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PROVIDER: PRJNA1108864 | ENA |
REPOSITORIES: ENA
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Project description:This a model from the article:
Mathematical model predicts a critical role for osteoclast autocrine regulation in the control of bone remodeling.
Komarova SV, Smith RJ, Dixon SJ, Sims SM, Wahl LM Bone2003 Aug;33(2):206-15 14499354,
Abstract:
Bone remodeling occurs asynchronously at multiple sites in the adult skeleton and involves resorption by osteoclasts, followed by formation of new bone by osteoblasts. Disruptions in bone remodeling contribute to the pathogenesis of disorderssuch as osteoporosis, osteoarthritis, and Paget's disease. Interactions among cells of osteoblast and osteoclast lineages are critical in the regulation of bone remodeling. We constructed a mathematical model of autocrine and paracrine interactions among osteoblasts and osteoclasts that allowed us to calculate cell population dynamics and changes in bone mass at a discrete site of bone remodeling. Themodel predicted different modes of dynamic behavior: a single remodeling cycle in response to an external stimulus, a series of internally regulated cycles of bone remodeling, or unstable behavior similar to pathological bone remodeling in Paget's disease. Parametric analysis demonstrated that the mode of dynamic behaviorin the system depends strongly on the regulation of osteoclasts by autocrine factors, such as transforming growth factor beta. Moreover, simulations demonstratedthat nonlinear dynamics of the system may explain the differing effects of immunosuppressants on bone remodeling in vitro and in vivo. In conclusion, the mathematical model revealed that interactions among osteoblasts and osteoclasts result in complex, nonlinear system behavior, which cannot be deduced from studies of each cell type alone. The model will be useful in future studies assessing the impact of cytokines, growth factors, and potential therapies on the overall process ofremodeling in normal bone and in pathological conditions such as osteoporosis and Paget's disease.
The model reproduces Fig 2A and Fig 2B of the paper. Note that the Y-axis scale is not right, the osteoblast steadystate is approximatley 212 and not 0 as depicted in the figure. Also, there is atypo in the equation for x2_bar which has been corrected here. Model successfully tested on MathSBML.
This model originates from BioModels Database: A Database of Annotated Published Models. It is copyright (c) 2005-2009 The BioModels Team.For more information see the terms of use.To cite BioModels Database, please use Le Novère N., Bornstein B., Broicher A., Courtot M., Donizelli M., Dharuri H., Li L., Sauro H., Schilstra M., Shapiro B., Snoep J.L., Hucka M. (2006) BioModels Database: A Free, Centralized Database of Curated, Published, Quantitative Kinetic Models of Biochemical and Cellular Systems Nucleic Acids Res., 34: D689-D691.
2024-09-02 | BIOMD0000000148 | BioModels
Project description:Jason M. Graham, Bruce P. Ayati, Sarah A. Holstein & James A. Martin. The role of osteocytes in targeted bone remodeling: a mathematical model. PLoS ONE 8, 5 (2013).
Until recently many studies of bone remodeling at the cellular level have focused on the behavior of mature osteoblasts and osteoclasts, and their respective precursor cells, with the role of osteocytes and bone lining cells left largely unexplored. This is particularly true with respect to the mathematical modeling of bone remodeling. However, there is increasing evidence that osteocytes play important roles in the cycle of targeted bone remodeling, in serving as a significant source of RANKL to support osteoclastogenesis, and in secreting the bone formation inhibitor sclerostin. Moreover, there is also increasing interest in sclerostin, an osteocyte-secreted bone formation inhibitor, and its role in regulating local response to changes in the bone microenvironment. Here we develop a cell population model of bone remodeling that includes the role of osteocytes, sclerostin, and allows for the possibility of RANKL expression by osteocyte cell populations. We have aimed to give a simple, yet still tractable, model that remains faithful to the underlying system based on the known literature. This model extends and complements many of the existing mathematical models for bone remodeling, but can be used to explore aspects of the process of bone remodeling that were previously beyond the scope of prior modeling work. Through numerical simulations we demonstrate that our model can be used to explore theoretically many of the qualitative features of the role of osteocytes in bone biology as presented in recent literature.
