Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

Human 3D cellular model of hypoxic brain injury of prematurity

Abstract

Owing to recent medical and technological advances in neonatal care, infants born extremely premature have increased survival rates1,2. After birth, these infants are at high risk of hypoxic episodes because of lung immaturity, hypotension and lack of cerebral-flow regulation, and can develop a severe condition called encephalopathy of prematurity3. Over 80% of infants born before post-conception week 25 have moderate-to-severe long-term neurodevelopmental impairments4. The susceptible cell types in the cerebral cortex and the molecular mechanisms underlying associated gray-matter defects in premature infants remain unknown. Here we used human three-dimensional brain-region-specific organoids to study the effect of oxygen deprivation on corticogenesis. We identified specific defects in intermediate progenitors, a cortical cell type associated with the expansion of the human cerebral cortex, and showed that these are related to the unfolded protein response and changes. Moreover, we verified these findings in human primary cortical tissue and demonstrated that a small-molecule modulator of the unfolded protein response pathway can prevent the reduction in intermediate progenitors following hypoxia. We anticipate that this human cellular platform will be valuable for studying the environmental and genetic factors underlying injury in the developing human brain.

Access options

Rent or Buy article

Get time limited or full article access on ReadCube.

from$8.99

All prices are NET prices.

Fig. 1: Human cellular model for studying changes in oxygen tension in hCS.
Fig. 2: Proportion of TBR2+ cells in hCS exposed to low oxygen.
Fig. 3: Unfolded protein response pathway in hCS exposed to low oxygen.
Fig. 4: Validation in primary human cortical tissue in vitro.

Data availability

Gene expression data are available in the Gene Expression Omnibus (GEO) under accession number GSE112137. The data that support the findings of this study are available on request from the corresponding author.

References

  1. 1.

    Penn, A. A., Gressens, P., Fleiss, B., Back, S. A. & Gallo, V. Controversies in preterm brain injury. Neurobiol. Dis 92, 90–101 (2016).

    Article  Google Scholar 

  2. 2.

    Volpe, J. J. Brain injury in premature infants: a complex amalgam of destructive and developmental disturbances. Lancet Neurol. 8, 110–124 (2009).

    Article  Google Scholar 

  3. 3.

    Volpe, J. J. The encephalopathy of prematurity—brain injury and impaired brain development inextricably intertwined. Semin. Pediatr. Neurol. 16, 167–178 (2009).

    Article  Google Scholar 

  4. 4.

    Jarjour, I. T. Neurodevelopmental outcome after extreme prematurity: a review of the literature. Pediatr. Neurol. 52, 143–152 (2015).

    Article  Google Scholar 

  5. 5.

    Salmaso, N., Jablonska, B., Scafidi, J., Vaccarino, F. M. & Gallo, V. Neurobiology of premature brain injury. Nat. Neurosci. 17, 341–346 (2014).

    CAS  Article  Google Scholar 

  6. 6.

    Sousa, A. M. M., Meyer, K. A., Santpere, G., Gulden, F. O. & Sestan, N. Evolution of the human nervous system function, structure, and development. Cell 170, 226–247 (2017).

    CAS  Article  Google Scholar 

  7. 7.

    Pasca, S. P. The rise of three-dimensional human brain cultures. Nature 553, 437–445 (2018).

    CAS  Article  Google Scholar 

  8. 8.

    Sloan, S. A., Andersen, J., Pasca, A. M., Birey, F. & Pasca, S. P. Generation and assembly of human brain region-specific three-dimensional cultures. Nat. Protoc. 13, 2062–2085 (2018).

    CAS  Article  Google Scholar 

  9. 9.

    Pasca, A. M. et al. Functional cortical neurons and astrocytes from human pluripotent stem cells in 3D culture. Nat. Methods 12, 671–678 (2015).

    CAS  Article  Google Scholar 

  10. 10.

    Yoon, S. J. et al. Reliability of human cortical organoid generation. Nat. Methods 16, 75–78 (2019).

    CAS  Article  Google Scholar 

  11. 11.

    Sloan, S. A. et al. Human astrocyte maturation captured in 3D cerebral cortical spheroids derived from pluripotent stem cells. Neuron 95, 779–790 (2017).

