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Demonstrate familiarity with various cell surface specializations
In this outcome, we’ll learn about the cell surface including the cell membrane, cell junctions, and the cell wall.
What You’ll Learn to Do
- Explain the structure and function of cell membranes
- Describe cell junctions found in plant cells (plasmodesmata) and animal cells (tight junctions, desmosomes, gap junctions)
- Describe the structure and function of the cell wall
The learning activities for this section include the following:
- Cell Membranes
- Cell Junctions
- The Cell Wall
- Self Check: Cell Surface
Cell surface receptor
Cell surface receptors (membrane receptors, transmembrane receptors) are receptors that are embedded in the plasma membrane of cells. They act in cell signaling by receiving (binding to) extracellular molecules. They are specialized integral membrane proteins that allow communication between the cell and the extracellular space. The extracellular molecules may be hormones, neurotransmitters, cytokines, growth factors, cell adhesion molecules, or nutrients they react with the receptor to induce changes in the metabolism and activity of a cell. In the process of signal transduction, ligand binding affects a cascading chemical change through the cell membrane.
Viral and Nonviral Vectors for In Vivo and Ex Vivo Gene Therapies
2.2.1 Magnetic Nanoparticles
One of the pioneers using magnetofection for in vitro applications was Lin et al. 91 There are various cationic magnetic nanoparticles types that have the capacity to bind nucleotidic material on their surface. With this method, the magnetic nanoparticles are concentrated in the target cells by the influence of an external magnetic field (EMF). Normally, the internalization is accomplished by endocytosis or pinocytosis, so the membrane architecture stays intact. This is an advantage over other physical transfection methods. Other advantages are the low vector dose needed to reach saturation yield and the short incubation time needed to achieve high transfection efficiency. Moreover, with the application of an EMF, cells transfected with magnetic nanoparticles can be used to target the region of interest in vivo.
220.127.116.11 Iron Oxide Nanoparticles
The magnetic nanoparticles most used in magnetofection include the iron oxide nanoparticles (IONPs). IONPs are biodegradable and not cytotoxic and can be easily functionalized with PEI, PEG, or PLL. Poly- l -lysine-modified iron oxide nanoparticles (IONP–PLL) are good candidates as DNA and microRNA (miRNA) vectors because they bind and protect nucleic acids and showed high transfection efficiency in vitro. In addition, they are highly biocompatible in vivo.
Chen et al. 92 used human vascular endothelial growth factor siRNA bound to superparamagnetic iron oxide nanoparticles (SPIONs) and it was capable of hepatocellular carcinoma growth inhibition in nude mice. Moreover, Li et al. 93 demonstrated that the intravenous injection of IONP–PLL carrying NM23-H1 (a tumor suppressor gene) plasmid DNA significantly extended the survival time of an experimental pulmonary metastasis mouse model.
Another advantage of this kind of nanoparticles is that they can be used as MRI agents. Chen et al. 94 bound siRNA to PEG-PEI SPIONs together to a gastric cancer-associated CD44v6 single-chain variable fragment. This bound permitted both cancer cell’s transfection and their visualization by MRI.
But those complexes might be used for cell therapies as well. Schade et al. 95 used iron oxide magnetic nanoparticles (MNPs) to bind miRNA and transfect human mesenchymal stem cells. As the binding between the MNPs and PEI took place via biotin-streptavidin conjugation, these particles cannot pass the nuclear barrier, so they are good candidates to deliver miRNA, as it exerts its function in the cytosol. They functionalized the surface nanoparticles with PEI and were able to obtain a better transfection than PEI 72 h after transfection. Moreover, they demonstrated that magnetic polyplexes provided a better long-term effect, also when included inside of the stem cells.
Neuropilin Functions as an Essential Cell Surface Receptor
The Neuropilins (Nrps) are a family of essential cell surface receptors involved in multiple fundamental cellular signaling cascades. Nrp family members have key functions in VEGF-dependent angiogenesis and semaphorin-dependent axon guidance, controlling signaling and cross-talk between these fundamental physiological processes. More recently, Nrp function has been found in diverse signaling and adhesive functions, emphasizing their role as pleiotropic co-receptors. Pathological Nrp function has been shown to be important in aberrant activation of both canonical and alternative pathways. Here we review key recent insights into Nrp function in human health and disease.
Keywords: VEGFR angiogenesis heparin-binding protein neuropilin protein-protein interaction receptor structure-function semaphorin vascular endothelial growth factor (VEGF).
© 2015 by The American Society for Biochemistry and Molecular Biology, Inc.
Design and development of a generic ligand system
We aimed to design a system requiring minimal manipulation of the receptor, in order to preserve its structure and interactions. In addition, we sought to create a cell surface–expressed ligand that would engage receptors with an affinity comparable to physiological NTR–ligand interactions and that, when bound to receptor, would preserve the cell–cell intermembrane distance.
We developed a generic ligand based on the interaction between the peptide Twin-Strep-tag (sequence WSHPQFEK GGGSGGGSGGSA WSHPQFEK ), which has two Strep-tag II motifs, and Strep-Tactin, a variant of streptavidin (outlined in Fig 1) [26–28].
