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Analysis of the Leishmania mexicana promastigote cell cycle using imaging flow cytometry provides new insights into cell cycle flexibility and events of short duration
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Promastigote Leishmania mexicana have a complex cell division cycle characterised by the ordered replication of several single-copy organelles, a prolonged S phase and rapid G2 and cytokinesis phases, accompanied by cell cycle stage-associated morphological changes. Here we exploit these morphological changes to develop a high-throughput and semi-automated imaging flow cytometry (IFC) pipeline to analyse the cell cycle in live L. mexicana. Firstly, we demonstrate that, unlike several other DNA stains, Vybrant™ DyeCycle™ Orange (DCO) is non-toxic and enables quantitative DNA imaging in live promastigotes. Secondly, by tagging the orphan spindle kinesin, KINF, with mNeonGreen, we describe KINF’s cell cycle-dependent expression and localisation. Then, by combining manual gating of DCO DNA intensity profiles with automated masking and morphological measurements of parasite images, visual determination of the number of flagella per cell, and automated masking and analysis of mNG:KINF fluorescence, we provide a newly detailed description of L. mexicana promastigote cell cycle events that, for the first time, includes the durations of individual G2, mitosis and post-mitosis phases, and identifies G1 cells within the first 12 minutes of the new cell cycle. Our custom-developed masking and gating scheme allowed us to identify elusive G2 cells and to demonstrate that the CDK-inhibitor, flavopiridol, arrests cells in G2 phase, rather than mitosis, providing proof-of-principle of the utility of IFC for drug mechanism-of-action studies. Further, the high-throughput nature of IFC allowed the close examination of promastigote cytokinesis, revealing considerable flexibility in both the timing of cytokinesis initiation and the direction of furrowing, in contrast to the related kinetoplastid parasite, Trypanosoma brucei and many other cell types. Our new pipeline offers many advantages over traditional methods of cell cycle analysis such as fluorescence microscopy and flow cytometry and paves the way for novel high-throughput analysis of Leishmania cell division.
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![Fig 2 DCO stains DNA quantitatively in live L. mexicana promastigotes. (A) Brightfield and fluorescence images of L. mexicana promastigote C9T7 cells at different cell cycle stages stained with DCO. N: nucleus; K: kinetoplast; F: flagellum. Scale bars: 7 μm. Note that, consistent with previous fluorescence studies, the nucleus appears to divide before the kinetoplast. (B) The fluorescence intensity profile of C9T7 cells (n = 13920) stained with DCO and analysed with IFC. Peaks are indicated with arrowheads for non-replicated DNA (2C; corresponding to cells in G1 phase), replicated DNA (4C; cells in G2/M phase or cytokinesis) and cells with intermediate DNA content (Int.; cells undergoing S phase). (C) Cell cycle modelling of the DCO DNA intensity profile (panel B) using the FCS Express™ Multicycle engine (Rabinovitch & Bagwell debris subtraction [43, 44] and Dean/Jett/Fox cell cycle modelling [45]. The cell cycle stage of each curve is indicated. (D) Graph comparing the proportions of cells with different DNA contents, as modelled following staining with PI (S2A and S2B Fig) and DCO (panels B and C). Error bars represent the standard deviations of the means of three replicates. See S1B Table for raw data.](/paper-figures/3f92be6551d4426da09f52eb51958c6f/analysis-of-the-leishmania-mexicana-promastigote-cell-cycle-using-imaging-flow-figure-2.jpg)





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“This method can be used to evaluate the proliferation rates of microalgae depending on the cultivation conditions, e.g., changes in nutrient availability or light intensity [235].”
From Multi-Sensing Monitoring of the Microalgae Biomass Cultivation Systems for Biofuels and Added Value Products Synthesis—Challenges and Opportunities (2025) · cites this paper as [235]
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Self-citationGupta, A. R., Beg, M. A., Badhwar, S., Srivastava, S., Srivastava, R., Puri, N., Saxena, A. K., Abdin, M. Z., & Selvapandiyan, A. (2025) · Microbial Pathogenesis · doi:10.1016/j.micpath.2025.108192 · Cited by 1
Metadata
- Authors
- Howell, J., Omwenga, S., Jimenez, M., & Hammarton, T. C.
- Affiliations
- University of Glasgow (GB)
- Corresponding author
- Hammarton, Tansy C.
- Venue
- PLOS ONE
- Publisher
- Public Library of Science (PLoS)
- Published
- 2024-10-03
- Volume
- 19
- Issue
- 10
- Pages
- e0311367
- ISSN
- 1932-6203 (ISSN-L)
- PMC
- PMC11449296
- OpenAlex
- W4403092611
- Cited by
- 10
- References
- 85
- Citations by year
- 2026: 5 · 2025: 5
- FWCI
- 4.14
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- PLoS ONE (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- ENLIGHTEN (Jurnal Bimbingan dan Konseling Islam) (acceptedVersion, cc-by-sa)
- Strathprints: The University of Strathclyde institutional repository (University of Strathclyde) (acceptedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Funders
- Engineering and Physical Sciences Research Council (EP/R513222/1)
- Royal Academy of Engineering (RF/201718/1741)
- The Cunningham Trust (PhD-CT-19-14)
- Topics
- Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Research on Leishmaniasis Studies
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Biophysics › Cell Image Analysis Techniques
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Digital Imaging for Blood Diseases
- Keywords
- Leishmania mexicana, promastigotes, cell cycle, imaging flow cytometry, mNeonGreen tagging, G2 phase, cytokinesis, mitosis, flavopiridol, cyclin-dependent kinase inhibitors, cell morphology, mechanism of action
- MeSH terms
- Cell Cycle, Flow Cytometry, Leishmania mexicana, Mitosis, Protozoan Proteins, Kinesins
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Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
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