scholarly journals High throughput sequencing provides exact genomic locations of inducible prophages and accurate phage-to-host ratios in gut microbial strains

Microbiome ◽  
2021 ◽  
Vol 9 (1) ◽  
Author(s):  
Mirjam Zünd ◽  
Hans-Joachim Ruscheweyh ◽  
Christopher M. Field ◽  
Natalie Meyer ◽  
Miguelangel Cuenca ◽  
...  

Abstract Background Temperate phages influence the density, diversity and function of bacterial populations. Historically, they have been described as carriers of toxins. More recently, they have also been recognised as direct modulators of the gut microbiome, and indirectly of host health and disease. Despite recent advances in studying prophages using non-targeted sequencing approaches, methodological challenges in identifying inducible prophages in bacterial genomes and quantifying their activity have limited our understanding of prophage-host interactions. Results We present methods for using high-throughput sequencing data to locate inducible prophages, including those previously undiscovered, to quantify prophage activity and to investigate their replication. We first used the well-established Salmonella enterica serovar Typhimurium/p22 system to validate our methods for (i) quantifying phage-to-host ratios and (ii) accurately locating inducible prophages in the reference genome based on phage-to-host ratio differences and read alignment alterations between induced and non-induced prophages. Investigating prophages in bacterial strains from a murine gut model microbiota known as Oligo-MM12 or sDMDMm2, we located five novel inducible prophages in three strains, quantified their activity and showed signatures of lateral transduction potential for two of them. Furthermore, we show that the methods were also applicable to metagenomes of induced faecal samples from Oligo-MM12 mice, including for strains with a relative abundance below 1%, illustrating its potential for the discovery of inducible prophages also in more complex metagenomes. Finally, we show that predictions of prophage locations in reference genomes of the strains we studied were variable and inconsistent for four bioinformatic tools we tested, which highlights the importance of their experimental validation. Conclusions This study demonstrates that the integration of experimental induction and bioinformatic analysis presented here is a powerful approach to accurately locate inducible prophages using high-throughput sequencing data and to quantify their activity. The ability to generate such quantitative information will be critical in helping us to gain better insights into the factors that determine phage activity and how prophage-bacteria interactions influence our microbiome and impact human health.

MycoKeys ◽  
2018 ◽  
Vol 39 ◽  
pp. 29-40 ◽  
Author(s):  
Sten Anslan ◽  
R. Henrik Nilsson ◽  
Christian Wurzbacher ◽  
Petr Baldrian ◽  
Leho Tedersoo ◽  
...  

Along with recent developments in high-throughput sequencing (HTS) technologies and thus fast accumulation of HTS data, there has been a growing need and interest for developing tools for HTS data processing and communication. In particular, a number of bioinformatics tools have been designed for analysing metabarcoding data, each with specific features, assumptions and outputs. To evaluate the potential effect of the application of different bioinformatics workflow on the results, we compared the performance of different analysis platforms on two contrasting high-throughput sequencing data sets. Our analysis revealed that the computation time, quality of error filtering and hence output of specific bioinformatics process largely depends on the platform used. Our results show that none of the bioinformatics workflows appears to perfectly filter out the accumulated errors and generate Operational Taxonomic Units, although PipeCraft, LotuS and PIPITS perform better than QIIME2 and Galaxy for the tested fungal amplicon dataset. We conclude that the output of each platform requires manual validation of the OTUs by examining the taxonomy assignment values.


Genomics ◽  
2017 ◽  
Vol 109 (2) ◽  
pp. 83-90 ◽  
Author(s):  
Yan Guo ◽  
Yulin Dai ◽  
Hui Yu ◽  
Shilin Zhao ◽  
David C. Samuels ◽  
...  

2014 ◽  
Author(s):  
Simon Anders ◽  
Paul Theodor Pyl ◽  
Wolfgang Huber

Motivation: A large choice of tools exists for many standard tasks in the analysis of high-throughput sequencing (HTS) data. However, once a project deviates from standard work flows, custom scripts are needed. Results: We present HTSeq, a Python library to facilitate the rapid development of such scripts. HTSeq offers parsers for many common data formats in HTS projects, as well as classes to represent data such as genomic coordinates, sequences, sequencing reads, alignments, gene model information, variant calls, and provides data structures that allow for querying via genomic coordinates. We also present htseq-count, a tool developed with HTSeq that preprocesses RNA-Seq data for differential expression analysis by counting the overlap of reads with genes. Availability: HTSeq is released as open-source software under the GNU General Public Licence and available from http://www-huber.embl.de/HTSeq or from the Python Package Index, https://pypi.python.org/pypi/HTSeq


Author(s):  
Anthony Federico ◽  
Stefano Monti

Abstract Summary Geneset enrichment is a popular method for annotating high-throughput sequencing data. Existing tools fall short in providing the flexibility to tackle the varied challenges researchers face in such analyses, particularly when analyzing many signatures across multiple experiments. We present a comprehensive R package for geneset enrichment workflows that offers multiple enrichment, visualization, and sharing methods in addition to novel features such as hierarchical geneset analysis and built-in markdown reporting. hypeR is a one-stop solution to performing geneset enrichment for a wide audience and range of use cases. Availability and implementation The most recent version of the package is available at https://github.com/montilab/hypeR. Contact [email protected] or [email protected]


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