Nanometa Live: a user-friendly application for real-time metagenomic data analysis and pathogen identification

SUMMARY

Nanometa Live presents a user-friendly interface designed for real-time metagenomic data analysis and pathogen identification utilizing Oxford Nanopore Technologies' MinION and Flongle flow cells. It offers an efficient workflow and graphical interface for the visualization and interpretation of metagenomic data as it is being generated. Key features include automated BLAST validation, streamlined handling of custom Kraken2 databases, and a simplified graphical user interface for enhanced user experience. Nanometa Live is particularly notable for its capability to run without constant internet or server access once installed, setting it apart from similar tools. It provides a comprehensive view of taxonomic composition and facilitates the detection of user-defined pathogens or other species of interest, catering to both researchers and clinicians.

AVAILABILITY AND IMPLEMENTATION

Nanometa Live has been implemented as a local web application using the Dash framework with Snakemake handling the data processing. The source code is freely accessible on the GitHub repository at https://github.com/FOI-Bioinformatics/nanometa_live and it is easily installable using Bioconda. It includes containerization support via Docker and Singularity, ensuring ease of use, reproducibility, and portability.

FlexTaxD: flexible modification of taxonomy databases for improved sequence classification

SUMMARY

The Flexible Taxonomy Database (FlexTaxD) framework provides a method for modification and merging official and custom taxonomic databases to create improved databases. Using such databases will increase accuracy and precision of existing methods to classify sequence reads.

AVAILABILITY AND IMPLEMENTATION

Source code is freely available at https://github.com/FOI-Bioinformatics/flextaxd and installable through Bioconda.

Reorganized Genomic Taxonomy of Francisellaceae Enables Design of Robust Environmental PCR Assays for Detection of Francisella tularensis

In recent years, an increasing diversity of species has been recognized within the family Francisellaceae. Unfortunately, novel isolates are sometimes misnamed in initial publications or multiple sources propose different nomenclature for genetically highly similar isolates. Thus, unstructured and occasionally incorrect information can lead to confusion in the scientific community. Historically, detection of Francisella tularensis in environmental samples has been challenging due to the considerable and unknown genetic diversity within the family, which can result in false positive results. We have assembled a comprehensive collection of genome sequences representing most known Francisellaceae species/strains and restructured them according to a taxonomy that is based on phylogenetic structure. From this structured dataset, we identified a small number of genomic regions unique to F. tularensis that are putatively suitable for specific detection of this pathogen in environmental samples. We designed and validated specific PCR assays based on these genetic regions that can be used for the detection of F. tularensis in environmental samples, such as water and air filters.

Genotyping of Francisella tularensis subsp. holarctica from Hares in Germany

Francisella tularensis is the causative agent of the zoonotic disease tularemia. In Germany, most human infections are caused by contact with infected hares. The aim of this study was to characterize Francisella tularensis subsp. holarctica strains isolated from hares in Germany and to develop bioinformatics tools to analyze their genetic relatedness. In total, 257 German isolates-obtained mainly from hares (n = 233), other vertebrate animals, and ticks, but also from humans (n = 3)-were analyzed within this study. Publically available sequence data from 49 isolates were used to put our isolates into an epidemiological context and to compare isolates from natural foci and humans. Whole-genome sequences were analyzed using core-genome Multi-Locus-Sequence-Typing, canonical Single Nucleotide Polymorphism (SNP) typing and whole-genome SNP typing. An overall conformity of genotype clustering between the typing methods was found, albeit with a lower resolution for canonical single SNP typing. The subclade distribution, both on local and national levels, among strains from humans and hares was similar, suggesting circulation of the same genotypes both in animals and humans. Whilst close to identical isolates of the same subclade were found distributed over large areas, small geographical foci often harbored members of different subclades. In conclusion, although genomic high-resolution typing was shown to be robust, reproducible and allowed the identification of highly closely related strains, genetic profiling alone is not always conclusive for epidemiological linkage of F. tularensis strains.

doepipeline: a systematic approach to optimizing multi-level and multi-step data processing workflows

BACKGROUND

Selecting the proper parameter settings for bioinformatic software tools is challenging. Not only will each parameter have an individual effect on the outcome, but there are also potential interaction effects between parameters. Both of these effects may be difficult to predict. To make the situation even more complex, multiple tools may be run in a sequential pipeline where the final output depends on the parameter configuration for each tool in the pipeline. Because of the complexity and difficulty of predicting outcomes, in practice parameters are often left at default settings or set based on personal or peer experience obtained in a trial and error fashion. To allow for the reliable and efficient selection of parameters for bioinformatic pipelines, a systematic approach is needed.

