Luisa Cutillo

Serotype-dependent packaging of large genes in adeno-associated viral vectors results in effective gene delivery in mice

Vectors derived from adeno-associated virus (AAV) are promising for human gene therapy, including treatment for retinal blindness. One major limitation of AAVs as vectors is that AAV cargo capacity has been considered to be restricted to 4.7 kb. Here we demonstrate that vectors with an AAV5 capsid (i.e., rAAV2/5) incorporated up to 8.9 kb of genome more efficiently than 6 other serotypes tested, independent of the efficiency of the rAAV2/5 production process. Efficient packaging of the large murine Abca4 and human MYO7A and CEP290 genes, which are mutated in common blinding diseases, was obtained, suggesting that this packaging efficiency is independent of the specific sequence packaged. Expression of proteins of the appropriate size and function was observed following transduction with rAAV2/5 carrying large genes. Intraocular administration of rAAV2/5 encoding ABCA4 resulted in protein localization to rod outer segments and significant and stable morphological and functional improvement of the retina in Abca4(-/-) mice. This use of rAAV2/5 may be a promising therapeutic strategy for recessive Stargardt disease, the most common form of inherited macular degeneration. The possibility of packaging large genes in AAV greatly expands the therapeutic potential of this vector system.

Coexistence of hereditary spherocytosis (HS) due to band 3 deficiency and β-thalassaemia trait: partial correction of HS phenotype

Summary. A kindred with hereditary spherocytosis and β‐thalassaemia trait was identified. Detailed studies of the red cell membrane proteins on polyacrylamide gels with sodium dodecyl sulphate (SDS‐PAGE) demonstrated the presence of band 3 (anion transporter) deficiency in all HS subjects (20–25% reduction) whereas spectrin content was in the normal range. The molecular defect of β thalassaemia in this kindred was due to a β° codon 39 (C‐T) mutation, as assessed by β globin gene amplification and ASO‐probe hybridization. Seven subjects of this family were studied: two were normal, two had HS alone, two co‐inherited HS and β‐thalassaemia trait, and one had β‐thalassaemia trait only. The two subjects with HS alone had a typical clinical form of spherocytosis with anaemia, reticulocytosis and increased red cell osmotic fragility. The two with both HS and β‐thalassaemia trait were not anaemic and showed a small, well‐compensated haemoIysis. Hence the finding of red cells with abnormalities of both HS and β‐thalassaemia indicates that β‐thalassaemic trait ‘silences’ HS caused by band 3 deficiency.

Disease rescue and increased lifespan in a model of cardiomyopathy and muscular dystrophy by combined AAV treatments.

Background The BIO14.6 hamster is an excellent animal model for inherited cardiomyopathy, because of its lethal and well-documented course, due to a spontaneous deletion of delta-sarcoglycan gene promoter and first exon. The muscle disease is progressive and average lifespan is 11 months, because heart slowly dilates towards heart failure. Methodology/Principal Findings Based on the ability of adeno-associated viral (AAV) vectors to transduce heart together with skeletal muscle following systemic administration, we delivered human delta-sarcoglycan cDNA into male BIO14.6 hamsters by testing different ages of injection, routes of administration and AAV serotypes. Body-wide restoration of delta-SG expression was associated with functional reconstitution of the sarcoglycan complex and with significant lowering of centralized nuclei and fibrosis in skeletal muscle. Motor ability and cardiac functions were completely rescued. However, BIO14.6 hamsters having less than 70% of fibers recovering sarcoglycan developed cardiomyopathy, even if the total rescued protein was normal. When we used serotype 2/8 in combination with serotype 2/1, lifespan was extended up to 22 months with sustained heart function improvement. Conclusions/Significance Our data support multiple systemic administrations of AAV as a general therapeutic strategy for clinical trials in cardiomyopathies and muscle disorders.

Tbx1 is a negative modulator of Mef2c

The developmental role of the T-box transcription factor Tbx1 is exquisitely dosage-sensitive. In this study, we performed a microarray-based transcriptome analysis of E9.5 embryo tissues across a previously generated Tbx1 mouse allelic series. This analysis identified several genes whose expression was affected by Tbx1 dosage. Interestingly, we found that the expression of the gene encoding the cardiogenic transcription factor Mef2c was negatively correlated to Tbx1 dosage. In vivo data revealed Mef2c up-regulation in the second heart field (SHF) of Tbx1 null mutant embryos compared with wild-type littermates at E9.5. Conversely, Mef2c expression was decreased in the SHF and in somites of Tbx1 gain-of-function mutants. These results are consistent with the described role of Tbx1 in suppressing cardiac progenitor cell differentiation and indicate also a negative effect of Tbx1 on Mef2c during skeletal muscle differentiation. We show that Tbx1 occupies conserved regulatory regions of the Mef2c locus, suggesting a direct effect on Mef2c transcription. However, we also show that Tbx1 interferes with the Gata4→ Mef2c regulatory pathway. Overall, our study uncovered a target of Tbx1 with critical developmental roles, so highlighting the power of the dosage gradient approach that we used.

