The Vaginal Microbiota: What Have We Learned after a Decade of Molecular Characterization?

We conducted a systematic review of the Medline database (U.S. National Library of Medicine, National Institutes of Health, Bethesda, MD, U.S.A) to determine if consistent molecular vaginal microbiota (VMB) composition patterns can be discerned after a decade of molecular testing, and to evaluate demographic, behavioral and clinical determinants of VMB compositions. Studies were eligible when published between 1 January 2008 and 15 November 2013, and if at least one molecular technique (sequencing, PCR, DNA fingerprinting, or DNA hybridization) was used to characterize the VMB. Sixty three eligible studies were identified. These studies have now conclusively shown that lactobacilli-dominated VMB are associated with a healthy vaginal micro-environment and that bacterial vaginosis (BV) is best described as a polybacterial dysbiosis. The extent of dysbiosis correlates well with Nugent score and vaginal pH but not with the other Amsel criteria. Lactobacillus crispatus is more beneficial than L. iners. Longitudinal studies have shown that a L. crispatus-dominated VMB is more likely to shift to a L. iners-dominated or mixed lactobacilli VMB than to full dysbiosis. Data on VMB determinants are scarce and inconsistent, but dysbiosis is consistently associated with HIV, human papillomavirus (HPV), and Trichomonas vaginalis infection. In contrast, vaginal colonization with Candida spp. is more common in women with a lactobacilli-dominated VMB than in women with dysbiosis. Cervicovaginal mucosal immune responses to molecular VMB compositions have not yet been properly characterized. Molecular techniques have now become more affordable, and we make a case for incorporating them into larger epidemiological studies to address knowledge gaps in etiology and pathogenesis of dysbiosis, associations of different dysbiotic states with clinical outcomes, and to evaluate interventions aimed at restoring and maintaining a lactobacilli-dominated VMB.     

Translational systems biology of inflammation

Inflammation is a complex, multi-scale biologic response to stress that is also required for repair and regeneration after injury. Despite the repository of detailed data about the cellular and molecular processes involved in inflammation, including some understanding of its pathophysiology, little progress has been made in treating the severe inflammatory syndrome of sepsis. To address the gap between basic science knowledge and therapy for sepsis, a community of biologists and physicians is using systems biology approaches in hopes of yielding basic insights into the biology of inflammation. “Systems biology” is a discipline that combines experimental discovery with mathematical modeling to aid in the understanding of the dynamic global organization and function of a biologic system (cell to organ to organism). We propose the term translational systems biology for the application of similar tools and engineering principles to biologic systems with the primary goal of optimizing clinical practice. We describe the efforts to use translational systems biology to develop an integrated framework to gain insight into the problem of acute inflammation. Progress in understanding inflammation using translational systems biology tools highlights the promise of this multidisciplinary field. Future advances in understanding complex medical problems are highly dependent on methodological advances and integration of the computational systems biology community with biologists and clinicians.     

An updated SYSCILIA gold standard (SCGSv2) of known ciliary genes,revealing the vast progress that has been made in the cilia research field

Cilia are microtubule-based organelles with important functions in motility and sensation. They contribute to a broad spectrum of developmental disorders called ciliopathies and have recently been linked to common conditions such as cancers and congenital heart disease. There has been increasing interest in the biology of cilia and their contribution to disease over the past two decades. In 2013 we published a “Gold Standard” list of genes confirmed to be associated with cilia. This was published as part of the SYSCILIA consortium for systems biology study dissecting the contribution of cilia to human health and disease, and was named the Syscilia Gold Standard (SCGS). Since this publication, interest in cilia and understanding of their functions have continued to grow, and we now present an updated SCGS version 2. This includes an additional 383 genes, more than doubling the size of SCGSv1. We use this dataset to conduct a review of advances in understanding of cilia biology 2013– 2021 and offer perspectives on the future of cilia research. We hope that this continues to be a useful resource for the cilia community.     

