Tag: Microbial ecology

Last week, we published a paper which has been cooking for a long time. It is the result of years of hard work from particularly the first author – Tove Wikström – but also Sanna who did the bulk of the bioinformatic analysis with some help from me (well, I mostly contributed as a sounding board for ideas, but hopefully that was useful). The paper describes the gene expression of both the human host and the microbial community in the vagina during pregnancy and how the expressed genes (and the composition of bacteria) are linked to early births (1) and was published in Clinical and Translational Medicine.

We found 17 human genes potentially influencing preterm births. Most prominently the kallikrein genes (KLK2 and KLK3) and four different forms of of metallothioneins (MT1s) were higher in the preterm group than among fullterm women. These genes may be involved in inflammatory pathways associated with preterm birth.

We also found 11 bacterial species associated with preterm birth, but most of them had low occurrence and abundance. In contrary to some earlier studies, we saw no differences in bacterial diversity or richness between women who delivered preterm and women who delivered at term. Nor did Lactobacillus crispatus – often proposed to be protective against preterm birth (2,3) – seem to be a protective factor against preterm birth. However, most other studies have used DNA-based approaches to determine the bacterial community composition, while we used a metatranscriptomic approach looking at only expressed genes. In this context it is interesting that other metatranscriptomic results (4) agree with ours in that it was mainly microbes of low occurrence that differed between the preterm and term group.

Overall, the lack of clear differences in the transcriptionally active vaginal microbiome between women with term and preterm pregnancies, suggests that the metatranscriptome has a limited ability to serve as a diagnostic tool for identification of those at high risk for preterm delivery.

Great job Tove and the rest of the team! It was a pleasure working with all of you! The entire paper can be read here.

References

1. Wikström T, Abrahamsson S, Bengtsson-Palme J, Ek CJ, Kuusela P, Rekabdar E, Lindgren P, Wennerholm UB, Jacobsson B, Valentin L, Hagberg H: Microbial and human transcriptome in vaginal fluid at midgestation: association with spontaneous preterm delivery. Clinical and Translational Medicine, 12, 9, e1023 (2022). doi: 10.1002/ctm2.1023 [Paper link]
2. Kindinger LM, Bennett PR, Lee YS, et al.: The interaction between vaginal microbiota, cervical length, and vaginal progesterone treatment for preterm birth risk. Microbiome, 5, 1, 1-14 (2017).
3. Tabatabaei N, Eren AM, Barreiro LB, et al.: Vaginal microbiome in early pregnancy and subsequent risk of spontaneous preterm birth: a case-control study. BJOG, 126, 3, 349-358 (2019).
4. Fettweis JM, Serrano MG, Brooks JP, et al.: The vaginal microbiome and preterm birth. Nature Medicine, 25, 6, 1012-1021 (2019).

Our open doctoral student and postdoc positions closed over the weekend, and in total we had 110 applications, although some persons applied to more than one of the positions, bringing the total number of applicants down a bit. Still, this will be a lot of work for me. I will prioritize the postdoc position, as this had the fewest applications. So if you applied to one of the two PhD student positions, please give it some time.

A quick skimming of the applications shows that we have had extraordinary high quality of applications overall, although some of the applicants will be a bit too wet-lab oriented for these specific positions.

Thanks a lot for your interest in the lab’s work! I appreciate all of your efforts!

As I wrote a few days ago, I have now started my new position at Chalmers SysBio. This position is funded by the SciLifeLab and Wallenberg National Program for Data-Driven Life Science (DDLS), which also funds PhD and postdoc positions. We are now announcing two doctoral student projects and one postdoc project within the DDLS program in my lab.

Common to all projects is that they will the use of large-scale data-driven approaches (including machine learning and (meta)genomic sequence analysis), high-throughput molecular methods and established theories developed for macro-organism ecology to understand biological phenomena. We are for all three positions looking for people with a background in bioinformatics, computational biology or programming. In all three cases, there will be at least some degree of analysis and interpretation of large-scale data from ongoing and future experiments and studies performed by the group and our collaborators. The positions are all part of the SciLifeLab national research school on data-driven life science, which the students and postdoc will be expected to actively participate in.