2024-09-02 | BIOMD0000000721 | BioModels
Project description:The venom of cone snails is highly variable both between and within species, as well as spatially along the venom duct. However, defferences of defensive and predatory venoms in "hook-and-line" fish hunting clades and their venom duct origins has not been investigated. In this study a combination of proteomics and transcriptomic approaches were used to decode the venom profiles of C. striatus from the Pionoconus clade. The raw data files obtained from the reduced alkylated and digested venom duct sections (distal, central and proximal), injected predatory and defensive induced venoms are submitted here.
2022-02-17 | PXD026194 | Pride
Project description:Marine cone snails have attracted researchers from all disciplines but early life stages have received limited attention due to difficulties accessing or rearing juvenile specimens. Here, we document the culture of Conus magus from eggs through metamorphosis to reveal dramatic shifts in predatory feeding behaviour between post-metamorphic juveniles and adult specimens. Adult C. magus capture fish using a set of paralytic venom peptides combined with a hooked radular tooth used to tether envenomed fish. In contrast, early juveniles feed exclusively on polychaete worms using a unique “sting-and-stalk” foraging behaviour facilitated by short, unbarbed radular teeth and a distinct venom repertoire that induces hypoactivity in prey. Our results demonstrate how coordinated morphological, behavioural and molecular changes facilitate the shift from worm- to fish-hunting in C. magus, and showcase juvenile cone snails as a rich and unexplored source of novel venom peptides for ecological, evolutionary and biodiscovery studies.
2023-05-11 | PXD042133 | Pride
Project description:While the unique symbiotic relationship between anemonefish and sea anemones is iconic, it is still not fully understood how anemonefish withstand and thrive within this venomous host environment. In this study we used a proteotranscriptomics approach to elucidate the proteinaceous toxin repertoire from the most popular host sea anemone Entacmaea quadricolor. Although 1251 different toxin or toxin-like RNA transcripts were expressed in E.quadricolor tentacles and 2736 proteins were detected in milked venom, only 135 (approx. 10%) of proteins in venom were classified as putative toxins. This work raises the perils of defining a dominant venom type based on transcriptomics data alone in sea anemones, as we found that the dominant venom type differed between the transcriptome and proteome data. Moreover, anemonefishes interact with sea anemone proteins, so it is important when determining the dominant toxin type to examine the peptides and proteins that are present in host sea anemone venom and mucus which anemonefishes are known to interact.
2024-01-24 | PXD048736 | Pride
Project description:Diet and venom evolution in cone snails (Family, Conidae)
| PRJNA298293 | ENA
Project description:Background The generalist dipteran pupal parasitoid Nasonia vitripennis injects 79 venom peptides into the host before egg laying. This venom induces several important changes in the host, including developmental arrest, immunosuppression, and alterations to normal metabolism. It is hoped that diverse and potent bioactivities of N. vitripennis venom provide an opportunity for the design of novel acting drugs. However, currently very little is known about the individual functions of N. vitripennis venom peptides and less than half can be bioinformatically annotated. The paucity of annotation information complicates the design of studies that seek to better understand the potential mechanisms underlying the envenomation response. Although the RNA interference system of N. vitripennis provides an opportunity to functionally characterise venom encoding genes, with 79 candidates this represents a daunting task. For this reason we were interested in determining the expression levels of venom encoding genes in the venom gland, such that this information could be used to rank candidate venoms. To do this we carried out deep sequencing of the transcriptome of the venom gland and neighbouring ovary tissue and used RNA-seq to measure expression from the 79 venom encoding genes. The generation of a specific venom gland transcriptome dataset also provides further opportunities to investigate novel features of this highly specialised organ. Results High throughput sequencing and RNA-seq revealed that the highest expressed venom encoding gene in the venom gland was a serine protease called Nasvi2EG007167, which has previously been implicated in the apoptotic activity of N. vitripennis venom. As expected the RNA-seq confirmed that the N. vitripennis venom encoding genes are almost exclusively expressed in the venom gland relative to the neighbouring ovary tissue. Novel peptides appear to perform key roles in N. vitripennis venom function as only four of the highest 15 expressed venom encoding genes are bioinformatically annotationed. The high throughput sequencing data also provided evidence for the existence of an additional 471 novel genes in the Nasonia genome that are expressed in the venom gland and ovary. Finally, metagenomic analysis of venom gland transcripts identified viral transcripts that may play an important part in the N. vitripennis venom function. Conclusions The expression level information provided here for the 79 venom encoding genes provides an unbiased dataset that can be used by the N. vitripennis community to identify high value candidates for further functional characterisation. These candidates represent bioactive peptides that have value in drug development pipelines.
