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Affecting a quarter million people every year and resulting in more than 180,000 deaths annually, Cryptococcus neoformans is a pathogenic, intracellular yeast and the causative agent of cryptococcosis1,2,3. Hardest hit are HIV-positive patients in poor countries who do not have ready access to antiretroviral therapy, making them acutely susceptible to the illness4,5,6. Data from the CDC indicate that in sub-Saharan Africa, C. neoformans kills more people than tuberculosis annually and more every month than any Ebola outbreak on record1. The most common route of exposure occurs from inhaling desiccated spores that are commonplace in the environment7. Upon entering the lungs, there are several virulence factors that contribute to the success of C. neoformans within infected individuals. The polysaccharide capsule is considered the microbe's primary virulence factor, as acapsular strains are not virulent8.
The cryptococcal capsule is made of up three principle components: glucuronoxylomannan (GXM), galactoxylomannan (GalXM), and mannoproteins (MPs)9. While MPs are a relatively minor cell wall-associated component of the capsule, they are immunogenic and can promote a mostly pro-inflammatory response9,10. In contrast, GXM and GalXM make up the bulk of the capsule (>90% by weight) and have immunosuppressive effects11. In addition to its immunomodulatory effects, the rapid enlargement of the capsule in vivo creates a mechanical barrier to ingestion by host phagocytic cells (i.e., neutrophils and macrophages)12. The C. neoformans capsule and its synthesis are complex, but overall, increased capsule diameter is correlated with increased virulence6,13,14. Given this, it is important for C. neoformans researchers to be able to quickly and accurately quantify capsule measurements.
Both the C. neoformans cell and its polysaccharide capsule are dynamic structures and show changes over time15. The capsule can change in density, size, and assembly in response to changes in the host environment16,17,18. Low iron or nutrient levels, exposure to serum, the human physiological pH, and increased CO2 are known to initiate capsule growth16,18,19,20. Further, researchers have shown structural changes resulting in significant differences in immunoreactivity during an infection, lending an advantage to C. neoformans over its host21,22. This is known because the architecture of the C. neoformans capsule has been analyzed in a variety of ways. Electron microscopy, for example, has revealed that the capsule has a heterogeneous matrix with an inner electron-dense layer underneath an outer, more permeable layer23. Light scattering and the use of optical tweezers have allowed researchers to further elucidate its macromolecular properties24. Analyzing the results from both static and dynamic light scattering measurements, we know that the polysaccharide capsule has a complex branching structure23. Optical tweezers have been used to test the rigidity of the structure as well as evaluate its antibody reactivity24. However, by far the most frequently employed analysis of the C. neoformans capsule is the measurement of its size.
To quantify capsule size, researchers use what should be a simple measurement: the linear diameter of the capsule. Digital microscopes are used to capture images of multiple C. neoformans cells (generally hundreds) stained with either India ink or fluorescent dyes. The size of each cell body and surrounding capsule is measured. The data are compiled, and the average diameter of the capsule is calculated by subtracting the cell body diameter from the whole cell diameter (cell body + capsule). Up until this point, these measurements have been done manually. While generally accurate, this method has drawbacks for researchers. Large data sets can take days or even weeks to analyze by hand. And because these measurements are done manually, subjectivity and human error may affect the result.
Automated computational image analysis has become an indispensable tool for researchers in many areas of molecular cell biology, enabling faster and more reliable analysis of biological images 25,26,27. Precise image analysis techniques are necessary to mine quantitative information from what are often complex and immense data sets. However, some measurements, especially the measurement of C. neoformans capsule, have been difficult to automate. Accurately identifying the interface between the cell wall and capsule, which generally appears as a dark ring when imaged by phase-contrast microscopy, can be troublesome to resolve using a simple threshold. Further, C. neoformans cells in culture tend to clump together and accurate segmentation of the cells is necessary for accurate measurements.
The aim of this project was to (i) illustrate one of the standard protocols for capsule induction in C. neoformans, (ii) compare and contrast India ink and fluorescence staining as they pertain to capsule diameter measurements, (iii) develop simple, computational methods to measure capsule diameter using images of India ink stained cells using an image analysis software, and, (iv) assess the benefits and limitations of measuring capsule diameter manually and using software automation. We find that of the two staining methods, fluorescent labeling of the cell wall and capsule, while more time-consuming, provided the most consistent results between experiments. However, both methods enabled us to successfully distinguish between lab and clinical C. neoformans strains exhibiting different capsule sizes. Further, we were able to automate the measurement of capsule diameter from India ink stained images and found that this was a viable alternative to manual measurement of capsule.