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nature-iconNature
clock-iconPUBLISHEDJune 17, 2020

When It Comes To Proteins, Life On Earth Has More In Common Than Previously Thought

Dr. Alfredo Carpineti headshot

Dr. Alfredo Carpineti

Alfredo has a PhD in Astrophysics and a Master's in Quantum Fields and Fundamental Forces from Imperial College London.

Space & Physics Editor

Alfredo has a PhD in Astrophysics and a Master's in Quantum Fields and Fundamental Forces from Imperial College London.View full profile

Alfredo has a PhD in Astrophysics and a Master's in Quantum Fields and Fundamental Forces from Imperial College London.

View full profile
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Proteins are crucial little molecules for life. They provide structure to cells, respond to stimuli, help chemical reactions, and much more. Each organism has its own proteome, a library of every single protein that can be assembled by its cells. Different species have wildly different proteomes, but new research has shown a surprising commonality: we all use proteins in the same way.

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As reported in Nature, the work looked at 100 different species and analyzed 349,164 proteins across these species. The team discovered that the largest share of these proteins either work in producing energy for the organism or they keep the balance of the internal conditions, a phenomenon called homeostasis. Organisms have evolved different proteins to perform similar functions.

“We have mapped the proteins, together called the proteome of 100 different species. And it is obvious that they are extremely different. At the same time, though, they have more in common than we thought. In all these life forms, a large share of the proteins focus on metabolism and on maintaining a protein balance,” senior author Professor Matthias Mann, from the Max Planck Institute of Biochemistry, said in a statement.

The team has employed mass spectrometry to study all the proteins created by the 100 species in question. In the past, many proteins were just assumed to exist based on the genetic code of the species in question. The new work provides experimental data on these proteins, doubling the number of confirmed proteins among the species. The team also used available datasets of known proteins and used machine learning algorithms to reveal correlations within the new dataset.

“Our work connecting quantitative mass spectrometry-based proteomics with database resources has resulted in a data set of eight million data points with 53 million interconnections. We made all the data publicly available, enabling other researchers to use it to identify new correlations. New technologies enabled by machine learning are on the rise and we expect those to benefit from the large and uniform dataset we provide publicly,” added lead author and PhD student Johannes Mueller, also from the Max Planck Institute of Biochemistry.  

All the data used in the project is publicly available and can be downloaded at www.proteomesofife.org.


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