Breaking the diffraction barrier: super-resolution imaging of cells

Anyone who has used a light microscope has wished that its resolution could be a little better. Now,?after centuries of gradual improvements, fluorescence microscopy has made a quantum leap in its resolving power due, in large part, to advancements over the past several years in a new area of research called super-resolution fluorescence microscopy. In this Primer, we explain the principles of various super-resolution approaches, such as STED, (S)SIM, and STORM/(F)PALM. Then, we describe recent applications of super-resolution microscopy in cells, which demonstrate how these approaches are beginning to provide new insights into cell biology, microbiology, and neurobiology.     

Biodiversity as insurance: from concept to measurement and application

Biological insurance theory predicts that, in a variable environment, aggregate ecosystem properties will vary less in more diverse communities because declines in the performance or abundance of some species or phenotypes will be offset, at least partly, by smoother declines or increases in others. During the past two decades, ecology has accumulated strong evidence for the stabilising effect of biodiversity on ecosystem functioning. As biological insurance is reaching the stage of a mature theory, it is critical to revisit and clarify its conceptual foundations to guide future developments, applications and measurements. In this review, we first clarify the connections between the insurance and portfolio concepts that have been used in ecology and the economic concepts that inspired them. Doing so points to gaps and mismatches between ecology and economics that could be filled profitably by new theoretical developments and new management applications. Second, we discuss some fundamental issues in biological insurance theory that have remained unnoticed so far and that emerge from some of its recent applications. In particular, we draw a clear distinction between the two effects embedded in biological insurance theory, i.e. the effects of biodiversity on the mean and variability of ecosystem properties. This distinction allows explicit consideration of trade-offs between the mean and stability of ecosystem processes and services. We also review applications of biological insurance theory in ecosystem management. Finally, we provide a synthetic conceptual framework that unifies the various approaches across disciplines, and we suggest new ways in which biological insurance theory could be extended to address new issues in ecology and ecosystem management. Exciting future challenges include linking the effects of biodiversity on ecosystem functioning and stability, incorporating multiple functions and feedbacks, developing new approaches to partition biodiversity effects across scales, extending biological insurance theory to complex interaction networks, and developing new applications to biodiversity and ecosystem management.     

Recent advances in drug repurposing using machine learning

Drug repurposing aims to find new uses for already existing and approved drugs. We now provide a brief overview of recent developments in drug repurposing using machine learning alongside other computational approaches for comparison. We also highlight several applications for cancer using kinase inhibitors, Alzheimer’s disease as well as COVID-19.     

Applications of mass spectrometry to signal transduction

Advances in mass spectrometry instrumentation, protocols for sample handling, and computational methods provide powerful new approaches to solving problems in analytical biochemistry. This review summarizes recent work illustrating ways in which mass spectrometry has been used to address questions relevant to signal transduction. Rather than encompass all of the instruments or methodologies that might be brought to bear on these problems, we present an overview of commonly used techniques, promising new methodologies, and some applications.     

The first releases of transgenic mosquitoes: an argument for the sterile insect technique

Potential applications for reducing transmission of mosquito-borne diseases by releasing genetically modified mosquitoes have been proposed, and mosquitoes are being created with such an application in mind in several laboratories. The use of the sterile insect technique (SIT) provides a safe programme in which production, release and mating competitiveness questions related to mass-reared genetically modified mosquitoes could be answered. It also provides a reversible effect that would be difficult to accomplish with gene introgression approaches. Could new technologies, including recombinant DNA techniques, have improved the success of previous mosquito releases? Criteria for an acceptable transgenic sterile mosquito are described, and the characteristics of radiation-induced sterility are compared with that of current transgenic approaches. We argue that SIT using transgenic material would provide an essentially safe and efficacious foundation for other possible approaches that are more ambitious.     

