Flow Cytometric Method for in situ Preparation of Standard Materials of a Small Defined Number of Microbial Cells with Colony-Forming Potentiality

2014 ◽  
Vol 97 (2) ◽  
pp. 479-483 ◽  
Author(s):  
Hideaki Matsuoka ◽  
Koichiro Nakano ◽  
Norimasa Takatani ◽  
Tomonori Yoshida ◽  
Shizunobu Igimi ◽  
...  

Abstract Standard materials of a small defined number of cells with colony-forming potentiality are essential for the rational validation of food microbiological methods. An in situ flow cytometric method using viable staining with 6-carboxyfluorescein diacetate (CFDA) and tryptic soy agar (TSA) was previously proposed and its feasibility was demonstrated with five strains. In this study, this method was applied to 16 strains to support its broad applicability. The cellsorting gate was previously determined based on the CFDA stainability alone. Now the structural properties of cells designated by forward and side-scattering intensities have been introduced as the second gating criteria. Under the optimum gate condition, 100 cells have been selected and sorted on TSA. Consequently, a 95% or higher colony-forming rate has been attained for every strain. A successful application to microaerophilic Campylobacter spp. is especially of great importance because it suggests further broader applicability.

Blood ◽  
2010 ◽  
Vol 116 (21) ◽  
pp. 4727-4727
Author(s):  
Guat Bee Tan ◽  
Christina Sum ◽  
Ponnudurai Kuperan

Abstract Abstract 4727 The examination of blood films by microscopy remains one of the major labour intensive procedures in the laboratory and the challenge is to reduce the number of blood films examined without missing important diagnostic information. Automated blood cell counters offer a leucocyte count, red cell and platelet count and five-part (some 6-part) leucocyte differential. Haematology instrument differentials provide only limited information on cell morphology using abnormal cell flags and are often unable to reliably classify abnormal and immature cells. The examination of blood films is not only time consuming, it also requires highly trained staff. The impact of a wrong diagnosis necessitates that experienced staff are present in the laboratory 24 hours a day. Furthermore, manual cell classification is subjective, with significant inter and intra observer variation (Koepke et al. 1985) and is also subject to significant statistical variance (Rumke 1985). There have recently been several reports of using monoclonal antibody cocktails for an extended leucocyte differential by flow cytometry (Faucher et al. 2007, Roussel et al. 2010). The aim of this study was to compare a flow cytometric method for the white blood cell differential with the automated count from the Beckman Coulter LH750 haematology analyser and the reference manual microscopic 2 × 200 cell count (CLSI H20-A2). Cell morphology was also assessed microscopically for the presence of cells such as reactive or abnormal lymphocytes or blasts. The flow cytometric method, described by Faucher et al. 2007, uses 6 antibodies (CD45, CD36, CD2, CD294, CD19 and CD16) premixed in a single tube. The protocol allows detection of all white blood cells, mature neutrophils, total lymphocytes, total monocytes, eosinophils, basophils, immature granulocytes, B lymphocytes, non-cytotoxic T-lymphocytes, cytotoxic T/NK lymphocytes, CD16 positive and CD16 negative monocytes, and blasts cells with lineage orientation. A 5-colour flow cytometer, the Beckman Coulter FC500, was used for analysis. The gating strategy described by Faucher et al. (2007) was used. EDTA blood was analysed on 27 normal samples and 148 abnormal samples which demonstrated abnormal cell flags on the LH750. These samples included the presence of blast cells, immature granulocytes and abnormal lymphocytes. Results for most cell populations measured by the flow cytometric differential compared well with both the LH750 automated differential and the manual reference method. Comparative results using Pearson correlation show that the automated LH750 differential produced r values of greater than 0.94 for neutrophils, lymphocytes and eosinophils. The manual reference method produced r values of greater than 0.89 for neutrophils, lymphocytes and eosinophils. Results for flow cytometric monocytes compared to the LH750 and manual differential gave an r value of 0.84 and 0.87 respectively. Results for basophils were significantly better when the flow cytometric method was compared to the LH750 rather than the manual method, r = 0.68 for flow cytometry versus LH750 and r = 0.43 for flow cytometry versus manual method. The value of the manual differential is diminished because of the low number of cells counted; the precision is not good for smaller cell populations (Hübl et al. 1995). Very good correlation of blast cells, r = 0.98 and immature granulocytes, r = 0.92 was seen between the manual and flow cytometric method. The flow cytometric differential is superior to the microscopic method since it is objective and due to the higher number of cells counted, it can detect subpopulations of cells that are present in smaller number with greater statistical and interpretive confidence. More importantly, it recognises and quantitates morphologically abnormal cells such as reactive lymphocytes, inflammatory monocytes and the lineage of blast cells. However, the examination of blood cell morphology by microscopy still has an important role in the diagnosis of diseases. Disclosures: No relevant conflicts of interest to declare.