The postdoc and one of the doctoral students are expected to be involved in a project aiming to uncover interactions between the bacteria in microbiomes that are important for community stability and resilience to being colonized by pathogens. This project also seeks to unearth which environmental and genetic factors that are important determinants of bacterial invasiveness and community stability. The project tasks may include things like predicting genes involved in pathogenicity and other interactions from sequencing data, and performing large-scale screening for such genes in microbiomes.

The second doctoral student is expected to work in a project dealing with understanding and limiting the spread of antibiotic resistance through the environment, identifying genes involved in antibiotic resistance, defining the conditions that select for antibiotic resistance in different settings, and developing approaches for monitoring for antibiotic resistance in the environment. Specifically, the tasks involved in this project may be things like identifying risk environments for AMR, define potential novel antibiotic resistance genes, and building a platform for AMR monitoring data.

For all these three positions, there is some room for adapting the specific tasks of the projects to the background and requests of the recruited persons!

We are very excited to see your applications and to jointly build the next generation of data driven life scientist! Read more about the positions here.

As part of a series highlighting the research at the Institute of Biomedicine, I was a few weeks a go interviewed about the research in the lab and my history. This interview has now been published on the department website, both in Swedish and English. I think it is a pretty nice read and a good introduction to our work and why we do what we do. Could make for a good weekend read!

We are hiring a PhD student to work with interactions between the bacteria in human and environmental microbiomes that are important for community stability and resilience to being colonized by unwanted bacteria (including pathogens). The project seeks to unearth which environmental and genetic factors that are important determinants of bacterial invasiveness and community stability. You can read more at our Open Positions page.

We are looking for a candidate with experience with both bioinformatics and experimental microbiology. Previous experience with microbial communities is a plus, but not a must, as is work with human cell lines.

The project is fully funded by a grant from the Swedish Research Council and the position is planned for 4.5 years, with 4 years of research and course work and half a year of teaching.

If you feel that you are the right person for this position, you can apply here. We look forward to your application! The deadline for applications is October 21.

Last week, a preprint describing a study which I have played a small part in was posted on bioRxiv. This paper (1) uses the Metaxa2 database (2) to tease out how much of an effect mitochondrial rRNA sequences have on studies of bacterial diversity in corals. And it turns out that it matters… a lot. Importantly, by supplementing the taxonomic databases with diverse mitochondrial rRNA sequences from the Metaxa2 database, ~97% of unique unclassified sequences could be resolved as mitochondrial, without increasing the level of misannotation in mock communities. Thus the study not only points to a problem, but also to its solution! You can read it all here.

References

1. Sonnet D, Brown T, Bengtsson-Palme J, Padilla-Gamiño J, Zaneveld JR: The Organelle in the Room: Under-annotated Mitochondrial Reads Bias Coral Microbiome Analysis. bioRxiv, 431501 (2021). doi: 10.1101/2021.02.23.431501 [Link]
2. Bengtsson-Palme J, Hartmann M, Eriksson KM, Pal C, Thorell K, Larsson DGJ, Nilsson RH: Metaxa2: Improved identification and taxonomic classification of small and large subunit rRNA in metagenomic data. Molecular Ecology Resources, 15, 6, 1403–1414 (2015). doi: 10.1111/1755-0998.12399 [Paper link]

I am happy to report that today a preprint on a recent collaboration with Christian Wurzbacher‘s group came out on bioRxiv. In the preprint study, we explore microbial communities in stormwater runoff from roads in terms of microbial composition and the potential for these settings to disseminate and select for antibiotic resistance, as well as metal resistance. My part of this study is quite small; I mostly provided the analysis of resistance genes on integrons, but it was a fun study and I look forward to work more with Christian and his excellent team!

Full reference:

• Ligouri R, Rommel SH, Bengtsson-Palme J, Helmreich B, Wurzbacher C: Microbial retention and resistances in stormwater quality improvement devices treating road runoff. bioRxiv, 426166 (2021). doi: 10.1101/2021.01.12.426166 [Link]

Emil Burman, master student in the lab, defends his master’s thesis today, titled “Biofilms, how cool are they? Effects of temperature and invasion on model microbial communities“. We wish him the best of luck today presenting this excellent work!

