Becker W.,Becker and Hickl GmbH |
Shcheslavkiy V.,Becker and Hickl GmbH |
Frere S.,Tel Aviv University |
Slutsky I.,Tel Aviv University
Microscopy Research and Technique | Year: 2014
We present a technique that records transient changes in the fluorescence lifetime of a sample with spatial resolution along a one-dimensional scan. The technique is based on scanning the sample with a high-frequency pulsed laser beam, detecting single photons of the fluorescence light, and building up a photon distribution over the distance along the scan, the arrival times of the photons after the excitation pulses and the time after a stimulation of the sample. The maximum resolution at which lifetime changes can be recorded is given by the line scan period. Transient lifetime effects can thus be resolved at a resolution of about one millisecond. We demonstrate the technique for recording photochemical and nonphotochemical chlorophyll transients in plants and transient changes in free Ca2+ in cultured neurons. Microsc. Res. Tech. 77:216-224, 2014. © 2014 Wiley Periodicals, Inc.
Becker W.,Becker and Hickl GmbH |
Shcheslavskiy V.,Becker and Hickl GmbH
Photonics and Lasers in Medicine | Year: 2015
Near-infrared (NIR) dyes are used as fluorescence markers in small animal imaging and in diffuse optical tomography. In these applications it is important to know whether the dyes bind to proteins or to other tissue constituents, and whether their fluorescence lifetimes depend on the targets they bind to. Unfortunately, neither the optical beam paths nor the detectors of commonly used in confocal and multiphoton laser scanning microscopes (LSMs) directly allow for excitation and detection of NIR fluorescence. This paper presents three ways of adapting existing LSMs with time-correlated single photon counting (TCSPC) fluorescence lifetime imaging (FLIM) systems for NIR FLIM: 1) confocal systems with wideband beamsplitters and diode laser excitation, 2) confocal systems with wideband beamsplitters and one-photon excitation by titanium-sapphire lasers, and 3) two-photon systems with optical parametric oscillator (OPO) excitation and non-descanned detection. A number of NIR dyes are tested in biological tissue. All of them show clear lifetime changes depending on the tissue structures they are bound to. We therefore believe that NIR FLIM can deliver supplementary information about the tissue composition and on local biochemical parameters. © 2015 by De Gruyter.
Becker W.,Becker and Hickl GmbH
Journal of Microscopy | Year: 2012
Fluorescence lifetime imaging (FLIM) uses the fact that the fluorescence lifetime of a fluorophore depends on its molecular environment but not on its concentration. Molecular effects in a sample can therefore be investigated independently of the variable, and usually unknown concentration of the fluorophore. There is a variety of technical solutions of lifetime imaging in microscopy. The technical part of this paper focuses on time-domain FLIM by multidimensional time-correlated single photon counting, time-domain FLIM by gated image intensifiers, frequency-domain FLIM by gain-modulated image intensifiers, and frequency-domain FLIM by gain-modulated photomultipliers. The application part describes the most frequent FLIM applications: Measurement of molecular environment parameters, protein-interaction measurements by Förster resonance energy transfer (FRET), and measurements of the metabolic state of cells and tissue via their autofluorescence. Measurements of local environment parameters are based on lifetime changes induced by fluorescence quenching or conformation changes of the fluorophores. The advantage over intensity-based measurements is that no special ratiometric fluorophores are needed. Therefore, a much wider selection of fluorescence markers can be used, and a wider range of cell parameters is accessible. FLIM-FRET measures the change in the decay function of the FRET donor on interaction with an acceptor. FLIM-based FRET measurement does not have to cope with problems like donor bleedthrough or directly excited acceptor fluorescence. This relaxes the requirements to the absorption and emission spectra of the donors and acceptors used. Moreover, FLIM-FRET measurements are able to distinguish interacting and noninteracting fractions of the donor, and thus obtain independent information about distances and interacting and noninteracting protein fractions. This is information not accessible by steady-state FRET techniques. Autofluorescence FLIM exploits changes in the decay parameters of endogenous fluorophores with the metabolic state of the cells or the tissue. By resolving changes in the binding, conformation, and composition of biologically relevant compounds FLIM delivers information not accessible by steady-state fluorescence techniques. © 2012 Royal Microscopical Society.
Becker1 W.,Becker and Hickl GmbH
Springer Series in Chemical Physics | Year: 2015
Classic time-correlated single photon counting (TCSPC) detects single photons of a periodic optical signal, determines the times of the photons relative to a reference pulse, and builds up the waveform of the signal from the detection times. The technique achieves extremely high time resolution and near-ideal detection efficiency. The modern implementation of TCSPC is multi-dimensional. For each photon not only the time in the signal period is determined but also other parameters, such as the wavelength of the photons, the time from the start of the experiment, the time after a stimulation of the sample, the time within the period of an additional modulation of the excitation light source, spatial coordinates within an image area, or other parameters which can either vary randomly or are actively be modulated in the external experiment setup. The recording process builds up a photon distribution over these parameters. The result can be interpreted as a (usually large) number of optical waveforms for different combination of the parameters. The advantage of multidimensional TCSPC is that the recording process does not suppress any photons, and that it works even when the parameters vary faster than the photon detection rate. Typical multi-dimensional TCSPC implementations are multi-wavelength recording, recording at different excitation wavelengths, time-series recording, combined fluorescence and phosphorescence decay recording, fluorescence lifetime imaging, and combinations of these techniques. Modern TCSPC also delivers parameter-tagged data of the individual photons. These data can be used to build up fluorescence correlation and cross-correlation spectra (FCS and FCCS), to record fluorescence data from single molecules, or to record time-traces of photon bursts originating from single molecules diffusing through a small detection volume. These data are used to derive multi-dimensional histograms of the changes in the fluorescence signature of a single molecules over time or over a large number of different molecules passing the detection volume. The chapter describes the technical principles of the various multi-dimensional TCSPC configurations and gives examples of typical applications. ©Springer International Publishing Switzerland 2015
Yaseen M.A.,Massachusetts General Hospital |
Sakadzic S.,Massachusetts General Hospital |
Wu W.,Massachusetts General Hospital |
Becker W.,Becker and Hickl GmbH |
And 2 more authors.