    CAS  Article  Google Scholar 

  12. 12.

    Arshad, A. et al. Extended production of cortical interneurons into the third trimester of human gestation. Cereb. Cortex 26, 2242–2256 (2016).

    Article  Google Scholar 

  13. 13.

    Zecevic, N., Chen, Y. & Filipovic, R. Contributions of cortical subventricular zone to the development of the human cerebral cortex. J. Comp. Neurol. 491, 109–122 (2005).

    Article  Google Scholar 

  14. 14.

    Malik, S. et al. Neurogenesis continues in the third trimester of pregnancy and is suppressed by premature birth. J. Neurosci. 33, 411–423 (2013).

    CAS  Article  Google Scholar 

  15. 15.

    Carreau, A., El Hafny-Rahbi, B., Matejuk, A., Grillon, C. & Kieda, C. Why is the partial oxygen pressure of human tissues a crucial parameter? Small molecules and hypoxia. J. Cell. Mol. Med. 15, 1239–1253 (2011).

    CAS  Article  Google Scholar 

  16. 16.

    Miller, J. A. et al. Transcriptional landscape of the prenatal human brain. Nature 508, 199–206 (2014).

    CAS  Article  Google Scholar 

  17. 17.

    Bershteyn, M. et al. Human iPSC-derived cerebral organoids model cellular features of lissencephaly and reveal prolonged mitosis of outer radial glia. Cell Stem Cell 20, 435–449 (2017).

    CAS  Article  Google Scholar 

  18. 18.

    Wagenfuhr, L., Meyer, A. K., Braunschweig, L., Marrone, L. & Storch, A. Brain oxygen tension controls the expansion of outer subventricular zone-like basal progenitors in the developing mouse brain. Development 142, 2904–2915 (2015).

    Article  Google Scholar 

  19. 19.

    Stuart, J. M., Segal, E., Koller, D. & Kim, S. K. A gene-coexpression network for global discovery of conserved genetic modules. Science 302, 249–255 (2003).

    CAS  Article  Google Scholar 

  20. 20.

    Voineagu, I. et al. Transcriptomic analysis of autistic brain reveals convergent molecular pathology. Nature 474, 380–384 (2011).

    CAS  Article  Google Scholar 

  21. 21.

    Zhang, B. & Horvath, S. A general framework for weighted gene co-expression network analysis. Stat. Appl. Genet. Mol. Biol. 4, Article17 (2005).

    Article  Google Scholar 

  22. 22.

    Wang, M. & Kaufman, R. J. Protein misfolding in the endoplasmic reticulum as a conduit to human disease. Nature 529, 326–335 (2016).

    CAS  Article  Google Scholar 

  23. 23.

    Fels, D. R. & Koumenis, C. The PERK/eIF2α/ATF4 module of the UPR in hypoxia resistance and tumor growth. Cancer Biol. Ther. 5, 723–728 (2006).

    CAS  Article  Google Scholar 

  24. 24.

    Laguesse, S. et al. A dynamic unfolded protein response contributes to the control of cortical neurogenesis. Dev. Cell 35, 553–567 (2015).

    CAS  Article  Google Scholar 

  25. 25.

    Sidrauski, C. et al. Pharmacological brake-release of mRNA translation enhances cognitive memory. eLife 2, e00498 (2013).

    Article  Google Scholar 

  26. 26.

    Sidrauski, C. et al. Pharmacological dimerization and activation of the exchange factor eIF2B antagonizes the integrated stress response. eLife 4, e07314 (2015).

    Article  Google Scholar 

  27. 27.

    Zyryanova, A. F. et al. Binding of ISRIB reveals a regulatory site in the nucleotide exchange factor eIF2B. Science 359, 1533–1536 (2018).

    CAS  Article  Google Scholar 

  28. 28.

    Wang, H. et al. Tunicamycin-induced unfolded protein response in the developing mouse brain. Toxicol. Appl. Pharmacol. 283, 157–167 (2015).

    CAS  Article  Google Scholar 

  29. 29.

    Javaherian, A. & Kriegstein, A. A stem cell niche for intermediate progenitor cells of the embryonic cortex. Cereb. Cortex 19 (Suppl 1), i70–i77 (2009).

