scholarly journals Modeling the C. elegans Germline Stem Cell Genetic Network using Automated Reasoning

2021 ◽  
Author(s):  
Ani Amar ◽  
E. Jane Albert Hubbard ◽  
Hillel Kugler
Keyword(s):  
Decision Making ◽  
Stem Cell ◽  
Germ Line ◽  
Genetic Network ◽  
Genetic Networks ◽  
Genetic Interactions ◽  
Formal Reasoning ◽  
Regulatory Interactions ◽  
C Elegans ◽  
Cellular Decision Making

Computational methods and tools are a powerful complementary approach to experimental work for studying regulatory interactions in living cells and systems. We demonstrate the use of formal reasoning methods as applied to the Caenorhabditis elegans germ line, which is an accessible model system for stem cell research. The dynamics of the underlying genetic networks and their potential regulatory interactions are key for understanding mechanisms that control cellular decision making between stem cells and differentiation.We model the 'stem cell fate' versus entry into the 'meiotic development' pathway decision circuit in the young adult germ line based on an extensive study of published experimental data and known/hypothesized genetic interactions. We apply a formal reasoning framework to derive predictive networks for control of differentiation. Using this approach we simultaneously specify many possible scenarios and experiments together with potential genetic interactions, and synthesize genetic networks consistent with all encoded experimental observations. In silico analysis of knock-down and overexpression experiments within our model recapitulate published phenotypes of mutant animals and can be applied to make predictions on cellular decision-making. This work lays a foundation for developing realistic whole tissue models of the C. elegans germ line where each cell in the model will execute a synthesized genetic network.

scholarly journals Progression from a stem cell–like state to early differentiation in the C. elegans germ line

2010 ◽  
Vol 107 (5) ◽  
pp. 2048-2053 ◽  
Author(s):  
Olivier Cinquin ◽  
Sarah L. Crittenden ◽  
Dyan E. Morgan ◽  
Judith Kimble
Keyword(s):  
Stem Cell ◽  
Germ Cells ◽  
Cell Biology ◽  
Germ Line ◽  
Stem Cell Biology ◽  
Self Renewal ◽  
Early Differentiation ◽  
C Elegans ◽  
Stem Cell Maintenance ◽  
System A

Controls of stem cell maintenance and early differentiation are known in several systems. However, the progression from stem cell self-renewal to overt signs of early differentiation is a poorly understood but important problem in stem cell biology. The Caenorhabditis elegans germ line provides a genetically defined model for studying that progression. In this system, a single-celled mesenchymal niche, the distal tip cell (DTC), employs GLP-1/Notch signaling and an RNA regulatory network to balance self-renewal and early differentiation within the “mitotic region,” which continuously self-renews while generating new gametes. Here, we investigate germ cells in the mitotic region for their capacity to differentiate and their state of maturation. Two distinct pools emerge. The “distal pool” is maintained by the DTC in an essentially uniform and immature or “stem cell–like” state; the “proximal pool,” by contrast, contains cells that are maturing toward early differentiation and are likely transit-amplifying cells. A rough estimate of pool sizes is 30–70 germ cells in the distal immature pool and ≈150 in the proximal transit-amplifying pool. We present a simple model for how the network underlying the switch between self-renewal and early differentiation may be acting in these two pools. According to our model, the self-renewal mode of the network maintains the distal pool in an immature state, whereas the transition between self-renewal and early differentiation modes of the network underlies the graded maturation of germ cells in the proximal pool. We discuss implications of this model for controls of stem cells more broadly.

Early determination in the C. elegans embryo: a gene, cib-1, required to specify a set of stem-cell-like blastomeres

Development ◽  
1990 ◽  
Vol 108 (1) ◽  
pp. 107-119 ◽  
Author(s):  
R. Schnabel ◽  
H. Schnabel
Keyword(s):  
Cell Cycle ◽  
Decision Making ◽  
Stem Cell ◽  
Early Embryo ◽  
Cell Cycles ◽  
C Elegans ◽  
Lethal Mutations ◽  
A Cell ◽  
Early Decision ◽  
P Cells

The early somatic blastomeres founding the tissues in the C. elegans embryo are derived in a stem-cell-like lineage from the P cells. We have isolated maternal effect lethal mutations defining the gene cib-1 in which the P cells, P1-P3, skip a cell cycle and acquire the fates of only their somatic daughters. Therefore, the cib-1 gene is required for the specification of the stem-cell-like fate of these cells. The analysis of the development of these mutants suggests that the clock controlling the cell cycles in the early embryo is directly coupled to the fate of a cell and that there must be another developmental clock that activates the determinative inventory for the early decision-making.

scholarly journals Recent Advances in the Genetic, Anatomical, and Environmental Regulation of the C. elegans Germ Line Progenitor Zone

2020 ◽  
Vol 8 (3) ◽  
pp. 14
Author(s):  
Kacy Gordon
Keyword(s):  
Stem Cell ◽  
Cell Population ◽  
Germ Line ◽  
Stem Cell Population ◽  
Developmental Genetics ◽  
C Elegans ◽  
Open Questions ◽  
Genetic Features ◽  
Adult Hermaphrodite ◽  
Cell Niche

