Tag: Anna Abramova

In just a few days, Environment International has published two papers coming out from the EMBARK consortium which are somewhat connected to each other.

The first (or technically the second, but the other order makes more sense when explaining this…) is the first paper involving most of the people who have been working in the EMBARK consortium for an extended period of time. It’s an overview paper titled “Towards monitoring of antimicrobial resistance in the environment: For what reasons, how to implement Itit, and what are the data needs?” (1) and I think the title describes the topic pretty well. Basically, we go through why it would be interesting to monitor for antibiotic resistance in the environments, how that could be implemented and what we would need to know to get there.

The very condensed story is that if one is considering implementing monitoring for environmental resistance, these are a few things that should be considered:

• The purpose of monitoring: What is the motivation? What should be achieved? What type of risk should be assessed? What type of action would monitoring enable?
• Choice of methods: Which methods are economically feasible? Which methods would deliver results within a useful timeframe for taking appropriate actions?
• Targeted environments: In what type of environment would monitoring for a given purpose be worthwhile?
• Intended users: Who would be able to use, implement and act upon this strategy?
• Integration potential: How does this monitoring integrate with other monitoring efforts? How can the resulting data be communicated?

We then dive into the knowledge gaps we are currently facing, and particularly highlight the following areas:

• Establish how different existing methods for monitoring resistance compare to each other
• Extend pathogen-centric databases for resistance genes with latent resistance genes (2)
• Determine the locations and type of environments relevant for resistance monitoring
  To reduce costs, utilizing already existing environmental monitoring should be prioritized, as should locations integrated into operating or planned surveillance programs. More efforts should also be made to identify additional pathways for resistance transmission through the environment.
• Study the environment as a source and transmission route for antibiotic resistance
  Stratify risks associated with resistance genes found in the environment. Define typical levels of antibiotic resistance in different environments (3), and define how these levels change over time.
• Identify settings where the relationship between fecal bacteria and antibiotic resistance is absent
  Usually, these levels follow each other, but the environments where they don’t are important as they deviate from the expected baseline of resistance. This knowledge can aid in identifying situations in which it would be helpful to investigate a microbial community for resistance to specific antibiotics.
• Identify the origins for more antibiotic resistance genes (4)
  This knowledge will be instrumental in preventing the emergence of new forms of resistance in pathogens in the future.

An important outcome of this paper is that we realise that we are still not at a level of understanding where routine monitoring for resistance in the environment can be easily justified or implemented. Still, there is a need for monitoring data in natural environments to even get started, and therefore we support the implementation of national, regional and global of initiatives without having all the scientific answers. The lack of comprehensive understanding should not be an obstacle to starting environmental monitoring for AMR, nor for action against environmental development and spread of AMR.

The second paper is very much related to the first, in that it actually tries to address one of these knowledge gaps: the need for normal background levels of antibiotic resistance in different environments. In this paper, Anna Abramova did an herculean effort collecting (we hope) all qPCR data on antibiotic resistance gene abundances in the environment for the past two decades. All in all, she collected data for more than 1500 samples across 150 studies and integrated these into an analys of what we could consider normal levels of resistance in different environments.

For an ‘average’ resistance gene, we found that the normal relative abundance range was form 10^-5 to 10^-3 copies per bacterial 16S rRNA, or that around one in 1,000 bacteria would carry a given resistance gene. This level varied quite a bit between different resistance genes, however, but not so much between environmental types (except for in human and animal feces, where some resistance genes were clearly more abundant, most prominently tetracycline resistance genes). What was more striking was that there was a clear difference between environments impacted or likely impacted by human activities, as opposed to more pristine environments with little to none human impact. Some resistance genes, such as tetA, tetG, blaTEM and blaCTX-M, showed very marked differences between these impacted and non-impacted environments, making them great markers of human-activity-associated resistance.

Our final recommendations with regards to monitoring include:

• Include the intI1, sul1, blaTEM, blaCTX-M and qnrS genes in environmental monitoring, along with a selection of tetracycline resistance genes, including either tetA or tetG.
• Other potential target genes could be sul3, vanA, tetH, aadA2, floR, ereA and mexF, which are abundant in some environments, but are not often included in qPCR studies of environmental AMR
• If a gene deviates from the expected 10^-5 to 10^-3 interval, this warrants further investigation of the causes.
• Maximum acceptable levels need to be determined not only taking relative abundances of genes into account, but also risks to human health as well as the numbers of bacteria in a given volume of sample into account (5,6) and transmission routes to humans (7)
• The different standards of reporting DNA abundances constituted a complicating factor for this study. Both abundances of resistance genes relative to the 16S rRNA gene and to the sample volume or weight should be reported.
• The absence of clear trends of increases or decreases in resistance gene abundances over time indicates a need for more systematic time series data in a variety of environments.

