Synthetic biology has the potential to positively transform society in many application areas, including medicine. In common with all revolutionary new technologies, synthetic biology can also enable crime. Like cybercrime, that emerged following the advent of the internet, biocrime can have a significant effect on society, but may also impact on peoples' health. For example, the scale of harm caused by the SARS-CoV-2 pandemic illustrates the potential impact of future biocrime and highlights the need for prevention strategies. Systematic evidence quantifying the crime opportunities posed by synthetic biology has to date been very limited. Here, we systematically reviewed forms of crime that could be facilitated by synthetic biology with a view to informing their prevention. A total of 794 articles from four databases were extracted and a three-step screening phase resulted in 15 studies that met our threshold criterion for thematic synthesis. Within those studies, 13 exploits were identified. Of these, 46% were dependent on technologies characteristic of synthetic biology. Eight potential crime types emerged from the studies: bio-discrimination, cyber-biocrime, bio-malware, biohacking, at-home drug manufacturing, illegal gene editing, genetic blackmail, and neuro-hacking. 14 offender types were identified. For the most commonly identified offenders (>3 mentions) 40% were outsider threats. These observations suggest that synthetic biology presents substantial new offending opportunities. Moreover, that more effective engagement, such as ethical hacking, is needed now to prevent a crime harvest from developing in the future. A framework to address the synthetic biology crime landscape is proposed.
Diatoms are photosynthetic microeukaryotes that dominate phytoplankton populations and have increasing applicability in biotechnology. Uncovering their complex biology and elevating strains to commercial standards depends heavily on robust genetic engineering tools. However, engineering microalgal genomes predominantly relies on random integration of transgenes into nuclear DNA, often resulting in detrimental “position-effects” such as transgene silencing, integration into transcriptionally-inactive regions, and endogenous sequence disruption. With the recent development of extrachromosomal transgene expression via independent episomes, it is timely to investigate both strategies at the phenotypic and genomic level. Here, we engineered the model diatom Phaeodactylum tricornutum to produce the high-value heterologous monoterpenoid geraniol, which, besides applications as fragrance and insect repellent, is a key intermediate of high-value pharmaceuticals. Using high-throughput phenotyping we confirmed the suitability of episomes for synthetic biology applications and identified superior geraniol-yielding strains following random integration. We used third generation long-read sequencing technology to generate a complete analysis of all integration events, genomic locations, and transgene arrangements associated with high-performing strains at a genome-wide scale with subchromosomal detail, never before reported in any microalga. This revealed very large, highly concatenated insertion islands, offering profound implications on diatom functional genetics and next generation genome editing technologies, and are key for developing more precise genome engineering approaches in diatoms, including possible genomic safe harbour locations to support high transgene expression for targeted integration approaches. Furthermore, we have demonstrated that exogenous DNA is not integrated inadvertently into the nuclear genome of extrachromosomal-expression clones, an important characterisation of this novel engineering approach that paves the road to synthetic biology applications.
BACKGROUND: Synthetic biology approaches can make a significant contribution to the advance of metabolic engineering by reducing the development time of recombinant organisms. However, most of synthetic biology tools have been developed for Escherichia coli. Here we provide a platform for rapid engineering of C. glutamicum, a microorganism of great industrial interest. This bacteria, used for decades for the fermentative production of amino acids, has recently been developed as a host for the production of several economically important compounds including metabolites and recombinant proteins because of its higher capacity of secretion compared to traditional bacterial hosts like E. coli. Thus, the development of modern molecular platforms may significantly contribute to establish C. glutamicum as a robust and versatile microbial factory. RESULTS: A plasmid based platform named pTGR was created where all the genetic components are flanked by unique restriction sites to both facilitate the evaluation of regulatory sequences and the assembly of constructs for the expression of multiple genes. The approach was validated by using reporter genes to test promoters, ribosome binding sites, and for the assembly of dual gene operons and gene clusters containing two transcriptional units. Combinatorial assembly of promoter (tac, cspB and sod) and RBS (lacZ, cspB and sod) elements with different strengths conferred clear differential gene expression of two reporter genes, eGFP and mCherry, thus allowing transcriptional "fine-tuning"of multiple genes. In addition, the platform allowed the rapid assembly of operons and genes clusters for co-expression of heterologous genes, a feature that may assist metabolic pathway engineering. CONCLUSIONS: We anticipate that the pTGR platform will contribute to explore the potential of novel parts to regulate gene expression, and to facilitate the assembly of genetic circuits for metabolic engineering of C. glutamicum. The standardization provided by this approach may provide a means to improve the productivity of biosynthetic pathways in microbial factories for the production of novel compounds.
