Biology subjects

Kamei, K.-i. F.

Publications and source records attributed to Kamei, K.-i. F..

4 recordsLinked to original sources

bioRxiv2025

Global propagation of genetic perturbation effects through genome-wide stoichiometry conservation architecture

Understanding how specific genetic changes lead organisms to different phenotypes is the cornerstone of genetics. However, even a single gene perturbation can cause global changes in gene expression profiles. Consequently, predicting which genes will be affected by a particular genetic perturbation remains a challenge. Here, we analyze changes in genome-wide gene expression profiles caused by single-gene perturbations in bacterial, worm, and human cells and show a simple rule that genes that intrinsically maintain the ratio of expression levels (stoichiometry) with a perturbed gene are more likely to be affected when it is deleted or inactivated. Furthermore, deleting a gene that maintains their stoichiometry with more genes tend to affect the expression levels of other genes genome-wide. Stoichiometry-conserving gene clusters can be found beyond local transcriptional regulatory units and metabolic pathways. Thus, the effects of genetic perturbations are propagated to other genes through a multi-level stoichiometry-conserving architecture in cells.

systems biology↗

bioRxiv2024

Raman spectra identify heterogeneous vancomycin resistance and transcriptomes of Staphylococcus aureus

Staphylococcus aureus is a pathogenic bacterium that has caused multiple epidemics linked with the emergence of new antibiotic resistance. Vancomycin is the first-line antibiotic to treat methicillin-resistant S. aureus (MRSA) infections. However, several types of vancomycin-non-susceptible MRSA strains have been isolated from patients to date. Rapid assessment of their resistance levels and underlying molecular profiles is crucial for preventing their spread and counteracting resistance; however, the broad resistance spectrum and the diversity of genetic changes have impeded this practice. Here, we demonstrate that the vancomycin resistance levels of various MRSA strains can be determined using dimension-reduced Raman spectra obtained from single cells. The transcriptome profiles of the different strains can also be predicted from their dimensionally reduced Raman spectra by simple linear regression. This Raman-transcriptome correspondence allows us to map the transcriptome components onto dimension-reduced Raman space and characterize groups of genes associated with different phenotypes. Furthermore, single-cell Raman spectra predicted a cell strain with greater phenotypic heterogeneity, which was confirmed by single-cell growth analysis. Overall, our results demonstrate the efficacy of Raman spectroscopy in identifying resistant phenotypes, their associated gene expression features, and intrapopulation phenotypic heterogeneity.

microbiology↗

bioRxiv2023

Raman spectra and gene expression correspondences reveal global stoichiometry conservation architecture in cells

Cells can adapt to various environments by changing their biomolecular profiles while maintaining physiological homeostasis. What organizational principles in cells enable the simultaneous realization of adaptability and homeostasis? To address this question, 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 correlates with its essentiality and evolutionary conservation, and these correlations are preserved from bacteria to human cells. 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 stoichiometrically constrained 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.

genomics↗

bioRxiv2017

Transcriptomes and Raman spectra are linked linearly through a shared low-dimensional subspace

Raman spectroscopy is an imaging technique that can reflect whole-cell molecular compositions in vivo, and has been applied recently in cell biology to characterize different cell types and states. However, due to the complex molecular compositions and spectral overlaps, the interpretation of cellular Raman spectra have remained unclear. In this report, we compared cellular Raman spectra to transcriptomes of Schizosaccharomyces pombe and Escherichia coli, and provide firm evidence that they can be computationally connected and interpreted. Specifically, we find that the dimensions of high-dimensional Raman spectra and transcriptomes measured by RNA-seq can be effectively reduced and connected linearly through a shared low-dimensional subspace. Accordingly, we were able to reconstruct global gene expression profiles by applying the calculated transformation matrix to Raman spectra, and vice versa. Strikingly, highly expressed ncRNAs contributed to the Raman-transcriptome linear correspondence more significantly than mRNAs in S. pombe, which implies their major role in coordinating molecular compositions. This compatibility between whole-cell Raman spectra and transcriptomes marks an important and promising step towards establishing spectroscopic live-cell omics studies.

systems biology↗