Our results also highlighted the scarcity of resistance gene data from parts of the world, particularly from Africa and South America, and underscores the need for a concerted effort to quantify typical background levels of resistance in the environment more broadly to enable efficient environmental surveillance schemes akin to those that exist in clinical and veterinary settings.

I encourage anyone with an interesting these topics to at least skim the full papers [Monitoring overview paper here, Normal qPCR resistance abundances here]. These will be great resources and I am very proud of them both. I would really like to thank the entire EMBARK team and our collaborators in CORNELIA, WastPAN and in other organisations. I would also like to thank Anna for her hard work on collecting and analysing the qPCR data for around two years. It has been a long ride, and I think we are both happy, proud and a bit relieved to finally see this paper published!

References

1. Bengtsson-Palme J, Abramova A, Berendonk TU, Coelho LP, Forslund SK, Gschwind R, Heikinheimo A, Jarquin-Diaz VH, Khan AA, Klümper U, Löber U, Nekoro M, Osińska AD, Ugarcina Perovic S, Pitkänen T, Rødland EK, Ruppé E, Wasteson Y, Wester AL, Zahra R: Towards monitoring of antimicrobial resistance in the environment: For what reasons, how to implement it, and what are the data needs? Environment International, 108089 (2023). doi: 10.1016/j.envint.2023.108089
2. Inda-Díaz JS, Lund D, Parras-Moltó M, Johnning A, Bengtsson-Palme J, Kristiansson E: Latent antibiotic resistance genes are abundant, diverse, and mobile in human, animal, and environmental microbiomes. Microbiome, 11, 44 (2023). doi: 10.1186/s40168-023-01479-0
3. Abramova A, Berendonk TU, Bengtsson-Palme J: A global baseline for qPCR-determined antimicrobial resistance gene prevalence across environments. Environment International, 178, 108084 (2023). doi: 10.1016/j.envint.2023.108084
4. Ebmeyer S, Kristiansson E, Larsson DGJ: A framework for identifying the recent origins of mobile antibiotic resistance genes. Communications Biology, 4 (2021). doi:10.1038/s42003-020-01545-5
5. Larsson DGJ, Andremont A, Bengtsson-Palme J, Brandt KK, de Roda Husman AM, Fagerstedt P, Fick J, Flach C-F, Gaze WH, Kuroda M, Kvint K, Laxminarayan R, Manaia CM, Nielsen KM, Ploy M-C, Segovia C, Simonet P, Smalla K, Snape J, Topp E, van Hengel A, Verner-Jeffreys DW, Virta MPJ, Wellington EM, Wernersson A-S: Critical knowledge gaps and research needs related to the environmental dimensions of antibiotic resistance. Environment International, 117, 132–138 (2018). doi: 10.1016/j.envint.2018.04.041
6. Pruden A, Larsson DGJ, Amézquita A, Collignon P, Brandt KK, Graham DW, et al. Management options for reducing the release of antibiotics and antibiotic resistance genes to the environment. Environmental Health Perspectives, 121, 878–885 (2013). doi:10.1289/ehp.1206446
7. Bengtsson-Palme J, Kristiansson E, Larsson DGJ: Environmental factors influencing the development and spread of antibiotic resistance. FEMS Microbiology Reviews, 42, 1, 68–80 (2018). doi: 10.1093/femsre/fux053

In this episode Microbiology Lab Pod, the team (Johan Bengtsson-Palme, Emil Burman, Anna Abramova, Marcus Wenne, Sebastian Wettersten and Mahbuba Lubna Akter, Shumaila Malik, Emilio Rudbeck and Camille Wuyts) discusses the evolution of antibiotic resistance from different perspectives. We also interview Rémi Gschwind about his work on novel antibiotic resistance genes in the EMBARK program.

