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Visconti, A.

Publications and source records attributed to Visconti, A..

8 recordsLinked to original sources

Discovering and exploring the hidden diversity of human gut viruses using highly enriched virome samples

Viruses are an abundant and crucial component of the human microbiome, but accurately discovering them via metagenomics is still challenging. Currently, the available viral reference genomes poorly represent the diversity in microbiome samples, and expanding such a set of viral references is difficult. As a result, many viruses are still undetectable through metagenomics even when considering the power of de novo metagenomic assembly and binning, as viruses lack universal markers. Here, we describe a novel approach to catalog new viral members of the human gut microbiome and show how the resulting resource improves metagenomic analyses. We retrieved >3,000 viral-like particles (VLP) enriched metagenomic samples (viromes), evaluated the efficiency of the enrichment in each sample to leverage the viromes of highest purity, and applied multiple analysis steps involving assembly and comparison with hundreds of thousands of metagenome-assembled genomes to discover new viral genomes. We reported over 162,000 viral sequences passing quality control from thousands of gut metagenomes and viromes. The great majority of the retrieved viral sequences ([~]94.4%) were of unknown origin, most had a CRISPR spacer matching host bacteria, and four of them could be detected in >50% of a set of 18,756 gut metagenomes we surveyed. We included the obtained collection of sequences in a new MetaPhlAn 4.1 release, which can quantify reads within a metagenome matching the known and newly uncovered viral diversity. Additionally, we released the viral database for further virome and metagenomic studies of the human microbiome.

microbiology↗

Escape from X-inactivation in twins exhibits intra- and inter-individual variability across tissues and is heritable

X-chromosome inactivation (XCI) silences one X-chromosome in female cells to balance sex-differences in X-dosage. A subset of X-linked genes escape XCI, but the extent to which this phenomenon occurs and how it varies across tissues and in a population is as yet unclear. In order to characterize the incidence and variability of escape across individuals and tissues, we conducted a large scale transcriptomic study of XCI escape in adipose, skin, lymphoblastoid cell lines (LCLs) and immune cells in 248 twins drawn from a healthy population cohort. We identify 159 X-linked genes with detectable escape, of which 54 genes, including 19 lncRNAs, were not previously known to escape XCI. Across tissues we find a range of tissue-specificity, with 11% of genes escaping XCI constitutively across tissues and 24% demonstrating tissue-restricted escape, including genes with cell-type specific escape between immune cell types (B, T-CD4+, T-CD8+ and NK cells) of the same individual. Escape genes interact with autosomal-encoded proteins and are involved in varied biological processes such as gene regulation. We find substantial variability in escape between individuals. 49% of genes show inter-individual variability in escape, indicating escape from XCI is an under-appreciated source of gene expression differences. We utilized twin models to investigate the role of genetics in variable escape. Overall, monozygotic (MZ) twin pairs share more similar escape than dizygotic twin pairs, indicating that genetic factors underlie differences in escape across individuals. However, we also identify instances of discordant XCI within MZ co-twin pairs, suggesting that environmental factors also influence escape. Thus, XCI escape may be shaped by an interplay of genetic factors with tissue- and cell type-specificity, and environment. These results illuminate an intricate phenotype whose characterization aids understanding the basis of variable trait expressivity in females.

genetics↗

Multi-omic analyses reveal antibody-dependent natural killer cell-mediated cytotoxicity in autoimmune thyroid diseases

The pathogenesis of autoimmune thyroid diseases (AITD) is poorly understood. We previously observed systemic depletion of IgG core fucosylation and antennary 1,2 fucosylation of peripheral blood mononuclear cells in AITD, correlated with thyroid peroxidase antibody (TPOAb) levels. We hypothesized that deficiency in IgG core fucose enhances antibody-dependent cell-mediated cytotoxicity of thyrocytes by TPOAb, contributing to thyroid autoimmunity. Multi-omic evaluations in 622 individuals (172 with AITD) from the TwinsUK cohort showed decreased IgG core fucosylation levels associated with a subpopulation of natural killer (NK) cells featuring CD335, CD314, and CD158b immunoreceptors, and increased levels of apoptosis-associated Caspase-2 and Interleukin-1, positively associated with AITD. AITD-associated genetic variants rs1521 and rs3094228 alter expression of thyrocyte ligands of the CD314 and CD158b immunoreceptors on NK cells. The combination of low-core fucose IgG associated with an NK cell subpopulation and genetic variant-promoted ligand activation in thyrocytes may promote antibody-dependent NK cell-mediated cytotoxicity of thyrocytes in AITD.

immunology↗

Interplay between the human gut microbiome and host metabolism

The human gut is inhabited by a complex and metabolically active microbial ecosystem regulating host health. While many studies have focused on the effect of individual microbial taxa, the metabolic potential of the entire gut microbial ecosystem has been largely under-explored. We characterised the gut microbiome of 1,004 twins via whole shotgun metagenomic sequencing (average 39M reads per sample). We observed greater similarity, across unrelated individuals, for functional metabolic pathways (82%) than for taxonomic composition (43%). We conducted a microbiota-wide association study linking both taxonomic information and microbial metabolic pathways with 673 blood and 713 faecal metabolites (Metabolon, Inc.). Metabolic pathways associated with 34% of blood and 95% of faecal metabolites, with over 18,000 significant associations, while species-level results identified less than 3,000 associations, suggesting that coordinated action of multiple taxa is required to affect the metabolome. Finally, we estimated that the microbiome mediated a crosstalk between 71% of faecal and 15% of blood metabolites, highlighting six key species (unclassified Subdoligranulum spp., Faecalibacterium prausnitzii, Roseburia inulinivorans, Methanobrevibacter smithii, Eubacterium rectale, and Akkermansia muciniphila). Because of the large inter-person variability in microbiome composition, our results underline the importance of studying gut microbial metabolic pathways rather than focusing purely on taxonomy to find therapeutic and diagnostic targets.

