Tag: CAFE

The Microbiology Lab Pod is back with season two. This first episode was recorded on February 4 and has the theme of global change and effects on microbes. The crew (Johan Bengtsson-Palme, Emil Burman, Anna Abramova, Marcus Wenne, Sebastian Wettersten and Mahbuba Lubna Akter) is joined by two guests – Shumaila Malik and Emilio Rudbeck – and talks about the lab’s most recent publication, the one-year covid anniversary, the effects of global warming and other global change factors on soil microbial communities, and thawing permafrost.

The specific papers discussed in the pod (with approximate timings) are as follows:

• 5:45 – Abramova, A., Osińska, A., Kunche, H., Burman, E., Bengtsson-Palme, J., 2021. CAFE: a software suite for analysis of paired-sample transposon insertion sequencing data. Bioinformatics. https://doi.org/10.1093/bioinformatics/btaa1086
• 8:00 – Bengtsson, J., et al., 2011. Metaxa: a software tool for automated detection and discrimination among ribosomal small subunit (12S/16S/18S) sequences of archaea, bacteria, eukaryotes, mitochondria, and chloroplasts in metagenomes and environmental sequencing datasets. Antonie van Leeuwenhoek 100, 471–475. https://doi.org/10.1007/s10482-011-9598-6
• 29:30 – Donhauser, J., Niklaus, P.A., Rousk, J., Larose, C., Frey, B., 2020. Temperatures beyond the community optimum promote the dominance of heat-adapted, fast growing and stress resistant bacteria in alpine soils. Soil Biology and Biochemistry 148, 107873. https://doi.org/10.1016/j.soilbio.2020.107873
• 54:30 – Zhou, Z., Wang, C., Luo, Y., 2020. Meta-analysis of the impacts of global change factors on soil microbial diversity and functionality. Nat Commun 11, 3072. https://doi.org/10.1038/s41467-020-16881-7
• 60:45 – Bahram, M., et al., 2018. Structure and function of the global topsoil microbiome. Nature 320, 1039. https://doi.org/10.1038/s41586-018-0386-6
• 68:15 – Lozano, G.L., et al., 2019. Introducing THOR, a Model Microbiome for Genetic Dissection of Community Behavior. mBio 10. https://doi.org/10.1128/mBio.02846-18
• 70:15 – Bengtsson-Palme, J., 2020. Microbial model communities: To understand complexity, harness the power of simplicity. Computational and Structural Biotechnology Journal 18, 3987–4001. https://doi.org/10.1016/j.csbj.2020.11.043
• 72:00 – Sajjad, W., et al., 2020. Resurrection of inactive microbes and resistome present in the natural frozen world: Reality or myth? Science of The Total Environment 735, 139275. https://doi.org/10.1016/j.scitotenv.2020.139275
• 74:00 – Yashina, S., et al., 2012. Regeneration of whole fertile plants from 30,000-y-old fruit tissue buried in Siberian permafrost. Proceedings of the National Academy of Sciences 109, 4008–4013. https://doi.org/10.1073/pnas.1118386109
• 74:30 – Pikuta, E.V., et al., 2005. Carnobacterium pleistocenium sp. nov., a novel psychrotolerant, facultative anaerobe isolated from permafrost of the Fox Tunnel in Alaska. International Journal of Systematic and Evolutionary Microbiology 55, 473–478. https://doi.org/10.1099/ijs.0.63384-0
• 75:00 – Bidle, K.D., Lee, S., Marchant, D.R., Falkowski, P.G., 2007. Fossil genes and microbes in the oldest ice on Earth. Proceedings of the National Academy of Sciences 104, 13455–13460. https://doi.org/10.1073/pnas.0702196104
• 75:15 – Timofeev, V., et al., 2019. Insights from Bacillus anthracis strains isolated from permafrost in the tundra zone of Russia. PLoS ONE 14, e0209140. https://doi.org/10.1371/journal.pone.0209140
• 83:15 – Bengtsson-Palme, J., Boulund, F., Fick, J., Kristiansson, E., Larsson, D.G.J., 2014. Shotgun metagenomics reveals a wide array of antibiotic resistance genes and mobile elements in a polluted lake in India. Frontiers in microbiology 5, 648. https://doi.org/10.3389/fmicb.2014.00648
• 84:00 – Bengtsson-Palme, J., Larsson, D.G.J., 2015. Antibiotic resistance genes in the environment: prioritizing risks. Nature reviews Microbiology 13, 396. https://doi.org/10.1038/nrmicro3399-c1

The podcast was recorded on February 4, 2021. If you want to reach out to us with comments, suggestions, or other feedback, please send an e-mail to podcast at microbiology dot se or contact @bengtssonpalme via Twitter. The music that can be heard on the pod is composed by Johan Bengtsson-Palme and is taken from the album Cafe Phonocratique.

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We start the new year with a bang, or at least a new paper published. Bioinformatics put our paper (1) describing the software package CAFE online today (although it was accepted late last year). The CAFE package is a combination of Perl and R tools that can analyze data from paired transposon mutant sequencing experiments (2-4), generate fitness coefficients for each gene and condition, and perform appropriate statistical testing on these fitness coefficients. The paper is short, but shows that CAFE performs as good as the best competing tools (5-7) while being superior at controlling for false positives (you’ll have to dig into the supplement to find the data for that though).

Importantly, this is a collaborative effort by basically the entire research group from last spring: me, Haveela, Emil, Anna and our visiting student Adriana. A big thanks to all of you for working on this short but important paper! You can read the full paper here.

References

1. Abramova A, Osińska A, Kunche H, Burman E, Bengtsson-Palme J (2021) CAFE: A software suite for analysis of paired-sample transposon insertion sequencing data. Bioinformatics, advance article doi: 10.1093/bioinformatics/btaa1086
2. Chao,M.C. et al. (2016) The design and analysis of transposon insertion sequencing experiments. Nature reviews Microbiology, 14, 119–128.
3. van Opijnen,T. and Camilli,A. (2013) Transposon insertion sequencing: a new tool for systems-level analysis of microorganisms. Nature reviews Microbiology, 11, 435–442.
4. Goodman,A.L. et al. (2011) Identifying microbial fitness determinants by insertion sequencing using genome-wide transposon mutant libraries. Nature Protocols, 6, 1969–1980.
5. McCoy,K.M. et al. (2017) MAGenTA: a Galaxy implemented tool for complete Tn- Seq analysis and data visualization. Bioinformatics, 33, 2781– 2783.
6. Zhao,L. et al. (2017) TnseqDiff: identification of conditionally essential genes in transposon sequencing studies. BMC Bioinformatics, 18.
7. Zomer,A. et al. (2012) ESSENTIALS: Software for Rapid Analysis of High Throughput Transposon Insertion Sequencing Data. PLoS ONE, 7, e43012.