Watch the clock-engineering biological systems to be on time. Curr Opin Genet Dev
Inspired by natural time-keeping devices controlling the circadian clock, managing information processing in the brain and coordinating physiological activities on a daily (feeding and sleeping) or seasonal timescale (reproductive activity or hibernation), synthetic biologists have successfully assembled functional synthetic clocks from cataloged genetic components with standardized activities and arranging them in transcription circuits containing positive and negative feedback loops with integrated time-delay dynamics. While the positive feedback loop drives the clock like the (balance) spring in a mechanical watch the negative time-delay circuit represents the pulse generator defining a minimal time unit and precision of the clock like the pendulum fallback or the movement of the balance wheel in a classical mechanic watch. This basic design principle enabled the construction of a variety of synthetic oscillators whose design details are concisely covered in this review.
[Show abstract] [Hide abstract] ABSTRACT: Improved characterization of infectious disease dynamics is required. To that end, three-dimensional (3D) data analysis of feedback-like processes may be considered. To detect infectious disease data patterns, a systems biology (SB) and evolutionary biology (EB) approach was evaluated, which utilizes leukocyte data structures designed to diminish data variability and enhance discrimination. Using data collected from one avian and two mammalian (human and bovine) species infected with viral, parasite, or bacterial agents (both sensitive and resistant to antimicrobials), four data structures were explored: (i) counts or percentages of a single leukocyte type, such as lymphocytes, neutrophils, or macrophages (the classic approach), and three levels of the SB/EB approach, which assessed (ii) 2D, (iii) 3D, and (iv) multi-dimensional (rotating 3D) host-microbial interactions. In all studies, no classic data structure discriminated disease-positive (D+, or observations in which a microbe was isolated) from disease-negative (D-, or microbial-negative) groups: D+ and D- data distributions overlapped. In contrast, multi-dimensional analysis of indicators designed to possess desirable features, such as a single line of observations, displayed a continuous, circular data structure, whose abrupt inflections facilitated partitioning into subsets statistically significantly different from one another. In all studies, the 3D, SB/EB approach distinguished three (steady, positive, and negative) feedback phases, in which D- data characterized the steady state phase, and D+ data were found in the positive and negative phases. In humans, spatial patterns revealed false-negative observations and three malaria-positive data classes. In both humans and bovines, methicillin-resistant Staphylococcus aureus (MRSA) infections were discriminated from non-MRSA infections. More information can be extracted, from the same data, provided that data are structured, their 3D relationships are considered, and well-conserved (feedback-like) functions are estimated. Patterns emerging from such structures may distinguish well-conserved from recently developed host-microbial interactions. Applications include diagnosis, error detection, and modeling.0Comments 5Citations
- "Such structure can distinguish the temporal sequence of biological responses regardless of chronological scales (minutes/hours/days) and is robust to the absence (or presence) of slow (or fast) immune responders . While the cyclic nature of feedback features is useful to describe dynamics484950, to detect infectious disease dynamics, logical aspects should also be addressed. Fallacies may occur at theFigure 5. "
[Show abstract] [Hide abstract] ABSTRACT: A challenge in biology is to understand how complex molecular networks in the cell execute sophisticated regulatory functions. Here we explore the idea that there are common and general principles that link network structures to biological functions, principles that constrain the design solutions that evolution can converge upon for accomplishing a given cellular task. We describe approaches for classifying networks based on abstract architectures and functions, rather than on the specific molecular components of the networks. For any common regulatory task, can we define the space of all possible molecular solutions? Such inverse approaches might ultimately allow the assembly of a design table of core molecular algorithms that could serve as a guide for building synthetic networks and modulating disease networks.0Comments 50Citations
- "Minimal designs have been identified that yield robust oscillations with either tunable amplitude or frequency, and these match architectures observed in natural oscillator systems. Thus iterative synthetic cycles have been useful in defining the space of oscillatory networks, and in distinguishing bare bones oscillator designs from slightly more complex designs that show far more robust behaviors or more specialized classes of behaviors (Atkinson et al., 2003; Fung et al., 2005; Stricker et al., 2008; Tsai et al., 2008; Tigges et al., 2009 Tigges et al., , 2010 Aubel and Fussenegger, 2010). In addition to oscillators, synthetic biology approaches have been used to explore the construction of systems performing a range of other functional behaviors, including bistable memory switches, logic gate operations, population control, multicellular patterning, multicellular boundary formation, and cell polarization (Figures 4D and 4E). "
- [Show abstract] [Hide abstract] ABSTRACT: This paper reviews the FEOL technologies for fabricating the transistor for high performance logic and system LSI devices of 100 nm node, especially, doping process, gate dielectric formation and shallow junction formation using spike annealing. The optimization of ion implantation for gate doping contact source drain, and gate oxide, spike annealing are described0Comments 0Citations