Defining systems biology: a brief overview of the term and field

Aligning with the 3Rs: alternative models for research into muscle development and inherited myopathies

Inherited and acquired muscle diseases are an important cause of morbidity and mortality in human medical and veterinary patients. Researchers use models to study skeletal muscle development and pathology, improve our understanding of disease pathogenesis and explore new treatment options. Experiments on laboratory animals, including murine and canine models, have led to huge advances in congenital myopathy and muscular dystrophy research that have translated into clinical treatment trials in human patients with these debilitating and often fatal conditions. Whilst animal experimentation has enabled many significant and impactful discoveries that otherwise may not have been possible, we have an ethical and moral, and in many countries also a legal, obligation to consider alternatives. This review discusses the models available as alternatives to mammals for muscle development, biology and disease research with a focus on inherited myopathies. Cell culture models can be used to replace animals for some applications: traditional monolayer cultures (for example, using the immortalised C2C12 cell line) are accessible, tractable and inexpensive but developmentally limited to immature myotube stages; more recently, developments in tissue engineering have led to three-dimensional cultures with improved differentiation capabilities. Advances in computer modelling and an improved understanding of pathogenetic mechanisms are likely to herald new models and opportunities for replacement. Where this is not possible, a 3Rs approach advocates partial replacement with the use of less sentient animals (including invertebrates (such as worms Caenorhabditis elegans and fruit flies Drosophila melanogaster) and embryonic stages of small vertebrates such as the zebrafish Danio rerio) alongside refinement of experimental design and improved research practices to reduce the numbers of animals used and the severity of their experience. An understanding of the advantages and disadvantages of potential models is essential for researchers to determine which can best facilitate answering a specific scientific question. Applying 3Rs principles to research not only improves animal welfare but generates high-quality, reproducible and reliable data with translational relevance to human and animal patients.

UNaProd: A Universal Natural Product Database for Materia Medica of Iranian Traditional Medicine

BACKGROUND

Iranian traditional medicine (ITM) is a holistic medical system that uses a wide range of medicinal substances to treat disease. Reorganization and standardization of the data on ITM concepts is a necessity for optimal use of this rich source. In an initial step towards this goal, we created a database of ITM materia medica. Main Body. Primarily based on Makhzan al-Advieh, which is the most recent encyclopedia of materia medica in ITM with the largest number of monographs, a database of natural medicinal substances was created using both text mining methods and manual editing. UNaProd, a Universal Natural Product database for materia medica of ITM, is currently host to 2696 monographs, from herbal to animal to mineral compounds in 16 diverse attributes such as origin and scientific name. Currently, systems biology, and more precisely systems medicine and pharmacology, can be an aid in providing rationalizations for many traditional medicines and elucidating a great deal of knowledge they can offer to guide future research in medicine.

CONCLUSIONS

A database of materia medica is a stepping stone in creating a systems pharmacology platform of ITM that encompasses the relationships between the drugs, their targets, and diseases. UNaProd is hyperlinked to IrGO and CMAUP databases for Mizaj and molecular features, respectively, and it is freely available at http://jafarilab.com/unaprod/.

Understanding the high L-valine production in Corynebacterium glutamicum VWB-1 using transcriptomics and proteomics

Toward the elucidation of the advanced mechanism of l-valine production by Corynebacterium glutamicum, a highly developed industrial strain VWB-1 was analyzed, employing the combination of transcriptomics and proteomics methods. The transcriptional level of 1155 genes and expression abundance of 96 proteins were changed significantly by the transcriptome and proteome comparison of VWB-1 and ATCC 13869. It was indicated that the key genes involved in the biosynthesis of l-valine, ilvBN, ilvC, ilvD, ilvE were up-regulated in VWB-1, which together made prominent contributions in improving the carbon flow towards l-valine. The l-leucine and l-isoleucine synthesis ability were weakened according to the down-regulation of leuB and ilvA. The up-regulation of the branched chain amino acid transporter genes brnFE promoted the l-valine secretion capability of VWB-1. The NADPH and ATP generation ability of VWB-1 were strengthened through the up-regulation of the genes involved in phosphate pentose pathway and TCA pathway. Pyruvate accumulation was achieved through the weakening of the l-lactate, acetate and l-alanine pathways. The up-regulation of the genes coding for elongation factors and ribosomal proteins were beneficial for l-valine synthesis in C. glutamicum. All information acquired were useful for the genome breeding of better industrial l-valine producing strains.