Here I examine the potential for art-science collaborations to be the basis for deliberative discussions on research agendas and direction. Responsible Research and Innovation (RRI) has become a science policy goal in synthetic biology and several other high-profile areas of scientific research. While art-science collaborations offer the potential to engage both publics and scientists and thus possess the potential to facilitate the desired "mutual responsiveness" (René von Schomberg) between researchers, institutional actors, publics and various stakeholders, there are potential challenges in effectively implementing collaborations as well as dangers in potentially instrumentalizing artistic work for science policy or innovation agendas when power differentials in collaborations remain unacknowledged. Art-science collaborations can be thought of as processes of exchange which require acknowledgement of and attention to artistic agendas (how can science be a conceptual and material resource for new aesthetics work) as well as identification of and attention to aesthetic dimensions of scientific research (how are aesthetics and affective framings a part of a specific epistemological resource for scientific research). I suggest the advantage of specifically identifying public engagement/science communication as a distinct aspect of such projects so that aesthetic, scientific or social science/philosophical research agendas are not subsumed to the assumption that the primary or only value of art-science collaborations is as a form of public engagement or science communication to mediate biological research community public relations. Likewise, there may be potential benefits of acknowledging an art-science-RRI triangle as stepping stone to a more reflexive research agenda within the STS/science communication/science policy community. Using BrisSynBio, an EPSRC/BBSRC-funded research centre in synthetic biology, I will discuss the framing for art-science collaborations and practical implementation and make remarks on what happened there. The empirical evidence reviewed here supports the model I propose but additionally, points to the need to broaden the conception of and possible purposes, or motivations for art, for example, in the case of cross-sectoral collaboration with community engaged art.
This report, prepared for the Synthetic Biology Project at the Woodrow Wilson International Center for Scholars, analyzes the 2010 Nagoya Protocol to the Convention on Biological Diversity and how it may affect U.S. researchers working in the field of synthetic biology. The objective of the Protocol is to provide a transparent framework for the acquisition and sharing of genetic resources on fair and equitable terms that facilitate the conservation of biological diversity and associated traditional knowledge. The report finds significant uncertainty surrounding the temporal scope of the Agreement as well as the types of genetic material that will be covered at the implementing country level. Even though the United States is not a signatory to the Protocol, the report recommends that U.S. researchers should engage in discussions regarding the crafting of implementing legislation as they develop, verify the origin of the genetic material that they use, and ensure that such material was taken in compliance with the domestic law of a provider country.
BACKGROUND: Many difficult problems in evolutionary genomics are related to mutations that have weak effects on fitness, as the consequences of mutations with large effects are often simple to predict. Current systems biology has accumulated much data on mutations with large effects and can predict the properties of knockout mutants in some systems. However experimental methods are too insensitive to observe small effects. RESULTS: Here I propose a novel framework that brings together evolutionary theory and current systems biology approaches in order to quantify small effects of mutations and their epistatic interactions in silico. Central to this approach is the definition of fitness correlates that can be computed in some current systems biology models employing the rigorous algorithms that are at the core of much work in computational systems biology. The framework exploits synergies between the realism of such models and the need to understand real systems in evolutionary theory. This framework can address many longstanding topics in evolutionary biology by defining various 'levels' of the adaptive landscape. Addressed topics include the distribution of mutational effects on fitness, as well as the nature of advantageous mutations, epistasis and robustness. Combining corresponding parameter estimates with population genetics models raises the possibility of testing evolutionary hypotheses at a new level of realism. CONCLUSION: EvoSysBio is expected to lead to a more detailed understanding of the fundamental principles of life by combining knowledge about well-known biological systems from several disciplines. This will benefit both evolutionary theory and current systems biology. Understanding robustness by analysing distributions of mutational effects and epistasis is pivotal for drug design, cancer research, responsible genetic engineering in synthetic biology and many other practical applications.
