FPbase: The Community-Driven Resource for Fluorescent Proteins

Fluorescent proteins are essential tools in biological research, enabling scientists to visualize and track cellular processes with precision. Choosing the right fluorescent protein requires careful consideration of brightness, photostability, and spectral properties. Given the rapid development of new variants, researchers benefit from centralized resources that compile and compare these options efficiently.

FPbase serves as a community-driven database where users can explore detailed information on fluorescent proteins, their characteristics, and applications. It provides an interactive platform for organizing data, analyzing spectral profiles, and contributing updates.

Major Protein Variants

Fluorescent proteins are categorized by their emission spectra, with green, red, and far-red variants being widely used. Each class has unique properties that determine its suitability for specific imaging applications. FPbase offers a structured comparison of these variants to help researchers select the best option for their experiments.

Green

Green fluorescent proteins (GFPs) are among the most commonly used, with enhanced GFP (EGFP) serving as a benchmark for brightness and stability. Originally derived from Aequorea victoria, GFP has been extensively engineered for improved spectral properties and performance in live-cell imaging. Variants like mNeonGreen, sourced from a lancelet species, offer superior brightness compared to EGFP.

GFP-based proteins are compatible with standard fluorescence microscopy filters, making them widely adopted in research. Their excitation peaks around 488 nm align well with common laser lines used in confocal and flow cytometry applications. However, GFP variants may be susceptible to photobleaching, requiring careful experimental design. Researchers often use GFP for protein localization studies, Förster resonance energy transfer (FRET) assays, and gene expression tracking due to its well-characterized properties.

Red

Red fluorescent proteins (RFPs) are advantageous for deep-tissue imaging due to their longer wavelengths, which reduce scattering and autofluorescence. The first widely adopted RFP, DsRed, was isolated from Discosoma coral but had a tendency to oligomerize, limiting its use in fusion proteins. Engineering efforts led to monomeric variants such as mCherry and mRuby, which perform better in live-cell imaging.

These proteins typically have excitation peaks around 560–590 nm, making them compatible with standard red fluorescence filter sets. mCherry is popular for its photostability and fast maturation, while mRuby variants offer greater brightness for single-molecule tracking and super-resolution microscopy. Despite their benefits, RFPs often have lower quantum yields than GFPs, requiring optimization to maximize signal-to-noise ratios. Researchers frequently use RFPs in multiplexed imaging workflows, combining them with GFPs or far-red proteins to track multiple targets.

Far-Red

Far-red fluorescent proteins extend the emission spectrum beyond 600 nm, minimizing background interference from cellular autofluorescence and improving imaging depth. Engineered from bacterial phytochromes and other natural sources, these proteins include widely used variants such as mKate2 and TagRFP657. Their spectral properties are particularly useful for intravital imaging.

These proteins often have excitation peaks between 600 and 650 nm, aligning with near-infrared laser sources. mKate2 is notable for its high photostability and fast maturation, making it ideal for long-term imaging. However, far-red proteins can be less bright than their green and red counterparts, requiring optimized imaging conditions. They are frequently used in deep-tissue imaging, multicolor fluorescence microscopy, and optogenetic experiments where spectral separation is essential.

Database Organization

FPbase provides an intuitive platform for exploring fluorescent protein data. The database allows users to filter and compare proteins based on attributes such as excitation and emission spectra, quantum yield, maturation time, and photostability. Each protein entry includes a detailed summary of its properties, with references to peer-reviewed publications documenting its development.

A key feature of FPbase is its interactive spectral viewer, which enables users to overlay excitation and emission curves of multiple fluorescent proteins. This helps design multiplexed experiments by minimizing spectral overlap. The database also integrates known filter sets and laser lines, allowing users to match fluorophores with imaging system specifications, streamlining experimental planning.

Beyond individual protein characterization, FPbase tracks fluorophore evolution, linking related variants to illustrate their modifications. This historical perspective helps researchers understand trade-offs introduced by specific mutations. The database also includes mutational data to predict how future modifications may influence fluorophore behavior.

FPbase supports user-generated collections, allowing researchers to curate and share lists of fluorescent proteins tailored to specific experimental needs. These collections can be based on spectral properties, organism compatibility, or imaging techniques. By facilitating the exchange of curated datasets, FPbase fosters collaboration and accelerates best practices in fluorescence microscopy. Additionally, the database includes application notes and user-submitted performance reviews, providing insights into real-world imaging conditions.

Spectral Profiles And Photostability

A fluorescent protein’s effectiveness depends on its spectral properties, which determine how efficiently it absorbs and emits light. Excitation and emission spectra define the wavelengths at which a fluorophore interacts with a light source and releases photons, influencing compatibility with imaging systems. A well-matched fluorophore-laser combination maximizes signal intensity while reducing background noise, which is critical in live-cell imaging and super-resolution microscopy. FPbase provides interactive spectral overlays to help researchers assess these parameters visually.

Brightness, determined by extinction coefficient and quantum yield, affects visualization clarity. A high quantum yield means more absorbed photons are converted into emitted light, enhancing detection. However, photostability is equally important, as fluorescent proteins vary in their resistance to photobleaching, which can lead to irreversible signal loss. This issue is particularly relevant in time-lapse microscopy and single-molecule tracking, where fluorescence must be maintained over multiple imaging cycles.

To reduce photobleaching, researchers use strategies such as minimizing excitation intensity, using antifade reagents, or selecting stable fluorophores. Some proteins, like mNeonGreen and mKate2, exhibit strong resistance to photobleaching, making them ideal for long-duration experiments. Others, including certain red-shifted variants, may require additional stabilization techniques. Environmental factors like pH and oxygen availability also influence photostability, as oxidative damage can accelerate degradation. Understanding these interactions helps optimize imaging conditions to preserve signal integrity.

Community Editing Features

FPbase stands out for its user-driven approach to maintaining and expanding its database. Unlike static repositories, it allows researchers to update protein characteristics, add new variants, and refine existing data. This crowdsourced model ensures the database stays current with the latest advancements in fluorescent protein engineering.

A structured verification process ensures accuracy. While any registered user can propose modifications, changes undergo review by contributors and moderators, who assess accuracy based on experimental data and published literature. This prevents misinformation while maintaining transparency. Users can also leave comments on protein entries, facilitating discussions about performance nuances that may not be immediately evident from numerical metrics.

These insights are particularly valuable for troubleshooting imaging conditions, providing anecdotal evidence on how specific proteins behave in different experimental contexts. By enabling real-time updates and collaborative validation, FPbase reduces the lag between discovery and accessibility, allowing scientists to incorporate new fluorophores into their work more efficiently.