Sequencing enabling design and learning in synthetic biology

The ability to read and quantify nucleic acids such as DNA and RNA using sequencing technologies has revolutionized our understanding of life. With the emergence of synthetic biology, these tools are now being put to work in new ways — enabling de novo biological design. Here, we show how sequencing is supporting the creation of a new wave of biological parts and systems, as well as providing the vast data sets needed for the machine learning of design rules for predictive bioengineering. However, we believe this is only the tip of the iceberg and end by providing an outlook on recent advances that will likely broaden the role of sequencing in synthetic biology and its deployment in real-world environments.     

Potentials of single‐cell biology in identification and validation of disease biomarkers

Single‐cell biology is considered a new approach to identify and validate disease‐specific biomarkers. However, the concern raised by clinicians is how to apply single‐cell measurements for clinical practice, translate the message of single‐cell systems biology into clinical phenotype or explain alterations of single‐cell gene sequencing and function in patient response to therapies. This study is to address the importance and necessity of single‐cell gene sequencing in the identification and development of disease‐specific biomarkers, the definition and significance of single‐cell biology and single‐cell systems biology in the understanding of single‐cell full picture, the development and establishment of whole‐cell models in the validation of targeted biological function and the figure and meaning of single‐molecule imaging in single cell to trace intra‐single‐cell molecule expression, signal, interaction and location. We headline the important role of single‐cell biology in the discovery and development of disease‐specific biomarkers with a special emphasis on understanding single‐cell biological functions, e.g. mechanical phenotypes, single‐cell biology, heterogeneity and organization of genome function. We have reason to believe that such multi‐dimensional, multi‐layer, multi‐crossing and stereoscopic single‐cell biology definitely benefits the discovery and development of disease‐specific biomarkers.     

Interview with Sydney Brenner

The following text is an edited version of a recent interview with Sydney Brenner who has been at the forefront of many developments in molecular biology since the 1950s. It provides a participant’s view on current issues in the history and epistemology of molecular biology. The main issue raised by Brenner regards the relation of molecular biology to the new field of systems biology. Brenner defends the original programme of molecular biology—the molecular explanation of living processes—that in his view has yet to be completed. The programme of systems biology in contrast he views as either trivial or as not achievable since it purports to deal with inverse problems that are impossible to solve in complex living systems. Other issues covered in the conversation concern the impact of the human genome sequencing project, the commercial turn in molecular biology and the contested disciplinary status of the science.     

Application of Bayesian networks on large-scale biological data

The investigation of the interplay between genes, proteins, metabolites and diseases plays a central role in molecular and cellular biology. Whole genome sequencing has made it possible to examine the behavior of all the genes in a genome by high-throughput experimental techniques and to pinpoint molecular interactions on a genome-wide scale, which form the backbone of systems biology. In particular, Bayesian network (BN) is a powerful tool for the ab-initial identification of causal and non-causal relationships between biological factors directly from experimental data. However, scalability is a crucial issue when we try to apply BNs to infer such interactions. In this paper, we not only introduce the Bayesian network formalism and its applications in systems biology, but also review recent technical developments for scaling up or speeding up the structural learning of BNs, which is important for the discovery of causal knowledge from large-scale biological datasets. Specifically, we highlight the basic idea, relative pros and cons of each technique and discuss possible ways to combine different algorithms towards making BN learning more accurate and much faster.     

Stages in the development of a model organism as a platform for mechanistic models in developmental biology: Zebrafish, 1970-2000

Model organisms became an indispensable part of experimental systems in molecular developmental and cell biology, constructed to investigate physiological and pathological processes. They are thought to play a crucial role for the elucidation of gene function, complementing the sequencing of the genomes of humans and other organisms. Accordingly, historians and philosophers paid considerable attention to various issues concerning this aspect of experimental biology. With respect to the representational features of model organisms, that is, their status as models, the main focus was on generalization of phenomena investigated in such experimental systems. Model organisms have been said to be models for other organisms or a higher taxon. This, however, presupposes a representation of the phenomenon in question. I will argue that prior to generalization, model organisms allow researchers to built generative material models of phenomena - structures, processes or the mechanisms that explain them - through their integration in experimental set-ups that carve out the phenomena from the whole organism and thus represent them. I will use the history of zebrafish biology to show how model organism systems, from around 1970 on, were developed to construct material models of molecular mechanisms explaining developmental or physiological processes.     