Biomedical Optics Express | Year: 2013
Minimally invasive, specific measurement of cellular energy metabolism is crucial for understanding cerebral pathophysiology. Here, we present high-resolution, in vivo observations of autofluorescence lifetime as a biomarker of cerebral energy metabolism in exposed rat cortices. We describe a customized two-photon imaging system with time correlated single photon counting detection and specialized software for modeling multiple-component fits of fluorescence decay and monitoring their transient behaviors. In vivo cerebral NADH fluorescence suggests the presence of four distinct components, which respond differently to brief periods of anoxia and likely indicate different enzymatic formulations. Individual components show potential as indicators of specific molecular pathways involved in oxidative metabolism. © 2013 Optical Society of America.
Becker W.,Becker and Hickl GmbH
Medical Photonics | Year: 2015
Fluorescence lifetime imaging (FLIM) techniques for biological imaging have to unite several features, such as high photon efficiency, high lifetime accuracy, resolution of multi-exponential decay profiles, simultaneous recording in several wavelength intervals and optical sectioning capability. The combination of multi-dimensional time-correlated single photon counting (TCSPC) with confocal or two-photon laser scanning meets these requirements almost ideally. Multi-dimensional TCSPC is based on the excitation of the sample by a high repetition rate laser and the detection of single photons of the fluorescence signal. Each photon is characterised by its arrival time with respect to the laser pulse and the coordinates of the laser beam in the scanning area. The recording process builds up a photon distribution over these parameters. The result can be interpreted as an array of pixels, each containing a full fluorescence decay curve. More parameters can be added to the photon distribution, such as the wavelength of the photons, the time from a stimulation of the sample, or the time with respect to an additional modulation of the laser. In this review, the application of the technique will be described for the measurement of molecular environment parameters within a sample, protein interaction experiments by Förster resonance energy transfer (FRET), autofluorescence measurements of cells and tissue, and in-vivo imaging of human skin and the fundus of the human eye. © 2015
Agency: Cordis | Branch: FP7 | Program: CP-FP | Phase: HEALTH-2007-1.2-2 | Award Amount: 7.53M | Year: 2008
The proposal aims at the development and clinical validation of advanced non-invasive optical methodologies for in-vivo diagnosis, monitoring, and prognosis of major neurological diseases (stroke, epilepsy, ischemia), based on diffuse optical imaging by pulsed near infrared light. Established diagnostic imaging modalities (e.g. X-ray Computed Tomography, Magnetic Resonance Imaging, Positron Emission Tomography) provide 3D anatomical, functional or pathological information with spatial resolution in the millimetre range. However, these methods cannot be applied continuously or at the bedside. Diffuse optical imaging is expected to provide a valuable complementing tool to assess perfusion and blood oxygenation in brain tissue and their time evolution in a continuous or quasi-continuous manner. The devices will be portable and comparably inexpensive and can be applied in adults and in children. Time-domain techniques are acknowledged as offering superior information content and sensitivity compared to other optical methods, allowing for separation between contributions of surface tissues (skin and skull) and brain tissue. Time-domain imaging can also differentiate between the effects of scatter and those of absorption.The consortium plans major developments in technology and data analysis that will enhance time-domain diffuse optical imaging with respect to spatial resolution, sensitivity, robustness of quantification as well as performance of related instruments in clinical diagnosis and monitoring. The diagnostic value of time-domain diffuse optical imaging will be assessed by clinical pilot studies addressing specific neurological disorders, in comparison with established neurophysiological and neuroimaging techniques. Perspectives regarding clinical application of time-domain diffuse optical brain imaging will be estimated and a reliable basis for a potential commercialisation of this novel technique by European system manufacturers will be created.
Agency: Cordis | Branch: FP7 | Program: CP-FP | Phase: HEALTH-2007-1.2-2;HEALTH-2007-2.4.1-4 | Award Amount: 5.54M | Year: 2008
The overall objective of this proposal is to develop and validate a quantitative, minimally invasive diagnostic tool for early and conclusive detection, diagnosis and monitoring of disease and disease progression of breast and prostate cancer. A methodology will be developed making use of a combination of the probably most exciting recent advances in the field of light microscopy, for fluorescence-based optical imaging of individual sample cells. It includes advances which will take the spatial resolution far beyond the fundamental limits of optical resolution, the sensitivity down to an ultimate single-molecule level, and multi-parameter detection schemes significantly increasing the fluorescence information by which these cellular images can be analysed. Apart from detecting and identifying tumour markers in the samples, tumour-specific spatio-temporal molecular distributions within the intact sample cells will be exploited. This is to date an almost unexploited dimension of diagnostic information. By combining and supporting these novel optical methods with state-of-the-art affinity molecule biotechnology, , tumor biomarkers, fluorophore chemistry, and bioinformatic validation tools, all possible means will be exploited to extract a maximum amount of information out of very small amounts of sample material. We thereby expect that an improved, early and reliable diagnosis of breast and prostate cancer will be possible, from amounts of sample material small enough that a minimally invasive procedure such as Fine-needle aspiration (FNA) can be used. In addition, by the minimally invasive FNA-based sampling, serious sampling-related side-effects, such as seeding and spread of cancer cells can be completely avoided. Given the high incidence of breast and prostate cancer, and the utmost importance of an early and conclusive diagnosis for the prognosis of these diseases, the relevance of this project can not be overestimated.