We are hiring a PhD student to work with effects of antibiotics on microbial communities! The project will use large-scale techniques to investigate how sub-inhibitory concentrations of antibiotics affect microbial communities. Specifically, the project will examine how the ability for bacteria to colonize and invade established microbial communities is impacted by antibiotics. The project will also explore how antibiotics influence the interactions between different species in bacterial communities and if this may change their ability to withstand invasions. The goal is to identify the genes and mechanisms that contribute to change and stability in microbial communities.

A cool thing about this position is that it is fairly adaptable to the eventual candidate, and the project can be somewhat tailored to suit the profile of the PhD student. This means that we’re looking for someone who is either a bioinformatician or an experimentalist (or both). Previous experience with microbial communities is a plus, but not a must.

If you feel that you are the right person for this position, you can apply here. More information is also available here. We look forward to your application! The deadline for applications is December 9.

I am happy to share the news that the paper describing out software tool Mumame is now out in its final form! (1) The paper got published today in the journal Metabarcoding and Metagenomics after being available as a preprint (2) since last autumn. This version has not changed a whole lot since the preprint, but it is more polished and better argued (thanks to a great review process). The software is virtually the same, but is not also available via Conda.

In the paper, we describe the Mumame software, which can be used to distinguish between wildtype and mutated sequences in shotgun metagenomic sequencing data and quantify their relative abundances. We further demonstrate the utility of the tool by quantifying antibiotic resistance mutations in several publicly available metagenomic data sets (3-6), and find that the tool is useful but that sequencing depth is a key factor to detect rare mutations. Therefore, much larger numbers of sequences may be required for reliable detection of mutations than is needed for most other applications of shotgun metagenomics. Since the preprint was published, Mumame has also found use in our recently published paper on selection for antibiotic resistance in a Croatian macrolide production wastewater treatment plant, unfortunately with inconclusive results (7). Mumame is freely available here.

I again want to stress the fantastic work that Shruthi Magesh did last year as a summer student at WID in the evaluation of this tool. As I have pointed out earlier, I did write the code for the software (with a lot of input from Viktor Jonsson), but Shruthi did the software testing and evaluations. Thanks and congratulations Shruthi, and good luck in pursuing your PhD program!

References

1. Magesh S, Jonsson V, Bengtsson-Palme J: Mumame: A software tool for quantifying gene-specific point-mutations in shotgun metagenomic data. Metabarcoding and Metagenomics, 3: 59–67 (2019). doi: 10.3897/mbmg.3.36236
2. Magesh S, Jonsson V, Bengtsson-Palme J: Quantifying point-mutations in metagenomic data. bioRxiv, 438572 (2018). doi: 10.1101/438572
3. Bengtsson-Palme J, Boulund F, Fick J, Kristiansson E, Larsson DGJ: Shotgun metagenomics reveals a wide array of antibiotic resistance genes and mobile elements in a polluted lake in India. Frontiers in Microbiology, 5, 648 (2014). doi: 10.3389/fmicb.2014.00648
4. Lundström S, Östman M, Bengtsson-Palme J, Rutgersson C, Thoudal M, Sircar T, Blanck H, Eriksson KM, Tysklind M, Flach C-F, Larsson DGJ: Minimal selective concentrations of tetracycline in complex aquatic bacterial biofilms. Science of the Total Environment, 553, 587–595 (2016). doi: 10.1016/j.scitotenv.2016.02.103
5. Pal C, Bengtsson-Palme J, Kristiansson E, Larsson DGJ: The structure and diversity of human, animal and environmental resistomes. Microbiome, 4, 54 (2016). doi: 10.1186/s40168-016-0199-5
6. Kraupner N, Ebmeyer S, Bengtsson-Palme J, Fick J, Kristiansson E, Flach C-F, Larsson DGJ: Selective concentration for ciprofloxacin in Escherichia coli grown in complex aquatic bacterial biofilms. Environment International, 116, 255–268 (2018). doi: 10.1016/j.envint.2018.04.029
7. Bengtsson-Palme J, Milakovic M, Švecová H, Ganjto M, Jonsson V, Grabic R, Udiković Kolić N: Pharmaceutical wastewater treatment plant enriches resistance genes and alter the structure of microbial communities. Water Research, 162, 437-445 (2019). doi: 10.1016/j.watres.2019.06.073