Quantifying autophagy: Measuring LC3 puncta and autolysosome formation in cells using multispectral imaging flow cytometry.

The use of multispectral imaging flow cytometry has been gaining popularity due to its quantitative power, high throughput capabilities, multiplexing potential and its ability to acquire images of every cell. Autophagy is a process in which dysfunctional organelles and cellular components that accumulate during growth and differentiation are degraded via the lysosome and recycled. During autophagy, cytoplasmic LC3 is processed and recruited to the autophagosomal membranes; the autophagosome then fuses with the lysosome to form the autolysosome. Therefore, cells undergoing autophagy can be identified by visualizing fluorescently labeled LC3 puncta and/or the co-localization of fluorescently labeled LC3 and lysosomal markers. Multispectral imaging flow cytometry is able to collect imagery of large numbers of cells and assess autophagy in an objective, quantitative, and statistically robust manner. This review will examine the four predominant methods that have been used to measure autophagy via multispectral imaging flow cytometry.

Quantifying autophagosomes and autolysosomes in cells using imaging flow cytometry.

Autophagy dysregulation has been implicated in numerous diseases and many therapeutic agents are known to modulate this pathway. Therefore, the ability to accurately monitor autophagy is critical to understanding its role in the pathogenesis and treatment of many diseases. Recently an imaging flow cytometry method measuring colocalization of microtubule associated protein 1B light chain 3 (LC3) and lysosomal signals via Bright Detail Similarity (BDS) was proposed which enabled evaluation of autophagic processing. However, since BDS only evaluates colocalization of LC3 and lysosomal signals, the number of autophagy organelles was not taken into account. We found that in cells classified as having Low BDS, there was a large degree of variability in accumulation of autophagosomes. Therefore, we developed a new approach wherein BDS was combined with number of LC3+ puncta, which enabled us to distinguish between cells having very few autophagy organelles versus cells with accumulation of autophagosomes or autolysosomes. Using this method, we were able to distinguish and quantify autophagosomes and autolysosomes in breast cancer cells cultured under basal conditions, with inhibition of autophagy using chloroquine, and with induction of autophagy using amino acid starvation. This technique yields additional insight into autophagy processing making it a useful supplement to current techniques.

Integrated analysis of genotype and phenotype reveals clonal evolution and cytogenetically driven disruption of myeloid cell maturation in myelodysplastic syndromes.

BACKGROUND: Myelodysplastic syndromes (MDS) are a heterogenous collection of clonal bone marrow diseases characterized by cytopenias, abnormal karyotypes, molecular abnormalities, and dysplasia by flow cytometry and/or morphology. The progression of MDS to severe cytopenias and/or overt leukemia is associated with the accumulation of additional cytogenetic abnormalities, suggesting clonal evolution. The impact of these accumulated abnormalities on myeloid maturation and the severity of the disease is poorly understood. METHODS: Bone marrow specimens from 16 patients with cytogenetic abnormalities were flow cytometrically sorted into three myeloid populations: progenitors, immature myeloid cells, and mature myeloid cells. Fluorescence in situ hybridization analysis was performed on each to determine the distribution of chromosomal abnormalities during myeloid maturation. RESULTS: Our findings revealed three distinct distributions of cytogenetic abnormalities across myeloid maturation, each of which corresponded to specific cytogenetic abnormalities. Group 1 had continuous distribution across all maturational stages and contained patients with a single cytogenetic aberration associated with good-to-intermediate prognosis; Group 2 had accumulation of abnormalities in immature cells and contained patients with high-risk monosomy 7; and Group 3 had abnormalities defining the founding clone equally distributed across maturational stages while subclonal abnormalities were enriched in progenitor cells and contained patients with multiple, non-monosomy 7, abnormalities with evidence of clonal evolution. CONCLUSIONS: Our findings demonstrate that low-risk abnormalities (e.g., del(20q) and trisomy 8) occurring in the founding clone display a markedly different disease etiology, with respect to myeloid maturation, than monosomy 7 or abnormalities acquired in subclones, which result in a disruption of myeloid cell maturation in MDS.

Automation of the Micronucleus Assay Using Imaging Flow Cytometry and Artificial Intelligence.

The micronucleus (MN) assay is used worldwide by regulatory bodies to evaluate chemicals for genetic toxicity. The assay can be performed in two ways: by scoring MN in once-divided, cytokinesis-blocked binucleated cells or fully divided mononucleated cells. Historically, light microscopy has been the gold standard method to score the assay, but it is laborious and subjective. Flow cytometry has been used in recent years to score the assay, but is limited by the inability to visually confirm key aspects of cellular imagery. Imaging flow cytometry (IFC) combines high-throughput image capture and automated image analysis, and has been successfully applied to rapidly acquire imagery of and score all key events in the MN assay. Recently, it has been demonstrated that artificial intelligence (AI) methods based on convolutional neural networks can be used to score MN assay data acquired by IFC. This paper describes all steps to use AI software to create a deep learning model to score all key events and to apply this model to automatically score additional data. Results from the AI deep learning model compare well to manual microscopy, therefore enabling fully automated scoring of the MN assay by combining IFC and AI.

Conventional, High-Resolution and Imaging Flow Cytometry: Benchmarking Performance in Characterisation of Extracellular Vesicles.