(1) Each receptor is constructed with a Twin-Strep-tag at the extracellular terminus and expressed in cell lines. (2) The generic ligand is made of two components: a cell surface–expressed ligand anchor with N-terminal SpyTag and soluble trivalent Strep-Tactin-SpyCatcher protein. Trivalent Strep-Tactin-SpyCatcher is added to cells expressing the generic ligand anchor. When SpyCatcher and SpyTag interact, a spontaneous covalent isopeptide bond forms between them, creating the complete generic ligand. (3) The three binding sites of trivalent Strep-Tactin-SpyCatcher are available for ligation by the Twin-Strep-tagged receptor. Two binding sites are required for the full engagement of Twin-Strep-tag.
The NTR of interest, expressed on a ‘receptor’ cell, is genetically engineered to add the Twin-Strep-tag peptide to the extracellular N terminus, where it is accessible for engagement by the generic ligand presented on another ‘ligand’ cell (Fig 1). This ligand is made up of two components: a cell surface ligand anchor and a soluble fusion protein that spontaneously forms a covalent bond with the anchor. The ligand anchor comprises the transmembrane and cytoplasmic portions of mouse CD80 fused to an N-terminal SpyTag peptide, forming one-half of the covalent bond-forming split-protein pair SpyTag/SpyCatcher [11, 29, 30]. The soluble fusion protein comprises trivalent Strep-Tactin, which has three binding sites for Strep-tag II motifs, fused to SpyCatcher (trivalent Strep-Tactin-SpyCatcher) [26, 27]. When soluble trivalent Strep-Tactin-SpyCatcher is incubated with cells expressing the ligand anchor, SpyTag and SpyCatcher spontaneously form a covalent bond. This yields a cell surface ligand able to bind a Twin-Strep-tagged receptor (Fig 1).
Based on the available structures of Strep-Tactin and SpyTag/SpyCatcher and estimates of linker lengths, we predict the complete generic ligand to have an extracellular length similar to 2–3 immunoglobulin-like domains when extended (Protein Data Bank [PDB] accession numbers: 1KL3, 4MLI) [12, 31]. This is comparable to physiological NTR ligands (discussed by Dushek and colleagues ).
Preparation of trivalent Strep-Tactin-SpyCatcher
To prepare trivalent Strep-Tactin-SpyCatcher tetramers, we employed a method previously used to generate streptavidin tetramers of defined valency [9, 32]. This uses a mutated streptavidin subunit that has negligible biotin-binding activity, termed ‘dead’ streptavidin. Biotin and Strep-tag II occupy the same surface pocket of streptavidin, and so we assumed that the dead streptavidin subunit is also unable to bind Strep-tag II . Strep-Tactin subunits were refolded from bacterial inclusion bodies with subunits of dead streptavidin fused at its C terminus to SpyCatcher (dead streptavidin-SpyCatcher) in a 3:1 molar ratio (S1 Fig).
Dead streptavidin-SpyCatcher contains a polyaspartate insertion allowing purification of the trivalent Strep-Tactin-SpyCatcher tetramer from other possible configurations using anion exchange chromatography (S1 Fig).
We analysed a sample from the first eluted peak, predicted to be that of trivalent Strep-Tactin-SpyCatcher, using SDS-PAGE. Upon boiling, the tetramer is reduced to individual monomers of Strep-Tactin and dead streptavidin-SpyCatcher, allowing visualisation of the relative proportion of the subunits (S1 Fig). For comparison, we analysed a sample from a later peak, which we predict to contain monovalent Strep-Tactin (1 × Strep-Tactin, 3 × dead streptavidin-SpyCatcher) based on order of elution. The ratio of Strep-Tactin to dead streptavidin-SpyCatcher subunits was higher than expected (4.7:1 for trivalent Strep-Tactin-SpyCatcher) but was consistent with a 3:1 ratio when compared to the subunit ratio of the monovalent protein (S1 Fig).
To confirm that the purified protein was the desired tetramer, we used a biotin-4-fluorescein fluorescence-quenching assay previously used to estimate the number of biotin-binding sites per streptavidin tetramer (S1 Fig) . When bound to Strep-Tactin, the fluorescence of biotin-4-fluorescein is quenched. As the concentration of biotin-4-fluorescein added to trivalent Strep-Tactin-SpyCatcher increases above binding-site saturation, there is an increasing amount of free (nonquenched) biotin-4-fluorescein in solution. This is visualised as a sharp increase in fluorescence, with the inflection point indicating saturation. Titration of biotin-4-fluorescein yielded an estimated number of 4.2 binding sites per trivalent Strep-Tactin-SpyCatcher (S1 Fig). Although higher than the expected value of 3, it is three times the estimated binding-site number calculated for the predicted monovalent Strep-Tactin peak (1.4). We assume there are the same number of available Strep-tag II–binding sites per tetramer.