RESULTS

We present doepipeline, a novel approach to optimizing bioinformatic software parameters, based on core concepts of the Design of Experiments methodology and recent advances in subset designs. Optimal parameter settings are first approximated in a screening phase using a subset design that efficiently spans the entire search space, then optimized in the subsequent phase using response surface designs and OLS modeling. Doepipeline was used to optimize parameters in four use cases; 1) de-novo assembly, 2) scaffolding of a fragmented genome assembly, 3) k-mer taxonomic classification of Oxford Nanopore Technologies MinION reads, and 4) genetic variant calling. In all four cases, doepipeline found parameter settings that produced a better outcome with respect to the characteristic measured when compared to using default values. Our approach is implemented and available in the Python package doepipeline.

CONCLUSIONS

Our proposed methodology provides a systematic and robust framework for optimizing software parameter settings, in contrast to labor- and time-intensive manual parameter tweaking. Implementation in doepipeline makes our methodology accessible and user-friendly, and allows for automatic optimization of tools in a wide range of cases. The source code of doepipeline is available at https://github.com/clicumu/doepipeline and it can be installed through conda-forge.

NorWood: a gene expression resource for evo-devo studies of conifer wood development

The secondary xylem of conifers is composed mainly of tracheids that differ anatomically and chemically from angiosperm xylem cells. There is currently no high-spatial-resolution data available profiling gene expression during wood formation for any coniferous species, which limits insight into tracheid development. RNA-sequencing data from replicated, high-spatial-resolution section series throughout the cambial and woody tissues of Picea abies were used to generate the NorWood.conGenIE.org web resource, which facilitates exploration of the associated gene expression profiles and co-expression networks. Integration within PlantGenIE.org enabled a comparative regulomics analysis, revealing divergent co-expression networks between P. abies and the two angiosperm species Arabidopsis thaliana and Populus tremula for the secondary cell wall (SCW) master regulator NAC Class IIB transcription factors. The SCW cellulose synthase genes (CesAs) were located in the neighbourhoods of the NAC factors in A. thaliana and P. tremula, but not in P. abies. The NorWood co-expression network enabled identification of potential SCW CesA regulators in P. abies. The NorWood web resource represents a powerful community tool for generating evo-devo insights into the divergence of wood formation between angiosperms and gymnosperms and for advancing understanding of the regulation of wood development in P. abies.

AspWood: High-Spatial-Resolution Transcriptome Profiles Reveal Uncharacterized Modularity of Wood Formation in Populus tremula

Trees represent the largest terrestrial carbon sink and a renewable source of ligno-cellulose. There is significant scope for yield and quality improvement in these largely undomesticated species, and efforts to engineer elite varieties will benefit from improved understanding of the transcriptional network underlying cambial growth and wood formation. We generated high-spatial-resolution RNA sequencing data spanning the secondary phloem, vascular cambium, and wood-forming tissues of Populus tremula The transcriptome comprised 28,294 expressed, annotated genes, 78 novel protein-coding genes, and 567 putative long intergenic noncoding RNAs. Most paralogs originating from the Salicaceae whole-genome duplication had diverged expression, with the exception of those highly expressed during secondary cell wall deposition. Coexpression network analyses revealed that regulation of the transcriptome underlying cambial growth and wood formation comprises numerous modules forming a continuum of active processes across the tissues. A comparative analysis revealed that a majority of these modules are conserved in Picea abies The high spatial resolution of our data enabled identification of novel roles for characterized genes involved in xylan and cellulose biosynthesis, regulators of xylem vessel and fiber differentiation and lignification. An associated web resource (AspWood, http://aspwood.popgenie.org) provides interactive tools for exploring the expression profiles and coexpression network.

The Plant Genome Integrative Explorer Resource: PlantGenIE.org

Accessing and exploring large-scale genomics data sets remains a significant challenge to researchers without specialist bioinformatics training. We present the integrated PlantGenIE.org platform for exploration of Populus, conifer and Arabidopsis genomics data, which includes expression networks and associated visualization tools. Standard features of a model organism database are provided, including genome browsers, gene list annotation, Blast homology searches and gene information pages. Community annotation updating is supported via integration of WebApollo. We have produced an RNA-sequencing (RNA-Seq) expression atlas for Populus tremula and have integrated these data within the expression tools. An updated version of the ComPlEx resource for performing comparative plant expression analyses of gene coexpression network conservation between species has also been integrated. The PlantGenIE.org platform provides intuitive access to large-scale and genome-wide genomics data from model forest tree species, facilitating both community contributions to annotation improvement and tools supporting use of the included data resources to inform biological insight.

