scholarly journals The Identification and Evolutionary Trends of the Solute Carrier Superfamily in Arthropods

2020 ◽  
Vol 12 (8) ◽  
pp. 1429-1439
Author(s):  
Shane M Denecke ◽  
Olympia Driva ◽  
Hang Ngoc Bao Luong ◽  
Panagiotis Ioannidis ◽  
Marc Linka ◽  
...  
Keyword(s):  
Web Application ◽  
Gene Family Evolution ◽  
Rapid Expansion ◽  
Slc Transporters ◽  
Arthropod Species ◽  
A Genome ◽  
R Shiny ◽  
Solute Carrier ◽  
Slc Transporter ◽  
Systematic Identification

Abstract The solute carrier (SLC) transporter superfamily comprises an ancient and ubiquitous group of proteins capable of translocating a range of nutrients, endogenous molecules, and xenobiotics. Although the group has been the subject of intense investigation in both bacteria and mammals, its systematic identification in arthropods has not yet been undertaken. Here, we present a genome-wide identification of all 66 human SLC families in 174 arthropod species. A pipeline (SLC_id) was constructed to identify and group SLCs using a combination of hidden Markov model and BLAST searches followed by filtering based on polypeptide length and the number of transmembrane domains. Comparative analysis of the number of transporters in each family across diverse arthropod lineages was accomplished using one-way analysis of variance (ANOVA) and the Computational Analysis of gene Family Evolution (CAFE). These results suggested that many SLC families have undergone expansions or contractions in particular evolutionary lineages. Notably, the sugar transporting SLC2 family was significantly larger in insects compared with arachnids. This difference may have been complemented by a rapid expansion of the SLC60 family in arachnids which also acts on dietary sugars. Furthermore, the SLC33 family underwent a recent and drastic expansion in aphids, although the biological relevance of this expansion was not possible to infer. Information on specific SLC transporter families across arthropod species can be accessed through an R shiny web application at http://chrysalida.imbb.forth.gr : 3838/Arthropod_SLC_Database/. The present study greatly facilitates further investigation of the diverse group of SLC transporters in arthropods.

Genetic variations in microRNA binding sites of solute carrier transporter genes as predictors of clinical outcome in colorectal cancer

2020 ◽  
Author(s):  
Petra Bendova ◽  
Barbara Pardini ◽  
Simona Susova ◽  
Jachym Rosendorf ◽  
Miloslav Levy ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Messenger Rna ◽  
Drug Transport ◽  
Chemotherapy Resistance ◽  
Regression Tree ◽  
Classification And Regression Tree ◽  
Nucleotide Polymorphisms ◽  
Slc Transporters ◽  
Solute Carrier ◽  
Slc Transporter

Abstract One of the principal mechanisms of chemotherapy resistance in highly frequent solid tumors like colorectal cancer (CRC) is the decreased activity of drug transport into tumor cells due to low expression of important membrane proteins, such as solute carrier (SLC) transporters. Sequence complementarity is a major determinant for target gene recognition by microRNAs (miRNAs). Single nucleotide polymorphisms (SNPs) in target sequences transcribed into messenger RNA may therefore alter miRNA binding to these regions by either creating a new site or destroying an existing one. miRSNPs may explain the modulation of expression levels in association with increased/decreased susceptibility to common diseases as well as in chemoresistance and the consequent interindividual variability in drug response. In the present study, we investigated whether miRSNPs in SLC transporter genes may modulate CRC susceptibility and patient’s survival. Using an in silico approach for functional predictions, we analyzed twenty-six miRSNPs in nine SLC genes in a cohort of 1368 CRC cases and 698 controls from the Czech Republic. After correcting for multiple tests, we found several miRSNPs significantly associated with patient’s survival. SNPs in SLCO3A1, SLC22A2, and SLC22A3 genes were defined as prognostic factors in the classification and regression tree analysis. In contrast, we did not observe any significant association between miRSNPs and CRC risk. To the best of our knowledge, this is the first study investigating miRSNPs potentially affecting miRNA binding to SLC transporter genes and their impact on CRC susceptibility or patient’s prognosis.