Characterisation of the generic ligand
Affinity between Twin-Strep-tag and trivalent Strep-Tactin-SpyCatcher.
We used surface plasmon resonance and a Twin-Strep-tag–mTFP fusion protein to analyse Twin-Strep-tag binding to trivalent Strep-Tactin-SpyCatcher at 37°C. The KD was measured as 6.8 μM (Fig 2A). This is comparable to the affinities reported for physiological NTR–ligand interactions we wish to replicate [34–36].
(A) Representative equilibrium binding measured by surface plasmon resonance of Twin-Strep-tag–mTFP injected over immobilised trivalent Strep-Tactin-Spycatcher at 37°C is shown. The KD (SEM) for the collated data (n = 11) is 6.8 μM (0.62 μM), and the mean Hill slope (SEM) is 0.46 (0.03) to 2 s.f. (B) A relative indication of the level of generic ligand per cell as a function of trivalent Strep-Tactin-SpyCatcher concentration added to cells. Median fluorescence intensity values extracted from flow cytometry analyses of cells incubated with ATTO 647 biotin are shown. (C) CHO ligand anchor cells preincubated with trivalent Strep-Tactin-SpyCatcher or buffer alone were incubated with a titration of biotin-4-fluorescein in a fluorescence-quenching assay. The inflection point is used to calculate average absolute number of generic ligands per cell. (D) The saturating concentration of biotin-4-fluorescein was extracted from C and converted into number of generic ligands per cell. This was substituted as the maximum into the fitted curve in (B) to interpolate the average number of generic ligands per cell as a function of trivalent Strep-Tactin-SpyCatcher concentration added to cells. Summary numerical data are provided in S1 Data. CHO, Chinese hamster ovary mTFP, monomeric teal fluorescent protein SEM, standard error of the mean s.f., significant figures.
Characterising the optimal conditions for ligand anchor:trivalent Strep-Tactin-SpyCatcher binding.
A stable, high-expressing ligand anchor cell line was established and maintained under selection (S2 Fig). CHO cells were used to avoid any confounding receptor–ligand interactions that might occur if both receptor and ligand cells were human.
We explored the optimal conditions for covalent coupling between the cell surface–presented ligand anchor and soluble trivalent Strep-Tactin-SpyCatcher. In line with the findings of Zakeri and colleagues, we found that coupling between CHO ligand anchor cells and trivalent Strep-Tactin-SpyCatcher was most efficient in buffer at pH 5–6 (S2 Fig) . The widest range of surface densities was achieved with a 5–10-minute incubation of trivalent Strep-Tactin-SpyCatcher at a wide range of concentrations (S2 Fig).
Using western blotting on boiled cell lysates separated by SDS-PAGE, we visualised the ligand anchor by probing for the N-terminal HA tag (S2 Fig). Addition of trivalent Strep-Tactin-SpyCatcher to the cells led to a substantial increase in the molecular weight of a significant proportion of ligand anchor consistent with covalent coupling to the soluble fusion protein. Probing with anti-streptavidin antibody confirmed this (S2 Fig).
A time course showed that a significant proportion of generic ligand remains at the cell surface for many hours post-reconstitution (S2 Fig). Receptor stimulation assays are commonly conducted over this time frame so that the ligand is able to provide a strong stimulus for this duration.
Measuring the number of generic ligands per cell
A major strength of the generic ligand system is that the ligand dose can be varied easily by titrating the concentration of soluble trivalent Strep-Tactin-SpyCatcher added to cells. To enable us to determine the ligand surface density required for activation, we developed a method to measure the number of generic ligands per cell. This method uses two assays. The first, whereby CHO generic ligand cells are incubated with ATTO 647 biotin, gives an indication of how the relative number of generic ligand sites varies with Strep-Tactin-SpyCatcher concentration (Fig 2B).
The second assay measures the average maximum number of generic ligands per cell in a population of cells saturated with trivalent Strep-Tactin-SpyCatcher. This uses the same biotin-4-fluorescein fluorescence-quenching assay shown in S1 Fig. Assuming complete binding, the biotin-4-fluorescein concentration that saturates the cells is indicated by the inflection point of the graph (Fig 2C). This saturating concentration for a known number of cells in a defined volume can then be converted into an average number of generic ligands per cell (see the Measuring generic ligand numbers per cell section). By combining the absolute number of generic ligands per cell at saturation (Fig 2C) and the relative ligand levels across a range of soluble trivalent Strep-Tactin-SpyCatcher concentrations (Fig 2B), the average number of generic ligands per cell for a given soluble trivalent Strep-Tactin-SpyCatcher concentration can be estimated (Fig 2D). A maximum of 3 million generic ligands per cell can be consistently achieved, and the ligand dose can therefore easily be varied over several orders of magnitude.
Representative activating NTRs can be stimulated by generic ligand
Representative activating human NTRs from various receptor families were genetically modified to have an N-terminal Twin-Strep-tag (Fig 3A).
