In Silico Study Suggesting the Bias of Primers Choice in the Molecular Identification of Fungal Aerosols

This paper presents an in silico analysis to assess the current state of the fungal UNITE database in terms of the two eukaryote nuclear ribosomal regions, Internal Transcribed Spacers 1 and 2 (ITS1 and ITS2), used in describing fungal diversity. Microbial diversity is often evaluated with amplicon-based high-throughput sequencing approaches, which is a target enrichment method that relies on the amplification of a specific target using particular primers before sequencing. Thus, the results are highly dependent on the quality of the primers used for amplification. The goal of this study is to validate if the mismatches of the primers on the binding sites of the targeted taxa could explain the differences observed when using either ITS1 or ITS2 in describing airborne fungal diversity. Hence, the choice of the pairs of primers for each barcode concur with a study comparing the performance of ITS1 and ITS2 in three occupational environments. The sequence length varied between the amplicons retrieved from the UNITE database using the pair of primers targeting ITS1 and ITS2. However, the database contains an equal number of unidentified taxa from ITS1 and ITS2 regions in the six taxonomic levels employed (phylum, class, order, family, genus, species). The chosen ITS primers showed differences in their ability to amplify fungal sequences from the UNITE database. Eleven taxa consisting of Trichocomaceae, Dothioraceae, Botryosphaeriaceae, Mucorales, Saccharomycetes, Pucciniomycetes, Ophiocordyceps, Microsporidia, Archaeorhizomycetes, Mycenaceae, and Tulasnellaceae showed large variations between the two regions. Note that members of the latter taxa are not all typical fungi found in the air. As no universal method is currently available to cover all the fungal kingdom, continuous work in designing primers, and particularly combining multiple primers targeting the ITS region is the best way to compensate for the biases of each one to get a larger view of the fungal diversity.

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Best practices in metabarcoding of fungi: from experimental design to results

10.22541/au.163430390.04226544/v1 ◽

2021 ◽

Author(s):

Leho Tedersoo ◽

Mohammad Bahram ◽

Lucie Zinger ◽

Henrik Nilsson ◽

Peter Kennedy ◽

...

Keyword(s):

Experimental Design ◽

Best Practices ◽

Fungal Diversity ◽

High Throughput Sequencing ◽

Its Region ◽

Fungal Communities ◽

Sequence Variants ◽

Transcriptomic Data ◽

Operational Taxonomic Units ◽

Computational Analyses

The development of high-throughput sequencing (HTS) technologies has greatly improved our capacity to identify fungi and unveil their ecological roles across a variety of ecosystems. Here we provide an overview about current best practices in metabarcoding analysis of fungal communities, from experimental design through molecular and computational analyses. By re-analysing published datasets, we find that operational taxonomic units (OTUs) outperform amplified sequence variants (ASVs) in recovering fungal diversity, which is particularly evident for long markers. Additionally, analysis of the full-length ITS region allows more accurate taxonomic placement of fungi and other eukaryotes compared with the ITS2 subregion. We conclude that metabarcoding analyses of fungi are especially promising for co-analyses with the functional metagenomic or transcriptomic data, integrating fungi in the entire microbiome, recovery of novel fungal lineages and ancient organisms as well as barcoding of old specimens including type material.

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An in silico analysis of robust but fragile gene regulation links enhancer length to robustness

10.1101/677641 ◽

2019 ◽

Author(s):

Kenneth A Barr ◽

John Reinitz ◽

Ovidiu Radulescu

Keyword(s):

