scholarly journals XTalkiiS: a tool for finding data-driven cross-talks between intra-/inter-species pathways

2018 ◽  
Author(s):  
A. K. M. Azad
Keyword(s):  
Cell Communication ◽  
Network Models ◽  
Computational Prediction ◽  
Single Species ◽  
Data Driven ◽  
Web Crawler ◽  
Pathway Network ◽  
Kegg Pathways ◽  
Link Type ◽  
Multiple Species

AbstractCell-cell communication via pathway cross-talks within a single species have been studied in silico recently to decipher various disease phenotype. However, computational prediction of pathway cross-talks among multiple species in a data-driven manner is yet to be explored. In this article, I present XTalkiiS (Cross-talks between inter-/intra species pathways), a tool to automatically predict pathway cross-talks from data-driven models of pathway network, both within the same organism (intra-species) and between two organisms (inter-species). XTalkiiS starts with retrieving and listing up-to-date pathway information in all the species available in KEGG database using RESTful APIs (exploiting KEGG web services) and an in-house built web crawler. I hypothesize that data-driven network models can be built by simultaneously quantifying co-expression of pathway components (i.e. genes/proteins) in matched samples in multiple organisms. Next, XTalkiiS loads a data-driven pathway network and applies a novel cross-talk modelling approach to determine interactions among known KEGG pathways in selected organisms. The potentials of XTalkiiS are huge as it paves the way of finding novel insights into mechanisms how pathways from two species (ideally host-parasite) may interact that may contribute to the various phenotype of interests such as malaria disease. XTalkiiS is made open sourced at https://github.com/Akmazad/XTalkiiS and its binary files are freely available for downloading from https://sourceforge.net/projects/xtalkiis/.

Computational Analysis of miRNA and their Gene Targets Significantly Involved in Colorectal Cancer Progression

MicroRNA ◽  
2018 ◽  
Vol 8 (1) ◽  
pp. 68-75 ◽  
Author(s):  
Jeyalakshmi Kandhavelu ◽  
Kumar Subramanian ◽  
Amber Khan ◽  
Aadilah Omar ◽  
Paul Ruff ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Colon Cancer ◽  
Cancer Progression ◽  
Target Prediction ◽  
Computational Prediction ◽  
Initial Step ◽  
Kegg Pathways ◽  
Candidate Mirnas ◽  
Common Cancer ◽  
Colon Cancer Progression

Background:Globally, colorectal cancer (CRC) is the third most common cancer in women and the fourth most common cancer in men. Dysregulation of small non-coding miRNAs have been correlated with colon cancer progression. Since there are increasing reports of candidate miRNAs as potential biomarkers for CRC, this makes it important to explore common miRNA biomarkers for colon cancer. As computational prediction of miRNA targets is a critical initial step in identifying miRNA: mRNA target interactions for validation, we aim here to construct a potential miRNA network and its gene targets for colon cancer from previously reported candidate miRNAs, inclusive of 10 up- and 9 down-regulated miRNAs from tissues; and 10 circulatory miRNAs. </P><P> Methods: The gene targets were predicted using DIANA-microT-CDS and TarBaseV7.0 databases. Each miRNA and its targets were analyzed further for colon cancer hotspot genes, whereupon DAVID analysis and mirPath were used for KEGG pathway analysis.Results:We have predicted 874 and 157 gene targets for tissue and serum specific miRNA candidates, respectively. The enrichment of miRNA revealed that particularly hsa-miR-424-5p, hsa-miR-96-5p, hsa-miR-1290, hsa-miR-224, hsa-miR-133a and has-miR-363-3p present possible targets for colon cancer hallmark genes, including BRAF, KRAS, EGFR, APC, amongst others. DAVID analysis of miRNA and associated gene targets revealed the KEGG pathways most related to cancer and colon cancer. Similar results were observed in mirPath analysis. A new insight gained in the colon cancer network pathway was the association of hsa-mir-133a and hsa-mir-96-5p with the PI3K-AKT signaling pathway. In the present study, target prediction shows that while hsa-mir-424-5p has an association with mostly 10 colon cancer hallmark genes, only their associations with MAP2 and CCND1 have been experimentally validated.These miRNAs and their targets require further evaluation for a better understanding of their associations, ultimately with the potential to develop novel therapeutic targets.

scholarly journals Best practices on the differential expression analysis of multi-species RNA-seq

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Matthew Chung ◽  
Vincent M. Bruno ◽  
David A. Rasko ◽  
Christina A. Cuomo ◽  
José F. Muñoz ◽  
...  
Keyword(s):  
Best Practices ◽  
Differential Expression ◽  
Expression Analysis ◽  
Differential Expression Analysis ◽  
Single Species ◽  
Rna Seq ◽  
Species Analysis ◽  
Differential Gene ◽  
Multiple Species ◽  
Downstream Analysis