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

• 7:45 – EMBARK website: http://antimicrobialresistance.eu
• 26:15 – Seemann, T., 2014. Prokka: rapid prokaryotic genome annotation. Bioinformatics 30, 2068–2069. https://doi.org/10.1093/bioinformatics/btu153
• 29:00 – 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
• 29:30 – Ebmeyer, S., Kristiansson, E., Larsson, D.G.J., 2021. A framework for identifying the recent origins of mobile antibiotic resistance genes. Communications Biology 4. https://doi.org/10.1038/s42003-020-01545-5
• 54:15 – Gillings, M.R., Stokes, H.W., 2012. Are humans increasing bacterial evolvability? Trends in Ecology & Evolution 27, 346–352. https://doi.org/10.1016/j.tree.2012.02.006
• 55:15 – Woods, L.C., et al., 2020. Horizontal gene transfer potentiates adaptation by reducing selective constraints on the spread of genetic variation. Proc Natl Acad Sci USA 117, 26868–26875. https://doi.org/10.1073/pnas.2005331117
• 76:15 – Card, K.J., Thomas, M.D., Graves, J.L., Barrick, J.E., Lenski, R.E., 2021. Genomic evolution of antibiotic resistance is contingent on genetic background following a long-term experiment with Escherichia coli. Proc Natl Acad Sci USA 118, e2016886118. https://doi.org/10.1073/pnas.2016886118

The podcast was recorded on March 18, 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.

Podcast: Play in new window | Download

Subscribe: RSS

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.

Podcast: Play in new window | Download

Subscribe: RSS

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.

The fall semester has begun, and with that we have started a new round of recordings of the Microbiology Lab Pod. Our fourth episode was recorded on August 20, and the now-familiar crew (Johan Bengtsson-Palme, Emil Burman, Haveela Kunche and Anna Abramova) has been augmented with two new master students in the lab: Sebastian Wettersten and Mahbuba Lubna Akter. This time, we discuss microbial communities of dead and alive deep-sea hydrothermal vents, look at a model system for pathogenic biofilm formation in the lungs, and check in on why patients with covid-19 commonly lose their sense of smell.

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

• 11:30 – Hou, J., Sievert, S.M., Wang, Y. et al., 2020. Microbial succession during the transition from active to inactive stages of deep-sea hydrothermal vent sulfide chimneys. Microbiome 8, 102. https://doi.org/10.1186/s40168-020-00851-8
• 28:45 – Harrington, N.E., Sweeney, E., Harrison, F., 2020. Building a better biofilm – Formation of in vivo-like biofilm structures by Pseudomonas aeruginosa in a porcine model of cystic fibrosis lung infection. Biofilm 2, 100024. https://doi.org/10.1016/j.bioflm.2020.100024
• 52:30 – Brann, D.H., Tsukahara, T., Weinreb, C., et al., 2020. Non-neuronal expression of SARS-CoV-2 entry genes in the olfactory system suggests mechanisms underlying COVID-19-associated anosmia. Science Advances 6, eabc5801. https://doi.org/10.1126/sciadv.abc5801
• 71:45 – Chen, M., Shen, W., Rowan, N.R., et al., 2020. Elevated ACE2 expression in the olfactory neuroepithelium: implications for anosmia and upper respiratory SARS-CoV-2 entry and replication. European Respiratory Journal 2001948. https://doi.org/10.1183/13993003.01948-2020
• 77:15 – Zhang, X., Wang, J., 2020. Deducing the Dose-response Relation for Coronaviruses from COVID-19, SARS and MERS Meta-analysis Results. medRxiv. https://doi.org/10.1101/2020.06.26.20140624
• 78:30 – Sekine, T., Perez-Potti, A., Rivera-Ballesteros, O., et al., 2020. Robust T cell immunity in convalescent individuals with asymptomatic or mild COVID-19. Cell. https://doi.org/10.1016/j.cell.2020.08.017
• 79:45 – Mateus, J., Grifoni, A., Tarke, A., et al., 2020. Selective and cross-reactive SARS-CoV-2 T cell epitopes in unexposed humans. Science eabd3871. https://doi.org/10.1126/science.abd3871
• 80:30 – Lv, H., Wu, N.C., Tsang, O.T.-Y., et al., 2020. Cross-reactive Antibody Response between SARS-CoV-2 and SARS-CoV Infections. Cell Reports 31, 107725. https://doi.org/10.1016/j.celrep.2020.107725

The podcast was recorded on August 20, 2020. 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.

Podcast: Play in new window | Download

Subscribe: RSS

The fall is here and with it comes the arrival of three new group members. This fall, we are joined by Mahbuba Lubna, Sebastian Wettersten and Marcus Wenne. All three are master students from the University of Gothenburg and they will work on very different things.