News Article | October 5, 2016
Human recombinant BDNF was purchased from Millipore; d-2-amino-5-phosphonovalerate (d-AP5) and NSC-23766 were from Tocris; 1’-naphthylmethyl-4-amino-1-tert-butyl-3-(p-methylphenyl)pyrazolo[3,4-d] pyrimidine (1NMPP1) was from Santa Cruz and Shanghai Institute of Materia Medica, Chinese Academy of Sciences; and TrkB-Ig was a gift from Regeneron. The tat-CN21 peptide (YGRKKRRQRRRKRPPKLGQIGRSKRVVIEDDR) was synthesized by GenScript. All animal procedures were approved by the Duke Univeristy School of Medicine Animal Care and Use Committee. Both male and female rats and mice were used. TrkbF616A mutant mice were provided by D. Ginty21. Bdnffl/fl and Trkbfl/fl were provided by L. Parada17, 36. Rac1fl/fl animals were acquired from C. Brakebusch30. The genotype of each animal was verified before and after preparing slices using PCR of genomic DNA isolated from tail DNA before and slice samples after. Plasmids containing human RAC1 and PAK1(65–118) are gifts from M. Matsuda and S. Soderling, respectively. The Pak GTPase binding domain of PAK2 (PBD2) was prepared by introducing mutations L77P and S115L into PAK1(60–118) using a Site-Directed Mutagenesis kit (Stratagene). W56–mCh–MTBD was prepared by amplifying the Rac1 inhibitory peptide W56 (ref. 23) using overhang PCR with a C-terminal linker (GGGGGGGGGGGGGGGGGGGGGGGGMADQLTEEWHRGTAGPGS) and inserting it into pCAG-mCh-mCh (ref. 3) by removing the first mCh with EcoRI and KpnI restriction digest and replacing it with the W56-linker amplicon, creating pCAG-W56-(linker)-mCh. In parallel, the MTBD of human MAP2 (272-end)25 was isolated from a human cDNA library and PCR amplification. This amplicon was then further amplified with overhang PCR to contain a linker (same as above), and then inserted into pCAG-mCh-mCh using BamHI-NotI restriction digest to produce pCAG-mCh-(Linker)-MTBD. The two constructs were then combined using BamHI plus NotI restriction digest to create pCAG-W56-(linker)-mCh-(linker)-MTBD. The scrambled variant of W56–MTBD was created by randomly re-ordering the residues of W56. ARHGAP15-mCh-MTBD was made by inserting ARHGAP15 (1–723; Addgene plasmid 38903) into the -mCh-MTBD sequence described above by adding EcoRI and KpnI sites at the N and C terminus, respectively. DNRhoA and DNCdc42 variants of the X-mCh-MTBD construct were prepared by first incorporating an MfeI digestion site on the 3′ end of W56, then removing W56 by digestion with NheI/MfeI and insertion of the dominant-negative construct. Hippocampal slices were prepared from postnatal day 5–7 rats or mice in accordance with the animal care and use guidelines of Duke University Medical Centre. In brief, we deeply anaesthetized the animal with isoflurane, after which the animal was quickly decapitated and the brain removed. The hippocampi were isolated and cut into 350-μm sections using a McIlwain tissue chopper. Hippocampal slices were plated on tissue culture inserts (Millicell) fed by tissue medium (for 2.5 l: 20.95 g MEM, 17.9 g HEPES, 1.1 g NaHCO 5.8 g d-glucose, 120 μl 25% ascorbic acid, 12.5 ml l-glutamine, 2.5 ml insulin, 500 ml horse serum, 5 ml 1 M MgSO , 2.5 ml 1 M CaCl ). Slices were incubated at 35 °C in 3% CO . After 1–2 weeks in culture, CA1 pyramidal neurons were transfected with ballistic gene transfer using gold beads (8–12 mg) coated with plasmids containing 30 μg of total cDNA (Rac1 sensor, donor:acceptor = 1:2; eGFP + W56–MTBD, 5:1; Rac1 sensor + W56–MTBD, donor:acceptor:inhibitor = 2:4:1; TrkB sensor, donor:acceptor = 1:1; Cdc42 sensor, donor:acceptor = 1:1; RhoA sensor, donor:acceptor = 1:1). Cells expressing only eGFP were imaged 1–5 days after transfection, cells expressing TrkB were imaged 1–2 days after transfection, and all other plasmid combinations were imaged 2–5 days after transfection. For structural plasticity experiments, conditional knockout slices (Bdnffl/fl and Rac1fl/fl) were transfected with either eGFP alone or eGFP and tdTomato-Cre (1:1) for 3–7 days before imaging. For sensor experiments in these slices, the sensors were used in the ratios listed above with an amount of Cre recombinase equal to the amount of donor DNA. The presence of Cre was confirmed by nuclear-localized tdTomato signal. HEK293T cells (ATCC) were cultured in DMEM supplemented with 10% fetal calf serum at 37 °C in 5% CO . Transfection was performed at ~50–90% cell confluency using Lipofectamine (Invitrogen) and 2 μg ml−1 of total cDNA/35 mm dish, following the ratios listed above. Cells were used as an expression platform only, and were thus not rigorously tested for potential contamination from other cell lines. FRET imaging using a custom-built two-photon fluorescence lifetime imaging microscope was performed as previously described3, 31, 32. Two-photon imaging was performed using a Ti-sapphire laser (MaiTai, Spectraphysics) tuned to a wavelength of 920 nm, allowing simultaneous excitation of eGFP and mCh. All samples were imaged using <2 mW laser power measured at the objective. Fluorescence emission was collected using an immersion objective (60×, numerical aperture 0.9, Olympus), divided with a dichroic mirror (565 nm), and detected with two separate photoelectron multiplier tubes (PMTs) placed downstream of two wavelength filters (Chroma, HQ510-2p to select for green and HQ620/90-2p to select for red). The green channel was fitted with a PMT having a low transfer time spread (H7422-40p; Hamamatsu) to allow for fluorescence lifetime imaging, while the red channel was fitted with a wide-aperture PMT (R3896; Hamamatsu). Photon counting for fluorescence lifetime imaging was performed using a time-correlated single photon counting board (SPC-150; Becker and Hickl) controlled with custom software31, while the red channel signal was acquired using a separate data acquisition board (PCI-6110) controlled with Scanimage software33. A second Ti-sapphire laser tuned at a wavelength of 720 nm was used to uncage 4-methoxy-7-nitroindolinyl-caged-l-glutamate (MNI-caged glutamate) in extracellular solution with a train of 4–6 ms, 4–5 mW pulses (30 times at 0.5 Hz) near a spine of interest (‘sLTP stimulus’). Experiments were performed in Mg2+ fee artificial cerebral spinal fluid (ACSF; 127 mM NaCl, 2.5 mM KCl, 4 mM CaCl , 25 mM NaHCO , 1.25 mM NaH PO and 25 mM glucose) containing 1 μM tetrodotoxin (TTX) and 4 mM MNI-caged l-glutamate aerated with 95% O and 5% CO at 30 °C, as described previously. Subthreshold stimuli were delivered using a train of 1 ms, 4–5 mW pulses (30 times at 0.5 Hz). Crosstalk experiments were performed by first delivering an sLTP stimulus (4–6 ms), then delivering a subthreshold stimulus to a nearby (~2–5 μm) spine on the same dendrite ~90 s later, as previously described19. Anywhere from 1–5 spines were stimulated per cell, and a maximum of 3 crosstalk experiments were performed on a single cell. Spine volume was calculated as the background-subtracted integrated fluorescence intensity over a region of interest around the dendritic spine head (fluorescence, F). Change in spine volume was measured as F/F , in which F is the average fluorescence intensity before stimulation. Analysis of two-photon images outside of the context of 2pFLIM was performed in ImageJ. All experiments involving dendritic inhibitor constructs were performed in a blinded fashion until the experiments were complete (when the groups significantly diverged, or until 15–20 individual experiments across at least three cells were complete, whichever came first). To measure the fraction of donor bound to acceptor, we fit a fluorescence lifetime curve summing all pixels over a whole image with a double exponential function convolved with the Gaussian pulse response function: where τ is the fluorescence lifetime of donor bound with acceptor, P and P are the fraction of free donor and donor bound with acceptor, respectively, and H(t) is a fluorescence lifetime curve with a single exponential function convolved with the Gaussian pulse response function: in which τ is the fluorescence lifetime of the free donor, τ is the width of the Guassian pulse response function, F is the peak fluorescence before convolution and t is the time offset, and erfc is the error function. We fixed τ to the fluorescence lifetime obtained from free eGFP (2.6 ns). To generate the fluorescence lifetime image, we calculated the mean photon arrival time, 〈t〉, in each pixel as: then, the mean photon arrival time is related to the mean fluorescence lifetime, 〈τ〉, by an offset arrival time, t , which is obtained by fitting the whole image: For small regions-of-interest (ROIs) in an image (spines or dendrites), we calculated the binding fraction (P ) as: Polyhistidine-tagged super-folder GFP (sfGFP)–Rac1, mCh-PBD2 and their mutants were cloned into the pRSET bacterial expression vector (Invitrogen). Proteins were overexpressed in Escherichia coli (DH5α), purified with a Ni+-nitrilotriacetate (NTA) column (HiTrap, GE Healthcare), and desalted with a desalting column (PD10, GE Healthcare) equilibrated with PBS. The concentration of the purified protein was measured by the absorbance of the fluorophore (sfGFP, A = 83,000 cm−1 M−1 (ref. 34); mCh, A = 72,000 cm−1 M−1 (ref. 35)). Purified sfGFP–Rac1 was loaded with GppNHp (2’,3’-O-N-methyl anthraniloyl-GppNHp) and GDP by incubating in the presence of tenfold molar excess of GppNHp and GDP in MgCl -free PBS containing 1 mM EDTA for 10 min, respectively. The reaction was terminated by adding 10 mM MgCl . sfGFP–Rac1 and mCh–PBD2 were mixed and incubated at room temperature for 20 min. FRET between sfGFP and mCh was measured under 2pFLIM, and the fraction of sfGFP–Rac1 bound to mCh–PDB2 was calculated by fitting the fluorescence lifetime curve with a double exponential function (equation (1)). The dissociation constant was obtained by fitting the relationship between the binding fraction and the concentration of mCh–PDB2 ([mCh–PDB2]) with a Michaelis–Menten function. Sample sizes for all experiments were chosen based on signal-to-noise ratios identified in pilot experiments. The variances of all data were estimated and compared using Bartlett’s test or Levene’s test before further statistical analysis. The distribution patterns of Rho GTPase sensor activity was determined by performing a Shapiro–Wilk test for normality on the peak response (the same points used for statistical comparisons). All of the sensors tested adhered to the null hypothesis, and thus are considered normally distributed. As such, parametric statistics were used to compare values of Rho GTPases response. For multiple comparisons of sensor activity, data were first subjected to ANOVA, followed by a post-hoc test to determine statistical significance, according to the structure of the comparison being made. In cases where each condition is being compared to all other conditions in the group, the Tukey–Kramer method was used. In cases where each condition is being compared to a single control, Dunnet’s test was used instead. To compare values of non-normally distribution changes in spine volume, data were log-transformed to resolve skewness, then subjected to normal parametric statistics, as indicated in the figure legends. To support these statistical claims, non-parametric statistics were also applied to the original, non-transformed data using a Wilcoxon rank-sum test in place of t-tests, and the Kruskal–Wallis procedure in place of ANOVA, followed by a post-hoc analysis using Dunn’s test. All of the data tested were significant by both of these approaches. Data were only excluded if obvious signs of poor cellular health (for example, dendritic blebbing, spine collapse) were apparent. Crosstalk experiments comparing different genetic perturbations were performed in a blinded fashion. Experimenters were unblinded when either statistical significance was reached, or when experimental number was comparable to similar experiments that had reached statistical significance.