(A) Cartoon depictions of four representative NTRs with Twin-Strep-tags and adaptor proteins are shown. In the case of 1G4 TCR, the β chain has an N-terminal Twin-Strep-tag. The extracellular region of each receptor contains one or more immunoglobulin-like domains (see legend in Fig 1). Response of Twin-Strep-tagged SIRPβI (B), Siglec-14 (C), or NKp30 (D) expressing THP-1 cells to generic ligand presented on CHO cells. Receptor response is measured by IL-8 secretion. (E) Response of Jurkat NFκB eGFP 1G4 TCRα/β-Twin-Strep-tag cells to generic ligand presented on CHO cells. Receptor response, indicated by eGFP expression under the control of the NFκB promoter, is shown as percentage of cells positive for eGFP above background. Error bars indicate the range (n = 2), and data are representative of three independent experiments. Within each stimulation, a sample of CHO cells were taken and used to measure the number of generic ligands per cell as in (Fig 2). Ligand density was calculated from these numbers using an estimated CHO cell surface area of 700 μm 2 (see the Measuring generic ligand numbers per cell section) [22, 23]. (F) EC50 values from individual experiments of THP-1 SIRPβI DAP12, THP-1 Siglec-14 DAP12, THP-1 NKp30 FcRγ, or Jurkat NFκB eGFP 1G4 TCRα/β cells responding to generic ligand are plotted. Bars indicate the mean and standard deviation (n = 3). Summary numerical data are provided in S1 Data. CHO, Chinese hamster ovary DAP12, DNAX-activating protein of 12 kDa eGFP, enhanced green fluorescent protein IL-8, interleukin 8 NFκB, nuclear factor kappa-light-chain-enhancer of activated B cells NK, natural killer NTR, non-catalytic tyrosine-phosphorylated receptor Siglec-14, Sialic acid–binding immunoglobulin-type lectin 14 SIRPβI, signal regulatory protein βI TCR, T-cell receptor.
SIRPβI (CD172b) and Siglec-14 are expressed in a number of leukocytes, including monocytes and macrophages [37, 38]. Siglec-14 binds to sialic acid presented by numerous bacteria to induce responses including cytokine secretion . There is evidence that SIRPβI contributes to neutrophil transepithelial migration and macrophage phagocytosis, but a ligand has yet to be identified . A generic ligand is therefore very useful for the study of SIRPβI. As a member of the NK cell cytotoxicity family, NKp30 (CD337) is expressed in NK cells and binds both pathogen and cellular ligands to mediate NK cell cytotoxicity .
SIRPβI, Siglec-14, and NKp30 receptors each associate with adaptor proteins that contain cytoplasmic phosphorylatable tyrosine residues that mediate immune signalling [37–39]. Therefore, to establish stable cell lines, THP-1 cells were cotransduced with lentiviruses encoding the tagged receptor and appropriate adaptor (S3 Fig).
The αβ TCR complex consists of TCR α and β chains associated with a TCRζ homodimer and CD3δε and CD3γε heterodimers. The 1G4 TCR α chain and Twin-Strep-tagged β chain were transduced into a Jurkat nuclear factor kappa-light-chain-enhancer of activated B cells (NFκB) reporter cell line in which the production of eGFP is under the control of the NFκB promoter (S3 Fig) [14, 15]. Any 1G4 TCR α and β chains expressed at the cell surface are presumed to be associated with endogenous TCR/CD3 signalling subunits.
All four tagged receptors were activated by generic ligand cells with a clear dose-dependent response, which increased with the number of generic ligands per cell (Fig 3B–3E). This response was specific as shown by the absence of IL-8 secretion or NFκB-driven eGFP expression in samples containing negative control receptor cells (Fig 3B–3E). The EC50 values of the receptor responses from three independent experiments are shown in Fig 3F. Thus, the generic ligand can bind to and trigger several different receptors bearing an N-terminal Twin-Strep-tag.
Twin-Strep-tagged TCR responds to generic ligand and native ligand with a similar sensitivity
In order to validate this approach, we compared the response of the TCR to generic ligand with its response to native ligand, pMHC.
1G4 TCR and its cognate ligand NY-ESO-1157−165 9V peptide variant (SLLMWITQV) presented in complex with HLA-A*02 is a well-characterised receptor–ligand pair [40–42]. The dissociation constant of 1G4 TCR binding to 9V-HLA-A*02 (KD = 6–7 μM) is comparable to the KD we have measured for Twin-Strep-tag and trivalent Strep-Tactin-SpyCatcher (Fig 2A) [41, 42].
To compare the TCR response to either generic or native ligand, the Jurkat NFκB eGFP reporter cell line transduced with 1G4 TCR α and Twin-Strep-tagged β chains (S3 Fig) was presented to CHO cells that express both HLA-A*02 in the form of an SCD and the generic ligand anchor (Fig 4A, S3 Fig). These CHO cells were either preincubated with trivalent Strep-Tactin-SpyCatcher or loaded with 9V peptide. To allow a direct comparison between generic and pMHC ligand, the Jurkat NFκB eGFP cells were not transduced with the coreceptor CD8, since it binds MHC but not generic ligand.