Gene Regulation ◽

In Silico ◽

In Silico Analysis ◽

Mathematical Concept ◽

Sequence Length ◽

Local Concentration ◽

Quantitative Evidence ◽

Regulatory Systems ◽

Genetic Sequences ◽

Gene Regulatory

1AbstractOrganisms must ensure that expression of genes is directed to the appropriate tissues at the correct times, while simultaneously ensuring that these gene regulatory systems are robust to perturbation. This idea is captured by a mathematical concept called r-robustness, which says that a system is robust to a perturbation in up to r - 1 randomly chosen parameters. In this work we use this idea to investigate the robustness of gene regulation using a sequence level model of the Drosophila melanogaster gene even-skipped. We find that gene regulation can be remarkably sensitive to changes in transcription factor concentrations at the boundaries of expression features, while it is robust to perturbation elsewhere. We also find that the length of sequence used to control an expression feature correlates negatively with the number of nucleotides that are sensitive to mutation in both natural and in silico predicted enhancers. In all cases, the exact degree of robustness obtained is dependent not only on DNA sequence, but also on the local concentration of regulatory factors. By analyzing both natural and synthetic sequences, we provide strong quantitative evidence that increased sequence length makes gene regulatory systems more robust to genetic perturbation.2Author SummaryRobustness assures that organisms can survive when faced with unpredictable environments or genetic mutations. In this work, we characterize the robustness of gene regulation using an experimentally validated model of the regulation of the Drosophila gene even-skipped. We use a mathematically precise definition of robustness that allows us to make quantitative comparisons of robustness between different genetic sequences or between different nuclei. From this analysis, we found that genetic sequences that were not previously known to be important for gene regulation reduce sensitivity to genetic perturbation. In contrast, we found that gene regulation can be very sensitive to the levels of regulators. This extreme sensitivity was only observed at the boundaries of expression features, where switch-like behavior is desirable. This highlights the importance of considering context when assessing robustness.

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Comparison of the performance of ITS1 and ITS2 as barcodes in amplicon-based sequencing of bioaerosols

PeerJ ◽

10.7717/peerj.8523 ◽

2020 ◽

Vol 8 ◽

pp. e8523 ◽

Cited By ~ 5

Author(s):

Hamza Mbareche ◽

Marc Veillette ◽

Guillaume Bilodeau ◽

Caroline Duchaine

Keyword(s):

Fungal Diversity ◽

High Throughput Sequencing ◽

Dairy Farms ◽

Culture Methods ◽

Specific Target ◽

Taxonomic Profile ◽

Differential Abundance Analysis ◽

Metagenomic Approach ◽

Its1 And Its2

This paper presents the performance of two eukaryotic genomic ribosomal regions, ITS1 and ITS2, in describing fungal diversity in aerosol samples using amplicon-based High-Throughput Sequencing (HTS). Composting sites, biomethanization facilities, and dairy farms, all affected by the presence of fungi, were visited to collect air samples. The amplicon-based HTS approach is a target enrichment method that relies on the amplification of a specific target using particular primers before sequencing. Thus, the results are highly dependent on the quality of amplification. For this reason, the authors of this paper used a shotgun metagenomic approach to compare its outcome with the amplicon-based method. Indeed, shotgun metagenomic does not rely on any amplification prior to sequencing, because all genes are sequenced without a specific target. In addition, culture methods were added to the analyses in biomethanization and dairy farms samples to validate their contribution to fungal diversity of aerosols. The results obtained are unequivocal towards ITS1 outperformance to ITS2 in terms of richness, and taxonomic coverage. The differential abundance analysis did demonstrate that some taxa were exclusively detected only by ITS2, and vice-versa for ITS1. However, the shotgun metagenomic approach showed a taxonomic profile more resembling to ITS1 than ITS2. Based on these results, neither of the barcodes evaluated is perfect in terms of distinguishing all species. Using both barcodes offers a broader view of the fungal aerosol population. However, with the actual knowledge, the authors strongly recommend using ITS1 as a universal fungal barcode for quick general analyses of diversity and when limited financial resources are available, primarily due its ability to capture taxonomic profiles similar to those obtained using the shotgun metagenomic. The culture comparison with amplicon-based sequencing showed the complementarity of both approaches in describing the most abundant taxa.

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Basal Role for Nrf2-transgne on transcriptional (mRNA/miRNA) regulation in the mouse myocardium

10.1101/490953 ◽

2018 ◽

Author(s):

Arun Jyothidasan ◽

Gobinath Shanmugam ◽

John Zhang ◽

Brain Dally ◽

David Crossman ◽

...

