Back

Life Under Pressure: Dissection of Cross-Phyla Metazoan Responses to Extreme Hydrostatic Pressure Reveals Pressure-Protective Heat Shock Acclimation

Corkins, M. E.; Bhattad, A.; Hao, T.; Ford, M. P.; Colin, S. E.; Costello, J. H. H.; Davidson, L.

2026-07-10 evolutionary biology
10.64898/2026.07.06.736787 bioRxiv
Show abstract

The deepest ocean is one of the most extreme environments for life on our planet, combining near-freezing temperatures, low oxygen levels, and hydrostatic pressures reaching 111 MPa (1100 atm). Extreme pressures are predicted to alter many aspects of biology, including the physical properties of biological hydrogels, protein structure, and the solubility of gases in water. How organisms have adapted to live in these conditions is poorly understood. Studying these organisms in situ is difficult and requires specialized deep-sea equipment capable of withstanding the extreme pressure; raising these organisms in captivity is also challenging due to their extreme habitat requirements. Given these difficulties in studying deep-sea organisms, we set out to identify the problems shallow-dwelling organisms face due to increased pressure. These can provide insights into how organisms tolerate life in the deepest parts of the ocean. This project aims to take embryos of the shallow-dwelling aquatic organism Xenopus laevis, determine how surface-dwelling organisms fail under high hydrostatic pressure, and identify a means to survive this deadly pressure. We have designed a system to expose different embryonic stages of X. laevis to high pressures and observe its effects. After identifying the limits of survivability, we sought to understand how these embryos can acclimate to changing pressures. Comparative RNA-seq and cross-species analyses revealed a conserved, pressure-induced transcriptional response across phyla, with the heat shock pathway among the most strongly activated. Pre-activation of this pathway via prior pressure or other stressors enhances survival under otherwise lethal hydrostatic conditions.

Matching journals

The top 8 journals account for 50% of the predicted probability mass.

1
PLOS ONE
5266 papers in training set
Top 13%
14.8%
2
Philosophical Transactions of the Royal Society B: Biological Sciences
72 papers in training set
Top 0.1%
8.7%
3
Scientific Reports
3612 papers in training set
Top 11%
6.6%
4
Proceedings of the Royal Society B: Biological Sciences
393 papers in training set
Top 1%
5.4%
5
iScience
1154 papers in training set
Top 3%
5.1%
6
Proceedings of the National Academy of Sciences
2444 papers in training set
Top 12%
4.2%
7
eLife
5828 papers in training set
Top 30%
4.0%
8
Ecology and Evolution
267 papers in training set
Top 2%
3.4%
50% of probability mass above
9
Journal of Experimental Biology
259 papers in training set
Top 1%
3.2%
10
Royal Society Open Science
214 papers in training set
Top 2%
2.3%
11
Frontiers in Ecology and Evolution
69 papers in training set
Top 0.9%
2.3%
12
Molecular Ecology
336 papers in training set
Top 2%
1.7%
13
Cell Stress and Chaperones
11 papers in training set
Top 0.1%
1.7%
14
Genome Biology and Evolution
338 papers in training set
Top 2%
1.6%
15
PeerJ
308 papers in training set
Top 6%
1.6%
16
Current Biology
665 papers in training set
Top 7%
1.5%
17
Journal of Experimental Zoology Part B: Molecular and Developmental Evolution
22 papers in training set
Top 0.3%
1.3%
18
Communications Biology
993 papers in training set
Top 19%
1.3%
19
Molecular Biology and Evolution
542 papers in training set
Top 4%
1.1%
20
BMC Evolutionary Biology
18 papers in training set
Top 0.2%
1.0%
21
Protein Science
246 papers in training set
Top 3%
1.0%
22
Biology Open
156 papers in training set
Top 3%
1.0%
23
Frontiers in Marine Science
62 papers in training set
Top 0.9%
1.0%
24
ISME Communications
120 papers in training set
Top 2%
0.9%
25
Ecology Letters
135 papers in training set
Top 2%
0.9%
26
Science Advances
1243 papers in training set
Top 31%
0.8%
27
Evolution Letters
85 papers in training set
Top 2%
0.8%
28
BMC Biology
265 papers in training set
Top 6%
0.8%
29
mBio
833 papers in training set
Top 11%
0.8%
30
Nature Communications
5641 papers in training set
Top 57%
0.8%