(A) A cartoon depicting 1G4 TCR with β-chain N-terminal Twin-Strep-tag presented to either 9V-HLA-A*02 or generic ligand on CHO cells. (B) The average number of 9V-HLA-A*02 per cell as a function of peptide concentration added was measured using soluble fluorescent 1G4 high-affinity TCR and fluorescence quantitation beads. Interpolated numbers of 9V-HLA-A*02 are shown. (C) Response of Jurkat NFκB eGFP 1G4 TCRα/β cells to either generic ligand or 9V-HLA-A*02 presented on CHO cells. Receptor response, as indicated by eGFP expression under the control of the NFκB promoter, is shown normalised to the maximal receptor response to either 9V-HLA-A*02 or generic ligand. Error bars indicate the range (n = 2), and data are representative of three independent experiments. (D) EC50 values from individual experiments of Jurkat NFκB eGFP 1G4 TCRα/β cells responding to 9V-HLA-A*02 or generic ligand are plotted. Bars indicate the mean and standard deviation (n = 3). Summary numerical data are provided in S1 Data. AU, arbitrary units CHO, Chinese hamster ovary eGFP, enhanced green fluorescent protein NFκB, nuclear factor kappa-light-chain-enhancer of activated B cells TCR, T-cell receptor.
In order to quantitatively compare the TCR response to generic ligand or 9V-HLA-A*02, we measured the number of 9V-HLA-A*02 molecules on the CHO ligand cells. For this, we used a soluble affinity-enhanced (c58/c61) form of the 1G4 TCR that binds to 9V-HLA-A*02 with a much higher affinity than the wild-type TCR (KD = 71 pM) [25, 43]. This soluble 1G4 high-affinity TCR was labelled with Alexa Fluor 647 (1G4hi TCR AF647) and used in combination with fluorescence quantitation beads to interpolate the average number of 9V-HLA-A*02 per cell (Fig 4B, S4 Fig). Incubating CHO ligand anchor HLA-A*02 cells with varying concentrations of 9V peptide yielded a large dynamic range of ligand number per cell (Fig 4B). Therefore, we were able to present Jurkat NFκB eGFP 1G4 TCRα/β-Twin-Strep-tag cells with CHO ligand anchor HLA-A*02 cells presenting either 9V-HLA-A*02 or generic ligand at similar densities.
Jurkat NFκB eGFP 1G4 TCRα/β-Twin-Strep-tag cells responded to both 9V-HLA-A*02 and generic ligand in a dose-dependent, specific manner, visualised using the NFκB reporter (Fig 4C). The EC50 values from three independent experiments are shown in Fig 4D. There is a 2-fold difference in the average sensitivity between the receptor response to 9V-HLA-A*02 versus generic ligand.
Based on the structure of soluble 1G4 TCRα/β bound to cognate pMHC, we predict the presence of Twin-Strep-tag should not interfere with TCR-pMHC binding (PDB accession number: 2BNR) . We used soluble pMHC class I tetramer staining to confirm this. Because tetramer staining of Jurkat NFκB eGFP 1G4 TCRα/β cells in the absence of CD8 coreceptor expression was very poor, we used cells that express CD8. Jurkat NFκB eGFP cells expressing either nontagged, Strep-tag II–tagged, or Twin-Strep-tagged 1G4 TCRα/β and CD8α/β were matched for TCRβ chain and CD8α expression (S4 Fig). These cells showed comparable cognate pMHC tetramer staining (S4 Fig), suggesting the presence of Strep-tag II does not significantly interfere with pMHC binding.
In summary, we have demonstrated that the generic ligand can elicit a receptor response comparable to physiological ligand, reinforcing its usefulness for studying receptor activation.
Manipulating the generic ligand system
Our generic ligand system could be adapted to allow manipulation of ligand properties other than surface density, such as length, affinity, and valency, as illustrated in (Fig 5A–5C). For example, the receptor can be tagged with an N-terminal Strep-tag II and presented to monovalent Strep-Tactin-SpyCatcherΔ on cells, yielding a receptor–ligand pair with a 6-fold higher dissociation constant than the Twin-Strep-tag-trivalent Strep-Tactin pair, (KD = 43 μM) (Fig 5B, S5 Fig). Preparation of monovalent Strep-Tactin-SpyCatcherΔ and quantitation of monovalent Strep-Tactin-SpyCatcherΔ ligand numbers per cell are performed in the same manner as for the higher-affinity system (S5 Fig, S6 Fig). Siglec-14 with N-terminal Strep-tag II and expressed with its adaptor in THP-1 cells was able to respond to monovalent Strep-Tactin-SpyCatcherΔ presented on CHO cells (Fig 5D). The EC50 of this response (mean value and standard deviation of 1,000,000 and 330,000 generic ligands per cell) to a lower-affinity interaction was higher, by approximately 5-fold, compared to that measured for Siglec-14 with Twin-Strep-tag and trivalent Strep-Tactin-SpyCatcher (mean EC50 value and standard deviation of 190,000 and 170,000 generic ligands per cell) (Fig 3F, Fig 5E). Although this difference in EC50 correlates with the difference in KD, the expression levels of the Strep-tag II and Twin-Strep-tag receptors were not matched in these preliminary experiments.