Mahbuba will work together with Emil Burman on genes responsible for invasion in microbial communities (primarily THOR), expanding on Emil’s work and testing new and existing candidate genes in a wider diversity of conditions.

Sebastian will work on improving Metaxa2, making its classifications better and also enabling even better automation of database creation. Hopefully this will increase the pace of the Metaxa2 development, which has been stagnating a bit over the last two years.

Marcus, finally, will work together with Anna Abramova on analysing antibiotic resistance in a huge metagenomic dataset previously generated in the lab.

This means that we are now seven people in the lab (so if it weren’t for the covid-associated work from home recommendations, it would start to get crowded…) We welcome our three new members and look forward to an exciting fall!

In the third episode of Microbiology Lab Pod, recorded in June, a crew consisting of Johan Bengtsson-Palme, Emil Burman, Haveela Kunche and Anna Abramova goes into depth with what we knew about the novel coronavirus at the time. We also talk about Emil‘s master thesis, potential alternative antibiotic treatment regimes and the lung microbiome in cystic fibrosis.

Unfortunately, the sound quality of this episode is quite bad at times. We have tried to rescue the audio as best as we can, but it is still a bit annoying. We promise to do better next time!

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

• 18:15 – Lozano, G.L., Bravo, J.I., Garavito Diago, M.F., Park, H.B., Hurley, A., Peterson, S.B., Stabb, E.V., Crawford, J.M., Broderick, N.A., Handelsman, J., 2019. Introducing THOR, a Model Microbiome for Genetic Dissection of Community Behavior. mBio 10. https://doi.org/10.1128/mBio.02846-18
• 25:15 – Ghazizadeh, Z. et al. 2020 Androgen Regulates SARS-CoV-2 Receptor Levels and Is Associated with Severe COVID-19 Symptoms in Men. bioArxiv, https://doi.org/10.1101/2020.05.12.091082
• 34:45 – St. John, A.L., Rathore, A.P.S 2020. Early Insights into Immune Responses during COVID-19. The Journal of Immunology 205, 555-564. https://doi.org/10.4049/jimmunol.2000526
• 49:30 – Worobey, M., Pekar, J., Larsen, B.B., Nelson, M.I., Hill, V., Joy, J.B., Rambaut, A., Suchard, M.A., Wertheim, J.O., Lemey, P., 2020. The emergence of SARS-CoV-2 in Europe and the US. bioRxiv. https://doi.org/10.1101/2020.05.21.109322
• 52:00 – La Rosa, G., Mancini, P., Bonanno Ferraro, G., Veneri, C., Iaconelli, M., Bonadonna, L., Lucentini, L., Suffredini, E., 2020. SARS-CoV-2 has been circulating in northern Italy since December 2019: evidence from environmental monitoring. medRxiv. https://doi.org/10.1101/2020.06.25.20140061
• 52:30 – https://lakartidningen.se/aktuellt/nyheter/2020/06/viruset-kan-ha-funnits-i-dalarna-redan-i-december/
• 53:15 – Deslandes, A., Berti, V., Tandjaoui-Lambotte, Y., Alloui, C., Carbonnelle, E., Zahar, J.R., Brichler, S., Cohen, Y., 2020. SARS-CoV-2 was already spreading in France in late December 2019. International Journal of Antimicrobial Agents 55, 106006. https://doi.org/10.1016/j.ijantimicag.2020.106006
• 54:45 – Li, X., Giorgi, E.E., Marichannegowda, M.H., Foley, B., Xiao, C., Kong, X.-P., Chen, Y., Gnanakaran, S., Korber, B., Gao, F., 2020. Emergence of SARS-CoV-2 through recombination and strong purifying selection. Science Advances eabb9153. https://doi.org/10.1126/sciadv.abb9153
• 56:00 – Lehmann, D., Halbwax, M.L., Makaga, L., Whytock, R., Ndindiwe Malata, L., Bombenda Mouele, W., Momboua, B.R., Koumba Pambo, A.F., White, L.J.T., 2020. Pangolins and bats living together in underground burrows in Lopé National Park, Gabon. African Journal of Ecology 58, 540–542. https://doi.org/10.1111/aje.12759
• 61:15 – Cuthbertson, L., Walker, A.W., Oliver, A.E., Rogers, G.B., Rivett, D.W., Hampton, T.H., Ashare, A., Elborn, J.S., De Soyza, A., Carroll, M.P., Hoffman, L.R., Lanyon, C., Moskowitz, S.M., O’Toole, G.A., Parkhill, J., Planet, P.J., Teneback, C.C., Tunney, M.M., Zuckerman, J.B., Bruce, K.D., van der Gast, C.J., 2020. Lung function and microbiota diversity in cystic fibrosis. Microbiome 8. https://doi.org/10.1186/s40168-020-00810-3
• 70:15 – Hansen, E., Karslake, J., Woods, R.J., Read, A.F., Wood, K.B., 2020. Antibiotics can be used to contain drug-resistant bacteria by maintaining sufficiently large sensitive populations. PLOS Biology 18, e3000713. https://doi.org/10.1371/journal.pbio.3000713

