The role and uses of antibodies in COVID-19 infections: a living review

Coronavirus disease 2019 has generated a rapidly evolving field of research, with the global scientific community striving for solutions to the current pandemic. Characterizing humoral responses towards SARS-CoV-2, as well as closely related strains, will help determine whether antibodies are central to infection control, and aid the design of therapeutics and vaccine candidates. This review outlines the major aspects of SARS-CoV-2-specific antibody research to date, with a focus on the various prophylactic and therapeutic uses of antibodies to alleviate disease in addition to the potential of cross-reactive therapies and the implications of long-term immunity

T cell phenotypes in COVID-19 - a living review

COVID-19 is characterized by profound lymphopenia in the peripheral blood, and the remaining T cells display altered phenotypes, characterized by a spectrum of activation and exhaustion. However, antigen-specific T cell responses are emerging as a crucial mechanism for both clearance of the virus and as the most likely route to long-lasting immune memory that would protect against re-infection. Therefore, T cell responses are also of considerable interest in vaccine development. Furthermore, persistent alterations in T cell subset composition and function post-infection have important implications for patients’ long-term immune function. In this review, we examine T cell phenotypes, including those of innate T cells, in both peripheral blood and lungs, and consider how key markers of activation and exhaustion correlate with, and may be able to predict, disease severity. We focus on SARS-CoV-2-specific T cells to elucidate markers that may indicate formation of antigen-specific T cell memory. We also examine peripheral T cell phenotypes in recovery and the likelihood of long-lasting immune disruption. Finally, we discuss T cell phenotypes in the lung as important drivers of both virus clearance and tissue damage. As our knowledge of the adaptive immune response to COVID-19 rapidly evolves, it has become clear that while some areas of the T cell response have been investigated in some detail, others, such as the T cell response in children remain largely unexplored. Therefore, this review will also highlight areas where T cell phenotypes require urgent characterisation

HCC1954

Files are 16-bit tiffs (which means they will appear black if opened in Preview, Photoshop, or similar program). Each file is a Multi-plane tiff, containing three fluorescence channels: Channel 1 = DAPI (Sigma) Channel 2 = NF-kappaB (anti-p65; Abcam ab16502 / Alexa-488 anti-rabbit; Invitrogen) Channel 3 = DHE (dihydroethidium, hydroethidine; Sigma) File names refer to [row][column]-[field

ZR75.1

Files are 16-bit tiffs (which means they will appear black if opened in Preview, Photoshop, or similar program). Each file is a Multi-plane tiff, containing three fluorescence channels: Channel 1 = DAPI (Sigma) Channel 2 = NF-kappaB (anti-p65; Abcam ab16502 / Alexa-488 anti-rabbit; Invitrogen) Channel 3 = DHE (dihydroethidium, hydroethidine; Sigma) File names refer to [row][column]-[field] See ReadMe file for culture and staining information

Data from: Cell shape and the microenvironment regulate nuclear translocation of NF-kappaB in breast epithelial and tumor cells

Although a great deal is known about the signaling events that promote nuclear translocation of NF‐κB, how cellular biophysics and the microenvironment might regulate the dynamics of this pathway is poorly understood. In this study, we used high‐content image analysis and Bayesian network modeling to ask whether cell shape and context features influence NF‐κB activation using the inherent variability present in unperturbed populations of breast tumor and non‐tumor cell lines. Cell–cell contact, cell and nuclear area, and protrusiveness all contributed to variability in NF‐κB localization in the absence and presence of TNFα. Higher levels of nuclear NF‐κB were associated with mesenchymal‐like versus epithelial‐like morphologies, and RhoA‐ROCK‐myosin II signaling was critical for mediating shape‐based differences in NF‐κB localization and oscillations. Thus, mechanical factors such as cell shape and the microenvironment can influence NF‐κB signaling and may in part explain how different phenotypic outcomes can arise from the same chemical cues

hs578T

Files are 16-bit tiffs (which means they will appear black if opened in Preview, Photoshop, or similar program). Each file is a Multi-plane tiff, containing three fluorescence channels: Channel 1 = DAPI (Sigma) Channel 2 = NF-kappaB (anti-p65; Abcam ab16502 / Alexa-488 anti-rabbit; Invitrogen) Channel 3 = DHE (dihydroethidium, hydroethidine; Sigma) File names refer to [row][column]-[field

HeLa

Files are 16-bit tiffs (which means they will appear black if opened in Preview, Photoshop, or similar program). Each file is a Multi-plane tiff, containing three fluorescence channels: Channel 1 = DAPI (Sigma) Channel 2 = NF-kappaB (anti-p65; Abcam ab16502 / Alexa-488 anti-rabbit; Invitrogen) Channel 3 = DHE (dihydroethidium, hydroethidine; Sigma) File names refer to [row][column]-[field

MCF12A-no EGF

Files are 16-bit tiffs (which means they will appear black if opened in Preview, Photoshop, or similar program). Each file is a Multi-plane tiff, containing three fluorescence channels: Channel 1 = DAPI (Sigma) Channel 2 = NF-kappaB (anti-p65; Abcam ab16502 / Alexa-488 anti-rabbit; Invitrogen) Channel 3 = DHE (dihydroethidium, hydroethidine; Sigma) File names refer to [row][column]-[field

JIMT1

Files are 16-bit tiffs (which means they will appear black if opened in Preview, Photoshop, or similar program). Each file is a Multi-plane tiff, containing three fluorescence channels: Channel 1 = DAPI (Sigma) Channel 2 = NF-kappaB (anti-p65; Abcam ab16502 / Alexa-488 anti-rabbit; Invitrogen) Channel 3 = DHE (dihydroethidium, hydroethidine; Sigma) File names refer to [row][column]-[field

SKBR3

Files are 16-bit tiffs (which means they will appear black if opened in Preview, Photoshop, or similar program). Each file is a Multi-plane tiff, containing three fluorescence channels: Channel 1 = DAPI (Sigma) Channel 2 = NF-kappaB (anti-p65; Abcam ab16502 / Alexa-488 anti-rabbit; Invitrogen) Channel 3 = DHE (dihydroethidium, hydroethidine; Sigma) File names refer to [row][column]-[field] See ReadMe file for culture and staining information