(A) The extracellular region of the generic ligand can be elongated by insertion of inert spacer domains. (B) Mutated forms of Strep-Tactin/streptavidin can be substituted into the receptor–generic ligand interaction to investigate how changing binding affinity affects receptor activation and signalling. Strep-Tactin variants are shown in different colours. (C) Strep-Tactin-SpyCatcher tetramers with varying numbers of Strep-tag II–binding sites can be coupled to CHO ligand anchor cells to examine the effect of varying the valency of the generic ligand on NTR triggering. For example, Strep-tag II–tagged receptors can be presented to either monovalent or trivalent generic ligand. (D) Response of THP-1 Siglec-14–Strep-tag II DAP12 cells to monovalent Strep-Tactin or trivalent Strep-Tactin generic ligand presented on CHO cells. Receptor response is measured by IL-8 secretion. Data are representative of three independent experiments. Within each stimulation, a sample of CHO cells were taken and used to measure the number of Strep-tag II–binding sites per cell as in Fig 2. Ligand density was calculated from these numbers (see the Measuring generic ligand numbers per cell section). EC50 (E) and maximal response values (F) from individual experiments of THP-1 Siglec-14–Strep-tag II DAP12 cells responding to monovalent Strep-Tactin or trivalent Strep-Tactin generic ligand are plotted. Bars indicate the mean and standard deviation (n = 3). Summary numerical data are provided in S1 Data. CHO, Chinese hamster ovary DAP12, DNAX-activating protein of 12 kDa IL-8, interleukin 8 NTR, non-catalytic tyrosine-phosphorylated receptor Siglec-14, Sialic acid–binding immunoglobulin-type lectin 14.
In addition to monovalent Strep-Tactin, we presented the THP-1 Siglec-14 Strep-tag II cells to trivalent Strep-Tactin-SpyCatcher on CHO cells (Fig 5D). This increase in valency of the receptor–generic ligand interaction from monovalent to trivalent resulted in a 5-fold lower EC50 of IL-8 secretion response by the THP-1 cells (mean EC50 values of 200,000 versus 1,000,000 Strep-tag II–binding sites per cell for the trivalent and monovalent ligands, respectively). Although this shows that increased valency enhances activation of the Siglec-14 receptor, further experiments are required to determine to what extent this is the result of increasing receptor engagement or enhanced signalling.
The principles of the system can also be exploited to investigate poorly understood features of CARs such as requirements for their optimal signalling. There is growing interest in CARs with nanobody-based antigen-binding domains targeting tumour antigens (reviewed in ) [45, 46].
Here, we use standard first-generation CARs with either LaG17 or LaM8 nanobodies for ligand binding and TCRζ-chain intracellular region for signalling (LaG17-ζ and LaM8-ζ, Fig 6A and 6B). LaG17 and LaM8 bind to GFP and mCherry, respectively, with KD values of 50 nM and 63 nM (at 25°C) . To form the CAR ligands, CHO ligand anchor cells were incubated with varying concentrations of soluble GFP or mCherry fused to SpyCatcherΔ (Fig 6A–6D). GFP or mCherry are thereby presented on CHO cell surfaces at a wide range of concentrations (Fig 6C and 6D) for engagement by the appropriate CAR.
(A-B) LaG17 anti-GFP and LaM8 anti-mCherry CARs are expressed in Jurkat cells. The CAR ligands comprise the cell surface–expressed ligand anchor with N-terminal SpyTag and soluble GFP-SpyCatcherΔ or mCherry-SpyCatcherΔ covalently coupled to the anchor. For simplicity, CARs are shown bound to a single ligand. (C-D) Amount of CAR ligand per CHO cell as a function of GFP-SpyCatcherΔ (C) or mCherry-SpyCatcherΔ (D) concentration added to cells. Median fluorescence intensity values extracted from flow cytometry analyses of cells are shown. (E-F) Response of Jurkat LaG17-ζ and Jurkat LaM8-ζ cells to either GFP-SpyCatcherΔ or mCherry-SpyCatcherΔ presented on CHO cells. Jurkat CD69 cell surface expression is plotted against the relative levels of the specific CAR ligand on CHO cells. These are the GFP or mCherry median fluorescence intensity values interpolated from the data shown in Fig 6C and 6D. Data are representative of two independent experiments. (G) To extend this system to study the requirements for optimal costimulatory and inhibitory receptor signalling, cells expressing the LaG17-ζ CAR and a fusion protein consisting of LaM8 nanobody followed by the transmembrane and intracellular regions of a costimulatory or inhibitory receptor can be presented to CHO ligand anchor cells presenting both GFP-SpyCatcherΔ and mCherry-SpyCatcherΔ at titratable levels. (H) CHO ligand anchor cells were first incubated with a single below-saturation concentration of GFP-SpyCatcherΔ and then titrating concentrations of mCherry-SpyCatcherΔ. Median fluorescence intensity values extracted from flow cytometry analyses of cells are shown. Summary numerical data are provided in S1 Data. CAR, chimeric antigen receptor CHO, Chinese hamster ovary GFP, green fluorescent protein IgG4, immunoglobulin G4 mCherry, monomeric Cherry.
