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Various intracellular degradation organelles, including autophagosomes, lysosomes, and endosomes, work in tandem to perform autophagy, which is crucial for cellular homeostasis. Altered autophagy contributes to the pathophysiology of various diseases, including cancers and metabolic diseases. This paper aims to describe an approach to reproducibly identify and distinguish subcellular structures involved in macroautophagy. Methods are provided that help avoid common pitfalls. How to distinguish between lysosomes, lipid droplets, autolysosomes, autophagosomes, and inclusion bodies are also discussed. These methods use transmission electron microscopy (TEM), which is able to generate nanometer-scale micrographs of cellular degradation components in a fixed sample. Serial block face-scanning electron microscopy is also used to visualize the 3D morphology of degradation machinery using the Amira software. In addition to TEM and 3D reconstruction, other imaging techniques are discussed, such as immunofluorescence and immunogold labeling, which can be used to classify cellular organelles, reliably and accurately. Results show how these methods may be used to accurately quantify cellular degradation machinery under various conditions, such as treatment with the endoplasmic reticulum stressor thapsigargin or ablation of the dynamin-related protein 1. 

Persons Excluded from science because of Ethnicity and Race (PEERs) face chronic exposure to interpersonal stressors, such as social discrimination, throughout their scientific careers, leading to a long-term decline in physical and mental health. Many PEERs exhibit John Henryism, a coping mechanism to prolonged stress where an individual expends higher levels of effort and energy at the cost of their physical and mental health. In this article, we discuss how social dominance may increase John Henryism within the STEM community; the causes, effects and costs of John Henryism; and highlight solutions to combat these social adversity stressors within the academic institution. 

High-resolution 3D images of organelles are of paramount importance in cellular biology. Although light microscopy and transmission electron microscopy (TEM) have provided the standard for imaging cellular structures, they cannot provide 3D images. However, recent technological advances such as serial block-face scanning electron microscopy (SBF-SEM) and focused ion beam scanning electron microscopy (FIB-SEM) provide the tools to create 3D images for the ultrastructural analysis of organelles. Here, we describe a standardized protocol using the visualization software, Amira, to quantify organelle morphologies in 3D, thereby providing accurate and reproducible measurements of these cellular substructures. We demonstrate applications of SBF-SEM and Amira to quantify mitochondria and endoplasmic reticulum (ER) structures. 

Transmission electron microscopy (TEM) is widely used as an imaging modality to provide high-resolution details of subcellular components within cells and tissues. Mitochondria and endoplasmic reticulum (ER) are organelles of particular interest to those investigating metabolic disorders. A straightforward method for quantifying and characterizing particular aspects of these organelles would be a useful tool. In this protocol, we outline how to accurately assess the morphology of these important subcellular structures using open source software ImageJ, originally developed by the National Institutes of Health (NIH). Specifically, we detail how to obtain mitochondrial length, width, area, and circularity, in addition to assessing cristae morphology and measuring mito/endoplasmic reticulum (ER) interactions. These procedures provide useful tools for quantifying and characterizing key features of sub-cellular morphology, leading to accurate and reproducible measurements and visualizations of mitochondria and ER. 

Autophagosomes and lysosomes work in tandem to conduct autophagy, an intracellular degradation system which is crucial for cellular homeostasis. Altered autophagy contributes to the pathophysiology of various diseases, including cancers and metabolic diseases. Although many studies have investigated autophagy to elucidate disease pathogenesis, specific identification of the various components of the cellular degradation machinery remains difficult. The goal of this paper is to describe an approach to reproducibly identify and distinguish subcellular structures involved in autophagy. We provide methods that avoid common pitfalls, including a detailed explanation for how to distinguish lysosomes and lipid droplets and discuss the differences between autophagosomes and inclusion bodies. These methods are based on using transmission electron microscopy (TEM), capable of generating nanometer-scale micrographs of cellular degradation components in a fixed sample. In addition to TEM, we discuss other imaging techniques, such as immunofluorescence and immunogold labeling, which can be utilized for the reliable and accurate classification of cellular organelles. Our results show how these methods may be employed to accurately quantify the cellular degradation machinery under various conditions, such as treatment with the endoplasmic reticulum stressor thapsigargin or the ablation of dynamin-related protein 1.