scholarly journals Systematic in silico discovery of novel solute carrier-like proteins from proteomes

2021 ◽  
Author(s):  
Gergely Gyimesi ◽  
Matthias A. Hediger
Keyword(s):  
Sequence Similarity ◽  
Structural Heterogeneity ◽  
Protein Families ◽  
Systematic Analysis ◽  
Slc Transporters ◽  
Solute Carrier ◽  
The Many ◽  
Slc Transporter ◽  
Transmembrane Transporters ◽  
Similarity Searches

Solute carrier (SLC) proteins represent the largest superfamily of transmembrane transporters, the systematic analysis of which is hampered by their functional and structural heterogeneity, despite their biological importance. Based on available nomenclature systems, we suspected that many as yet unidentified SLC transporters exist in the human genome. Here, we present criteria for defining "SLC-likeness" and apply them to curate a set of "SLC-like" protein families from the Transporter Classification Database (TCDB) and Protein families (Pfam) databases. Computational sequence similarity searches then surprisingly yielded ~130 more proteins in human with SLC-like properties, compared to previous annotations. Several of these novel putative SLC transporter proteins actually have documented transport activity in the scientific literature. We complete our overview of the SLC-ome by presenting an algorithm to classify SLC-like proteins into protein families, investigating their known functions and evolutionary relationships to similar proteins from 6 other clinically relevant experimental organisms, and pinpointing structural orphans. We envision that our work will serve as a stepping stone for future studies of the biological function and the identification of the natural substrates of the many under-explored SLC transporters, as well as the development of new therapeutic applications, including strategies for personalized medicine and drug delivery.

scholarly journals The genetic landscape of the human solute carrier (SLC) transporter superfamily

2019 ◽  
Vol 138 (11-12) ◽  
pp. 1359-1377 ◽  
Author(s):  
Lena Schaller ◽  
Volker M. Lauschke
Keyword(s):  
Individual Differences ◽  
Small Sample ◽  
Next Generation Sequencing Data ◽  
Human Populations ◽  
Mendelian Disease ◽  
Sequence Information ◽  
Data Set ◽  
Slc Transporters ◽  
Solute Carrier ◽  
Slc Transporter

Abstract The human solute carrier (SLC) superfamily of transporters is comprised of over 400 membrane-bound proteins, and plays essential roles in a multitude of physiological and pharmacological processes. In addition, perturbation of SLC transporter function underlies numerous human diseases, which renders SLC transporters attractive drug targets. Common genetic polymorphisms in SLC genes have been associated with inter-individual differences in drug efficacy and toxicity. However, despite their tremendous clinical relevance, epidemiological data of these variants are mostly derived from heterogeneous cohorts of small sample size and the genetic SLC landscape beyond these common variants has not been comprehensively assessed. In this study, we analyzed Next-Generation Sequencing data from 141,456 individuals from seven major human populations to evaluate genetic variability, its functional consequences, and ethnogeographic patterns across the entire SLC superfamily of transporters. Importantly, of the 204,287 exonic single-nucleotide variants (SNVs) which we identified, 99.8% were present in less than 1% of analyzed alleles. Comprehensive computational analyses using 13 partially orthogonal algorithms that predict the functional impact of genetic variations based on sequence information, evolutionary conservation, structural considerations, and functional genomics data revealed that each individual genome harbors 29.7 variants with putative functional effects, of which rare variants account for 18%. Inter-ethnic variability was found to be extensive, and 83% of deleterious SLC variants were only identified in a single population. Interestingly, population-specific carrier frequencies of loss-of-function variants in SLC genes associated with recessive Mendelian disease recapitulated the ethnogeographic variation of the corresponding disorders, including cystinuria in Jewish individuals, type II citrullinemia in East Asians, and lysinuric protein intolerance in Finns, thus providing a powerful resource for clinical geneticists to inform about population-specific prevalence and allelic composition of Mendelian SLC diseases. In summary, we present the most comprehensive data set of SLC variability published to date, which can provide insights into inter-individual differences in SLC transporter function and guide the optimization of population-specific genotyping strategies in the bourgeoning fields of personalized medicine and precision public health.