Reverse engineering a mouse embryonic stem cell-specific transcriptional network reveals a new modulator of neuronal differentiation

Gene expression profiles can be used to infer previously unknown transcriptional regulatory interaction among thousands of genes, via systems biology ‘reverse engineering’ approaches. We ‘reverse engineered’ an embryonic stem (ES)-specific transcriptional network from 171 gene expression profiles, measured in ES cells, to identify master regulators of gene expression (‘hubs’). We discovered that E130012A19Rik (E13), highly expressed in mouse ES cells as compared with differentiated cells, was a central ‘hub’ of the network. We demonstrated that E13 is a protein-coding gene implicated in regulating the commitment towards the different neuronal subtypes and glia cells. The overexpression and knock-down of E13 in ES cell lines, undergoing differentiation into neurons and glia cells, caused a strong up-regulation of the glutamatergic neurons marker Vglut2 and a strong down-regulation of the GABAergic neurons marker GAD65 and of the radial glia marker Blbp. We confirmed E13 expression in the cerebral cortex of adult mice and during development. By immuno-based affinity purification, we characterized protein partners of E13, involved in the Polycomb complex. Our results suggest a role of E13 in regulating the division between glutamatergic projection neurons and GABAergic interneurons and glia cells possibly by epigenetic-mediated transcriptional regulation.

An atlas of gene expression and gene co-regulation in the human retina

The human retina is a specialized tissue involved in light stimulus transduction. Despite its unique biology, an accurate reference transcriptome is still missing. Here, we performed gene expression analysis (RNA-seq) of 50 retinal samples from non-visually impaired post-mortem donors. We identified novel transcripts with high confidence (Observed Transcriptome (ObsT)) and quantified the expression level of known transcripts (Reference Transcriptome (RefT)). The ObsT included 77 623 transcripts (23 960 genes) covering 137 Mb (35 Mb new transcribed genome). Most of the transcripts (92%) were multi-exonic: 81% with known isoforms, 16% with new isoforms and 3% belonging to new genes. The RefT included 13 792 genes across 94 521 known transcripts. Mitochondrial genes were among the most highly expressed, accounting for about 10% of the reads. Of all the protein-coding genes in Gencode, 65% are expressed in the retina. We exploited inter-individual variability in gene expression to infer a gene co-expression network and to identify genes specifically expressed in photoreceptor cells. We experimentally validated the photoreceptors localization of three genes in human retina that had not been previously reported. RNA-seq data and the gene co-expression network are available online (http://retina.tigem.it).

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.

Network Selection: A Method for Ranked Lists Selection

We consider the problem of finding the set of rankings that best represents a given group of orderings on the same collection of elements (preference lists). This problem arises from social choice and voting theory, in which each voter gives a preference on a set of alternatives, and a system outputs a single preference order based on the observed voters’ preferences. In this paper, we observe that, if the given set of preference lists is not homogeneous, a unique true underling ranking might not exist. Moreover only the lists that share the highest amount of information should be aggregated, and thus multiple rankings might provide a more feasible solution to the problem. In this light, we propose Network Selection, an algorithm that, given a heterogeneous group of rankings, first discovers the different communities of homogeneous rankings and then combines only the rank orderings belonging to the same community into a single final ordering. Our novel approach is inspired by graph theory; indeed our set of lists can be loosely read as the nodes of a network. As a consequence, only the lists populating the same community in the network would then be aggregated. In order to highlight the strength of our proposal, we show an application both on simulated and on two real datasets, namely a financial and a biological dataset. Experimental results on simulated data show that Network Selection can significantly outperform existing related methods. The other way around, the empirical evidence achieved on real financial data reveals that Network Selection is also able to select the most relevant variables in data mining predictive models, providing a clear superiority in terms of predictive power of the models built. Furthermore, we show the potentiality of our proposal in the bioinformatics field, providing an application to a biological microarray dataset.

Identifying regulatory sites using neighborhood species

The annotation of transcription binding sites in new sequenced genomes is an important and challenging problem. We have previously shown how a regression model that linearly relates gene expression levels to the matching scores of nucleotide patterns allows us to identify DNA-binding sites from a collection of co-regulated genes and their nearby non-coding DNA sequences. Our methodology uses Bayesian models and stochastic search techniques to select transcription factor binding site candidates. Here we show that this methodology allows us to identify binding sites in nearby species. We present examples of annotation crossing from Schizosaccharomyces pombe to Schizosaccharomyces japonicus. We found that the eng1 motif is also regulating a set of 9 genes in S. japonicus. Our framework may have an effective interest in conveying information in the annotation process of a new species. Finally we discuss a number of statistical and biological issues related to the identification of binding sites through covariates of genes expression and sequences.

Networks of Financial Contagion

Banks develop relationships in order to protect themselves against liquidity risk. Despite this benefit, fragility of financial markets stems from these interconnections. A cornerstone in the microeconomic analysis of contagion in financial systems is the contribution of Allen and Gale (2000). Our work takes up the challenge of generalizing their contagion analysis to complex networks. We provide an effective procedure to construct a network of financial contagion which enables the analysis of complex networks via simulations. Our study shows that it is possible to find a minimal number of links to guarantee contagion resiliency, and that the Allen and Gale conjecture holds: the system becomes more fragile as the number of links decreases.