Highlights► Complex diseases are an outcome of multiple triggers that precipitate into similar phenotypes. ► Systems level understanding can reveal dynamic aspects of disease progression profile. ► Correlation of metabolic remodeling to phenotypic alteration can delineate critical nodes of interventions. ► Multitargeting of key nodes of metabolic networks can be an effective therapeutic strategy. ► Robust and high-throughput data integration in conjunction with simulation would make the drug discovery process more efficient. 相似文献
Highlights► Microbial production of pharmaceutical and fuel molecules. ► Systems biology tools advanced our understanding about synthetic pathway design. ► Synthetic biology led us to cell factories tailor-made for chemical production. ► Combinatorial gene assembly for synthetic pathway diversification. ► Engineering static, dynamic and spatial control for better production phenotype. 相似文献
Metabolomics is a well-established tool in systems biology, especially in the top–down approach. Metabolomics experiments often results in discovery studies that provide intriguing biological hypotheses but rarely offer mechanistic explanation of such findings. In this light, the interpretation of metabolomics data can be boosted by deploying systems biology approaches.
Objectives
This review aims to provide an overview of systems biology approaches that are relevant to metabolomics and to discuss some successful applications of these methods.
Methods
We review the most recent applications of systems biology tools in the field of metabolomics, such as network inference and analysis, metabolic modelling and pathways analysis.
Results
We offer an ample overview of systems biology tools that can be applied to address metabolomics problems. The characteristics and application results of these tools are discussed also in a comparative manner.
Conclusions
Systems biology-enhanced analysis of metabolomics data can provide insights into the molecular mechanisms originating the observed metabolic profiles and enhance the scientific impact of metabolomics studies.
Highlights► This review covers current know-how on cheese flavor development. ► Proteolysis, autolysis and amino acid catabolism by lactic acid bacteria are discussed. ► Systems biology approaches will drive future technology improvements. ► Next-generation sequencing holds promise for fast increase in exploitable knowledge. ► Culture heterogeneity may be significant for industrial flavor production by LAB. 相似文献
Highlights? Top-down and bottom-up approaches to genome streamlining. ? Computational support for constructing and refactoring streamlined genomes. ? From genome engineering to metabolic reprogramming. ? Perspectives in applied genome engineering. 相似文献
Highlights► Highly variable and complex pathogens remain challenging vaccine targets. ► Systems biology and reverse vaccinology continue to foster success. ► New ways of presenting conserved, functionally critical epitopes hold promise. ► Adjuvant systems allow for enduring, native antigen presentation. ► An ideal vaccine provides synergy between innate, cellular, and humoral immunity. 相似文献
Highlights? Self-organization is a property of developmental systems and pluripotent stem cells. ? Tissue engineering approaches can be applied to control self-organization in vitro. ? Maturation of pluripotent stem cells in vitro may be promoted by self-organization. ? Subtle, dynamic signals are provided to pluripotent cells through self-organization. 相似文献
Highlights► Metabolic dependencies that arise in tumors may present new opportunities for therapy. ► Advanced methods in metabolic systems biology can help identify these dependencies. ► Application of isotope tracers to cancer models can facilitates quantitation of fluxes. ► Tumors with compromised TCA metabolism exhibit unique metabolic profiles. 相似文献
Highlights► A powerful range of tools has been developed for metabolic network flux analysis. ► These tools yield insights that are used to aid microbial metabolic engineering. ► Plants present great opportunities and special challenges to applying these tools. ► Tool selection and knowledge of plant systems is key to practical success. 相似文献
•Perturbation nature of signaling is a fundamental feature of allosteric regulation.
•Experimental and theoretical studies of allostery using perturbation approach.
•Structure-based statistical mechanical model of allostery.
•Inducing and fine-tuning targeted allosteric response.
•From current understanding of allosteric control to future tasks in its design.
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Regardless of the diversity of systems, allosteic signalling is found to be always caused by perturbations. This recurring trait of allostery serves as a foundation for developing different experimental efforts and theoretical models for the studies of allosteric mechanisms. Among computational approaches considered here particular emphasis is given to the structure-based statistical mechanical model of allostery (SBSMMA), which allows one to study the causality and energetics of allosteric communication. We argue that the reverse allosteric signaling on the basis of SBSMMA can be used for predicting latent allosteric sites and inducing a tunable allosteric response. Per-residue allosteric effects of mutations can also be explored and ‘latent drivers’ expanding the cancer mutational landscape can be predicted using SBSMMA. Most recent and important implementations of computational models in web-resources along with a brief outlook on future research directions are also discussed. 相似文献
Highlights► Genome-scale metabolic modelling is being increasingly applied in LAB research. ► Novel techniques that broaden applicability of models remain to be applied to LAB. ► Additional constraints allow better predictions of genome-scale metabolic models. ► Novel approaches to move from modelling monocultures to mixed cultures are being developed. ► The feasibility of metagenome-based modelling approaches is being appreciated. 相似文献
The quantitative determination of sarcosine is of great importance in clinical chemistry, food and fermentation industries. Elevated sarcosine levels are associated with Alzheimer, dementia, prostate cancer, colorectal cancer, stomach cancer and sarcosinemia. This review summarizes the various methods for quantitative analysis of sarcosine with special emphasis on various strategies of biosensors and their analytical performance. The current bio sensing methods have overcome the drawbacks of conventional methods. Sarcosine biosensors work optimally at pH 7.0 to 8.0 in the linear range of 0.1 to 100?μM within 2 to 17?s and between 25 and 37?°C, within a limit of detection (LOD) between 0.008 and 500?mM. The formulated biosensors can be reused within a stability period of 3–180?days. Future research could be focused to modify existing sarcosine biosensors, leading to simple, reliable, and economical sensors ideally suited for point-of-care treatment.
