Biology subjects

Fontana, E.

Publications and source records attributed to Fontana, E..

6 recordsLinked to original sources

bioRxiv2023

Embryonic lymphocytes contribute to a genetic form of autoimmune inflammation

Omenn Syndrome (OS) is a rare hematological disorder, caused by hypomorphic mutations in genes involved in B-/T-cell receptor (BCR/TCR) rearrangement that result in impaired lymphocyte development and immunodeficiency. Notwithstanding, few T-cell clones enriched in self-reactive specificities expand in peripheral tissues, where they trigger severe inflammation and autoimmune reactions. Interestingly, residual OS lymphocytes display characteristics proper of embryonic lymphocytes that emerge before, and independently from, hematopoietic stem cells (HSCs). This prompted us to hypothesize whether OS autoreactive T-cells are generated in the embryo independently from HSCs. Here we show that in the Rag2R229Q/R229Q OS mouse model, embryonic but not adult bone marrow-derived hematopoietic progenitors can generate T-cells. T-lymphopoiesis can be rescued in adult OS blood progenitors via their Lin28-mediated reprogramming to an embryonic-like state. Remarkably, when transplanted in immunodeficient mice, embryonic-like OS progenitors trigger tissue morphological alterations and inflammation in the large intestine of the recipients, recapitulating the typical OS inflammatory phenotype. Our study describes the previously unappreciated contribution of embryonic progenitors to the pool of autoreactive infilitrating T-cells, providing a novel platform for both the detailed study of human autoimmune disorders and the design of more targeted therapies.

developmental biology↗

bioRxiv2022

The TaxUMAP atlas: efficient display of large clinical microbiome data reveals ecological competition involved in protection against bacteremia

The microbiome is associated with health and disease, but causal effects are hard to quantify-- especially in humans where controlled experiments are nearly impossible. Akin to natural experiments, closely monitored patients offer an alternative to characterize microbiome effects. We present TaxUMAP, a taxonomically-informed visualization method to effectively display diverse microbiome states. TaxUMAP charts a microbiome atlas from 1,870 cancer patients as they progress through therapy-induced perturbations, and quantifies the microbiome contribution to patients risk for life-threatening bacteremia. We find that the lowest diversity states (gut dominations) that follow antibiotic treatments are stable, and that diverse communities harbor more diverse antimicrobial resistance genes than dominations. We reveal that certain Klebsiella species are associated with reduced risk for bacteremia, an effect driven by bacterial competition that we validate experimentally in vitro and in vivo. TaxUMAP effectively maps longitudinal microbiome data that can facilitate research into causal microbiome effects on human health. HIGHLIGHTSO_LITaxUMAP charts an atlas of patients microbiome states and their clinical context to reveal new causal effects. C_LIO_LIAntibiotics deplete the biodiversity and reduce the number of different antimicrobial resistance genes in the gut microbiome. C_LIO_LICertain Klebsiella species are associated with lower risk of bacteremia by other gut-borne pathogens. C_LIO_LIThese Klebsiella outcompete other gram-negative pathogens in vivo. C_LI

microbiology↗

bioRxiv2021

A compilation of fecal microbiome shotgun metagenomics from hospitalized patients undergoing hematopoietic cell transplantation

Hospitalized patients receiving hematopoietic cell transplants provide a unique opportunity to study how the human gut microbiome changes in response to perturbations, and how the resulting changes in the microbiome feedback on its living host. We previously compiled a large-scale longitudinal dataset of stool microbiome compositions from these patients and associated metadata1. In that dataset the microbiome analysis was limited to the taxonomic composition of the bacterial population obtained from 16S rRNA gene sequencing. Here, we augment those data with shotgun metagenomic sequences from a nested subset of 395 stool samples. We provide accession numbers that link each sample to the paired-end sequencing files deposited in a public repository, which can be directly accessed by the online services of PATRIC2 to be analyzed without the users having to download or transfer the files. We provide examples that show how shotgun sequencing enriches microbiome analyses beyond the taxonomic composition such as the analysis of gene functions including virulence factors and antibiotic resistances, and the assembly of genomes from metagenomic data.

systems biology↗

bioRxiv2020

Immunogenomic profile of colorectal cancer response to immune checkpoint blockade

