Label‐Free Biomedical Imaging of Lipids by Stimulated Raman Scattering Microscopy

Ramachandran, Prasanna Venkatesh; Mutlu, Ayse Sena; Wang, Meng C.

doi:10.1002/0471142727.mb3003s109

Cited by 25 publications

(23 citation statements)

References 20 publications

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“…Coverslips were washed with cytoskeleton stabilizing buffer for three times and mounted onto microscope slides using 4% n-propyl gallate. The slides were visualized under a confocal fluorescence microscope (Olympus) for mitochondrial morphology, or imaged under a Stimulated Raman Scattering (SRS) microscope (Ramachandran et al, 2015; Wang et al, 2011) for determining fat storage levels.…”

Section: Methods Detailsmentioning

confidence: 99%

Microbial Genetic Composition Tunes Host Longevity

Han

Sivaramakrishnan

Lin

et al. 2017

Cell

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258

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Summary Homeostasis of the gut microbiota critically influences host health and aging. Developing genetically engineered probiotics holds great promise as a new therapeutic paradigm to promote healthy aging. Here, through screening 3,983 Escherichia coli mutants, we discovered that 29 bacterial genes, when deleted, increase longevity in the host Caenorhabditis elegans. A dozen of these bacterial mutants also protect the host from age-related progression of tumor growth and amyloid-beta accumulation. Mechanistically, we discovered that five bacterial mutants promote longevity through increased secretion of the polysaccharide colanic acid (CA), which regulates mitochondrial dynamics and unfolded protein response (UPRmt) in the host. Purified CA polymers are sufficient to promote longevity via ATFS-1, the host UPRmt-responsive transcription factor. Furthermore, the mitochondrial changes and longevity effects induced by CA are conserved across different species. Together, our results identified molecular targets for developing pro-longevity microbes, and a bacterial metabolite acting on host mitochondria to promote longevity.

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Section: Methods Detailsmentioning

confidence: 99%

Microbial Genetic Composition Tunes Host Longevity

Han

Sivaramakrishnan

Lin

et al. 2017

Cell

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258

191

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“…1a). To analyze their fat content, we employed stimulated Raman scattering (SRS) microscopy, which is a chemical imaging technique for direct, label-free quantification of lipid molecules in living cells and organisms 16 . Among the 30 mutants that we screened, we identified that the mutants of daf-11, which encodes a conserved transmembrane guanylyl cyclase, show a fat storage increase ( Supplementary Fig.…”

Section: Resultsmentioning

confidence: 99%

Olfactory specificity regulates lipid metabolism through neuroendocrine signaling in Caenorhabditis elegans

et al. 2020

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Olfactory and metabolic dysfunctions are intertwined phenomena associated with obesity and neurodegenerative diseases; yet how mechanistically olfaction regulates metabolic homeostasis remains unclear. Specificity of olfactory perception integrates diverse environmental odors and olfactory neurons expressing different receptors. Here, we report that specific but not all olfactory neurons actively regulate fat metabolism without affecting eating behaviors in Caenorhabditis elegans, and identified specific odors that reduce fat mobilization via inhibiting these neurons. Optogenetic activation or inhibition of the responsible olfactory neural circuit promotes the loss or gain of fat storage, respectively. Furthermore, we discovered that FLP-1 neuropeptide released from this olfactory neural circuit signals through peripheral NPR-4/neuropeptide receptor, SGK-1/serum-and glucocorticoid-inducible kinase, and specific isoforms of DAF-16/FOXO transcription factor to regulate fat storage. Our work reveals molecular mechanisms underlying olfactory regulation of fat metabolism, and suggests the association between olfactory perception specificity of each individual and his/her susceptibility to the development of obesity.

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“…Interestingly, C. elegans exposed to different strains of E. coli exhibit different physiological phenotypes (Brooks et al, 2009; Han et al, 2017; MacNeil,et al, 2013; Sowa et al, 2015), for example, the reproductive lifespan and intestinal fat levels are increased when C. elegans are grown on the OP50 E. coli strain compared to those animals grown on the HB101 or MG1655 E. coli strains (Brooks et al, 2009; Lin and Wang, 2017; Sowa et al, 2015). Using stimulated Raman scattering (SRS) microscopy (Ramachandran et al, 2015; Yong Yu et al, 2014), we quantitatively examined fat content levels in C. elegans exposed to those different bacterial strains. In line with previous studies (Brooks et al, 2009), we found that C. elegans on OP50 show more fat storage than those on HB101 or MG1655 in the intestine, the major fat storage tissue (Figure 1A).…”

Section: Resultsmentioning

confidence: 99%

“…Day-2-old adults (∼10 for each of three biological replicates) were anesthetized in 1% sodium azide in M9 buffer (3g KH2PO4, 6g Na2HPO4, 5g NaCl, 1ml 1M MgSO4, H2O to 1 liter, sterilized by autoclaving), and mounted on 2% agarose pads sandwiched between glass microscopic slides and coverslips. Images were taken using the SRS system as described in previous studies (Ramachandran et al, 2015; Wang et al, 2011). In brief, when using Stokes beam at 1064nm and pump beam at 817nm, the energy difference between the Stokes and pump photons resonates with the vibrational frequency of CH2 bonds (2845cm-1).…”

Section: Methodsmentioning

confidence: 99%

Escherichia coli Metabolite Profiling Leads to the Development of an RNA Interference Strain for Caenorhabditis elegans

Neve

Sowa

Sivaramakrishnan

et al. 2019

Preprint

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1The relationship of genotypes to phenotypes can be modified by environmental 2 inputs. Such crucial environmental inputs include metabolic cues derived from microbes 3 living together with animals. Thus the analysis of genetic effects on animals' physiology 4 can be confounded by variations in the metabolic profile of microbes. Caenorhabditis 5 elegans exposed to distinct bacterial strains and species exhibit phenotypes different at 6 cellular, developmental and behavioral levels. Here we reported metabolomic profiles of 7 three Escherichia coli strains, B strain OP50, K-12 strain MG1655, and B-K-12 hybrid 8 strain HB101, and also different mitochondrial and fat storage phenotypes of C. elegans 9 exposed to MG1655 and HB101 versus OP50. We found that these metabolic 1 0 phenotypes of C. elegans are not correlated with overall metabolic patterning of 1 1 bacterial strains, but their specific metabolites. In particular, the fat storage phenotype is 1 2 traced to the betaine level in different bacterial strains. HT115 is another K-12 E. coli 1 3 strain that is commonly utilized to elicit an RNA interference response, and we showed 1 4 that C. elegans exposed to OP50 and HT115 exhibit differences in mitochondrial 1 5 morphology and fat storage levels. We thus generated an RNA interference competent 1 6 OP50 (iOP50) strain that can robustly and consistently knockdown endogenous C. 1 7 elegans genes in different tissues. Together, these studies suggest the importance of 1 8 specific bacterial metabolites in regulating the host's physiology, and provide a tool to 1 9

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Label‐Free Biomedical Imaging of Lipids by Stimulated Raman Scattering Microscopy

Cited by 25 publications

References 20 publications

Microbial Genetic Composition Tunes Host Longevity

Microbial Genetic Composition Tunes Host Longevity

Olfactory specificity regulates lipid metabolism through neuroendocrine signaling in Caenorhabditis elegans

Escherichia coli Metabolite Profiling Leads to the Development of an RNA Interference Strain for Caenorhabditis elegans

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