大数据时代土壤微生物地理学研究综述

土壤蕴含极为丰富的微生物多样性,它们在物质分解、元素生物地球化学循环、植物生产力和生物健康中扮演着关键角色。理解土壤微生物的生物地理分布格局、形成机制与群落构建规则,有助于预测在全球变化背景下土壤微生物组的功能演变及其对陆地生态系统的调控影响。自21世纪以来,土壤微生物生物地理学在各种大型国际微生物计划的推动下逐步形成了分子生物学技术耦合大数据分析的模式,实现了多种尺度上的关联研究。阐述了土壤微生物在分布格局和群落构建规则方面的研究进展,重点介绍了分子生物学技术和大数据分析在土壤微生物生物地理研究中的应用,对土壤微生物生物地理学未来在微生物分类分辨率、模型验证与构建和功能基因地理学的发展方向进行了展望。     

The simulation approach in synthetic biology

Synthetic biology and systems biology are often highlighted as antagonistic strategies for dealing with the overwhelming complexity of biology (engineering versus understanding; tinkering in the lab versus modelling in the computer). However, a closer view of contemporary engineering methods (inextricably interwoven with mathematical modelling and simulation) and of the situation in biology (inextricably confronted with the intrinsic complexity of biomolecular environments) demonstrates that tinkering in the lab is increasingly supported by rational design methods. In other words: Synthetic biology and systems biology are merged by the use of computational techniques. These computational techniques are needed because the intrinsic complexity of biomolecular environments (stochasticity, non-linearities, system-level organization, evolution, independence, etc.) require advanced concepts of bio bricks and devices. A philosophical investigation of the history and nature of bio parts and devices reveals that these objects are imitating generic objects of engineering (switches, gates, oscillators, sensors, etc.), but the well-known design principles of generic objects are not sufficient for complex environments like cells. Therefore, the rational design methods have to be used to create more advanced generic objects, which are not only generic in their use, but also adaptive in their behavior. Case studies will show how simulation-based rational design methods are used to identify adequate parameters for synthesized designs (stability analyses), to improve lab experiments by ‘looking through noise’ (estimation of hidden variables and parameters), and to replace laborious and time-consuming post hoc tweaking in the lab by in-silico guidance (in-silico variation of bio brick properties). The overall aim of these developments, as will be argued in the discussion, is to achieve adaptive-generic instrumentality for bio parts and devices and thus increasingly merging systems and synthetic biology.     

Modelling malaria pathogenesis

Almost 20 years after the development of models of malaria pathogenesis began, we are beyond the 'proof-of-concept' phase and these models are no longer abstract mathematical exercises. They have refined our knowledge of within-host processes, and have brought insights that could not easily have been obtained from experimentation alone. There is much potential that remains to be realized, however, both in terms of informing the design of interventions and health policy, and in terms of addressing lingering questions about the basic biology of malaria. Recent research has begun to iterate theory and data in a much more comprehensive way, and the use of statistical techniques for model fitting and comparison offers a promising approach for providing a quantitative understanding of the pathogenesis of such a complex disease.     

Some conditions apply: Systems for studying Plasmodium falciparum protein function

Malaria, caused by infection with Plasmodium parasites, remains a significant global health concern. For decades, genetic intractability and limited tools hindered our ability to study essential proteins and pathways in Plasmodium falciparum, the parasite associated with the most severe malaria cases. However, recent years have seen major leaps forward in the ability to genetically manipulate P. falciparum parasites and conditionally control protein expression/function. The conditional knockdown systems used in P. falciparum target all 3 components of the central dogma, allowing researchers to conditionally control gene expression, translation, and protein function. Here, we review some of the common knockdown systems that have been adapted or developed for use in P. falciparum. Much of the work done using conditional knockdown approaches has been performed in asexual, blood-stage parasites, but we also highlight their uses in other parts of the life cycle and discuss new ways of applying these systems outside of the intraerythrocytic stages. With the use of these tools, the field’s understanding of parasite biology is ever increasing, and promising new pathways for antimalarial drug development are being discovered.     

