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essay

Freely available online!!!

www.nature.com/articles/srep17084

Here we published a correlative study of bacterial assemblages on naturally-spawned brown trout (Salmo trutta) eggs. During my first year as a PhD student I collected brown trout eggs within a big river system in the canton of Berne. I joined Joachim Guthruf, a passionate brown trout specialist, who monitored natural spawning in the main river Aare and its tributaries. He studied the fish for days in order to see them spawning and mark the burial sites of the eggs. About three weeks later he would go back and dig out the eggs, count them and analyze the spawning success at the different spawning sites. I had the opportunity to join and help him during most his trips. While I helped him with his data acquisition, I also collected eggs at the late-eyed developmental stage for my own studies. I was interested in investigating the spatial pattern of host-associated bacterial communities in brown trout eggs across a rivers system. Recent experiments with salmonid embryos established important principles of microbial colonization, maternal transmission of bacteria, bacterial virulence factors, and host genetic responses to bacterial infections. This progress stands in sharp contrast to what is known about the diversity of host-associated bacteria of fish in their natural environment.

Salmo trutta

For this study we characterized bacteria at nine different locations. Eight locations were within the river Aare system and one location was in Sils/Maria, within a non-connected river system of a different river, the river Inn. Bacterial communities on brown trout eggs differed markedly from the composition of bacteria found in their water environment. However, they were strikingly similar across different habitats and rivers regardless of (i) geographic distance among spawning places (isolation-by-distance) and (ii) host genetic and morphological differentiation. These findings strongly suggest that brown trout have egg-specific microbiomes. In the paper we describe the trout egg-associated microbiomes in detail and report evidence that bacterial diversity increases with water temperature.

I worked a very long time on this manuscript and I learned some very important conceptual points about working with environmental sampling of bacterial communities. First, I think it is extremely important to collect water samples or any kind of environmental samples when characterizing host-associated bacteria in their natural environment. This allows the discrimination of bacteria that are specifically associated with a host and bacteria that seem to be omnipresent in their environment. Second, I find it important to sample blank samples and sequence them. It is an illusion to think that we can work under sterile conditions in the field. So why not capturing all kinds of contaminations that we collect in the course of the study and subtract this from the real samples? We already followed this approach in our Aquatic Sciences paper earlier this year (blog post about it). Recently, Noah Fierer also tweeted about the importance of this approach and I must admit that I was very proud I already have published some articles where we took care of this issue. Third, we were dealing with some pretty low sample sizes for some locations. As we had to find a way to optimize the rather expensive sequencing technique (454 Pyrosequencing, Roche), we ended up pooling all the different sites where brown trout bury their eggs for each spawning location so the comparisons between locations could not be based anymore on variance estimates. Consequently, our data only allowed for (i) correlations of water temperature with bacterial community diversity, (ii) correlations of geographic and host genetic distance among spawning places with phylogenetic distance of bacterial communities, (iii) characterizations of core bacterial communities on all brown trout eggs, and (iv) comparisons of egg samples and water samples with regard to bacterial composition and its putative function. With regard to the comparison between the bacterial communities of the main river Aare with its tributaries we added a bootstrapping approach that is similar to a power analysis. Here we increased the number of samples for the main river Aare and its tributaries sequentially, using simulations, and investigated how many samples would be needed to find a significant difference in bacterial composition given the observed distribution of bacteria in our dataset. With regard to relationships between phylogenetic distance of bacterial communities among spawning places with geographic distance and host genetic distance respectively, we also analyzed the effect of reducing the number of pairwise comparisons on slope estimates and discussed this in the light of low sample sizes.

At this point I would like to thank Joachim for his time in the field with me, his patience and his generosity, sharing all this insider information about the local brown trout populations. I am also grateful to Claus and Luca for letting me follow my own curiosity and helping me a great deal with the writing for this manuscript. Aude, my first Master student at the University of Lausanne helped me a lot with the wet lab work for this manuscript, which was very time consuming and also under time pressure as I was expecting my daughter Linnea at that time. Finally, Frédéric supported me with the statistical analysis after the first revision by two very competent Scientific Reports reviewers. He backed up my statistical approaches and pointed out some weaknesses. I am very happy that this article is out now!

