Direct Visualizationof Self-Mineralized Biohybrid-TriggeredApoptosis–Ferroptosis Synergistic Tumor Therapy by Cryo-SoftX‑ray Tomography

Bionano robots have been recognized as a tumor-selective and effective platform for therapeutic outcomes as they synergize the merits of living organisms and nanoparticles. Here, we construct a self-mineralized system (denoted as SO@FeS) by employing the facultative anaerobic bacterium Shewanella oneidensis MR-1 to biosynthesize FeS NPs for effective cancer therapy with dual cell death pathways. Biogenic FeS NPs are embedded into the cell surface with inherent photothermal conversion ability and low crystallinity and tend to simultaneously release Fe<sup>2+</sup> and hydrogen sulfide (H<sub>2</sub>S) in an acidic environment. As a result, the obtained SO@FeS hybrid can couple the versatility of the nanoparticles with the respiration and tumor-targeting capacities of bacterium, ultimately leading to the collaborative clearance of tumor cells. Specifically, cryo-soft X-ray tomography (cryo-SXT) is a near-native 3D imaging modality that directly displays the trafficking pathway of SO@FeS in cancer cells. More importantly, cryo-SXT captures the 3D maps of SO@FeS-initiated ferroptosis and apoptosis, as evidenced by the remodeling of cytoplasmic organelles. This work offers valuable theoretical insights from the perspective of organelle morphology, links subcellular reorganization and cell death pathways, and facilitates the design of living nanoplatforms that integrate multiple therapies.

Publication Details

Journal
Figshare
Published
2025-03-21
DOI
https://doi.org/10.1021/acsnano.5c00715.s001
Primary Topic
Cancer Research and Treatments
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Direct Visualizationof Self-Mineralized Biohybrid-TriggeredApoptosis–Ferroptosis Synergistic Tumor Therapy by Cryo-SoftX‑ray Tomography

Figshare
Cancer Research and Treatments
article

Direct Visualizationof Self-Mineralized Biohybrid-TriggeredApoptosis–Ferroptosis Synergistic Tumor Therapy by Cryo-SoftX‑ray Tomography

article en

Abstract

Bionano robots have been recognized as a tumor-selective and effective platform for therapeutic outcomes as they synergize the merits of living organisms and nanoparticles. Here, we construct a self-mineralized system (denoted as SO@FeS) by employing the facultative anaerobic bacterium Shewanella oneidensis MR-1 to biosynthesize FeS NPs for effective cancer therapy with dual cell death pathways. Biogenic FeS NPs are embedded into the cell surface with inherent photothermal conversion ability and low crystallinity and tend to simultaneously release Fe<sup>2+</sup> and hydrogen sulfide (H<sub>2</sub>S) in an acidic environment. As a result, the obtained SO@FeS hybrid can couple the versatility of the nanoparticles with the respiration and tumor-targeting capacities of bacterium, ultimately leading to the collaborative clearance of tumor cells. Specifically, cryo-soft X-ray tomography (cryo-SXT) is a near-native 3D imaging modality that directly displays the trafficking pathway of SO@FeS in cancer cells. More importantly, cryo-SXT captures the 3D maps of SO@FeS-initiated ferroptosis and apoptosis, as evidenced by the remodeling of cytoplasmic organelles. This work offers valuable theoretical insights from the perspective of organelle morphology, links subcellular reorganization and cell death pathways, and facilitates the design of living nanoplatforms that integrate multiple therapies.

Figshare
Good health and well-being
Openalex Percentile: Top 57%
Cancer Research and Treatments
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.