Background: One of the underlying assumptions of synthetic biology is that biological processes can be engineered in a controllable way.

Results: Here we discuss this assumption as it relates to synthetic gene regulatory networks (GRNs). We first cover the theoretical basis of GRN control, then address three major areas in which control has been leveraged: engineering and analysis of network stability, temporal dynamics, and spatial aspects.

Conclusion: These areas lay a strong foundation for further expansion of control in synthetic GRNs and pave the way for future work synthesizing these disparate concepts.

Controlling the behavior of gene networks is the basis of much of synthetic biology. Here we review major theoretical concepts underpinning gene regulatory network (GRN) control and how these concepts are implemented to organize biological parts into functional and predictable synthetic GRNs. We present several contexts in which theory and practice have been synthesized in constructed GRNs to generate biologically relevant behaviors: multistability, designed temporal dynamics, and spatial patterning. These proof-of-concept works set researchers up to engineer more complex and controllable circuits in the future.

Background: The shortage of available organs for transplantation is the major obstacle hindering the application of regenerative medicine, and has also become the desperate problem faced by more and more patients nowadays. The recent development and application of 3D printing technique in biological research (bioprinting) has revolutionized the tissue engineering methods, and become a promising solution for tissue regeneration.

Results: In this review, we summarize the current application of bioprinting in producing tissues and organoids, and discuss the future directions and challenges of 3D bioprinting.

Conclusions: Currently, 3D bioprinting is capable to generate patient-specialized bone, cartilage, blood vascular network, hepatic unit and other simple components/tissues, yet pure cell-based functional organs are still desired.

Recent advances in 3D printing has prompted the development of tissue engineering methods, enabling researchers to design and fabricate native-like simple organs to an unprecedented level of resolution and resemblance. Here, we review the commonly used 3D printing strategy in tissue engineering and the current progresses of 3D printed organs, we also discuss the future perspectives regarding the improvement of tissue engineering.

Background: Recently we proposed a quantum theory on the conformational change of biomolecule, deduced several equations on protein folding rate from the first principles and discussed the experimental tests of the theory. The article is a review of these works.

Methods: Based on the general equation of the conformation-transitional rate several theoretical results are deduced and compared with experimental data through bioinformatics methods.

Results: The temperature dependence and the denaturant concentration dependence of the protein folding rate are deduced and compared with experimental data. The quantitative relation between protein folding rate and torsional mode number (or chain length) is deduced and the obtained formula can be applied to RNA folding as well. The quantum transition theory of two-state protein is successfully generalized to multi-state protein folding. Then, how to make direct experimental tests on the quantum property of the conformational transition of biomolecule is discussed, which includes the study of protein photo-folding and the observation of the fluctuation of the fluorescence intensity emitted from the protein folding/unfolding event. Finally, the potential applications of the present quantum folding theory to molecular biological problems are sketched in two examples: the glucose transport across membrane and the induced pluripotency in stem cell.

Conclusions: The above results show that the quantum mechanics provides a unifying and logically simple theoretical starting point in studying the conformational change of biological macromolecules. The far-reaching results in practical application of the theory are expected.

Quantum theory on the conformational change of biomolecule is reviewed. The protein folding is looked as a quantum transition between torsion states of the chain of amino acids. It means that the protein could “jump” from one shape to another without necessarily forming the shapes in between. The review emphasizes the checking of the new theory against experimental data. All comparisons (including on the non-Arrhenius temperature dependence of the folding rate) show that the quantum mechanism does exist in the conformational transition of biomolecules and the quantum mechanics provides a unifying and logically simple starting point for studying these problems.

Background: Although significant progress has been made to map chromatin structure at unprecedented resolution and scales, we are short of tools that enable the intuitive visualization and navigation along the three-dimensional (3D) structure of chromatins. The available tools people have so far are generally script-based or present basic features that do not easily enable the integration of genomic data along with 3D chromatin structure, hence, many scientists find themselves in the obligation to hack tools designed for other purposes such as tools for protein structure study.

Methods: We present HiC-3DViewer, a new browser-based interactive tool designed to provide an intuitive environment for investigators to facilitate the 3D exploratory analysis of Hi-C data along with many useful annotation functionalities. Among the key features of HiC-3DViewer relevant to chromatin conformation studies, the most important one is the 1D-to-2D-to-3D mapping, to highlight genomic regions of interest interactively. This feature enables investigators to explore their data at different levels/angels. Additionally, investigators can superpose different genomic signals (such as ChIP-Seq, SNP) on the top of the 3D structure.

Results: As a proof of principle we applied HiC-3DViewer to investigate the quality of Hi-C data and to show the spatial binding of GATA1 and GATA2 along the genome.

Conclusions: As a user-friendly tool, HiC-3DViewer enables the visualization of inter/intra-chromatin interactions and gives users the flexibility to customize the look-and-feel of the 3D structure with a simple click. HiC-3DViewer is implemented in Javascript and Python, and is freely available at: http://bioinfo.au.tsinghua.edu.cn/member/nadhir/HiC3DViewer/. Supplementary information (User Manual, demo data) is also available at this website.

Recently, many tools have developed to analyze and visualize chromatin conformation data. However, we are short of tools that enable the interactive visualization of the 3D chromatin structure. Here, we introduce HiC3D-Viewer, a new browser-based interactive visualization tool designed to provide an intuitive environment that facilitates the 3D exploratory analysis of Hi-C data. Among the key features of HiC-3DViewer is the 1D-to-2D-to-3D interactive highlight of genomic regions, display of inter- and intra-chromatin interactions and 3D model predictions, in addition to the flexibility to customize the displayed models, which make very valuable for the chromatin structure community.

Owing to its interdisciplinary nature, quantitative biology is playing ever-increasing roles in biological researches. To make quantitative biology even more powerful, it is important to develop a holistic perspective by integrating information from multiple biological levels and by considering related biocomplexity simultaneously. Using complex diseases as an example, I show in this paper how their ontological connections can be revealed by considering the diseases on a common ground. The obtained insights may be useful to the prediction and treatment of the diseases. Although the example involves only with cancer and diabetes, the approaches are applicable to the study of other diseases, or even to other biological problems.

Deep connections may exist between seemingly disparate things. Using complex diseases as an example, the author shows that the connections between diseases can be revealed by using powerful approaches of mathematics and quantitative biology. The obtained insights may be useful to the prediction and treatment of the diseases. It is promising to apply the approaches to study other biological problems.