    Article  Google Scholar 

  30. 30.

    Ortega, J. A., Sirois, C. L., Memi, F., Glidden, N. & Zecevic, N. Oxygen levels regulate the development of human cortical radial glia cells. Cereb. Cortex 27, 3736–3751 (2017).

    PubMed  Google Scholar 

  31. 31.

    Pollen, A. A. et al. Molecular identity of human outer radial glia during cortical development. Cell 163, 55–67 (2015).

    CAS  Article  Google Scholar 

  32. 32.

    Godin, J. D., Creppe, C., Laguesse, S. & Nguyen, L. Emerging roles for the unfolded protein response in the developing nervous system. Trends Neurosci. 39, 394–404 (2016).

    CAS  Article  Google Scholar 

  33. 33.

    Jantzie, L. L. & Robinson, S. Preclinical models of encephalopathy of prematurity. Dev. Neurosci. 37, 277–288 (2015).

    CAS  Article  Google Scholar 

  34. 34.

    Amin, N. D. & Pasca, S. P. Building models of brain disorders with three-dimensional organoids. Neuron 100, 389–405 (2018).

    CAS  Article  Google Scholar 

  35. 35.

    Soothill, P. W., Nicolaides, K. H., Rodeck, C. H. & Gamsu, H. Blood gases and acid-base status of the human second-trimester fetus. Obstet. Gynecol. 68, 173–176 (1986).

    CAS  PubMed  Google Scholar 

  36. 36.

    Lacaille, H. et al. Impaired interneuron development in a novel model of neonatal brain injury. eNeuro 6, 0300–0318 (2019).

    Article  Google Scholar 

  37. 37.

    Robinson, S., Li, Q., Dechant, A. & Cohen, M. L. Neonatal loss of γ-aminobutyric acid pathway expression after human perinatal brain injury. J. Neurosurg. 104, 396–408 (2006).

    PubMed  PubMed Central  Google Scholar 

  38. 38.

    Paredes, M. F. et al. Extensive migration of young neurons into the infant human frontal lobe. Science 354, aaf7073 (2016).

    Article  Google Scholar 

  39. 39.

    Birey, F. et al. Assembly of functionally integrated human forebrain spheroids. Nature 545, 54–59 (2017).

    CAS  Article  Google Scholar 

  40. 40.

    Marton, R. M. et al. Differentiation and maturation of oligodendrocytes in human three-dimensional neural cultures. Nat. Neurosci. 22, 484–491 (2019).

    CAS  Article  Google Scholar 

  41. 41.

    Pașca, S. P. et al. Using iPSC-derived neurons to uncover cellular phenotypes associated with Timothy syndrome. Nat. Med. 17, 1657–1662 (2011).

    Article  Google Scholar 

  42. 42.

    Lui, J. H. et al. Radial glia require PDGFD–PDGFRβ signalling in human but not mouse neocortex. Nature 515, 264–268 (2014).

    CAS  Article  Google Scholar 

  43. 43.

    Dobin, A. et al. STAR: ultrafast universal RNA-seq aligner. Bioinformatics 29, 15–21 (2013).

    CAS  Article  Google Scholar 

  44. 44.

    Anders, S., Pyl, P. T. & Huber, W. HTSeq—a Python framework to work with high-throughput sequencing data. Bioinformatics 31, 166–169 (2015).

    CAS  Article  Google Scholar 

  45. 45.

    Hansen, K. D., Irizarry, R. A. & Wu, Z. Removing technical variability in RNA-seq data using conditional quantile normalization. Biostatistics 13, 204–216 (2012).

    Article  Google Scholar 

  46. 46.

    McCarthy, D. J., Chen, Y. & Smyth, G. K. Differential expression analysis of multifactor RNA-seq experiments with respect to biological variation. Nucleic Acids Res. 40, 4288–4297 (2012).

    CAS  Article  Google Scholar 

  47. 47.

    Robinson, M. D., McCarthy, D. J. & Smyth, G. K. edgeR: a Bioconductor package for differential expression analysis of digital gene expression data. Bioinformatics 26, 139–140 (2010).

    CAS  Article  Google Scholar 

  48. 48.

