Smart-RRBS for single-cell methylome and transcriptome analysis

The integration of DNA methylation and transcriptional state within single cells is of broad interest. Several single-cell dual- and multi-omics approaches have been reported that enable further investigation into cellular heterogeneity, including the discovery and in-depth study of rare cell populations. Such analyses will continue to provide important mechanistic insights into the regulatory consequences of epigenetic modifications. We recently reported a new method for profiling the DNA methylome and transcriptome from the same single cells in a cancer research study. Here, we present details of the protocol and provide guidance on its utility. Our Smart-RRBS (reduced representation bisulfite sequencing) protocol combines Smart-seq2 and RRBS and entails physically separating mRNA from the genomic DNA. It generates paired epigenetic promoter and RNA-expression measurements for ~24% of protein-coding genes in a typical single cell. It also works for micro-dissected tissue samples comprising hundreds of cells. The protocol, excluding flow sorting of cells and sequencing, takes ~3 d to process up to 192 samples manually. It requires basic molecular biology expertise and laboratory equipment, including a PCR workstation with UV sterilization, a DNA fluorometer and a microfluidic electrophoresis system

Tracing animal genomic evolution with the chromosomal-level assembly of the freshwater sponge Ephydatia muelleri

Abstract The genomes of non-bilaterian metazoans are key to understanding the molecular basis of early animal evolution. However, a full comprehension of how animal-specific traits such as nervous systems arose is hindered by the scarcity and fragmented nature of genomes from key taxa, such as Porifera. Ephydatia muelleri is a freshwater sponge found across the northern hemisphere. Here we present its 326 Mb genome, assembled to high contiguity (N50: 9.88 Mb) with 23 chromosomes on 24 scaffolds. Our analyses reveal a metazoan-typical genome architecture, with highly shared synteny across Metazoa, and suggest that adaptation to the extreme temperatures and conditions found in freshwater often involves gene duplication. The pancontinental distribution and ready laboratory culture of E. muelleri make this a highly practical model system, which with RNAseq, DNA methylation and bacterial amplicon data spanning its development and range allows exploration of genomic changes both within sponges and in early animal evolution

Inositol 1,4,5- Trisphosphate Receptor Function in Drosophila Insulin Producing Cells

The Inositol 1,4,5- trisphosphate receptor (InsP3R) is an intracellular ligand gated channel that releases calcium from intracellular stores in response to extracellular signals. To identify and understand physiological processes and behavior that depends on the InsP3 signaling pathway at a systemic level, we are studying Drosophila mutants for the InsP3R (itpr) gene. Here, we show that growth defects precede larval lethality and both are a consequence of the inability to feed normally. Moreover, restoring InsP3R function in insulin producing cells (IPCs) in the larval brain rescues the feeding deficit, growth and lethality in the itpr mutants to a significant extent. We have previously demonstrated a critical requirement for InsP3R activity in neuronal cells, specifically in aminergic interneurons, for larval viability. Processes from the IPCs and aminergic domain are closely apposed in the third instar larval brain with no visible cellular overlap. Ubiquitous depletion of itpr by dsRNA results in feeding deficits leading to larval lethality similar to the itpr mutant phenotype. However, when itpr is depleted specifically in IPCs or aminergic neurons, the larvae are viable. These data support a model where InsP3R activity in non-overlapping neuronal domains independently rescues larval itpr phenotypes by non-cell autonomous mechanisms

Association of kidney disease measures with risk of renal function worsening in patients with type 1 diabetes

Background: Albuminuria has been classically considered a marker of kidney damage progression in diabetic patients and it is routinely assessed to monitor kidney function. However, the role of a mild GFR reduction on the development of stage 653 CKD has been less explored in type 1 diabetes mellitus (T1DM) patients. Aim of the present study was to evaluate the prognostic role of kidney disease measures, namely albuminuria and reduced GFR, on the development of stage 653 CKD in a large cohort of patients affected by T1DM. Methods: A total of 4284 patients affected by T1DM followed-up at 76 diabetes centers participating to the Italian Association of Clinical Diabetologists (Associazione Medici Diabetologi, AMD) initiative constitutes the study population. Urinary albumin excretion (ACR) and estimated GFR (eGFR) were retrieved and analyzed. The incidence of stage 653 CKD (eGFR < 60 mL/min/1.73 m2) or eGFR reduction > 30% from baseline was evaluated. Results: The mean estimated GFR was 98 \ub1 17 mL/min/1.73m2 and the proportion of patients with albuminuria was 15.3% (n = 654) at baseline. About 8% (n = 337) of patients developed one of the two renal endpoints during the 4-year follow-up period. Age, albuminuria (micro or macro) and baseline eGFR < 90 ml/min/m2 were independent risk factors for stage 653 CKD and renal function worsening. When compared to patients with eGFR > 90 ml/min/1.73m2 and normoalbuminuria, those with albuminuria at baseline had a 1.69 greater risk of reaching stage 3 CKD, while patients with mild eGFR reduction (i.e. eGFR between 90 and 60 mL/min/1.73 m2) show a 3.81 greater risk that rose to 8.24 for those patients with albuminuria and mild eGFR reduction at baseline. Conclusions: Albuminuria and eGFR reduction represent independent risk factors for incident stage 653 CKD in T1DM patients. The simultaneous occurrence of reduced eGFR and albuminuria have a synergistic effect on renal function worsening

Anti-Mullerian hormone as a predictor of ovarian reserve in ART protocols: the hidden role of thyroid autoimmunity

BACKGROUND: Protocols of controlled ovarian hyper-stimulation (COH) require, as a crucial step, the identification of reliable predictors of ovarian reserve. Anti-Mullerian hormone (AMH) is one of the most reliable predictors of ovarian reserve but other factors including autoimmune thyroid diseases (ATD) have been associated with reduced fertility and poor COH outcome. Aim of the present study was to evaluate the relationship between ATD and AMH, and their role on the outcome of COH. METHODS: The study group included 288 sub-fertile euthyroid women aged less than 40 years attending a single center for Reproductive Medicine. Among them, 55 were ATD-positive and 233 ATD-negative. The serum levels of AMH, FSH, LH, estradiol (E2), and TSH were measured before COH. The ratio between serum E2 concentration on the day of oocytes pick-up and the total dose of administered recombinant FSH (r-FSH) (E2/r-FSH ratio) was calculated. RESULTS: The serum levels of AMH were significantly related to E2/r-FSH ratio, total dose of r-FSH and number of M II oocytes, both in ATD-positive and ATD-negative women. Within the low stratum of AMH levels, the presence of ATD did not further affect the outcome of COH. When the serum levels of AMH were in the high stratum, the presence of ATD significantly affected the E2/rFSH ratio, the total dose of r-FSH and the number of M II oocytes. CONCLUSIONS: The probability of a poor response to COH is high, and independent from ATD, in women with low AMH serum levels. In women with a good ovarian reserve, as assessed by high AMH serum levels, the presence of ATD impairs the outcome of COH

A dual simulation environment for simulating MAS in telecommunication networks

This paper presents a dual simulation environment for simulating different type of telecommunication networks integrating intelligent agents. Agents are considered as advanced tools for resolving complex issues in networking based on intelligent and dynamic features. To test the efficiency of these proposals, new simulation environments, integrating both agents and network components, are required. In this paper we propose an extension with intelligent capabilities to a networking platform. This dual simulation environment has been tested for implementing agents in a DiffServ network to improve its performance. Simulation results show the efficiency of integrating agents within telecommunication networks and also prove that such a dual simulation environment is needed to test new techniques based on agents and multi-agent systems in networking