construction of a living organism is a compelling vision. Despite the astonishing technologies developed to modify living cells, building a functioning cell "from scratch" has yet to be accomplished. The pursuit of this goal alone has─and will─yield scientific insights affecting fields as diverse as cell biology, biotechnology, medicine, and astrobiology. Multiple approaches have aimed to create biochemical systems manifesting common characteristics of life, such as compartmentalization, metabolism, and replication and the derived features, evolution, responsiveness to stimuli, and directed movement. Significant achievements in synthesizing each of these criteria have been made, individually and in limited combinations. Here, we review these efforts, distinguish different approaches, and highlight bottlenecks in the current research. We look ahead at what work remains to be accomplished and propose a "roadmap" with key milestones to achieve the vision of building cells from molecular parts.
Over the last decade the discourse of responsible innovation (RI) has become a significant feature of debates concerning the relationships between science, innovation and society in the fields of biosciences and biotechnologies. We document how this discourse has evolved over the period 2014–2019 at a Synthetic Biology Research Centre hosted within a University in the UK (BrisSynBio). We describe how an approach to RI has evolved to include but go beyond public engagement, by encouraging practices aimed at anticipation, reflexivity and deliberation in sometimes creative and innovative ways. We describe how the Centre has struggled to capture the impacts of RI interventions on the everyday practices and behaviours of scientists and the outcomes of their work. The study reveals the importance of leadership, creativity, innovation, institutional support, openness to change and mechanisms of capturing impact for successful RI institutionalisation.
Bottom-up synthetic biology has directed most efforts toward the construction of artificial compartmentalized systems that recreate living cell functions in their mechanical, morphological, or metabolic characteristics. However, bottom-up synthetic biology also offers great potential to study subcellular structures like organelles. Because of their intricate and complex structure, these key elements of eukaryotic life forms remain poorly understood. Here, the controlled assembly of lipid enclosed, organelle-like architectures is explored by droplet-based microfluidics. Three types of giant unilamellar vesicles (GUVs)-based synthetic organelles (SOs) functioning within natural living cells are procedured: (A) synthetic peroxisomes supporting cellular stress-management, mimicking an organelle innate to the host cell by using analogous enzymatic modules; (B) synthetic endoplasmic reticulum (ER) as intracellular light-responsive calcium stores involved in intercellular calcium signalling, mimicking an organelle innate to the host cell but utilizing a fundamentally different mechanism; and (C) synthetic magnetosomes providing eukaryotic cells with a magnetotactic sense, mimicking an organelle that is not natural to the host cell but transplanting its functionality from other branches of the phylogenetic tree. Microfluidic assembly of functional SOs paves the way for high-throughput generation of versatile intracellular structures implantable into living cells. This in-droplet SO design may support or expand cellular functionalities in translational nanomedicine.