AbstractAdvances in transcriptome sequencing allow for simultaneous interrogation of differentially expressed genes from multiple species originating from a single RNA sample, termed dual or multi-species transcriptomics. Compared to single-species differential expression analysis, the design of multi-species differential expression experiments must account for the relative abundances of each organism of interest within the sample, often requiring enrichment methods and yielding differences in total read counts across samples. The analysis of multi-species transcriptomics datasets requires modifications to the alignment, quantification, and downstream analysis steps compared to the single-species analysis pipelines. We describe best practices for multi-species transcriptomics and differential gene expression.

scholarly journals Evaluating Coexistence of Fish Species with Coastal Cutthroat Trout in Low Order Streams of Western Oregon and Washington, USA

Fishes ◽  
2021 ◽  
Vol 6 (1) ◽  
pp. 4
Author(s):  
Kyle D. Martens ◽  
Jason Dunham
Keyword(s):  
Pacific Northwest ◽  
Species Interactions ◽  
Coho Salmon ◽  
Cutthroat Trout ◽  
Single Species ◽  
The Pacific ◽  
Small Streams ◽  
Coastal Cutthroat Trout ◽  
Multiple Species ◽  
Low Order

When multiple species of fish coexist there are a host of potential ways through which they may interact, yet there is often a strong focus on studies of single species without considering these interactions. For example, many studies of forestry–stream interactions in the Pacific Northwest have focused solely on the most prevalent species: Coastal cutthroat trout. To examine the potential for interactions of other fishes with coastal cutthroat trout, we conducted an analysis of 281 sites in low order streams located on Washington’s Olympic Peninsula and along the central Oregon coast. Coastal cutthroat trout and juvenile coho salmon were the most commonly found salmonid species within these streams and exhibited positive associations with each other for both presence and density. Steelhead were negatively associated with the presence of coastal cutthroat trout as well as with coho salmon and sculpins (Cottidae). Coastal cutthroat trout most frequently shared streams with juvenile coho salmon. For densities of these co-occurring species, associations between these two species were relatively weak compared to the strong influences of physical stream conditions (size and gradient), suggesting that physical conditions may have more of an influence on density than species interactions. Collectively, our analysis, along with a review of findings from prior field and laboratory studies, suggests that the net effect of interactions between coastal cutthroat trout and coho salmon do not appear to inhibit their presence or densities in small streams along the Pacific Northwest.

scholarly journals Chemical Space Mapping for Multicomponent Gas Mixtures

2021 ◽  
Author(s):  
Airat Kotliar-Shapirov ◽  
Fedor S. Fedorov ◽  
Henni Ouerdane ◽  
Stanislav Evlashin ◽  
Albert G. Nasibulin ◽  
...  
Keyword(s):  
Cyclic Voltammetry ◽  
Data Processing ◽  
Electrochemical Sensors ◽  
Chemical Space ◽  
Chemical Species ◽  
Single Species ◽  
Data Driven ◽  
Multicomponent Gas ◽  
Data Driven Approach ◽  
Cyclic Voltammetry Data

In our manuscript, we present our protocol for data processing to mitigate the effects of interfering analytes on the identification of the chemical species detected by sensors. Considering NO2 and CO2, we designed electrochemical sensors whose response yielded the cyclic voltammetry data that we analyzed to classify single-species components and their mixtures using a data-driven approach to generate a chemical space where their mixtures can be deconvoluted.<br>

scholarly journals Data-driven reduction of dendritic morphologies with preserved dendro-somatic responses

2020 ◽  
Author(s):  
Willem A.M. Wybo ◽  
Jakob Jordan ◽  
Benjamin Ellenberger ◽  
Ulisses M. Mengual ◽  
Thomas Nevian ◽  
...  
Keyword(s):  
Action Potentials ◽  
Network Models ◽  
Data Driven ◽  
Fast Method ◽  
Average Difference ◽  
Neuron Models ◽  
Shape Information ◽  
Proximal Dendrite ◽  
Conductance Fluctuations ◽  
Software Toolbox