Bioluminescent indicators for in vivo measurements of gene expression

Recent developments in in vivo imaging using optical, radionuclide and paramagnetic reporter probes now enables continuous measurements of gene expression in living animals. In vivo bioluminescence imaging (BLI) is a sensitive, versatile and accessible imaging strategy that has been applied to a variety of small-animal models of human biology and disease. We discuss current strategies in BLI and the potential of combining BLI with other in vivo and ex vivo techniques. BLI will have a significant role in in vivo cellular and molecular imaging, a field that will help reveal the molecular basis of biology and disease.     

Toward quantitative phosphotyrosine profiling in vivo

Tyrosine phosphorylation is a dynamic reversible post-translational modification that regulates many aspects of cell biology. To understand how this modification controls biological function, it is necessary to not only identify the specific sites of phosphorylation, but also to quantify how phosphorylation levels on these sites may be altered under specific physiological conditions. Due to its sensitivity and accuracy, mass spectrometry (MS) has widely been applied to the identification and characterization of phosphotyrosine signaling across biological systems. In this review we highlight the advances in both MS and phosphotyrosine enrichment methods that have been developed to enable the identification of low level tyrosine phosphorylation events. Computational and manual approaches to ensure confident identification of phosphopeptide sequence and determination of phosphorylation site localization are discussed along with methods that have been applied to the relative quantification of large numbers of phosphorylation sites. Finally, we provide an overview of the challenges ahead as we extend these technologies to the characterization of tyrosine phosphorylation signaling in vivo. With these latest developments in analytical and computational techniques, it is now possible to derive biological insight from quantitative MS-based analysis of signaling networks in vitro and in vivo. Application of these approaches to a wide variety of biological systems will define how signal transduction regulates cellular physiology in health and disease.     

Database and tools for metabolic network analysis

Metabolic network analysis has attracted much attention in the area of systems biology. It has a profound role in understanding the key features of organism metabolic networks and has been successfully applied in several fields of systems biology, including in silico gene knockouts, production yield improvement using engineered microbial strains, drug target identification, and phenotype prediction. A variety of metabolic network databases and tools have been developed in order to assist research in these fields. Databases that comprise biochemical data are normally integrated with the use of metabolic network analysis tools in order to give a more comprehensive result. This paper reviews and compares eight databases as well as twenty one recent tools. The aim of this review is to study the different types of tools in terms of the features and usability, as well as the databases in terms of the scope and data provided. These tools can be categorised into three main types: standalone tools; toolbox-based tools; and web-based tools. Furthermore, comparisons of the databases as well as the tools are also provided to help software developers and users gain a clearer insight and a better understanding of metabolic network analysis. Additionally, this review also helps to provide useful information that can be used as guidance in choosing tools and databases for a particular research interest.     

Marine invertebrate immunodefense responses: Molecular and cellular approaches in tunicates

The reason for analyzing tunicate recognition systems is two-fold. First, they can be established as primitive models for understanding fundamental immunological mechanisms by analyzing either their individual cells in vivo or in vitro. Discovered mechanisms could provide alternatives to traditional mammalian (mouse, rat) and emerging models (fish, amphibians) in answering basic questions concerning immunity and disease. Moreover, their advantages lie in: (a) the simplicity of primitive systems (minimal hemopoietic sites), allowing a more effective dissection of variables; (b) their limited expense when compared to experimentation using vertebrates; and (c) their being socially non-controversial. Second, techniques of cell and molecular biology are equally applicable to tunicates as invertebrate models. Despite the considerable advances of recent years, many fundamental or conceptual aspects of immunological reactivity remain unresolved. A clear understanding of the system's evolutionary past will help to elucidate mechanisms which are complex and difficult to decipher in mammals, as we postulate, the immunorecognition systems of vertebrates evolved from simpler systems. Then tunicate immunodefense responses are excellent examples for analyses.     