Here is the Link!

I guess I should keep this going and write a little story for everybody about each of my manuscripts that some nice editors decide to accept.

This one here is about gene expression in whitefish embryos. Regarding the blog I wrote about the Aquatic Science paper, this could be interpreted as a continuation, a different perspective of our study system. Here we collected sperm and unfertilized eggs from whitefish that can be found in lake Geneva (Coregonus palaea). We fertilized the eggs in vitro and in a full-factorial breeding design. That means that we took the eggs of 4 females and the sperm of 4 males and then crossed them in all possible combinations. This gave us 16 little Tupperware buckets with freshly fertilized eggs. These we brought to the University where we have climate chambers at a constant temperature of 6.5° Celsius. All eggs were filled into individual wells with 2ml of standardized water. In their little microcosmos they grew and developed into embryos. At the late-eyed developmental stage when the blood circulation system is fully functional, we infected 13 replicates of each family with a nasty bacterial pathogen that can be found across many Swiss lakes and rivers Pseudomonas fluorescens. We also added some nutrients that these bacteria like. As a control we added only the nutrients without the pathogen to another 13 replicates of the same families. We already knew from previous studies that at this stage of development it matters who the father of the embryos was with regard to mortality and performance of the embryos under stress. Since the father only provided sperm and no paternal care, father effects can be interpreted as genetic effects. That means, he contributes genes to the embryos only. Once the embryo is old enough it starts expressing these genes and they have an impact on how it will perform under stress. However, what we did not know yet was which genes might be involved. So my goal for this study was to give these significant genetic effects a name.

Whitefish, an economically important fish species for the gastronomy in Switzerland

my husband waiting for me outside the cold climate chamber

Wells where embryos are raised.

Accordingly two days after treatment, we collected 3 embryos from each family and treatment and extracted all the gene expression products in their whole body, the so-called RNA. These are the gene products in all animals and plants that will be translated into proteins, which make up what we are. With the use of next-generation sequencing, we digitalized all this information. That means, that only messenger RNAs are filtered out, tagged according to which individual they belong to, pooled and then translated into letters. For this process we collaborated with a Swiss company in Geneva Fasteris. Months later, I received a huuuuuge text file that I could then use to satisfy my hunger for learning bioinformatics tools. With the help of a very friendly guy at Fasteris I found most overlapping sequences of text and aligned everything to a collection of longer text segments (contigs). These were then compared to an online reference of gene expression reads. The amount of data we produced was extremely big. Since I was only interested in genes that are differentially expressed between embryos in our treatment and control group, I decided to quantify the reads first and only compare the ones to a reference, that are also different between the two groups. Many of the reads did not result in a match, however, 1096 did and those could be characterized further. They told us which functional pathways are already active at this early stage of fish development and they gave us some insight into what defense mechanisms these embryos already have.

Whitefish embryos at the late-eyed developmental stage

There is some background information to this paper. First, I must admit that I convinced my PhD supervisor to conduct this experiment because I wanted to get the chance to learn more about bioinformatics. I was the one responsible for the experimental treatment, the laboratory analysis of extracting RNA, and the one who did all the bioinformatics and data analyses. It was also the first manuscript that I wrote mostly on my own. It is not a very ground-breaking story. I would call it a lesson.

This project was always a side project during my PhD. We started with the fieldwork in 2010 when I just began my doctoral studies in Lausanne. The lab work was done in the end of 2011. I had serious troubles getting RNA of good quality from these embryos. We did not extract RNA directly but froze the embryos first for a couple of months at -80° Celsius. I would not recommend that to anybody. I was very busy working on different projects, some of them I considered my main projects at that time, and therefore this side project had to wait several times.

From the 16 families I managed to get a rather high amount of good quality RNA from 4 families. I made sure that I would have gene products from the same mother, crossed with 4 different fathers. I would say that this is the heart of this study. We could reduce variation in gene expression due to maternal effects. Different genotypes from the fathers were investigated against a constant background of the same mother. The whitefish external breeding system allowed us to control for host genotypes and contrast environment-induced changes in gene expression. I am discussing this strength of the study in the paper and encourage other scientists to use the same host system of fish with an external breeding system to investigate gene expression due to different treatments. It does not only present a way to reduce variation in expression due to maternal and environmental effects, it also provides the possibility to study gene expression in natural populations and their ecologically-relevant context.