Keyword(s):

Oxidative Stress ◽

In Silico ◽

Defense Mechanisms ◽

High Throughput Sequencing ◽

Redox Homeostasis ◽

In Silico Analysis ◽

Mirna Regulation ◽

Sequencing Data ◽

High Throughput Sequencing Data ◽

Cellular Environment

Background: NFE2L2 (nuclear factor, erythroid 2 like 2; Nrf2), is a stress responsive transcription factor that regulates cellular redox homeostasis. The action mechanism of Nrf2 occurs through sensing oxidative stress in the cellular environment in responses to various stresses including altered metabolism, toxic insult and xenobiotic stresses. However, under the basal condition, the role of excess Nrf2 on global miRNA and mRNA interactions in the myocardium is unknown. Here, we tested a hypothesis that excess Nrf2 (transgene) will promote the transcription of antioxidants, which then might escalate the basal defense mechanisms in the heart. Furthermore, we investigated whether changes in the miRNA profile might have a strong role on the transcriptome in TG hearts. Methods: Non transgenic (NTG), and Cardiac specific Nrf2 transgenic (Nrf2 TG) mice in the C57/BL6 background at the age of 6 to 8 months were used to examine transcriptional and posttranscriptional signatures (mRNA and miRNA expressions) by performing next generation sequencing (NGS) for RNA (RNAseq) and small RNA (sRNAseq) for miRNA expressions in the heart (n=3 to 6/group). Validation of the NGS data was performed by quantitative real time PCR (qRT PCR) using specific primers targeting selected miRNAs or mRNAs. Finally, in silico analyses were performed to determine the miRNA and mRNA interactome networks and the pathways that are potentially regulated by these networks. Results: NGS analysis for mRNA indicated that there were 5727 differently expressed genes DEGs) in the Nrf2 TG vs. NTG myocardium. Of which, 3552 were upregulated and 2175 were downregulated significantly. Small RNAseq analysis revealed that 112 miRNAs were significantly altered in Nrf2TG versus NTG hearts. Among these miRNAs, 68 were upregulated and 44 were downregulated significantly. Validation of key targets for mRNA and miRNA by qPCR confirmed the NGS results. In silico analysis (IPA) revealed that the majority of the miRNAs and mRNAs that are significantly altered in response to transgene expression are potentially involved in Nrf2 mediated oxidative stress response, ILK Signaling, hypoxia signaling in the cardiovascular system and glutathione mediated detoxification etc. Conclusion: These high throughput sequencing data sets from cardiac specific Nrf2TG mice revealed the transcriptome wide effects of Nrf2 in the myocardium. Furthermore, our comprehensive analysis indicates that Nrf2 may directly or indirectly regulates these sub sets of cardiac miRNA and mRNA interactome networks under basal physiological setting.

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A systematic review with in silico analysis on transcriptomic profile of gallbladder carcinoma

Seminars in Oncology ◽

10.1053/j.seminoncol.2020.02.012 ◽

2020 ◽

Vol 47 (6) ◽

pp. 398-408

Author(s):

Sonam Tulsyan ◽

Showket Hussain ◽

Balraj Mittal ◽

Sundeep Singh Saluja ◽

Pranay Tanwar ◽

...

Keyword(s):

Systematic Review ◽

Gallbladder Carcinoma ◽

In Silico ◽

In Silico Analysis ◽

Transcriptomic Profile ◽

Silico Analysis

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In Silico Analysis of Single Nucleotide Polymorphism in Human Prothrombin Gene

10.1055/s-0039-1680245 ◽

2019 ◽

Author(s):

I. Farah ◽

A. El-Mubark ◽

M. Osman ◽

A. Soliman ◽

F. Ali ◽

...

