Faculty Opinions recommendation of In vivo lipidomics using single-cell Raman spectroscopy.

Author(s):  
Julia Kehr
2011 ◽  
Vol 108 (9) ◽  
pp. 3809-3814 ◽  
Author(s):  
Huawen Wu ◽  
Joanne V. Volponi ◽  
Ann E. Oliver ◽  
Atul N. Parikh ◽  
Blake A. Simmons ◽  
...  

The Analyst ◽  
2017 ◽  
Vol 142 (7) ◽  
pp. 1054-1060 ◽  
Author(s):  
Hyun Soo Kim ◽  
Sergio C. Waqued ◽  
Dawson T. Nodurft ◽  
Timothy P. Devarenne ◽  
Vladislav V. Yakovlev ◽  
...  

We present a method that allows for the use of Raman spectroscopy with PDMS-based microdevices to perform on-chip, droplet-based in vivo biomolecular analysis (i.e., microalgal lipid analysis) with single-cell resolution.


2021 ◽  
Vol 22 (19) ◽  
pp. 10481
Author(s):  
Aikaterini Pistiki ◽  
Anuradha Ramoji ◽  
Oleg Ryabchykov ◽  
Daniel Thomas-Rüddel ◽  
Adrian T. Press ◽  
...  

Biochemical information from activated leukocytes provide valuable diagnostic information. In this study, Raman spectroscopy was applied as a label-free analytical technique to characterize the activation pattern of leukocyte subpopulations in an in vitro infection model. Neutrophils, monocytes, and lymphocytes were isolated from healthy volunteers and stimulated with heat-inactivated clinical isolates of Candida albicans, Staphylococcus aureus, and Klebsiella pneumoniae. Binary classification models could identify the presence of infection for monocytes and lymphocytes, classify the type of infection as bacterial or fungal for neutrophils, monocytes, and lymphocytes and distinguish the cause of infection as Gram-negative or Gram-positive bacteria in the monocyte subpopulation. Changes in single-cell Raman spectra, upon leukocyte stimulation, can be explained with biochemical changes due to the leukocyte’s specific reaction to each type of pathogen. Raman spectra of leukocytes from the in vitro infection model were compared with spectra from leukocytes of patients with infection (DRKS-ID: DRKS00006265) with the same pathogen groups, and a good agreement was revealed. Our study elucidates the potential of Raman spectroscopy-based single-cell analysis for the differentiation of circulating leukocyte subtypes and identification of the infection by probing the molecular phenotype of those cells.


2010 ◽  
Author(s):  
Huawen Wu ◽  
Joanne Volponi ◽  
Ann Oliver ◽  
Atul Parikh ◽  
Blake Simmons ◽  
...  

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
David S. Fischer ◽  
Meshal Ansari ◽  
Karolin I. Wagner ◽  
Sebastian Jarosch ◽  
Yiqi Huang ◽  
...  

AbstractThe in vivo phenotypic profile of T cells reactive to severe acute respiratory syndrome (SARS)-CoV-2 antigens remains poorly understood. Conventional methods to detect antigen-reactive T cells require in vitro antigenic re-stimulation or highly individualized peptide-human leukocyte antigen (pHLA) multimers. Here, we use single-cell RNA sequencing to identify and profile SARS-CoV-2-reactive T cells from Coronavirus Disease 2019 (COVID-19) patients. To do so, we induce transcriptional shifts by antigenic stimulation in vitro and take advantage of natural T cell receptor (TCR) sequences of clonally expanded T cells as barcodes for ‘reverse phenotyping’. This allows identification of SARS-CoV-2-reactive TCRs and reveals phenotypic effects introduced by antigen-specific stimulation. We characterize transcriptional signatures of currently and previously activated SARS-CoV-2-reactive T cells, and show correspondence with phenotypes of T cells from the respiratory tract of patients with severe disease in the presence or absence of virus in independent cohorts. Reverse phenotyping is a powerful tool to provide an integrated insight into cellular states of SARS-CoV-2-reactive T cells across tissues and activation states.


2021 ◽  
Vol 358 ◽  
pp. 109192
Author(s):  
Yajie Liang ◽  
Liset M. de la Prida

2021 ◽  
Vol 133 (23) ◽  
Author(s):  
Camille Lombard‐Banek ◽  
Jie Li ◽  
Erika P. Portero ◽  
Rosemary M. Onjiko ◽  
Chase D. Singer ◽  
...  

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