The International Conference on Intelligent Biology and Medicine (ICIBM) 2016: putting systems biology to work

Between December 8–10, 2016, the International Conference on Intelligent Biology and Medicine (ICIBM 2016) was held in Houston, Texas, USA. The conference included eight scientific sessions, four tutorials, one poster session, four highlighted talks and four keynotes that covered topics in 3D genome structure analysis and visualization, next generation sequencing analysis, computational drug discovery, medical informatics, cancer genomics and systems biology. Systems biology has been a main theme in ICIBM 2016, with exciting advances were presented in many areas of systems biology. Here, we selected seven high quality papers to be published in BMC Systems Biology.     

Using flow cytometry to quantify microbial heterogeneity

Flow cytometry is a powerful technique for the study of single cells, and thus it is of particular utility in the study of heterogeneity in microbial populations. This review seeks to highlight the role of flow cytometric analyses in studies of microbial heterogeneity, drawing wherever possible on recently published research articles. Whilst microbial heterogeneity is well documented in both natural and laboratory environments, the underlying causes are less well understood. Possible sources for the heterogeneity that is observed in microbial systems are discussed, together with the flow cytometric tools that aid its study. The role of flow cytometry in molecular biology is discussed with reference to gene reporter systems, which enable heterogeneity of gene expression to be monitored. With the recent sequencing of a variety of microbial genomes, it is anticipated that flow cytometry will have an increasing role to play in studying the effects of gene expression and mutation on heterogeneity, and in resolving the interactions of genetics and physiology.     

Functional proteomics to exploit genome sequences.

The sequencing of various genomes has inaugurated a new stage in the understanding of normal and pathological cell function through the analysis of the role of proteins. Proteins, after all, that intervene in the different molecular mechanisms of life, during growth, reproduction, and in the interaction between cells, thus making it possible to describe the biology of integrated systems. In this article, we briefly describe the various stages in the progression of our knowledge, from the genome to the "functional" proteome. Emphasis is placed on a global approach to the protein-protein interactions used to describe the cellular "interactome".     

Structures in systems biology

Oil and water do not normally mix, and apparently structural biology and systems biology look like two different universes. It can be argued that structural biology could play a very important role in systems biology. Although at the final stage of understanding a signal transduction pathway, a cell, an organ or a living system, structures could be obviated, we need them to be able to reach that stage. Structures of macromolecules, especially molecular machines, could provide quantitative parameters, help to elucidate functional networks or enable rational designed perturbation experiments for reverse engineering. The role of structural biology in systems biology should be to provide enough understanding so that macromolecules can be translated into dots or even into equations devoid of atoms.     

The top five "game changers" in vaccinology: toward rational and directed vaccine development

Despite the tremendous success of the classical "isolate, inactivate, and inject" approach to vaccine development, new breakthroughs in vaccine research are increasingly reliant on novel approaches that incorporate cutting edge technology and advances in innate and adaptive immunology, microbiology, virology, pathogen biology, genetics, bioinformatics, and many other disciplines in order to: (1) deepen our understanding of the key biological processes that lead to protective immunity, (2) observe vaccine responses on a global, systems level, and (3) directly apply the new knowledge gained to the development of next-generation vaccines with improved safety profiles, enhanced efficacy, and even targeted utility in select populations. Here we highlight five key components foundational to vaccinomics efforts: applied immunogenomics, next generation sequencing and other cutting-edge "omics" technologies, advanced bioinformatics and analysis techniques, and finally, systems biology applied to immune profiling and vaccine responses. We believe these "game changers" will play a critical role in moving us toward the rational and directed development of new vaccines in the 21st century.     

