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dRep: a tool for fast and accurate genomic comparisons that enables improved genome recovery from metagenomes through de-replication
The number of microbial genomes sequenced each year is expanding rapidly, in part due to genome-resolved metagenomic studies that routinely recover hundreds of draft-quality genomes. Rapid algorithms have been developed to comprehensively compare large genome sets, but they are not accurate with draft-quality genomes. Here we present dRep, a program that reduces the computational time for pairwise genome comparisons by sequentially applying a fast, inaccurate estimation of genome distance, and a slow, accurate measure of average nucleotide identity. dRep achieves a 28 × increase in speed with perfect recall and precision when benchmarked against previously developed algorithms. We demonstrate the use of dRep for genome recovery from time-series datasets. Each metagenome was assembled separately, and dRep was used to identify groups of essentially identical genomes and select the best genome from each replicate set. This resulted in recovery of significantly more and higher-quality genomes compared to the set recovered using co-assembly.
Journal Article
ggClusterNet: An R package for microbiome network analysis and modularity‐based multiple network layouts
The network analysis has attracted increasing attention and interest from ecological academics, thus it is of great necessity to develop more convenient and powerful tools. For that reason, we have developed an R package, named “ggClusterNet,” to complete and display the network analysis in an easier manner. In that package, ten network layout algorithms are designed to better display the modules of microbiome network (randomClusterG, PolygonClusterG, PolygonRrClusterG, ArtifCluster, randSNEClusterG, PolygonModsquareG, PolyRdmNotdCirG, model_Gephi.2, model_igraph, and model_maptree). For the convenience of the users, many functions related to microbial network analysis, such as corMicor(), net_properties(), node_properties(), ZiPiPlot(), random_Net_compate(), are integrated to complete the network mining. Furthermore, the pipeline function named network.2() and corBionetwork() are also added for the quick achievement of the network or bipartite network analysis as well as their in‐depth mining. The ggClusterNet is publicly available via GitHub (https://github.com/taowenmicro/ggClusterNet/) or Gitee (https://gitee.com/wentaomicro/ggClusterNet) for users' access. A complete description of the usages can be found on the manuscript's GitHub page (https://github.com/taowenmicro/ggClusterNet/wiki). Highlights ggClusterNet is an R package for microbial networks. Analysis functions could help the user to easily complete network analysis and interpretation. Ten network layout algorithms allow users more alternatives to plot the network and generate published‐ready figures. It is free to access on GitHub and Gitee. ggClusterNet is an R package for microbial networks analysis and interpretation. Ten network layout algorithms allow users more alternatives to plot the network and generate published‐ready figures. It is free to access on GitHub and Gitee.
Journal Article
Ggtree: A serialized data object for visualization of a phylogenetic tree and annotation data
While phylogenetic trees and associated data have been getting easier to generate, it has been difficult to reuse, combine, and synthesize the information they provided, because published trees are often only available as image files and associated data are often stored in incompatible formats. To increase the reproducibility and reusability of phylogenetic data, the ggtree object was designed for storing phylogenetic tree and associated data, as well as visualization directives. The ggtree object itself is a graphic object and can be rendered as a static image. More importantly, the input tree and associated data that are used in visualization can be extracted from the graphic object, making it an ideal data structure for publishing tree (image, tree, and data in one single object) and thus enhancing data reuse and analytical reproducibility, as well as facilitating integrative and comparative studies. The ggtree package is freely available at https://www.bioconductor.org/packages/ggtree. The ggtree object is designed to store phylogenetic tree and associated data, and the object itself is a graphic object that can be rendered as an image file. This work will increase the reproducibility and reusability of phylogenetic data, as well as facilitate integrative and comparative studies. Highlights The phylogenetic tree and diverse accompanying data can be stored in a ggtree graph object, which improves the reproducibility and reusability of phylogenetic data. The phylogenetic tree and associated data can be extracted from the ggtree object, which can be reanalyzed and help various scientific disciplines synthesize their comparative studies and phylogenetic information. The ggtree graph object can be rendered as a static image, and the visualization directives that were previously saved in the object can be reused to display a different tree object in a manner akin to Microsoft Word Format Painter.
Journal Article
ImageGP: An easy‐to‐use data visualization web server for scientific researchers
Data visualization plays a crucial role in illustrating results and sharing knowledge among researchers. Though many types of visualization tools are widely used, most of them require enough coding experience or are designed for specialized usages, or are not free. Here, we present ImageGP, a specialized visualization platform designed for biology and chemistry data illustration. ImageGP could generate generalized plots like lines, bars, scatters, boxes, sets, heatmaps, and histograms with the most common input content in a user‐friendly interface. Normally plotting using ImageGP only needs a few mouse clicks. For some plots, one only needs to just paste data and click submit to get the visualization results. Additionally, ImageGP supplies up to 26 parameters to meet customizable requirements. ImageGP also contains specialized plots like volcano plot, functional enrichment plot for most omics‐data analysis, and other four specialized functions for microbiome analysis. Since 2017, ImageGP has been running for nearly 5 years and serving 336,951 visits from all over the world. Together, ImageGP (http://www.ehbio.com/ImageGP/) is an effective and efficient tool for experimental researchers to comprehensively visualize and interpret data generated from wet‐lab and dry‐lab. Representative visualization results of ImageGP. ImageGP supports 16 types of images (including heatmap, volcano plot, enrichment bubble plot) and four types of online analysis with up to 26 parameters for customization. Highlights Publication‐quality visualization results. Easy to use and customize. Reproducible results with scripts.
