How to detect Foci

In this video, we will apply the same technique we used for detecting bacteria, to instead detect fluorescent particles using the local maxima detection algorithm and then learn how we can associate these particles to the bacterial cells or relative to each other.

Starting with the same phase contrast image stack that we analyzed in the previous video, we will load the associated fluorescent image stack that corresponds to it.

If you already have both the phase contrast and fluorescence image stacks open, you can use the “channels” input mode, assign each stack to a channel: and click the open images button and they will be combined into a hyperstack and the image input mode will automatically change to “image.”

Of course if you already have a hyperstack you could have selected the ‘image mode’ right at the beginning.

We will now load our saved optimized settings for bacteria detection that we created earlier “settings.xml” by dragging it onto the MicrobeJ status bar and, click the test button to detect the bacteria.  

Use the channel slider to move to the fluorescent images in the hyperstack

On this fluorescent image, you can see the cell contours of the detected bacteria

Now let’s explore the features of the Maxima tab, where you will learn how to optimize the detection of fluorescent maxima, evaluate size and intensity of maxima, associate them with positional information inside the bacterial cells and once we have our raw data, explore some of the new features and functions available in the results interface for charts and statistics.

To activate the features in the Maxima tab, you must first check the box next to Maxima.

Below this, select the channel that contains the images you will be analyzing for fluorescent particles, in our example this is channel 2.

Now select the type of background.

The images in channel 2 have a dark background compared to the fluorescent particles that we want to detect, so we will use Dark mode.

Below this, in the “mode of detection” drop down menu, there are several choices available, for details about all the maxima detection modes, please refer to the documentation on our website.

Let’s select Point as the detection mode and press the test button.

As mentioned before, when you click on the test button, the maxima will be detected only on the active slice of your image stack using the current settings.

We can adjust the noise “tolerance” setting by positioning the cursor over the slider and moving the roller wheel on your mouse or by using the left and right arrow keys on your keyboard. The maxima detected updates as you move the slider.

You can see that decreasing the slider includes a lot of surrounding background noise while increasing the slider reduces the number of maxima detected.

The point mode is the fastest but also the most basic way to detect maxima in our image. In fact, because the maxima detected are single XY coordinates, there is a very limited number of attributes we can actually measure and use to filter out unwanted maxima.

This is where using the Foci mode of detection in MicrobeJ shines.  

So let’s select Foci as the detection mode and press the test button.

When you select the Foci mode, MicrobeJ will not only detect the local maxima in our image, but also the contiguous area around them.

To do that, we need to define a Z-score which basically defines how the pixels must be different from the background to be included in the surrounding area.

So watch as I move the slider and change the Z-score, how surrounding areas change on the image.

Try to find a Z-score value that optimizes the area around your maxima while keeping the distinction between what you consider as your foci and the background.

Sometime, we will notice that not every maxima detected will be a foci.

If you zoom in, you can see that similar to the bacteria, you have access to the specific attributes of the maxima. Such as their area, width, or length which can be used to filter out unwanted maxima.

So if you want to exclude this maxima for instance from the final analysis, just adjust the minimal area to something greater than 0.02, and click on the test button again.

Note that by optimizing the tolerance and the Z-score, you can easily refine the rejection process by using those basic attributes until your find the right combination of values.

Now let’s select the options that we want to measure  

There are many options that may be applied to detected Maxima, for a description of all of the options, please see the documentation on our website.

For example if you are interested by the fluorescence Intensity of our detected foci select ‘intensity’ and all those attributes will be listed in the raw data table.

If you are interested by the sub-pixel localization of the maxima, select the Gaussian Fit option.

More interestingly, if you want to associate the maxima with the bacteria, select ‘Association’. If you know that the maxima should be within a defined boundary of your cell, check the inside mode. Sometimes the maxima might be slightly outside the detected boundary of the bacterial cell, so I would recommend to define a tolerance. Something like 0.2 microns and then press the MAIN test button.

Notice that when maxima are associated with bacteria, that the boundary around the maxima changes to hexagon and stick.

Now let’s run our experiment and look at our raw data!

On the Results interface, in the Experiment panel, we see a hierarchical arrangement between the bacteria and the maxima we associated with them. Because the bacteria are the primary particle that the maxima are associated to, we refer to bacteria as the parent particle and maxima as the child particle.

If we select Bacteria from the experiment panel, we can see all the bacteria detected and which ones have maxima and the number of maxima.

If we select Maxima from the Experiment panel, we can see in the data table, a column for PARENT and below it the specific bacteria where the maxima were found. Right mouse clicking or control clicking on the column title, allows you to select the relative location or localization of the active maxima within the parent particle; For a detailed explanation of these options, please see the documentation on our website.

The data table and the image are connected as was true when we detected bacteria alone, because we associated the maxima with the bacteria, if you hide or remove a maxima in the data table, both will be hidden or removed in the image and from the final data analysis.

Notice that we now have access to subcellular localization tools such as

Heatmap and Bacteria Chart where we can plot the maxima on the shape of a bacterial cell either using XY or Histogram mode.

Finally, if you want to compare any maxima properties with any properties of their respective parent bacteria

For instance: Is there a correlation between the cell length and the fluorescence intensity of the associated maxima?

You can simply import that information into the maxima panel by creating a new column in the result interface. In the area next to the insert vertical column icon,  type the title of the new column, in this case length after the equal sign type the partent particle name, bacteria, then the attribute, here it is SHAPE.length then either hit the enter or + sign to generate a new column for this information

Then graph intensity of maxima vs length of bacteria

The Imported information can now be used as any other properties

So in this video, you should have learned how to load multi-channel image stacks, optimize the detection of fluorescent maxima & associate them to bacteria, get the raw data & import data between the associated particles and use the subcellular localization tools.

Thanks for your interest in the MicrobeJ project!

Stay tuned for more!

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