Ecological Monitoring and Health Research in Luambe National Park,Zambia: Generation of Baseline Data Layers

Classifying, describing and understanding the natural environment is an important element of studies of human, animal and ecosystem health, and baseline ecological data are commonly lacking in remote environments of the world. Human African trypanosomiasis is an important constraint on human well-being in sub-Saharan Africa, and spillover transmission occurs from the reservoir community of wild mammals. Here we use robust and repeatable methodology to generate baseline datasets on vegetation and mammal density to investigate the ecology of warthogs (Phacochoerus africanus) in the remote Luambe National Park in Zambia, in order to further our understanding of their interactions with tsetse (Glossina spp.) vectors of trypanosomiasis. Fuzzy set theory is used to produce an accurate landcover classification, and distance sampling techniques are applied to obtain species and habitat level density estimates for the most abundant wild mammals. The density of warthog burrows is also estimated and their spatial distribution mapped. The datasets generated provide an accurate baseline to further ecological and epidemiological understanding of disease systems such as trypanosomiasis. This study provides a reliable framework for ecological monitoring of wild mammal densities and vegetation composition in remote, relatively inaccessible environments.     

Dimerization and Bifunctionality Confer Robustness to the Isocitrate Dehydrogenase Regulatory System in Escherichia coli

An important goal of systems biology is to develop quantitative models that explain how specific molecular features give rise to systems-level properties. Metabolic and regulatory pathways that contain multifunctional proteins are especially interesting to study from this perspective because they have frequently been observed to exhibit robustness: the ability for a system to perform its proper function even as levels of its components change. In this study, we use extensive biochemical data and algebraic modeling to develop and analyze a model that shows how robust behavior arises in the isocitrate dehydrogenase (IDH) regulatory system of Escherichia coli, which was shown in 1985 to experimentally exhibit robustness. E. coli IDH is regulated by reversible phosphorylation catalyzed by the bifunctional isocitrate dehydrogenase kinase/phosphatase (IDHKP), and the level of IDH activity determines whether carbon flux is directed through the glyoxylate bypass (for growth on two-carbon substrates) or the full tricarboxylic acid cycle. Our model, which incorporates recent structural data on IDHKP, identifies several specific biochemical features of the system (including homodimerization of IDH and bifunctionality of IDHKP) that provide a potential explanation for robustness. Using algebraic techniques, we derive an invariant that summarizes the steady-state relationship between the phospho-forms of IDH. We use the invariant in combination with kinetic data on IDHKP to calculate IDH activity at a range of total IDH levels and find that our model predicts robustness. Our work unifies much of the known biochemistry of the IDH regulatory system into a single quantitative framework and highlights the importance of constructing biochemically realistic models in systems biology.     

Experimental biology of coral reef ecosystems

Coral reef ecosystems are at the crossroads. While significant gaps still exist in our understanding of how “normal” reefs work, unprecedented changes in coral reef systems have forced the research community to change its focus from basic research to understand how one of the most diverse ecosystems in the world works to basic research with strong applied implications to alleviate damage, save, or restore coral reef ecosystems. A wide range of stressors on local, regional, and global spatial scales including over fishing, diseases, large-scale disturbance events, global climate change (e.g., ozone depletion, global warming), and over population have all contributed to declines in coral cover or phase shifts in community structure on time scales never observed before. Many of these changes are directly or indirectly related to anthropogenically induced changes in the global support network that affects all ecosystems. This review focuses on some recent advances in the experimental biology of coral reef ecosystems, and in particular scleractinian corals, at all levels of biological organization. Many of the areas of interest and techniques discussed reflect a progression of technological advances in biology and ecology but have found unique and timely application in the field of experimental coral reef biology. The review, by nature, will not be exhaustive and reflects the author's interests to a large degree. Because of the voluminous literature available, an attempt has been made to capture the essential elements and references for each topic discussed.     

Network modelling of gene regulation

Gene regulatory network (GRN) modelling has gained increasing attention in the past decade. Many computational modelling techniques have been proposed to facilitate the inference and analysis of GRN. However, there is often confusion about the aim of GRN modelling, and how a gene network model can be fully utilised as a tool for systems biology. The aim of the present article is to provide an overview of this rapidly expanding subject. In particular, we review some fundamental concepts of systems biology and discuss the role of network modelling in understanding complex biological systems. Several commonly used network modelling paradigms are surveyed with emphasis on their practical use in systems biology research.