The podcast was recorded on June 23, 2020. 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.

Podcast: Play in new window | Download

Subscribe: RSS

In the second episode of Microbiology Lab Pod, a crew consisting of Johan Bengtsson-Palme, Emil Burman, Haveela Kunche and Anna Abramova discusses how to identify novel resistance genes with our special guest Marlies Böhm. We also talk about bacterial virulence: how do bacteria become virulent, how do virulence relate to competition, how do bacteria evade the immune system and can we attenuate virulence using fatty acids?

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

• 7:15 – Böhm, M.-E., Razavi, M., Flach, C.-F., Larsson, D.G.J., 2020a. A Novel, Integron-Regulated, Class C β-Lactamase. Antibiotics 9, 123. https://doi.org/10.3390/antibiotics9030123
• 7:15 – Böhm, M.-E., Razavi, M., Marathe, N.P., Flach, C.-F., Larsson, D.G.J., 2020b. Discovery of a novel integron-borne aminoglycoside resistance gene present in clinical pathogens by screening environmental bacterial communities. Microbiome 8. https://doi.org/10.1186/s40168-020-00814-z
• 9:15 – Makowska, N., et al., 2020. Occurrence of integrons and antibiotic resistance genes in cryoconite and ice of Svalbard, Greenland, and the Caucasus glaciers. Science of The Total Environment 716, 137022. https://doi.org/10.1016/j.scitotenv.2020.137022
• 20:45 – Marathe, N.P., et al., 2019. Scandinavium goeteborgense gen. nov., sp. nov., a New Member of the Family Enterobacteriaceae Isolated From a Wound Infection, Carries a Novel Quinolone Resistance Gene Variant. Frontiers in Microbiology 10. https://doi.org/10.3389/fmicb.2019.02511
• 33:45 – Kaito, C., Yoshikai, H., Wakamatsu, A., Miyashita, A., Matsumoto, Y., Fujiyuki, T., Kato, M., Ogura, Y., Hayashi, T., Isogai, T., Sekimizu, K., 2020. Non-pathogenic Escherichia coli acquires virulence by mutating a growth-essential LPS transporter. PLOS Pathogens 16, e1008469. https://doi.org/10.1371/journal.ppat.1008469
• 43:45 – Lories, B., Roberfroid, S., Dieltjens, L., De Coster, D., Foster, K.R., Steenackers, H.P., 2020. Biofilm Bacteria Use Stress Responses to Detect and Respond to Competitors. Current Biology 30, 1231-1244.e4. https://doi.org/10.1016/j.cub.2020.01.065
• 45:45 – Lozano, G.L., Bravo, J.I., Garavito Diago, M.F., Park, H.B., Hurley, A., Peterson, S.B., Stabb, E.V., Crawford, J.M., Broderick, N.A., Handelsman, J., 2019. Introducing THOR, a Model Microbiome for Genetic Dissection of Community Behavior. mBio 10. https://doi.org/10.1128/mBio.02846-18
• 55:45 – Kumar, P., Lee, J.-H., Beyenal, H., Lee, J., 2020. Fatty Acids as Antibiofilm and Antivirulence Agents. Trends in Microbiology. https://doi.org/10.1016/j.tim.2020.03.014
• 60:15 – Gullberg, E., Cao, S., Berg, O.G., Ilbäck, C., Sandegren, L., Hughes, D., Andersson, D.I., 2011. Selection of resistant bacteria at very low antibiotic concentrations. PLoS Pathogens 7, e1002158. https://doi.org/10.1371/journal.ppat.1002158
• 61:15 – Larsson, D.G.J., 2018. Risks of using the natural defence of commensal bacteria as antibiotics call for research and regulation. International Journal of Antimicrobial Agents 51, 277–278. https://doi.org/10.1016/j.ijantimicag.2017.12.018
• 65:15 – Lone, A.G., Bankhead, T., 2020. The Borrelia burgdorferi VlsE Lipoprotein Prevents Antibody Binding to an Arthritis-Related Surface Antigen. Cell Reports 30, 3663-3670.e5. https://doi.org/10.1016/j.celrep.2020.02.081

The podcast was recorded on May 7, 2020. 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.

