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Madamanchi, A.

Publications and source records attributed to Madamanchi, A..

3 recordsLinked to original sources

Stochastic Modeling of BMP Heterodimer-Receptor Interactions Shows Emergence of Low-Pass Filtering Behavior

In developing tissues, signal transduction from morphogen gradients conveys positional information to cells, resulting in cell specification and differentiation. One such morphogen is bone morphogenetic protein (BMP), of the TGF-{beta} superfamily, whose signaling network is highly conserved across many species. In Danio rerio (zebrafish), this signaling pathway directs dorsoventral axis formation during early embryogenesis. Many of the molecules that play a role in this network are well-understood; however, the mechanisms through which they achieve noise attenuation and gradient robustness have not been fully defined. Specifically, the heterodimer-heterotetramer complex has been shown to be required for signal transduction[1], but current understanding and modeling of the BMP membrane receptors at this stage has not given any insight into evolutionary drivers of the requirement. In this study, we develop a stochastic model of receptor oligomerization with the published reports of binding kinetics of BMP ligand-receptor interactions to mechanistically assess zebrafish phenotype variability related to the distributions of noise and stochasticity. We can also analyze time-dependent signaling and frequency metrics that are not available in traditional, deterministic modeling. Fast Fourier Transform and cumulative energy spectral density visualization show that the heterodimer-heterotetramer complex may function as part of a low-pass filter mechanism in the dorsal-ventral axis formation process, specifically tuned to the noise of the system. Under dynamic conditions such as the mid-blastula transition (MBT), wherein the morphogen gradient rapidly changes shape, established metrics of noise and information transduction, such as coefficient of variation and mutual information, overlook important temporal effects that may be particularly relevant during development. As the BMP signaling pathway is highly conserved and has been implicated in human bone growth and wound healing, its study in simpler systems stands to accelerate our comprehension of BMP network structure and molecular mechanisms with potential application in regenerative medical studies.

developmental biology↗

Computational modeling of TGF-β2:TβRI:TβRII receptor complex assembly as mediated by the TGF-β co-receptor betaglycan

Transforming growth factor-{beta}1, -{beta}2, and -{beta}3 (TGF-{beta}1, -{beta}2, and -{beta}3) are secreted signaling ligands that play essential roles in tissue development, tissue maintenance, immune response, and wound healing. TGF-{beta} homodimers signal by assembling a heterotetrameric complex comprised of two type I receptor (T{beta}RI):type II receptor (T{beta}RII) pairs. TGF-{beta}1 and TGF-{beta}3 signal with high potency due to their high affinity for T{beta}RII, which engenders high affinity binding of T{beta}RI through a composite TGF-{beta}:T{beta}RII binding interface. However, TGF-{beta}2 binds T{beta}RII 200-500 more weakly than T{beta}RII and signals with lower potency compared to TGF-{beta}1 and -{beta}3. Remarkably, potency of TGF-{beta}2 is increased to that of TGF-{beta}1 and -{beta}3 in the presence of an additional membrane-bound co-receptor, known as betaglycan (BG), even though betaglycan does not directly participate in the signaling mechanism and is displaced as the signaling receptors, T{beta}RI and T{beta}RII, bind. To determine the role of betaglycan in the potentiation of TGF-{beta}2 signaling, we developed deterministic computational models with different modes of betaglycan binding and varying cooperativity between receptor subtypes. The models, which were developed using published kinetic rate constants for known quantities and optimization to determine unknown quantities, identified conditions for selective enhancement of TGF-{beta}2 signaling. The models provide support for additional receptor binding cooperativity that has been hypothesized, but not evaluated in the literature. The models further showed that betaglycan binding to TGF-{beta}2 ligand through two domains provides an effective mechanism for transfer to the signaling receptors that has been tuned to efficiently promote assembly of the TGF-{beta}2(T{beta}RII)2(T{beta}RI)2 signaling complex.

biophysics↗

Supporting Computational Apprenticeship through educational and software infrastructure. A case study in a mathematical oncology research lab

There is growing awareness of the need for mathematics and computing to quantitatively understand the complex dynamics and feedbacks in the life sciences. Although several institutions and research groups are conducting pioneering multidisciplinary research, communication and education across fields remains a bottleneck. The opportunity is ripe for using education research-supported mechanisms of cross-disciplinary training at the intersection of mathematics, computation and biology. This case study uses the computational apprenticeship theoretical framework to describe the efforts of a computational biology lab to rapidly prototype, test, and refine a mentorship infrastructure for undergraduate research experiences. We describe the challenges, benefits, and lessons learned, as well as the utility of the computational apprenticeship framework in supporting computational/math students learning and contributing to biology, and biologists in learning computational methods. We also explore implications for undergraduate classroom instruction, and cross-disciplinary scientific communication.

scientific communication and education↗