A resource for characterizing genome-wide binding and putative target genes of transcription factors expressed during secondary growth and wood formation in Populus

Identifying transcription factor target genes is essential for modeling the transcriptional networks underlying developmental processes. Here we report a chromatin immunoprecipitation sequencing (ChIP-seq) resource consisting of genome-wide binding regions and associated putative target genes for four Populus homeodomain transcription factors expressed during secondary growth and wood formation. Software code (programs and scripts) for processing the Populus ChIP-seq data are provided within a publically available iPlant image, including tools for ChIP-seq data quality control and evaluation adapted from the human Encyclopedia of DNA Elements (ENCODE) project. Basic information for each transcription factor (including members of Class I KNOX, Class III HD ZIP, BEL1-like families) binding are summarized, including the number and location of binding regions, distribution of binding regions relative to gene features, associated putative target genes, and enriched functional categories of putative target genes. These ChIP-seq data have been integrated within the Populus Genome Integrative Explorer (PopGenIE) where they can be analyzed using a variety of web-based tools. We present an example analysis that shows preferential binding of transcription factor ARBORKNOX1 to the nearest neighbor genes in a pre-calculated co-expression network module, and enrichment for meristem-related genes within this module including multiple orthologs of Arabidopsis KNOTTED-like Arabidopsis 2/6.

Adaptation of Dekkera bruxellensis to lignocellulose-based substrate

Adaptation of Dekkera bruxellensis to lignocellulose hydrolysate was investigated. Cells of D. bruxellensis were grown for 72 and 192 H in batch and continuous culture, respectively (adapted cells). Cultivations in semisynthetic medium were run as controls (nonadapted cells). To test the adaptation, cells from these cultures were reinoculated in the lignocellulose medium, and growth and ethanol production characteristics were monitored. Cells adapted to lignocellulose hydrolysate had a shorter lag phase, grew faster, and produced a higher ethanol concentration as compared with nonadapted cells. A stability test showed that after cultivation in rich medium, cells partially lost the adapted phenotype but still showed faster growth and higher ethanol production as compared with nonadapted cells. Because alcohol dehydrogenase genes have been described to be involved in the adaptation to furfural in Saccharomyces cerevisiae, an analogous mechanism of adaptation to lignocelluloses hydrolysate of D. bruxellensis was hypothesized. However, gene expression analysis showed that genes homologous to S. cerevisiae ADH1 were not involved in the adaptation to lignocelluloses hydrolysate in D. bruxellensis.

ComPlEx: conservation and divergence of co-expression networks in A. thaliana, Populus and O. sativa

Background

Divergence in gene regulation has emerged as a key mechanism underlying species differentiation. Comparative analysis of co-expression networks across species can reveal conservation and divergence in the regulation of genes.

Results

We inferred co-expression networks of A. thaliana, Populus spp. and O. sativa using state-of-the-art methods based on mutual information and context likelihood of relatedness, and conducted a comprehensive comparison of these networks across a range of co-expression thresholds. In addition to quantifying gene-gene link and network neighbourhood conservation, we also applied recent advancements in network analysis to do cross-species comparisons of network properties such as scale free characteristics and gene centrality as well as network motifs. We found that in all species the networks emerged as scale free only above a certain co-expression threshold, and that the high-centrality genes upholding this organization tended to be conserved. Network motifs, in particular the feed-forward loop, were found to be significantly enriched in specific functional subnetworks but where much less conserved across species than gene centrality. Although individual gene-gene co-expression had massively diverged, up to ~80% of the genes still had a significantly conserved network neighbourhood. For genes with multiple predicted orthologs, about half had one ortholog with conserved regulation and another ortholog with diverged or non-conserved regulation. Furthermore, the most sequence similar ortholog was not the one with the most conserved gene regulation in over half of the cases.

Conclusions

We have provided a comprehensive analysis of gene regulation evolution in plants and built a web tool for Comparative analysis of Plant co-Expression networks (ComPlEx, http://complex.plantgenie.org/). The tool can be particularly useful for identifying the ortholog with the most conserved regulation among several sequence-similar alternatives and can thus be of practical importance in e.g. finding candidate genes for perturbation experiments.