Reproduction dynamics of planktonic microbial eukaryotes in the open ocean

Weinkauf, Manuel F. G.; Siccha, Michael; Weiner, Agnes

doi:10.1098/rsif.2021.0860

Cited by 9 publications

(8 citation statements)

References 84 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…[71] Little is known about how exactly these strategies evolved, though they may increase the likelihood of gametes meeting in the water column. [72] Heterokaryosis A few species have evolved heterokaryosis (i.e., nuclear dualism;…”

Section: Parfrey Et Al (2012)mentioning

confidence: 99%

See 1 more Smart Citation

Foraminifera as a model of the extensive variability in genome dynamics among eukaryotes

et al. 2022

Self Cite

View full text Add to dashboard Cite

Knowledge of eukaryotic life cycles and associated genome dynamics stems largely from research on animals, plants, and a small number of "model" (i.e., easily cultivable) lineages. This skewed sampling results in an underappreciation of the variability among the many microeukaryotic lineages, which represent the bulk of eukaryotic biodiversity. The range of complex nuclear transformations that exists within lineages of microbial eukaryotes challenges the textbook understanding of genome and nuclear cycles. Here, we look in-depth at Foraminifera, an ancient (∼600 million-year-old) lineage widely studied as proxies in paleoceanography and environmental biomonitoring.We demonstrate that Foraminifera challenge the "rules" of life cycles developed largely from studies of plants and animals. To this end, we synthesize data on foraminiferal life cycles, focusing on extensive endoreplication within individuals (i.e., single cells), the unusual nuclear process called Zerfall, and the separation of germline and somatic function into distinct nuclei (i.e., heterokaryosis). These processes highlight complexities within lineages and expand our understanding of the dynamics of eukaryotic genomes.

show abstract

Section: Parfrey Et Al (2012)mentioning

confidence: 99%

“…[ 71 ] Little is known about how exactly these strategies evolved, though they may increase the likelihood of gametes meeting in the water column. [ 72 ]…”

Section: Genome Dynamics Within Life Cycles Of Foraminiferamentioning

confidence: 99%

Foraminifera as a model of the extensive variability in genome dynamics among eukaryotes

et al. 2022

Self Cite

View full text Add to dashboard Cite

show abstract

“…It is important for the organism to coordinate the time and place of gamete release with other members of the species to maximize reproductive success (e.g. Weinkauf et al, 2022). As part of this process, many (not all) species probably sink to a particular depth or density layer at a particular phase of the lunar cycle (Bijma et al, 1990;Schiebel and Hemleben, 2017).…”

Section: Figure 2 Basic Pattern Of Test Layering Modified Frommentioning

confidence: 99%

Spine-like structures in Paleogene muricate planktonic foraminifera

Pearson

John

Wade

et al. 2022

J. Micropalaeontol.

View full text Add to dashboard Cite

Abstract. Muricate planktonic foraminifera comprise an extinct clade that was diverse and abundant in the Paleogene oceans and are widely used in palaeoclimate research as geochemical proxy carriers for the upper oceans. Their characteristic wall texture has surface projections called “muricae” formed by upward deflection and mounding of successive layers of the test wall. The group is generally considered to have lacked “true spines”: that is, acicular calcite crystals embedded in and projecting from the test surface such as occur in many modern and some Paleogene groups. Here we present evidence from polished sections, surface wall scanning electron microscope images and test dissections, showing that radially orientated crystalline spine-like structures occur in the centre of muricae in various species of Acarinina and Morozovella and projected from the test wall in life. Their morphology and placement in the wall suggest that they evolved independently of true spines. Nevertheless, they may have served a similar range of functions as spines in modern species, including aiding buoyancy and predation and especially harbouring algal photosymbionts, the function for which we suggest they probably first evolved. Our observations strengthen the analogy between Paleogene mixed-layer-dwelling planktonic foraminifera and their modern spinose counterparts.

show abstract

“…A quantitative study of the microbial life cycle is crucial to understand ecological and evolutionary processes that can be used to control parasites and pathogens [1][2][3][4] . However, defining the structure of a microbial life cycle traditionally relies on partial microscopy observations or genetic and theoretical evidence 5 . Although biochemical methods, such as immunostainings or single cell DNA/RNA sequencing, can provide molecular descriptions of developmental transitions 3,[6][7][8][9] , only live-cell imaging can directly visualize entire microbial life cycles in single cells in vivo, as demonstrated for bacterial 10,11 and eukaryotic 12 life cycles.…”

Section: Introductionmentioning

confidence: 99%

Deep learning-driven imaging of cell division and cell growth across an entire eukaryotic life cycle

Ramakanth,

Kennedy,

Yalcinkaya

et al. 2024

Preprint

View full text Add to dashboard Cite

The life cycle of biomedical and agriculturally relevant eukaryotic microorganisms involves complex transitions between proliferative and non-proliferative states such as dormancy, mating, meiosis, and cell division. New drugs, pesticides, and vaccines can be created by targeting specific life cycle stages of parasites and pathogens. However, defining the structure of a microbial life cycle often relies on partial observations that are theoretically assembled in an ideal life cycle path. To create a more quantitative approach to studying complete eukaryotic life cycles, we generated a deep learning-driven imaging framework to track microorganisms across sexually reproducing generations. Our approach combines microfluidic culturing, life cycle stage-specific segmentation of microscopy images using convolutional neural networks, and a novel cell tracking algorithm, FIEST, based on enhancing the overlap of single cell masks in consecutive images through deep learning video frame interpolation. As proof of principle, we used this approach to quantitatively image and compare cell growth and cell cycle regulation across the sexual life cycle of Saccharomyces cerevisiae. We developed a fluorescent reporter system based on a fluorescently labeled Whi5 protein, the yeast analog of mammalian Rb, and a new High-Cdk1 activity sensor, LiCHI, designed to report during DNA replication, mitosis, meiotic homologous recombination, meiosis I, and meiosis II. We found that cell growth preceded the exit from non-proliferative states such as mitotic G1, pre-meiotic G1, and the G0 spore state during germination. A decrease in the total cell concentration of Whi5 characterized the exit from non-proliferative states, which is consistent with a Whi5 dilution model. The nuclear accumulation of Whi5 was developmentally regulated, being at its highest during meiotic exit and spore formation. The temporal coordination of cell division and growth was not significantly different across three sexually reproducing generations. Our framework could be used to quantitatively characterize other single-cell eukaryotic life cycles that remain incompletely described. An off-the-shelf user interface Yeastvision provides free access to our image processing and single-cell tracking algorithms.

show abstract

Reproduction dynamics of planktonic microbial eukaryotes in the open ocean

Cited by 9 publications

References 84 publications

Foraminifera as a model of the extensive variability in genome dynamics among eukaryotes

Foraminifera as a model of the extensive variability in genome dynamics among eukaryotes

Spine-like structures in Paleogene muricate planktonic foraminifera

Deep learning-driven imaging of cell division and cell growth across an entire eukaryotic life cycle

Contact Info

Product

Resources

About