Environmental metagenomic analysis is typically accomplished by assigning taxonomy and/or function from whole genome sequencing or 16S amplicon sequences. Both of these approaches are limited, however, by read length, among other technical and biological factors. A nanopore-based sequencing platform, MinION™, produces reads that are ≥1 × 104 bp in length, potentially providing for more precise assignment, thereby alleviating some of the limitations inherent in determining metagenome composition from short reads. We tested the ability of sequence data produced by MinION (R7.3 flow cells) to correctly assign taxonomy in single bacterial species runs and in three types of low-complexity synthetic communities: a mixture of DNA using equal mass from four species, a community with one relatively rare (1%) and three abundant (33% each) components, and a mixture of genomic DNA from 20 bacterial strains of staggered representation. Taxonomic composition of the low-complexity communities was assessed by analyzing the MinION sequence data with three different bioinformatic approaches: Kraken, MG-RAST, and One Codex. Results: Long read sequences generated from libraries prepared from single strains using the version 5 kit and chemistry, run on the original MinION device, yielded as few as 224 to as many as 3497 bidirectional high-quality (2D) reads with an average overall study length of 6000 bp. For the single-strain analyses, assignment of reads to the correct genus by different methods ranged from 53.1% to 99.5%, assignment to the correct species ranged from 23.9% to 99.5%, and the majority of misassigned reads were to closely related organisms. A synthetic metagenome sequenced with the same setup yielded 714 high quality 2D reads of approximately 5500 bp that were up to 98% correctly assigned to the species level. Synthetic metagenome MinION libraries generated using version 6 kit and chemistry yielded from 899 to 3497 2D reads with lengths averaging 5700 bp with up to 98% assignment accuracy at the species level. The observed community proportions for “equal” and “rare” synthetic libraries were close to the known proportions, deviating from 0.1% to 10% across all tests. For a 20-species mock community with staggered contributions, a sequencing run detected all but 3 species (each included at <0.05% of DNA in the total mixture), 91% of reads were assigned to the correct species, 93% of reads were assigned to the correct genus, and >99% of reads were assigned to the correct family. Conclusions: At the current level of output and sequence quality (just under 4 × 103 2D reads for a synthetic metagenome), MinION sequencing followed by Kraken or One Codex analysis has the potential to provide rapid and accurate metagenomic analysis where the consortium is comprised of a limited number of taxa. Important considerations noted in this study included: high sensitivity of the MinION platform to the quality of input DNA, high variability of sequencing results across libraries and flow cells, and relatively small numbers of 2D reads per analysis limit. Together, these limited detection of very rare components of the microbial consortia, and would likely limit the utility of MinION for the sequencing of high-complexity metagenomic communities where thousands of taxa are expected. Furthermore, the limitations of the currently available data analysis tools suggest there is considerable room for improvement in the analytical approaches for the characterization of microbial communities using long reads. Nevertheless, the fact that the accurate taxonomic assignment of high-quality reads generated by MinION is approaching 99.5% and, in most cases, the inferred community structure mirrors the known proportions of a synthetic mixture warrants further exploration of practical application to environmental metagenomics as the platform continues to develop and improve. With further improvement in sequence throughput and error rate reduction, this platform shows great promise for precise real-time analysis of the composition and structure of more complex microbial communities.
Abstract Synthetic biology offers the opportunity to build solutions for improved capture and conversion of carbon dioxide (CO 2 ) that outcompete those evolved by nature. Here we demonstrate the design and construction of a new-to-nature CO 2 -fixation pathway, the reductive tricarboxylic acid branch/4-hydroxybutyryl-CoA/ethylmalonyl-CoA/acetyl-CoA (THETA) cycle. The THETA cycle encompasses 17 enzymes from 9 organisms and revolves around two of the most efficient CO 2 -fixing enzymes described in nature, crotonyl-CoA carboxylase/reductase and phosphoenolpyruvate carboxylase. Here using rational and machine learning-guided optimization approaches, we improved the yield of the cycle by two orders of magnitude and demonstrated the formation of different biochemical building blocks directly from CO 2 . Furthermore, we separated the THETA cycle into three modules that we successfully implemented in vivo by exploiting the natural plasticity of Escherichia coli metabolism. Growth-based selection and/or 13 C-labelling confirmed the activity of three different modules, demonstrating the first step towards realizing highly orthogonal and complex CO 2 -fixation pathways in the background of living cells.
