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1.
Front Immunol ; 15: 1380386, 2024.
Article in English | MEDLINE | ID: mdl-38707902

ABSTRACT

Introduction: B cells play a pivotal role in adaptive immunity which has been extensively characterised primarily via flow cytometry-based gating strategies. This study addresses the discrepancies between flow cytometry-defined B cell subsets and their high-confidence molecular signatures using single-cell multi-omics approaches. Methods: By analysing multi-omics single-cell data from healthy individuals and patients across diseases, we characterised the level and nature of cellular contamination within standard flow cytometric-based gating, resolved some of the ambiguities in the literature surrounding unconventional B cell subsets, and demonstrated the variable effects of flow cytometric-based gating cellular heterogeneity across diseases. Results: We showed that flow cytometric-defined B cell populations are heterogenous, and the composition varies significantly between disease states thus affecting the implications of functional studies performed on these populations. Importantly, this paper draws caution on findings about B cell selection and function of flow cytometric-sorted populations, and their roles in disease. As a solution, we developed a simple tool to identify additional markers that can be used to increase the purity of flow-cytometric gated immune cell populations based on multi-omics data (AlliGateR). Here, we demonstrate that additional non-linear CD20, CD21 and CD24 gating can increase the purity of both naïve and memory populations. Discussion: These findings underscore the need to reconsider B cell subset definitions within the literature and propose leveraging single-cell multi-omics data for refined characterisation. We show that single-cell multi-omics technologies represent a powerful tool to bridge the gap between surface marker-based annotations and the intricate molecular characteristics of B cell subsets.


Subject(s)
B-Lymphocyte Subsets , Flow Cytometry , Single-Cell Analysis , Humans , Flow Cytometry/methods , Single-Cell Analysis/methods , B-Lymphocyte Subsets/immunology , B-Lymphocyte Subsets/metabolism , B-Lymphocytes/immunology , B-Lymphocytes/metabolism , Immunophenotyping/methods , Biomarkers , Multiomics
2.
Int J Mol Sci ; 23(17)2022 Aug 30.
Article in English | MEDLINE | ID: mdl-36077247

ABSTRACT

Weevils, classified in the family Curculionidae (true weevils), constitute a group of phytophagous insects of which many species are considered significant pests of crops. Within this family, the red palm weevil (RPW), Rhynchophorus ferrugineus, has an integral role in destroying crops and has invaded all countries of the Middle East and many in North Africa, Southern Europe, Southeast Asia, Oceania, and the Caribbean Islands. Simple sequence repeats (SSRs), also termed microsatellites, have become the DNA marker technology most applied to study population structure, evolution, and genetic diversity. Although these markers have been widely examined in many mammalian and plant species, and draft genome assemblies are available for many species of true weevils, very little is yet known about SSRs in weevil genomes. Here we carried out a comparative analysis examining and comparing the relative abundance, relative density, and GC content of SSRs in previously sequenced draft genomes of nine true weevils, with an emphasis on R. ferrugineus. We also used Illumina paired-end sequencing to generate draft sequence for adult female RPW and characterized it in terms of perfect SSRs with 1-6 bp nucleotide motifs. Among weevil genomes, mono- to trinucleotide SSRs were the most frequent, and mono-, di-, and hexanucleotide SSRs exhibited the highest GC content. In these draft genomes, SSR number and genome size were significantly correlated. This work will aid our understanding of the genome architecture and evolution of Curculionidae weevils and facilitate exploring SSR molecular marker development in these species.


Subject(s)
Coleoptera , Weevils , Animals , Base Composition , Coleoptera/genetics , Forests , Humans , Mammals/genetics , Microsatellite Repeats/genetics , Weevils/genetics
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