Biology subjects

Nizet, O.

Publications and source records attributed to Nizet, O..

3 recordsLinked to original sources

bioRxiv2025

3D multi-omic mapping of whole nondiseased human fallopian tubes at cellular resolution reveals a large incidence of ovarian cancer precursors

Uncovering the spatial and molecular landscape of precancerous lesions is essential for developing meaningful cancer prevention and early detection strategies. High-Grade Serous Carcinoma (HGSC), the most lethal gynecologic malignancy, often originates from Serous Tubal Intraepithelial Carcinomas (STICs) in the fallopian tubes, yet their minute size and our historical reliance on standard 2D histology contribute to their underreporting. Here, we present a spatially resolved, multi-omics framework that integrates whole-organ 3D imaging at cellular resolution with targeted proteomic, metabolomic, and transcriptomic profiling to detect and characterize microscopic tubal lesions. Using this platform, we identified a total of 99 STICs and their presumed precursors that harbor TP53 mutations in morphologically unremarkable tubal epithelium in all five specimens obtained from cancer-free organ donors with average-risk of developing ovarian cancer. Although these lesions comprised only 0.2% of the epithelial compartment, they displayed geographic diversity, immune exclusion, metabolic rewiring, and DNA copy number changes among lesions and normal fallopian tube epithelium discovered alterations in STIC-associated genes and the pathways they control. In sum, this platform provides a comprehensive 3D atlas of early neoplastic transformation, yielding mechanistic insights into tumor initiation and informing clinical screening strategies for detecting cancer precursors in whole organs at cellular resolution.

bioinformatics↗

bioRxiv2024

A three-country analysis of the gut microbiome indicates taxon associations with diet vary by location and strain

Emerging research suggests that diet plays a vital role in shaping the composition and function of the gut microbiota. While significant efforts have been made to identify general patterns linking diet to the gut microbiome, much of this research lacks representation from low- and middle-income countries such as Mexico. Additionally, both diet and the gut microbiome have highly complex and individualized configurations, and there is growing evidence that tailoring diets to individual gut microbiota profiles may optimize the path toward improving or maintaining health and preventing disease. Using fecal metagenomic data from 1,291 individuals across three countries, we examine two bacterial genera prevalent in the human gut, Prevotella and Faecalibacterium, which have gained significant attention due to their potential roles in human health. We find that they show significant associations with many aspects of diet, but that these associations vary in scale and direction, depending on the level of metagenomic resolution and the contextual population. These results highlight the growing importance of assembling metagenomic datasets that are standardized, comprehensive, and representative of diverse populations to increase our ability to tease apart the complex relationship between diet and the microbiome.

microbiology↗

bioRxiv2022

Development of a High-Throughput Minimum Inhibitory Concentration (HT-MIC) Testing Workflow

The roots of the minimum inhibitory concentration (MIC) determination go back to the early 1900s. Since then, the test has undergone modifications and advancements in an effort to increase its dependability and accuracy. Although biological investigations use an ever-increasing number of samples, complicated processes and human error sometimes result in poor data quality, which makes it challenging to replicate scientific conclusions. The automation of the few manual steps using protocols decipherable by machine can ease some of the procedural difficulties. Originally relying on manual pipetting and human vision to determine the results, modern broth dilution MIC testing procedures have incorporated microplate readers to enhance sample analysis. However, current MIC testing procedures are unable to simultaneously evaluate a large number of samples efficiently. Here, we have created a workflow using the Opentrons OT-2 robot to enable high-throughput MIC testing. We have further optimized the analysis by incorporating Python programming for MIC assignment to streamline the automation. In this workflow, we performed MIC tests on four different strains, three replicates per strain, and analyzed a total of 1,152 wells. Comparing our our workflow to a conventional plate MIC procedure, we find that the HT-MIC method is 630% faster while simulataneously boasting a 100% accuracy. Our high-throughput MIC workflow can be applied in both academic and clinical settings since it is faster, more efficient, and more accurate than many conventional methods.

microbiology↗