Jurkat cells transduced to stably express either LaG17- ζ or LaM8-ζ were activated in a clear dose-dependent manner by CHO cells presenting GFP or mCherry, respectively (Fig 6E and 6F). This Jurkat cell response, indicated by up-regulation of CD69 surface expression, was specific. CD69 up-regulation in Jurkat LaG17-ζ cells was not seen in response to CHO mCherry ligand cells nor in Jurkat LaM8-ζ cells in response to CHO GFP ligand cells.
The efficiency of coupling and the high number of SpyTag ligand anchors suggested that the system could be extended to couple with multiple SpyCatcher fusion proteins to create cells presenting multiple ligands (Fig 6G). Indeed, we show by flow cytometry that CHO ligand anchor cells preincubated to present one level of GFP-SpyCatcherΔ can be subsequently incubated with varying concentrations of mCherry-SpyCatcherΔ to titrate the surface-presented levels of this second ligand (Fig 6H). These cells could be used, for example, in combination with cells presenting both LaG17-ζ and a receptor comprising the LaM8 nanobody fused to transmembrane and cytoplasmic regions of costimulatory or inhibitory receptors. This would facilitate analysis of signal integration between multiple receptors, which remains poorly understood.
Chapter 1 - Introduction to the Biochemistry and Molecular Biology of Denitrification
This chapter provides an overview of the biochemistry and genetics of denitrification in such organisms. It considers the aspects of denitrification that occur in archaea and certain fungi. Denitrification has been mostly studied in Paracoccus denitrificans and Pseudomonas stutzeri and so it describes denitrification for each of these organisms in turn before considering to what extent general principles can be discerned. In recent years, high-resolution crystal structures have become available for these enzymes with the exception of the structure for NO-reductase. In general, the proteins required for denitrification are only produced under (close to) anaerobic conditions, and if anaerobically grown, cells are exposed to O2 and then the activities of the proteins are inhibited. Specialized denitrifiers, such as P. denitrificans and the denitrifying Pseudomonads, contain more than 40 genes, which encode the proteins that make up a full denitrification pathway. They include the structural genes for the enzymes and e − donors, their regulators as well as many accessory genes required for assembly, cofactor synthesis, and insertion into the enzymes. In contrast, some denitrifiers can only carry out the two central reactions of the pathway and use these activities to support growth, but the cost of maintaining this capability is a very small amount of genome space. It provides insights into the regulation of gene expression and the way in which some denitrification enzymes play different roles in bacteria.
Function of the Cell Membrane
The cell membrane gives the cell its structure and regulates the materials that enter and leave the cell. It is a selectively permeable barrier, meaning it allows some substances to cross, but not others. Like a drawbridge intended to protect a castle and keep out enemies, the cell membrane only allows certain molecules to enter or exit.
Crossing the Membrane
Small molecules, such as oxygen, which cells need in order to carry out metabolic functions such as cellular respiration, and carbon dioxide, a byproduct of these functions, can easily enter and exit through the membrane. Water can also freely cross the membrane, although it does so at a slower rate.
However, highly charged molecules, like ions, cannot directly pass through, nor can large macromolecules like carbohydrates or amino acids. Instead, these molecules must pass through proteins that are embedded in the membrane. In this way, the cell can control the rate of diffusion of these substances.
Another way the cell membrane can bring molecules into the cytoplasm is through endocytosis. The reverse process, where the cell delivers contents outside the membrane barrier, is called exocytosis.
Cells can also deliver substances across the cell membrane to the external environment through exocytosis, which is the opposite of endocytosis. During exocytosis, vesicles form in the cytoplasm and move to the surface of the cell membrane. Here, they merge with the membrane and release their contents to the outside of the cell. Exocytosis removes the cell’s waste products, which are the parts of molecules that are not used by the cell, including old organelles.
Signaling at the Cell Membrane
The cell membrane also plays an important role in cell signaling and communication. The membrane contains several embedded proteins that can bind molecules found outside of the cell and pass on messages to the inside of the cell.
Importantly, these receptor proteins on the cell membrane can bind to substances produced by other areas of the body, such as hormones. When a molecule binds to its target receptor on the membrane, it initiates a signal transduction pathway inside the cell that transmits the signal to the appropriate molecules.
As a result of these often complex signaling pathways, the cell can perform the action specified by the signaling molecule, such as making or stopping the production of a certain protein.
How does the structure of the cell membrane allow it to carry out these functions?
Brief Revision Guide to Immune System and Immune System Questions and Markschemes
Immunity and the Immune system is a topic that students do find hard.
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Remember that specific immunity requires clonal selection and clonal expansion - and that each B and T lymphocyte has one shape of receptor on the surface which is complementary to only one antigen.