    Young, M. D., Wakefield, M. J., Smyth, G. K. & Oshlack, A. Gene ontology analysis for RNA-seq: accounting for selection bias. Genome Biol. 11, R14 (2010).

    Article  Google Scholar 

  49. 49.

    Chen, J., Bardes, E. E., Aronow, B. J. & Jegga, A. G. ToppGene Suite for gene list enrichment analysis and candidate gene prioritization. Nucleic Acids Res. 37, W305–W311 (2009).

    CAS  Article  Google Scholar 

  50. 50.

    Langfelder, P. & Horvath, S. WGCNA: an R package for weighted correlation network analysis. BMC Bioinformatics 9, 559 (2008).

    Article  Google Scholar 

Download references

Acknowledgements

We thank W.E. Benitz, D.K. Stevenson, V. K. Bhutani and U. Francke for valuable scientific advice and discussions. This work was supported by the US National Institute of Health (NIH) BRAINS Award (MH107800), the MQ Fellow Award, the NYSCF Robertson Stem Cell Investigator Award, the Stanford Neurosciences Institute’s Human Brain Organogenesis Program and the Brain Rejuvenation Project, Stanford Bio-X, the Kwan Research Fund and the California Institute of Regenerative Medicine (CIRM) (to S.P.P.); the UCSF Weill Institute for Neurosciences (startup funds to A.J.W.); NIH R01MH108659 and R01MH108659 (to T.D.P.); and the NIH K12-HD000850 (Pediatric Scientist Development Program), the Association of Medical School Pediatric Department Chairs (AMSPDC) and Stanford Maternal and Child Health Research Institute Fellowship (to A.M.P.).

Author information

Affiliations

Authors

Contributions

A.M.P. and J-Y. P. performed the neural differentiation and hypoxia experiments. A.M.P., J.-Y.P., H.-W.S., O.R., Q.Q., R.K., A.J.W., R.O. and T.D.P. carried out experiments, analyzed data or contributed critical reagents. A.M.P. and S.P.P. wrote the manuscript with input from all authors. S.P.P. supervised the work.

Corresponding author

Correspondence to Sergiu P. Pașca.

Ethics declarations

Competing interests

Stanford University has filed a provisional patent application that covers the generation of region-specific brain organoids from pluripotent stem cells (US Application Serial No. 15/158,408) (A.M.P. and S.P.P.).

Additional information

Publisher’s note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Extended data

Extended Data Fig 1 Oxygen tension and c-CAS3 in hCS following hypoxia.

a, Oxygen tension (\(P{\mathrm{o}_2}\), mm Hg) measurements inside hCS from Fig. 1b, shown as a function of depth (values for each hCS was normalized as a function of its radius) (n = 6 hCS for 21% O2 and n = 7 hCS for <1% O2; from three hiPS cell lines). Shaded area indicates s.e.m. b,c, Representative western blots (b) and quantification (c) of c-CAS3 in hCS after 24 h and 48 h of exposure to <1% O2 and at 72 h after reoxygenation (one-way ANOVA, F3,6 = 1.56, P = 0.29); normalized to β-actin (n = 3 differentiated hiPS cell lines with two hCS per condition; each line is shown in a different color). Western blots were cropped to show the relevant bands; molecular weight markers are indicated on the left (in kDa). See Supplementary Table 2 for quantifications. Uncropped blots are available as source data. Data are the mean ± s.e.m. Individual values are indicated by dots. Source data

Extended Data Fig 2 Gene expression changes in hCS following oxygen deprivation.

a, Hierarchical clustering of RNA-seq data showing clustering of samples on the basis of exposure to oxygen concentration. Samples (n = 24) from hCS differentiated from three hiPS cell lines were collected after 24 h or 48 h exposure to <1% O2, as well as 72 h after reoxygenation. We clustered on the basis of all differentially expressed genes identified (1,754 unique genes). Clustering with all expressed genes results in a similar dendrogram (data not shown). b,c, Validation by qPCR of hypoxia-related genes PLOD2 (two-tailed paired t-test, **P = 0.006), PFKP (two-tailed paired t-test, **P = 0.008), PDK1 (two-tailed paired t-test, ***P = 0.0005) and IGFBP2 (two-tailed paired t-test, ***P = 0.0002), and cortical progenitor and cell cycle-related genes EOMES (also known as TBR2) (two-tailed paired t-test, **P = 0.006), EMX1 (two-tailed paired t-test, *P = 0.02), ASPM (two-tailed paired t-test, **P = 0.002) and CENPF (two-tailed paired t-test, ****P < 0.0001), which were identified in the RNA-seq analysis (n = 4 hiPS cell lines differentiated; each line is shown in a different color; expression normalized to the RPL13a housekeeping gene). Data are the mean ± s.e.m. Individual values are indicated by dots.

