PD-1 knockout on cytotoxic primary murine CD8+ T cells improves their motility in retrovirus infected mice.

Cytotoxic T lymphocyte (CTL) motility is an important feature of effective CTL responses and is impaired when CTLs become exhausted, e.g. during chronic retroviral infections. A prominent T cell exhaustion marker is programmed cell death protein 1 (PD-1) and antibodies against the interaction of PD-1 and PD-ligand 1 (PD-L1) are known to improve CTL functions. However, antibody blockade affects all PD-1/PD-L1-expressing cell types, thus, the observed effects cannot be attributed selectively to CTLs. To overcome this problem, we performed CRISPR/Cas9 based knockout of the PD-1 coding gene PDCD1 in naïve Friend Retrovirus (FV)-specific CTLs. We transferred 1,000 of these cells into mice where they proliferated upon FV-infection. Using intravital two-photon microscopy we visualized CTL motility in the bone marrow and evaluated cytotoxic molecule expression by flow cytometry. Knockout of PDCD1 improved the CTL motility at 14 days post infection and enhanced the expression of cytotoxicity markers. Our data show the potential of genetic tuning of naive antiviral CTLs and might be relevant for future designs of improved T cell-mediated therapies.

Fatty acids are crucial to fuel NK cells upon acute retrovirus infection.

Natural killer (NK) cells are cytotoxic innate immune cells, able to recognize and eliminate virus-infected as well as cancer cells. Metabolic reprogramming is crucial for their activity as they have enhanced energy and nutritional demands for their functions during an infection. Fatty acids (FAs) represent an important source of cellular energy and are essential for proliferation of immune cells. However, the precise role of FAs for NK cells activity in retrovirus infection was unknown. Here we show that activated NK cells increase the expression of the FA uptake receptor CD36 and subsequently the uptake of FAs upon acute virus infection. We found an enhanced flexibility of NK cells to utilize FAs as source of energy compare to naïve NK cells. NK cells that were able to generate energy from FAs showed an augmented target cell killing and increased expression of cytotoxic parameters. However, NK cells that were unable to generate energy from FAs exhibited a severely decreased migratory capacity. Our results demonstrate that NK cells require FAs in order to fight acute virus infection. Susceptibility to severe virus infections as it is shown for people with malnutrition may be augmented by defects in the FA processing machinery, which might be a target to therapeutically boost NK cell functions in the future.

Macrophage migration inhibitory factor receptor CD74 expression is associated with expansion and differentiation of effector T cells in COVID-19 patients.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) caused millions of COVID-19 cases and deaths worldwide. Severity of pulmonary pathologies and poor prognosis were reported to be associated with the activation non-virus-specific bystander T cells. In addition, high concentrations of the macrophage migration inhibitory factor (MIF) were found in serum of COVID-19 patients. We hypothesized that these two pathogenic factors might be related and analyzed the expression of receptors for MIF on T cells in COVID-19. T cells from PBMCs of hospitalized patients with mild and severe COVID-19 were characterized. A significantly higher proportion of CD4+ and CD8+ T cells from COVID-19 patients expressed CD74 on the cell surface compared to healthy controls. To induce intracellular signaling upon MIF binding, CD74 forms complexes with CD44, CXCR2, or CXCR4. The vast majority of CD74+ T cells expressed CD44, whereas expression of CXCR2 and CXCR4 was low in controls but increased upon SARS-CoV-2 infection. Hence, T cells in COVID-19 patients express receptors that render them responsive to MIF. A detailed analysis of CD74+ T cell populations revealed that most of them had a central memory phenotype early in infection, while cells with an effector and effector memory phenotype arose later during infection. Furthermore, CD74+ T cells produced more cytotoxic molecules and proliferation markers. Our data provide new insights into the MIF receptor and co-receptor repertoire of bystander T cells in COVID-19 and uncovers a novel and potentially druggable aspect of the immunological footprint of SARS-CoV-2.

Regulatory T cells suppress the motility of cytotoxic T cells in Friend retrovirus-infected mice.

