I happened upon this website, saying alpha fold is helping with protein structure, which it probably is, but it hasn’t helped with the structure of SP-D yet —  as the areas of low significance (orange and red) are completely out of line with any microscopic evidence (see AFM from Arroyo et al) which shows nice correlation with the blue areas (high probability of being correct) vs the rest of the model which has absolutely no correlation with the shape of the rest of an SP-D trimer.  Images as presented in this model (proposed models left hand part of the figure below) are the reason I continue to try to establish an accurate count of the number of peaks, their height, and width, using various imaging and signal processing programs to help define the shape along the more or less “straight” collagen-like and N term domains of an SP-D trimer.

Carbohydrate recognition domain and neck domains (BLUE) are spot on, collagen-like domain and N termini junction (orange and yellow)… really really no good.

Summary of 392 plots from different signal and image processing algorithms of one (YES JUST ONE so far) SP-D dodecamer image, maybe a long and repetitive approach, but ultimately it may say something about which signal and imaging functions and filters get the most valuable structure data from an image of a molecule.  The reason for using SP-D was the host of wonderful images available in the published literature (Arroyo et al) and because the current molecular model of SP-D is unfinished.  Numerous models have been made of the carbohydrate recognition domain, but little else has surfaced.

I saw a need to compare the benefits of image vs signal processing to determine such things as peak width, height, and peak number in the arms of SP-D dodecamers to find the most informative, and easiest way to determine what the rest of the molecular landscape of SP-D might look like.

The image below was selected deliberately. It has features that are common to AFM images of SP-D, it had definite bilateral organization  (in this case it is better called radial symmetry since the N termini are a central very bright peak and the arms extend to the CRD of each trimer. The labels on the image are guides to the values (N, mean, sd and var). 392 different plots were obtained from trimers in this image which were processed in a dozen different filters and algorithms with different programs and to many different degrees.  You have seen this image many times before in this blog – i call the molecule 41 aka 45….  no surprises.

Some data here which can be explained by the labels in the image above: arm 1 is nearly horizontal, while arm 2 moves to a more vertical position from left to right. N termini – center black dotted ring, arrows indicate the directions of the plots.  The whole N terminus is included at the beginning of each trimer plot. The trimers 1 and 2 are subdivided into 1a (left side of the micrograph) and 1b (right side), and 2a (again, the left) and 2b the more vertical arm on the right. bar marker=100nm. the diameter is shown by a blue dotted line and the criteria were that the circle had to graze three of the four CRD, in this case, left, right and top were used to calculate the approximate diameter of the dodecamer (the N here includes that many measurements using various processing and filtering of the image above.

A comparison to a single imaging program and plots of this molecule are just very similar to the data from the bigger dataset above,  see those values here.

More measures below on this dataset. Thesse are values  from a single image. It is clear that there are some filters and algorithms that are more informative than others.

Comparing peak height and peak width for a single hexamer of surfactant protein D has lead me to the conclusion that:

1. many methods (image and signal processing) can be used that produce very similar results
2. many methods (image and signal processing) can produce rediculous results
3. concensus may or not provide the best results

I have examined this particular AFM image of SP-D (which i call 41_aka_45 (an image of am SP-D dodecamer from a publication by Arryoy et al) — the name is given here so it is possible to relate this post with many previous posts on this image)for hours, literally, using more than half a dozen image processing programs and dozens of image processing filters, as well as signal processing using two excel templates for finding plot peaks (by Tom O’Haver) and peak finding functions which use Octave. The purpose is to find the best (and easiest) method(s) for determining peak number, peak width, peak heights of grayscale plots (made using ImageJ) of this type of image and similar images. I was really pleasantly surprised when Aaron Miller added a function in one of the excel templates that displayed the valley points in the excel plot. This provided a second plot which, when exported as a metafile, could be used to quickly define peak widths as vertical lines. While not using peak slope to calculate peak width in a more sophisticated way, it does allow for easy comparison of peak number, width and height obtained as signal processing, with those parameters obtained with image processing and plotting in ImageJ.
Below are two plots, top identifies peak valleys (peak width) and height (on an image that had been filtered with a 5px gaussian blur, but no signal processing), and the lower plot was defined using signal processing on the same image, in this case the PeakAndValleyTemplate for excel (by Tom O’haver) with a smoothing factor of 11 or 9 – i need to check.

crd= corelDRAW 19; gausblur 5px-gaussian blur 5px; PVDxlsx (PVDxlsx=PeakAndValleyTemplate  for excel); (compare colors and widths in the two plots: dark orange outer peaks=CRD, yellow= possible neck domain, white, pink and darker green represent as yet undefined domains likely in the collagen-like dolmain, the light green the named glycosylation site (glycosylation appears to cause a lumpiness (perhaps relating to glycosylation of 1 – 3 molecules in the trimer) a small peak (purple) just before the N termini junction(light peach color), with the latter often divided at the center with a valley).

Most conservative estimate for number of brightness (LUT) peaks along an arm of a dodecamer of SP-D is shown in this plot, with color coding from CRD (orange) inward to the Ntermini junction (peach). The recognized peak (glycosylation site(s) are light green. Other peaks are not generally know but consistently divide out into height and width (nm) as shown here, cascading downward in height but varying in width from center (N) to CRD). In most plots the CRD are composed of two, even more, peaks as the CRD fall into irregular places during processing. In this plot however, they show up as one. My impression gained by using less “blur” and more edge detection is that the consistent number of peaks is more like 15, with tiny peaks beside the Nterm central peak. This will, I hope, show up in analysis of all the different processing filters, and with more than a single molecule, as shown here (this is SP-D dodecamer 41 aka 45 (named by me, from publication of Arroyo et al), seen many times before on this blog).

Each peak width and height has been measured, hopefully a summary of all different image and signal processing will confirm this pattern.

My hope is also that somehthing specific about the degree of glycosylation (light green peaks) can be determined, as seen here with different peak heights for that area. It is also clear that the peak area that has been shown to be glycosylated is rarely a single rounded peak, but more often multiple peaks within a general peak. This is vaguely demonstrated on the light green peak shown on the right hand side of the plot. Differences in the length of each trimer of this hexamer are most likely due to how the molecule was spread during preparation. This can be partly overcome by adjusting the trimer plots to the same widths.

Just looking at some grayscale peaks in a plot of a surfactant protein D dodecamer and noticed that one hexamer, plotted in ImageJ, of this molecule (AFM, 41 aka 45 – sorry for that id i have given this dodecamer) with a CorelDRAWx5 photopaint program and a 50 percent-10px minimum filter shows a drag on the peaks which I dont think i have noticed before. These occur on one trimer (left side, minimally on the first peak with the red arrow, then on the next four peaks more prominently) of the hexamer plotted (see actual dodecamer – bottom image) of this dodecamer, but not on the second trimer (right side of the plot).

It looks like a “nice” demonstration of a drag artifact.  A displacement from left to right seen on the LEFT half of this plot (horizontal trimer), but not the right side of the plot (vertical trimer).

Original image used to make this plot is below. It is interesting that the drag did not appear on the trimer which is more vertically oriented, i.e. the right hand trimer (closer inspection of the image also shows a smearing of that trimer which till now I had not paid any attention too, but it certainly translated into a change in the plot). bar=100nm