Search NASA⌕ Search
Home/Archive/NASA NTRS

NASA NTRS · 20040112370

Whole-cell biocomputing

Simpson, M. L.·Sayler, G. S.·Fleming, J. T.·Applegate, B.
View original source ↗Export metadata ↓

Abstract

The ability to manipulate systems on the molecular scale naturally leads to speculation about the rational design of molecular-scale machines. Cells might be the ultimate molecular-scale machines and our ability to engineer them is relatively advanced when compared with our ability to control the synthesis and direct the assembly of man-made materials. Indeed, engineered whole cells deployed in biosensors can be considered one of the practical successes of molecular-scale devices. However, these devices explore only a small portion of cellular functionality. Individual cells or self-organized groups of cells perform extremely complex functions that include sensing, communication, navigation, cooperation and even fabrication of synthetic nanoscopic materials. In natural systems, these capabilities are controlled by complex genetic regulatory circuits, which are only partially understood and not readily accessible for use in engineered systems. Here, we focus on efforts to mimic the functionality of man-made information-processing systems within whole cells.

Explore related subjects

Non-NASA CenterReviewNASA Discipline Life Sciences TechnologiesReview LiteratureComputational BiologySupport, Non-U.S. Gov'tSiliconSupport, U.S. Gov't, Non-P.H.S

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Simpson, M. L., Sayler, G. S., Fleming, J. T., Applegate, B.. 2001-08-01. Whole-cell biocomputing. https://ntrs.nasa.gov/citations/20040112370

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related reports

NASA NTRS2005

Cycle-averaged dynamics of a periodically driven, closed-loop circulation model

Time-varying elastance models have been used extensively in the past to simulate the pulsatile nature of cardiovascular waveforms. Frequently, however, one is interested in dynamics that occur over longer time scales, in which case a detailed simulation of each cardiac contraction becomes computationally burdensome. In this paper, we apply circuit-averaging techniques to a periodically driven, closed-loop, three-compartment recirculation model. The resultant cycle-averaged model is linear and time invariant, and greatly reduces the computational burden. It is also amenable to systematic order reduction methods that lead to further efficiencies. Despite its simplicity, the averaged model captures the dynamics relevant to the representation of a range of cardiovascular reflex mechanisms. c2004 Elsevier Ltd. All rights reserved.

Non-NASA Center↗
NASA NTRS2005

Early immune response and regulation of IL-2 receptor subunits

Affymetrix oligonucleotide arrays were used to monitor expression of 8796 genes and probe sets in activated T-cells; analysis revealed that 217 genes were significantly upregulated within 4 h. Induced genes included transcription factors, cytokines and their receptor genes. Analysis by semi-quantitative RT-PCR confirmed the significant induction of IL-2, IL-2R(gamma) and IL-2R(alpha). Forty-eight of the 217 induced genes are known to or predicted to be regulated by a CRE promoter/enhancer. We found that T-cell activation caused a significant increase in CREB phosphorylation furthermore, inhibition of the PKC pathway by GF109203 reduced CREB activation by 50% and inhibition of the PKA pathway caused a total block of CREB phosphorylation and significantly reduced IFN(gamma), IL-2 and IL-2R(alpha) gene expression by approximately 40% (p<0.001). PKC(theta) plays a major role in T-cell activation: inhibition of PKC significantly reduced the expression of IFN(gamma), IL-2 and IL-2R(alpha). Since PKC blocked activation of CREB, we studied potential cross-talk between the PKC and the PKA/MAPK pathways, PMA-stimulated Jurkat cells were studied with specific signal pathway inhibitors. Extracellular signal-regulated kinase-2 (ERK2) pathway was found to be significantly activated greater than seven-fold within 30 min; however, there was little activation of ERK-1 and no activation of JNK or p38 MAPK. Inhibition of the PKA pathway, but not the PKC pathway, resulted in inhibition of ERK1/2 activation at all time points, inhibition of MEK1 and 2 significantly blocked expression of IL-2 and IL-2R(alpha). Gene expression of IL-2R(alpha) and IFN(gamma) was dependent on PKA in S49 wt cells but not in kin- mutants. Using gel shift analysis, we found that forskolin activation of T-cells resulted in activation of AP1 sites; this increase in nuclear extract AP1 was significantly blocked by MEK1 inhibitor U0126. Taken together, these results suggest that the PKA in addition to PKC and MAPK pathways plays a role in early T-cell activation and induction of IL-2, IL-2R(alpha) and IFN(gamma) gene expression.

Non-NASA Center↗
NASA NTRS2005

Depth-varying density and organization of chondrocytes in immature and mature bovine articular cartilage assessed by 3d imaging and analysis

Articular cartilage is a heterogeneous tissue, with cell density and organization varying with depth from the surface. The objectives of the present study were to establish a method for localizing individual cells in three-dimensional (3D) images of cartilage and quantifying depth-associated variation in cellularity and cell organization at different stages of growth. Accuracy of nucleus localization was high, with 99% sensitivity relative to manual localization. Cellularity (million cells per cm3) decreased from 290, 310, and 150 near the articular surface in fetal, calf, and adult samples, respectively, to 120, 110, and 50 at a depth of 1.0 mm. The distance/angle to the nearest neighboring cell was 7.9 microm/31 degrees , 7.1 microm/31 degrees , and 9.1 microm/31 degrees for cells at the articular surface of fetal, calf, and adult samples, respectively, and increased/decreased to 11.6 microm/31 degrees , 12.0 microm/30 degrees , and 19.2 microm/25 degrees at a depth of 0.7 mm. The methodologies described here may be useful for analyzing the 3D cellular organization of cartilage during growth, maturation, aging, degeneration, and regeneration.

Non-NASA Center↗