Transition and heavy metals, such as Zn, Cu, Mn, and Fe, are found naturally in the environment in both nutrients in food and pollutants. All living organisms require different amounts of these micronutrients; however, exposure to high levels is deleterious to organisms. Metal acquisition is mainly through the diet, but metals can also be inhaled or absorbed through the skin1,2,3,4,5. It is important to note that the presence of metals in atmospheric particles is increasing and has been largely associated with health risks. Due to anthropogenic activities, increased levels of heavy metals such as Ag, As, Cd, Cr, Hg, Ni, Fe, and Pb have been detected in atmospheric particulate matter, rainwater, and soil6,7. These metals have the potential to compete with essential physiological trace elements, particularly Zn and Fe, and they induce toxic effects by inactivating fundamental enzymes for biological processes.
The trace element Zn is redox neutral and behaves as a Lewis acid in biological reactions, which makes it a fundamental cofactor necessary for protein folding and catalytic activity in over 10% of mammalian proteins8,9,10; consequently, it is essential for diverse physiological functions8,11. However, like many trace elements, there is a delicate balance between these metals facilitating normal physiological function and causing toxicity. In mammals, Zn deficiencies lead to anemia, growth retardation, hypogonadism, skin abnormalities, diarrhea, alopecia, taste disorders, chronic inflammation, and impaired immune and neurological functions11,12,13,14,15,16,17,18. In excess, Zn is cytotoxic and impairs absorption of other essential metals such as copper19,20,21.
Additionally, some metals like Cu and Fe have the potential to participate in harmful reactions. Production of reactive oxygen species (ROS) via Fenton chemistry can interfere with the assembly of iron sulfur cluster proteins and alter lipid metabolism22,23,24. To prevent this damage, cells utilize metal-binding chaperones and transporters to prevent toxic effects. Undoubtedly, metal homeostasis must be tightly controlled to ensure that specific cell types maintain proper levels of metals. For this reason, there is a significant need to advance techniques for accurate measurement of trace metals in biological samples. In developing and mature organisms there exists a differential biological need for trace elements at the cellular level, at different developmental stages, and in normal and pathological conditions. Therefore, precise determination of tissue and systemic metal levels is necessary to understand organismal metal homeostasis.
Graphite furnace atomic absorption spectrometry (GF-AAS) is a highly sensitive technique used for small sample volumes, making it ideal to measure transition and heavy metals present in biological and environmental samples25,26,27,28. Moreover, due to high sensitivity of the technique, it has been shown to be appropriate for studying the fine transport properties of Na+/K+-ATPase and gastric H+/K+-ATPase using Xenopus oocytes as a model system29. In GF-AAS, the atomized elements within a sample absorb a wavelength of radiation emitted by a light source containing the metal of interest, with the absorbed radiation proportional to the concentration of the element. Elemental electronic excitation takes place upon absorption of ultraviolet or visible radiation in a quantized process unique for each chemical element. In a single electron process, the absorption of a photon involves an electron moving from a lower energy level to higher level within the atom and GF-AAS determines the amount of photons absorbed by the sample, which is proportional to the number of radiation absorbing elements atomized in the graphite tube.
The selectivity of this technique relies on the electronic structure of the atoms, in which each element has a specific absorption/emission spectral line. In the case of Zn, the absorbance wavelength is 213.9 nm and can be precisely distinguished from other metals. Overall, GF-AAS can be used to quantify Zn with adequate limits of detection (LOD) and high sensitivity and selectivity25. The changes in absorbed wavelength are integrated and presented as peaks of energy absorption at specific and isolated wavelengths. The concentration of the Zn in a given sample is usually calculated from a standard curve of known concentrations according to the Beer-Lambert law, in which the absorbance is directly proportional to the concentration of Zn in the sample. However, applying the Beer-Lambert equation to GF-AAS analyses also presents some complications. For instance, variations in the atomization and/or non-homogenous concentrations of the samples can affect the metal measurements.
