Ellen C. Jensen

Quantitative analysis of histological staining and fluorescence using ImageJ.

An important objective for scientists is to statistically compare staining intensity (Fig. 1) or fluorescence (Fig. 2) for a particular marker between treatments or groups. Simply “eyeballing” an image and stating that a particular treatment or group is more densely stained or brightly fluorescent than another treatment or group is insufficient for scientific publications. Systems are available for image analysis in immunohistochemistry. However, many of these systems require expensive software and hardware attachments for acquisition, analysis, and storage of images. Therefore, an inexpensive and reliable alternative for image analysis is desirable. The cost effective answer for quantitative immunohistochemical analysis is ImageJ, developed by Wayne Rasband (http://imagej.nih.gov/ij/docs/index. html). ImageJ is a Java image processing and analysis program based on NIH Image for the Macintosh. ImageJ is available in the public domain (i.e., free). ImageJ runs on any computer that is a Java 1.5 or later virtual machine. Java runtime environments are available for free from Sun Microsystems or bundled with platform-specific installations of ImageJ (rsb.info.nih.gov/ij). Downloadable copies are available for Windows, Linux, and Mac OSX. For the evaluation of immunohistochemistry slides using ImageJ, images are captured onto the hard drive of the workstation computer. Thereafter, captured images are opened in NIH Image/ ImageJ for evaluating indices of positivity on immunohistochemistry slides, as well as fluorescence images.

Use of Fluorescent Probes: Their Effect on Cell Biology and Limitations

Fluorescent molecules, known as fluorophores, respond distinctly to light. Each fluorophore has distinct characteristics, which can be used to determine which fluorophore to use for a given application or experimental system. Some proteins or small molecules in cells are naturally fluorescent; this is called intrinsic fluorescence or autofluorescence [e.g., green fluorescent protein (GFP)]. Proteins, nucleic acids, lipids, or small molecules can be labeled with an extrinsic fluorophore—a fluorescent dye—which can be a small molecule, a protein or a quantum dot (Fig. 1). This article discusses pitfalls and problems with a variety of fluorescent compounds that are currently used.

The Basics of Western Blotting

The western (note that in this context ‘‘western’’ should be spelt with a lower-case ‘‘w’’) blot is commonly used to identify, quantify, and determine the size of specific proteins. Western blotting evolved from Southern blotting, which is used to detect specific DNA sequences among DNA fragments separated by gel electrophoresis, and northern blotting, which is used to detect and quantify RNA and to determine its size, and also involves gel electrophoresis to separate RNA. In the late 1970s, Towbin et al. (1979) enabled proteins to be electrophoretically separated using polyacrylamide–urea gels and transferred onto a nitrocellulose membrane. Burnette (1981) later employed the more widely used sodium dodecyl sulfate-polyacrylamide gels (SDS-PAGE), which eventually led to this method being termed western blotting. It is also called protein blotting or immunoblotting and has rapidly become a powerful tool for studying proteins. Basically, gel electrophoresis is used to separate native or denatured proteins. The proteins are then transferred to a membrane for detection using antibodies specific to the target protein. The technique has continued to evolve, and there are many reports on troubleshooting and improving the technique (Kurien and Scofield, 2009).

Technical Review: In Situ Hybridization

In situ hybridization is a technique that is used to detect nucleotide sequences in cells, tissue sections, and even whole tissue. This method is based on the complementary binding of a nucleotide probe to a specific target sequence of DNA or RNA. These probes can be labeled with either radio‐, fluorescent‐, or antigen‐labeled bases. Depending on the probe used, autoradiography, fluorescence microscopy, or immunohistochemistry, respectively, are used for visualization. In situ hybridization is extensively used in research, as well as clinical applications, especially for diagnostic purposes. This review discusses the basic technique of in situ hybridization. The standard in situ hybridization process is reviewed, and different types of in situ hybridization, their applications, and advantages and disadvantages are discussed. Anat Rec, 297:1349–1353, 2014.

Overview of live-cell imaging: requirements and methods used.

