M.A. was supported by a Schr&#246;dinger fellowship of the Austrian Science Fund (FWF, J3086-B11) and thanks the Max-Planck-Society for financial and administrative support. G.S. and J.H. were supported by the Vienna Science and Technology Fund (WWTF, LS13-030).

<ol>
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D., Varma, R., Dustin, M. L., Vale, R. D. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Mechanisms+for+segregating+T+cell+receptor+and+adhesion+molecules+during+immunological+synapse+formation+in+Jurkat+T+cells.">Mechanisms for segregating T cell receptor and adhesion molecules during immunological synapse formation in Jurkat T cells.</a> Proc Natl Acad Sci USA. 104, 20296-20301 (2007).</li><li>Varma, R., Campi, G., Yokosuka, T., Saito, T., Dustin, M. L. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=T+cell+receptor-proximal+signals+are+sustained+in+peripheral+microclusters+and+terminated+in+the+central+supramolecular+activation+cluster.">T cell receptor-proximal signals are sustained in peripheral microclusters and terminated in the central supramolecular activation cluster.</a> Immunity. 25, 117-127 (2006).</li><li>Purbhoo, M. A., Irvine, D. J., Huppa, J. B., Davis, M. M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=T+cell+killing+does+not+require+the+formation+of+a+stable+mature+immunological+synapse.">T cell killing does not require the formation of a stable mature immunological synapse.</a> Nat Immunol. 5, 524-530 (2004).</li><li>Binz, H. K., Stumpp, M. T., Forrer, P., Amstutz, P., Pluckthun, A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Designing+repeat+proteins:+well-expressed,+soluble+and+stable+proteins+from+combinatorial+libraries+of+consensus+ankyrin+repeat+proteins.">Designing repeat proteins: well-expressed, soluble and stable proteins from combinatorial libraries of consensus ankyrin repeat proteins.</a> J Mol Biol. 332, 489-503 (2003).</li></ol>

The authors declare that they have no competing financial interest.

Measuring protein-protein interactions in situ is highly desirable especially when dealing with low affinity interactions such as TCR-pMHC binding 11. This is because the on-rate as well as the stability of such interactions are significantly influenced by the particular circumstances under which binding takes place. Minimally-invasive FRET-based imaging approaches are thus in principle perfectly suited for such tasks, yet involve a number of hurdles that must first be overcome. Noise generated by cellular autofluorescence limits the sensitivity of the measurements and should therefore be kept at a minimum. TIRF microscopy serves this need very well 12 but requires the functionalization of glass-slides, ideally in the form of a planar glass-supported lipid bilayer decorated with proteins of choice 13-15. Another advantage of a partly reconstitutive approach is that recombinant bilayer-resident FRET partners can be much more easily labeled in a quantitative, site-specific and rational manner with smaller and brighter fluorophores than would be possible with cell surface-expressed proteins. TCRs are tagged with recombinant scFVs, which do not influence T-cell recognition, as was tested previously 2. Moreover, the protein composition of the SLB, for example the density of pMHCs and the choice of accessory factors can be adjusted to one&#8217;s specific needs. We have previously performed experiments with varying densities of stimulatory pMHCs, but have not detected significant differences in 2D-koff and 2D-KD2.
So far here the recognition of MHC class II molecules has been dealt with only, mainly because of the nature of their peptide binding cleft, which is open at both ends and thus accommodates larger peptides including a linker for fluorophore attachment. In some cases such approach might also work for labeling MHC class I molecules 16 but great caution should be taken to verify their use in experiments. The sensitivity of T-cells towards antigens, which can be measured via T-cell proliferation assays, as well as the pMHC-TCR binding kinetics as measured in vitro by surface plasmon resonance should not be affected by the addition of the linker and fluorophore to the peptide. Alternatively, MHC class I molecules themselves can be labeled in a site-specific manner with the introduction of an unpaired cysteine within the sequence of the heavy chain (unpublished observations).
With the use of appropriate molecular probes any synaptic protein-protein interaction can in principle be studied in a fashion described herein. Such probes, e.g., scFVs or Designed Ankyrin Repeat Proteins (DARPins)17, should be monovalent and should bind their target stably without affecting the interaction of interest. Of course, structural information is highly desirable for rational probe design but not absolutely required. When establishing a new pair of FRET partners, it is recommended to record and analyze FRET in bulk first. Sites of label attachment may be varied considerably to maximize the FRET signal and also to verify that measured FRET yields differ based on the inter-dye distance. Once the system is optimized, single molecule FRET signals may be recorded by limiting the labeling of the high abundance FRET partner to 10-30% and bleaching the low abundance FRET partner until single molecules are resolvable in the field of illumination.
Last but not least it should be noted that SLBs approximate some but not all aspects of a physiological plasma membrane. Qualities such as membrane curvature and flexibility, domain compartmentalization, cytoskeletal rearrangements and cell motility as well as a high variety of surface-expressed membrane proteins are not represented by SLBs but might influence the process under investigation. Much effort will need to be invested to establish imaging modalities that allow monitoring protein-protein interactions with single molecule resolution in physiological synapses, which are inaccessible to TIRF imaging.

