Chameleons

All tissue was imaged under a protocol approved by the Massachusetts Institute of Technology Committee on the Use of Humans as Experimental Subjects (COUHES) and the Beth Israel Deaconess Medical Center (BIDMC) Committee on Clinical Investigations (CCI). Surgical specimens which were discarded and not required for diagnosis were de-identified prior to enrollment by non-study personnel, transported to MIT in chilled RPMI solution, and dissected to expose relevant pathology. Specimens were then labeled with DAPI (a widely used fluorescent hematoxylin analog) and eosin and then fixed in formalin to enable repeated imaging over an extended period. DAPI was chosen because it is widely used in microscopy, however many other nuclear contrast agents could be used along with the appropriate filters. Total sample preparation excluding fixation was less than 3 minutes, substantially less than the ~1 day required for conventional histopathology processing. Following fixation, specimens were selected and imaged with a commercial multiphoton microscope (Thorlabs, Inc.) with a XLUMPFL20XW 1.0 NA 20x objective (Olympus) and a titanium sapphire laser (Chameleon, Coherent, Inc.) operating at 780 nm. The microscope generated images of 1024 by 1024 pixels at 16 frames per second. The axial sectioning resolution in tissue was approximately 1 micron. Detection was performed using H7422-40P photomultiplier tubes (Hamamatsu, Inc.) with a 510 nm dichroic beam splitter and a 460/50 nm emission filter (DAPI channel) and a 590/100 nm filter (eosin). To reduce the confounding effects of detector noise on image quality between linear and nonlinear rendering methods, each frame was averaged 16 times to reduce noise. To overcome the limited field of view of conventional multiphoton microscopy, a high speed translation stage (MLS203, Thorlabs, Inc.) was used to mosaic multiple, 500 micron size fields with 50% overlap using custom acquisition software written in C++.

The XOS contents were evaluated by high-performance anion-exchange chromatography (HPAEC). Samples were dissolved in ultrapure water, oscillated by ultrasound, and then centrifuged at 6000 × g for 15 min, and 1 mL of the supernatant was collected. Standards of xylobiose (X2), xylotriose (X3), xylotetraose (X4), xylopentaose (X5), and xylohexaose (X6) were purchased from Megazyme (Wicklow, Ireland, UK). The following steps were conducted according to the method [18 (link)]. Analysis of the standards and filtered samples was carried out on a Dionex ICS3000 system equipped with a pump and an amperometric detector. The chameleon chromatography management system (Dionex, Sunnyvale, CA, USA) was used for sugar identification and quantification. An analytical CarboPac PA10 pellicular anion-exchange resin column (250 mm × 4 mm) was used for sugar separation. The monoses were eluted with 250 mmol/L NaOH at a flow rate of 1.0 mL/min.

Live imaging of microglial processes was performed on 250 µm coronal brain slices from Nf1 ± or Nf1flox/wt mice and their WT littermates using a custom-built two-photon laser-scanning microscope (Till Photonics, Gräfelfing, Germany). EGFP or eYFP was excited by a Chameleon Ultra II laser (Coherent, Dieburg, Germany) at a wavelength of 940 nm. A 40X water-immersion objective (NA 0.8, Olympus, Hamburg, Germany) was used, with scanned 60 µm thick z-stacks and a step size of 3 µm covering a field of 320 × 320 µm. Laser lesions were set to 40 µm under the slice surface in the cortex by focusing the laser beam, set to a wavelength of 810 nm and to maximum power in the selected imaging volume, and scanned until autofluorescence of the injured tissue was visible. This procedure resulted in lesions of ~ 20 µm in diameter in the middle of the observed region. For the recording of microglia surveillance, no laser lesion was performed. IGOR Pro 6.37 (Lake Oswego, USA) was used for data analysis as in Davalos et al. [13 (link)] and Madry et al. [42 (link)]. The sequences of 3D image stacks were converted into sequences of 2D images by a maximum intensity projection algorithm. Grayscale images were first converted into binary form using a threshold. For quantification of laser lesion-induced movements, microglial response to focal lesion was defined as EGFP + pixel count in a proximal circular region 45 µm around the lesion site over time (Rx(t)). Distal fluorescence of the first time point was determined within a diameter of 45 µm to 90 µm around the lesion site for normalization (Ry(0)). Microglial responses were represented as R(t) = (Rx(t)-Rx(0))/Ry(0). For the quantification of baseline surveillance, cells of interest were individually selected by manually drawing a region of interest (ROI) around an area including all their process extensions throughout the 20 min movie and erasing data around that ROI. Starting with the second frame, we subtracted from each binarized frame the preceding frame and counted the number of pixels < 0 (retracting = PR) and > 0 (extending = PE). The surveillance index for each frame is then given by the sum of PR ad PE. The surveillance index of a given cell was then calculated by averaging the indices of the first 20 images in the movie. For ramification index (RI), we used the equation RI = (peri/area)/(2*sqrt(pi/area)), where peri and area are respectively the perimeter and area of a given cell in pixels. For the quantification of these two parameters, the ImageAnalyzeParticles operation in IGOR Pro 6.37 was applied on binarized images in which all analyzed microglia were manually examined and, if necessary, somata and processes connected.

The study was based on two computerized datasets: a Nephrology consultation database, which consists of records of hospitalized patients, from all the hospital wards requesting Nephrology consultation. The second is Soroka’s Chameleon electronic medical records database, which comprises records of all patients treated in Soroka hospital. Based on previous power calculations, two-thirds of the patients were randomly selected using an arbitrary digit of their ID number, as reported before [13 (link)]. The study was investigator-initiated and was approved by the Soroka University Medical Center institutional review board (IRB). All diagnoses were classified by the international classification of disease (ICD-9).