Biology subjects

Kogenaru, M.

Publications and source records attributed to Kogenaru, M..

4 recordsLinked to original sources

bioRxiv2026

KaryoTap-based scDNA seq assessment of aneuploidy induction by hydroquinone in hematopoietic stem cells

Monosomy 7 is a frequent cytogenetic alteration associated with poor outcomes in myelodysplastic syndrome and acute myeloid leukemia. The benzene metabolite hydroquinone (HQ) has been reported to induce chromosome 7 loss in cultured hematopoietic cells, suggesting a mechanism linking benzene exposure to these diseases. However, these findings were largely based on FISH analysis of selected chromosomes in relatively small numbers of cells. Here, we tested whether HQ increases aneuploidy in primary human CD34+ hematopoietic stem and progenitor cells (HSPCs) using KaryoTap, a single-cell DNA sequencing approach that measures copy number across all 22 autosomes, together with interphase FISH. We first identified 20 uM as the highest HQ concentration tested that preserved sufficient viable cells for single-cell analysis. We then examined cord blood and adult mobilized CD34+ cells, including the MPS1 inhibitor reversine as a positive control in the cord blood experiment. Reversine increased whole-chromosome gains and losses, including those of chromosome 7. HQ did not produce a reproducible increase in aneuploidy across three donors and two sources of CD34+ cells, including two concentrations and two timepoints in the adult donor. A modest increase in chromosome 7 loss in one cord blood donor was not reproduced in the other donors. In the other cord blood donor, the estimated upper bound on the HQ-associated increase was approximately 1.4 percentage points. HSPCs also showed a greater increase in chromosome losses than epithelial cells or melanocytes following the same reversine exposure. These findings do not support a substantial, reproducible increase in whole-chromosome aneuploidy after HQ exposure under the conditions tested. They are consistent with a model in which benzene exposure favors the expansion of pre-existing monosomy 7 clones, although this possibility requires direct testing.

cancer biology↗

bioRxiv2026

ZATELLITE: a toolkit to visualize and manipulate human centromeres in live cells using synthetic zinc fingers

Changes in the number of chromosomes or their spatial organization within the nucleus have critical consequences for cell fate. Yet capturing the karyotype or three-dimensional architecture of chromatin in living cells remains limited by the difficulty in labeling endogenous loci non-invasively. The most widely used tools rely on dCas9, a bulky protein whose persistent DNA binding interferes with DNA and RNA metabolism, causes DNA damage, and is hard to multiplex. We developed ZATELLITE, an AI-enabled tool to target endogenous repetitive sequences with fluorescently-tagged synthetic zinc fingers. ZATELLITE probes have key advantages over dCas9: they are smaller, easier to multiplex and, critically, they do not cause DNA damage or chromosomal abnormalities, even after long-term labeling. We generated a collection of ZATELLITE probes to label the centromeres of nearly all human chromosomes, enabling the capture of genome organization and karyotype alterations in real time in living cells. Finally, we show that ZATELLITE can be used for simultaneous labeling and epigenetic editing of centromeres. Thus, ZATELLITE is a non-toxic, versatile tool for genome visualization and manipulation.

cell biology↗

bioRxiv2023

Engineered transcription-associated Cas9 targeting in eukaryotic cells

DNA targeting Class 2 CRISPR-Cas effector nucleases, including the well-studied Cas9 proteins, evolved protospacer-adjacent motif (PAM) and guide RNA interactions that sequentially license their binding and cleavage activities at protospacer target sites. Both interactions are nucleic acid sequence specific but function constitutively; thus, they provide intrinsic spatial control over DNA targeting activities but naturally lack temporal control. Here we show that engineered Cas9 fusion proteins which bind to nascent RNAs near a protospacer can facilitate spatiotemporal coupling between transcription and DNA targeting at that protospacer: Transcription-associated Cas9 Targeting (TraCT). Engineered TraCT is enabled in eukaryotic yeast or human cells when suboptimal PAM interactions limit basal activity and when one or more nascent RNA substrates are still tethered to the actively transcribed target DNA in cis. Using yeast, we further show that this phenomenon can be applied for selective editing at one of two identical targets in distinct gene loci, or, in diploid allelic loci that are differentially transcribed. Our work demonstrates that temporal control over Cas9s targeting activity at specific DNA sites may be engineered without modifying Cas9s core domains and guide RNA components or their expression levels. More broadly, it establishes co-transcriptional RNA binding as a cis-acting mechanism that can conditionally stimulate CRISPR-Cas DNA targeting in eukaryotic cells.

bioengineering↗

bioRxiv2019

Evolutionary constraints in regulatory networks defined by partial order between phenotypes

Gene regulation networks allow organisms to adapt to diverse environmental niches. However, the constraints underlying the evolution of regulatory phenotypes remain ill-defined both theoretically and experimentally. Here, we show that the concept of partial order identifies such constraints, and test the predictions by experimentally evolving an engineered signal-integrating network in multiple environments. We find that populations: 1) expand in fitness space along the Pareto-optimal front predicted by conflicts in regulatory demands, by fine-tuning binding affinities within the network, 2) expand beyond this constraint by changes in the network structure, thus allowing access to new fitness domains. Strikingly, the constraint predictions are based on whether the network output increases or decreases in response to the different signals, and do not require information on the network architecture or underlying genetics. Overall, our findings show that limited knowledge on current regulatory phenotypes can provide predictions on future evolutionary constraints.

evolutionary biology↗