scholarly journals Genome-wide identification and characterization of long non-coding RNAs involved in flag leaf senescence of rice

2021 ◽  
Author(s):  
Xiaoping Huang ◽  
Hongyu Zhang ◽  
Qiang Wang ◽  
Rong Guo ◽  
Lingxia Wei ◽  
...  
Keyword(s):  
Transcription Factors ◽  
Leaf Senescence ◽  
Flag Leaf ◽  
Reduction Process ◽  
Sequencing Analysis ◽  
Biological Processes ◽  
Genome Wide ◽  
A Genome ◽  
Non Coding Rnas ◽  
Systematic Identification

Abstract Key message This study showed the systematic identification of long non-coding RNAs (lncRNAs) involving in flag leaf senescence of rice, providing the possible lncRNA-mRNA regulatory relationships and lncRNA-miRNA-mRNA ceRNA networks during leaf senescence. Abstract LncRNAs have been reported to play crucial roles in diverse biological processes. However, no systematic identification of lncRNAs associated with leaf senescence in plants has been studied. In this study, a genome-wide high throughput sequencing analysis was performed using rice flag leaves developing from normal to senescence. A total of 3953 lncRNAs and 38757 mRNAs were identified, of which 343 lncRNAs and 9412 mRNAs were differentially expressed. Through weighted gene co-expression network analysis (WGCNA), 22 continuously down-expressed lncRNAs targeting 812 co-expressed mRNAs and 48 continuously up-expressed lncRNAs targeting 1209 co-expressed mRNAs were considered to be significantly associated with flag leaf senescence. Gene Ontology results suggested that the senescence-associated lncRNAs targeted mRNAs involving in many biological processes, including transcription, hormone response, oxidation–reduction process and substance metabolism. Additionally, 43 senescence-associated lncRNAs were predicted to target 111 co-expressed transcription factors. Interestingly, 8 down-expressed lncRNAs and 29 up-expressed lncRNAs were found to separately target 12 and 20 well-studied senescence-associated genes (SAGs). Furthermore, analysis on the competing endogenous RNA (CeRNA) network revealed that 6 down-expressed lncRNAs possibly regulated 51 co-expressed mRNAs through 15 miRNAs, and 14 up-expressed lncRNAs possibly regulated 117 co-expressed mRNAs through 21 miRNAs. Importantly, by expression validation, a conserved miR164-NAC regulatory pathway was found to be possibly involved in leaf senescence, where lncRNA MSTRG.62092.1 may serve as a ceRNA binding with miR164a and miR164e to regulate three transcription factors. And two key lncRNAs MSTRG.31014.21 and MSTRG.31014.36 also could regulate the abscisic-acid biosynthetic gene BGIOSGA025169 (OsNCED4) and BGIOSGA016313 (NAC family) through osa-miR5809. The possible regulation networks of lncRNAs involving in leaf senescence were discussed, and several candidate lncRNAs were recommended for prior transgenic analysis. These findings will extend the understanding on the regulatory roles of lncRNAs in leaf senescence, and lay a foundation for functional research on candidate lncRNAs.

scholarly journals MALDIViz: A Comprehensive Informatics Tool for MALDI-MS Data Visualization and Analysis

2017 ◽  
Vol 22 (10) ◽  
pp. 1246-1252 ◽  
Author(s):  
Kishore Kumar Jagadeesan ◽  
Simon Ekström
Keyword(s):  
Mass Spectrometry ◽  
High Throughput ◽  
High Throughput Screening ◽  
Web Application ◽  
Low Cost ◽  
Maldi Ms ◽  
Ionization Mass ◽  
Label Free ◽  
Label Free Detection ◽  
R Shiny