Antiviral immunity often requires CD8+ cytotoxic T lymphocytes (CTLs) that actively migrate and search for virus-infected targets. Regulatory T cells (Tregs) have been shown to suppress CTL responses, but it is not known whether this is also mediated by effects on CTL motility. Here, we used intravital 2-photon microscopy in the Friend retrovirus (FV) mouse model to define the impact of Tregs on CTL motility throughout the course of acute infection. Virus-specific CTLs were very motile and had frequent short contacts with target cells at their peak cytotoxic activity. However, when Tregs were activated and expanded in late-acute FV infection, CTLs became significantly less motile and contacts with target cells were prolonged. This phenotype was associated with development of functional CTL exhaustion. Tregs had direct contacts with CTLs in vivo and, importantly, their experimental depletion restored CTL motility. Our findings identify an effect of Tregs on CTL motility as part of their mechanism of functional impairment in chronic viral infections. Future studies must address the underlying molecular mechanisms.

Immune response profiling of patients with spondyloarthritis reveals signalling networks mediating TNF-blocker function in vivo.

OBJECTIVES: Antitumour necrosis factor (TNF) therapy has revolutionised treatment of several chronic inflammatory diseases, including spondyloarthritis (SpA). However, TNF inhibitors (TNFi) are not effective in all patients and the biological basis for treatment failure remains unknown. We have analysed induced immune responses to define the mechanism of action of TNF blockers in SpA and to identify immunological correlates of responsiveness to TNFi. METHODS: Immune responses to microbial and pathway-specific stimuli were analysed in peripheral blood samples from 80 patients with axial SpA before and after TNFi treatment, using highly standardised whole-blood stimulation assays. Cytokines and chemokines were measured in a Clinical Laboratory Improvement Amendments (CLIA)-certified laboratory, and gene expression was monitored using nCounter assays. RESULTS: Anti-TNF therapy induced profound changes in patients' innate immune responses. TNFi action was selective, and had only minor effects on Th1/Th17 immunity. Modular transcriptional repertoire analysis identified prostaglandin E2 synthesis and signalling, leucocyte recirculation, macrophage polarisation, dectin and interleukin (IL)-1 signalling, as well as the nuclear factor kappa B (NF-kB) transcription factor family as key pathways targeted by TNF blockers in vivo. Analysis of induced immune responses before treatment initiation revealed that expression of molecules associated with leucocyte adhesion and invasion, chemotaxis and IL-1 signalling are correlated with therapeutic responses to anti-TNF. CONCLUSIONS: We show that TNFi target multiple immune cell pathways that cooperate to resolve inflammation. We propose that immune response profiling provides new insight into the biology of TNF-blocker action in patients and can identify signalling pathways associated with therapeutic responses to biological therapies.

A new unbiased and highly automated approach to find new prognostic markers in preclinical research.

Data acquisition in (pre)clinical studies is often based on a hypothesis. Numerical algorithms, however, may help to find biomarkers from existing data without formulating any hypothesis. By simply assessing whether a statistical relationship exists between two parameters from a (unlimited) database, every (in)conceivable combination of data becomes a hypothesis. The aim was to create an unbiased and highly automated approach for secondary analysis of (pre)clinical research, including the possibility of a non-linear functional relationship. In our example, an almost homogeneous database was formed by overall 45 parameters (vital, blood and plasma parameters) measured in 11 individual experimental studies at 6 different time points using 57 rats without and 63 rats with systemic inflammation following lipopolysaccharide infusion. For each rat, four group classifiers (treatment, survival, study, ID) were used to get valid samples by a later filtering of the statistical base. Any information about the hypothesis leading to the respective studies was suppressed. In order to assess whether a statistical relationship exists, a total of six different functional prototypes (linear and non-linear) were postulated and examined for their regression. Regression quality, correlation and significance were obtained in form of matrices. In our example, ultimately 510 300 regressions were optimized, automatically evaluated and filtered. The developed algorithm is able to reveal statistical relationships from a nearly crude database with low effort by systematic and unbiased analysis. The finding of well-known correlations proves its reliability, whose validity could be increased by clean aggregation of different studies. In addition, new interesting hints for future research could be gained. Thus, unknown markers can be found which are associated with an increased risk of death during systemic inflammation and sepsis. A further development of the program is planned including multiple regressions (more than two parameters could be related to each other) or cluster analysis.