A critical aspect of evolution is the layer of developmental physiology that operates between the genotype and the anatomical phenotype. While much work has addressed the evolution of developmental mechanisms and the evolvability of specific genetic architectures with emergent complexity, one aspect has not been sufficiently explored: the implications of morphogenetic problem-solving competencies for the evolutionary process itself. The cells that evolution works with are not passive components: rather, they have numerous capabilities for behavior because they derive from ancestral unicellular organisms with rich repertoires. In multicellular organisms, these capabilities must be tamed, and can be exploited, by the evolutionary process. Specifically, biological structures have a multiscale competency architecture where cells, tissues, and organs exhibit regulative plasticity-the ability to adjust to perturbations such as external injury or internal modifications and still accomplish specific adaptive tasks across metabolic, transcriptional, physiological, and anatomical problem spaces. Here, I review examples illustrating how physiological circuits guiding cellular collective behavior impart computational properties to the agential material that serves as substrate for the evolutionary process. I then explore the ways in which the collective intelligence of cells during morphogenesis affect evolution, providing a new perspective on the evolutionary search process. This key feature of the physiological software of life helps explain the remarkable speed and robustness of biological evolution, and sheds new light on the relationship between genomes and functional anatomical phenotypes.
Ion transport in biological and synthetic nanochannels is characterized by phenomena such as ion current fluctuations and rectification. Recently, it has been demonstrated that nanofabricated synthetic pores can mimic transport properties of biological ion channels [P. Yu. Apel, Nucl. Instrum Methods Phys. Res. B 184, 337 (2001); Z. Siwy, Europhys. Lett. 60, 349 (2002)]. Here, the ion current rectification is studied within a reduced one-dimensional (1D) Poisson-Nernst-Planck (PNP) model of synthetic nanopores. A conical channel of a few nm to a few hundred nm in diameter, and of a few mum long is considered in the limit where the channel length considerably exceeds the Debye screening length. The rigid channel wall is assumed to be weakly charged. A one-dimensional reduction of the three-dimensional problem in terms of corresponding entropic effects is put forward. The ion transport is described by the nonequilibrium steady-state solution of the 1D Poisson-Nernst-Planck system within a singular perturbation treatment. An analytic formula for the approximate rectification current in the lowest order perturbation theory is derived. A detailed comparison between numerical results and the singular perturbation theory is presented. The crucial importance of the asymmetry in the potential jumps at the pore ends on the rectification effect is demonstrated. This so constructed 1D theory is shown to describe well the experimental data in the regime of small-to-moderate electric currents.
This paper reports on a co-laborative laboratory ethnography in a molecular biology laboratory conducting research on environmental epigenetics. It focuses on a single study concerned with the material implications of social differentiation. The analysis briefly raises biopolitical concerns. Its main concern lies with an understanding of the human body as local in its working infrastructure or “inner laboratory”, an understanding that emerges from the co-laborative inquiry between biologists and anthropologist. This co-laborative mode of inquiry raises productive tensions within biology as to the universal or local nature of human nature and within anthropology as to the status of human biology within social theory. The paper cannot resolve this tension. Rather it explores it as an epistemic object in the context of interdisciplinarity, ontography and co-laboration. In concluding, it specifies co-laboration as temporary, non-teleological joint epistemic work aimed at producing new kinds of reflexivity.
Although efficient methods exist to assemble synthetic oligonucleotides into genes and genomes, these suffer from the presence of 1-3 random errors/kb of DNA. Here, we introduce a new method termed consensus shuffling and demonstrate its use to significantly reduce random errors in synthetic DNA. In this method, errors are revealed as mismatches by re-hybridization of the population. The DNA is fragmented, and mismatched fragments are removed upon binding to an immobilized mismatch binding protein (MutS). PCR assembly of the remaining fragments yields a new population of full-length sequences enriched for the consensus sequence of the input population. We show that two iterations of consensus shuffling improved a population of synthetic green fluorescent protein (GFPuv) clones from approximately 60 to >90% fluorescent, and decreased errors 3.5- to 4.3-fold to final values of approximately 1 error per 3500 bp. In addition, two iterations of consensus shuffling corrected a population of GFPuv clones where all members were non-functional, to a population where 82% of clones were fluorescent. Consensus shuffling should facilitate the rapid and accurate synthesis of long DNA sequences.