Colorectal cancers (CRCs) show variable response to immune checkpoint blockade, which can only partially be explained by the variability of tumour mutational burden. To dissect the cellular and molecular determinants of response we performed a multi-omic screen of 721 cancer regions from patients treated with Pembrolizumab (KEYNOTE 177 clinical trial) or Nivolumab. Multi-regional whole exome, RNA and T-cell receptor sequencing show that, within hypermutated CRCs, response to both anti-PD1 agents is not positively associated with tumour mutational burden but with high clonality of immunogenic mutations, expanded T cells, low activation of the WNT pathway and active immune escape mechanisms. Coupling high-dimensional imaging mass cytometry with multiplexed immunofluorescence and computational spatial analysis, we observe that responsive hypermutated CRCs are rich in cytotoxic and proliferating PD1-expressing CD8 cells interacting with high-density clusters of PDL1-expressing antigen presenting macrophages. We propose that anti-PD1 agents release the PD1-PDL1 interaction between CD8 T cells and macrophages thus promoting cytotoxic anti-tumour activity.

cancer biology↗

bioRxiv2019

Antibiotic-induced shifts in fecal microbiota density and composition during hematopoietic stem cell transplantation

BackgroundDramatic microbiota changes and loss of commensal anaerobic bacteria are associated with adverse outcomes in hematopoietic cell transplantation (HCT) recipients. In this study, we demonstrate these dynamic changes at high-resolution through daily stool sampling and assess the impact of individual antibiotics on those changes.\n\nMethodsWe collected 272 longitudinal stool samples (with mostly daily frequency) from 18 patients undergoing HCT and determined their composition by multi-parallel 16S rRNA gene sequencing, as well as density of bacteria in stool by qPCR. We calculated microbiota volatility to quantify rapid shifts and developed a new dynamic systems inference method to assess the specific impact of antibiotics.\n\nResultsThe greatest shifts in microbiota composition occurred between stem cell infusion and reconstitution of healthy immune cells. Piperacillin-tazobactam caused the most severe declines among obligate anaerobes.\n\nConclusionsOur approach of daily sampling, bacterial density determination and dynamic systems modeling allowed us to infer the independent effects of specific antibiotics on the microbiota of HCT patients.

microbiology↗

bioRxiv2017

A Low-Cost Multiplex Biomarker Assay Stratifies Colorectal Cancer Patient Samples into Clinically-Relevant Subtypes

Previously, we classified colorectal cancers (CRCs) into five CRCA subtypes with different prognoses and potential treatment responses, using a 786-gene signature. We merged our subtypes and those described by five other groups into four consensus molecular subtypes (CMS) that are similar to CRCA subtypes. Here we demonstrate the analytical development and application of a custom NanoString platform-based biomarker assay to stratify CRC into subtypes. To reduce costs, we switched from the standard protocol to a custom modified protocol (NanoCRCA) with a high Pearson correlation coefficient (>0.88) between protocols. Technical replicates were highly correlated (>0.96). The assay included a reduced robust 38-gene panel from the 786-gene signature that was selected using an in-laboratory developed computational pipeline of class prediction methods. We applied our NanoCRCA assay to untreated CRCs including fresh-frozen and formalin-fixed paraffin-embedded (FFPE) samples (n=81) with matched microarray or RNA-Seq profiles. We further compared the assay results with CMS classification, different platforms (microarrays/RNA-Seq) and gene-set classifiers (38 and 786 genes). NanoCRCA classified fresh-frozen samples (n=39; not including those showing a mixture of subtypes) into all five CRCA subtypes with overall high concordance across platforms (89.7%) and with CMS subtypes (84.6%), independent of tumour cellularity. This analytical validation of the assay shows the association of subtypes with their known molecular, mutational and clinical characteristics. Overall, our modified NanoCRCA assay with further clinical assessment may facilitate prospective validation of CRC subtypes in clinical trials and beyond.\n\nNovelty and ImpactWe previously identified five gene expression-based CRC subtypes with prognostic and potential predictive differences using a 786-gene signature and microarray platform. Subtype-driven clinical trials require a validated assay suitable for routine clinical use. This study demonstrates, for the first time, how molecular CRCA subtype can be detected using NanoString Technology-based biomarker assay (NanoCRCA) suitable for clinical validation. NanoCRCA is suitable for analysing FFPE samples, and this assay may facilitate patient stratification within clinical trials.

cancer biology↗