AbstractDendrites shape information flow in neurons. Yet, there is little consensus on the level of spatial complexity at which they operate. We present a flexible and fast method to obtain simplified neuron models at any level of complexity. Through carefully chosen parameter fits, solvable in the least squares sense, we obtain optimal reduced compartmental models. We show that (back-propagating) action potentials, calcium-spikes and NMDA-spikes can all be reproduced with few compartments. We also investigate whether afferent spatial connectivity motifs admit simplification by ablating targeted branches and grouping the affected synapses onto the next proximal dendrite. We find that voltage in the remaining branches is reproduced if temporal conductance fluctuations stay below a limit that depends on the average difference in input impedance between the ablated branches and the next proximal dendrite. Further, our methodology fits reduced models directly from experimental data, without requiring morphological reconstructions. We provide a software toolbox that automatizes the simplification, eliminating a common hurdle towards including dendritic computations in network models.

scholarly journals NetPyNE, a tool for data-driven multiscale modeling of brain circuits

eLife ◽  
2019 ◽  
Vol 8 ◽  
Author(s):  
Salvador Dura-Bernal ◽  
Benjamin A Suter ◽  
Padraig Gleeson ◽  
Matteo Cantarelli ◽  
Adrian Quintana ◽  
...  
Keyword(s):  
Multiple Scales ◽  
Network Models ◽  
Brain Regions ◽  
Data Driven ◽  
Model Parameters ◽  
Biophysical Modeling ◽  
Neuron Network ◽  
Graphical Interfaces ◽  
Information Theoretic Measures ◽  
High Level

Biophysical modeling of neuronal networks helps to integrate and interpret rapidly growing and disparate experimental datasets at multiple scales. The NetPyNE tool (www.netpyne.org) provides both programmatic and graphical interfaces to develop data-driven multiscale network models in NEURON. NetPyNE clearly separates model parameters from implementation code. Users provide specifications at a high level via a standardized declarative language, for example connectivity rules, to create millions of cell-to-cell connections. NetPyNE then enables users to generate the NEURON network, run efficiently parallelized simulations, optimize and explore network parameters through automated batch runs, and use built-in functions for visualization and analysis – connectivity matrices, voltage traces, spike raster plots, local field potentials, and information theoretic measures. NetPyNE also facilitates model sharing by exporting and importing standardized formats (NeuroML and SONATA). NetPyNE is already being used to teach computational neuroscience students and by modelers to investigate brain regions and phenomena.

scholarly journals Spiribacter aquaticus Leon et al. 2017 is a later heterotypic synonym of Spiribacter roseus Leon et al. 2016. Reclassification of Halopeptonella vilamensis Menes et al. 2016 as Spiribacter vilamensis comb. nov.

2020 ◽  
Vol 70 (4) ◽  
pp. 2873-2878 ◽  
Author(s):  
María José León ◽  
Cristina Galisteo ◽  
Antonio Ventosa ◽  
Cristina Sánchez-Porro
Keyword(s):  
Type Species ◽  
Single Species ◽  
Amino Acid Identity ◽  
The Other ◽  
Phylogenomic Analysis ◽  
Content Type ◽  
Link Type ◽  
Average Amino Acid Identity ◽  
Single Genus ◽  
Type Strains

A comparative taxonomic study of Spiribacter and Halopeptonella species was carried out using a phylogenomic approach based on comparison of the core genome, orthologous average nucleotide identity (OrthoANIu), Genome-to-Genome Distance Calculator (GGDC) and average amino acid identity (AAI). Phylogenomic analysis based on 976 core translated gene sequences obtained from their genomes showed that Spiribacter aquaticus SP30T, S. curvatus UAH-SP71T, S. roseus SSL50T, S. salinus M19-40T and Halopeptonella vilamensis DSM 21056T formed a robust cluster, clearly separated from the remaining species of closely related taxa. AAI between H. vilamensis DSM 21056T and the species of the genus Spiribacter was ≥73.1 %, confirming that all these species belong to the same single genus. On the other hand, S. roseus SSL50T and S. aquaticus SP30T showed percentages of OrthoANIu and digital DNA–DNA hybridization of 98.4 % and 85.3 %, respectively, while these values among those strains and the type strains of the other species of Spiribacter and H. vilamensis DSM 21056T were ≤80.8 and 67.8 %, respectively. Overall, these data show that S. roseus SSL50T and S. aquaticus SP30T constitute a single species and thus that S. aquaticus SP30T should be considered as a later, heterotypic synonym of S. roseus SSL50T based on the rules for priority of names. We propose an emended description of S. roseus , including the features of S. aquaticus . We also propose the reclassification of H. vilamensis as Spiribacter vilamensis comb. nov.

