Mosquito-borne viruses transmit between hosts and mosquito carriers through mosquito biting, which cause hundreds of millions of infections each year. These viral infections result in serious human diseases such as hemorrhagic fever, biphasic fever, arthritis, encephalitis and meningitis, which can lead to death if proper treatment is not available. Most mosquito-borne viruses are RNA viruses, with the flavivirus family as the most prevalent ones,including dengue virus, Zika virus, yellow fever virus, Japanese encephalitis virus and West Nile virus. Although there are effective vaccines for a few mosquito-borne flaviviruses, such as those for yellow fever virus and Japanese encephalitis virus, there are still no effective preventive vaccines and antiviral therapies for most mosquito-borne flaviviruses. Therefore, a comprehensive understanding of the mechanisms underlying the infection and transmission of mosquito-borne flaviviruses between vertebrate hosts and mosquitoes would provide insights for vaccine and drug development, enabling us to more effectively predict and control the transmission of mosquito-borne flavivirus and occurrence of the epidemics in the future, and providing solutions for addressing the public health threats posed by arboviruses. In this article, we firstly describe the biological and epidemiological characteristics of mosquito-borne flaviviruses, introduce the transmission routes and carrier models of mosquito-borne flaviviruses, and summarize the current research on the transmission and infection mechanisms of mosquito-borne flaviviruses between hosts and carriers. Furthermore, we highlight the development of novel vaccines and strategies for screening drugs to fight against mosquito-borne flaviviruses, providing an outlook for future research and development of vaccines and antiviral drugs.
Nature has invented a myriad of natural products through billions of years of evolution. Natural products own unique structural features selected by evolutionary pressure and serve as a treasure trove for drug discovery. The rapid growth of microbial genomic data now provides new opportunities for evolutionary and big data analysis of biosynthetic gene clusters, which not only gives us a clearer picture about the global landscape of natural products, but also enables us to reveal the evolutionary trajectory of natural products. Such holistic understanding of natural products can facilitate the phylogeny-guided genome mining, allow better functional prediction of biosynthetic enzymes, and even open the door to biosynthetic redesign to create non-natural molecules by evolution-guided engineering. The core essence of evolutionary and large-scale bioinformatics lies in that it visualizes the entire sequence space and their distribution of a particular analyte family. Therefore, big data-driven bioinformatics has the potential to answer some challenging questions such as "How many natural products remain to be discovered? ", and "How long can natural products discovery be sustainable? " This review summarizes recent advances in the application of evolution and big data-guided bioinformatics for natural products research from several perspectives including: 1) natural product discovery; 2) functional and structural prediction of biosynthetic enzymes and their products; and 3) bioengineering, with the emphasis on the assembly line enzymes such as polyketide synthases and non-ribosomal peptide synthetases. Due to the modular domain architecture they have, the assembly line enzymes have been the main targets for genome mining. The phylogenetic analysis of their domains has shown to be a powerful and effective way to predict their enzymatic function and substrate specificity. Recently, the evolutionary mechanism of the assembly line enzymes has been investigated, and several evolution-guided engineering strategies were shown to have much higher efficiency for the assembly line reprogramming, providing a potential breakthrough for the bioproduction of complex polyketides and peptides. Non-modular enzymes are also discussed with selected representative examples. Finally, we present current challenges and future prospects of big data-driven natural products research.