Recent developments in pyridine nucleotide regeneration

NAD(P)-dependent oxidoreductases are valuable tools for the synthesis of chiral compounds. Due to the high cost of the pyridine cofactors, in situ cofactor regeneration is required for preparative applications. In recent years, existing regeneration methodologies have been improved and new approaches have been devised. These include the use of newly discovered dehydrogenases that are stable in high contents of organic solvent and novel enzymes that can regenerate either the reduced or oxidized forms of the cofactor. The use of electrochemical methods has allowed cofactor regeneration for monooxygenases and natural or engineered whole-cell systems provide alternatives to approaches relying on purified enzymes.     

Statistical Tools and Status Symbols

This paper sets the stage for a series of edited papers which follow. It is argued that obvious statistical blunders (mortal sins) have not dissappeared entirely from the aging literature, but that the most frequent error now is that of choosing a less powerful analytic solution when a more powerful (and equally applicable) one is at hand (a venial sin). Clearly, it is argued, power must be considered in relationship to the theoretical model, the condition of the data set, and the research question. Editors and reviewers, it is argued, must cut through the “glitter” of new fads and the security of tradition in order to objectively consider the merits of new statistical applications. More importantly, without knowledge of the issues, limitations, and advantages of contemporary and emerging analytic techniques, authors cannot make good analytic choices and defend them effectively. The time between presentation of innovative approaches in the quantitative journals and application in the aging literature contributes to traditionalism in data analysis. Overzealousness by advocates of new approaches often contributes to premature embracing of them. Thus the papers that follow were designed to bring new methods to the “working-researcher” with a frank appraisal of assumptions, proper and improper applications, and limitations. Authors of these papers were challenged to communicate in plain and understandable terms and to provide practical examples.     

Biotechnology: impact on biological warfare and biodefense

Advances in biological research likely will permit development of a new class of advanced biological warfare (ABW) agents engineered to elicit novel effects. In addition, biotechnology will have applications supporting ABW weaponization, dissemination, and delivery. Such new agents and delivery systems would provide a variety of new use options, expanding the BW paradigm. Although ABW agents will not replace threats posed by traditional biological agents such as Bacillus anthracis (anthrax) and Variola (smallpox), they will necessitate novel approaches to counterproliferation, detection, medical countermeasures, and attribution.     

Candida spp. redox machineries: An ample biocatalytic platform for practical applications and academic insights

The use of oxidoreductases as biocatalysts for the production of a wide number of chiral building blocks is presently a mature (bio-)technology. In this context some industrial applications are currently performed by means of those enzymatic approaches, and new examples are expected to be realized. Moreover, oxidoreductases provide an interesting academic platform to undertake fundamental research in enzymology, to acquire a better understanding on catalytic mechanisms, and to facilitate the development of new biocatalytic applications. Within this area, a wide number of oxidoreductases from genus Candida spp. have been characterized and used as biocatalysts. These enzymes are rather diverse, and are able to carry out many useful reactions, like highly (enantio)selective keto-reductions, (de)racemizations and stereoinversions, and promiscuous catalytic imine reductions. In addition, some Candida spp. dehydrogenases are very useful for regenerating the cofactors, with the aid of sacrificial substrates. Addressing those features, the present paper aims to give an overview of these enzymes, by focusing on practical applications that these biocatalysts can provide. Furthermore, when possible, academic insights on the enzymatic performances will be discussed as well.     

Genomics for the ecological toolbox

Genomics technologies have expanded the types of question that can be addressed in human genetics and health and in fields such as ecology. Genome-scale approaches provide ways to examine physiological changes that occur when a pathogen invades a host, the response of an organism to a change in its environment, and the way in which changes in the microbial community affect ecosystem function. Here, we examine successful applications of genomics to ecological science to date and describe ways that classic ecological research disciplines might benefit from genomic approaches. We also address some of the challenges of using this methodology, and discuss how ecological researchers embracing these approaches enhance its effectiveness in applications such as gene hunting and gene expression analysis.     

