New fluorescent probe for microtubule doublets

We all know of the great probes to label mitochondria, nuclei, membranes and more but so far, there were no probes to label the centrioles.

Check out this article by the Pierre Gönczy lab: They engineered CenSpark, a new fluorescent probe that labels microtubule doublets found in centrioles! CenSpark is compatible with live samples and comes in different colours. 😀

Great to study cilia, cell division or immunological synapses, and much more!

Living Architectures

Amazing images of cells and pseudo cells on a miniature pattern replicating the facade of the Musée d’Orsay in Paris! The pattern was used to study the capacity of cells and cytoskeletal component to self-organise.

It was published by Manuel Théry and the CytoMorpho laboratory as a FocalPlane post and displayed as a night-show in Paris.

The conclusions of the experiments are highly inspiring, at the border between Biology, Art, Architecture and Philosophy. 😀

Conclusions

All of these experiments illustrate that it is by constantly breaking down that living systems are able to rebuild themselves by adapting to changes in their surroundings. The bonds between biological components are so fragile that they can be easily broken and rebuilt, which gives living structures great plasticity. This plasticity allows cells to constantly adapt to their environment. Unlike inert materials, in which the strength of the bonds allows them to resist and endure, it is the fragility of these bonds that allows living systems to constantly reinvent themselves. But their plasticity is also their weakness. If the balance between destruction and construction is not perfect, the system cannot hold together and dies quickly.

Cells thus use their internal dynamics to explore every possibility, without goal or intention, simply because it is possible. Anything too unstable will collapse and make way for other attempts. Cells therefore spend their time playing with the limits of their stability. Most of them will die as a result. We are today the product of an evolution paved by the death of trillions upon trillions of cells. These adventurers did not attempt to achieve a specific goal that would have made them more robust or more efficient. They tried everything made possible by their internal dynamics.

Image: Nevena Morel

 

SeeDB-Live: Clearing live samples with BSA

Amazing talk at the ELMI in Coimbra!

Takeshi Imai presented SeeDB-Live, a new clearing technique for live samples. The refractive index is 1.363 and the technique works exceptionally well in loose tissues like brain but allows also 2 times deeper imaging in live organoids. They could even image calcium with multiphoton repeatedly over several months in brain of live mice!

The paper was just published in Nature.

FLASH-PAINT: nm resolution, fast and highly multiplexed!

Just heard this amazing Eurobioimaging talk by Florian Shueder from EFPL. They published FLASH-PAINT, an improved version of DNA-Paint.

FLASH-PAINT combined with fluorogenic probes, eraser oligos and EXCHANGE-PAINT has many advantages over DNA-PAINT:

    • It keeps the very high resolution of just a few nm.
    • It is very fast.
    • It enables imaging with a widefield system instead of in TIRF.
    • It enables high multiplexing (they demonstrate 12 rounds) without needing to wash.

They demonstrate 12-plex imaging with 25nm resolution in just 2h!

 

Reproducibility?

Have you ever heard of the Antibody reproducibility crisis?

Well here is a new chapter in this sad saga and this one is about the possible image manipulation of the Western Blots on the datasheets of commercial antibodies.

There is a strong need for clearer ethical guidelines and more education.

3D imaging symposium

Dear all

An interesting whole-day 3D imaging symposium at Scilife on the 4th of December. Many really inspiring talks! 🙂

Clearing live samples!

A couple of super cool papers about transiently clearing live samples to obtain better images!

On Bioarxiv

In Science

The need to improve microscopy trainings

The LCI facility has just published an article about  ‘Improving light microscopy training routines with evidence-based education’. The article is now available in the Journal of Microscopy. We hope that this article will give useful tips to better design users’ training and improve their learning outcome. 🙂

Here is the abstract:

The low reproducibility of scientific data published in articles has recently become a cause of concern in many scientific fields. Data involving light microscopy is no exception. The low awareness of researchers of the technologies they use in their research has been identified as one of the main causes of the problem. Potential solutions have hinted at the need to improve technological and methodological education within research.

Despite the pivotal role of microscopy core facilities in the education of researchers being well documented, facility staff (FS) often learn their trade on the job, without receiving themselves any structured education about the technology they teach others to use. Additionally, despite endorsing an important role at the highest level of education, most FS never receive any training in pedagogy, the field of research on teaching and learning methods.

In this article, we argue that the low level of awareness that researchers have of microscopy stems from a knowledge gap formed between them and microscopy FS during training routines. On the one hand, FS consider that their teaching task is to explain what is needed to produce reliable data. On the other, despite understanding what is being taught, researchers fail to learn the most challenging aspects of microscopy, those involving their judgement and reasoning. We suggest that the misunderstanding between FS and researchers is due to FS not being educated in pedagogy and thus often confusing understanding and learning.

To bridge this knowledge gap and improve the quality of the microscopy education available to researchers, we propose a paradigm shift where training staff at technological core facilities be acknowledged as full-fledged teachers and offered structured education not only in the technology they teach but also in pedagogy. We then suggest that training routines at facilities be upgraded to follow the principles of the Constructive Alignment pedagogical method. We give an example of how this can be applied to existing microscopy training routines. We also describe a model to define where the responsibility of FS in training researchers begins and ends.

This involves a major structural change where university staff involved in teaching research technologies themselves receive appropriate education. For this to be achieved, we advocate that funding agencies, universities, microscopy and core facility organisations mobilise resources of time and funding. Such changes may involve funding the creation and development of ‘Train-the-trainer’ type of courses and giving incentives for FS to upgrade their technological and pedagogical knowledge, for example by including them in career paths. We believe that this paradigm shift is necessary to improve the level of microscopy education and ultimately the reproducibility of published data.

Cool stuff one can do with the LCI Primo

At the LCI core facility, you can use a machine called Primo to micropattern/print proteins at the bottom of a microscopy dish and enable real time imaging of cell-protein interactions.

Now we learnt that we can even micropattern lipids and antibodies on microscopy dishes to image how cells interact with these molecules! This can be done with any pattern and even in multiwell plates! 🙂

Lipid micropatterning: Here is a cool paper showing how filopodia interact with sourrounding lipids and proteins. They image with Structured Illumination and TIRF, techniques that are also on offer at our facility. 🙂

Antibody micropatterning: A new way to analyse extracellular vesicles with multiplexed detection of proteins and RNAs at single EV resolution.

The power of Deep Neural networks

I am wowed at the images published recently in BioArxiv in the Zero-shot deconvolution networks paper. It will be interesting to see the peer-reviewed paper.

I would be interested in visualizing the amount of errors made by the network. A simple way to do it is to acquire a short time lapse (eg 10 images) of a fixed sample, run it through the network and see which structures are stably identified and which change from frame to frame. 🙂

 

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