Extended Data Fig 3 Immunocytochemistry quantifications in hCS following oxygen deprivation.

a, Quantification of the density of Hoechst+ cells in proliferative areas in hCS after 48 h exposure to <1% O2. Data are shown as averages across individual hCS proliferative zones from three hiPS cell lines per condition (left, n = 21 areas for 21% O2 versus n = 18 areas for < 1% O2; two-tailed Mann–Whitney test, P = 0.09) and as averages across different hiPS cell lines (right, n = 3 hiPS cell lines, two-tailed Wilcoxon test, P = 0.50). b, Quantification of the percentage of PAX6+ cells in whole cryosections of hCS after 48 h exposure to <1% O2. Data are shown as averages across whole sections of hCS from four hiPS cell lines per condition (left, n = 25 sections for 21% O2 versus n = 23 sections for <1% O2; two-tailed unpaired t-test, P = 0.44) or as averages across different hiPS cell lines (right, n = 4 hiPS cell lines; two-tailed Wilcoxon test, P = 0.25). c, Quantification of the percentage of TBR2+ cells in whole cryosections of hCS after 48 h exposure to <1% O2. Data are shown as averages across whole sections of hCS from four hiPS cell lines per condition (left, n = 25 sections for 21% O2 versus n = 27 sections for <1% O2; two-tailed Mann–Whitney U test, ****P < 0.0001) or as averages across different hiPS cell lines (right, n = 4 hiPS cell lines; two-tailed paired t-test, *P = 0.03; each line is shown in a different color). d Quantification of the percentage of cells coexpressing SOX2 and TBR2 in cryosections of hCS after 48 h exposure to <1% O2. Data are shown as averages across individual hCS cryosections from four hiPS cell lines per condition (left, n = 10 sections for 21% O2 and n = 12 sections for <1% O2; two-tailed unpaired t-test, P = 0.82; from four hiPS cell lines) or as averages across different hiPS cell lines (right, n = 3 hiPS cell lines; two-tailed paired t-test, P = 0.06; each line is shown in a different color). Data are the mean ± s.e.m.; individual values are indicated by dots.

Extended Data Fig 4 Transcriptome analyses in hCS following oxygen deprivation.

a, Hierarchical clustering of WGCNA modules identified in the RNA-seq data. Clustering is based on the module eigengenes (average expression profile of all module genes). The turquoise and blue modules are very similar in overall eigengene expression pattern. b, Statistical significance for correlation of each module with exposure to low oxygen (bars are labeled by the color of the modules). The blue and turquoise modules are highly associated with exposure (FDR ≤ 0.05). c, Enrichment for pathways in the turquoise and blue modules (bars are labeled by the color of the modules in which they are enriched). Only pathways with Bonferroni-corrected FDR < 1 × 10−4 are shown. d, Validation by qPCR of the UPR-related genes PERK (two-tailed paired t-test, *P = 0.03), ATF3 (two-tailed paired t-test, *P = 0.03) and XBP1s (two-tailed paired t-test, *P = 0.04), which were identified in the RNA-seq analysis (n = 4 hiPS cell lines; each line is shown in a different color; expression normalized to the RPL13a housekeeping gene). Data are the mean ± s.e.m.; individual values are indicated by dots.