A chronology of plankton dynamics in silico: how computer models have been used to study marine ecosystems

Research on plankton ecology in the oceans has traditionally been conducted via two scientific approaches: in situ (in the field) and in vitro (in the laboratory). There is, however, a third approach: exploring plankton dynamics in silico, or using computer models as tools to study marine ecosystems. Models have been used for this purpose for over 60 years, and the innovations and implementations of historical studies provide a context for how future model applications can continue to advance our understanding. To that end, this paper presents a chronology of the in silico approach to plankton dynamics, beginning with modeling pioneers who worked in the days before computers. During the first 30 years of automated computation, plankton modeling focused on formulations for biological processes and investigations of community structure. The changing technological context and conceptual paradigms of the late-1970s and 1980s resulted in simulations becoming more widespread research tools for biological oceanographers. This period saw rising use of models as hypothesis-testing tools, and means of exploring the effects of circulation on spatial distributions of organisms. Continued computer advances and increased availability of data in the 1990s allowed old approaches to be applied to old and new problems, and led to developments of new approaches. Much of the modeling in the new millennium so far has incorporated these sophistications, and many cutting-edge applications have come from a new generation of plankton scientists who were trained by modeling gurus of previous eras. The future directions for modeling plankton dynamics are rooted in the historical studies.     

Applications of biotechnology and genomics in potato improvement

Potato is the third most important global food crop and the most widely grown noncereal crop. As a species highly amenable to cell culture, it has a long history of biotechnology applications for crop improvement. This review begins with a historical perspective on potato improvement using biotechnology encompassing pathogen elimination, wide hybridization, ploidy manipulation and applications of cell culture. We describe the past developments and new approaches for gene transfer to potato. Transformation is highly effective for adding single genes to existing elite potato clones with no, or minimal, disturbances to their genetic background and represents the only effective way to produce isogenic lines of specific genotypes/cultivars. This is virtually impossible via traditional breeding as, due to the high heterozygosity in the tetraploid potato genome, the genetic integrity of potato clones is lost upon sexual reproduction as a result of allele segregation. These genetic attributes have also provided challenges for the development of genetic maps and applications of molecular markers and genomics in potato breeding. Various molecular approaches used to characterize loci, (candidate) genes and alleles in potato, and associating phenotype with genotype are also described. The recent determination of the potato genome sequence has presented new opportunities for genomewide assays to provide tools for gene discovery and enabling the development of robustly unique marker haplotypes spanning QTL regions. The latter will be useful in introgression breeding and whole‐genome approaches such as genomic selection to improve the efficiency of selecting elite clones and enhancing genetic gain over time.     

Improving the ‘tool box’ for robust industrial enzymes

The speed of sequencing of microbial genomes and metagenomes is providing an ever increasing resource for the identification of new robust biocatalysts with industrial applications for many different aspects of industrial biotechnology. Using ‘natures catalysts’ provides a sustainable approach to chemical synthesis of fine chemicals, general chemicals such as surfactants and new consumer-based materials such as biodegradable plastics. This provides a sustainable and ‘green chemistry’ route to chemical synthesis which generates no toxic waste and is environmentally friendly. In addition, enzymes can play important roles in other applications such as carbon dioxide capture, breakdown of food and other waste streams to provide a route to the concept of a ‘circular economy’ where nothing is wasted. The use of improved bioinformatic approaches and the development of new rapid enzyme activity screening methodology can provide an endless resource for new robust industrial biocatalysts.This mini-review will discuss several recent case studies where industrial enzymes of ‘high priority’ have been identified and characterised. It will highlight specific hydrolase enzymes and recent case studies which have been carried out within our group in Exeter.