News Article | October 5, 2016
Human recombinant BDNF and human recombinant β-NGF were purchased from Millipore, K252a and d-2-amino-5-phosphonovalerate (d-AP5) and 2,3-dihydroxy-6-nitro-7-sulfamoyl-benzo[f]quinoxaline-2,3-dione (NBQX) were from Tocris, human-IgG was from Sigma, and 1’-naphthylmethyl-4-amino-1-tert-butyl-3-(p-methylphenyl)pyrazolo[3,4-d] pyrimidine (1NMPP1) was from Santa Cruz and Shanghai Institute of Materia Medica, Chinese Academy of Sciences. TrkB-Ig was a gift from Regeneron and the tat-CN21 peptide (YGRKKRRQRRRKRPPKLGQIGRSKRVVIEDDR) was synthesized by GenScript. TrkB–eGFP was prepared by inserting the coding sequence of mouse TrkB (obtained from a previously described plasmid29) into pEGFP-N1 (Clontech) containing the A206K monomeric mutation in eGFP and the CAG promoter30. The linker between TrkB and eGFP is TGRH. mRFP1–PLC–mRFP1 was prepared by inserting the coding sequence for the C-terminal SH2 domain of human PLC-γ1 (659–769; obtained from full-length, human PLC-γ1 purchased from Origene) into a tandem-mRFP1 plasmid containing the CAG promoter. The linkers between the mRFP1s and PLC-γ1 (659–769) are RSRAQASNS for the N terminus and GSG for the C terminus. TrkBY816F–eGFP was prepared by introducing a point mutation using the Site-Directed Mutagenesis Kit (Stratagene). Tandem mCherry (mCh–mCh) was generated as previously described16. HA–BDNF–Flag was a gift from A. West. The coding sequence for SEP (obtained from SEP-GluA1; ref. 31) was incorporated onto the 3′ end of HA–BDNF–Flag to generate HA–BDNF–Flag-SEP. HA–BDNF–Flag–mRFP1 was generated in a similar fashion. A plasmid containing mCh-IRES-TeTX was a gift from M. Ehlers. POMC-mCh was generated by amplifying the POMC peptide (MWCLESSQCQDLTTESNLLACIRACRLDL)27 using overhang PCR with a C-terminal linker (GGGGGGGGGGGGGGGGGGGGGGGGMADQLTEEWHRGTAGPGS). This amplicon was then inserted into the tandem mCh plasmid by replacing the coding sequence of the first mCh. All animal procedures were approved by the Duke University School of Medicine Animal Care and Use Committee, Max Planck Florida Institute for Neuroscience, and Weill Cornell Medical College Institutional Animal Care and Use Committees and were conducted in accordance with the NIH Guide for the Care and Use of Laboratory Animals. We used both male and female rats and mice. Rats and C57/B6 mice were obtained from Charles River, TrkbF616A mutant mice were provided by D. Ginty28, Bdnffl/fl and Trkbfl/fl mice were provided by L. Parada32, and Bdnf-HA mice were generated as previously described26. The genotype of each animal used was verified before and after preparing slices using PCR of genomic DNA isolated from tail DNA before and slice samples after. HeLa cells were obtained from the Duke University Cell Culture Facility. These cells had been authenticated using short-tandem repeat profiling and evaluated for mycoplasma contamination. Cells were cultured and maintained as previously described16. Cells were transfected with Lipofectamine 2000 using the manufacturer’s protocol (Invitrogen). Concentrations used were 0.5 μl ml−1 Lipofectamine and 1 μg ml−1 total cDNA (1:1 ratio of TrkB–eGFP to mRFP1–PLC–mRFP1 DNA). Then, 24–48 h later, culture media was replaced with HEPES-buffered ACSF for imaging (HACSF; 20 mM HEPES, 130 mM NaCl, 2 mM NaHCO , 25 mM d-glucose, 2.5 mM KCl and 1.25 mM NaH PO ; adjusted to pH 7.4 and 310 mOsm). After a 30-min equilibration period, transfected cells were imaged using 2pFLIM as described below. Cell stimulation was performed by directly adding BDNF or vehicle to the HACSF bathing the cells. Mixed cortical cultures were prepared as described previously33 and transfected with Lipofectamine 2000 using a modified protocol. For transfection of neurons in 3.5 cm dishes, 1 μl Lipofectamine was mixed with 1 μg of plasmid DNA (1 μg per construct transfected) in 100 μl of culture media for 20 min. Culture media was removed from the 3.5 cm dish until only 1 ml remained. The Lipofectamine/DNA solution was added to the neurons for 45 min. At this point, all the media was removed and replaced with 2 ml conditioned culture media. After 24–48 h, culture media was replaced with HACSF. To stimulate cells, we added BDNF or NGF directly to the HACSF bathing the cells. 30 min after stimulation, we added K252a to the HACSF. Cultured hippocampal slices were prepared from post-natal day 5–7 rats or mice, as previously described34, in accordance with the animal care and use guidelines of Duke University Medical Center. After 5–12 days in culture, CA1 pyramidal neurons were transfected with biolistic gene transfer using gold beads (12 mg; Biorad) coated with plasmids containing 20–40 μg of total cDNA (TrkB sensor: 15 μg TrkB–eGFP and 15 μg mRFP1–PLC–mRFP1; TrkB sensor plus mCh: 5 μg TrkB–eGFP, 5 μg mRFP1–PLC–mRFP1, and 20 μg mCh–mCh; TrkB sensor plus mCh and Cre: 5 μg TrkB–GFP, 5 μg mRFP1–PLC–mRFP1, 5 μg tdTom-Cre, and 15 μg mCh–mCh; BDNF–SEP plus mCh: 20 μg BDNF–SEP and 10 μg mCh–mCh; BDNF–SEP plus TeTX: 20 μg BDNF–SEP and 10 μg mCh-IRES-TeTX; BDNF–SEP plus POMC: 20 μg BDNF–SEP and 10 μg POMC–mCh; eGFP: 20 μg eGFP; and eGFP plus Cre: 10 μg eGFP plus 10 μg tdTom-Cre). Neurons expressing the TrkB sensor were imaged 12–48 h after transfection. Neurons expressing the TrkB sensor with mCh or mCh plus Cre were imaged 5–7 