Memory cells are produced in response to experiencing an antigen (either on a pathogen or a vaccine) - hence when you subsequently encounter the same antigen, the production of antibodies (specific only to that antigen) will be quicker and larger. If the pathogen mutates, then you will no longer possess a specific immunity as the antigens (proteins or glycoproteins) will be a different shape and no longer complementary to the receptors on the memory cells.
Learning the inflammatory response and being able to explain each part (rise in temperature, swelling, increased permeability. ) will help to reduce the number of pathogens is important.
You must know the structure and function of each part of the antibody.
There seems to be an obsession with opsonins.
You need to know phagocytosis in detail (phagolysosome, hydrolytic enzymes . )
You must be able to explain the differences between the primary and secondary responses of antibody production.
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What are Antigens?
An antigen is a foreign or &ldquonon-self&rdquo macromolecule (typically a protein) that reacts with cells of the immune system. However, not all antigens will provoke a response . For example, each of us produce a large number of self-antigens. Each of us has a unique set of self-antigens that do not trigger an immune response within ourselves. The absence of this immune response very important and highly regulated, it prevents scenarios where the immune cells begin to attack host cells. In the presence of foreign atnigens, proteins called antibodies attach to the antigens on the plasma membrane of the cell containing the antigen.
Antigens and ABO Blood Types
Like other cells, our red blood cells may or may not have self-antigens present on their cell membrane. The ABO blood typing is a naming scheme that states the presence or absence of just two antigens: antigen A and antigen B. The antigens that are present on the surface of our red blood cells determine our blood type. If we looking at the table below, we&rsquoll see that:
- &rarr Blood type A has A-antigens
- &rarr Blood type B has B-antigens
- &rarr Blood type AB has both A-antigens and B antigens
- &rarr Blood type O has neither antigen.
Molecular and Cell Biology
The teaching and research activities of the Department of Molecular and Cell Biology (MCB) concern the molecular structures and processes of cellular life and their roles in the function, reproduction, and development of living organisms.
This agenda covers a broad range of specialized disciplines, including biochemistry, biophysics, molecular biology, structural biology, genetics, genomics, bioinformatics, cell biology, developmental biology, tumor biology, microbiology, immunology, pathogenesis and neurobiology.
The types of living organisms from which the departmental faculty draws its working materials are as diverse as its disciplinary specializations — ranging from viruses and microbes through plants, roundworms, annelids, arthropods, and mollusks, to fish, amphibia, and mammals.
The faculty of the department is organized into five divisions: Biochemistry and Molecular Biology Cell and Developmental Biology Genetics, Genomics, and Development Neurobiology and Immunology and Pathogenesis.
The Cancer Research Laboratory is a research institute on the Berkeley campus that carries on a research, teaching, and service program designed to foster interdepartmental participation in cancer research. Some of the Department of Molecular and Cell Biology faculty are also members of the Cancer Research Laboratory. The central research program represents a multidisciplinary approach to an understanding of the mechanism of neoplastic transformation using a variety of systems. Graduate student and postdoctoral research programs are supported in various areas of tumor biology, biochemistry, cell biology, endocrinology, genetics, immunology, molecular biology, and tumor virology. The Cancer Research Laboratory also operates three research facilities:
Instrumentation in the facilities is operated by highly trained staff, and training is offered in methods and techniques associated with each facility. For more information, visit the CRL website.
The Functional Genomics Laboratory at Berkeley enables researchers to conduct state-of-the-art research in functional genomics, with a focus on using Next Generation sequencing technologies. These technologies include the sequencing of entire genomes of selected model systems and the ability to survey genome-wide patterns of gene expression and now allow the dissection of biological processes at unprecedented levels of detail. In particular, this research facility provides the infrastructure, technologies, and computational resources for the performance of DNA microarray experiments, which allow the analysis of mRNA expression from tens of thousands of genes at a time. The Functional Genomics Laboratory currently possesses all the equipment necessary for conducting DNA microarray experiments, including thermal cyclers fluidics robots microarray printing robots laser-scanning microscopes for microarray scanning an Affymetrix workstation and scanner and dedicated computers for data analysis and storage of informatics databases. For more information, go to this website.
The Robert D. Ogg Electron Microscope Laboratory is an instructional and research unit of the College of Letters and Science. It houses equipment for transmission electron microscopy (TEM) and scanning electron microscopy (SEM). The staff is skilled not only in the operation and maintenance of instruments but also in standard and most specialized techniques of sample preparation. Qualified undergraduates and graduate students, postdoctoral associates, faculty, and research staff in biological and physical sciences, once trained, may make arrangements for use of the instruments in research. Instruction is provided both in classes and in individual training. Registered students and faculty are not charged for training. Nominal charges are made for use of the laboratory for individual research work. With permission from the director, non-UC personnel can be accepted for training or laboratory use. Equipment can be used outside normal hours. The laboratory provides demonstrations of the electron microscope and preparative techniques for on-campus classes and can make special arrangements for tour groups. For more information, go to this website.