The C. elegans germ line and its gonadal support cells are well studied from a developmental genetics standpoint and have revealed many foundational principles of stem cell niche biology. Among these are the observations that a niche-like cell supports a self-renewing stem cell population with multipotential, differentiating daughter cells. While genetic features that distinguish stem-like cells from their differentiating progeny have been defined, the mechanisms that structure these populations in the germ line have yet to be explained. The spatial restriction of Notch activation has emerged as an important genetic principle acting in the distal germ line. Synthesizing recent findings, I present a model in which the germ stem cell population of the C. elegans adult hermaphrodite can be recognized as two distinct anatomical and genetic populations. This review describes the recent progress that has been made in characterizing the undifferentiated germ cells and gonad anatomy, and presents open questions in the field and new directions for research to pursue.

scholarly journals Intermittent Stem Cell Cycling Balances Self-Renewal and Senescence of the C. elegans Germ Line

PLoS Genetics ◽  
2016 ◽  
Vol 12 (4) ◽  
pp. e1005985 ◽  
Author(s):  
Amanda Cinquin ◽  
Michael Chiang ◽  
Adrian Paz ◽  
Sam Hallman ◽  
Oliver Yuan ◽  
...  
Keyword(s):  
Stem Cell ◽  
Germ Line ◽  
Self Renewal ◽  
C Elegans ◽  
Cell Cycling

scholarly journals Reduction of Derlin activity suppresses Notch-dependent tumours in the C. elegans germ line

2021 ◽  
Author(s):  
Ramya Singh ◽  
Ryan Smit ◽  
Xin Wang ◽  
Chris Wang ◽  
Hilary Racher ◽  
...  
Keyword(s):  
Stem Cell ◽  
Er Stress ◽  
Notch Signaling ◽  
Germ Line ◽  
Notch Receptor ◽  
Loss Of Function ◽  
Gain Of Function ◽  
Self Renewal ◽  
C Elegans ◽  
Proliferation Suppression

Regulating the balance between self-renewal (proliferation) and differentiation is key to the long-term functioning of all stem cell pools.  In the Caenorhabditis elegans germline, the primary signal controlling this balance is the conserved Notch signaling pathway.  Gain-of-function mutations in the GLP-1/Notch receptor cause increased stem cell self-renewal, resulting in a tumor of proliferating germline stem cells.  Notch gain-of-function mutations activate the receptor, even in the presence of little or no ligand, and have been associated with many human diseases, including cancers.  We demonstrate that reduction in CUP-2 and DER-2 function, which are Derlin family proteins that function in endoplasmic-reticulum-associated degradation (ERAD), suppresses the C. elegans germline over-proliferation phenotype associated with glp-1(gain-of-function) mutations.  We further demonstrate that their reduction does not suppress other mutations that cause over-proliferation, suggesting that over-proliferation suppression due to loss of Derlin activity is specific to glp-1/Notch (gain-of-function) mutations.  Reduction of CUP-2 Derlin activity reduces the expression of a read-out of GLP-1/Notch signaling, suggesting that the suppression of over-proliferation in Derlin loss-of-function mutants is due to a reduction in the activity of the mutated GLP-1/Notch(GF) receptor. Over-proliferation suppression in cup-2 mutants is only seen when the Unfolded Protein Response (UPR) is functioning properly, suggesting that the suppression, and reduction in GLP-1/Notch signaling levels, observed in Derlin mutants may be the result of activation of the UPR.  Chemically inducing ER stress also suppress glp-1(gf) over-proliferation but not other mutations that cause over-proliferation. Therefore, ER stress and activation of the UPR may help correct for increased GLP-1/Notch signaling levels, and associated over-proliferation, in the C. elegans germline.

AN INTEGRATED COMPREHENSIVE WORKBENCH FOR INFERRING GENETIC NETWORKS: VOYAGENE

2004 ◽  
Vol 02 (03) ◽  
pp. 533-550 ◽  
Author(s):  
YUKIHIRO MAKI ◽  
YORIKO TAKAHASHI ◽  
YUJI ARIKAWA ◽  
SHOJI WATANABE ◽  
KEN AOSHIMA ◽  
...  
Keyword(s):  
Expression Profiles ◽  
Genetic Network ◽  
Genetic Networks ◽  
Genetic Interactions ◽  
System Models ◽  
Threshold Test ◽  
Multi Level

We propose an integrated, comprehensive network-inferring system for genetic interactions, named VoyaGene, which can analyze experimentally observed expression profiles by using and combining the following five independent inferring models: Clustering, Threshold-Test, Bayesian, multi-level digraph and S-system models. Since VoyaGene also has effective tools for visualizing the inferred results, researchers may evaluate the combination of appropriate inferring models, and can construct a genetic network to an accuracy that is beyond the reach of a single inferring model. Through the use of VoyaGene, the present study demonstrates the effectiveness of combining different inferring models.

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