The metal atomization required for GF AAS trace elemental analysis consists of three fundamental steps. The first step is desolvation, where the liquid solvent is evaporated; leaving dry compounds after the furnace reaches a temperature of around 100 °C. Then, the compounds are vaporized by heating them from 800 to 1,400 °C (depending on the element to be analyzed) and become a gas. Finally, the compounds in the gaseous state are atomized with temperatures that range from 1,500 to 2,500 °C. As discussed above, increasing concentrations of a metal of interest will render proportional increases on the absorption detected by the GF-AAS, yet the furnace reduces the dynamic range of analysis, which is the working range of concentrations that can be determined by the instrument. Thus, the technique requires low concentrations and a careful determination of the dynamic range of the method by determining the LOD and limit of linearity (LOL) of the Beer-Lambert law. The LOD is the minimum quantity required for a substance to be detected, defined as three times the standard deviation of Zn in the matrix. The LOL is the maximum concentration that can be detected using Beer-Lambert law.
In this work, we describe a standard method to analyze the levels of Zn in whole cell extracts, cytoplasmic and nuclear fractions, and in proliferating and differentiating cultured cells (Figure 1). We adapted the rapid isolation of nuclei protocol to different cellular systems to prevent metal loss during sample preparation. The cellular models used were primary myoblasts derived from mouse satellite cells, murine neuroblastoma cells (N2A or Neuro2A), murine 3T3 L1 adipocytes, a human non-tumorigenic breast epithelial cell line (MCF10A), and epithelial Madin-Darby canine kidney (MDCK) cells. These cells were established from different lineages and are good models for investigating lineage specific variations of metal levels in vitro.
Primary myoblasts derived from mouse satellite cells constitute a well-suited in vitro model to investigate skeletal muscle differentiation. Proliferation of these cells is fast when cultured under high serum conditions. Differentiation into the muscular lineage is then induced by low serum conditions30. The murine neuroblastoma (N2A) established cell line was derived from the mouse neural crest. These cells present neuronal and amoeboid stem cell morphology. Upon differentiation stimulus, the N2A cells present several properties of neurons, such as neurofilaments. N2A cells are used to investigate Alzheimer's disease, neurite outgrowth, and neurotoxicity31,32,33. The 3T3-L1 murine pre-adipocytes established cell line is commonly used to investigate the metabolic and physiological changes associated with adipogenesis. These cells present a fibroblast-like morphology, but once stimulated for differentiation, they present enzymatic activation associated with lipid synthesis and triglycerides accumulation. This can be observed as morphological changes to produce cytoplasmic lipid droplets34,35. MCF10A is a non-tumor mammary epithelial cell line derived from a premenopausal woman with mammary fibrocystic disease36. It has been widely used for biochemical, molecular, and cellular studies related to mammary carcinogenesis such as proliferation, cell migration, and invasion. The Madin-Darby canine kidney (MDCK) epithelial cell line has been extensively used to investigate the properties and molecular events associated with the establishment of the epithelial phenotype. Upon reaching confluence, these cells become polarized and establish cell-cell adhesions, characteristics of mammalian epithelial tissues37.
To test the ability of AAS to measure the levels of Zn in mammalian cells, we analyzed whole and subcellular fractions (cytosol and nucleus) of these five cell lines. AAS measurements showed different concentrations of Zn in these cell types. Concentrations were lower in proliferating and differentiating primary myoblasts (4 to 7 nmol/mg of protein) and higher in the four established cell lines (ranging from 20 to 40 nmol/mg of protein). A small non-significant increase in Zn levels was detected in differentiating primary myoblasts and neuroblastoma cells when compared to proliferating cells. The opposite effect was detected in differentiated adipocytes. However, proliferating 3T3-L1 cells exhibited higher concentrations of the metal compared to differentiated cells. Importantly, in these three cell lines, subcellular fractionation showed that Zn is differentially distributed in the cytosol and nucleus according to the metabolic state of these cells. For instance, in proliferating myoblasts, N2A cells, and 3T3-L1 pre-adipocytes, a majority of the metal is localized to the nucleus. Upon induction of differentiation using specific cell treatments, Zn localized to the cytosol in these three cell types. Interestingly, both epithelial cell lines showed higher levels of Zn during proliferation compared to when reaching confluence, in which a characteristic tight monolayer was formed. In proliferating epithelial cells, the mammary cell line MCF10A had an equal Zn distribution between the cytosol and nucleus, while in the kidney-derived cell line, most of the metal was located in the nucleus. In these two cell types, when the cells reached confluence, Zn was predominantly located to the cytosol. These results demonstrate that GF-AAS is a highly sensitive and accurate technique for performing elemental analysis in low-yield samples. GF-AAS coupled with subcellular fractionation and can be adapted to investigate the levels of trace metal elements in different cell lines and tissues.