A more fundamental understanding of how T-cells recognize antigens requires looking at the right place, that is, within the immunological synapse formed between the T-cell and the APC. Here, molecular binding kinetics are not only determined by the inherent biochemical properties of the interaction partners involved but depend to a large extent on cellular parameters, which include cellular forces, membrane architecture and lateral interactions between membrane proteins as well as synapse-specific geometrical constraints 3. Biochemical approaches are limited in resolving power as they necessitate the disruption of at least one of the synaptic membranes involved. For this reason a FRET-based imaging methodology was developed to monitor binding of the TCR to antigenic pMHCs 2. Here T-cells are decorated with a recombinant and site-specifically labeled TCR&#946;-reactive single chain antibody fragment (scFV) and confronted with planar glass-supported lipid bilayers (SLBs), which harbor MHC class II molecules loaded with a fluorescently labeled antigenic peptide, costimulatory molecules and adhesion proteins. Synaptic binding between dye-labeled TCR and dye-labeled pMHC results in FRET, which can be monitored on a bulk and single molecule level by Total Internal Reflection Fluorescence (TIRF) microscopy.
In this article it is explained in detail how to utilize SLBs for assaying T-cell synapses, verify their integrity through a functional T-cell calcium-flux assay, conduct FRET measurements in bulk and with single molecule sensitivity, and analyze the acquired data. Recommendations are offered to producing properly conformed proteins required for bilayer functionalization. For more specific information regarding bilayer formation and setup of a suitable TIRF microscope please refer to an additional public access JoVE publication published back to back 4.
Nature of SLBs
Functionalizable SLBs can be readily generated from unilamellar vesicles (SUVs) containing the two lipids 1-palmitoyl-2-oleoyl-sn-gylcero-3-phosphocholine (short: POPC, 90-99%) and 1,2-dioleoyl-sn-glycero-3-{[N(5-amino-1-carboxypentyl) iminodiacetic acid] succinyl} (short: DGS NTA-Ni, 1-10%). SUVs spread on clean glass slides to form a contiguous planar bilayer 4. DGS-NTA-Ni serves to anchor polyhistidine-tagged proteins via polyhistidine-mediated complex-formation with the synthetic NTA-Ni-containing head group (Figure 1A). For stable association one typically replaces the native transmembrane domain and cytoplasmic tail of the adhesion protein ICAM-1 and the costimulatory molecule B7-1 with one tag containing twelve histidines (ICAM-1-12H, B7-1 -12H) (Figure 1B). The peptide-loaded class II molecule I-Ek contains two membrane-embedded (&#945; and &#946;) polypeptide chains. The transmembrane/cytoplasmic domains of both chains have to be replaced with a tag containing six histidines each (I-Ek&#945;6H &#946;6H or I-Ek-2x6H). As an alternative, extending the &#945;-chain with twelve histidines and leaving the extracellular domain of the &#946;-chain untagged (giving rise to I-Ek&#945;12H &#946;0H or I-Ek-12H) gives rise to satisfactory results (Figure 1B).
Site-specific labeling of pMHCs
It is important to label the pMHC stoichiometrically and site-specifically in order to be able to convert measured FRET yields into meaningful equilibrium binding constants. This can be achieved by chemical labeling of a synthetic peptide that is loaded into the peptide-binding cleft of recombinant histidine-tagged MHC class II molecules 2,5. The peptide includes all residues of the T-cell epitope as well as a short C-terminal linker (GGS) followed by cysteine (e.g. in the moth cytochrome c (MCC) peptide ANERADLIAYLKQATK-GGSC, the linker is marked in bold). This cysteine is used to label the peptide stoichiometrically with the use of maleimide-dye derivatives. At this point extra care should be devoted to verifying quantitative dye-coupling to the cysteine-containing peptide. HPLC-purification of the peptide-dye adduct is recommended and has to be followed by electrospray ionization mass spectroscopy. Any recorded masses corresponding to the peptide educt (without dye) reflect incomplete labeling. If this is true, the HPLC-purified peptide should be subjected to consecutive rounds of dye-labeling until labeling is deemed quantitative. Note that MALDI-TOF mass spectroscopy should be avoided as this method involves laser radiation for sample ionization. This treatment disintegrates the attached sensitive fluorophores before peptide mass is read out and thus underrepresents degrees of dye-conjugation.
Indirect yet site-specific labeling of cell-bound TCRs with the use of monovalent single chain FV fragments
It is still challenging to attach dyes to cell surface-associated proteins of living cells in a site-specific manner. To overcome this hurdle for surface-exposed TCRs, a monovalent single chain version (scFV) from the genes of the TCR&#946; -reactive monoclonal antibody H57-197 2has been constructed. The crystal structure of this antibody in complex with the TCR allows to rationally design a version, in which a serine residue in close proximity to the C-terminus of the MHC associated peptide (where the corresponding FRET partner dye is attached) is substituted for a cysteine residue. This mutant cysteine then serves as an acceptor for dye conjugation (Figure 2).
Methodologies to record FRET
Bulk FRET values are best suited to verify the relationship between chosen inter-dye distances and FRET efficiencies measured in this TCR-pMHC binding system 2. In addition, bulk FRET measurements reveal qualitative and quantitative differences in synaptic TCR-pMHC affinities (see below and protocol section 3.2). Various approaches for quantifying FRET efficiencies have been introduced in the literature 6. In this article FRET is recorded via
(a) donor recovery after acceptor bleaching, and via
(b) sensitized FRET acceptor emission.
The first method (a) requires the use of a FRET acceptor that can be easily photobleached, and a donor, which is rather photostable. In addition it is important to ensure that the photobleached acceptor is no longer capable of quenching the donor fluorescence. As the same detection channel (donor) is used for quantification, no correction factors and no chromatic aberrations have to be considered, which renders this methodology simple and reliable. However, quantitative measurements cannot be repeated on the same specimen spot and changes in FRET cannot be recorded over time. To avoid effects caused by molecular diffusion or cellular motility a fast bleaching step should be aimed for, which minimizes the time passing between the first FRET donor (before acceptor bleaching) and the second FRET donor image acquisition (after FRET acceptor bleaching). It is recommend to employ a powerful laser light source of the FRET acceptor excitation wavelength in order to minimize illumination and bleaching times.
In contrast, in the approach of sensitized FRET emission measurement (b) the FRET donor is excited and the emission of the FRET acceptor is observed in the FRET acceptor channel. Changes in FRET acceptor signal can be recorded over time but emission of the FRET donor into the red-shifted acceptor channel (termed bleedthrough) and FRET acceptor cross-excitation via donor excitation have to be accurately determined and subtracted from the recorded FRET acceptor channel. For this the corresponding FRET donor and FRET acceptor images have to be spatially aligned.
Detection of single molecule (sm) FRET events
With the use of lasers as excitation source, a sensitive camera and noise-attenuated TIRF microscopy the fluorescence of single fluorophores can be easily traced over time. Similar is true for the detection of intermolecular smFRET events. However, complications may be caused by FRET donor bleedthrough and cross-excitation of the FRET acceptor, and thus great care has to be taken when adjusting the fluorophore densities in the smFRET experiment.
In the protocol provided below (protocol section 4) the TCR was chosen as FRET donor in high abundance and pMHC as FRET acceptor in low abundance. To attenuate FRET donor bleedthrough sufficiently, decorate 10-30% of the TCRs with fluorescent scFV and 90-70% of the TCRs with non-fluorescent scFV. Here the FRET acceptor channel was chosen as single molecule channel because it is confocal with the single molecule FRET channel. This helps to align smFRET events with single molecule FRET acceptors, which is the basis of smFRET validation.
Extracting synaptic off-rates through smFRET measurements
Photobleaching of both FRET donor and FRET acceptor have to be accounted for when extracting the half-life of interactions from single molecule FRET traces. The number of observable FRET-signals at the beginning of their appearance as single donor-acceptor pair N(0) is reduced over time by both unbinding of the receptor-ligand complex and photobleaching. The number of surviving complexes at a given time N(t) can be mathematically expressed as follows:
<img alt="Equation 1" src="/files/ftp_upload/53157/53157eq1.jpg" />
In the photobleaching term exp(-t/&#964;bleach) the time t is described by the product of the number of observations n and the illumination time till because of the non-continuous, discrete observation mode (i.e., bleaching only occurs during illumination). Within the kinetic term exp-(t/&#964;off) the time t is the product of the number of observations n and the time tlag for a single FRET observation (i.e., kinetic unbinding happens continuously). Equation 1 can be expressed as:
<img alt="Equation 2" src="/files/ftp_upload/53157/53157eq2.jpg" />
The term &#964;bleach/&#964;ill describes the number of observations until bleaching occurs and is defined as the expectation value &#60;nbleach&#62; of its exponential function. Equation 2 can be simplified as follows:
<img alt="Equation 3" src="/files/ftp_upload/53157/53157eq3.jpg" />
The expectation value &#60;n(tlag)&#62; of the number of frames N(t) with observable FRET-events after time t is directly determined from the experiment. It depends on the settable time between observations (tlag) chosen in the experiment and the unknown values for &#964;off (the inverse of the off-rate koff ) and &#60;nbleach&#62;, the expectation value of number of observations before bleaching occurs.
Thus, calculation of the expectation value &#60;n(tlag)&#62; for at least two values of tlag allows the experimental determination of &#60;nbleach&#62; and &#964;off .
Extracting synaptic 2D-KD values through FRET-based measurements
Measuring TCR occupancy a, i.e., the ratio between bound TCRs and total TCRs, is central to determining synaptic 2D-KD values. According to equation 4 this term is directly proportional to the measured FRET yield as long as TCRs serves as FRET donors and pMHCs as FRET acceptors.
<img alt="Equation 4" src="/files/ftp_upload/53157/53157eq4.jpg" />
with a = TCR occupancy, C =conversion factor
C is a constant, which depends on the FRET system and the fluorophores used. It can be determined experimentally as shown below. a can be converted into a 2D-KD according to equation 5 when the initial density of TCR ligands prior to addition of T-cells to the bilayer is known. This is because of the high mobility of SLB-attached proteins and also because SLBs provide an almost inexhaustible reservoir of ligands 2.
<img alt="Equation 5" src="/files/ftp_upload/53157/53157eq5.jpg" />
with [pMHC initial] = initial density of pMHC prior to the addition of T-cells
With equations 4 and 5 one can now easily determine the synaptic 2D-KD between TCR and pMHC. This is most reliably done with FRET measurements based on donor recovery after acceptor bleaching (see protocol section 3.1).
However, to measure C the relationship between the FRET intensity IFRET (corrected for background, FRET donor bleedthrough and FRET acceptor cross-excitation) and TCR occupancy a has to be determined. For this, one needs to know the ratio R between the average fluorescence intensity of single TCR-associated FRET donor fluorophores (e.g. Cy3 or AF555) sm IFRET donor and the average intensity of single molecule FRET events sm IFRET. R depends on the FRET system in question, emission filters and camera used for fluorescence detection.
The TCR occupancy a can then be directly determined according to equation 6.
<img alt="Equation 6" src="/files/ftp_upload/53157/53157eq6.jpg" />
with R = sm IFRET donor / sm IFRET
R was determined as 1.45 for the H57 scFv- Cy3/pMHC-Cy5 system leads to:
a= bulk IFRET/ bulk ITCR-cy3 &#8226; 1.45
The relationship between the TCR occupancy a and the FRET yield can be determined by FRET donor recovery after acceptor bleaching. For this both parameters are plotted against one another for a number TCR microclusters as shown in Figure 4A.The slope of the linear fit indicates the conversion factor C (from equation 4).
As demonstrated in Figure 4A, C amounts for (a) the H57 scFV- Cy3/pMHC-Cy5 FRET system and (b) the applied microscope system configuration to 1.995. The TCR occupancy a can be readily deduced as follows:
TCR occupancy a = FRET yield &#8226; 1.995

<table border="1" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always">
	<tbody>
		<tr >
			<td >LB-media</td>
			<td >Fisher Scientific</td>
			<td >10000713</td>
			<td >bacterial expression</td>
		</tr>
		<tr >
			<td >Sf900 II</td>
			<td >Life Technologies</td>
			<td >10227402</td>
			<td>insect cell media for baculo virus production</td>
		</tr>
		<tr >
			<td >Insect-XPRESS with L-glutamine (Lonza)</td>
			<td >Fisher Scientific</td>
			<td >10564038</td>
			<td>insect cell media for baculo virus expression</td>
		</tr>
		<tr >
			<td >Sf9 cells</td>
			<td>Life Technologies</td>
			<td>11496-015</td>
			<td>cells for virus production and expansion</td>
		</tr>
		<tr >
			<td >High Five Cells</td>
			<td>Life Technologies</td>
			<td>B855-02</td>
			<td>cells for potein expression</td>
		</tr>
		<tr >
			<td >LB-media</td>
			<td >Fisher Scientific</td>
			<td >10000713</td>
			<td>bacterial expression</td>
		</tr>
		<tr >
			<td >Centramate System</td>
			<td>Pall</td>
			<td></td>
			<td>protein concentartion from large volumes</td>
		</tr>
		<tr >
			<td >Centramate cassette 10kDa cutoff</td>
			<td>Pall</td>
			<td>OS010T12</td>
			<td>protein concentartion from large volumes</td>
		</tr>
		<tr >
			<td >Amicon Ultra-15 Centrifugal Filter Units</td>
			<td>EMD Millipore</td>
			<td>UFC900308</td>
			<td>protein concentartion</td>
		</tr>
		<tr >
			<td >Amicon Ultra-4 Centrifugal Filter Units</td>
			<td>EMD Millipore</td>
			<td>UFC800308</td>
			<td>protein concentartion</td>
		</tr>
		<tr >
			<td >Amicon Stirred Ultrafiltration Cell Model 200 mL</td>
			<td>EMD Millipore</td>
			<td >5123</td>
			<td>protein concentartion</td>
		</tr>
		<tr >
			<td >&#196;kta pure 25L</td>
			<td >GE Healthcare</td>
			<td>29-0182-24</td>
			<td>protein purification</td>
		</tr>
		<tr >
			<td >Superdex 200 10/300 GL</td>
			<td >GE Healthcare</td>
			<td >17-5175-01</td>
			<td>protein purification</td>
		</tr>
		<tr >
			<td >Superdex 75 10/300 GL</td>
			<td >GE Healthcare</td>
			<td >17-5174-01</td>
			<td>protein purification</td>
		</tr>
		<tr >
			<td >Mono Q 5/50GL</td>
			<td >GE Healthcare</td>
			<td >17-5166-01</td>
			<td>protein purification</td>
		</tr>
		<tr >
			<td >Ni Sepharose 6 Fast Flow</td>
			<td >GE Healthcare</td>
			<td >17-5318-01</td>
			<td>protein purification</td>
		</tr>
		<tr >
			<td >Tricorn 10/20 column</td>
			<td >GE Healthcare</td>
			<td >28-4064-13</td>
			<td>protein purification</td>
		</tr>
		<tr >
			<td >Gilson HPLC system</td>
			<td >Gilson</td>
			<td ></td>
			<td>purificationof fluorochrome-coupled peptides</td>
		</tr>
		<tr >
			<td >Pursuit XRs C18, 5 &#181;m particle size, 21.2*250mm column size</td>
			<td >Agilent</td>
			<td >A6000250X212</td>
			<td>purificationof fluorochrome-coupled peptides</td>
		</tr>
		<tr >
			<td >Pursuit XRs C18, 5 &#181;m particle size, 21.2*50 mm column size</td>
			<td >Agilent</td>
			<td >A6000050G212</td>
			<td>purificationof fluorochrome-coupled peptides</td>
		</tr>
		<tr >
			<td >Tricorn 10/20 column&#160;</td>
			<td >GE Healthcare</td>
			<td >28-4064-13</td>
			<td>protein purification</td>
		</tr>
		<tr >
			<td >Gilson HPLC system</td>
			<td >Gilson</td>
			<td ></td>
			<td>purificationof fluorochrome-coupled peptides</td>
		</tr>
		<tr >
			<td >Pursuit XRs C18, 5 &#181;m particle size, 21.2*250mm column size</td>
			<td >Agilent</td>
			<td >A6000250X212</td>
			<td>purificationof fluorochrome-coupled peptides</td>
		</tr>
		<tr >
			<td >Pursuit XRs C18, 5 &#181;m particle size, 21.2*50 mm column size</td>
			<td >Agilent</td>
			<td >A6000050G212</td>
			<td>purificationof fluorochrome-coupled peptides</td>
		</tr>
		<tr >
			<td >Cy3 maleimide</td>
			<td >GE Healthcare</td>
			<td>PA23031</td>
			<td>site-specific protein labeling via mutant unpaired cysteines</td>
		</tr>
		<tr >
			<td >Cy5 maleimide</td>
			<td >GE Healthcare</td>
			<td>PA25031</td>
			<td>site-specific protein labeling via mutant unpaired cysteines</td>
		</tr>
		<tr >
			<td >Alexa Fluor 555 C2 Maleimide</td>
			<td >Life Technologies</td>
			<td>A-20346</td>
			<td>site-specific protein labeling via mutant unpaired cysteines</td>
		</tr>
		<tr >
			<td >Alexa Fluor 647 C2 Maleimide</td>
			<td >Life Technologies</td>
			<td >A-20347</td>
			<td>site-specific protein labeling via mutant unpaired cysteines</td>
		</tr>
		<tr >
			<td >Fura-2, AM, cell permeant</td>
			<td >Life Technologies</td>
			<td >F-1221</td>
			<td>calcium-sensitive dye for cell labeling</td>
		</tr>
		<tr >
			<td >dimethyl sulfoxide</td>
			<td >Sigma Aldrich</td>
			<td >151874</td>
			<td>for dissolving fura-2 am</td>
		</tr>
		<tr >
			<td >Hank&#39;s Balanced Salt Solution plus calcium/magnesium</td>
			<td >Fisher Scientific</td>
			<td >10225362</td>
			<td>imaging buffer</td>
		</tr>
		<tr >
			<td >PBS</td>
			<td >Life Technologies</td>
			<td >14190-136</td>
			<td></td>
		</tr>
		<tr >
			<td >Bovine Serum Albumin lyophilized powder</td>
			<td >Sigma Aldrich</td>
			<td >A2153</td>
			<td>supplement for imaging buffer</td>
		</tr>
		<tr >
			<td >14-4-4S antibody</td>
			<td >affimetrix eBioscience</td>
			<td >14-5980-81</td>
			<td>blocking antibody for H2-I-Ek (recognized by the 5c.c7, 2B4 and AND TCR)</td>
		</tr>
		<tr >
			<td >5 ml polypropylene round-bottom tube</td>
			<td >Becton Dickinson</td>
			<td >FALCON 352063</td>
			<td></td>
		</tr>
		<tr >
			<td >0.22 &#956;m Ultrafree-MC centrifugal filter unit</td>
			<td >EMD Millipore</td>
			<td >UFC30GV0S</td>
			<td></td>
		</tr>
		<tr >
			<td >Syringe filter 0.2&#181;m</td>
			<td >Millipore</td>
			<td >GVWP04700</td>
			<td></td>
		</tr>
		<tr >
			<td >TetraSpeck Microspheres, 0.1 &#181;m, fluorescent blue/green/orange/dark red</td>
			<td >Life technologies</td>
			<td >T-7279</td>
			<td></td>
		</tr>
		<tr >
			<td >Microscope for fura-2-based calcium measurements&#160;</td>
			<td >LEICA</td>
			<td >DMI4000B</td>
			<td></td>
		</tr>
		<tr >
			<td >Microscope for (single molecule) FRET measurements</td>
			<td >LEICA/ZEISS/NIKON/OLYMPUS</td>
			<td >for details please refer to parallel JoVE contribution by Axmann et al.</td>
			<td></td>
		</tr>
		<tr >
			<td >planar supported lipid bilayers</td>
			<td ></td>
			<td >for details please refer to parallel JoVE contribution by Axmann et al.</td>
			<td></td>
		</tr>
		<tr >
			<td >RPMI 1640, with L-Glutamine</td>
			<td >Life Technologies</td>
			<td >11554416</td>
			<td>T-cell media</td>
		</tr>
		<tr >
			<td >non-essential amino acid 100X</td>
			<td >Hyclone</td>
			<td >SH30238.01</td>
			<td>T-cell media supplement</td>
		</tr>
		<tr >
			<td >penicillin/streptomycin/L-glutamine 100x</td>
			<td >Life Technologies</td>
			<td >12000226</td>
			<td>T-cell media supplement</td>
		</tr>
		<tr >
			<td >2-mercaptoethanol</td>
			<td >Sigma Aldrich</td>
			<td >M6250</td>
			<td>T-cell media supplement</td>
		</tr>
		<tr >
			<td >mouse interleukin-2 recombinant protein</td>
			<td >BPS Bioscience</td>
			<td >90185-B</td>
			<td>T-cell media supplement</td>
		</tr>
		<tr >
			<td >Research Grade Fetal Bovine Serum</td>
			<td >Hyclone</td>
			<td >SV30160.03</td>
			<td>T-cell media supplement</td>
		</tr>
		<tr >
			<td >Origin (analysis program)</td>
			<td >OrigenLab</td>
			<td >http://www.originlab.com/</td>
			<td>non-linear fitting of two parameters (tauoff, [ntlag])</td>
		</tr>
	</tbody>
</table>

measuring tcr-pmhc binding in situ using a fret-based microscopy assay

T-cells are remarkably specific and effective when recognizing antigens in the form of peptides embedded in MHC molecules (pMHC) on the surface of Antigen Presenting Cells (APCs). This is despite T-cell antigen receptors (TCRs) exerting usually a moderate affinity (&#181;M range) to antigen when binding is measured in vitro1. In view of the molecular and cellular parameters contributing to T-cell antigen sensitivity, a microscopy-based methodology has been developed as a means to monitor TCR-pMHC binding in situ, as it occurs within the synapse of a live T-cell and an artificial and functionalized glass-supported planar lipid bilayer (SLB), which mimics the cell membrane of an Antigen presenting Cell (APC) 2. Measurements are based on F&#246;rster Resonance Energy Transfer (FRET) between a blue- and red-shifted fluorescent dye attached to the TCR and the pMHC. Because the efficiency of FRET is inversely proportional to the sixth power of the inter-dye distance, one can employ FRET signals to visualize synaptic TCR-pMHC binding. The sensitive of the microscopy approach supports detection of single molecule FRET events. This allows to determine the affinity and off-rate of synaptic TCR-pMHC interactions and in turn to interpolate the on-rate of binding. Analogous assays could be applied to measure other receptor-ligand interactions in their native environment.

The recording of intracellular calcium via the fura-2 calcium dye as well as the subsequent cellular analysis to verify the stimulatory potency and hence functionality of SLBs are shown in Figure 4. As becomes evident, calcium levels rise in T-cells (expressed as the normalized fura-2 340nm/380nm ratio with baseline being 1) immediately as soon as they settle onto the stimulatory SLBs. Calcium levels return to baseline levels shortly after the addition of a antibody which blocks pMHCs from TCR engagement and which terminates T-cell activation.
Figure 6 depicts a typical experiment involving FRET donor recovery after acceptor bleaching, which is employed to measure FRET yields and which serves to calculate 2D-KD values (shown in Figure 4). Please note the increase in FRET donor intensity, which represents TCR labeled via AF555, after rapid and complete ablation of the FRET acceptor species (here: AF647 associated with pMHCs). Also evident is the strong reduction in the FRET channel, i.e., the FRET-acceptor channel under FRET donor excitation, after FRET acceptor bleaching. The barely visible remaining signal corresponds to FRET donor bleedthrough. FRET yields within individual TCR microclusters or entire synapses are calculated based on the indicated measured intensity values (Figure 6B).
Figure 7 depicts a trajectory and time lapse of a single molecule FRET event visible in two time frames. As outlined above in the introduction such behavior is caused by both decay of synaptic TCR-pMHC binding and photobleaching. To discriminate between these two contributions, the experimental acquisition time frames have to be varied in duration: while photobleaching remains a constant, changes in FRET event trajectory length are only caused by the binding kinetics. A quantitation of tracelengths, which forms the basis for the calculation of off-rates and bleaching shown in Figure 7, are provided in tables 1 to 3.
Determination of 2D-KDs requires recording of bulk FRET yields for FRET-donor labeled TCRs. With the use of the experimentally deduced constant C (Figure 4), a FRET yield measured for a TCR microcluster or an entire synapse can be converted into the TCR occupancy a, i.e., the ratio of pMHC-engaged and total TCRs (Figure 4C). With known pMHC densities present on the SLB prior to addition of the T-cell, a values can be applied to determine synaptic 2D-KD values (Figure 4D). On-rates can be calculated with the law of mass action (2D-kon = 2D-koff/2D-KD) from the determined synaptic off-rate and 2D-KD values.
<img alt="Figure 1" src="/files/ftp_upload/53157/53157fig1.jpg" /> 
Figure 1. Schematic outline of the planar glass-supported lipid bilayer (SLB) system. (A) SLBs are composed of POPC (90-99%) and the synthetic lipid DGS Ni-NTA (1-10%) and form spontaneously when clean glass surfaces are charged with small unilamellar vesicles (SUVs) consisting of the corresponding lipids. (B) Once formed, such SLBs can be functionalized with soluble polyhistidine-tagged extracellular portions derived from pMHCs, costimulatory B7-1 proteins and ICAM-1 adhesion proteins, to serve as APCs for T-cells. For more information on preparing SLBs refer to Axmann et al.4. <a href="https://www.jove.com/files/ftp_upload/53157/53157fig1large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 2" src="/files/ftp_upload/53157/53157fig2.jpg" /> 
Figure 2. F&#246;rster Resonance Energy Transfer-based assay to quantitate TCR-pMHC binding in situ. (A) A composite structure of a TCR complexed with an H57 single chain fragment engaging a pMHC illustrates the FRET-based approach described herein. Note the short distance of about 41&#197; separating the two corresponding fluorophores undergoing FRET. Acceptor sites for fluorophore-maleimides are indicated in green and red. (B) The principle of detecting TCR-pMHC interactions in situ is illustrated. Only scFV-decorated TCRs and pMHCs (here I-Ek), which form specific complexes, give rise to a measurable FRET signal. <a href="https://www.jove.com/files/ftp_upload/53157/53157fig2large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 3" src="/files/ftp_upload/53157/53157fig3.jpg" /> 
Figure 3. Chromatograms of the final gel filtration step giving rise to monomeric scFVs and peptide-loaded I-Ek -2x6H molecules. X-axes represent retention volume in ml, Y-axes indicate absorbance at 280 nm in arbitrary units (AU). (A) H57 scFV site-specifically labeled with Alexa Fluor 555 maleimide was subjected to S75 chromatography to separate unreacted dye from the protein (step 1.2.5). Fractions corresponding to retention interval 14 to15 ml (dashed lines) represent labeled monomeric H57 scFV. (B) I-Ek -2x6H molecules complexed with the UV-cleavable ANP-space holder peptide had been UV-irradiated, incubated with site-specifically Alex 647 maleimide-labeled peptide and finally subjected to S200 chromatography to separate the protein from free peptide (step 1.1.2.4). The interval between the dashed lines contains properly folded and monomeric pMHCs. (A, B) 0.7 ml sample was applied to the column at the start of the rum (0 ml point). Collected fractions were concentrated. The protein-to-dye ratio was determined by photospectrometry prior to dialysis against PBS/50% glycerol (for storage at -20&#176;). <a href="https://www.jove.com/files/ftp_upload/53157/53157fig3large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 4" src="/files/ftp_upload/53157/53157fig4.jpg" /> 
Figure 4. Determining 2D-KDs and 2D-kons. (A) The correlation between the FRET yield as determined by donor recovery after acceptor bleaching and TCR occupancy was measured experimentally. TCR occupancy can be determined for individual TCR microclusters as explained in section 4.2. A linear fit of the data is displayed by the line, the slope of which is equal to the ratio C between TCR occupancy and the FRET yield. C is a constant specific for the FRET system and the fluorophores (here Cy3 and Cy5) employed. In this example it yielded 1.988. (B) FRET yield data were determined for individual TCR microclusters (N = 187, temperature = 24 &#176;C) through donor recovery of acceptor bleaching. Numbers below histogram bars indicate the upper limit within the interval. (C) Conversion of the data shown in (B) by multiplying measured FRET yields with the constant C determined in (A). Numbers below bars indicate the upper limit within the interval. (D) Histogram (semi-logarithmic, base = 4) depicting the distribution of 2D-KDs measured for individual TCR microclusters. The median 2D-KD is indicated in blue. Numbers below bars indicate the upper limit within the interval. (E) The histogram shown in (D) was converted into a 2D-kon -histogram (semi-logarithmic, base = 4) employing the synaptic koff for 24 &#176;C (0.41 s-1). The determined median 2D-kon value is indicated in blue. Data were originally published in Huppa et al.2 and are visualized here in a new format. <a href="https://www.jove.com/files/ftp_upload/53157/53157fig4large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 5" src="/files/ftp_upload/53157/53157fig5.jpg" /> 
Figure 5. Functional validation of SLBs employed for T-cell stimulation and imaging. (A) TCR-transgenic T-cell blasts loaded with fura-2 were confronted with stimulatory SLB harboring antigenic pMHCs, ICAM-1 and B-7. Cellular fura-2 emission excited at 340 nm and 380 nm as well as DIC images were recorded. As indicated, ratio values of the emission intensities excited at 340 and 380 nm are shown in the right panel. Addition of pMHC blocking antibodies 14 min into the experimental run resulted in a decrease in intracellular calcium levels comparable to that of resting T-cells. (B) A typical temporal profile of average fura-2 ratios in T-cells contacting stimulatory SLBs is characterized by a an initial rise in intracellular calcium which is 2 to 4 times higher compared to that of non-activated T-cells or T-cells deprived of antigen after antibody-mediated blockade. Green circles indicate time points illustrated in (A). <a href="https://www.jove.com/files/ftp_upload/53157/53157fig5large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 6" src="/files/ftp_upload/53157/53157fig6.jpg" /> 
Figure 6. Bulk FRET yields as measured through FRET donor recovery after FRET acceptor bleaching. (A) Shown is an example of a typical synaptic FRET-measurement. As is indicated on the left and on top a series of images was acquired with the use of a emission beam splitter giving rise to a FRET donor and a FRET acceptor channel (for more detailed information on beam splitters refer to Axmann et al4). The line shown in the left DIC image indicates the boundary of the T-cell synapse. Note the loss in intensity within the FRET acceptor channel as well is the increase in intensity in the FRET donor channel after FRET acceptor bleaching (step 4). (B) FRET efficiencies can be quantified as indicated for individual synaptic regions or for entire synapses. For inspection, images before and after FRET acceptor bleaching are shown with the use of two lookup tables (LUTs, green and physics). <a href="https://www.jove.com/files/ftp_upload/53157/53157fig6large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 7" src="/files/ftp_upload/53157/53157fig7.jpg" /> 
Figure 7. Single molecule FRET events appear and disappear insingle steps and are perfectly aligned with a single FRET acceptor fluorophore.The time lapse of the single molecule FRET event is shown. Images were acquired using a back-illuminated EMCCD camera. <a href="https://www.jove.com/files/ftp_upload/53157/53157fig7large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 8" src="/files/ftp_upload/53157/53157fig8.jpg" /> 
Figure 8. Determining &#964;off = 1/ koff from measured smFRET trajectories. (A) The normalized cumulative sums of observable FRET signals (derived from H57 scFV-AF555 decorated 5c.c7 TCR transgenic T-cell blasts recognizing I-Ek/K3-AF647 at 24&#176;C) for four different time lags (42 msec, 490 msec, 1,007 msec, 1,989 msec) were plotted as a function of the total number of observations. Mono-exponential fit functions give rise to corresponding the negative inverse of the expectation values &#60;n(tlag)&#62;. (B) Expectation values were plotted against delays tlag and fitted using equation&#160;&#60;n(tlag)&#62; = &#964;off /{(&#964;off /&#60;nbleach&#62;) + tlag} to yield&#964;offand &#60;nbleach&#62;. <a href="https://www.jove.com/files/ftp_upload/53157/53157fig8large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>

Watch this Scientific Journal Video about Measuring TCR-pMHC Binding In Situ using a FRET-based Microscopy Assay at JoVE.com

Measuring TCR-pMHC Binding In Situ using a FRET-based Microscopy Assay

This manuscript describes how to conduct (single molecule) F&#246;rster Resonance Energy Transfer (FRET)- based assays to measure the binding dynamics between T-cell antigen receptor (TCR) and antigenic peptide-loaded MHC molecules as they occur within the immunological synapse of a T-cell in contact with a functionalized planar supported lipid bilayer.

Measuring TCR-pMHC Binding In Situ using a FRET-based Microscopy Assay

T-cells are remarkably specific and effective when recognizing antigens in the form of peptides embedded in MHC molecules (pMHC) on the surface of Antigen ...

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12.2K Views.  Vienna University of Technology. This manuscript describes how to conduct (single molecule) Förster Resonance Energy Transfer (FRET)- based assays to measure the binding dynamics between T-cell antigen receptor (TCR) and antigenic peptide-loaded MHC molecules as they occur within the immunological synapse of a T-cell in contact with a functionalized planar supported lipid bilayer. 

Video: Measuring TCR-pMHC Binding In Situ using a FRET-based Microscopy Assay

Quantitatively Measuring In situ Flows using a Self-Contained Underwater Velocimetry Apparatus (SCUVA)

The ability to directly measure velocity fields in a fluid environment is necessary to provide empirical data for studies in fields as diverse as oceanography, ecology, biology, and fluid mechanics. Field measurements introduce practical challenges such as environmental conditions, animal availability, and the need for field-compatible measurement techniques. To avoid these challenges, scientists typically use controlled laboratory environments to study animal-fluid interactions. However, it is reasonable to question whether one can extrapolate natural behavior (i.e., that which occurs in the field) from laboratory measurements. Therefore, in situ quantitative flow measurements are needed to accurately describe animal swimming in their natural environment.
We designed a self-contained, portable device that operates independent of any connection to the surface, and can provide quantitative measurements of the flow field surrounding an animal. This apparatus, a self-contained underwater velocimetry apparatus (SCUVA), can be operated by a single scuba diver in depths up to 40 m. Due to the added complexity inherent of field conditions, additional considerations and preparation are required when compared to laboratory measurements. These considerations include, but are not limited to, operator motion, predicting position of swimming targets, available natural suspended particulate, and orientation of SCUVA relative to the flow of interest. The following protocol is intended to address these common field challenges and to maximize measurement success.

Quantitatively Measuring In situ Flows using a Self-Contained Underwater Velocimetry Apparatus SCUVA

This protocol provides instructions on how to use a self-contained underwater velocimetry apparatus (SCUVA), which is designed for quantification of in situ animal-generated flows. In addition, this protocol addresses challenges posed by field conditions, and includes operator motion, predicting position of animals, and orientation of SCUVA.

The ability to directly measure velocity fields in a fluid environment is necessary to provide empirical data for studies in fields as diverse as ...

Three-dimensional Optical-resolution Photoacoustic Microscopy

Optical microscopy, providing valuable insights at the cellular and organelle levels, has been widely recognized as an enabling biomedical technology. As the mainstays of in vivo three-dimensional (3-D) optical microscopy, single-/multi-photon fluorescence microscopy and optical coherence tomography (OCT) have demonstrated their extraordinary sensitivities to fluorescence and optical scattering contrasts, respectively. However, the optical absorption contrast of biological tissues, which encodes essential physiological/pathological information, has not yet been assessable. 
The emergence of biomedical photoacoustics has led to a new branch of optical microscopy optical-resolution photoacoustic microscopy (OR-PAM)1, where the optical irradiation is focused to the diffraction limit to achieve cellular1 or even subcellular2 level lateral resolution. As a valuable complement to existing optical microscopy technologies, OR-PAM brings in at least two novelties. First and most importantly, OR-PAM detects optical absorption contrasts with extraordinary sensitivity (i.e., 100%). Combining OR-PAM with fluorescence microscopy3 or with optical-scattering-based OCT4 (or with both) provides comprehensive optical properties of biological tissues. Second, OR-PAM encodes optical absorption into acoustic waves, in contrast to the pure optical processes in fluorescence microscopy and OCT, and provides background-free detection. The acoustic detection in OR-PAM mitigates the impacts of optical scattering on signal degradation and naturally eliminates possible interferences (i.e., crosstalks) between excitation and detection, which is a common problem in fluorescence microscopy due to the overlap between the excitation and fluorescence spectra. 
Unique for optical absorption imaging, OR-PAM has demonstrated broad biomedical applications since its invention, including, but not limited to, neurology5, 6, ophthalmology7, 8, vascular biology9, and dermatology10. In this video, we teach the system configuration and alignment of OR-PAM as well as the experimental procedures for in vivo functional microvascular imaging.

Optical-resolution photoacoustic microscopy (OR-PAM) is an emerging technology capable of imaging optical absorption contrasts in vivo with cellular resolution and sensitivity. Here, we provide a visualized instruction on the experimental protocols of OR-PAM, including system configuration, system alignment, typical in vivo experimental procedures, and functional imaging schemes.