Recently, mass spectrometry (MS) has emerged as an important tool for high-throughput screening (HTS) providing a direct and label-free detection method, complementing traditional fluorescent and colorimetric methodologies. Among the various MS techniques used for HTS, matrix-assisted laser desorption/ionization mass spectrometry (MALDI-MS) provides many of the characteristics required for high-throughput analyses, such as low cost, speed, and automation. However, visualization and analysis of the large datasets generated by HTS MALDI-MS can pose significant challenges, especially for multiparametric experiments. The datasets can be generated fast, and the complexity of the experimental data (e.g., screening many different sorbent phases, the sorbent mass, and the load, wash, and elution conditions) makes manual data analysis difficult. To address these challenges, a comprehensive informatics tool called MALDIViz was developed. This tool is an R-Shiny-based web application, accessible independently of the operating system and without the need to install any program locally. It has been designed to facilitate easy analysis and visualization of MALDI-MS datasets, comparison of multiplex experiments, and export of the analysis results to high-quality images.

scholarly journals Molecular Modeling and Ligand Docking for Solute Carrier (SLC) Transporters

2013 ◽  
Vol 13 (7) ◽  
pp. 843-856 ◽  
Author(s):  
Avner Schlessinger ◽  
Natalia Khuri ◽  
Kathleen M. Giacomini ◽  
Andrej Sali
Keyword(s):  
Molecular Modeling ◽  
Ligand Docking ◽  
Slc Transporters ◽  
Solute Carrier

scholarly journals A R-SHINY BASED PHENOLOGY ANALYSIS SYSTEM AND CASE STUDY USING DIGITAL CAMERA DATASET

2018 ◽  
Vol XLII-3 ◽  
pp. 2571-2574
Author(s):  
Y. K. Zhou
Keyword(s):  
Data Processing ◽  
Web Application ◽  
Vegetation Index ◽  
Digital Camera ◽  
Parameter Extraction ◽  
Growth Trajectory ◽  
Phenological Data ◽  
Combination Methods ◽  
Parameters Extraction ◽  
R Shiny

Accurate extracting of the vegetation phenology information play an important role in exploring the effects of climate changes on vegetation. Repeated photos from digital camera is a useful and huge data source in phonological analysis. Data processing and mining on phenological data is still a big challenge. There is no single tool or a universal solution for big data processing and visualization in the field of phenology extraction. In this paper, we proposed a R-shiny based web application for vegetation phenological parameters extraction and analysis. Its main functions include phenological site distribution visualization, ROI (Region of Interest) selection, vegetation index calculation and visualization, data filtering, growth trajectory fitting, phenology parameters extraction, etc. the long-term observation photography data from Freemanwood site in 2013 is processed by this system as an example. The results show that: (1) this system is capable of analyzing large data using a distributed framework; (2) The combination of multiple parameter extraction and growth curve fitting methods could effectively extract the key phenology parameters. Moreover, there are discrepancies between different combination methods in unique study areas. Vegetation with single-growth peak is suitable for using the double logistic module to fit the growth trajectory, while vegetation with multi-growth peaks should better use spline method.

scholarly journals Meta-analysis of transcriptomic data reveals clusters of consistently deregulated gene and disease ontologies in Down syndrome

2021 ◽  
Vol 17 (9) ◽  
pp. e1009317
Author(s):  
Ilario De Toma ◽  
Cesar Sierra ◽  
Mara Dierssen
Keyword(s):  
Down Syndrome ◽  
Differential Expression ◽  
Web Application ◽  
Meta Analysis ◽  
Chromosome 21 ◽  
Complex Disorders ◽  
Transcriptomic Data ◽  
Genome Wide ◽  
A Genome ◽  
The Impact