Extended Data Fig 5 Quantifications in hCS following oxygen deprivation or tunicamycin exposure.

a, Quantification of the percentage of cells coexpressing ATF4 and PAX6 in cryosections of hCS after 48 h exposure to <1% O2 in the presence or absence of 10 nM ISRIB. Data are shown as averages across individual hCS cryosections from three hiPS cell lines per condition (left, n = 7 sections for 21% O2 and n = 7 sections for <1% O2 versus n = 7 sections for <1% O2 + ISRIB; one-way ANOVA F2,18 = 1.37, P = 0.27; Dunnett’s multiple-comparison test versus 21% O2, P = 0.70, P = 0.54), or as averages across different hiPS cell lines (right, n = 3 hiPS cell lines; one-way ANOVA, F2,4 = 4.64, P = 0.09; Dunnett’s multiple-comparison test versus 21% O2, P = 0.48, P = 0.21; each line is shown in a different color). b, Quantification of the density of PAX6+ cells in hCS after exposure for 48 h to 1.2 μM tunicamycin in the presence or absence of 10 nM ISRIB. Data are shown as averages across individual hCS proliferative zones from three hiPS cell lines per condition (left, n = 22 areas for 21% O2, n = 23 areas for tunicamycin, n = 24 areas for tunicamycin + ISRIB; one-way ANOVA, F2,66 = 1.57, P = 0.21; Dunnett’s multiple-comparison test versus 21% O2, P = 0.37, P = 0.15), or as averages across different hiPS cell lines (right, n = 3 hiPS cell lines; Friedman’s test, P = 0.19; Dunnett’s multiple-comparison test versus 21% O2, P = 0.20, P = 0.08; each line is shown in a different color). c, Percentage of TBR2+ cells that coexpress c-CAS3 in whole cryosections of hCS maintained in 21% O2 or exposed to <1% O2 for 48 h. (two-tailed Mann–Whitney U test, P > 0.99; n = 8 cryosections from two hiPS cell lines). d, Quantification of the percentage of cells coexpressing p27 and PAX6 in cryosections of hCS after 48 h exposure to <1% O2 in the presence or absence of 10 nM ISRIB. Data are shown as averages across individual hCS cryosections from four hiPS cell lines per condition (left, n = 10 sections for 21% O2 versus n = 10 sections for 1% O2 and n = 9 sections for <1% O2 + ISRIB; one-way ANOVA, F2,26 = 0.10, P = 0.90 Dunnett’s multiple-comparison test versus 21% O2, P = 0.88, P = 0.90), or as averages across different hiPS cell lines (right, n = 4 hiPS cell lines; one-way ANOVA F2,6 = 0.30, P = 0.74; Dunnett’s multiple-comparison test versus 21% O2, P = 0.67, P = 0.94; each line is shown in a different color). e, Representative images of cells coexpressing TBR2, Ki67 and PH3 in cryosections of hCS. White arrows show examples of cells that are TBR2+PH3+ or TBR2+Ki67+. f, Quantification of the percentage of cells coexpressing Ki67 and TBR2 in cryosections of hCS after 48 h exposure to <1% O2. Data are shown as averages across individual hCS cryosections from three hiPS cell lines per condition (left, n = 6 sections for 21% O2 versus n = 6 sections for <1% O2; two-tailed unpaired t-test, P = 0.91) or as averages across different hiPS cell lines (n = 3 hiPS cell lines; two-tailed paired t-test, P = 0.91; each line is shown in a different color). g, Quantification of the percentage of cells coexpressing PH3 and TBR2 in cryosections of hCS after 48 h exposure to <1% O2. Data are shown as averages across individual hCS cryosections from three hiPS cell lines per condition (n = 6 sections for 21% O2 versus n = 6 sections for <1% O2; two-tailed unpaired t-test, P = 0.55) or as averages across different hiPS cell lines (right, n = 3 hiPS cell lines; two-tailed paired t-test, P = 0.56; each line is shown in a different color). Data are the mean ± s.e.m.; individual values are indicated by dots.

Supplementary information

Supplementary Information

Supplementary Tables 1, 2 and 4

Reporting Summary

Supplementary Table 3

List of differentially expressed genes (RNA-seq)

Source data

Source Data Fig. 1

Uncropped western blots.

Source Data Fig. 4

Uncropped western blots.

Source Data Extended Data Fig. 1

Uncropped western blots

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Pașca, A.M., Park, JY., Shin, HW. et al. Human 3D cellular model of hypoxic brain injury of prematurity. Nat Med 25, 784–791 (2019). https://doi.org/10.1038/s41591-019-0436-0

Download citation

Further reading

Search

Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing