user manual, is available at https://github.com/smarini/tardis-phylogenetics

scholarly journals clusTCR: a Python interface for rapid clustering of large sets of CDR3 sequences

2021 ◽  
Author(s):  
Sebastiaan Valkiers ◽  
Max Van Houcke ◽  
Kris Laukens ◽  
Pieter Meysman
Keyword(s):  
T Cell ◽  
Large Data ◽  
Cell Receptor ◽  
Amino Acid Sequences ◽  
Large Data Sets ◽  
Data Sets ◽  
Clustering Methods ◽  
Link Type ◽  
Large Sets ◽  
Similar Accuracy

The T-cell receptor (TCR) determines the specificity of a T-cell towards an epitope. As of yet, the rules for antigen recognition remain largely undetermined. Current methods for grouping TCRs according to their epitope specificity remain limited in performance and scalability. Multiple methodologies have been developed, but all of them fail to efficiently cluster large data sets exceeding 1 million sequences. To account for this limitation, we developed clusTCR, a rapid TCR clustering alternative that efficiently scales up to millions of CDR3 amino acid sequences. Benchmarking comparisons revealed similar accuracy of clusTCR with other TCR clustering methods. clusTCR offers a drastic improvement in clustering speed, which allows clustering of millions of TCR sequences in just a few minutes through efficient similarity searching and sequence hashing.clusTCR was written in Python 3. It is available as an anaconda package (https://anaconda.org/svalkiers/clustcr) and on github (https://github.com/svalkiers/clusTCR).

scholarly journals Quickomics: exploring omics data in an intuitive, interactive and informative manner

2021 ◽  
Author(s):  
Benbo Gao ◽  
Jing Zhu ◽  
Soumya Negi ◽  
Xinmin Zhang ◽  
Stefka Gyoneva ◽  
...  
Keyword(s):  
Modular Design ◽  
Functional Module ◽  
Supplementary Information ◽  
Data Sets ◽  
Omics Data ◽  
Proteomics Data ◽  
Primary Analysis ◽  
Link Type ◽  
R Shiny ◽  
Advanced Analysis

AbstractSummaryWe developed Quickomics, a feature-rich R Shiny-powered tool to enable biologists to fully explore complex omics data and perform advanced analysis in an easy-to-use interactive interface. It covers a broad range of secondary and tertiary analytical tasks after primary analysis of omics data is completed. Each functional module is equipped with customized configurations and generates both interactive and publication-ready high-resolution plots to uncover biological insights from data. The modular design makes the tool extensible with ease.AvailabilityResearchers can experience the functionalities with their own data or demo RNA-Seq and proteomics data sets by using the app hosted at http://quickomics.bxgenomics.com and following the tutorial, https://bit.ly/3rXIyhL. The source code under GPLv3 license is provided at https://github.com/interactivereport/[email protected], [email protected] informationSupplementary materials are available at https://bit.ly/37HP17g.

scholarly journals Microbiome Search Engine 2: a Platform for Taxonomic and Functional Search of Global Microbiomes on the Whole-Microbiome Level

mSystems ◽  
2021 ◽  
Vol 6 (1) ◽  
Author(s):  
Gongchao Jing ◽  
Lu Liu ◽  
Zengbin Wang ◽  
Yufeng Zhang ◽  
Li Qian ◽  
...  
Keyword(s):  
Big Data ◽  
User Interface ◽  
Search Engine ◽  
Functional Similarity ◽  
Metagenomic Data ◽  
Data Sets ◽  
Data Space ◽  
Link Type ◽  
Database Platform ◽  
Microbiome Data