Trisomy of human chromosome 21 (HSA21) causes Down syndrome (DS). The trisomy does not simply result in the upregulation of HSA21--encoded genes but also leads to a genome-wide transcriptomic deregulation, which affect differently each tissue and cell type as a result of epigenetic mechanisms and protein-protein interactions. We performed a meta-analysis integrating the differential expression (DE) analyses of all publicly available transcriptomic datasets, both in human and mouse, comparing trisomic and euploid transcriptomes from different sources. We integrated all these data in a “DS network”. We found that genome wide deregulation as a consequence of trisomy 21 is not arbitrary, but involves deregulation of specific molecular cascades in which both HSA21 genes and HSA21 interactors are more consistently deregulated compared to other genes. In fact, gene deregulation happens in “clusters”, so that groups from 2 to 13 genes are found consistently deregulated. Most of these events of “co-deregulation” involve genes belonging to the same GO category, and genes associated with the same disease class. The most consistent changes are enriched in interferon related categories and neutrophil activation, reinforcing the concept that DS is an inflammatory disease. Our results also suggest that the impact of the trisomy might diverge in each tissue due to the different gene set deregulation, even though the triplicated genes are the same. Our original method to integrate transcriptomic data confirmed not only the importance of known genes, such as SOD1, but also detected new ones that could be extremely useful for generating or confirming hypotheses and supporting new putative therapeutic candidates. We created “metaDEA” an R package that uses our method to integrate every kind of transcriptomic data and therefore could be used with other complex disorders, such as cancer. We also created a user-friendly web application to query Ensembl gene IDs and retrieve all the information of their differential expression across the datasets.

scholarly journals Standardised mortality ratios as a user-friendly performance metric and trigger for quality improvement in a Flemish hospital network: multicentre retrospective study

BMJ Open ◽  
2019 ◽  
Vol 9 (9) ◽  
pp. e029857
Author(s):  
Wim Tambeur ◽  
Pieter Stijnen ◽  
Guy Vanden Boer ◽  
Pieter Maertens ◽  
Caroline Weltens ◽  
...  
Keyword(s):  
Quality Improvement ◽  
Hospital Mortality ◽  
Web Application ◽  
Hospital Admissions ◽  
Diagnosis Related Groups ◽  
Medical Officer ◽  
Custom Made ◽  
Before And After ◽  
R Shiny ◽  
Concomitant Reduction

ObjectiveTo illustrate the development and use of standardised mortality rates (SMRs) as a trigger for quality improvement in a network of 27 hospitals.DesignThis research was a retrospective observational study. The primary outcome was in-hospital mortality. SMRs were calculated for All Patient Refined—Diagnosis-Related Groups (APR-DRGs) that reflect 80% of the Flemish hospital network mortality. Hospital mortality was modelled using logistic regression. The metrics were communicated to the member hospitals using a custom-made R-Shiny web application showing results at the level of the hospital, patient groups and individual patients. Experiences with the metric and strategies for improvement were shared in chief medical officer meetings organised by the Flemish hospital network.Setting27 Belgian hospitals.Participants1 198 717 hospital admissions for registration years 2009–2016.ResultsPatient gender, age, comorbidity as well as admission source and type were important predictors of mortality. Altogether the SMR models had a C-statistic of 88%, indicating good discriminatory capability. Seven out of ten APR-DRGs with the highest percentage of hospitals statistically significantly deviating from the benchmark involved malignancy. The custom-built web application and the trusted environment of the Flemish hospital network created an interoperable strategy to get to work with SMR findings. Use of the web application increased over time, with peaks before and after key discussion meetings within the Flemish hospital network. A concomitant reduction in crude mortality for the selected APR-DRGs from 6.7% in 2009 to 5.9% in 2016 was observed.ConclusionsThis study reported on the phased approach for introducing SMR reporting to trigger quality improvement. Prerequisites for the successful use of quality metrics in hospital benchmarks are a collaborative approach based on trust among the participants and a reporting platform that allows stakeholders to interpret and analyse the results at multiple levels.

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