science

GFP-cDNA

GFP-cDNA is a science topic covered in the lgStudy science library. This page brings together a partial reference excerpt, illustrations, worked examples, real-world applications and a short study plan, so you can understand GFP-cDNA rather than just read about it. In short: The GFP-cDNA project documents the localisation of proteins to subcellular compartments of the eukaryotic cell applying fluorescence microscopy. Experimental data are complemented with bioinformatic analyses and published online in a database.

Key takeaways

GFP-cDNA belongs to science; place it in that map before memorising details.
Learn the definition first, then one example that makes the definition concrete.
Connect GFP-cDNA to a quantity you can measure, compute or draw — that is where exam questions come from.
Reproduce the core statement of GFP-cDNA from memory before moving on to harder problems.

Reference excerpt

The GFP-cDNA project documents the localisation of proteins to subcellular compartments of the eukaryotic cell applying fluorescence microscopy. Experimental data are complemented with bioinformatic analyses and published online in a database. A search function allows the finding of proteins containing features or motifs of particular interest. The project is a collaboration of the research groups of Rainer Pepperkok Archived 2007-07-22 at the Wayback Machine at the European Molecular Biology Laboratory (EMBL) and Stefan Wiemann at the German Cancer Research Centre (DKFZ).

What kinds of experiments are made? The cDNAs of novel identified Open Reading Frames(ORF) are tagged with Green Fluorescent Protein (GFP) and expressed in eukaryotic cells. Subsequently, the subcellular localisation of the fusion proteins is recorded by fluorescence microscopy. Steps:

1. Large-scale cloning Any large-scale manipulation of ORFs requires cloning technologies which are free of restriction enzymes. In this respect those that utilise recombination cloning (Gateway of Invitrogen or Creator of BD Biosciences) have proved to be the most suitable. This cloning technology is based on recombination mechanisms used by phages to integrate their DNA into the host genome. It allows the ORFs to be rapidly and conveniently shuttled between functionally useful vectors without the need for conventional restriction cloning. In the cDNA-GFP project the ORFs are transferred into CFP/YFP expression vectors. For the localisation analysis both N- and C-terminal fusions are generated. This maximises the possibility of correctly ascertaining the localisation, since the presence of GFP may mask targeting signals that may be present at one end of the native protein.

N-Terminal Fluorescent Fusions Insert your gene of interest into the MCS upstream of the fluorescent protein gene, and express your gene as a fusion to the N-terminus of the fluorescent protein.

C-Terminal Fluorescent Fusions Insert your gene of interest into the MCS downstream of the fluorescent protein gene, and express your gene as a fusion to the C-terminus of the fluorescent protein.

2. Transfection of eukaryotic cells, Expression The fusion vectors are transfected in Vero cells (monkey kidney fibroblasts). Particularly interesting ORFs are also screened for localisation in PC12 cells and hippocampal neurons.

3. Protein localisation At different time points, the subcellular localisation of the fusion proteins is recorded via fluorescence microscopy. At the end of the live cell imaging, the cells can still be fixed and colocalisation experiments made.

4. Bioinformatic Analysis As the sequence of the cDNAs is known, bioinformatics can make predictions regarding the localisation and function of the encoded protein. The bioinformatics analysis is facilitated by the bioinformatic search engine Harvester.

5. Assignment of subcellular localization category Results from the N- and C-terminal fusions are assessed and in turn these data are compared to the bioinformatic predictions. A final subcellular localisation (from approximately 20 categories) is then assigned for each ORF. Similar localisations with both N- and C-terminal constructs provide a higher degree of reliability of the result. For those ORFs where the two fusions do not give a similar localisation pattern, a series of other criteria, including bioinformatic predictions, are considered. Occasionally a clear cut localization cannot be assigned.

Which data is published? Every data sheet contains the fluorescence images of both N- and C-terminal fusions, the assigned localization, other localizations, comments and the Swissprot ID. For every protein entry, a link is provided to the corresponding Harvester bioinformatics page.

How do I use the GFP-cDNA database? Images of all localised proteins and their bioinformatic analysis can be viewed via the ‘Results Table’ or ‘Results Images’ buttons. In addition, use the search window on the entry site to find proteins containing features or motifs of particular interest to you that have been localised in this project.

External links GFP-cDNA database FAQ Harvester bioinformatic search engine

Sources Homepage of the GFP-cDNA project

Illustrations

Worked examples

Example 1 — a first encounter with GFP-cDNA

Start with the simplest possible case. Write down what GFP-cDNA claims or describes in one sentence, then invent the smallest concrete situation in which that sentence is true. In science, the smallest case is usually a single object, a single equation or a single measurement. Check that every symbol or term in your sentence has a meaning in that case.

Example 2 — changing one variable

Take the situation from Example 1 and change exactly one quantity: double it, halve it, or set it to zero. Predict what should happen to GFP-cDNA before you calculate. Comparing your prediction with the result is the fastest way to find out whether you understand the idea or only the words.

Example 3 — an exam-style question

Typical questions about GFP-cDNA ask you to (a) state it precisely, (b) apply it to given data, and (c) explain a limitation. Practise writing all three answers in under five minutes; the third part is what separates a full-mark answer from an average one.

Applications of GFP-cDNA

In research: GFP-cDNA appears in science research whenever the underlying quantities have to be modelled precisely. Papers usually cite it as a starting assumption and then explore where it breaks down.
In technology and industry: Engineering practice reuses GFP-cDNA in design rules, simulations and safety margins. Knowing the idea lets you read a specification sheet and understand why the numbers look the way they do.
In the classroom: GFP-cDNA is common in secondary-school and first-year university syllabi. It links to neighbouring topics Bioinformatics, so understanding it makes those chapters shorter.
In everyday life: Look for GFP-cDNA outside the textbook — in sport, cooking, traffic, electronics or the sky above you. An example you found yourself is remembered far longer than one you were given.

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How to study GFP-cDNA in 20 minutes

Read the reference excerpt below once, without taking notes.
Close the page and write down what GFP-cDNA means in your own words.
Compare your version with the excerpt and mark what you missed.
Work through the three examples above with pen and paper.
Explain GFP-cDNA out loud to somebody else — or to Teacher Smith in the lgStudy chat.

Frequently asked questions

What is GFP-cDNA in simple terms?

Why does GFP-cDNA matter?

Because it connects several science ideas at once: it gives you a definition you can apply, a quantity you can calculate, and a way to check whether a result is plausible.

How should I study GFP-cDNA?

Read the excerpt, restate it from memory, then work through the examples and applications listed on this page. The five-step study plan above takes about twenty minutes.

What does this page cover?

It gives you a compact reference excerpt plus original lgStudy explanations, examples, applications and study material on GFP-cDNA.