Short term plasticity and E/I balance combine to control Purkinje cell discharge in the cerebellum

Speaker: Philippe Isope
Department:
Neuroscience
Subject: Short term plasticity and E/I balance combine to control Purkinje cell discharge in the cerebellum
Location: Erasmus MC
Date: 03-04-2017
Author: Renée van der Winden

Philippe Isope came to talk to us about his work on some of the workings of the cerebellum. He started with giving us a very brief overview of how the cerebellum works, namely, that it is for motor coordination. He mentioned two mechanisms that were important for the rest of his talk. Those were the fact that the cerebellum can predict the sensory input caused by a voluntary movement and that it adapts its feedback systems through plasticity. One of the questions Isope was concerned with was: ‘Do different tasks of the cerebellum rely on the same processing mechanism?
He then went on to talk about Purkinje cells, which provide the sole output of the cerebellar cortex. The firing of these cells can precede movement, which is linked to the predictive function of the cerebellum. The next topic was the different modules in the cerebellum. It turns out the cerebellum is physiologically heterogeneous and is divided into different modules. The parallel processing this makes possible ensures precision in the cerebellum. Moreover, the communication between the different modules did not seem to be important. This led to a working hypothesis, which said that the individual modules can be coordinated by parallel fibers. However, this raises the question of how they can be precise if the information is spread between them.

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Figure 1: A brief overview of the different ways a Purkinje cell is regulated

In order to test this, Isope and his group first identified the modules they wanted to work with. After that, they mapped granule cell inputs in the Purkinje cells. They found out that activity can quite easily tune these maps, so they are apparently not genetically determined. This shows the cerebellum is capable of plasticity. The conclusion was that the E/I (excitation/inhibition) balance is spatially organized and that that leads to precision. In the end, these two things were put together to show that both short term plasticity and the E/I balance working together to control the discharge of the Purkinje cells.
I thought this talk was quite difficult to follow, in part because of the very thick accent of the speaker. This made it less enjoyable to listen to. However, I am still curious about neuroscience so the topic in itself interested me. However, I am sorry to say that I just did not understand quite enough of it to find it truly interesting.

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Steroid hormone receptor profiling in human cancers: from biomarkers to novel therapeutics

  • Speaker:             Wilbert Zwart
  • Department:     Cell biology
  • Subject:              Steroid hormone receptor profiling in human cancers
  • Location:            Erasmus MC Rotterdam
  • Date:                    30-03-2017
  • Author:               Katja Slangewal

Breast- and prostate cancers are the most frequently diagnosed cancers in women and men respectively (figure 1). They are the second deathliest cancers both behind lung cancer. This makes breast- and prostate cancer an important research topic.

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Figure 1: The most frequently diagnosed cancers in male and females in the UK in 2014. According to Zwart, this graph also beholds for the rest of the world.  http://www.cancerresearchuk.org/health-professional/cancer-statistics/incidence/common-cancers-compared#heading-Zero

Approximately 75% of breast cancers and 100% of prostate cancers are related to hormonal defects. The main hormonal players are estrogen and androgen. These hormones lead to nuclear enriched transcription factors, which will cause the transcription of genes related to cell growth and division (figure 2). Both receptors complementing the estrogen and androgen receptor have a similar structure.

The relation between hormonal function and cancer is not a new concept. This relation has already been described in 1896. The treatments in that time were a little less subtle than nowadays. Cases have been described in which the entire ovary of female patients had been removed. This lead to the reduction of breast cancer, due to the removal of the estrogen source.

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Figure 2: The estrogen receptor pathway. Its stimulation leads eventually to the transcription of multiple genes and the synthesis of proteins important for cell growth and division. https://www.jci.org/articles/view/27987/figure/1

Nowadays more subtle treatments are used. The main treatment consists of tamoxifen, aromatase inhibitors or enzalutamide injections. These substances block the estrogen receptor or the nuclear import of the androgen receptor. The treatment works, but unfortunately not perfectly. This is where the research of Wilbert Zwart and his colleagues comes into play. They are looking for predictive biomarkers, which are able to tell whether the hormonal treatment will have an effect or whether it will be better to start immediately with chemotherapy.