microbiology↗

Genes associated with neuropsychiatric disease increase vulnerability to abnormal deep grey matter development

1.BackgroundNeuropsychiatric disease has polygenic determinants but is often precipitated by environmental pressures, including adverse perinatal events. However, the way in which genetic vulnerability and early-life adversity interact remains obscure. Preterm birth is associated with abnormal brain development and psychiatric disease. We hypothesised that the extreme environmental stress of premature extra-uterine life could contribute to neuroanatomic abnormality in genetically vulnerable individuals.\n\nMethodsWe combined Magnetic Resonance Imaging (MRI) and genome-wide single nucleotide polymorphism (SNP) data from 194 infants, born before 33 weeks of gestation, to test the prediction that: the characteristic deep grey matter abnormalities seen in preterm infants are associated with polygenic risk for psychiatric illness. Summary statistics from a meta-analysis of SNP data for five psychiatric disorders were used to compute individual polygenic risk scores (PRS). The variance explained by the PRS in the relative volumes of four deep grey matter structures (caudate nucleus, thalamus, subthalamic nucleus and lentiform nucleus) was estimated using linear regression both for the full, mixed-ancestral, cohort and a subsample of European infants.\n\nResultsThe PRS was negatively associated with: lentiform volume in the full cohort ({beta}=-0.24, p=8x10-4) and the European subsample ({beta}=-0.24, p=8x10-3); and with subthalamic nuclear volume in the full cohort ({beta}=-0.18, p=0.01) and the European subsample ({beta}=-0.26, p=3x10-3).\n\nConclusionsGenetic variants associated with neuropsychiatric disease increase vulnerability to abnormal deep grey matter development and are associated with neuroanatomic changes in the perinatal period. This suggests a mechanism by which perinatal adversity leads to later neuropsychiatric disease in genetically predisposed individuals.

neuroscience↗

YAMP: a framework enabling reproducibility in metagenomics research

YAMP is a user-friendly workflow that enables the analysis of whole shotgun metagenomic data while using containerisation to ensure computational reproducibility and facilitate collaborative research. YAMP can be executed on any UNIX-like system, and offers seamless support for multiple job schedulers as well as for Amazon AWS cloud. Although YAMP has been developed to be ready-to-use by non-experts, bioinformaticians will appreciate its flexibility, modularisation, and simple customisation.\n\nThe YAMP script, parameters, and documentation are available at https://github.com/alesssia/YAMP.

bioinformatics↗

Novel pleiotropic risk loci for melanoma and nevus density implicate multiple biological pathways

The total number of acquired melanocytic nevi on the skin is strongly correlated with melanoma risk. Here we report a meta-analysis of 11 nevus GWAS from Australia, Netherlands, United Kingdom, and United States, comprising a total of 52,506 phenotyped individuals. We confirm known loci including MTAP, PLA2G6, and IRF4, and detect novel SNPs at a genome-wide level of significance in KITLG, DOCK8, and a broad region of 9q32. In a bivariate analysis combining the nevus results with those from a recent melanoma GWAS meta-analysis (12,874 cases, 23,203 controls), SNPs near GPRC5A, CYP1B1, PPARGC1B, HDAC4, FAM208B and SYNE2 reached global significance, and other loci, including MIR146A and OBFC1, reached a suggestive level of significance. Overall, we conclude that most nevus genes affect melanoma risk (KITLG an exception), while many melanoma risk loci do not alter nevus count. For example, variants in TERC and OBFC1 affect both traits, but other telomere length maintenance genes seem to affect melanoma risk only. Our findings implicate multiple pathways in nevogenesis via genes we can show to be expressed under control of the MITF melanocytic cell lineage regulator.

genetics↗

PopPAnTe: population and pedigree association testing for quantitative data

Family-based designs, from twin studies to isolated populations with their complex genealogical data, are a valuable resource for genetic studies of heritable molecular biomarkers. Existing software for family-based studies have mainly focused on facilitating association between response phenotypes and genetic markers, and no user-friendly tools are at present available to straightforwardly extend association studies in related samples to large datasets of generic quantitative data, as those generated by current -omics technologies.\n\nWe developed PopPAnTe, a user-friendly Java program, which evaluates the association of quantitative data in related samples. Additionally, Pop-PAnTe implements data pre and post processing, region based testing, and empirical assessment of associations.\n\nPopPAnTe is an integrated and flexible framework for pairwise association testing in related samples with a large number of predictors and response variables. It works either with family data of any size and complexity, or, when the genealogical information is unknown, it uses genetic similarity information between individuals as those inferred from genome-wide genetic data. It can therefore be particularly useful in facilitating usage of biobank data collections from population isolates when extensive genealogical information is missing.

bioinformatics↗