Keyword(s):

Single Nucleotide Polymorphism ◽

In Silico ◽

In Silico Analysis ◽

Nucleotide Polymorphism ◽

Single Nucleotide ◽

Prothrombin Gene ◽

Silico Analysis

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Enalos Suite of Tools: Enhancing Cheminformatics and Nanoinfor - matics through KNIME

Current Medicinal Chemistry ◽

10.2174/0929867327666200727114410 ◽

2020 ◽

Vol 27 (38) ◽

pp. 6523-6535 ◽

Cited By ~ 3

Author(s):

Antreas Afantitis ◽

Andreas Tsoumanis ◽

Georgia Melagraki

Keyword(s):

Data Analysis ◽

Virtual Screening ◽

In Silico ◽

Model Development ◽

In Silico Analysis ◽

Material Design ◽

Efficient Solutions ◽

Biological Data ◽

Cost Efficient ◽

Silico Analysis

Drug discovery as well as (nano)material design projects demand the in silico analysis of large datasets of compounds with their corresponding properties/activities, as well as the retrieval and virtual screening of more structures in an effort to identify new potent hits. This is a demanding procedure for which various tools must be combined with different input and output formats. To automate the data analysis required we have developed the necessary tools to facilitate a variety of important tasks to construct workflows that will simplify the handling, processing and modeling of cheminformatics data and will provide time and cost efficient solutions, reproducible and easier to maintain. We therefore develop and present a toolbox of >25 processing modules, Enalos+ nodes, that provide very useful operations within KNIME platform for users interested in the nanoinformatics and cheminformatics analysis of chemical and biological data. With a user-friendly interface, Enalos+ Nodes provide a broad range of important functionalities including data mining and retrieval from large available databases and tools for robust and predictive model development and validation. Enalos+ Nodes are available through KNIME as add-ins and offer valuable tools for extracting useful information and analyzing experimental and virtual screening results in a chem- or nano- informatics framework. On top of that, in an effort to: (i) allow big data analysis through Enalos+ KNIME nodes, (ii) accelerate time demanding computations performed within Enalos+ KNIME nodes and (iii) propose new time and cost efficient nodes integrated within Enalos+ toolbox we have investigated and verified the advantage of GPU calculations within the Enalos+ nodes. Demonstration data sets, tutorial and educational videos allow the user to easily apprehend the functions of the nodes that can be applied for in silico analysis of data.

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In Silico Study of 1, 4 Alpha Glucan Branching Enzyme and Substrate Docking Studies

Current Proteomics ◽

10.2174/1570164616666190401204009 ◽

2020 ◽

Vol 17 (1) ◽

pp. 40-50

Author(s):

Farzane Kargar ◽

Amir Savardashtaki ◽

Mojtaba Mortazavi ◽

Masoud Torkzadeh Mahani ◽

Ali Mohammad Amani ◽

...

Keyword(s):

Phylogenetic Tree ◽

In Silico ◽

Alpha Helix ◽

In Silico Analysis ◽

Glycogen Storage ◽

Docking Studies ◽

Random Coil ◽

Special Topic ◽

Industrial Biotechnology ◽

In Silico Study

Background: The 1,4-alpha-glucan branching protein (GlgB) plays an important role in the glycogen biosynthesis and the deficiency in this enzyme has resulted in Glycogen storage disease and accumulation of an amylopectin-like polysaccharide. Consequently, this enzyme was considered a special topic in clinical and biotechnological research. One of the newly introduced GlgB belongs to the Neisseria sp. HMSC071A01 (Ref.Seq. WP_049335546). For in silico analysis, the 3D molecular modeling of this enzyme was conducted in the I-TASSER web server. Methods: For a better evaluation, the important characteristics of this enzyme such as functional properties, metabolic pathway and activity were investigated in the TargetP software. Additionally, the phylogenetic tree and secondary structure of this enzyme were studied by Mafft and Prabi software, respectively. Finally, the binding site properties (the maltoheptaose as substrate) were studied using the AutoDock Vina. Results: By drawing the phylogenetic tree, the closest species were the taxonomic group of Betaproteobacteria. The results showed that the structure of this enzyme had 34.45% of the alpha helix and 45.45% of the random coil. Our analysis predicted that this enzyme has a potential signal peptide in the protein sequence. Conclusion: By these analyses, a new understanding was developed related to the sequence and structure of this enzyme. Our findings can further be used in some fields of clinical and industrial biotechnology.

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