Optical microscopy, providing valuable insights at the cellular and organelle levels, has been widely recognized as an enabling biomedical technology. As ...

Measuring the Mechanical Properties of Living Cells Using Atomic Force Microscopy

Mechanical properties of cells and extracellular matrix (ECM) play important roles in many biological processes including stem cell differentiation, tumor formation, and wound healing. Changes in stiffness of cells and ECM are often signs of changes in cell physiology or diseases in tissues. Hence, cell stiffness is an index to evaluate the status of cell cultures. Among the multitude of methods applied to measure the stiffness of cells and tissues, micro-indentation using an Atomic Force Microscope (AFM) provides a way to reliably measure the stiffness of living cells. This method has been widely applied to characterize the micro-scale stiffness for a variety of materials ranging from metal surfaces to soft biological tissues and cells. The basic principle of this method is to indent a cell with an AFM tip of selected geometry and measure the applied force from the bending of the AFM cantilever. Fitting the force-indentation curve to the Hertz model for the corresponding tip geometry can give quantitative measurements of material stiffness. This paper demonstrates the procedure to characterize the stiffness of living cells using AFM. Key steps including the process of AFM calibration, force-curve acquisition, and data analysis using a MATLAB routine are demonstrated. Limitations of this method are also discussed.

This paper demonstrates a protocol to characterize the mechanical properties of living cells by means of microindentation using an Atomic Force Microscope (AFM).

Mechanical  properties of cells and extracellular matrix (ECM) play important roles in many  biological processes including stem cell differentiation, ...

Real Time Monitoring of Intracellular Bile Acid Dynamics Using a Genetically Encoded FRET-based Bile Acid Sensor

F&#246;rster Resonance Energy Transfer (FRET) has become a powerful tool for monitoring protein folding, interaction and localization in single cells. Biosensors relying on the principle of FRET have enabled real-time visualization of subcellular signaling events in live cells with high temporal and spatial resolution. Here, we describe the application of a genetically encoded Bile Acid Sensor (BAS) that consists of two fluorophores fused to the farnesoid X receptor ligand binding domain (FXR-LBD), thereby forming a bile acid sensor that can be activated by a large number of bile acids species and other (synthetic) FXR ligands. This sensor can be targeted to different cellular compartments including the nucleus (NucleoBAS) and cytosol (CytoBAS) to measure bile acid concentrations locally. It allows rapid and simple quantitation of cellular bile acid influx, efflux and subcellular distribution of endogenous bile acids without the need for labeling with fluorescent tags or radionuclei. Furthermore, the BAS FRET sensors can be useful for monitoring FXR ligand binding. Finally, we show that this FRET biosensor can be combined with imaging of other spectrally distinct fluorophores. This allows for combined analysis of intracellular bile acid dynamics and i) localization and/or abundance of proteins of interest, or ii) intracellular signaling in a single cell.

We provide a detailed protocol to study bile acid dynamics in living cells using a genetically encoded BAS FRET sensor. This Bile Acid Sensor represents a unique tool to study (regulation of) bile acid transport and FXR activation in a wide range of cell types.

F&#246;rster Resonance Energy Transfer (FRET) has become a powerful tool for monitoring protein folding, interaction and localization in single cells. ...

Correlative Light- and Electron Microscopy Using Quantum Dot Nanoparticles

A method is described whereby quantum dot (QD) nanoparticles can be used for correlative immunocytochemical studies of human pathology tissue using widefield fluorescence light microscopy and transmission electron microscopy (TEM). To demonstrate the protocol we have immunolabeled ultrathin epoxy sections of human somatostatinoma tumor using a primary antibody to somatostatin, followed by a biotinylated secondary antibody and visualization with streptavidin conjugated 585 nm cadmium-selenium (CdSe) quantum dots (QDs). The sections are mounted on a TEM specimen grid then placed on a glass slide for observation by widefield fluorescence light microscopy. Light microscopy reveals 585 nm QD labeling as bright orange fluorescence forming a granular pattern within the tumor cell cytoplasm. At low to mid-range magnification by light microscopy the labeling pattern can be easily recognized and the level of non-specific or background labeling assessed. This is a critical step for subsequent interpretation of the immunolabeling pattern by TEM and evaluation of the morphological context. The same section is then blotted dry and viewed by TEM. QD probes are seen to be attached to amorphous material contained in individual secretory granules. Images are acquired from the same region of interest (ROI) seen by light microscopy for correlative analysis. Corresponding images from each modality may then be blended to overlay fluorescence data on TEM ultrastructure of the corresponding region.

A method is described whereby quantum dot (QD) nanoparticles can be used for correlative immunocytochemical studies of epoxy embedded human pathology tissue. We employ commercial antibody fragment conjugated QDs that are visualized by widefield fluorescence light microscopy and transmission electron microscopy.

A method is described whereby quantum dot (QD) nanoparticles can be used for correlative immunocytochemical studies of human pathology tissue using ...

Quantifying Microorganisms at Low Concentrations Using Digital Holographic Microscopy (DHM)

Accurately detecting and counting sparse bacterial samples has many applications in the food, beverage, and pharmaceutical processing industries, in medical diagnostics, and for life detection by robotic missions to other planets and moons of the solar system. Currently, sparse bacterial samples are counted by culture plating or epifluorescence microscopy. Culture plates require long incubation times (days to weeks), and epifluorescence microscopy requires extensive staining and concentration of the sample. Here, we demonstrate how to use off-axis digital holographic microscopy (DHM) to enumerate bacteria in very dilute cultures (100-104 cells/mL). First, the construction of the custom DHM is discussed, along with detailed instructions on building a low-cost instrument. The principles of holography are discussed, and a statistical model is used to estimate how long videos should be to detect cells, based on the optical performance characteristics of the instrument and the concentration of the bacterial solution (Table 2). Video detection of cells at 105, 104, 103, and 100 cells/mL is demonstrated in real time using un-reconstructed holograms. Reconstruction of amplitude and phase images is demonstrated using an open-source software package.

Quantifying Microorganisms at Low Concentrations Using Digital Holographic Microscopy DHM

Digital holographic microscopy (DHM) is a volumetric technique that allows imaging samples 50-100X thicker than brightfield microscopy at comparable resolution, with focusing performed post-processing. Here DHM is used for identifying, counting, and tracking microorganisms at very low densities and compared with optical density measurements, plate count, and direct count.

Accurately detecting and counting sparse bacterial samples has many applications in the food, beverage, and pharmaceutical processing industries, in ...

In Situ Microscopy for Real-time Determination of Single-cell Morphology in Bioprocesses

In situ monitoring in microbial bioprocesses is mostly restricted to chemical and physical properties of the medium (e.g.,pH value and the dissolved oxygen concentration). Nevertheless, the morphology of cells can be a suitable indicator for optimal conditions, since it changes with dependence on the growth state, product accumulation and cell stress. Furthermore, the single-cell size distribution provides not only information about the cultivation conditions, but also about the population heterogeneity. To gain such information, a photo-optical in situ microscopy device1 was developed to enable the monitoring of the single-cell size distribution directly in the cell suspension in bioreactors. An automated image analysis is coupled to the microscopy based on a neural network model, which is trained with user-annotated images. Several parameters, which are gained from the captures of the microscope, are correlated to process relevant features of the cells, like their metabolic activity. Until now, the presented in situ microscopy probe series was applied to measure the pellet size in filamentous fungi suspensions. It was used to distinguish the single-cell size in microalgae cultivation and relate it to lipid accumulation. The shape of cellular particles was related to budding in yeast cultures. The microscopy analysis can be generally split into three steps: (i) image acquisition, (ii) particle identification, and (iii) data analysis, respectively. All steps have to be adapted to the organism, and therefore specific annotated information is required in order to achieve reliable results. The ability to monitor changes in cell morphology directly in line or on line (in a by-pass) enables real-time values for monitoring and control, in process development as well as in production scale. If the off line data correlates with the real-time data, the current tedious off line measurements with unknown influences on the cell size become needless.