ABSTRACT Metagenomic data sets from diverse environments have been growing rapidly. To ensure accessibility and reusability, tools that quickly and informatively correlate new microbiomes with existing ones are in demand. Here, we introduce Microbiome Search Engine 2 (MSE 2), a microbiome database platform for searching query microbiomes in the global metagenome data space based on the taxonomic or functional similarity of a whole microbiome to those in the database. MSE 2 consists of (i) a well-organized and regularly updated microbiome database that currently contains over 250,000 metagenomic shotgun and 16S rRNA gene amplicon samples associated with unified metadata collected from 798 studies, (ii) an enhanced search engine that enables real-time and fast (<0.5 s per query) searches against the entire database for best-matched microbiomes using overall taxonomic or functional profiles, and (iii) a Web-based graphical user interface for user-friendly searching, data browsing, and tutoring. MSE 2 is freely accessible via http://mse.ac.cn. For standalone searches of customized microbiome databases, the kernel of the MSE 2 search engine is provided at GitHub (https://github.com/qibebt-bioinfo/meta-storms). IMPORTANCE A search-based strategy is useful for large-scale mining of microbiome data sets, such as a bird’s-eye view of the microbiome data space and disease diagnosis via microbiome big data. Here, we introduce Microbiome Search Engine 2 (MSE 2), a microbiome database platform for searching query microbiomes against the existing microbiome data sets on the basis of their similarity in taxonomic structure or functional profile. Key improvements include database extension, data compatibility, a search engine kernel, and a user interface. The new ability to search the microbiome space via functional similarity greatly expands the scope of search-based mining of the microbiome big data.

Further studies of cyclical transmission and antigenic variation of the ILDar 1 serodeme of Trypanosoma vivax

Parasitology ◽  
1986 ◽  
Vol 92 (3) ◽  
pp. 581-593 ◽  
Author(s):  
P. R. Gardiner ◽  
R. Thatthi ◽  
H. Gathuo ◽  
R. Nelson ◽  
S. K. Moloo
Keyword(s):  
Antigenic Variation ◽  
West African ◽  
Bloodstream Form ◽  
Tsetse Flies ◽  
Trypanosoma Vivax ◽  
Mixed Populations ◽  
Cyclical Transmission

SUMMARYAntigenic variation in the ILDar 1 serodeme of the naturally rodent-infective stock of West African Trypanosoma vivax has been investigated following cyclical transmission. The immunofluorescent and immune lysis tests were employed with a panel of 39 variant-specific mouse antisera. When antigenically homogeneous, or mixed, populations were transmitted by tsetse flies to goats, the first peak parasitaemias arising in the goats were antigenic mixtures (up to 9 major, and several minor variants being recognized in some cases) from which the ingested variant was absent. Although first peak parasitaemias in similarly infected goats showed some variants in common, there was no obvious relationship between the VAT profiles in different goats. When these populations were expanded in irradiated mice, VAT heterogeneity was maintained with a tendency towards the development of predominant variants in some, but not all, instances. Six additional variants, derived following the growth of bloodstream form ILDat 1·9 in 37°C culture, were also represented in goat and mouse populations. Two further variants, isolated after cyclical development of ILDat 1·9-derived trypanosomes in vitro, were not present in the early parasitaemias in goats and mice.

scholarly journals CoMM: A Collaborative Mixed Model That Integrates GWAS and eQTL Data Sets to Investigate the Genetic Architecture of Complex Traits

2019 ◽  
Vol 13 ◽  
pp. 117793221988143 ◽  
Author(s):  
Kar-Fu Yeung ◽  
Yi Yang ◽  
Can Yang ◽  
Jin Liu
Keyword(s):  
Gene Expression ◽  
Association Study ◽  
Genetic Variants ◽  
Complex Traits ◽  
Mixed Model ◽  
Genome Wide Association Study ◽  
Data Sets ◽  
Transcriptome Data ◽  
Data Set ◽  
Expression Levels

Genome-wide association study (GWAS) analyses have identified thousands of associations between genetic variants and complex traits. However, it is still a challenge to uncover the mechanisms underlying the association. With the growing availability of transcriptome data sets, it has become possible to perform statistical analyses targeted at identifying influential genes whose expression levels correlate with the phenotype. Methods such as PrediXcan and transcriptome-wide association study (TWAS) use the transcriptome data set to fit a predictive model for gene expression, with genetic variants as covariates. The gene expression levels for the GWAS data set are then ‘imputed’ using the prediction model, and the imputed expression levels are tested for their association with the phenotype. These methods fail to account for the uncertainty in the GWAS imputation step, and we propose a collaborative mixed model (CoMM) that addresses this limitation by jointly modelling the multiple analysis steps. We illustrate CoMM’s ability to identify relevant genes in the Northern Finland Birth Cohort 1966 data set and extend the model to handle the more widely available GWAS summary statistics.

Sign in / Sign up

Export Citation Format

Share Document