Biotechnology Institute

In 2008 we published the first set of guidelines for standardizing research in autophagy. Since then, research on this topic has continued to accelerate, and many new scientists have entered the field. Our knowledge base and relevant new technologies have also been expanding. Accordingly, it is important to update these guidelines for monitoring autophagy in different organisms. Various reviews have described the range of assays that have been used for this purpose. Nevertheless, there continues to be confusion regarding acceptable methods to measure autophagy, especially in multicellular eukaryotes. For example, a key point that needs to be emphasized is thatthere is a difference between measurements that monitor the numbers or volume of autophagic elements (e.g., autophagosomes or autolysosomes) at any stage of the autophagic process versus those that measure flux through the autophagy pathway (i.e., the completeprocess including the amount and rate of cargo sequestered and degraded). In particular, a block in macroautophagy that results in autophagosome accumulation must be differentiated from stimuli that increase autophagic activity, defined as increasedautophagy induction coupled with increased delivery to, and degradation within, lysosomes (inmost higher eukaryotes and some protists such as Dictyostelium) or the vacuole (in plants and fungi). In other words, it is especially important that investigators new to the field understand that the appearance of more autophagosomes does not necessarily equate with more autophagy. In fact, in manycases, autophagosomes accumulate because of a block in trafficking to lysosomes without a concomitant change in autophagosome biogenesis, whereas an increase in autolysosomes may reflect a reduction in degradative activity. It is worth emphasizing here that lysosomal digestion is a stage of autophagy and evaluating its competence is a crucial part of the evaluation of autophagic flux, or complete autophagy. Here, we present a set of guidelines for the selection and interpretation of methods for use by investigators who aim to examine macroautophagy and related processes, as well as forreviewers who need to provide realistic and reasonable critiques of papers that are focused on these processes. These guidelines are not meant to be a formulaic set of rules, because the appropriate assays depend in part on the question being asked and the system being used. In addition, we emphasize that no individual assay is guaranteed to be the most appropriate one in every situation, and we strongly recommend the use of multipleassays to monitor autophagy. Along these lines, because of the potential for pleiotropic effects due to blocking autophagy through genetic manipulation, it is imperative to target by gene knockout or RNA interference more than one autophagyrelated protein. In addition, some individual Atg proteins, or groups of proteins, are involved in other cellular pathways implying that not all Atg proteins can be used as a specific marker for an autophagic process. In these guidelines, we consider these various methods of assessing autophagy and what information can, or cannot, be obtained from them. Finally, by discussing the merits and limits of particular assays, we hope to encourage technical innovation in the field.

The rhizosphere encompasses the millimeters of soil surrounding a plant root where complex biological and ecological processes occur. This review describes recent advances in elucidating the role of root exudates in interactions between plant roots and other plants, microbes, and nematodes present in the rhizosphere. Evidence indicating that root exudates may take part in the signaling events that initiate the execution of these interactions is also presented. Various positive and negative plant-plant and plant-microbe interactions are highlighted and described from the molecular to the ecosystem scale. Furthermore, methodologies to address these interactions under laboratory conditions are presented.

MOLREP is an automated program for molecular replacement that utilizes a number of original approaches to rotational and translational search and data preparation. Since the first publication describing the program, MOLREP has acquired a variety of features that include weighting of the X-ray data and search models, multi-copy search, fitting the model into electron density, structural superposition of two models and rigid-body refinement. The program can run in a fully automatic mode using optimized parameters calculated from the input data.

UNLABELLED: Although de novo assembly graphs contain assembled contigs (nodes), the connections between those contigs (edges) are difficult for users to access. Bandage (a Bioinformatics Application for Navigating De novo Assembly Graphs Easily) is a tool for visualizing assembly graphs with connections. Users can zoom in to specific areas of the graph and interact with it by moving nodes, adding labels, changing colors and extracting sequences. BLAST searches can be performed within the Bandage graphical user interface and the hits are displayed as highlights in the graph. By displaying connections between contigs, Bandage presents new possibilities for analyzing de novo assemblies that are not possible through investigation of contigs alone. AVAILABILITY AND IMPLEMENTATION: Source code and binaries are freely available at https://github.com/rrwick/Bandage. Bandage is implemented in C++ and supported on Linux, OS X and Windows. A full feature list and screenshots are available at http://rrwick.github.io/Bandage. CONTACT: rrwick@gmail.com SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Secreted membrane-enclosed vesicles, collectively called extracellular vesicles (EVs), which include exosomes, ectosomes, microvesicles, microparticles, apoptotic bodies and other EV subsets, encompass a very rapidly growing scientific field in biology and medicine. Importantly, it is currently technically challenging to obtain a totally pure EV fraction free from non-vesicular components for functional studies, and therefore there is a need to establish guidelines for analyses of these vesicles and reporting of scientific studies on EV biology. Here, the International Society for Extracellular Vesicles (ISEV) provides researchers with a minimal set of biochemical, biophysical and functional standards that should be used to attribute any specific biological cargo or functions to EVs.