Aestuariisphingobium litorale Li et al. 2020 is a later heterotypic synonym of Chakrabartia godavariana Jani et al. 2019

2021 ◽  
Vol 71 (8) ◽  
Author(s):  
Peng Wang ◽  
Yuxin Gao
Keyword(s):  
16S Rrna ◽  
16S Rrna Gene ◽  
Type Species ◽  
Phylogenetic Analyses ◽  
Single Species ◽  
Rrna Gene ◽  
Genomic Comparison ◽  
Content Type ◽  
Link Type ◽  
Type Strains

Chakrabartia godavariana PRB40T was compared with Aestuariisphingobium litorale SYSU M10002T to examine the taxonomic relationship between the two type strains. The 16S rRNA gene sequence of C. godavariana PRB40T had high similarity (99.8 %) to that of A. litorale SYSU M10002T. The results of phylogenetic analyses based on 16S rRNA gene sequences indicated that the two strains formed a tight cluster within the genus Chakrabartia . A draft genomic comparison between the two strains revealed an average nucleotide identity of 97.3 % and a digital DNA–DNA hybridization estimate of 79.5±2.9 %, strongly indicating that the two strains represented a single species. In addition, neither strain displayed any striking differences in metabolic, physiological or chemotaxonomic features. Therefore, we propose that Aestuariisphingobium litorale is a later heterotypic synonym of Chakrabartia godavariana .

scholarly journals Subtyping psychological distress in the population: a semi-parametric network approach

2019 ◽  
Vol 29 ◽  
Author(s):  
S. de Vos ◽  
S. Patten ◽  
E. C. Wit ◽  
E. H. Bos ◽  
K. J. Wardenaar ◽  
...  
Keyword(s):  
Psychological Distress ◽  
Community Sample ◽  
A Priori ◽  
Network Models ◽  
Optimal Choice ◽  
Data Driven ◽  
Network Density ◽  
Parametric Network ◽  
Distress Scale ◽  
Non Parametric

Abstract Aims The mechanisms underlying both depressive and anxiety disorders remain poorly understood. One of the reasons for this is the lack of a valid, evidence-based system to classify persons into specific subtypes based on their depressive and/or anxiety symptomatology. In order to do this without a priori assumptions, non-parametric statistical methods seem the optimal choice. Moreover, to define subtypes according to their symptom profiles and inter-relations between symptoms, network models may be very useful. This study aimed to evaluate the potential usefulness of this approach. Methods A large community sample from the Canadian general population (N = 254 443) was divided into data-driven clusters using non-parametric k-means clustering. Participants were clustered according to their (co)variation around the grand mean on each item of the Kessler Psychological Distress Scale (K10). Next, to evaluate cluster differences, semi-parametric network models were fitted in each cluster and node centrality indices and network density measures were compared. Results A five-cluster model was obtained from the cluster analyses. Network density varied across clusters, and was highest for the cluster of people with the lowest K10 severity ratings. In three cluster networks, depressive symptoms (e.g. feeling depressed, restless, hopeless) had the highest centrality. In the remaining two clusters, symptom networks were characterised by a higher prominence of somatic symptoms (e.g. restlessness, nervousness). Conclusion Finding data-driven subtypes based on psychological distress using non-parametric methods can be a fruitful approach, yielding clusters of persons that differ in illness severity as well as in the structure and strengths of inter-symptom relationships.

scholarly journals Labour sharing promotes coexistence in atrazine degrading bacterial communities

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Loren Billet ◽  
Marion Devers ◽  
Nadine Rouard ◽  
Fabrice Martin-Laurent ◽  
Aymé Spor
Keyword(s):  
Bacterial Communities ◽  
Gene Loss ◽  
Bacterial Species ◽  
Single Species ◽  
Microbial Consortia ◽  
The Public ◽  
Herbicide Atrazine ◽  
Set Up ◽  
Multiple Species ◽  
Isolated Species

AbstractMicrobial communities are pivotal in the biodegradation of xenobiotics including pesticides. In the case of atrazine, multiple studies have shown that its degradation involved a consortia rather than a single species, but little is known about how interdependency between the species composing the consortium is set up. The Black Queen Hypothesis (BQH) formalized theoretically the conditions leading to the evolution of dependency between species: members of the community called ‘helpers’ provide publicly common goods obtained from the costly degradation of a compound, while others called ‘beneficiaries’ take advantage of the public goods, but lose access to the primary resource through adaptive degrading gene loss. Here, we test whether liquid media supplemented with the herbicide atrazine could support coexistence of bacterial species through BQH mechanisms. We observed the establishment of dependencies between species through atrazine degrading gene loss. Labour sharing between members of the consortium led to coexistence of multiple species on a single resource and improved atrazine degradation potential. Until now, pesticide degradation has not been approached from an evolutionary perspective under the BQH framework. We provide here an evolutionary explanation that might invite researchers to consider microbial consortia, rather than single isolated species, as an optimal strategy for isolation of xenobiotics degraders.

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