Zwart has performed Chip-seq experiments to identify the DNA binding sites of the estrogen and androgen receptors. This led to the identification of many thousands of binding sites. Only a few of these binding sites were located at a promoter. However, most binding sites were near the start site of transcription. Zwart also found the importance of FoxA1, this protein is necessary for the estrogen/androgen receptor to be functional.

A point of consideration is related to the cell lines used for research. All cell lines are quite old and 90% of the research is done on one single cell line: MC7. This of course does not show the complexity and diversity of cancers. So Zwart decided to perform his research on newly derived tissues from recent patients. He compared the DNA binding sites of the receptors between the new tissue and MC7 cell line. Most of the binding sites did overlap. However, the necessity of FoxA1 in MC7 cell lines did not show as clearly in newly derived tissues. Zwart showed that FoxA1 is mainly present in the primary tumor, but is quite often absent in metastasis. This is an important observation, because the hormonal treatments only work in presence of FoxA1. So, this makes FoxA1 and important biomarker, to check how promising the hormonal treatment is.

Next, Zwart went back to the thousands of DNA binding sites he found. The goal is to identify the sites that matter. Individual binding sites can have a direct causal effect on proliferation. So, it is important to check them individually by making knock-outs and see what happens. The selection of specific binding sites is based on several factors. One example of these factors is whether Crispr-Cas can reach the binding site easily.

Several genes were identified nearby binding sites of the estrogen/androgen receptors. One of them is the gene FEN1. FEN1 is up regulated in breast cancer and it influences the survival after hormonal therapy. The gene is required for hormone induced gene expression, so it forms another good biomarker to test whether hormonal treatments will have an effect. In the future, more biomarkers should be identified and also be used in the clinic.

I thought the seminar was quite interesting. I really notice the difference between now and the beginning of last year, considering how much of a talk I actually understand. I liked the talk mainly because of the content. The presenting could be a bit better. I often had trouble listening, mainly because Wilbert often turned around and talked to the slides instead of to the audience. This decreased the volume a lot. Also, he had a lot of images per slide, which made the images quite small and hard to read. So sometimes the talk was hard to follow, but the main message was interesting. I had for instance no idea that most of the breast cancer research is based on one specific cell line. So I learned some new things.

Information processing in neural and gene regulatory networks

Speaker: Gašper Tkačik
Department:
Bionanoscience
Subject: Information processing in neural and gene regulatory networks
Location: TU Delft
Date: 22-03-2017
Author: Renée van der Winden

Gašper Tkačik came to talk to us about his research on information processing in biological networks. His main goal is to predict what biological networks do from first principles and to quantify their function in this sense. He first gave us a brief introduction into Shannon’s information theory, which quantifies and optimizes information transmission. He also posed the question: ‘How can we recover the input at the end of a process?’. To illustrate his points, Tkačik explained two examples to us.

The first example was about the retina and how it encodes information. Through measuring the information flow into and out of the retina, it was predicted what modification the neurons make on the incoming light. Namely, that they perform center-surround filtering. After this prediction was made, it was confirmed by measurements. So in this case they succeeded in predicting the function of a network from first principles. Continuing with the retina, a different experiment was performed in which the pattern of neurons firing when a movie was shown was examined. Through measurements, the scientists found a probability distribution for these patterns. Looking at this distribution they found out that the neural output actually is not decorrelated, as was previously thought. In fact, each pair of neurons is weakly correlated. Moreover, they succeeded in decoding what movie had been shown by looking at the output information provided by the retina.

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Figure 1: A shortened overview of how the movie was decoded from the retinal code

The second experiment was about how morphogen gradients convey information in early development. The question that was posed was: ‘How much information is stored in the pattern?’. It turned out that the answer is approximately 2 bits per gene. However, four genes store 4.3 bits of information. By finding these numbers, Tkačik formalized an established concept of positional information.

The idea of quantifying what happens in biological networks is very interesting to me. I am interested in how organisms work, but I also really like the certainty that mathematics and physics give you. This is a way to combine the two. The talk was relatively easy to understand, which is always nice. It was also the first seminar in which I recognized concepts that I have learned during my own courses.