Clinical significance
Elevated sarcosine levels are associated with prostate and colorectal cancer, Alzheimer, dementia, stomach cancer and sarcosinemia.
Quantitative determination of sarcosine is of great importance in clinical chemistry as well as food and fermentation industries.
Attempts made in development of sarcosine biosensors have been reviewed with their advantages and disadvantages, so that scientist and clinicians can improvise the methods of developing more potent sarcosine biosensor applicable in multitudinous fields.
This is the first comprehensive review which compares the various immobilization methods, sensing principles, strategies used in biosensors and their analytical performance in detail.
Highlights? Activation surge reconstituted in vitro with purified SK and RR ? ADP can be endogenously generated from ATP to stimulate an SK's phosphatase activity ? SK's affinity for ADP governs the switch from the kinase to phosphatase state ? Lid region of SK PhoQ controls its phosphatase activity and surge of RR PhoP 相似文献
Robin Fears and co-authors discuss evidence-informed regional and global policy responses to health impacts of climate change.Summary points
Effective policy making depends on synthesising and improving the use of existing robust scientific evidence, tackling misinformation, and identifying knowledge gaps to be filled by new research.
A global project organised by the InterAcademy Partnership (IAP) is bringing together evidence from Africa, Asia, the Americas, and Europe to evaluate climate change effects on health and to assess policy priorities for adaptation and mitigation solutions. Project design encouraged inclusivity in assessing research from across disciplines and from diverse geographical and socioeconomic contexts encompassing issues for vulnerable groups (including Indigenous Peoples) and integrating outputs at national, regional, and global levels.
Coordinated policy development approaches across sectors and regions and integration at national–regional–global levels are essential to understand trade-offs, avoid inadvertent consequences, and capitalise on potential synergies for multiple benefits for health, equity, and environment.
National priorities must include integrating health actions into national climate adaptation plans and Nationally Determined Contributions (NDCs) under the Paris Agreement. Regional policy action is important to address cross-boundary issues and to build critical mass for quantifying and implementing solutions.
A focus on human health can catalyse the strengthening of international coherence and commitment to tackling shared climate change challenges. Health must be prioritised in current global policy initiatives, including the United Nations Framework Convention on Climate Change (UNFCC) Conference of the Parties 26 (COP26), UN Convention on Biological Diversity (CBD) Conference of the Parties 15 (COP15), and the UN Food Systems Summit. The scientific and health communities have a key role to help lead efforts by engaging at the science–policy interfaces to address barriers to action.
1.1. The organization of the motor systems underlying locomotion in insects and mammals is surprisingly similar. There are also parallels between the insect motor system and the system underlying reaching and the occulomotor system in primates.
2.2. The movements generated by all these systems are planned or prepared before their execution and there is a partial separation of circuits for preparation and execution.
3.3. These circuits consist of multiple descending pathways interconnected to form overlapping loops which work co-operatively to determine the motor output. Thus, both insect and mammalian motor systems can be treated as parallel distributed (PDP) systems.
4.4. This enables a comparison of functional levels of processing in the different systems and also provides a basis for modelling motor systems with attractor neural networks.
Highlights► Stable isotopes provide insights about in situ biodegradation mechanisms and rates. ► Isotopic approaches can be confounded by abiotic processes and heterogeneity effects. ► Isotopic applications are improving with new methods of analysis and modeling. ► Isotopic data are most useful when combined with other approaches for fate assessment. 相似文献
Proteins do not function in isolation; it is their interactions with one another and also with other molecules (e.g. DNA, RNA) that mediate metabolic and signaling pathways, cellular processes, and organismal systems. Due to their central role in biological function, protein interactions also control the mechanisms leading to healthy and diseased states in organisms. Diseases are often caused by mutations affecting the binding interface or leading to biochemically dysfunctional allosteric changes in proteins. Therefore, protein interaction networks can elucidate the molecular basis of disease, which in turn can inform methods for prevention, diagnosis, and treatment. In this chapter, we will describe the computational approaches to predict and map networks of protein interactions and briefly review the experimental methods to detect protein interactions. We will describe the application of protein interaction networks as a translational approach to the study of human disease and evaluate the challenges faced by these approaches.
What to Learn in This Chapter
Experimental and computational methods to detect protein interactions
Highlights► Thiol compounds (glutathione) protect LAB from multiple environmental stresses. ► Engineering antioxidative properties of LAB can improve the overall robustness. ► Genomics approaches helped to reveal the molecular mechanism of stress response. 相似文献