Mathematical models of biological reactions at the system-level lead to a set of ordinary differential equations with many unknown parameters that need to be inferred using relatively few experimental measurements. Having a reliable and robust algorithm for parameter inference and prediction of the hidden dynamics has been one of the core subjects in systems biology, and is the focus of this study. We have developed a new systems-biology-informed deep learning algorithm that incorporates the system of ordinary differential equations into the neural networks. Enforcing these equations effectively adds constraints to the optimization procedure that manifests itself as an imposed structure on the observational data. Using few scattered and noisy measurements, we are able to infer the dynamics of unobserved species, external forcing, and the unknown model parameters. We have successfully tested the algorithm for three different benchmark problems.
// Hae Kyung Lee 1 , Susan Finniss 1 , Simona Cazacu 1 , Efrat Bucris 2 , Amotz Ziv-Av 2 , Cunli Xiang 1 , Kevin Bobbitt 3 , Sandra A. Rempel 4 , Laura Hasselbach 5 , Tom Mikkelsen 5 Shimon Slavin 6 and Chaya Brodie 1,2 1 Davidson Laboratory of Cell Signaling and Tumorigenesis, Hermelin Brain Tumor Center, Department of Neurosurgery, Henry Ford Hospital, Detroit, MI, 2 Everard and Mina Goodman Faculty of Life Sciences, Bar-Ilan University, Ramat-Gan, Israel, 3 Department of Public Health Sciences, 4 Barbara Jane Levy Laboratory of Molecular Neuro-Oncology, 5 Eugene & Marcia Applebaum Laboratory of Invasion & Molecular Therapeutics and 6 The international center for Cell Therapy and Cancer Immunotherapy (CTCI), Tel Aviv, Israel Correspondence: Chaya Brodie, email: // Keywords : miRNA delivery, mesenchymal stem cells, glioma, exosomes Received : February 12, 2013 Accepted : February 27, 2013 Published : February 28, 2013 Abstract MicroRNAs (miRNAs) have emerged as potential cancer therapeutics; however, their clinical use is hindered by lack of effective delivery mechanisms to tumor sites. Mesenchymal stem cells (MSCs) have been shown to migrate to experimental glioma and to exert anti-tumor effects by delivering cytotoxic compounds. Here, we examined the ability of MSCs derived from bone marrow, adipose tissue, placenta and umbilical cord to deliver synthetic miRNA mimics to glioma cells and glioma stem cells (GSCs). We examined the delivery of miR-124 and miR-145 mimics as glioma cells and GSCs express very low levels of these miRNAs. Using fluorescently labeled miRNA mimics and in situ hybridization, we demonstrated that all the MSCs examined delivered miR-124 and miR-145 mimics to co-cultured glioma cells and GSCs via gap junction–dependent and independent processes. The delivered miR-124 and miR-145 mimics significantly decreased the luciferase activity of their respected reporter target genes, SCP-1 and Sox2, and decreased the migration of glioma cells and the self-renewal of GSCs. Moreover, MSCs delivered Cy3-miR-124 mimic to glioma xenografts when administered intracranially. These results suggest that MSCs can deliver synthetic exogenous miRNA mimics to glioma cells and GSCs and may provide an efficient route of therapeutic miRNA delivery in vivo .