Brain-computer interfaces（BCI） currently exist primarily as a neuroprosthesis that allows electronic devices to communicate directly with parts of human brain, typically the cerebral cortex. In recent years, implantable BCI technology has made remarkable progress, and its applications have been expanded significantly, indicating that research achievements on neuroscience and their important transformation to BCI technology are interacted more efficiently and effectively. BCI is a process in which collected brain signals are decoded into digital information by a decoding algorithm through signal analysis, and computer, mechanical prosthesis, or other electrical stimulation device can be controlled based on this information. The most common applications of BCI are in medical applications, usually by capturing brain signals to synthesize understandable communications. For example, artificial tactile stimuli can be obtained through targeted electrical stimulation of the sensory cortex of brain, allowing patients with upper limb paralysis to imaginatively move their arms with the help from a tablet computer, restoring hand control through electrical stimulation of specific muscle tissues in the hand, and so on. Diseases like spinal cord injury, motor neuron disease, and stroke are currently untreatable, and BCI can be used to restore many interactive functions for paralyzed patients so that they can live and work normally, such as being able to communicate with others, such as talking, typing, and online socializing. On the other hand, BCI is also a powerful tool in neuroscience to study brain functions, such as conscious and subconscious feedback in brain-behavioral relationships. BCI for the motor function is the mainstream of research in these two fields. More and more BCI applications would be introduced in the near future, which could benefit paralyzed patients and patients with mental disorders, improving, even restoring their life qualities. In this article, we review the development of BCI and the different types of signal sources, with a focus on the medical-oriented and research-oriented BCI as well.
Mammalian chromosome engineering refers to its editing through various methods to create animal models for chromosome diseases, pharmaceutical factories of human proteins, dissection of mechanism underlying evolution,and even synthetic life. In recent years, some milestone technologies of mammalian chromosome engineering, such as natural chromosome modifications, chromosome design and synthesis, and chromosome large fragment transfer, have been developed and integrated with each other. At the same time, embryonic stem cells have also been developed as a new chassis for mammalian synthetic biology. Applications of embryonic stem cells to synthetic biology greatly promote the development of mammalian chromosome engineering, giving birth to a large number of animal models for studies on diseases and evolution, including mouse models for Down syndrome, mice producing human monoclonal antibodies, and chromosome-ligation mice to study the biological effects of chromosome recombination. However, the manipulations of mammalian chromosomes are still challenging due to the lack of comprehensive understanding on chromosome composition and mammalian development. In addition to technological challenges, there are issues with bioethics and bio-safety. In this review, we review main technologies and current applications of mammalian chromosome engineering, and we also highlight future applications and challenges of mammalian chromosome engineering.
Synthetic biology（SB） is an emerging discipline, which utilizes genetic engineering, systems biology,computer science, and other disciplines as tools to design, and even re-synthesize biological systems for specific needs.In the past 20 years, milestone breakthroughs in SB have been achieved and applied in the diagnosis and treatment of human diseases, particularly in the discovery of new drugs. SB not only provides new ideas and technical tools for the early and accurate diagnosis of diseases, but also develops a variety of new approaches for treating diseases, including cell therapy, bacteriotherapy, vaccines, and biomedical materials. Using SB-based methods, we can precisely diagnose diseases at an early stage, specifically engineer cells or bacteria, conduct mechanistic studies and drug screening, and rapidly produce vaccines and biomedical materials. SB with the “design-build-test” cycle greatly facilitates the development of new diagnostic and therapeutic approaches. Moreover, SB applies engineering principles（modularity, composability, abstraction, and standardization） to redefine biological systems in a more modular and composable way. Through this framework, the basic units of the biological system are fully characterized as standardized motifs（DNA sequences or gene-encoded products）, and these motifs are mixed and matched to construct a fully functional genetic apparatus. By utilizing recently developed gene editing tools, such as the clustered regularly interspaced palindromic repeats（CRISPR/Cas9） technology, SB can integrate programmed devices into a chassis（e.g., bacteria and yeast）, create new systems capable of producing target biomolecules or behaviors, and precisely manipulate the genome of cells and individuals to repair genetic defects. SB-based disease diagnosis and treatment will be one of the important development directions in the field of scientific research to completely change the way of diagnosis and clinical treatment of diseases in the future. This article reviews the applications of SB-based technologies in disease diagnosis and treatment, as well as in the production of vaccines and biomedical materials, as well as in new drug development.