days after transfection. The addition of the mCh proved critical in limiting the TrkB sensor expression thereby allowing neurons to survive longer with the sensor present. Neurons expressing only eGFP were imaged 1–7 days after transfection. Neurons expressing eGFP plus Cre were imaged 5–9 days after transfection. FRET imaging using a custom-built two-photon fluorescence lifetime imaging microscope was performed as previously described13, 35. Two-photon imaging was performed using a Ti-sapphire laser (MaiTai, Spectraphysics) tuned to a wavelength of 920 nm, allowing simultaneous excitation of eGFP, mRFP1 and mCh. All samples were imaged using <2 mW laser power measured at the objective. Fluorescence emission was collected using an immersion objective (60×, numerical aperture 0.9, Olympus), divided with a dichroic mirror (565 nm), and detected with two separate photoelectron multiplier tubes (PMTs) placed downstream of two wavelength filters (Chroma, HQ510-2p to select for green and HQ620/90-2p to select for red). The green channel was fitted with a PMT having a low transfer time spread (H7422-40p; Hamamatsu) to allow for fluorescence lifetime imaging, while the red channel was fitted with a wide-aperture PMT (R3896; Hamamatsu). Photon counting for fluorescence lifetime imaging was performed using a time-correlated single photon counting board (SPC-150; Becker and Hickl) controlled with custom software13, while the red channel signal was acquired using a separate data acquisition board (PCI-6110) controlled with Scanimage software36. A second Ti-sapphire laser tuned at a wavelength of 720 nm was used to uncage 4-methoxy-7-nitroindolinyl-caged-l-glutamate (MNI-caged glutamate) in extracellular solution with a train of 4–6 ms, 4–5 mW pulses (30 times at 0.5 Hz) near a spine of interest. Experiments were performed in Mg2+ free artificial cerebral spinal fluid (ACSF; 127 mM NaCl, 2.5 mM KCl, 4 mM CaCl , 25 mM NaHCO , 1.25 mM NaH PO and 25 mM glucose) containing 1 μM tetrodotoxin (TTX) and 4 mM MNI-caged l-glutamate aerated with 95% O and 5% CO Experiments were performed at 24–26 °C (room temperature) or 30–32 °C using a heating block holding the ACSF container. Temperature measurements were made from ACSF within the perfusion chamber holding the slice. To measure the fraction of donor bound to acceptor, we fit a fluorescence lifetime curve summing all pixels over a whole image with a double exponential function convolved with the Gaussian pulse response function: in which τ is the fluorescence lifetime of donor bound with acceptor, P and P are the fraction of free donor and donor bound with acceptor, respectively, and H(t) is a fluorescence lifetime curve with a single exponential function convolved with the Gaussian pulse response function: in which τ is the fluorescence lifetime of the free donor, τ is the width of the Guassian pulse response function, F is the peak fluorescence before convolution and t is the time offset, and erfc is the error function. We fixed τ to the fluorescence lifetime obtained from free mEGFP (2.6 ns). To generate the fluorescence lifetime image, we calculated the mean photon arrival time, 〈t〉, in each pixel as: then, the mean photon arrival time is related to the mean fluorescence lifetime, 〈τ〉, by an offset arrival time, t , which is obtained by fitting the whole image: For small regions-of-interest (ROIs) in an image (spines or dendrites), we calculated the binding fraction (P ) as: BDNF–SEP imaging was performed by interleaving 8 Hz two-photon imaging with two-photon glutamate uncaging (30 pulses at 0.5 Hz). Multiple (1–30) spines were imaged on each neuron. Change in BDNF–SEP fluorescence was measured as ΔF/F after subtracting background fluorescence. Uncaging-triggered averages were calculated as the average increase in SEP fluorescence after each individual uncaging pulse. Red fluorescence increase was smoothed using a 16-frame window. For visualizing BDNF–mRFP1 localization in CA1 pyramidal neurons, images were obtained using a Leica SP5 laser scanning confocal microscope (Leica). During 2pFLIM and BDNF–SEP imaging (Figs 2, 3), spine volume was reported using the red fluorescent intensity from mRFP1 or mCh. For two-photon imaging without FLIM (Fig. 4), green fluorescent intensity from eGFP was used. In all experiments, spine volume was measured as the integrated fluorescent intensity after subtracting background (F). Spine volume change was calculated by F/F , in which F is the average spine volume before stimulation. Additionally, to compare basal spine size/morphology between various conditions, maximal spine (F ) and dendrite (F ) fluorescent intensities were measured and the F /F ratio was calculated after subtracting background fluorescence. E14.5/15.5 timed-pregnant Bdnffl/fl mice were deeply anaesthetized using an isoflurane–oxygen mixture. The uterine horns were exposed and approximately 1–2 μl of AAV solution mix (containing AAV1.CAG.EGFP, AAV1.CAG.Flex.tdTomato and AAV1.hSyn.Cre, all from U Penn vector core) was injected through a pulled-glass capillary tube into the right lateral ventricle of each embryo. To achieve sufficient labelling of eGFP CA1 neurons alongside sparse expression of Cre + BDNF knockout tdTomato neurons, eGFP and Flex-tdTomato viruses were used at concentration of ~1012 viral genome