The selective application of insecticides is one of the cornerstones of integrated pest management (IPM) and management strategies for pest resistance to insecticides. The present work provides a comprehensive overview of the traditional and new methods for the application of gas, liquid, gel, and solid physical insecticide formulations to control stored-product and food industry urban pests from the taxa Acarina, Blattodea, Coleoptera, Diptera, Hymenoptera, Lepidoptera, Psocoptera, and Zygentoma. Various definitions and concepts historically and currently used for various pesticide application formulations and methods are also described. This review demonstrates that new technological advances have sparked renewed research interest in the optimization of conventional methods such as insecticide aerosols, sprays, fumigants, and inert gases. Insect growth regulators/disruptors (IGRs/IGDs) are increasingly employed in baits, aerosols, residual treatments, and as spray-residual protectants for long-term stored-grain protection. Insecticide-impregnated hypoxic multilayer bags have been proven to be one of the most promising low-cost and safe methods for hermetic grain storage in developing countries. Insecticide-impregnated netting and food baits were originally developed for the control of urban/medical pests and have been recognized as an innovative technology for the protection of stored commodities. New biodegradable acaricide gel coatings and nets have been suggested for the protection of ham meat. Tablets and satchels represent a new approach for the application of botanicals. Many emerging technologies can be found in the form of impregnated protective packaging (insect growth regulators/disruptors (IGRs/IGDs), natural repellents), pheromone-based attracticides, electrostatic dust or sprays, nanoparticles, edible artificial sweeteners, hydrogels, inert baits with synthetic attractants, biodegradable encapsulations of active ingredients, and cyanogenic protective grain coatings. Smart pest control technologies based on RNA-based gene silencing compounds incorporated into food baits stand at the forefront of current strategic research. Inert gases and dust (diatomaceous earth) are positive examples of alternatives to synthetic pesticide products, for which methods of application and their integration with other methods have been proposed and implemented in practice. Although many promising laboratory studies have been conducted on the biological activity of natural botanical insecticides, published studies demonstrating their effective industrial field usage in grain stores and food production facilities are scarce. This review shows that the current problems associated with the application of some natural botanical insecticides (e.g., sorption, stability, field efficacy, and smell) to some extent echo problems that were frequently encountered and addressed almost 100 years ago during the transition from ancient to modern classical chemical pest control methods.
We present a powerful experimental-computational technology for inferring network models that predict the response of cells to perturbations, and that may be useful in the design of combinatorial therapy against cancer. The experiments are systematic series of perturbations of cancer cell lines by targeted drugs, singly or in combination. The response to perturbation is quantified in terms of relative changes in the measured levels of proteins, phospho-proteins and cellular phenotypes such as viability. Computational network models are derived de novo, i.e., without prior knowledge of signaling pathways, and are based on simple non-linear differential equations. The prohibitively large solution space of all possible network models is explored efficiently using a probabilistic algorithm, Belief Propagation (BP), which is three orders of magnitude faster than standard Monte Carlo methods. Explicit executable models are derived for a set of perturbation experiments in SKMEL-133 melanoma cell lines, which are resistant to the therapeutically important inhibitor of RAF kinase. The resulting network models reproduce and extend known pathway biology. They empower potential discoveries of new molecular interactions and predict efficacious novel drug perturbations, such as the inhibition of PLK1, which is verified experimentally. This technology is suitable for application to larger systems in diverse areas of molecular biology.
The pandemic of the novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has been posing great threats to the world in many aspects. Effective therapeutic and preventive approaches including drugs and vaccines are still unavailable although they are in development. Comprehensive understandings on the life logic of SARS-CoV-2 and the interaction of the virus with hosts are fundamentally important in the fight against SARS-CoV-2. In this review, we briefly summarized the current advances in SARS-CoV-2 research, including the epidemic situation and epidemiological characteristics of the caused disease COVID-19. We further discussed the biology of SARS-CoV-2, including the origin, evolution, and receptor recognition mechanism of SARS-CoV-2. And particularly, we introduced the protein structures of SARS-CoV-2 and structure-based therapeutics development including antibodies, antiviral compounds, and vaccines, and indicated the limitations and perspectives of SARS-CoV-2 research. We wish the information provided by this review may be helpful to the global battle against SARS-CoV-2 infection.