2013 ◽  
Vol 93 (1) ◽  
pp. 49-51 ◽  
Author(s):  
Hideaki Matsuoka ◽  
Tomoya Shigetomi ◽  
Hisakage Funabashi ◽  
Mikako Saito ◽  
Shizunobu Igimi

2020 ◽  
Vol 8 (Suppl 3) ◽  
pp. A873-A873
Author(s):  
Arika Feils ◽  
Mackenzie Heck ◽  
Anna Hoefges ◽  
Peter Carlson ◽  
Luke Zangl ◽  
...  

BackgroundMice bearing B78 melanoma tumors can be cured using an in situ vaccine (ISV) regimen that includes radiation (RT) together with immunocytokine (tumor-targeting mAb conjugated to IL-2). B78 melanoma cells, derived from B16 cells, express minimal to no MHC-I but express MHC-II upon IFN-g/TNF-a stimulation. Although B78 cells are primarily MHC-I-deficient, an increased CD8 T cell infiltration into the tumor microenvironment (TME) has been shown following ISV.1 To further investigate the potential role of specific immune cell lineages in the B78 anti-tumor response to ISV, immune subset depletion studies and flow cytometric analyses were performed.MethodsC57BL/6 mice bearing B78 tumors were depleted of immune cell subsets with mAbs (anti-CD4, anti-CD8, anti-NK1.1, or Rat IgG control) for 3 weeks during the course of treatment. Treatment groups included no treatment, RT (12 Gy), or ISV (RT D0 and immunocytokine D5-D9). 6 mice/group (repeated three times) were followed for survival/tumor growth, and flow cytometry studies included 4 mice/group, sacrificed on D8 and D13 following the start of ISV.ResultsMice depleted of CD4 T cells during the course of ISV showed a significant reduction of anti-tumor effect as compared to mice treated with ISV/Rat IgG (pConclusionsThese studies suggest that CD4 T cells are essential for an anti-tumor response in the B78 melanoma model. In vivo depletion data show that CD4 T cells, but not CD8 or NK cells, are required for a decrease in tumor growth via ISV. Flow cytometric analyses suggest an interplay between CD4 and CD8 T cells as indicated by a decrease in CD8/IFN-g expression following ISV in the absence of CD4 T cells. The role that MHC-I and MHC-II expression plays in this CD4/CD8 T cell anti-tumor response is under investigation. In future studies, B78 melanoma may serve as a critical syngeneic model for development of more effective immunotherapy treatment regimens.Ethics ApprovalAll animal experiments were performed in accordance with protocols approved by Animal Care and Use Committees of the University of Wisconsin-Madison.ReferenceMorris Z, Guy E, Francis D, et al. In situ tumor vaccination by combining local radiation and tumor-specific antibody or immunocytokine treatments. Cancer Res 2016;76(13):3929-3941.


2021 ◽  
Vol 765 ◽  
pp. 138284
Author(s):  
Junqi Wang ◽  
Xiaoping Zou ◽  
Jialin Zhu ◽  
Jin Cheng ◽  
Xiao Bai ◽  
...  

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