In 2008 we published the first set of guidelines for standardizing research in autophagy. Since then, research on this topic has continued to accelerate, and many new scientists have entered the field. Our knowledge base and relevant new technologies have also been expanding. Accordingly, it is important to update these guidelines for monitoring autophagy in different organisms. Various reviews have described the range of assays that have been used for this purpose. Nevertheless, there continues to be confusion regarding acceptable methods to measure autophagy, especially in multicellular eukaryotes. A key point that needs to be emphasized is that there is a difference between measurements that monitor the numbers or volume of autophagic elements (e.g., autophagosomes or autolysosomes) at any stage of the autophagic process vs. those that measure flux through the autophagy pathway (i.e., the complete process); thus, a block in macroautophagy that results in autophagosome accumulation needs to be differentiated from stimuli that result in increased autophagic activity, defined as increased autophagy induction coupled with increased delivery to, and degradation within, lysosomes (in most higher eukaryotes and some protists such as Dictyostelium) or the vacuole (in plants and fungi). In other words, it is especially important that investigators new to the field understand that the appearance of more autophagosomes does not necessarily equate with more autophagy. In fact, in many cases, autophagosomes accumulate because of a block in trafficking to lysosomes without a concomitant change in autophagosome biogenesis, whereas an increase in autolysosomes may reflect a reduction in degradative activity. Here, we present a set of guidelines for the selection and interpretation of methods for use by investigators who aim to examine macroautophagy and related processes, as well as for reviewers who need to provide realistic and reasonable critiques of papers that are focused on these processes. These guidelines are not meant to be a formulaic set of rules, because the appropriate assays depend in part on the question being asked and the system being used. In addition, we emphasize that no individual assay is guaranteed to be the most appropriate one in every situation, and we strongly recommend the use of multiple assays to monitor autophagy. In these guidelines, we consider these various methods of assessing autophagy and what information can, or cannot, be obtained from them. Finally, by discussing the merits and limits of particular autophagy assays, we hope to encourage technical innovation in the field

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While a variety of software packages are available for analyzing two-dimensional electrophoresis (2-DE) gel images, no comparisons between these packages have been published, making it difficult for end users to determine which package would best meet their needs. The goal here was to develop a set of tests to quantitatively evaluate and then compare two software packages, Melanie 3.0 and Z3, in three of the fundamental steps involved in 2-DE image analysis: (i) spot detection, (ii) gel matching, and (iii) spot quantitation. To test spot detection capability, automatically detected protein spots were compared to manually counted, "real" protein spots. Spot matching efficiency was determined by comparing distorted (both geometrically and nongeometrically) gel images with undistorted original images, and quantitation tests were performed on artificial gels with spots of varying Gaussian volumes. In spot detection tests, Z3 performed better than Melanie 3.0 and required minimal user intervention to detect approximately 89% of the actual protein spots and relatively few extraneous spots. Results from gel matching tests depended on the type of image distortion used. For geometric distortions, Z3 performed better than Melanie 3.0, matching 99% of the spots, even for extreme distortions. For nongeometrical distortions, both Z3 and Melanie 3.0 required user intervention and performed comparably, matching 95% of the spots. In spot quantitation tests, both Z3 and Melanie 3.0 predicted spot volumes relatively well for spot ratios less than 1:6. For higher ratios, Melanie 3.0 did much better. In summary, results suggest Z3 requires less user intervention than Melanie 3.0, thus simplifying differential comparison of 2-DE gel images. Melanie 3.0, however, offers many more optional tools for image editing, spot detection, data reporting and statistical analysis than Z3. All image files used for these tests and updated information on the software are available on the internet (http://www.umbc.edu/proteome), allowing similar testing of other 2-DE image analysis software packages.