The extension of the amyloid hypothesis to include non-protein metabolite assemblies invokes a paradigm for the pathology of inborn error of metabolism disorders. However, a direct demonstration of the assembly of metabolite amyloid-like structures has so far been provided only in vitro. Here, we established an in vivo model of adenine self-assembly in yeast, in which toxicity is associated with intracellular accumulation of the metabolite. Using a strain blocked in the enzymatic pathway downstream to adenine, we observed a non-linear dose-dependent growth inhibition. Both the staining with an indicative amyloid dye and anti-adenine assemblies antibodies demonstrated the accumulation of adenine amyloid-like structures, which were eliminated by lowering the supplied adenine levels. Treatment with a polyphenol inhibitor reduced the occurrence of amyloid-like structures while not affecting the dramatic increase in intracellular adenine concentration, resulting in inhibition of cytotoxicity, further supporting the notion that toxicity is triggered by adenine assemblies.

Fungal cell walls are medically important since they represent a drug target site for antifungal medication. So far there is no method to directly visualize structurally similar cell wall components such as α-glucan, β-glucan and mannan with high specificity, especially in a label-free manner. In this study, we have developed a Raman spectroscopy based molecular imaging method and combined multivariate curve resolution analysis to enable detection and visualization of multiple polysaccharide components simultaneously at the single cell level. Our results show that vegetative cell and ascus walls are made up of both α- and β-glucans while spore wall is exclusively made of α-glucan. Co-localization studies reveal the absence of mannans in ascus wall but are distributed primarily in spores. Such detailed picture is believed to further enhance our understanding of the dynamic spore wall architecture, eventually leading to advancements in drug discovery and development in the near future.

Lipid droplets have been hypothesized to be intimately associated with intracellular proteins. However, there is little direct evidence for both spatiotemporal and functional relations between lipid droplets and proteins provided by molecular-level studies on intact cells. Here, we present in vivo time-lapse Raman imaging, coupled with stable-isotope ((13)C) labeling, of single living Schizosaccharomyces pombe cells. Using characteristic Raman bands of proteins and lipids, we dynamically visualized the process by which (13)C-glucose in the medium was assimilated into those intracellular components. Our results show that the proteins newly synthesized from incorporated (13)C-substrate are localized specifically to lipid droplets as the lipid concentration within the cell increases. We demonstrate that the present method offers a unique platform for proteome visualization without the need for tagging individual proteins with fluorescent probes.

Understanding cellular metabolism is a major challenge in current systems biology and has triggered extensive metabolomics research, which in most cases involves destructive analysis. However, the information obtainable only in a nondestructive manner will be required for accurately mapping the global structure of the organism's metabolic network at a given instant. Here we report that metabolic pathways can be explored in vivo by mixed stable isotope-labeled Raman microspectroscopy in conjunction with multivariate curve resolution analysis. As a model system, we studied ergosterol biosynthesis in single living fission yeast cells grown in mixtures of normal and (13)C-labeled glucose as the sole carbon source. The multivariate spectral data analysis of space-resolved Raman spectra revealed the intrinsic spectra and relative abundances of all isotopomers of ergosterol whose carbon atoms in the 5,7-diene moiety of the sterol skeleton are either partly or fully substituted with (13)C. Our approach is applicable to other metabolites and will earn a place in the toolbox of metabolomic analysis.

With the continuous development in nanoscience and nanotechnology, analytical techniques like surface-enhanced Raman spectroscopy (SERS) render structural and chemical information of a variety of analyte molecules in ultra-low concentration.