The Pigino Group developed a detailed protocol to obtain super-resolution images of the green alga Chlamydomonas reinhardtii by using conventional optical light microscopes.
The advent of super-resolution imaging techniques coupled with fluorescence microscopy allowed the visualisation of a vast array of biological samples with a resolution higher than that imposed by the light diffraction limit. However, super-resolution microscopes are usually expensive instruments with complicated setups and require experienced personnel for sample preparation and image acquisition. Expansion Microscopy (ExM) has recently been developed to overcome these limitations and uses swellable hydrogels to obtain up to fourfold isotropic expansion of the sample before imaging with a confocal microscope.
Gaia Pigino, Associate Head of the Structural Biology Research Centre at Human Technopole, Nikolai Klena and Giovanni Maltinti, members of the Pigino Group, in collaboration with Paul Guichard and Virginie Hamel at the University of Geneve, developed an ExM-based protocol to visualise the three-dimensional (3D) ultrastructural organisation of Chlamydomonas reinhardtii (Ultrastructure Expansion Microscopy, U-ExM). The protocol is now published in the open-access journal Bio-protocol and made available to the research community.
Chlamydomonas is a single-cell model organism widely used to investigate the molecular mechanisms of cilia and flagella motility. In this protocol, the researchers compare different fixation and staining procedures and provide instructions on how to embed the sample in a hydrogel and acquire images with a confocal microscope as well as how to analyse them.
The Pigino Group has already used this protocol to study the assembly of intraflagellar transport trains (IFT) at the Chlamydomonas ciliary base1, thus showing that this new procedure will be instrumental for researchers to perform super-resolution analysis of target proteins in a native 3D environment without the need for expensive super-resolution microscopes and specific training.
The Human Technopole, ELIXIR Italia, the national node of the European life sciences research infrastructure coordinated by the National Research Council (CNR), and the Centro Cardiologico Monzino, as the Italian coordinating centre, have been selected as the Italian partners of Genome of Europe (GoE), the largest EU-funded genomic project, whose ultimate goal is to make […]
On Friday 13 December, at Palazzo Mezzanotte in Milan, the Human Technopole Foundation’s ‘Integrated Report 2023’ received the Oscar di Bilancio in the social enterprises and non-profit organisations category. The award was presented to President Gianmario Verona, Elena Trovesi, Head of Administration, as well as the project leaders Giovanni Selmi, Head of Finance, and Alessandro […]
An international team of scientists from Human Technopole and the University of Milan has developed and validated an innovative approach to studying human brain development across multiple individuals simultaneously using single organoids—laboratory models that replicate key cellular processes of human neurodevelopment. The research paves the way for in vitro population studies. Additionally, the scientists have developed a novel computational method to more accurately quantify the genetic identity of individual cells profiled from multiple individuals concurrently. The findings have been published in Nature Methods.
Human Technopole researchers have identified adducin-γ (ADD3) as a crucial regulator of glioblastoma cancer stem cell morphology and intercellular bridges between tumour cells. These connections facilitate communication and allow tumour cells to share resources, evade chemotherapy, and survive in challenging conditions. The study has been funded by AIRC and the findings are published in Life Science Alliance.
An international collaborative study led by Human Technopole, Candiolo Cancer Institute IRCCS in Turin, the University of Turin, and the Wellcome Sanger Institute in Cambridge (UK) has identified new factors associated with therapeutic response in colorectal cancer. The research has led to the development of a machine-learning model capable of accurately predicting the effects of cetuximab, a drug in clinical use, on different colorectal tumour subtypes. Funded by the AIRC Foundation, the study paves the way to identifying molecular features that could serve as biomarkers for predicting treatment response in patients with this type of cancer.
Manage Cookie Consent
This website uses technical cookies to provide you with a better browsing experience and, subject to your consent, profiling cookies to offer you information and advertising in line with your preferences. For more details, you can consult our cookie policy by clicking on the link below, or set your preferences by clicking "set preferences". By selecting "accept cookies" you consent to the use of all types of cookies while you can revoke your consent by clicking on "refuse". By deciding to refuse or closing the banner, only the technical cookies necessary for the correct functioning of the site will be activated.
Technical cookies (required)
Always active
The technical storage or access is strictly necessary for the legitimate purpose of enabling the use of a specific service explicitly requested by the subscriber or user, or for the sole purpose of carrying out the transmission of a communication over an electronic communications network.
Preferences
The technical storage or access is necessary for the legitimate purpose of storing preferences that are not requested by the subscriber or user.
Third party cookies for statistics
The technical storage or access that is used exclusively for statistical purposes.The technical storage or access that is used exclusively for anonymous statistical purposes. Without a subpoena, voluntary compliance on the part of your Internet Service Provider, or additional records from a third party, information stored or retrieved for this purpose alone cannot usually be used to identify you.
Third party cookies for profiling
The technical storage or access is required to create user profiles to send advertising, or to track the user on a website or across several websites for similar marketing purposes.