Quantitative evaluation of ImageJ thresholding algorithms for microbial cell counting

Nichele, Lorenzo; Persichetti, Valeria; Lucidi, Massimiliano; Cincotti, Gabriella

doi:10.1364/osac.393971

Cited by 52 publications

(26 citation statements)

References 13 publications

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“…For Methods 2 and 3, we found that ImageJ global “Default” thresholding was superior to other ImageJ thresholding methods that have been suggested for cell enumeration routines. ImageJ global Otsu and local Bernsen thresholding methods were recommended by Nichele et al (2020) for a cell analysis routine to resolve cell merging and resulting undercounting (as observed using our Method 2). We found that thresholding using global Otsu thresholding identified most cells, but aggregated closely‐spaced cells, resulting in undercounting.…”

Section: Assessment and Discussionmentioning

confidence: 99%

Applying fluorescence in situ hybridization to aquatic systems with cyanobacteria blooms: Autofluorescence suppression and high‐throughput image analysis

Cohen

Novkov-Bloom

Wesselborg

et al. 2021

Limnology & Ocean Methods

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Cyanobacterial Harmful Algal Blooms (CyanoHABs) are expanding geographically in both fresh and marine water bodies due to coastal eutrophication and global climate change and are restructuring the microbial ecology of these systems. Cyanobacterial autofluorescence can pose a significant impediment to accurately identifying prokaryotic taxonomic groups in environmental samples using fluorescence in situ hybridization (FISH). This can hinder our ability to accurately quantify, and therefore fully understand ecological changes. As abundances of FISH target cells and autofluorescent cells can often be of the same the order of magnitude, simply subtracting average autofluorescent cell concentrations-determined from enumerating unhybridized samplesyields apparent concentrations of target cells with unacceptably large analytical uncertainty. Here we present a CuSO 4 /EtOH chemical pretreatment protocol that significantly reduces undesirable autofluorescence in hybridized environmental samples. We apply a novel data filtration routine to FISH images that efficiently removes residual autofluorescent cells from final cell counts. We then subject images to an automated image analysis routine that accurately enumerates probe-positive cells. This method is inexpensive and easy to implement as part of a routine FISH workflow. By applying this method to cyanobacteria rich samples, we can better understand how microbial community changes are contributing to globally changing biogeochemical cycles.

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Section: Assessment and Discussionmentioning

confidence: 99%

Applying fluorescence in situ hybridization to aquatic systems with cyanobacteria blooms: Autofluorescence suppression and high‐throughput image analysis

Cohen

Novkov-Bloom

Wesselborg

et al. 2021

Limnology & Ocean Methods

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“…Ceca were removed from mice in the anaerobic chamber. The number of colony‐forming units on day 2 and day 7 was quantitated using ImageJ software (National Institutes of Health) (9).…”

Section: Methodsmentioning

confidence: 99%

Host Genetics But Not Commensal Microbiota Determines the Initial Development of Systemic Autoimmune Disease in BXD2 Mice

Hong

Alduraibi

Ponder

et al. 2022

Arthritis & Rheumatology

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Objective To determine the extent to which the gut microbiome influences systemic autoimmunity in a mouse model of lupus. Methods We generated germ‐free (GF) lupus‐prone BXD2 mice, which under normal conditions develop spontaneous germinal centers (GCs) and high titers of serum autoantibodies. GF status was confirmed by gut bacterial culture. The autoimmune phenotypes of 6‐ and 12‐month‐old gnotobiotic GF BXD2 mice and specific pathogen–free (SPF) BXD2 mice were compared. Serum levels of autoantibodies were measured by enzyme‐linked immunosorbent assay. Histologic sections of the mouse kidney and joints were evaluated. Flow cytometry was used to analyze GCs and age‐associated B cells. CD4+ T cells were analyzed for PD‐1+ICOS+ activated T cells, T follicular regulatory (Tfr) cells (Foxp3+CD25+ PD‐1+CXCR5+), and PD‐1+ICOS+ T cells expressing interleukin‐17A (IL‐17A) or interferon‐γ (IFNγ) after stimulation with phorbol myristate acetate (PMA)/ionomycin. Results In 6‐month‐old mice, GF status did not affect splenomegaly, GC B cells, age‐associated B cells, or serum autoantibody levels, except for IgG antihistone. GF BXD2 mice exhibited a significantly higher percentage of Tfr cells compared to their SPF counterparts (P < 0.05). At 12 months of age, however, GF BXD2 mice had significantly diminished IgG autoantibody levels and a lower percentage of GC B cells and age‐associated B cells (P < 0.05). Following stimulation with PMA/ionomycin, PD‐1+ICOS+ CD4+ T cells expressed significantly lower IL‐17A, but not IFNγ, levels in GF BXD2 mice compared to SPF BXD2 mice (P < 0.01). SPF BXD2 mice and GF BXD2 mice developed equivalent renal and joint disease with no significant differences in severity. Conclusion Our results suggest a model in which genetics plays a dominant role in determining the initial development of autoimmunity. In contrast, gut microbiomes may regulate the persistence of certain aspects of systemic autoimmunity.

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“…Water surface as the background of the image while the suspended particles as the foreground that will be counted from the image. Generally, this separation process involves the thresholding and segmentation process to get the clear suspended particles separated image [12]. This processing method formerly used for bacterial cell/colony counting both automatically or manually, such already conducted by several previous researchers.…”

Section: Data Acqusition Data Process and Data Analysismentioning

confidence: 99%

Turbidity Level Prediction Based on Suspended Particle Counting Through Image Processing Approach

Wikaningrum¹,

Alvasa²,

Panelin³

et al. 2021

JSE

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Monitoring of pollutant concentrations in surface water becomes a concern, considering the utilization of surface water as the raw water for drinking water treatment plants (WTP). The fluctuation of pollutant concentrations in surface water can affect the performance of WTP. This research was conducted to assess the potential for turbidity level prediction based on the calculation of the number and surface area of suspended particles through a digital image processing approach. Measurements of the amount and surface area were carried out in the form of laboratory-scale experiments using the open source software ImageJ 1.46r. The algorithm in ImageJ can convert pixels into a number “value” and surface area through a series of digital image processing steps, henceforth compared with the existing measurement method. The results showed that there was a strong correlation between the number of particles and the concentration of formazine suspension (r = 0.9821), but does not apply to the surface area. Referring to the results of laboratory experiments, it can be concluded that the approach to measure the number of suspended particles can be the basis for predicting the turbidity level in the turbidity range 100-800 NTU, but does not apply to the turbidity range 0.02-20 NTU.

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Quantitative evaluation of ImageJ thresholding algorithms for microbial cell counting

Cited by 52 publications

References 13 publications

Applying fluorescence in situ hybridization to aquatic systems with cyanobacteria blooms: Autofluorescence suppression and high‐throughput image analysis

Applying fluorescence in situ hybridization to aquatic systems with cyanobacteria blooms: Autofluorescence suppression and high‐throughput image analysis

Host Genetics But Not Commensal Microbiota Determines the Initial Development of Systemic Autoimmune Disease in BXD2 Mice

Turbidity Level Prediction Based on Suspended Particle Counting Through Image Processing Approach

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