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A unique Mitochondrial Quality Control (MQC) mechanism reverses the phagosome maturation arrest caused by Mycobacterium tuberculosis

GSE216985 Homo sapiens (human) RNA-seq (gene expression) 36 samples Submitted 2026/07/31 Platform GPL20301
At a glance

RNA-seq (gene expression) · human · 36 samples

What it is
RNA-seq (gene expression)Gene activity measured by sequencing. The summary does not mention single-cell work, so this is most likely bulk: one average per sample, the usual starting point for comparing groups.
Organism
Homo sapiens (human)
Samples
36 samples: 36 samples, each with a distinct title — no replicated groupsGroups are read from the sample names, not from the paper. Check the list below.
Data you can get
A processed table (series matrix) and supplementary files from NCBI; the raw sequencing reads from ENA. Which of these hold counts depends on the study, so check the file list.
Summary (written by the submitters)
Phagosome maturation arrest (PMA) imposed by Mycobacterium tuberculosis (Mtb) is among the classic tools that helps Mtb evade macrophage anti-bacterial response. Here we report a unique crosstalk between mitochondrial quality control (MQC) pathways and the phagosome maturation pathway, which unblocks the PMA and results in the efficient killing of Mtb.
Read the full summary ↓
Depletion of p62/SQSTM1, a major autophagy adaptor, in human macrophages enhances Mtb killing. However, depletion of p62/SQSTM1 does not impact mitochondrial quality, despite an apparent block in mitophagy flux. Interestingly, in p62KD cells, MQC is ensured via TOM20+-mitochondria-derived vesicles (MDVs). MDVs, being dependent on RAB7 for maturation, are heavily recruited on Mtb-phagosomes in p62KD cells inadvertently aiding RAB7 recruitment on Mtb-phagosomes thereby releasing the PMA that facilitates efficient lysosomal delivery and killing of Mtb. Finally, blocking MQC in the p62KD cells, augments bacterial killing, underscoring the crosstalk between MQC and host-antibacterial mechanisms, providing an unexplored host-directed therapy strategy against tuberculosis.
This dataset
Open GSE216985 in finder → Find more human RNA-seq datasets →
Download · which file do I need?

Direct links to NCBI and ENA, no account and no request form. Pick by what you want to do: take the small processed table to look, the supplementary files to re-analyse, or the original raw data to start over.

1 · Just have a look

Processed table

The series matrix: one table of values per sample as the submitters processed it. The smallest download, and it opens in Excel or R. Start here to see what the data look like.

Series matrix ↓
2 · Re-analyse it

Supplementary files

The count tables and other files the authors uploaded. Take only the samples you need, or the whole study as GSE216985_RAW.tar (it can run to tens of gigabytes).

All supplementary files ↗ Whole study · RAW.tar ↓
3 · Start from the raw reads

Raw sequencing reads

The original FASTQ files, straight from the sequencer, held at ENA. Large, and you align them yourself, so only choose this if you need to re-process the study from scratch.

Raw reads on ENA ↗

What the files usually look like: For RNA-seq the counts are usually a table among the supplementary files (look for 'counts', 'expression', 'FPKM' or 'TPM' in the file name). The series matrix of a sequencing study is sometimes nearly empty.

Also filed as BioProject PRJNA896529 and SRA study SRP405643. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
36 samples, each with a distinct title — no replicated groups

Any grouping that defines a comparison lives in the sample characteristics, which GEO records separately from the titles.

How we read this: Read from 36 sample titles: 36 distinct titles with little repetition. These groups are guessed from the sample names, not taken from the paper, so check them against the sample list below before relying on them.

Samples in this study
Datasets on a similar topic

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Metadata from NCBI GEO, cached and refreshed periodically — the NCBI page above is authoritative. Downloads link straight to NCBI/ENA; nothing is proxied through BioTransfer.