Mantra 2.0: An online collaborative resource for drug mode of action and repurposing by network analysis

Elucidation of molecular targets of a compound (mode of action, MoA) and of its off-targets is a crucial step in drug development. We developed an online collaborative resource (MANTRA 2.0) that supports this process by exploiting similarities between drug-induced transcriptional profiles. Drugs are organised in a network of nodes (drugs) and edges (similarities) highlighting “communities” of drugs sharing a similar MoA. A user can upload gene expression profiles (GEPs) before and after drug treatment in one or multiple cell types. An automated processing pipeline transforms the GEPs into a unique drug ”node” embedded in the drug-network. Visual inspection of the neighbouring drugs and communities helps in revealing its MoA, and to suggest new applications of known drugs (drug repurposing). MANTRA 2.0 allows storing and sharing user-generated network nodes, thus making MANTRA 2.0 a collaborative ever-growing resource

Borehole water level response to barometric pressure as an indicator of aquifer vulnerability

The response of borehole water levels to barometric pressure changes in semiconfined aquifers can be used to determine barometric response functions from which aquifer and confining layer properties can be obtained. Following earlier work on barometric response functions and aquifer confinement, we explore the barometric response function as a tool to improve the assessment of groundwater vulnerability in semiconfined aquifers, illustrated through records from two contrasting boreholes in the semiconfined Chalk Aquifer, East Yorkshire, UK. After removal of recharge and Earth tide influences on the water level signal, barometric response functions were estimated and aquifer and confining layer properties determined through an analytical model of borehole water level response to barometric pressure. A link between the thickness and vertical diffusivity of the confining layer determined from the barometric response function, and groundwater vulnerability is proposed. The amplitude spectrum for barometric pressure and instrument resolution favor determination of the barometric response function at frequencies to which confining layer diffusivities are most sensitive. Numerical modeling indicates that while the high frequency response reflects confining layer properties in the immediate vicinity of the borehole, the low frequency response reflects vertical, high diffusivity pathways though the confining layer some hundreds of meters distant. A characteristic time scale parameter, based on vertical diffusivities and thicknesses of the saturated and unsaturated confining layer, is introduced as a measure of semiconfined aquifer vulnerability. The study demonstrates that the barometric response function has potential as a tool for quantitative aquifer vulnerability assessment in semiconfined aquifers

Mild clinical course of covid-19 in 3 patients receiving therapeutic monoclonal antibodies targeting c5 complement for hematologic disorders

© Am J Case Rep, 2020. Objective: Rare co-existance of disease or pathology Background: Patients receiving immunosuppressive therapies might be more susceptible to COVID-19. Conversely, an exaggerated inflammatory response to the SARS-CoV-2 infection might be blunted by certain forms of immunosuppression, which could be protective. Indeed, there are data from animal models demonstrating that complement may be a part of the pathophysiology of coronavirus infections. There is also evidence from an autopsy series demonstrating complement deposition in the lungs of patients with COVID-19. This raises the question of whether patients on anti-complement therapy could be protected from COVID-19. Case Reports: Case 1 is a 39-year-old woman with an approximately 20-year history of paroxysmal nocturnal hemoglobinuria (PNH), who had recently been switched from treatment with eculizumab to ravulizumab prior to SARS-CoV-2 infection. Case 2 is a 54-year-old woman with a cadaveric renal transplant for lupus nephritis, complicated by thrombotic microangiopathy, who was maintained on eculizumab, which she started several months before she developed the SARS-CoV-2 infection. Case 3 is a 60-year-old woman with a 14-year history of PNH, who had been treated with eculizumab since 2012, and was diagnosed with COVID-19 at the time of her scheduled infusion. All 3 patients had a relatively mild course of COVID-19. Conclusions: We see no evidence of increased susceptibility to SARS-CoV-2 in these patients on anti-complement therapy, which might actually have accounted for the mild course of infection. The effect of anti-complement therapy on COVID-19 disease needs to be determined in clinical trials

The impact of microRNAs on transcriptional heterogeneity and gene co-expression across single embryonic stem cells

MicroRNAs act posttranscriptionally to suppress multiple target genes within a cell population. To what extent this multi-target suppression occurs in individual cells and how it impacts transcriptional heterogeneity and gene co-expression remains unknown. Here we used single-cell sequencing combined with introduction of individual microRNAs. miR-294 and let-7c were introduced into otherwise microRNA-deficient Dgcr8 knockout mouse embryonic stem cells. Both microRNAs induce suppression and correlated expression of their respective gene targets. The two microRNAs had opposing effects on transcriptional heterogeneity within the cell population, with let-7c increasing and miR-294 decreasing the heterogeneity between cells. Furthermore, let-7c promotes, whereas miR-294 suppresses, the phasing of cell cycle genes. These results show at the individual cell level how a microRNA simultaneously has impacts on its many targets and how that in turn can influence a population of cells. The findings have important implications in the understanding of how microRNAs influence the co-expression of genes and pathways, and thus ultimately cell fate

Assessing the Effect of Variable Ambient Temperature on the Self-ignition of a Reaction-diffusion System Employing a Reduced Order Modelling Methodology

