Counting Melanosomes

The TEM-mosaics are acquired to give an overview of the entire epidermis. This allows the investigation of whole cells and avoids double analysis of the same cell in different images, covering adjacent areas. The melanosome distribution is determined per cell by counting melanosomes and melanosome clusters, considering the amount of melanosomes that form the respective clusters, and correlating the numbers to the area of the analyzed cell.

Figure 13: Annotated TEM-mosaic. The mosaic covers the entire epidermis from SC (on top) to basement membrane (bottom). The boundaries of the epidermal layers – St. corneum, upper St. spinosum, lower St.

spinosum and St. basale – are marked in red. The Stratum granulosum (between SC and uSSp) is not analyzed.

Ten cells of each layer are investigated. Melanosome numbers and the area of the respective cell are determined.

Bar: 5 µm

SB

SC

uSSp

lSSp

Materials & Methods

Four layers of the epidermis are distinguished: the Stratum corneum (SC), the Stratum spino-sum which is further divided into an upper (uSSp) and lower (lSSp) part, and the Stratum ba-sale (SB). The Stratum granulosum is not examined due to the high density of the cells, which makes it difficult to distinguish melanosomes and other electron dense material. Figure 13 shows an example of a TEM-mosaic (African skin) demonstrating the location of the bounda-ries of the individual epidermal layers. A minimum of 10 cells per epidermal layer is ana-lyzed.

A melanosome is a melanin-filled organelle. In TEM images, melanosomes appear as black, electron dense particles of roundish or oval shape, 100-200 nm in size. They occur within the keratinocyte either as individual particles (single melanosome) or appear in agglomerations of 2-3, sometimes up to ten or more particles (cluster). Both, single melanosomes and clusters are delimited by a surrounding single membrane.

Figure 14: Definition of single melanosomes and melanosome clusters. Melanosome clusters are defined as two or more melanin particles grouped together within an organelle with a visible surrounding membrane. If only one melanin particle is contained within the organelle, it is referred to as single melanosome. If no membranes are visible because of poor sample preservation, clusters are defined by the size of the individual particles and the distance between them. In addition, the shape of clustered particles matches that of the flanking particles; an example is marked with an asterisk.

siM = single melanosome, C = cluster of melanosomes Bar: 200 nm

siM C

siM siM

C

C

*

Materials & Methods In a first approach, single particles and clusters are each rated as one melanosome. Notwith-standing, the numbers of particles within one cluster are documented for further analysis.

Figure 14 demonstrates the classification of melanosomes. If, due to poor structural preser-vation of the sample, surrounding membranes can not be discerned, other criteria such as size, shape and proximity of the melanin particles are used to define a cluster. The particles within a cluster are usually smaller than individually distributed melanosomes. Furthermore, clus-tered particles show an adjustment in shape to match the adjacent particles, reducing the dis-tance between them (marked with an asterisk). A single membrane is clearly visible sur-rounding the single melanosomes (siM) as well as clusters (C).

A second approach to counting melanosomes rates every melanin particle as one melanosome.

The obtained melanosome numbers are correlated to the area of each analyzed cell and a mean value is calculated for each of the epidermal layers. Both, counting and measurement of cell area are done using the measurement tool of ImageAccess.

VIII.5 Automated Analysis of Melanosome Distribution

To shorten the process of data acquisition, an image analysis tool for the automated identi-fication and counting of melanosomes in TEM-images was developed by FIT, the Fraunhofer Institute for Applied Information Technology in Sankt Augustin, Germany. The analysis tool is based on the FIT-devised software ZETA (Schwarz et al., 2006). This software is trained to identify melanosomes by manually annotating sample images. Melanosomes are labelled by mouse-click. In a second step, structures that resemble melanosomes either in shape, or appear as electron dense as melanosomes, are denoted to prevent false-positive identification.

Two training data sets were generated, one for the identification of melanosomes in the lower epidermal layers (SB to SG) and one to match the image quality of the SC, where the melano-somes are smaller than in the underlying layers.

The results are listed as comma separated values (csv), including information on

- the investigated epidermal layer

- the total number of identified melanosomes per image - the number of isolated melanosomes per image - the number of clusters per image

- the number of particles allocated to a cluster

Materials & Methods

- total area allocated to identified melanosomes per image

- a melanosome ID, corresponding to the annotation of the image

The automated processing also provides an annotated image, showing the detected melano-somes to control the quality of the detection. Isolated melanomelano-somes are denoted in red, melanosome clusters are marked in yellow, with a frame indicating which melanosomes belong to the cluster. Each identified melanosome is labelled with an ID to enable the allo-cation to the particular set of values in the text file. False-positive results can thus be elimi-nated from the text file.

D S KIN P IGMENT C HARACTERIZATION BY L IGHT AND

E LECTRON M ICROSCOPY

A large variety of imaging and staining techniques are available specifically for the analysis of skin pigmentation. However, the investigation and especially the quantification of melano-cytes require different staining methods and microscopic imaging techniques compared to the quantification and evaluation of their product, the melanosomes. This chapter covers the tested staining and ensuing imaging methods and includes an evaluation concerning the usefulness of the individual methods for the respective task of morphological and quantitative investigation.

I Identification of Melanocytes in the Context of Human Epidermis

When examined through a conventional light microscope, melanocytes appear as clear cells, at least after standard chemical fixation. The clear space actually is an artefact of fixation during which cytoplasm collapses around the nucleus (Griffiths, 1993). But as this phenome-non can be observed for all kinds of dendritic cells, it is no suitable criterion for the identifi-cation of melanocytes. Furthermore, it is not desirable to employ artefact-based imaging methods, if melanocytes and their interaction with keratinocytes have to be accurately described. It was therefore necessary to find imaging techniques that enable both, artefact-free identification of melanocytes as well as the description of the surrounding tissue.