Systems Biology-Driven Hypotheses Tested In Vivo: The Need to Advancing Molecular Imaging Tools

Processing and interpretation of biological images may provide invaluable insights on complex, living systems because images capture the overall dynamics as a "whole." Therefore, "extraction" of key, quantitative morphological parameters could be, at least in principle, helpful in building a reliable systems biology approach in understanding living objects. Molecular imaging tools for system biology models have attained widespread usage in modern experimental laboratories. Here, we provide an overview on advances in the computational technology and different instrumentations focused on molecular image processing and analysis. Quantitative data analysis through various open source software and algorithmic protocols will provide a novel approach for modeling the experimental research program. Besides this, we also highlight the predictable future trends regarding methods for automatically analyzing biological data. Such tools will be very useful to understand the detailed biological and mathematical expressions under in-silico system biology processes with modeling properties.

Recent Progress on Systems and Synthetic Biology Approaches to Engineer Fungi As Microbial Cell Factories

Filamentous fungi are remarkable organisms naturally specialized in deconstructing plant biomass and this feature has a tremendous potential for biofuel production from renewable sources. The past decades have been marked by a remarkable progress in the genetic engineering of fungi to generate industry-compatible strains needed for some biotech applications. In this sense, progress in this field has been marked by the utilization of high-throughput techniques to gain deep understanding of the molecular machinery controlling the physiology of these organisms, starting thus the Systems Biology era of fungi. Additionally, genetic engineering has been extensively applied to modify wellcharacterized promoters in order to construct new expression systems with enhanced performance under the conditions of interest. In this review, we discuss some aspects related to significant progress in the understating and engineering of fungi for biotechnological applications, with special focus on the construction of synthetic promoters and circuits in organisms relevant for industry. Different engineering approaches are shown, and their potential and limitations for the construction of complex synthetic circuits in these organisms are examined. Finally, we discuss the impact of engineered promoter architecture in the single-cell behavior of the system, an often-neglected relationship with a tremendous impact in the final performance of the process of interest. We expect to provide here some new directions to drive future research directed to the construction of high-performance, engineered fungal strains working as microbial cell factories.

Identifying a biomarker network for corticosteroid resistance in asthma from bronchoalveolar lavage samples

Corticosteroid resistance (CR) is a major barrier to the effective treatment of severe asthma. Hence, a better understanding of the molecular mechanisms involved in this condition is a priority. Network analysis is an emerging strategy to explore this complex heterogeneous disorder at system level to identify a small own network for CR in asthma. Gene expression profile of GSE7368 from bronchoalveolar lavage (BAL) of CR in subjects with asthma was downloaded from the gene expression omnibus (GEO) database and compared to BAL of corticosteroid-sensitive (CS) patients. DEGs were identified by the Limma package in R language. In addition, DEGs were mapped to STRING to acquire protein-protein interaction (PPI) pairs. Topological properties of PPI network were calculated by Centiscape, ClusterOne and BINGO. Subsequently, text-mining tools were applied to design one own cell signalling for CR in asthma. Thirty-five PPI networks were obtained; including a major network consisted of 370 nodes, connected by 777 edges. After topological analysis, a minor PPI network composed by 48 nodes was indentified, which is composed by most relevant nodes of major PPI network. In this subnetwork, several receptors (EGFR, EGR1, ESR2, PGR), transcription factors (MYC, JAK), cytokines (IL8, IL6, IL1B), one chemokine (CXCL1), one kinase (SRC) and one cyclooxygenase (PTGS2) were described to be associated with inflammatory environment and steroid resistance in asthma. We suggest a biomarker network composed by 48 nodes that could be potentially explored with diagnostic or therapeutic use.

An Overview of Biofield Devices

Advances in biophysics, biology, functional genomics, neuroscience, psychology, psychoneuroimmunology, and other fields suggest the existence of a subtle system of "biofield" interactions that organize biological processes from the subatomic, atomic, molecular, cellular, and organismic to the interpersonal and cosmic levels. Biofield interactions may bring about regulation of biochemical, cellular, and neurological processes through means related to electromagnetism, quantum fields, and perhaps other means of modulating biological activity and information flow. The biofield paradigm, in contrast to a reductionist, chemistry-centered viewpoint, emphasizes the informational content of biological processes; biofield interactions are thought to operate in part via low-energy or "subtle" processes such as weak, nonthermal electromagnetic fields (EMFs) or processes potentially related to consciousness and nonlocality. Biofield interactions may also operate through or be reflected in more well-understood informational processes found in electroencephalographic (EEG) and electrocardiographic (ECG) data. Recent advances have led to the development of a wide variety of therapeutic and diagnostic biofield devices, defined as physical instruments best understood from the viewpoint of a biofield paradigm. Here, we provide a broad overview of biofield devices, with emphasis on those devices for which solid, peer-reviewed evidence exists. A subset of these devices, such as those based upon EEG- and ECG-based heart rate variability, function via mechanisms that are well understood and are widely employed in clinical settings. Other device modalities, such a gas discharge visualization and biophoton emission, appear to operate through incompletely understood mechanisms and have unclear clinical significance. Device modes of operation include EMF-light, EMF-heat, EMF-nonthermal, electrical current, vibration and sound, physical and mechanical, intentionality and nonlocality, gas and plasma, and other (mode of operation not well-understood). Methodological issues in device development and interfaces for future interdisciplinary research are discussed. Devices play prominent cultural and scientific roles in our society, and it is likely that device technologies will be one of the most influential access points for the furthering of biofield research and the dissemination of biofield concepts. This developing field of study presents new areas of research that have many important implications for both basic science and clinical medicine.

