Author Archives: tinaenviro

About tinaenviro

Researcher in microbial ecology

New publication: Global and local-scale variation in bacterial community structure of snow from the Swiss and Australian Alps

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The online version of our latest article published in FEMS Microbiology Ecology is now available. Here is the abstract:

Seasonally, snow environments cover up to 50% of the lands surface, yet the microbial diversity and ecosystem functioning within snow, particularly from alpine regions is not well described. This study explores the bacterial diversity in snow using next generation sequencing technology. Our data expands the global inventory of snow microbiomes by focusing on two understudied regions, the Swiss Alps and the Australian Alps. A total biomass similar to cell numbers in polar snow was detected, with 5.2 to 10.5×103 cells mL−1 of snow. We found that microbial community structure of surface snow varied by country and site and along the altitudinal range (alpine and sub-alpine). The bacterial communities present were diverse, spanning 25 distinct phyla, but the six phyla Proteobacteria (Alpha– and Betaproteobacteria), Acidobacteria, Actinobacteria, Bacteroidetes, Cyanobacteria, and Firmicutes, accounted for 72–98% of the total relative abundance. Taxa such as Acidobacteriaceae and Methylocystaceae, associated with cold soils, may be part of the atmospherically sourced snow community, while families like Sphingomonadaceae were detected in every snow sample and are likely part of the common snow biome.

You can access the pdf of the advanced publication here.

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New video publication

A new publication of our experimental method to separate bacterial endospores from sample matrix and bacterial cells has been published in video format. This is the principal method developed during my PhD thesis, which we then applied to lake sediment cores. The video has been published in the “Journal of Visual Experiments”. Check it out! It is a really cool idea to publish complicated experimental procedures in video formats, so that other researchers can reproduce it more easily. If access is restricted send me a mesage and I’ll send you the mp4 file via email.

https://www.jove.com/embed/player?id=53411&t=1&a=1&s=1

New Publication

A new publication from our group is now published online.

Junier T, Hervé V, Wunderlin T, and Junier P (2015). MLgsc: A Maximum-Likelihood General Sequence Classifier. PLOS One DOI: 10.1371/journal.pone.0129384

We present a software package for classifying protein or nucleotide sequences to user-specified sets of reference sequences. The software trains a model using a multiple sequence alignment and a phylogenetic tree, both supplied by the user. The latter is used to guide model construction and as a decision tree to speed up the classification process. The software was evaluated on all the 16S rRNA gene sequences of the reference dataset found in the GreenGenes database. On this dataset, the software was shown to achieve an error rate of around 1% at genus level. Examples of applications based on the nitrogenase subunit NifH gene and a protein-coding gene found in endospore-forming Firmicutes is also presented. The programs in the package have a simple, straightforward command-line interface for the Unix shell, and are free and open-source. The package has minimal dependencies and thus can be easily integrated in command-line based classification pipelines.

Here’s looking at bacteria in the snow

This is a microscopy image of the bacteria from freshly fallen snow. The snow samples were collected on the terrasse of the High Altitude Research Station Jungfraujoch in Switzerland. The bacteria present in the snow were preserved with formaldehyde. The liquid sample was then passed through a filter, which retained the bacterial cells larger than 0.2 micrometers (which are most of the known bacteria). A fluorescent stain (DAPI)  makes the bacterial cells visible under UV light and we can image them using a microscope.

With this method we can not only see that there is a large diversity of shapes of bacteria, but  the number of cells present in 1 ml of melted snow can be estimated. In these samples, the bacterial cell counts average to around a million cells per ml! Isn’t that astounding considering that snow looks so super clean.

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International Conference on Polar and Alpine Microbiology – September 2015

Information is out about the next conference on polar and alpine microbiology, which will be held in České Budějovice, Czech Republic from September 6th to 10th 2015. Registration and abstract submission is until 15th of May 2015. Here is the conference website. This conference brings together scientists from all over the world whos research is focused on cryosphere microbiology. With ever new technologies to study microbes in the environment and continuous support for cryosphere reserach projects, we will surely here about some very exciting research.

Welcome to my world of science in snow microbiology!

Snow environments are found on every continent on earth. In the last decades, alarming changes due to global warming have been recorded both in polar and mountainous snow regions (melting of glaciers, reduced snowfall). Snow ecosystems harbor ecologically interesting organisms highly adapted for life at extremely cold temperatures, with little water and nutrients, and under high radiation and extreme wind conditions. Little is known about the specific organisms that are living in snow and we do not know their ability to adapt to a changing climate. In this research, a detailed inventory of microbial organisms found in snow will be undertaken via gene sequencing approaches and cultivation of bacteria and fungi isolated from snow.