Discover Community Create You

Loading publication...

Noodle always counts identifier-free feature events for service operation. With your permission, Google Analytics can also estimate audience and engagement. Search text, publication identifiers, cookies, IP addresses and browser fingerprints are never included in Noodle's first-party event counters.

Privacy details

Article

High-throughput cytological profiling uncovers genotype-phenotype associations in Mycobacterium tuberculosis clinical isolates.

mSystems - 18 Nov 2025

Liu Qingyun, Liu Yue J, Liu Ruiyuan, Culviner Peter H, Wang Xin, Wolf Ian D, Chen Ken, Chen Yiwang, Xiao Yi, Zhang Guiming, Sun Rongfeng, Wakabayashi Shoko, Howard Nicole C, Gan Mingyu, Rubin Eric J, Fortune Sarah M, Zhu Junhao

Abstract excerpt

Understanding the functional impact of bacterial genetic diversity is crucial for linking pathogen variants to clinical outcomes. Here, we introduce a high-throughput cytological profiling pipeline optimized for Mycobacterium tuberculosis (Mtb) clinical strains, integrating OD-calibrated feature analysis and high-content microscopy. Our system quantifies single-bacterium morphological and physiological traits...

Read the complete abstract on PubMed

Topics

Share this publication in a Topic to start or enrich a Post.

Share to Genetic Association Studies
Share to Genetic Variation

Methodology Data sources Editorial policy Privacy About Contact Helena Bioinformatics

Share to Genotype

Share to High-Throughput Screening Assays

Share to Mutation

Share to Mycobacterium tuberculosis

Share to Phenotype

Share to Tuberculosis

Source

Open in PubMed Open full text

Identifiers

PMID: 41065399
DOI: 10.1128/msystems.00972-25
PMCID: PMC12625746

Provenance

PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 8 Sept 2026.

Related research

Semantic proximity does not establish scientific evidence.

Research trail→

Click a neighbor to travelStep 1 · 12 closest

High-throughput cytological profiling uncovers genotype-phenotype associations in Mycobacterium tuberculosis clinical isolates.PMID 41065399Read ↗

Identification of bacterial determinants of tuberculosis infection and treatment outcomes: a phenogenomic analysis of clinical strains.Semantic proximity Read ↗

Stellar quality control for single-cell image-based profiling with coSMicQCSemantic proximity Read ↗

Single cell analysis of M. tuberculosis phenotype and macrophage lineages in the infected lungSemantic proximity Read ↗

Multiplexed strain phenotyping defines consequences of genetic diversity in <i>Mycobacterium tuberculosis</i> for infection and vaccination outcomesSemantic proximity Read ↗

Functional genetic diversity among Mycobacterium tuberculosis complex clinical isolates: delineation of conserved core and lineage-specific transcriptomes during intracellular survival.Semantic proximity Read ↗

Stress-responsive <i>Mycobacterium tuberculosis</i> subpopulations manipulate macrophage polarization and can be targeted to limit inflammationSemantic proximity Read ↗

Deletion of a mycobacterial divisome factor collapses single-cell phenotypic heterogeneity.Semantic proximity Read ↗

High-throughput phenogenotyping <i>of Mycobacteria tuberculosis</i> clinical strains reveals bacterial determinants of treatment outcomesSemantic proximity Read ↗

Research progress of single-cell sequencing in tuberculosisSemantic proximity Read ↗

High-throughput characterization of Mycobacterium tuberculosis gene function across diverse conditions.Semantic proximity Read ↗

Dynamic microfluidic single-cell screening identifies pheno-tuning compounds to potentiate tuberculosis therapy.Semantic proximity Read ↗

Arrayed CRISPRi and Quantitative Imaging Describe the Morphotypic Landscape of Essential Mycobacterial GenesSemantic proximity Read ↗

⌁Select a neighboring publication to make it the new centre.