2016-12-31 | GSE76257 | GEO
Project description:This a model from the article:
Modeling the interactions between osteoblast and osteoclast activities in bone remodeling.
Lemaire V, Tobin FL, Greller LD, Cho CR, Suva LJ.
J Theor Biol.2004 Aug 7;229(3):293-309.
15234198,
Abstract:
We propose a mathematical model explaining the interactions between osteoblasts and osteoclasts, two cell types specialized in the maintenance of the bone integrity. Bone is a dynamic, living tissue whose structure and shape continuously evolves during life. It has the ability to change architecture by removal of old bone and replacement with newly formed bone in a localized process called remodeling. The model described here is based on the idea that the relative proportions of immature and mature osteoblasts control the degree of osteoclastic activity. In addition, osteoclasts control osteoblasts differentially depending on their stage of differentiation. Despite the tremendous complexity of the bone regulatory system and its fragmentary understanding, we obtain surprisingly good correlations between the model simulations and the experimental observations extracted from the literature. The model results corroborate all behaviors of the bone remodeling system that we have simulated, including the tight coupling between osteoblasts and osteoclasts, the catabolic effect induced by continuous administration of PTH, the catabolic action of RANKL, as well as its reversal by soluble antagonist OPG. The model is also able to simulate metabolic bone diseases such as estrogen deficiency, vitamin D deficiency, senescence and glucocorticoid excess. Conversely, possible routes for therapeutic interventions are tested and evaluated. Our model confirms that anti-resorptive therapies are unable to partially restore bone loss, whereas bone formation therapies yield better results. The model enables us to determine and evaluate potential therapies based on their efficacy. In particular, the model predicts that combinations of anti-resorptive and anabolic therapies provide significant benefits compared with monotherapy, especially for certain type of skeletal disease. Finally, the model clearly indicates that increasing the size of the pool of preosteoblasts is an essential ingredient for the therapeutic manipulation of bone formation. This model was conceived as the first step in a bone turnover modeling platform. These initial modeling results are extremely encouraging and lead us to proceed with additional explorations into bone turnover and skeletal remodeling.
This model corresponds to the core model published in the paper. There is no corresponding plot to reproduce for this model.
To obtain each of the 9 plots in the Figure 2 of the reference publication, there are some changes to be made to the core model.
The curation figure reproduces figure 2 of the reference publication. There is a corresponding SBML and Copasi files for each of the plot. See curation tab for more details.
This model originates from BioModels Database: A Database of Annotated Published Models (http://www.ebi.ac.uk/biomodels/). It is copyright (c) 2005-2010 The BioModels.net Team.
For more information see the terms of use.
To cite BioModels Database, please use: Li C, Donizelli M, Rodriguez N, Dharuri H, Endler L, Chelliah V, Li L, He E, Henry A, Stefan MI, Snoep JL, Hucka M, Le Novère N, Laibe C (2010) BioModels Database: An enhanced, curated and annotated resource for published quantitative kinetic models. BMC Syst Biol., 4:92.
2024-09-02 | BIOMD0000000278 | BioModels
Project description:We generated ATAC-seq data for pre- and post-extraction venom gland samples and H3K4me3, H3K27ac, and CTCF ChIP-seq from post-extraction venom gland samples from the Prairie Rattlesnake to investigate patterns of chromatin accessibility, transcription factor binding, and insulation during venom production, and to identify open promoters and active enhancer regions.
2022-04-07 | GSE169217 | GEO