Solid-phase chemical tools for glycobiology

Techniques involving solid supports have played crucial roles in the development of genomics, proteomics, and in molecular biology in general. Similarly, methods for immobilization or attachment to surfaces and resins have become ubiquitous in sequencing, synthesis, analysis, and screening of oligonucleotides, peptides, and proteins. However, solid-phase tools have been employed to a much lesser extent in glycobiology and glycomics. This review provides a comprehensive overview of solid-phase chemical tools for glycobiology including methodologies and applications. We provide a broad perspective of different approaches, including some well-established ones, such as immobilization in microtiter plates and to cross-linked polymers. Emerging areas such as glycan microarrays and glycan sequencing, quantum dots, and gold nanoparticles for nanobioscience applications are also discussed. The applications reviewed here include enzymology, immunology, elucidation of biosynthesis, and systems biology, as well as first steps toward solid-supported sequencing. From these methods and applications emerge a general vision for the use of solid-phase chemical tools in glycobiology.     

The International Conference on Intelligent Biology and Medicine (ICIBM) 2018: systems biology on diverse data types

Between June 10–12, 2018, the International Conference on Intelligent Biology and Medicine (ICIBM 2018) was held in Los Angeles, California, USA. The conference included 11 scientific sessions, four tutorials, one poster session, four keynote talks and four eminent scholar talks that covered a wide range of topics in 3D genome structure analysis and visualization, next generation sequencing analysis, computational drug discovery, medical informatics, cancer genomics and systems biology. Systems biology has been a main theme in ICIBM 2018, with exciting advances presented in many areas of systems biology, covering various different data types such as gene regulation, circular RNAs expression, single-cell RNA-Seq, inter-chromosomal interactions, metabolomics, proteomics and phosphoproteomics. Here, we describe ten high quality papers to be published in BMC Systems Biology.     

Whole exome sequencing of a Saudi family and systems biology analysis identifies CPED1 as a putative causative gene to Celiac Disease

Celiac disease (CD) is a gastrointestinal disorder whose genetic basis is not fully understood. Therefore, we studied a Saudi family with two CD affected siblings to discover the causal genetic defect. Through whole exome sequencing (WES), we identified that both siblings have inherited an extremely rare and deleterious CPED1 genetic variant (c.241 A > G; p.Thr81Ala) segregating as autosomal recessive mutation, suggesting its putative causal role in the CD. Saudi population specific minor allele frequency (MAF) analysis has confirmed its extremely rare prevalence in homozygous condition (MAF is 0.0004). The Sanger sequencing analysis confirmed the absence of this homozygous variant in 100 sporadic Saudi CD cases. Genotype-Tissue Expression (GTEx) data has revealed that CPED1 is abundantly expressed in gastrointestinal mucosa. By using a combination of systems biology approaches like protein 3D modeling, stability analysis and nucleotide sequence conservation analysis, we have further established that this variant is deleterious to the structural and functional aspects of CPED1 protein. To the best of our knowledge, this variant has not been previously reported in CD or any other gastrointestinal disease. The cell culture and animal model studies could provide further insight into the exact role of CPED1 p.Thr81Ala variant in the pathophysiology of CD. In conclusion, by using WES and systems biology analysis, present study for the first-time reports CPED1 as a potential causative gene for CD in a Saudi family with potential implications to both disease diagnosis and genetic counseling.     

An expanded role for microbial physiology in metabolic engineering and functional genomics: moving towards systems biology

Microbial physiology has traditionally played a very important role in both fundamental research and in industrial applications of microorganisms. The classical approach in microbial physiology has been to analyze the role of individual components (genes or proteins) in the overall cell function. With the progress in molecular biology it has become possible to optimize industrial fermentations through introduction of directed genetic modification - an approach referred to as metabolic engineering. Furthermore, as a consequence of large sequencing programs the complete genomic sequence has become available for an increasing number of microorganisms. This has resulted in substantial research efforts in assigning function to all identified open reading frames - referred to as functional genomics. In both metabolic engineering and functional genomics there is a trend towards application of a macroscopic view on cell function, and this leads to an expanded role of the classical approach applied in microbial physiology. With the increased understanding of the molecular mechanisms it is envisaged that in the future it will be possible to describe the interaction between all the components in the system (the cell), also at the quantitative level, and this is the goal of systems biology. Clearly this will have a significant impact on microbial physiology as well as on metabolic engineering.