Flow cytometry remains a commonly used methodology due to its ability to characterise multiple parameters on single particles in a high-throughput manner. In order to address limitations with lacking sensitivity of conventional flow cytometry to characterise extracellular vesicles (EVs), novel, highly sensitive platforms, such as high-resolution and imaging flow cytometers, have been developed. We provided comparative benchmarks of a conventional FACS Aria III, a high-resolution Apogee A60 Micro-PLUS and the ImageStream X Mk II imaging flow cytometry platform. Nanospheres were used to systematically characterise the abilities of each platform to detect and quantify populations with different sizes, refractive indices and fluorescence properties, and the repeatability in concentration determinations was reported for each population. We evaluated the ability of the three platforms to detect different EV phenotypes in blood plasma and the intra-day, inter-day and global variabilities in determining EV concentrations. By applying this or similar methodology to characterise methods, researchers would be able to make informed decisions on choice of platforms and thereby be able to match suitable flow cytometry platforms with projects based on the needs of each individual project. This would greatly contribute to improving the robustness and reproducibility of EV studies.

Assessing Autophagic Flux by Measuring LC3, p62, and LAMP1 Co-localization Using Multispectral Imaging Flow Cytometry.

Autophagy is a catabolic pathway in which normal or dysfunctional cellular components that accumulate during growth and differentiation are degraded via the lysosome and are recycled. During autophagy, cytoplasmic LC3 protein is lipidated and recruited to the autophagosomal membranes. The autophagosome then fuses with the lysosome to form the autolysosome, where the breakdown of the autophagosome vesicle and its contents occurs. The ubiquitin-associated protein p62, which binds to LC3, is also used to monitor autophagic flux. Cells undergoing autophagy should demonstrate the co-localization of p62, LC3, and lysosomal markers. Immunofluorescence microscopy has been used to visually identify LC3 puncta, p62, and/or lysosomes on a per-cell basis. However, an objective and statistically rigorous assessment can be difficult to obtain. To overcome these problems, multispectral imaging flow cytometry was used along with an analytical feature that compares the bright detail images from three autophagy markers (LC3, p62 and lysosomal LAMP1) and quantifies their co-localization, in combination with LC3 spot counting to measure autophagy in an objective, quantitative, and statistically robust manner.

Applications of Imaging Flow Cytometry for Microalgae.

The ability to image large numbers of cells at high resolution enhances flow cytometric analysis of cells and cell populations. In particular, the ability to image intracellular features adds a unique aspect to analyses, and can enable correlation between molecular phenomena resulting in alterations in cellular phenotype. Unicellular microalgae are amenable to high-throughput analysis to capture the diversity of cell types in natural samples, or diverse cellular responses in clonal populations, especially using imaging cytometry. Using examples from our laboratory, we review applications of imaging cytometry, specifically using an Amnis(®) ImageStream(®)X instrument, to characterize photosynthetic microalgae. Some of these examples highlight advantages of imaging flow cytometry for certain research objectives, but we also include examples that would not necessarily require imaging and could be performed on a conventional cytometer to demonstrate other concepts in cytometric evaluation of microalgae. We demonstrate the value of these approaches for (1) analysis of populations, (2) documentation of cellular features, and (3) analysis of gene expression.

Fluorescein thiocarbamyl amino acids as internal standards for migration time correction in capillary sieving electrophoresis.

A number of algorithms have been developed to correct for migration time drift in capillary electrophoresis. Those algorithms require identification of common components in each run. However, not all components may be present or resolved in separations of complex samples, which can confound attempts for alignment. This paper reports the use of fluorescein thiocarbamyl derivatives of amino acids as internal standards for alignment of 3-(2-furoyl)quinoline-2-carboxaldehyde (FQ)-labeled proteins in capillary sieving electrophoresis. The fluorescein thiocarbamyl derivative of aspartic acid migrates before FQ-labeled proteins and the fluorescein thiocarbamyl derivative of arginine migrates after the FQ-labeled proteins. These compounds were used as internal standards to correct for variations in migration time over a two-week period in the separation of a cellular homogenate. The experimental conditions were deliberately manipulated by varying electric field and sample preparation conditions. Three components of the homogenate were used to evaluate the alignment efficiency. Before alignment, the average relative standard deviation in migration time for these components was 13.3%. After alignment, the average relative standard deviation in migration time for these components was reduced to 0.5%.

Detection of green fluorescent protein in a single bacterium by capillary electrophoresis with laser-induced fluorescence.

Green fluorescence protein (GFP) is a common reporter used to monitor protein expression in single cells. However, autofluorescence from endogenous components can mask the signal from GFP, particularly at low expression levels in prokaryotes. We employ capillary electrophoresis with laser-induced fluorescence for the analysis of the expression of green fluorescent protein in a single bacterium. Capillary electrophoresis separates GFP from native cellular autofluorescent components, reducing the background signal and improving detection limits. Our system provides 100 ymol (60 copies) limits of detection for GFP. To demonstrate the performance of this instrument, we employ a model system of Deinococcus radiodurans that has been engineered to express GFP under the control of the recA promoter. We report resolution and detection of GFP and autofluorescent components in a single D. radiodurans bacterium. This paper presents the first example of expression of GFP in D. radiodurans and the first detection of GFP in a single bacterium by capillary electrophoresis.