Live-cell imaging is an important analytical tool in laboratories studying biomedical research disciplines, such as cell biology, neurobiology, pharmacology, and developmental biology. Imaging of fixed cells and tissues (for which photobleaching is the major issue) usually requires a high illumination intensity and long exposure time; however, these must be avoided when imaging living cells. Live-cell microscopy usually involves a compromise between obtaining image quality and maintaining healthy cells. Therefore, to avoid a high illumination intensity and long exposure time, spatial and temporal resolutions are often limited in an experiment. Imaging live cells involves a wide range of contrast-enhanced imaging methods for optical microscopy. Most investigations use one of the many types of fluorescence microscopy, and this is often combined with transmitted light techniques, which will be discussed below. Continual advances in imaging techniques and design of fluorescent probes improve the power of this approach, ensuring that live-cell imaging will continue to be an important tool in biology.

Types of Imaging, Part 2: An Overview of Fluorescence Microscopy

Fluorescence optical microscopy is a powerful imaging tool in biology used to collect spatial and functional information about both endogenous autofluorescent and exogenously labeled molecules and structures. Fluorescent molecules enable researchers to obtain spatial and functional information. The two main sources of light are mercury vapor or xenon arc lamps with an excitation filter, or lasers. In the fluorescence microscope, the highenergy light irradiates and excites fluorophores in the specimen. The excited fluorophore then emits lower energy fluorescent light. Filters separate the lower energy emitted light, which is seen by the eye or other detector. Fluorescence microscopy is the only type of microscopy where the specimen emits its own light (Davidson and Abramowitz, 1999) (http://www. microscopyu.com/).

Types of imaging, Part 1: Electron microscopy.

This article is the first in a series of articles that are intended to provide a brief overview of the types of microscopy currently used in the biological sciences. The high-resolution electron microscope is a powerful tool for analyzing molecular structure, interactions, and processes. This article will discuss the types, characteristics, and practical application of electron microscopy. Electrons differ fromX-rays and neutrons by their ability to form images and small probes. An electron microscope uses electrostatic and electromagnetic lenses to control an electron beam and focus it to form an image. There is a wide range of different methods in electron microscopy that use the various signals arising from the interaction of the electron beam with the sample to obtain information regarding structure, morphology, and composition.

Real‐Time Reverse Transcription Polymerase Chain Reaction to Measure mRNA: Use, Limitations, and Presentation of Results

Quantitative polymerase chain reaction (PCR) was originally developed for DNA quantitation. There are various applications for quantitative PCR, and it is now increasingly used for measurement of messenger RNA (mRNA) levels (VanGuilder et al., 2008). Quantitative PCR became well known with the introduction of real-time quantitative PCR methods. The focus of this article is the use of quantitative realtime reverse transcription PCR for the measurement of mRNA.

Technical Review: Types of Imaging—Direct STORM

In the 1990s, new concepts of microscopy revolutionized the imaging field by breaking the lateral resolution diffraction limit for the first time, even with propagating light and regular lenses (i.e., far‐field). In 2006, several research groups independently showed super‐resolution microscopy using high‐precision localization of single fluorophores. These new developments in single‐molecule spectroscopy enabled a different approach to achieving nanometer‐scale optical microscopy. Direct stochastic optical reconstruction microscopy (dSTORM) is a technique of single‐molecule super‐resolution imaging that does not require an activator fluorophore. This technique is used to visualize cellular structures with a resolution of approximately 20 nm. dSTORM is compatible with many conventionally used fluorophores. This article provides an overview of the principles and uses of dSTORM. Advantages and disadvantages of dSTORM are also discussed. Anat Rec, 297:2227–2231, 2014.

Technical review: colocalization of antibodies using confocal microscopy.

Imaging of fluorescent signals is often performed for investigating localization of proteins, organelles, ions, and cells. Whether two molecules of interest are located in the same area, (i.e., colocalization) is an issue faced by researchers. Conventional colocalization is where two or more antigens are viewed in the same section by secondary antibodies labeled with fluorescent compounds. Conventional colocalization only shows the coexistence of molecules without any quantification. This method does not examine whether the intensity of staining for two or more molecules varies in synchrony, which would be expected if they were part of the same complex. Various methods have been developed to solve these issues and are discussed in this article. This article discusses techniques and issues of colocalization associated with confocal microscopy. In particular, the article discusses methods used for quantification of colocalization, such as intensity correlation analysis, an automated method based on spatial statistics, and fuzzy system models. Anat Rec, 297:183–187, 2014. VC 2013 Wiley Periodicals, Inc.