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Several regulators of mitochondrial DNA (mtDNA) replication and transcription are known, and a canonical pathway that regulates mitochondrial biogenesis in response to stimulus and metabolic stress has been established. However, mechanisms governing homeostatic maintenance of mtDNA copy numbers remain poorly understood. McNulty et al. address this knowledge gap by using a fluorescent-based genome-wide CRISPR screen that identifies ABCB7 as a previously unrecognized negative regulator of mtDNA abundance.

ABCB7 is a mitochondrial inner membrane ABC transporter exports Fe-S related intermediates to the cytosol. ABCB7 silencing increased mtDNA copy number, TOMM20-positive mitochondrial area, and basal oxygen consumption in human cells. Authors propose that impaired Fe-S export perturbs cellular iron homeostasis and is associated with increased abundance of mitochondrial glutathione transporter, SLC25A39. They observed mitochondrial glutathione and cystine accumulation along with reduced whole cell cystine abundance. ABCB7 depletion also induced the integrated stress response (ISR) markers and increased PGC1β and ERRα transcripts, while inhibition of ISR suppressed the mtDNA response. Furthermore, silencing ABCB7 homologs increased mtDNA copy number in D. melanogaster, S. cerevisiae, and A. thaliana, suggesting evolutionary conservation of this regulatory phenotype.

Overall, this study identifies an intriguing link between ABCB7-dependent Fe-S homeostasis, glutathione/cystine distribution, and mtDNA regulation through proposed ABCB7-SLC25A39-ISR-PGC1β/ERRα axis, with evidence support that the mtDNA response to ABCB7 impairment is conserved across eukaryotes. This finding provides new insights into how mitochondrial metabolism may influence mitochondrial biogenesis and genome maintenance. While data support the involvement of this regulatory axis, further experimental validation of some aspects of the proposed mechanism would help strengthen the authors’ conclusions.

Major points:

1. Extended data Fig. 2a-c indicate that ABCB7 is essential across multiple cell lines, yet ABCB7-targeting sgRNAs are enriched in the TFAM-high fraction after 13 days of selection (Figure 1g). Although enrichment of guides targeting an essential gene is possible in a FACS-based screen, it remains unclear whether these guides were depleted in the unsorted population relative to the initial library and how much ABCB7 function persisted in surviving cells. The authors might consider including individual sgRNA counts and enrichment relative to the unsorted population. These data would help distinguish enrichment among surviving cells from the effects of ABCB7 disruption on cell fitness.

2. In lines 312 - 323, authors propose that ABCB7 depletion induces GCN2-dependent ISR signaling that promotes mitochondrial biogenesis through PGC1β and ERRα rather than the canonical PGC1α/NRF1 axis. They report increased GCN2 transcript and protein abundance, induction of ISR-associated genes, increased PGC1β and ERRα transcripts, and suppression of the mtDNA abundance increase upon inhibition of the ISR. However, GCN2 activity and functional requirement are not established, nor are PGC1β or ERRα shown to be necessary for the mtDNA response. The authors might consider assessing whether GCN2 inhibition prevents PGC1β/ERRα induction, and genetically perturbing GCN2 and PGC1β/ERRα to establish their respective roles in the proposed signaling cascade.

3. In lines 299 - 301, authors suggest that cytosolic cysteine depletion contributes to ISR-dependent mitochondrial biogenesis. Figure 4 f and m show decreased whole cell cystine abundance and increased mitochondrial cystine abundance, however, without direct measurement of cystine in cytosol. Authors might consider directly measuring cysteine levels across cellular compartments to determine whether cytosolic cysteine is indeed depleted. This would more directly support the proposed mechanism linking altered cysteine distribution to mitochondrial biogenesis.

4. In lines 178 - 193, authors interpret succinate accumulation, U-¹³C-glutamine tracing, and multi-omic profiling as evidence for an over-reduced CoQ pool in ABCB7-depleted cells. Although these observations are consistent with altered respiratory redox balance, they do not directly establish the CoQ reduction state. Authors could quantify oxidized CoQ and reduced CoQH₂ to test this interpretation and distinguish it from alternative explanations for the metabolic changes.

Minor points:

1. In lines 78 - 79, the authors note that “...the top and bottom 5% of fluorescent cells (hereafter TFAM-low and TFAM-high) were sorted...”. Since higher fluorescence corresponds to TFAM-high and lower fluorescence to TFAM-low, authors might consider reverse the order in parentheses to match the order in the text and improve readability.

2. Figure 1a indicates that a PAM site at the TFAM locus was mutated to protect the engineered strain from Cas9 editing. However, extended data Figure 1g shows reduced TFAM-mCherry fluorescence after introduction of sgRNA targeting TFAM. Since the Brunello library includes four guides targeting TFAM, the result may reflect protection of one target site, leaving others susceptible to editing. Authors might benefit from providing a more detailed explanation of which PAM was modified and how the reporter responds to the remaining TFAM-targeting guides to reduce potential confusion and clarify how the reporter behaves in the screen.

3. Figures 4e, f, and h and 5c, e, and g use repeated “+” and “−” symbols to distinguish experimental groups. Authors could consider using color-coded bars with the treatment groups defined in the figure legend. This change would make the panels cleaner and easier to read.

4. In figure 4g, i, l, and m, the meaning of different colors are not consistently clear. Readers can benefit from a well-defined color coding in the figure legend. This would improve readability and maintain consistence across figures.

I reviewed this preprint as part of the Transparent and Accountable Peer Review training program. This report was written with the support of my research mentor.

Competing interests

The authors declare that they have no competing interests.

Use of Artificial Intelligence (AI)

The authors declare that they did not use generative AI to come up with new ideas for their review.