Details

Autor(en) / Beteiligte

• Cavrois, Marielle
• Banerjee, Trambak
• Mukherjee, Gourab
• Raman, Nandhini
• Hussien, Rajaa
• Rodriguez, Brandon Aguilar
• Vasquez, Joshua
• Spitzer, Matthew H.
• Lazarus, Nicole H.
• Jones, Jennifer J.
• Ochsenbauer, Christina
• McCune, Joseph M.
• Butcher, Eugene C.
• Arvin, Ann M.
• Sen, Nandini
• Greene, Warner C.
• Roan, Nadia R.

Titel

Mass Cytometric Analysis of HIV Entry, Replication, and Remodeling in Tissue CD4+ T Cells

Ist Teil von

• Cell reports (Cambridge), 2017-07, Vol.20 (4), p.984-998

Ort / Verlag

United States: Elsevier Inc

Erscheinungsjahr

2017

Quelle

MEDLINE

Beschreibungen/Notizen

• To characterize susceptibility to HIV infection, we phenotyped infected tonsillar T cells by single-cell mass cytometry and created comprehensive maps to identify which subsets of CD4+ T cells support HIV fusion and productive infection. By comparing HIV-fused and HIV-infected cells through dimensionality reduction, clustering, and statistical approaches to account for viral perturbations, we identified a subset of memory CD4+ T cells that support HIV entry but not viral gene expression. These cells express high levels of CD127, the IL-7 receptor, and are believed to be long-lived lymphocytes. In HIV-infected patients, CD127-expressing cells preferentially localize to extrafollicular lymphoid regions with limited viral replication. Thus, CyTOF-based phenotyping, combined with analytical approaches to distinguish between selective infection and receptor modulation by viruses, can be used as a discovery tool. [Display omitted] •CyTOF-generated atlas of CD4+ T cells susceptible to HIV entry and infection•High-dimensional analysis to distinguish remodeling from preferential infection•Development of a statistical method to identify receptors modulated on infected cells•Identification of a CD4+ T memory subset with post-entry block Cavrois et al. conduct a global characterization of HIV entry and productive infection of tissue CD4+ T cells by CyTOF and develop an analytical approach that takes advantage of the high-dimensional nature of CyTOF datasets to distinguish receptors modulated during infection from those differentially expressed on preferentially infected cells.