Teaching plan for the course unit
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General information

 

Course unit name: High-Content Screening: Image and Data Analysis of Cellular Populations

Course unit code: 575031

Academic year: 2021-2022

Coordinator: Carles Rentero Alfonso

Department: Faculty of Medicine and Health Sciences

Credits: 3

Single program: S

Estimated learning time

Total number of hours 75

 

Face-to-face and/or online activities

40

	-  Lecture	Face-to-face and online		7
	-  Lecture with practical component	Face-to-face and online		5
	(Flow cytometry in HCS)
	-  Problem-solving class	Face-to-face and online		9
	(Statistical analysis for HCS)
	-  IT-based class	Face-to-face and online		6
	(Image processing and analysis)
	-  Laboratory session	Face-to-face and online		8
	(Laboratory training)
	-  Student presentation and discussion	Face-to-face and online		0
	(Assessment)
	-  Seminar	Face-to-face and online		5
	(Seminars)

Supervised project

15

Independent learning

20

Recommendations

 

Suggested previous readinngs: Boutros M, Heigwer F, Laufer C. "Microscopy-Based High-Content Screening" Cell. 2015 Dec 3;163(6):1314-25. Conway JR, Carragher NO, Timpson P. "Developments in preclinical cancer imaging: innovating the discovery of therapeutics". Nat Rev Cancer. 2014 May;14(5):314-28   Further recommendations It is highly recommended to have previous knowledge of Light Microscopy and Flow Cytometry concepts. To course the optional subject "Fluorescence Microscopy Techniques" (code 569907) is then recommended. Requisites 569907 - Tècniques de Microscòpia de Fluorescència (Recommended)

Competences to be gained during study

 

Basic knowledge on automated microscopy and cytometry to develop high-content screening (HCS) assays. General concepts to stablish workflows for high content microscopy and cytometry-based assays. Knowledge of staining, miniaturization and automation procedures to develop HCS microscopy assays. Knowledge of state-of-the-art techniques in fluorescence microscopy-based and Cytometry HCS assays. Ability to automatically process and analyse images from microscopy-based HCS assays. Ability to analyse flow cytometry data. Ability to handle and analyse statistically data from HCS assays. Knowledge of applicability in preclinical assays.

Learning objectives

Referring to knowledge Overview of microscopy and flow cytometry HCS techniques. Description of screening strategies and experimental working plans in fluorescence microscopy and flow cytometry. Overview of automatized Image Processing and Analysis. Introduction to different processing and analysis software such as FIJI/ImageJ, Imaris and other dedicated HCS software. Overview of cytometry analysis. Introduction to manual sequential gating and computational cytometry tools. Introduction of automatization and batch processing and analysis in HCS. Macro programming in ImageJ. Biostatistical approaches to represent, analyse and interpret obtained data and information.

 

 

Teaching blocks

 

1. High-content Screening in Biomedicine

*  Fundamentals and principles. Steps and Workflow in the design of HCS assays. Miniaturization and labelling. Microscopy methodologies for high-content screening. Microscopy imaging acquisition and automation.

2. Flow cytometry in high-content screenings.

3. Image processing and analysis

*  Image processing and segmentation concepts. Feature extraction. Classification of Phenotypes. Image processing and analysis software (FIJI, ImageJ, Imaris). HCS software (Cell Profiler/Analyst, commercial HCS software packages).

4. Data analysis

*  Basic statistics and plots. The correlation matrix. Heat maps. Selection of features. Classification of phenotypes.

 

 

Teaching methods and general organization

 

Lectures. Teachers will introduce all the theoretical blocks of the subject. It will take place both during the theoretical lectures and the theory-practical lessons. Presentation of experimental cases that will be resolved through a High Content Screening approach.   Laboratory training Practical sessions will include sample processing, labelling, automated image or data acquisition of the experimental cases. This block will be performed at the Microscopy Unit and Biology Unit of the Centres Científics i Tecnològics in the Faculty of Medicine and Health Sciences - Campus Clínic and Bellvitge, respectively.   Image Processing and Analysis Image Processing and Analysis concepts will be introduced through ImageJ/FIJI software. Images from the experimental cases will be processed and analysed. It will be performed at the Faculty of Medicine and Health Sciences - Campus Clínic and Bellvitge.   Statistical analysis Statistical data analysis will be performed at the Faculty of Biology.   Seminars Experts in applications of HCS assays from academia and pharma industry will be invited to explain cases of success.   Demonstrations of Technology Innovation HCS developer and manufacturer companies* will be invited to present their technological innovation in lectures or workshops. (*) Participation of HCS Companies will depend on their availability during Master’s dates.

 

 

Official assessment of learning outcomes

 

Attendance, involvement in proposed activities and acquired abilities will be also evaluated. Examination-based assessment The theoretical and practical acquired knowledge will be evaluated.

Reading and study resources

Consulteu la disponibilitat a CERCABIB

Book

Haney SA (Editor), Bowman D (Editor), Chakravarty A (Editor), Davies A (Associate Editor) and Shamu C (Associate Editor). An Introduction to High Content Screening: Imaging Technology, Assay Development, and Data Analysis in Biology and Drug Discovery. ISBN: 978-0-470-62456-2. December 2014

Article

Boutros M, Heigwer F and Laufer C. (2015) Microscopy-Based High-Content Screening. Cell, 163(6):1314-25.

DOI  

Conway JR, Carragher NO and Timpson P. (2014) Developments in preclinical cancer imaging: innovating the discovery of therapeutics. Nat Rev Cancer. 14(5):314-28.

DOI  

Kraus OZ and Frey BJ (2016) Computer vision for high content screening. Crit Rev Biochem Mol Biol. 51(2):102-9

DOI  

Cossarizza A et al. (2017) Guidelines for the use of flow cytometry and cell sorting in immunological studies Eur. J. Immunol. 47: 1584–1797

DOI