copies per μl, and Cre was diluted (~100-fold) in PBS at a dilution determined to achieve a sparse labelling density of Cre-positive CA1 neurons. LTP experiments in Fig. 5 and Extended Data Fig. 10 were performed in Max Planck Florida Institute (MPFI) and Duke University, respectively. Mice (wild type, TrkbF616A, or Bdnffl/fl age 21–42 days) were sedated by isoflurane inhalation, and the brain was removed and dissected in a chilled cutting solution (124 mM choline chloride, 2.5 mM KCl, 26 mM NaHCO , 3.3 mM MgCl , 1.2 mM NaH PO , 10 mM d-glucose and 0.5 mM CaCl : MPFI or 110 mM sucrose, 60 mM NaCl, 3 mM KCl, 1.25 mM NaH PO , 28 mM NaHCO , 0.5 mM CaCl , 7.0 mM MgCl , and 5 mM d-glucose. The solutions were saturated with 95% O plus 5% CO , pH 7.4)37. Coronal slices (250 μm: MPFI) or transverse hippocampal slices (400 μm: Duke) were prepared and maintained in oxygenated ACSF (MPFI/Duke: 127/124 mM NaCl, 2.5/1.75 mM KCl, 10/11 mM d-glucose, 26/25 mM NaHCO , 1.25/0 mM NaH PO , 0/1.25 mM KH PO , 1.3/2.0 MgCl and 2.4/2.0 CaCl ,) in a submerged chamber at 32–34 °C for at least 1 h before use. Electrophysiological recordings were performed in ACSF (plus picrotoxin at MPFI). CA1 pyramidal neurons in acute hippocampal slices from wild-type and TrkbF616A mice were visualized using oblique illumination or differential interference contrast (DIC). For Bdnffl/fl experiments, Cre-negative (eGFP-expressing) and Cre-positive (tdTomato-expressing) neurons were identified and targeted with fluorescence microscopy. Patch pipettes (3–6 MΩ) were filled with an internal solution (130 mM K gluconate, 10 mM, Na phosphocreatine 4 mM MgCl ,4 mM NaATP, 0.3 mM MgGTP, 3 mM l-ascorbic acid and 10 mM HEPES, pH 7.4, and 310 mOsm at MPFI or K-gluconate 140 mM, HEPES 10 mM, EGTA 1 mM, NaCl 4 mM, Mg ATP 4 mM, and Mg GTP 0.3 mM, pH 7.25, and 290 mOsm at Duke). Series resistances (10–40 MΩ) and input resistances (100–300 MΩ) were monitored throughout the experiment using negative voltage steps. The membrane potential was held at −70 mV. Experiments were performed at room temperature (~21 °C) and slices were perfused with oxygenated ACSF. For TrkbF616A/wild-type experiments, 1NMMP1 or vehicle was added to the ACSF before stimulation. For TrkB-Ig experiments, slices were incubated in 2 μg ml−1 TrkB-Ig or control human IgG for at least 2 h before the experiments. EPSCs were evoked by extracellular stimulation of Schaffer collaterals using a concentric bipolar stimulating electrode (World Precision Instruments) at a rate of 0.03 Hz. LTP was induced by pairing a 2-Hz stimulation with a postsynaptic depolarization to 0 mV for 15 s (MPFI) or 75 s (Duke). EPSC potentiation was assessed for 30–45 min (for TrkbF616A experiments), 40–60 min (for Bdnffl/fl experiments) or 20–30 min (for TrkB-Ig experiments) after stimulation. HeLa cells were transfected with the TrkB sensor (TrkB–eGFP and mRFP1–PLC–mRFP1) using Lipofectamine 2000 as described above. Then, 24–48 h after transfection, the media bathing the cells was exchanged for HEPES buffered ACSF for biochemistry (150 mM NaCl, 3 mM KCl, 10 mM HEPES pH 7.35, 20 mM glucose, and 310 mOsM). After a 30-min equilibration period, cells were stimulated with 100 ng ml−1 BDNF for 10 min. Following stimulation, cells were washed in ice-cold PBS (Gibco), and then lysed in modified RIPA buffer (50 mM Tris-HCl pH 7.4, 150 mM NaCl, 1% NP-40, 0.25% sodium deoxycholate, 1 mM EDTA, 1 mM PMSF, 1 mM Na VO , and protease inhibitors) for 10 min on ice. The supernatant was collected after a 10 min centrifugation at 16,000g at 4 °C. At this point, a small volume of the supernatant was added to SDS-sample buffer and saved as the ‘cell lysate’ sample. The remaining supernatant was pre-cleared using protein G Sepharose beads (25 μl, Roche) for 30 min at 4 °C. After pre-clearing, the supernatant was incubated with 20 μg mouse monoclonal anti-phosphotyrosine (BD Transduction Labs) at 4 °C overnight. The immunocomplexes were precipitated with protein G Sepharose beads (50 μl) for 3 h at 4 °C and then analysed with western blotting. Antibodies used in western blotting included TrkB (Millipore), GFP (Abcam), actin (Sigma), and pTrkB(Y515) (Sigma). Male adult (~2–3 months old) Bdnf-HA knock-in mice26 and aged matched wild-type C57/BL mice were used. The same investigator (T.A.M.) perfused all mice (Bdnf-HA and wild type) to maintain consistency between groups. Mice (3 per group) were deeply anaesthetized with sodium pentobarbital (150 mg kg−1, i.p.) and perfused sequentially through the ascending aorta with: (1) ~5 ml saline (0.9%) containing 2% heparin, and (2) 30 ml of 3.75% acrolein and 2% paraformaldehyde in 0.1 M phosphate buffer (PB; pH 7.4)38. Following removal from the skull, the brain was post-fixed for in 2% acrolein and 2% paraformaldehyde in PB 30 min. Brains were then sectioned (40 μm thick) on a Vibratome and stored at −20 °C in cryoprotectant until use. For each animal, two dorsal hippocampal sections were processed for immunoelectron microscopy (immunoEM) experiments using previously described methods38. Before immunohistochemical processing, sections were rinsed in PB, and experimental groups were coded with hole-punches so that tissue could be run in single crucibles, ensuring identical exposure to all reagents. Before processing for immunolabelling, sections