Journal Article
ASCT2/SLC1A5 controls glutamine uptake and tumour growth in triple-negative basal-like breast cancer
Alanine, serine, cysteine-preferring transporter 2 (ASCT2; SLC1A5) mediates uptake of glutamine, a conditionally essential amino acid in rapidly proliferating tumour cells. Uptake of glutamine and subsequent glutaminolysis is critical for activation of the mTORC1 nutrient-sensing pathway, which regulates cell growth and protein translation in cancer cells. This is of particular interest in breast cancer, as glutamine dependence is increased in high-risk breast cancer subtypes. Pharmacological inhibitors of ASCT2-mediated transport significantly reduced glutamine uptake in human breast cancer cell lines, leading to the suppression of mTORC1 signalling, cell growth and cell cycle progression. Notably, these effects were subtype-dependent, with ASCT2 transport critical only for triple-negative (TN) basal-like breast cancer cell growth compared with minimal effects in luminal breast cancer cells. Both stable and inducible shRNA-mediated ASCT2 knockdown confirmed that inhibiting ASCT2 function was sufficient to prevent cellular proliferation and induce rapid cell death in TN basal-like breast cancer cells, but not in luminal cells. Using a bioluminescent orthotopic xenograft mouse model, ASCT2 expression was then shown to be necessary for both successful engraftment and growth of HCC1806 TN breast cancer cells
in vivo
. Lower tumoral expression of ASCT2 conferred a significant survival advantage in xenografted mice. These responses remained intact in primary breast cancers, where gene expression analysis showed high expression of
ASCT2
and glutamine metabolism-related genes, including
GLUL
and
GLS
, in a cohort of 90 TN breast cancer patients, as well as correlations with the transcriptional regulators,
MYC
and
ATF4
. This study provides preclinical evidence for the feasibility of novel therapies exploiting ASCT2 transporter activity in breast cancer, particularly in the high-risk basal-like subgroup of TN breast cancer where there is not only high expression of ASCT2, but also a marked reliance on its activity for sustained cellular proliferation.
Journal Article
Ultra-high-throughput microbial community analysis on the Illumina HiSeq and MiSeq platforms
DNA sequencing continues to decrease in cost with the Illumina HiSeq2000 generating up to 600 Gb of paired-end 100 base reads in a ten-day run. Here we present a protocol for community amplicon sequencing on the HiSeq2000 and MiSeq Illumina platforms, and apply that protocol to sequence 24 microbial communities from host-associated and free-living environments. A critical question as more sequencing platforms become available is whether biological conclusions derived on one platform are consistent with what would be derived on a different platform. We show that the protocol developed for these instruments successfully recaptures known biological results, and additionally that biological conclusions are consistent across sequencing platforms (the HiSeq2000 versus the MiSeq) and across the sequenced regions of amplicons.
Journal Article
Soil protist communities form a dynamic hub in the soil microbiome
Soil microbes are essential for soil fertility. However, most studies focus on bacterial and/or fungal communities, while the top-down drivers of this microbiome composition, protists, remain poorly understood. Here, we investigated how soil amendments affect protist communities and inferred potential interactions with bacteria and fungi. Specific fertilization treatments impacted both the structure and function of protist communities. Organic fertilizer amendment strongly reduced the relative abundance of plant pathogenic protists and increased bacterivorous and omnivorous protists. The addition of individual biocontrol bacteria and fungi further altered the soil protist community composition, and eventually function. Network analysis integrating protist, bacterial and fungal community data, placed protists as a central hub in the soil microbiome, linking diverse bacterial and fungal populations. Given their dynamic response to soil management practices and key position in linking soil microbial networks, protists may provide the leverage between soil management and the enhancement of bacterial and fungal microbiota at the service of improved soil health.
Journal Article
Absolute quantification of microbial taxon abundances
High-throughput amplicon sequencing has become a well-established approach for microbial community profiling. Correlating shifts in the relative abundances of bacterial taxa with environmental gradients is the goal of many microbiome surveys. As the abundances generated by this technology are semi-quantitative by definition, the observed dynamics may not accurately reflect those of the actual taxon densities. We combined the sequencing approach (16S rRNA gene) with robust single-cell enumeration technologies (flow cytometry) to quantify the absolute taxon abundances. A detailed longitudinal analysis of the absolute abundances resulted in distinct abundance profiles that were less ambiguous and expressed in units that can be directly compared across studies. We further provide evidence that the enrichment of taxa (increase in relative abundance) does not necessarily relate to the outgrowth of taxa (increase in absolute abundance). Our results highlight that both relative and absolute abundances should be considered for a comprehensive biological interpretation of microbiome surveys.
Journal Article
Phylogenetic network analysis applied to pig gut microbiota identifies an ecosystem structure linked with growth traits
The ecological interactions within the gut microbial communities are complex and far from being fully understood. Here we report the first study that aims at defining the interaction network of the gut microbiota in pigs and comparing it with the enterotype-like clustering analysis. Fecal microbiota of 518 healthy piglets was characterized by 16S ribosomal RNA gene sequencing. Two networks were constructed at the genus and operational taxonomic unit levels. Within-network interactions mirrored the human gut microbiota relationships, with a strong co-exclusion between Prevotella and Ruminococcus genera, and were consistent with the two enterotype-like clusters identified in the pig microbiota. Remarkably, the cluster classification of the individuals was significantly associated with the body weight at 60 days of age (P=0.005) and average daily gain (P=0.027). To the best of our knowledge, this is the first study to provide an integrated overview of the porcine gut microbiota that suggests a conservation of the ecological community interactions and functional architecture between humans and pig. Moreover, we show that the microbial ecosystems and porcine growth traits are linked, which allows us to foresee that the enterotype concept may have an important role in the animal production industry.The ISME Journal advance online publication, 13 May 2016; doi:10.1038/ismej.2016.77.
Journal Article