Revealing global stoichiometry conservation architecture in cells from Raman spectral patterns
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Abstract
Changes in molecular profiles in cells are often correlated and suggested to be effectively low dimensional. However, what kinds of biological principles entail such constraints remains elusive. Here, we measure Raman scattering light from Escherichia coli cells under diverse conditions, whose spectral patterns convey their comprehensive molecular composition. We reveal that dimension-reduced Raman spectra can predict condition-dependent proteome profiles. Quantitative analysis of the Raman-proteome correspondence characterizes a low-dimensional hierarchical stoichiometry-conserving proteome structure. The network centrality of each gene in the stoichiometry conservation relations is biologically significant, correlating with its essentiality and evolutionary conservation. Furthermore, stoichiometry-conserving core components obey growth law and ensure homeostasis across conditions, whereas peripheral stoichiometry-conserving components enable adaptation to specific conditions. Mathematical analysis reveals that the stoichiometric architecture is reflected in major changes in Raman spectral patterns. These results uncover coordination of global stoichiometric balance in cells and demonstrate that vibrational spectroscopy can decipher such biological constraints beyond statistical or machine-learning inference of cellular states.
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We measured Raman spectra of single cells
It would be nice to have a more expansive description of how Raman spectra (optical layout of apparatus, single cell capture, etc...) were collected.
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Here we show that proteome profiles
This is an extremely compelling result and you provide significant evidence that Raman spectra and proteomes can be related. Such a result has extremely compelling implications for the possible uses of Raman spectroscopy for predicting proteome profiles. Here you work with proteomic data from another group and collect raman spectra from single bacterial cells grown in conditions that are as close as possible to the original conditions. It would be even more compelling if you could do this analysis, capture the Raman spectra, then validate (for at least some growth conditions) the proteomic profile matches that which was previously published.
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