The system under study in this work is a self-igniting pile of solid material. To predict and understand the effect of steep changes of the state variables on such systems, a reaction-diffusion model is employed. These systems can exhibit complex oscillatory behaviour, and changes in ambient conditions over time may strongly impact the inherent oscillations. To simulate the unsteady evolution of the pile, both a classical numerical technique (method of lines) and a reduced order approach are employed in combination with a stiff ODE solver. To account for circadian fluctuations in temperature, time-variable boundary conditions are assumed upon formulating the problem. The reduced order model is introduced in view of understanding if an approximated formulation characterized by a much lower number of state variables can accurately predict the complex behaviour of the system even in the case of sudden, steep variations of the values of the state variables due to the phenomenon of self-ignition, intensified here by variable boundary conditions. The selected case studies have the goal of exploring the effect of stockpile properties on the self-ignition phenomenon. Numerical solutions show the anticipated coupling between the system intrinsic dynamics and the oscillating temperature imposed at the boundary. All of the analysed cases are accurately replicated by the reduced order model

OscoNet: Inferring oscillatory gene networks

Background: Oscillatory genes, with periodic expression at the mRNA and/or protein level, have been shown to play a pivotal role in many biological contexts. However, with the exception of the circadian clock and cell cycle, only a few such genes are known. Detecting oscillatory genes from snapshot single-cell experiments is a challenging task due to the lack of time information. Oscope is a recently proposed method to identify co-oscillatory gene pairs using single-cell RNA-seq data. Although promising, the current implementation of Oscope does not provide a principled statistical criterion for selecting oscillatory genes. Results: We improve the optimisation scheme underlying Oscope and provide a wellcalibrated non-parametric hypothesis test to select oscillatory genes at a given FDR threshold. We evaluate performance on synthetic data and three real datasets and show that our approach is more sensitive than the original Oscope formulation, discovering larger sets of known oscillators while avoiding the need for less interpretable thresholds. We also describe how our proposed pseudo-time estimation method is more accurate in recovering the true cell order for each gene cluster while requiring substantially less computation time than the extended nearest insertion approach. Conclusions: OscoNet is a robust and versatile approach to detect oscillatory gene networks from snapshot single-cell data addressing many of the limitations of the original Oscope method

ROBustness In Network (robin): an R Package for Comparison and Validation of Communities

In network analysis, many community detection algorithms have been developed. However, their implementation leaves unaddressed the question of the statistical validation of the results. Here, we present robin (ROBustness In Network), an R package to assess the robustness of the community structure of a network found by one or more methods to give indications about their reliability. The procedure initially detects if the community structure found by a set of algorithms is statistically significant and then compares two selected detection algorithms on the same graph to choose the one that better fits the network of interest. We demonstrate the use of our package on the American College Football benchmark dataset

Expanding the spectrum of neonatal-onset AIFM1-associated disorders

Objectives: Pathogenic variants in AIFM1 have been associated with a wide spectrum of disorders, spanning from CMT4X to mitochondrial encephalopathy. Here we present a novel phenotype and review the existing literature on AIFM1-related disorders. Methods: We performed EEG recordings, brain MRI and MR Spectroscopy, metabolic screening, echocardiogram, clinical exome sequencing (CES) and family study. Effects of the variant were established on cultured fibroblasts from skin punch biopsy. Results: The patient presented with drug-resistant, electro-clinical, multifocal seizures 6 h after birth. Brain MRI revealed prominent brain swelling of both hemispheres and widespread signal alteration in large part of the cortex and of the thalami, with sparing of the basal nuclei. CES analysis revealed the likely pathogenic variant c.5T>C; p.(Phe2Ser) in the AIFM1 gene. The affected amino acid residue is located in the mitochondrial targeting sequence. Functional studies on cultured fibroblast showed a clear reduction in AIFM1 protein amount and defective activities of respiratory chain complexes I, III and IV. No evidence of protein mislocalization or accumulation of precursor protein was observed. Riboflavin, Coenzyme Q10 and thiamine supplementation was therefore given. At 6 months of age, the patient exhibited microcephaly but did not experience any further deterioration. He is still fed orally and there is no evidence of muscle weakness or atrophy. Interpretation: This is the first AIFM1 case associated with neonatal seizures and diffuse white matter involvement with relative sparing of basal ganglia, in the absence of clinical signs suggestive of myopathy or motor neuron disease

Identification of genes with oscillatory expression in glioblastoma: the paradigm of SOX2

Quiescence, a reversible state of cell-cycle arrest, is an important state during both normal development and cancer progression. For example, in glioblastoma (GBM) quiescent glioblastoma stem cells (GSCs) play an important role in re-establishing the tumour, leading to relapse. While most studies have focused on identifying differentially expressed genes between proliferative and quiescent cells as potential drivers of this transition, recent studies have shown the importance of protein oscillations in controlling the exit from quiescence of neural stem cells. Here, we have undertaken a genome-wide bioinformatic inference approach to identify genes whose expression oscillates and which may be good candidates for controlling the transition to and from the quiescent cell state in GBM. Our analysis identified, among others, a list of important transcription regulators as potential oscillators, including the stemness gene SOX2, which we verified to oscillate in quiescent GSCs. These findings expand on the way we think about gene regulation and introduce new candidate genes as key regulators of quiescence