Mathematical modelling of metabolic regulation in aging

The underlying cellular mechanisms that characterize aging are complex and multifaceted. However, it is emerging that aging could be regulated by two distinct metabolic hubs. These hubs are the pathway defined by the mammalian target of rapamycin (mTOR) and that defined by the NAD+-dependent deacetylase enzyme, SIRT1. Recent experimental evidence suggests that there is crosstalk between these two important pathways; however, the mechanisms underpinning their interaction(s) remains poorly understood. In this review, we propose using computational modelling in tandem with experimentation to delineate the mechanism(s). We briefly discuss the main modelling frameworks that could be used to disentangle this relationship and present a reduced reaction pathway that could be modelled. We conclude by outlining the limitations of computational modelling and by discussing opportunities for future progress in this area.

Simultaneous Quantification of Viral Antigen Expression Kinetics Using Data-Independent (DIA) Mass Spectrometry

The generation of antigen-specific reagents is a significant bottleneck in the study of complex pathogens that express many hundreds to thousands of different proteins or to emerging or new strains of viruses that display potential pandemic qualities and therefore require rapid investigation. In these instances the development of antibodies for example can be prohibitively expensive to cover the full pathogen proteome, or the lead time may be unacceptably long in urgent cases where new highly pathogenic viral strains may emerge. Because genomic information on such pathogens can be rapidly acquired this opens up avenues using mass spectrometric approaches to study pathogen antigen expression, host responses and for screening the utility of therapeutics. In particular, data-independent acquisition (DIA) modalities on high-resolution mass spectrometers generate spectral information on all components of a complex sample providing depth of coverage hitherto only seen in genomic deep sequencing. The spectral information generated by DIA can be iteratively interrogated for potentially any protein of interest providing both evidence of protein expression and quantitation. Here we apply a solely DIA mass spectrometry based methodology to profile the viral antigen expression in cells infected with vaccinia virus up to 9 h post infection without the need for antigen specific antibodies or other reagents. We demonstrate deep coverage of the vaccinia virus proteome using a SWATH-MS acquisition approach, extracting quantitative kinetics of 100 virus proteins within a single experiment. The results highlight the complexity of vaccinia protein expression, complementing what is known at the transcriptomic level, and provide a valuable resource and technique for future studies of viral infection and replication kinetics. Furthermore, they highlight the utility of DIA and mass spectrometry in the dissection of host-pathogen interactions.

Systems and synthetic biology approaches to alter plant cell walls and reduce biomass recalcitrance

Fine-tuning plant cell wall properties to render plant biomass more amenable to biofuel conversion is a colossal challenge. A deep knowledge of the biosynthesis and regulation of plant cell wall and a high-precision genome engineering toolset are the two essential pillars of efforts to alter plant cell walls and reduce biomass recalcitrance. The past decade has seen a meteoric rise in use of transcriptomics and high-resolution imaging methods resulting in fresh insights into composition, structure, formation and deconstruction of plant cell walls. Subsequent gene manipulation approaches, however, commonly include ubiquitous mis-expression of a single candidate gene in a host that carries an intact copy of the native gene. The challenges posed by pleiotropic and unintended changes resulting from such an approach are moving the field towards synthetic biology approaches. Synthetic biology builds on a systems biology knowledge base and leverages high-precision tools for high-throughput assembly of multigene constructs and pathways, precision genome editing and site-specific gene stacking, silencing and/or removal. Here, we summarize the recent breakthroughs in biosynthesis and remodelling of major secondary cell wall components, assess the impediments in obtaining a systems-level understanding and explore the potential opportunities in leveraging synthetic biology approaches to reduce biomass recalcitrance.