I also would like to add that it was very pleasant to work with Laurent Farinelli at Fasteris. He is one of the founders of the Illumina sequencing methodology and he had the balls to start his own company. Now he is collaborating on many very exciting projects and he delivers high quality data and an exceptional service. I enjoyed my few meetings in Geneva at his company.

To end the story of this paper I have to mention that I finally sent the extracted RNA for sequencing in summer 2012. I received the data during my maternity leave and already started playing with it. In 2013 I managed to assemble all reads. I had to digest quite a bit of theory about partly assembled gene expression reads (transcriptomes) and I learned how to use a high-performance computing system (clusters at the SIB). In 2014 I did the differential gene expression analysis and compared reads of interest to different online reference databanks. Here I could rely on the theory about differential gene expression in lung cancer datasets that I was exposed to during my internship at Novartis. This project would not have been possible without the help of several co-workers at UNIL, such as Oksana Riba, Kate Ridout, Paris Veltsos and my co-author Emily Clark. At this point I would like to thank them again for their help and advice.

At the moment I am supervising a Master student who is applying the same experimental set-up in grayling (Thymallus thymallus). He is looking at sex-specific gene expression of grayling embryos under estrogen stress. In this project we also did all the steps from fieldwork until bioinformatics ourselves. However, he can rely on several collaborators who are specialized in the different aspects of the project and as a Master student he concentrates on only one project at a time. I am very excited to see him advancing so fast.

Table 1: The influence of treatment, maternal, paternal, maternal x paternal effects, and bacterial diversity on brown trout embryo survival.

a = Five main logistic mixed effect models were compared to a reference model (in bold) to test if treatment ‘T’, dam ‘D’, sire ‘S’, and bacterial alpha diversity (phylogenetic distance, for its calculation see Material and methods) on the eggs explain a significant part of the variance in embryo mortality of brown trout. Alpha diversity was measured on the eggs before fertilization ‘A1’ or 14 days after treatment with nutrient broth ‘A2’. Two additional models were fitted to investigate the interaction of treatment with dam and sire effects. These models were fitted using the combined data of all three treatments (controls, nutrient broth at a dilution of 1:1000 and 1:500 in the wells).

b = The effects of the two different bacterial alpha diversity measures, random sire and random dam effects on embryo survival were also investigated within treatments.

While I am waiting for my dropbox to synchronize I will do a little brainstorm about women in science. Recently I discussed with Donny about the ‘glass ceiling’.

What is the “glass ceiling”? – There appear to be two main bottlenecks for women in Science:

1)   Getting permanent positions

2)   Getting awards and invitations

Tasks where we are good at take us away from the final place. We seem to diverge away from the goal. That is mainly because we are good at it, because women say “yes” and are more cooperative than men in general. Also, women are asked more frequently than men. Because there still are fewer women than men it makes sense that women are asked more often, not only because of their gender.

–> We need to reveal these facts and make people in the individual departments aware of it.

Take home message:

A)   TRANSPARENCY

B)   VALIDATE WHAT YOU SAY YES TO

If you have already too many tasks and you are asked to take on more give a positive “no” as answer. Make your own work visible. Suggest another task that you can take over. Set time limits, re-evaluate, and help to find a replacement when the time limit is met. Allow other people to mess tasks up. Do not step in to help. Take over graduate school work. In the end of a PhD you can use “finishing up” as a good excuse not to take another task.

What remains an open question: What is your goal? You need to define your goal before you can evaluate what to say “yes” to. The tasks you need to do to become a full professor differ among universities, even among departments. In the UK, for example, there are criteria what you need to achieve in order to be able to step up.

Generally we evaluate people on their self-promotion. You need to think you are the best before you can get a position. This selects for alpha-males and we lose a lot of good researchers. There should be a place for any kind of character in science, as long as he or she is a brilliant researcher.

General take home messages:

–       ask people to nominate you for awards

–       define your goals

–       find a mentor

–       preferably at another university

–       email to people and start groups

–       be present

–       be seen

–       ask for stuff

–       volunteer at hosting symposia

–       build a network during grad school

–       be your own personality