     

miRNAs在肝癌干细胞中的作用

MicroRNAs (miRNAs)是一类参与转录后调控的小分子RNA,它在调控细胞的增殖、分化及肿瘤的形成等多种生理及病理过程中发挥着重要的作用.肝癌干细胞是肝癌组织中具有自我更新能力和分化潜能的一个微群体,它能够启始肝癌的发生,并且与肝癌的抗药性及复发等密切相关.已经有研究表明miRNAs对肝癌干细胞的发生发展起着重要的调控作用,包括致癌和抑癌的作用,因此总结miRNAs在肝癌干细胞中作用,有助于更好理解肝癌干细胞的特性及肝癌肿瘤生物学.近年来,除了传统的分子生物学手段,组学和系统生物学研究策略的运用也为miRNAs在肝癌中的研究提供了新的思路.鉴于此,深入研究miRNAs在肝癌干细胞中的分子机制,将为靶向肝癌干细胞的临床治疗提供新的途径.     

A novel assembly pipeline and functional annotations for targeted sequencing: A case study on the globally threatened Margaritiferidae (Bivalvia: Unionida)

The proliferation of genomic sequencing approaches has significantly impacted the field of phylogenetics. Target capture approaches provide a cost-effective, fast and easily applied strategy for phylogenetic inference of non-model organisms. However, several existing target capture processing pipelines are incapable of incorporating whole genome sequencing (WGS). Here, we develop a new pipeline for capture and de novo assembly of the targeted regions using whole genome re-sequencing reads. This new pipeline captured targeted loci accurately, and given its unbiased nature, can be used with any target capture probe set. Moreover, due to its low computational demand, this new pipeline may be ideal for users with limited resources and when high-coverage sequencing outputs are required. We demonstrate the utility of our approach by incorporating WGS data into the first comprehensive phylogenomic reconstruction of the freshwater mussel family Margaritiferidae. We also provide a catalogue of well-curated functional annotations of these previously uncharacterized freshwater mussel-specific target regions, representing a complementary tool for scrutinizing phylogenetic inferences while expanding future applications of the probe set.     

Interpreting and Testing Interactions in Conditional Mixture Models

Mixture modeling applications in psychology often include covariates to explain class membership and aid in construct validation of the latent classification variable. These applications tend to use between-class models involving only main effects of predictors. However, a variety of developmental theories posit interactions among risk and protective variables in predicting membership in trajectory classes or behavioral symptom profiles. This article bridges this disconnect between substantive theory and methodological practice by presenting and comparing two approaches for testing interactive effects of predictors on class membership: product term (PT) and multiple group (MG) approaches. For each approach, we discuss alternative interpretation strategies involving predicted probabilities and odds ratios; we also discuss when the approaches provide equivalent inferences. Published longitudinal and cross-sectional mixture model applications that had originally allowed for only additive effects on class membership are re-analyzed to illustrate the testing and interpretation of interactive effects on class membership using both PT and MG approaches.     

Animal models of regenerative medicine for biological treatment approaches of degenerative disc diseases

Degenerative disc disease (DDD) is a painful, chronic and progressive disease, which is characterized by inflammation, structural and biological deterioration of the intervertebral disc (IVD) tissues. DDD is specified as cell-, age-, and genetic-dependent degenerative process that can be accelerated by environmental factors. It is one of the major causes of chronic back pain and disability affecting millions of people globally. Current treatment options, such as physical rehabilitation, pain management, and surgical intervention, can provide only temporary pain relief. Different animal models have been used to study the process of IVD degeneration and develop therapeutic options that may restore the structure and function of degenerative discs. Several research works have depicted considerable progress in understanding the biological basis of disc degeneration and the therapeutic potentials of cell transplantation, gene therapy, applications of supporting biomaterials and bioactive factors, or a combination thereof. Since animal models play increasingly significant roles in treatment approaches of DDD, we conducted an electronic database search on Medline through June 2020 to identify, compare, and discuss publications regarding biological therapeutic approaches of DDD that based on intradiscal treatment strategies. We provide an up-to-date overview of biological treatment strategies in animal models including mouse, rat, rabbit, porcine, bovine, ovine, caprine, canine, and primate models. Although no animal model could profoundly reproduce the clinical conditions in humans; animal models have played important roles in specifying our knowledge about the pathophysiology of DDD. They are crucial for developing new therapy approaches for clinical applications.