Podcast: Play in new window | Download

Subscribe: RSS

In the very first episode of the Bengtsson-Palme lab podcast, a crew consisting of Johan Bengtsson-Palme, Emil Burman, Haveela Kunche and Anna Abramova discusses the origin of the novel coronavirus, interactions between influenza and the respiratory tract microbiome, resistant bacteria in glaciers, pathway analysis methods, a new genus of bacteria discovered in Gothenburg, as well as life in research during a global pandemic.

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

• 10:15 – Andersen, K.G., Rambaut, A., Lipkin, W.I., Holmes, E.C., Garry, R.F., 2020. The proximal origin of SARS-CoV-2. Nature Medicine 26, 450–452. https://doi.org/10.1038/s41591-020-0820-9
• 17:30 – Zhou, P., et al., 2020. A pneumonia outbreak associated with a new coronavirus of probable bat origin. Nature 579, 270–273. https://doi.org/10.1038/s41586-020-2012-7
• 19:30 – https://www.fli.de/en/press/press-releases/press-singleview/novel-coronavirus-sars-cov-2-fruit-bats-and-ferrets-are-susceptible-pigs-and-chickens-are-not/
• 20:45 – Kadioglu, O., Saeed, M., Greten, H.J., Efferth, T, 2020. Identification of novel compound against three targets of SARS CoV-2 coronavirus by combined virtual screening and supervised machine learning. Bulletin of the World Health Organization. https://doi.org/10.2471/BLT.20.255943
• 21:45 – Cheng, V.C.C., Lau, S.K.P., Woo, P.C.Y., Yuen, K.Y., 2007. Severe Acute Respiratory Syndrome Coronavirus as an Agent of Emerging and Reemerging Infection. Clinical Microbiology Reviews 20, 660–694. https://doi.org/10.1128/CMR.00023-07
• 22:15 – Fan, Y., Zhao, K., Shi, Z.-L., Zhou, P., 2019. Bat Coronaviruses in China. Viruses 11, 210. https://doi.org/10.3390/v11030210
• 29:15 – Zhang, L., et al., 2020. Characterization of antibiotic resistance and host-microbiome interactions in the human upper respiratory tract during influenza infection. Microbiome 8. https://doi.org/10.1186/s40168-020-00803-2
• 39:15 – Makowska, N., et al., 2020. Occurrence of integrons and antibiotic resistance genes in cryoconite and ice of Svalbard, Greenland, and the Caucasus glaciers. Science of The Total Environment 716, 137022. https://doi.org/10.1016/j.scitotenv.2020.137022
• 49:45 – 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
• 58:45 – Gillings, M.R., 2014. Integrons: past, present, and future. Microbiology and molecular biology reviews : MMBR 78, 257–277. https://doi.org/10.1128/MMBR.00056-13
• 60:45 – Moradi, E., Marttinen, M., Häkkinen, T., Hiltunen, M., Nykter, M., 2019. Supervised pathway analysis of blood gene expression profiles in Alzheimer’s disease. Neurobiology of Aging 84, 98–108. https://doi.org/10.1016/j.neurobiolaging.2019.07.004
• 62:15 – Johnson, W.E., Li, C., Rabinovic, A., 2007. Adjusting batch effects in microarray expression data using empirical Bayes methods. Biostatistics 8, 118–127. https://doi.org/10.1093/biostatistics/kxj037
• 72:15 – Marathe, N.P., et al., 2019. Scandinavium goeteborgense gen. nov., sp. nov., a New Member of the Family Enterobacteriaceae Isolated From a Wound Infection, Carries a Novel Quinolone Resistance Gene Variant. Frontiers in Microbiology 10. https://doi.org/10.3389/fmicb.2019.02511
• 76:00 – Boulund, F., et al., 2017. Computational discovery and functional validation of novel fluoroquinolone resistance genes in public metagenomic data sets. BMC Genomics 18, 438. https://doi.org/10.1186/s12864-017-4064-0

The podcast was recorded on April 9, 2020. 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.

Podcast: Play in new window | Download

Subscribe: RSS