In Situ Microscopy for Real-time Determination of Single-cell Morphology in Bioprocesses

A photo-optical in situ microscopy device was developed to monitor the size of single cells directly in the cell suspension. The real-time measurement is conducted by coupling the photo-optical sterilizable probe to an automated image analysis. Morphological changes appear with dependence on the growth state and cultivation conditions.

In situ monitoring in microbial bioprocesses is mostly restricted to chemical and physical properties of the medium (e.g.,pH value and the dissolved ...

An Automated Method to Perform The In Vitro Micronucleus Assay using Multispectral Imaging Flow Cytometry

The in vitro micronucleus (MN) assay is often used to evaluate cytotoxicity and genotoxicity but scoring the assay via manual microscopy is laborious and introduces uncertainty in results due to variability between scorers. To remedy this, automated slide-scanning microscopy as well as conventional flow cytometry methods have been introduced in an attempt to remove scorer bias and improve throughput. However, these methods have their own inherent limitations such as inability to visualize the cytoplasm of the cell and the lack of visual MN verification or image data storage with flow cytometry. Multispectral Imaging Flow Cytometry (MIFC) has the potential to overcome these limitations. MIFC combines the high resolution fluorescent imagery of microscopy with the statistical robustness and speed of conventional flow cytometry. In addition, all collected imagery can be stored in dose-specific files. This paper describes the protocol developed to perform a fully automated version of the MN assay on MIFC. Human lymphoblastoid TK6 cells were enlarged using a hypotonic solution (75 mM KCl), fixed with 4% formalin and the nuclear content was stained with Hoechst 33342. All samples were run in suspension on the MIFC, permitting acquisition of high resolution images of all key events required for the assay (e.g. binucleated cells with and without MN as well as mononucleated and polynucleated cells). Images were automatically identified, categorized and enumerated in the MIFC data analysis software, allowing for automated scoring of both cytotoxicity and genotoxicity. Results demonstrate that using MIFC to perform the in vitro MN assay allows statistically significant increases in MN frequency to be detected at several different levels of cytotoxicity when compared to solvent controls following exposure of TK6 cells to Mitomycin C and Colchicine, and that no significant increases in MN frequency are observed following exposure to Mannitol.

The in vitro micronucleus assay is a well-established method for evaluating genotoxicity and cytotoxicity but scoring the assay using manual microscopy is laborious and suffers from subjectivity and inter-scorer variability. This paper describes the protocol developed to perform a fully automated version of the assay using multispectral imaging flow cytometry.

The in vitro micronucleus (MN) assay is often used to evaluate cytotoxicity and genotoxicity but scoring the assay via manual microscopy is laborious and ...

High-Throughput Identification of Resistance to Pseudomonas syringae pv. Tomato in Tomato using Seedling Flood Assay

Tomato is an agronomically important crop that can be infected by Pseudomonas syringae, a Gram-negative bacterium, resulting in bacterial speck disease. The tomato-P. syringae pv. tomato pathosystem is widely used to dissect the genetic basis of plant innate responses and disease resistance. While disease was successfully managed for many decades through the introduction of the Pto/Prf gene cluster from Solanum pimpinellifolium into cultivated tomato, race 1 strains of P. syringae have evolved to overcome resistance conferred by the Pto/Prf gene cluster and occur worldwide.
Wild tomato species are important reservoirs of natural diversity in pathogen recognition, because they evolved in diverse environments with different pathogen pressures. In typical screens for disease resistance in wild tomato, adult plants are used, which can limit the number of plants that can be screened due to their extended growth time and greater growth space requirements. We developed a method to screen 10-day-old tomato seedlings for resistance, which minimizes plant growth time and growth chamber space, allows a rapid turnover of plants, and allows large sample sizes to be tested. Seedling outcomes of survival or death can be treated as discrete phenotypes or on a resistance scale defined by amount of new growth in surviving seedlings after flooding. This method has been optimized to screen 10-day-old tomato seedlings for resistance to two P. syringae strains and can easily be adapted to other P. syringae strains.

High-Throughput Identification of Resistance to Pseudomonas syringae pv. Tomato in Tomato using Seedling Flood Assay

The seedling flood assay facilitates rapid screening of wild tomato accessions for the resistance to the Pseudomonas syringae bacterium. This assay, used in conjunction with the seedling bacterial growth assay, can assist in further characterizing the underlying resistance to the bacterium, and can be used to screen mapping populations to determine the genetic basis of resistance.

Tomato is an agronomically important crop that can be infected by Pseudomonas syringae, a Gram-negative bacterium, resulting in bacterial speck disease. ...

Continuous Measurement of Biological Noise in Escherichia Coli Using Time-lapse Microscopy

The protocol developed here offers a tool to enable computer tracking of Escherichia coli division and fluorescent levels over several hours. The process starts by screening for colonies that survive on minimal media, assuming that only Escherichia coli harboring the correct plasmid will be able to thrive in the specific conditions. Since the process of building large genetic circuits, requiring the assembly of many DNA parts, is challenging, circuit components are often distributed between multiple plasmids at different copy numbers requiring the use of several antibiotics. Mutations in the plasmid can destroy transcription of the antibiotic resistance genes and interject with resources management in the cell leading to necrosis. The selected colony is set on a glass-bottom Petri dish and a few focus planes are selected for microscopy tracking in both bright field and fluorescent domains. The protocol maintains the image focus for more than 12 hours under initial conditions that cannot be regulated, creating a few difficulties. For example, dead cells start to accumulate in the lenses' field of focus after a few hours of imaging, which causes toxins to buildup and the signal to blur and decay. Depletion of nutrients introduces new metabolic processes and hinder the desired response of the circuit. The experiment's temperature lowers the effectivity of inducers and antibiotics, which can further damage the reliability of the signal. The minimal media gel shrinks and dries, and as a result the optical focus changes over time. We developed this method to overcome these challenges in Escherichia coli, similar to previous works developing analogous methods for other micro-organisms. In addition, this method offers an algorithm to quantify the total stochastic noise in unaltered and altered cells, finding that the results are consistent with flow analyzer predictions as shown by a similar coefficient of variation (CV).

Continuous Measurement of Biological Noise in Escherichia Coli Using Time-lapse Microscopy

This work presents a microscopy method that allows live imaging of a single cell of Escherichia coli for analysis and quantification of the stochastic behavior of synthetic gene circuits.

The protocol developed here offers a tool to enable computer tracking of Escherichia coli division and fluorescent levels over several hours. The process ...