Abstract

African trypanosomes cause sleeping sickness in humans and nagana in cattle. These unicellular parasites are transmitted by the bloodsucking tsetse fly. In the mammalian host's circulation, proliferating slender stage cells differentiate into cell cycle-arrested stumpy stage cells when they reach high population densities. This stage transition is thought to fulfil two main functions: first, it auto-regulates the parasite load in the host; second, the stumpy stage is regarded as the only stage capable of successful vector transmission. Here, we show that proliferating slender stage trypanosomes express the mRNA and protein of a known stumpy stage marker, complete the complex life cycle in the fly as successfully as the stumpy stage, and require only a single parasite for productive infection. These findings suggest a reassessment of the traditional view of the trypanosome life cycle. They may also provide a solution to a long-lasting paradox, namely the successful transmission of parasites in chronic infections, despite low parasitemia.

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Article and author information

Author details

  1. Sarah Schuster

    Department of Cell and Developmental Biology, University of Würzburg, Würzburg, Germany
    Competing interests
    The authors declare that no competing interests exist.
  2. Jaime Lisack

    Department of Cell and Developmental Biology, University of Würzburg, Würzburg, Germany
    Competing interests
    The authors declare that no competing interests exist.
  3. Ines Subota

    Department of Cell and Developmental Biology, University of Würzburg, Würzburg, Germany
    Competing interests
    The authors declare that no competing interests exist.
  4. Henriette Zimmermann

    Department of Cell and Developmental Biology, University of Würzburg, Würzburg, Germany
    Competing interests
    The authors declare that no competing interests exist.
  5. Christian Reuter

    Department of Cell and Developmental Biology, University of Würzburg, Würzburg, Germany
    Competing interests
    The authors declare that no competing interests exist.
  6. Tobias Mueller

    University of Wuerzburg, Wuerzburg, Germany
    Competing interests
    The authors declare that no competing interests exist.
  7. Brooke Morriswood

    University of Wuerzburg, Wuerzburg, Germany
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-7031-3801
  8. Markus Engstler

    Department of Cell and Developmental Biology, University of Würzburg, Würzburg, Germany
    For correspondence
    markus.engstler@biozentrum.uni-wuerzburg.de
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-1436-5759

Funding

Deutsche Forschungsgemeinschaft (EN305)

  • Markus Engstler

Deutsche Forschungsgemeinschaft (SPP1726)

  • Markus Engstler

German-Israeli Foundation for Scientific Research and Development (ant I-473-416.13/2018)

  • Markus Engstler

Deutsche Forschungsgemeinschaft (GRK2157)

  • Markus Engstler

Deutsche Forschungsgemeinschaft (396187369)

  • Brooke Morriswood

Bundesministerium für Bildung und Forschung (NUM Organostrat)

  • Markus Engstler

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

Reviewing Editor

  1. Christine Clayton, DKFZ-ZMBH Alliance, Germany

Publication history

  1. Preprint posted: July 29, 2019 (view preprint)
  2. Received: December 22, 2020
  3. Accepted: August 5, 2021
  4. Accepted Manuscript published: August 6, 2021 (version 1)
  5. Version of Record published: September 17, 2021 (version 2)
  6. Version of Record updated: January 31, 2022 (version 3)

Copyright

© 2021, Schuster et al.

This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.

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  1. Sarah Schuster
  2. Jaime Lisack
  3. Ines Subota
  4. Henriette Zimmermann
  5. Christian Reuter
  6. Tobias Mueller
  7. Brooke Morriswood
  8. Markus Engstler
(2021)
Unexpected plasticity in the life cycle of Trypanosoma brucei
eLife 10:e66028.
https://doi.org/10.7554/eLife.66028

Further reading

    1. Microbiology and Infectious Disease
    Fabien Guegan, Luisa Figueiredo
    Insight

    The parasite that causes African sleeping sickness can be transmitted from mammals to tsetse flies in two stages of its lifecycle, rather than one as was previously thought.

    1. Computational and Systems Biology
    2. Microbiology and Infectious Disease
    Flora Mikaeloff, Marco Gelpi ... Ujjwal Neogi
    Research Article Updated

    Multiomics technologies improve the biological understanding of health status in people living with HIV on antiretroviral therapy (PWH). Still, a systematic and in-depth characterization of metabolic risk profile during successful long-term treatment is lacking. Here, we used multi-omics (plasma lipidomic, metabolomic, and fecal 16 S microbiome) data-driven stratification and characterization to identify the metabolic at-risk profile within PWH. Through network analysis and similarity network fusion (SNF), we identified three groups of PWH (SNF-1–3): healthy (HC)-like (SNF-1), mild at-risk (SNF-3), and severe at-risk (SNF-2). The PWH in the SNF-2 (45%) had a severe at-risk metabolic profile with increased visceral adipose tissue, BMI, higher incidence of metabolic syndrome (MetS), and increased di- and triglycerides despite having higher CD4+ T-cell counts than the other two clusters. However, the HC-like and the severe at-risk group had a similar metabolic profile differing from HIV-negative controls (HNC), with dysregulation of amino acid metabolism. At the microbiome profile, the HC-like group had a lower α-diversity, a lower proportion of men having sex with men (MSM) and was enriched in Bacteroides. In contrast, in at-risk groups, there was an increase in Prevotella, with a high proportion of MSM, which could potentially lead to higher systemic inflammation and increased cardiometabolic risk profile. The multi-omics integrative analysis also revealed a complex microbial interplay of the microbiome-associated metabolites in PWH. Those severely at-risk clusters may benefit from personalized medicine and lifestyle intervention to improve their dysregulated metabolic traits, aiming to achieve healthier aging.