were treated with 1% sodium borohydride for 30 min to remove free aldehyde sites. Sections then were rinsed in PB followed by a rinse in 0.1 M Tris-saline (TS; pH 7.6) and then a 30 min incubation in 0.5% BSA in TS. Sections then were incubated in primary rabbit anti-HA (1:1,000; Sigma) in 0.025% Triton-X 100 and 0.1% BSA in TS for 1 day at room temperature and 4 days at 4 °C. Sections then were incubated in donkey anti-rabbit biotinylated IgG (1:400; Jackson Immunoresearch Laboratories) for 30 min followed by a 30 min incubation in avidin-biotin complex (ABC; Vectastain Elite Kit, Vector Laboratories) in TS (1:100 dilution). Sections were developed in 3,3′-diaminobenzidine (Sigma-Aldrich) and H O in TS. All antibody incubations were performed in 0.1% BSA/TS and separated by washes in TS. Sections were post-fixed in 2% osmium tetroxide for 1 h, dehydrated, and flat embedded in Embed-812 (EMS) between two sheets of Aclar plastic. Brain sections containing the CA1 and dentate gyrus were selected from the plastic embedded sections, glued onto Epon blocks and trimmed to 1 mm-wide trapezoids. Ultra-thin sections (70 nm thickness) through the tissue-plastic interface were cut with a diamond knife (EMS) on a Leica EM UC6 ultratome, and sections were collected on 400-mesh, thin-bar copper grids (EMS). Grids were then counterstained with uranyl acetate and Reynold’s lead citrate. An investigator blinded to animal condition performed the data collection and analysis. One section from each of Bdnf-HA and wild-type animals was analysed (n = 3 each group). The thin sections were examined and photographed on a Tecnai Biotwin transmission electron microscope (FEI). Cell profiles were identified by defined morphological criteria39. Dendritic profiles generally were postsynaptic to axon terminals and contained regular microtubule arrays. Dendritic spines also were usually postsynaptic to axon terminal profiles and sometimes contained a spine apparatus. Axon terminals contained small synaptic vesicles and occasional dense-core vesicles. Unmyelinated axons were profiles smaller than 0.15 μm that contained a few small synaptic vesicles and lacked a synaptic junction in the plane of section. Glial profiles were distinguished by the presence of glial filaments (astrocytic profiles), by the presence of microtubules and/or their tendency to conform irregularly to the boundaries of surrounding profiles. ‘Unknown profiles’ were those that contained immunoperoxidase reaction product but could not be definitively placed in one of the above categories. From each block, 4 grid squares (each square was 55 × 55 μm2) each from the CA1 near stratum radiatum (nSR in Fig. 3; that is, adjacent to the pyramidal cell layer) and distal stratum radiatum (dSR in Fig. 3; that is, 50–150 μm away from the pyramidal cell layer) were randomly sampled for analysis. Thus, 12,100 μm2 was sampled for each area in each block. Grid squares were selected plastic-tissue interface to ensure even antibody tissue penetration38. Immunoperoxidase labelling for HA was evident as a characteristic, electron-dense DAB reaction product precipitate. All peroxidase labelled profiles from each square were photographed and categorized. Animal codes were not broken until all 6 blocks were analysed. Sample sizes for all experiments were chosen based on signal-to-noise ratios identified in pilot experiments. Variances of all data sets were estimated and compared using Bartlett’s or Levene’s test before further statistical analysis. Randomization of animals and/or slices was not needed. To evaluate distribution patterns of TrkB sensor activity, spine volume change, and BDNF–SEP signal, peak responses for each data set (the same points used for statistical comparisons) were subjected to a Shapiro–Wilk test for normality. TrkB sensor activity adhered to the null hypothesis (normal distribution) while spine volume change and BDNF–SEP signal did not. Because TrkB sensor activity had a normal distribution, parametric statistics were used: paired and unpaired two-tailed t-test, ANOVA, and repeated-measures ANOVA with appropriate post-hoc analysis, as indicated in the figure legends and supplementary note. For t-tests, homoscedasticity between groups was evaluated using the F-test. If variance was unequal, Welch’s corrected t-test was performed. For ANOVA, homoscedasticity was evaluated with Bartlett’s test. For multiple comparisons of sensor activity, data were subjected to ANOVA or repeated-measures ANOVA followed by a post-hoc test to determine statistical significance. In cases where each condition was compared to all other conditions in the experiment, the Tukey–Kramer method was employed. In cases where each condition was compared to a single control, Dunnet’s test was used. Since spine volume change had a non-normal distribution, data were log-transformed to resolve skewness and then analysed with parametric statistics (the same tests described above), as indicated in the figure legends. For the BDNF–SEP signal, log-transformation of the data did not resolve the skewness. As such, non-parametric statistics were used—Wilcoxon rank-sum test and Kruskal–Wallis test with followed by a Dunn’s test. Data were only excluded if obvious signs of poor cellular health (dendritic blebbing, spine collapse, etc.) were apparent.