Role of Amino Acid Transporter SNAT1/SLC38A1 in Human Melanoma

The tumor metabolism is an important driver of cancer cell survival and growth, as rapidly dividing tumor cells exhibit a high demand for energetic sources and must adapt to microenvironmental changes. Therefore, metabolic reprogramming of cancer cells and the associated deregulation of nutrient transporters are a hallmark of cancer cells. Amino acids are essential for cancer cells to synthesize the necessary amount of protein, DNA, and RNA. Although cancer cells can synthesize glutamine de novo, most cancer cells show an increased uptake of glutamine from the tumor microenvironment. Especially SNAT1/SLC38A1, a member of the sodium neutral amino acid transporter (SNAT) family, plays an essential role during major net import of glutamine. In this study, we revealed a significant upregulation of SNAT1 expression in human melanoma tissue in comparison to healthy epidermis and an increased SNAT1 expression level in human melanoma cell lines when compared to normal human melanocytes (NHEMs). We demonstrated that functional inhibition of SNAT1 with α-(methylamino) isobutyric acid (MeAIB), as well as siRNA-mediated downregulation reduces cancer cell growth, cellular migration, invasion, and leads to induction of senescence in melanoma cells. Consequently, these results demonstrate that the amino acid transporter SNAT1 is essential for cancer growth, and indicates a potential target for cancer chemotherapy

Alpha-Synuclein and Its Role in Melanocytes

Pigmentation is an important process in skin physiology and skin diseases and presumably also plays a role in Parkinson’s disease (PD). In PD, alpha-Synuclein (aSyn) has been shown to be involved in the pigmentation of neurons. The presynaptic protein is intensively investigated for its pathological role in PD, but its physiological function remains unknown. We hypothesized that aSyn is both involved in melanocytic differentiation and melanosome trafficking processes. We detected a strong expression of aSyn in human epidermal melanocytes (NHEMs) and observed its regulation in melanocytic differentiation via the microphthalmia-associated transcription factor (MITF), a central regulator of differentiation. Moreover, we investigated its role in pigmentation by performing siRNA experiments but found no effect on the total melanin content. We discovered a localization of aSyn to melanosomes, and further analysis of aSyn knockdown revealed an important role in melanocytic morphology and a reduction in melanosome release. Additionally, we found a reduction of transferred melanosomes in co-culture experiments of melanocytes and keratinocytes but no complete inhibition of melanosome transmission. In summary, this study highlights a novel physiological role of aSyn in melanocytic morphology and its so far unknown function in the pigment secretion in melanocytes

Loss of Gene Information: Discrepancies between RNA Sequencing, cDNA Microarray, and qRT-PCR

Molecular analyses of normal and diseased cells give insight into changes in gene expression and help in understanding the background of pathophysiological processes. Years after cDNA microarrays were established in research, RNA sequencing (RNA-seq) became a key method of quantitatively measuring the transcriptome. In this study, we compared the detection of genes by each of the transcriptome analysis methods: cDNA array, quantitative RT-PCR, and RNA-seq. As expected, we found differences in the gene expression profiles of the aforementioned techniques. Here, we present selected genes that exemplarily demonstrate the observed differences and calculations to reveal that a strong RNA secondary structure, as well as sample preparation, can affect RNA-seq. In summary, this study addresses an important issue with a strong impact on gene expression analysis in general. Therefore, we suggest that these findings need to be considered when dealing with data from transcriptome analyses

Additional file 2: of ABO allele-level frequency estimation based on population-scale genotyping by next generation sequencing

JAGS model specification file (ABO_model.bug). (BUG 38 kb

Additional file 4: of ABO allele-level frequency estimation based on population-scale genotyping by next generation sequencing

Mappings from EAG group codes as used in the JAGS model calculations to the allele groups (AlleleGroupIdentifiers.csv). (CSV 6 kb