Measuring the Shape and Size of Activated Sludge Particles Immobilized in Agar with an Open Source Software Pipeline

Summary

The size and shape of particles in activated sludge are important parameters that are measured using varying methods. Inaccuracies arise from non-representative sampling, suboptimal images, and subjective analysis parameters. To minimize these errors and ease measurement, we present a protocol specifying every step, including an open source software pipeline.

Abstract

Experimental bioreactors, such as those treating wastewater, contain particles whose size and shape are important parameters. For example, the size and shape of activated sludge flocs can indicate the conditions at the microscale, and also directly affect how well the sludge settles in a clarifier.

Particle size and shape are both misleadingly 'simple' measurements. Many subtle issues, often unaddressed in informal protocols, can arise when sampling, imaging, and analyzing particles. Sampling methods may be biased or not provide enough statistical power. The samples themselves may be poorly preserved or undergo alteration during immobilization. Images may not be of sufficient quality; overlapping particles, depth of field, magnification level, and various noise can all produce poor results. Poorly specified analysis can introduce bias, such as that produced by manual image thresholding and segmentation.

Affordability and throughput are desirable alongside reproducibility. An affordable, high throughput method can enable more frequent particle measurement, producing many images containing thousands of particles. A method that uses inexpensive reagents, a common dissecting microscope, and freely-available open source analysis software allows repeatable, accessible, reproducible, and partially-automated experimental results. Further, the product of such a method can be well-formatted, well-defined, and easily understood by data analysis software, easing both within-lab analyses and data sharing between labs.

We present a protocol that details the steps needed to produce such a product, including: sampling, sample preparation and immobilization in agar, digital image acquisition, digital image analysis, and examples of experiment-specific figure generation from the analysis results. We have also included an open-source data analysis pipeline to support this protocol.

Introduction

The purpose of this method is to provide a well-defined, repeatable, and partially-automated method for determining size and shape distributions of particles in bioreactors, particularly those containing activated sludge flocs and aerobic granules^1,2. The rationale behind this method were to enhance the affordability, simplicity, throughput, and repeatability of our existing in-house protocols^3,4, ease particle measurement for others, and facilitate sharing and comparison of data.

There are two broad categories of particle m....

Protocol

1. Collect samples for particle analysis

1. Determine the sample volume for specific reactors that will produce sufficient particles for statistical analysis¹⁰ (>500) while avoiding particle overlap.
   1. Assume that a range of 0.5 to 2 mL per sample of mixed liquor is sufficient for activated sludge samples with a mixed liquor suspended solids (MLSS) between 250 and 5,000 mg/L.
   2. Otherwise, prepare three test agar plates using 0.5, 2, and 5 mL of sample (steps 1.2 through 2.7).
   3. Visually estimate which (if any) sample volumes best meet the criteria listed in step 1.1.
   4. If particles still overlap....

Results

Files Generated
The process illustrated in Figure 1 will produce two files per image analyzed. The first file is a comma separated value (CSV) text file where each row corresponds to an individual particle and the columns describe various particle metrics such as area, circularity, and solidity and defined in the ImageJ manual¹⁷. Example CSV files are included as supplemental information and in the examples/data di.......

Discussion

Although the image analysis system is fairly robust and QC steps are taken to ensure poor images are removed, proper attention to specific issues in sampling, plate preparation, and image acquisition can improve both the accuracy of the data and the proportion of images passing QC.

Sampling concentration
Assuming a representative sample has been taken, the most important step is to ensure that sufficient particles are present for representative⁹ and.......

Materials

List of materials used in this article

Name	Company	Catalog Number	Comments
10% Bleach solution	Chlorox	31009	For workspace disinfection.
15 mL centrifuge tube with cap	Corning	430790	Per sample.
50 mL Erlenmeyer flask	Corning	4980-50	Other vessels are suitable so long as they can contain > 40 mL of sample and allow mixing
500 mL Kimax Bottle	Kimble-Chase	14395-50	Or otherwise sufficient for agar handling
Agar	BD	214010	Solid, to prepare 7.5% gel. 7 mL per sample.
Data analysis software	N/A	N/A	R or Python are suggested
Deionized water	N/A	N/A	Sufficient to prepare stain and agar. If unavailable, tap should be fine.
Desktop computer	N/A	N/A	Image analysis is not CPU intensive, any 'ordinary' desktop computer circa 2017 should be sufficient.
External hard drive	Seagate	STEB5000100	Not fully required, but extremely useful given the number an size of images. 2 or more TB of storage suggested.
FIJI	NIH	version 1.51d	Version is ImageJ core. Plugins are updated as of writing. Available at: https://imagej.net/Fiji/Downloads
GIT	Open Source	version 2.19.1 or later	Available at: https://git-scm.com/
Image capture software	ToupView	version 3.7.5177	Any compatible with camera, may come with camera. Should allow saving TIFF images with spatial calibration data.
Mechanical (X/Y) Stage	OMAX	A512	Not fully required, but greatly aids image acquisition.
Methylene blue	Fisher	M291-100	Solid, to prepare 1% w/v solution. 5 uL solution per sample.
Microscope camera	OMAX	A35140U	Any digitial camera compatible with microscope. Resolution providing at least 5 um per pixel at 10x magnification and a dynamic range of at least 8 bits per pixel per color channel is suggested.
Optical Stage Micrometer	OMAX	A36CALM1	Or otherwise sufficient for spatial calibration.
Petri dish, 100 mm	Fisher	FB0875712	1 per sample.
PPE	N/A	N/A	Standard lab coat, gloves, and eyewear.
Sparmoria macro	NCSU	version 0.2.1	Available at github repository : https://github.com/joeweaver/SParMorIA-Sludge-Particle-Morphological-Image-Analysis
Stereo/dissecting microscope	Nikon	SMZ-2T	Should provide 10 to 20x magnficiation and allow digital photos either with a buit-in camera or profide a mounting point for a CCD.