Raman spectroscopic imaging of the whole Ciona intestinalis embryo during development

Multimodal factor evaluation system for organismal transparency by hyperspectral imaging

Organismal transparency constitutes a significant concern in whole-body live imaging, yet its underlying structural, genetic, and physiological foundations remain inadequately comprehended. Diverse environmental and physiological factors (multimodal factors) are recognized for their influence on organismal transparency. However, a comprehensive and integrated quantitative evaluation system for biological transparency across a broad spectrum of wavelengths is presently lacking. In this study, we have devised an evaluation system to gauge alterations in organismal transparency induced by multimodal factors, encompassing a wide range of transmittance spanning from 380 to 1000 nm, utilizing hyperspectral microscopy. Through experimentation, we have scrutinized the impact of three environmental variables (temperature, salinity, and pH) and the effect of 11 drugs treatment containing inhibitors targeting physiological processes in the ascidian Ascidiella aspersa. This particular species, known for its exceptionally transparent eggs and embryos, serves as an ideal model. We calculated bio-transparency defined as the mean transmittance ratio of visible light within the range of 400-760 nm. Our findings reveal a positive correlation between bio-transparency and temperature, while an inverse relationship is observed with salinity levels. Notably, reduced pH levels and exposure to six drugs have led to significant decreasing in bio-transparency (ranging from 4.2% to 58.6%). Principal component analysis (PCA) on the measured transmittance data classified these factors into distinct groups. This suggest diverse pathways through which opacification occurs across different spectrum regions. The outcome of our quantitative analysis of bio-transparency holds potential applicability to diverse living organisms on multiple scales. This analytical framework also contributes to a holistic comprehension of the mechanisms underlying biological transparency, which is susceptible to many environmental and physiological modalities.

Label-free optical imaging in developmental biology [Invited]

Application of optical imaging in developmental biology marks an exciting frontier in biomedical optics. Optical resolution and imaging depth allow for investigation of growing embryos at subcellular, cellular, and whole organism levels, while the complexity and variety of embryonic processes set multiple challenges stimulating the development of various live dynamic embryonic imaging approaches. Among other optical methods, label-free optical techniques attract an increasing interest as they allow investigation of developmental mechanisms without application of exogenous markers or fluorescent reporters. There has been a boost in development of label-free optical imaging techniques for studying embryonic development in animal models over the last decade, which revealed new information about early development and created new areas for investigation. Here, we review the recent progress in label-free optical embryonic imaging, discuss specific applications, and comment on future developments at the interface of photonics, engineering, and developmental biology.

Fatty Acid and Lipid Profiles with Emphasis on n-3 Fatty Acids and Phospholipids from Ciona intestinalis

In order to establish Ciona intestinalis as a new bioresource for n-3 fatty acids-rich marine lipids, the animal was fractionated into tunic and inner body tissues prior to lipid extraction. The lipids obtained were further classified into neutral lipids (NL), glycolipids (GL) and phospholipids (PL) followed by qualitative and quantitative analysis using GC-FID, GC-MS, (1)H NMR, 2D NMR, MALDI-TOF-MS and LC-ESI-MS methods. It was found that the tunic and inner body tissues contained 3.42-4.08% and 15.9-23.4% of lipids respectively. PL was the dominant lipid class (42-60%) irrespective of the anatomic fractions. From all lipid fractions and classes, the major fatty acids were 16:0, 18:1n-9, C20:1n-9, C20:5n-3 (EPA) and C22:6n-3 (DHA). The highest amounts of long chain n-3 fatty acids, mainly EPA and DHA, were located in PL from both body fractions. Cholestanol and cholesterol were the dominant sterols together with noticeable amounts of stellasterol, 22 (Z)-dehydrocholesterol and lathosterol. Several other identified and two yet unidentified sterols were observed for the first time from C. intestinalis. Different molecular species of phosphatidylcholine (34 species), sphingomyelin (2 species), phosphatidylethanolamine (2 species), phosphatidylserine (10 species), phosphatidylglycerol (9 species), ceramide (38 species) and lysophospholipid (5 species) were identified, representing the most systematic PL profiling knowledge so far for the animal. It could be concluded that C. intestinalis lipids should be a good alternative for fish oil with high contents of n-3 fatty acids. The lipids would be more bioavailable due to the presence of the fatty acids being mainly in the form of PL.

Visualizing cell state transition using Raman spectroscopy

System level understanding of the cell requires detailed description of the cell state, which is often characterized by the expression levels of proteins. However, understanding the cell state requires comprehensive information of the cell, which is usually obtained from a large number of cells and their disruption. In this study, we used Raman spectroscopy, which can report changes in the cell state without introducing any label, as a non-invasive method with single cell capability. Significant differences in Raman spectra were observed at the levels of both the cytosol and nucleus in different cell-lines from mouse, indicating that Raman spectra reflect differences in the cell state. Difference in cell state was observed before and after the induction of differentiation in neuroblastoma and adipocytes, showing that Raman spectra can detect subtle changes in the cell state. Cell state transitions during embryonic stem cell (ESC) differentiation were visualized when Raman spectroscopy was coupled with principal component analysis (PCA), which showed gradual transition in the cell states during differentiation. Detailed analysis showed that the diversity between cells are large in undifferentiated ESC and in mesenchymal stem cells compared with terminally differentiated cells, implying that the cell state in stem cells stochastically fluctuates during the self-renewal process. The present study strongly indicates that Raman spectral morphology, in combination with PCA, can be used to establish cells' fingerprints, which can be useful for distinguishing and identifying different cellular states.