23 research outputs found
Recommended from our members
Dynamic regulation of T cell priming in cancer and infection
An immunological challenge initiates cascades of migration, activation, and interactions between diverse immune cell subsets that ultimately lead to protection of the host. Previous technological limitations have favored reductionist experimentation and hindered experimental and analytical assessment of the full breadth of immunological responses. Therefore, many emergent properties of pan-lineage dynamic immune responses have remained elusive. The present body of work addresses this gap in fundamental immunology by leveraging high-dimensional single-cell technologies and in vivo mouse models of immune responses to dissect the dynamic regulation of T cell priming in both cancer and infection. Generation of immune organization maps in eight tumor models showed that the global immune macroenvironment in cancer is significantly dysregulated as shown by gross alterations in cell frequencies and phenotypes. Orthogonal pathogen challenges in tumor-burdened mice revealed peripheral defects in CD8 T cell differentiation that were caused by impaired dendritic cell (DC) activation. To further profile natural immunity to bacterial challenges, mass cytometry was adapted to profile metabolic enzymes during an in vivo bacterial immune response. We revealed a highly transient early activated CD8 T cell state characterized by peak utilization of oxidative phosphorylation and glycolysis. Assessing all splenic immune lineages during an antibacterial immune response uncovered a DC activation zenith at two days post-infection. Peak DC activation functioned as a temporal regulator of T cell fate as late arriving T cells acquired memory T cell fate exclusively. Taken together these studies reveal transient functionally significant stages of regulation during cancer and infection
Recommended from our members
Dynamic regulation of T cell priming in cancer and infection
An immunological challenge initiates cascades of migration, activation, and interactions between diverse immune cell subsets that ultimately lead to protection of the host. Previous technological limitations have favored reductionist experimentation and hindered experimental and analytical assessment of the full breadth of immunological responses. Therefore, many emergent properties of pan-lineage dynamic immune responses have remained elusive. The present body of work addresses this gap in fundamental immunology by leveraging high-dimensional single-cell technologies and in vivo mouse models of immune responses to dissect the dynamic regulation of T cell priming in both cancer and infection. Generation of immune organization maps in eight tumor models showed that the global immune macroenvironment in cancer is significantly dysregulated as shown by gross alterations in cell frequencies and phenotypes. Orthogonal pathogen challenges in tumor-burdened mice revealed peripheral defects in CD8 T cell differentiation that were caused by impaired dendritic cell (DC) activation. To further profile natural immunity to bacterial challenges, mass cytometry was adapted to profile metabolic enzymes during an in vivo bacterial immune response. We revealed a highly transient early activated CD8 T cell state characterized by peak utilization of oxidative phosphorylation and glycolysis. Assessing all splenic immune lineages during an antibacterial immune response uncovered a DC activation zenith at two days post-infection. Peak DC activation functioned as a temporal regulator of T cell fate as late arriving T cells acquired memory T cell fate exclusively. Taken together these studies reveal transient functionally significant stages of regulation during cancer and infection
Recommended from our members
Systemic immunity in cancer.
Immunotherapy has revolutionized cancer treatment, but efficacy remains limited in most clinical settings. Cancer is a systemic disease that induces many functional and compositional changes to the immune system as a whole. Immunity is regulated by interactions of diverse cell lineages across tissues. Therefore, an improved understanding of tumour immunology must assess the systemic immune landscape beyond the tumour microenvironment (TME). Importantly, the peripheral immune system is required to drive effective natural and therapeutically induced antitumour immune responses. In fact, emerging evidence suggests that immunotherapy drives new immune responses rather than the reinvigoration of pre-existing immune responses. However, new immune responses in individuals burdened with tumours are compromised even beyond the TME. Herein, we aim to comprehensively outline the current knowledge of systemic immunity in cancer
Recommended from our members
Systemic immunity in cancer.
Immunotherapy has revolutionized cancer treatment, but efficacy remains limited in most clinical settings. Cancer is a systemic disease that induces many functional and compositional changes to the immune system as a whole. Immunity is regulated by interactions of diverse cell lineages across tissues. Therefore, an improved understanding of tumour immunology must assess the systemic immune landscape beyond the tumour microenvironment (TME). Importantly, the peripheral immune system is required to drive effective natural and therapeutically induced antitumour immune responses. In fact, emerging evidence suggests that immunotherapy drives new immune responses rather than the reinvigoration of pre-existing immune responses. However, new immune responses in individuals burdened with tumours are compromised even beyond the TME. Herein, we aim to comprehensively outline the current knowledge of systemic immunity in cancer
Bioinformatic identification of <i>T</i>. <i>thermophilus</i> HB8 promoters potentially regulated by SbtR.
<p>Shown are sequences +/- 200 bp of the first codon of a target gene identified through FIMO analysis as being potentially regulated by SbtR (see <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0159408#pone.0159408.t002" target="_blank">Table 2</a>). Longest open reading frames with identical orientation as the target gene are indicated with blue nucleotides. Open reading frames with opposite orientation are indicated with green nucleotides. Black nucleotides indicate intragenic regions. Potential promoter elements (-30 and -10 boxes, +1 start site of transcription) were identified using Softberry BPROM and are indicated with blue highlighting. SbtR-binding sites are indicated with yellow highlighting. Regions of overlap between SbtR-binding sites and promoter elements are indicated by green highlighting.</p
Validation of REPSA-selected SbtR-binding DNA species.
<p>Shown are LICOR images of electrophoretic mobility shift assays containing pooled DNA from either Round 1 (left lanes) or Round 7 (right lanes) of REPSA selection and different concentrations of SbtR protein (from left to right: 0, 1, 10, 100, or 1000 nM SbtR dimer). The electrophoretic mobility of two protein-DNA complexes (S2 and S1) as well as uncomplexed ST2R24 selection template (T) and IRD7_ST2R primer (P) are indicated at right of figure.</p
Comparison of CASTing and REPSA selection methods.
<p>Shown are flow diagrams depicting Cyclic Amplification and Selection of Targets (CASTing) and Restriction Endonuclease Protection Selection and Amplification (REPSA), combinatorial selection methods for the identification of preferred ligand-binding sequences in duplex DNA. Both methods rely on large populations of randomized DNA sequences, ligand-binding to a subpopulation of these DNAs, and PCR amplification of selected DNAs. However, CASTing and similar methods rely on the physical separation of ligand-bound from unbound DNAs (<i>e</i>.<i>g</i>., immunoprecipitation) for its selection process, whereas REPSA utilizes ligand-dependent interference with a template inactivation process (type IIS restriction endonuclease cleavage) for selection.</p
Expression and purification of SbtR protein.
<p>Shown is a Coomassie Brilliant Blue R250-stained 4–20% SDS-PAGE gradient gel onto which was loaded whole cell extracts or partially purified fractions containing SbtR protein. Lanes shown left to right: (log) 14 μg whole cell extract from logarithmic growth <i>E coli</i> BL21(DE3) bacteria containing the plasmid pET-sbtR, (ind) 24 μg whole cell extract from the aforementioned bacteria following IPTG-induction, (pur) 36 μg purified SbtR protein loaded under standard reducing conditions, (pur/ox) as previous, except that the sample was loaded under oxidizing conditions. The location of molecular weight standards is indicated at the left of the figure. SbtR and SbtR<sub>2</sub> indicate the locations of reduced monomeric and oxidized dimeric SbtR proteins, respectively.</p
FIMO of Best Possible Match TGACTGGCCAGTCA.
<p>FIMO of Best Possible Match TGACTGGCCAGTCA.</p