Sphingolipids, long thought to be passive components of biological membranes with merely a structural role, have proved throughout the past decade to be major players in the pathogenesis of many human diseases. The study and characterization of several genetic disorders like Fabry’s and Tay Sachs, where sphingolipid metabolism is disrupted, leading to a systemic array of clinical symptoms, have indeed helped elucidate and appreciate the importance of sphingolipids and their metabolites as active signaling molecules. In addition to being involved in dynamic cellular processes like apoptosis, senescence and differentiation, sphingolipids are implicated in critical physiological functions such as immune responses and pathophysiological conditions like inflammation and insulin resistance. Interestingly, the kidneys are among the most sensitive organ systems to sphingolipid alterations, rendering these molecules and the enzymes involved in their metabolism, promising therapeutic targets for numerous nephropathic complications that stand behind podocyte injury and renal failure.

Assessment of differential gene expression by qPCR is heavily influenced by the choice of reference genes. Although numerous statistical approaches have been proposed to determine the best reference genes, they can give rise to conflicting results depending on experimental conditions. Hence, recent studies propose the use of RNA-Seq to identify stable genes followed by the application of different statistical approaches to determine the best set of reference genes for qPCR data normalization. In this study, however, we demonstrate that the statistical approach to determine the best reference genes from commonly used conventional candidates is more important than the preselection of ‘stable’ candidates from RNA-Seq data. Using a qPCR data normalization workflow that we have previously established; we show that qPCR data normalization using conventional reference genes render the same results as stable reference genes selected from RNA-Seq data. We validated these observations in two distinct cross-sectional experimental conditions involving human iPSC derived microglial cells and mouse sciatic nerves. These results taken together show that given a robust statistical approach for reference gene selection, stable genes selected from RNA-Seq data do not offer any significant advantage over commonly used reference genes for normalizing qPCR assays.

Childhood adversities (CAs) are well reviewed in mental health and addiction research internationally. However, these variables have not been studied within the framework of addiction in the Middle East region. The present study reports the prevalence of Childhood Adversities in a sample of outpatients seeking treatment for Substance Use Disorder. We used the Adverse Childhood Experiences - International Questionnaire (ACE-IQ) to map out the prevalence of childhood adversities. The studied population was composed of a clinical outpatient sample that met criteria for substance use disorder (N = 144). Results indicated that almost all the sample reported having experienced at least 1 CA, whereby three quarters of the clinical sample reported experiencing 6 or more adversities. Childhood adversities are highly prevalent in a Lebanese substance use disorder population which raises the need for better screening strategies and more understanding of Adverse Childhood Experiences in this specific population.

Embryonic Dissociated Dorsal Root Ganglia (DRG) cultures are often used to investigate the role of novel molecular pathways or drugs in Schwann cell development and myelination. These cultures largely recapitulate the order of cellular and molecular events that occur in Schwann cells of embryonic nerves. However, the timing of Schwann cell developmental transitions, notably the transition from Schwann Cell Precursors (SCP) to immature Schwann cells (iSC) and then to myelinating Schwann cells, has not been estimated so far in this culture system. In this study, we determined the expression profiles of Schwann cell developmental genes during the first week of culture and then compared our data to the expression profiles of these genes in developing spinal nerves. This helped in identifying that SCP transition into iSC between the 5th and 7th day in vitro. Furthermore, we also investigated the transition of immature cells into pro-myelinating and myelinating Schwann cells upon the induction of myelination in vitro. Our results suggest that Schwann cell differentiation beyond the immature stage can be observed as early as 4 days post the induction of myelination in cocultures. Finally, we compared the myelinating potential of coculture-derived Schwann cell monocultures to cultures established from neonatal sciatic nerves and found that both these culture systems exhibit similar myelinating phenotypes. In effect, our results allow for a better understanding and interpretation of coculture experiments especially in studies that aim to elucidate the role of a novel actor in Schwann cell development and myelination.

Assessment of differential gene expression by qPCR is heavily influenced by the choice of reference genes. Although numerous statistical approaches have been proposed to determine the best reference genes, they can give rise to conflicting results depending on experimental conditions. Hence, recent studies propose the use of RNA-Seq to identify stable genes followed by the application of different statistical approaches to determine the best set of reference genes for qPCR data normalization. In this study, we demonstrate that the statistical approach to determine the best reference genes from randomly selected candidates is more important than the preselection of stable candidates from RNA-Seq data. Using a qPCR data normalization workflow that we have previously established; we show that qPCR data normalization using randomly chosen conventional reference genes renders the same results as stable reference genes selected from RNA-Seq data. Furthermore, the differential expression of target genes assessed by qPCR using our normalization strategy is comparable to RNA-Seq results. We validated these observations in two distinct cross-sectional experimental conditions involving human iPSC derived microglial cells and mouse sciatic nerves. These results taken together show that given a robust statistical approach for reference gene selection, stable genes selected from RNA-Seq data do not offer any significant advantage over commonly used reference genes for normalizing qPCR assays.

No abstract