Biology subjects

Kobayashi-Kirschvink, K. J.

Publications and source records attributed to Kobayashi-Kirschvink, K. J..

6 recordsLinked to original sources

bioRxiv2025

Capture, Confine, Characterize: High-Throughput Dielectrophoresis-Based Single-Cell Microfluidics Platform to Analyze Mammalian and Yeast Cells Using Raman Spectroscopy

Single-cell analysis technologies are pivotal in unraveling complex biological mechanisms, yet existing platforms are often limited to sequencing-based end-point measurements, which fail to capture live cell dynamics. Here, we present a microfluidic- microelectronic device, the Microfluidic dielectrophoretic Arresting System (MiDAS) that employs dielectrophoresis (DEP) for high-throughput single-cell and droplet trapping in a compact array. We tested multiple trap geometries, including a 20 m-diameter DEP trap for polymer microbeads, fungal and mammalian cells, and a 40 m-diameter trap for water-in-oil droplets. The platform demonstrates broad sample compatibility, reliably immobilizing cells and beads of varying sizes. By integrating optical imaging and Raman spectroscopy, we enable rapid, non-destructive interrogation of individual cells with temporal resolution. We describe different modes of MiDAS operation to trap and manipulate single-cells or reverse emulsion droplets on demand, with applications in droplet microfluidics. Our MiDAS platforms simple fabrication, robust performance, and broad compatibility with diverse sample types position it as a versatile tool with transformative potential for single-cell analysis, offering researchers an innovative approach to interrogate cellular dynamics with unprecedented precision and throughput.

bioengineering↗

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

Episymbiotic bacterium induces intracellular lipid droplet production in its host bacteria

Saccharibacteria (formerly TM7) Nanosynbacter lyticus type strain TM7x exhibits a remarkably compact genome and an extraordinarily small cell size. This obligate epibiotic parasite forms a symbiotic relationship with its bacterial host, Schaalia odontolytica, strain XH001 (formerly Actinomyces odontolyticus strain XH001). Due to its limited genome size, TM7x possesses restrained metabolic capacities, predominantly living on the surface of its bacterial host to sustain this symbiotic lifestyle. To comprehend this intriguing, yet understudied interspecies interaction, a thorough understanding of the physical interaction between TM7x and XH001 is imperative. In this study, we employed super-resolution fluorescence imaging to investigate the physical association between TM7x and XH001. We found that the binding with TM7x led to a substantial alteration in the membrane fluidity of the host bacterium XH001. Unexpectedly, we revealed the formation of intracellular lipid droplets in XH001 when forming episymbiosis with TM7x, a feature not commonly observed in oral bacteria cells. The TM7x-induced LD accumulation in XH001 was further confirmed by label-free non-invasive Raman spectroscopy, which also unveiled additional phenotypical features when XH001 cells are physically associated with TM7x. Further exploration through culturing host bacterium XH001 alone under various stress conditions showed that LD accumulation was a general response to stress. Intriguingly, a survival assay demonstrated that the presence of LDs likely plays a protective role in XH001, enhancing its overall survival under adverse conditions. In conclusion, our study sheds new light on the intricate interaction between Saccharibacteria and its host bacterium, highlighting the potential benefit conferred by TM7x to its host, and further emphasizing the context-dependent nature of symbiotic relationships.

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↗

bioRxiv2021

Raman2RNA: Live-cell label-free prediction of single-cell RNA expression profiles by Raman microscopy

Single cell RNA-Seq (scRNA-seq) and other profiling assays have opened new windows into understanding the properties, regulation, dynamics, and function of cells at unprecedented resolution and scale. However, these assays are inherently destructive, precluding us from tracking the temporal dynamics of live cells, in cell culture or whole organisms. Raman microscopy offers a unique opportunity to comprehensively report on the vibrational energy levels of molecules in a label-free and non-destructive manner at a subcellular spatial resolution, but it lacks in genetic and molecular interpretability. Here, we developed Raman2RNA (R2R), an experimental and computational framework to infer single-cell expression profiles in live cells through label-free hyperspectral Raman microscopy images and multi-modal data integration and domain translation. We used spatially resolved single-molecule RNA-FISH (smFISH) data as anchors to link scRNA-seq profiles to the paired spatial hyperspectral Raman images, and trained machine learning models to infer expression profiles from Raman spectra at the single-cell level. In reprogramming of mouse fibroblasts into induced pluripotent stem cells (iPSCs), R2R accurately (r>0.96) inferred from Raman images the expression profiles of various cell states and fates, including iPSCs, mesenchymal-epithelial transition (MET) cells, stromal cells, epithelial cells, and fibroblasts. R2R outperformed inference from brightfield images, showing the importance of spectroscopic content afforded by Raman microscopy. Raman2RNA lays a foundation for future investigations into exploring single-cell genome-wide molecular dynamics through imaging data, in vitro and in vivo.

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↗