The human impact on life on Earth has increased sharply since the 1970s, driven by the demands of a growing population with rising average per capita income. Nature is currently supplying more materials than ever before, but this has come at the high cost of unprecedented global declines in the extent and integrity of ecosystems, distinctness of local ecological communities, abundance and number of wild species, and the number of local domesticated varieties. Such changes reduce vital benefits that people receive from nature and threaten the quality of life of future generations. Both the benefits of an expanding economy and the costs of reducing nature's benefits are unequally distributed. The fabric of life on which we all depend-nature and its contributions to people-is unravelling rapidly. Despite the severity of the threats and lack of enough progress in tackling them to date, opportunities exist to change future trajectories through transformative action. Such action must begin immediately, however, and address the root economic, social, and technological causes of nature's deterioration.

Many biologically interesting phenomena occur on a time scale that is too long to be studied by atomistic simulations. These phenomena include the dynamics of large proteins and self-assembly of biological materials. Coarse-grained (CG) molecular modeling allows computer simulations to be run on length and time scales that are 2-3 orders of magnitude larger compared to atomistic simulations, providing a bridge between the atomistic and the mesoscopic scale. We developed a new CG model for proteins as an extension of the MARTINI force field. Here, we validate the model for its use in peptide-bilayer systems. In order to validate the model, we calculated the potential of mean force for each amino acid as a function of its distance from the center of a dioleoylphosphatidylcholine (DOPC) lipid bilayer. We then compared amino acid association constants, the partitioning of a series of model pentapeptides, the partitioning and orientation of WALP23 in DOPC lipid bilayers and a series of KALP peptides in dimyristoylphosphatidylcholine and dipalmitoylphosphatidylcholine (DPPC) bilayers. A comparison with results obtained from atomistic models shows good agreement in all of the tests performed. We also performed a systematic investigation of the partitioning of five series of polyalanine-leucine peptides (with different lengths and compositions) in DPPC bilayers. As expected, the fraction of peptides partitioned at the interface increased with decreasing peptide length and decreasing leucine content, demonstrating that the CG model is capable of discriminating partitioning behavior arising from subtle differences in the amino acid composition. Finally, we simulated the concentration-dependent formation of transmembrane pores by magainin, an antimicrobial peptide. In line with atomistic simulation studies, disordered toroidal pores are formed. In conclusion, the model is computationally efficient and effectively reproduces peptide-lipid interactions and the partitioning of amino acids and peptides in lipid bilayers.

BindingDB (http://www.bindingdb.org) is a publicly accessible database currently containing approximately 20,000 experimentally determined binding affinities of protein-ligand complexes, for 110 protein targets including isoforms and mutational variants, and approximately 11,000 small molecule ligands. The data are extracted from the scientific literature, data collection focusing on proteins that are drug-targets or candidate drug-targets and for which structural data are present in the Protein Data Bank. The BindingDB website supports a range of query types, including searches by chemical structure, substructure and similarity; protein sequence; ligand and protein names; affinity ranges and molecular weight. Data sets generated by BindingDB queries can be downloaded in the form of annotated SDfiles for further analysis, or used as the basis for virtual screening of a compound database uploaded by the user. The data in BindingDB are linked both to structural data in the PDB via PDB IDs and chemical and sequence searches, and to the literature in PubMed via PubMed IDs.

MDAnalysis (http://mdanalysis.org) is a library for structural and temporal analysis of molecular dynamics (MD) simulation trajectories and individual protein structures. MD simulations of biological molecules have become an important tool to elucidate the relationship between molecular structure and physiological function. Simulations are performed with highly optimized software packages on HPC resources but most codes generate output trajectories in their own formats so that the development of new trajectory analysis algorithms is confined to specific user communities and widespread adoption and further development is delayed. MDAnalysis addresses this problem by abstracting access to the raw simulation data and presenting a uniform object-oriented Python interface to the user. It thus enables users to rapidly write code that is portable and immediately usable in virtually all biomolecular simulation communities. The user interface and modular design work equally well in complex scripted work flows, as foundations for other packages, and for interactive and rapid prototyping work in IPython / Jupyter notebooks, especially together with molecular visualization provided by nglview and time series analysis with pandas. MDAnalysis is written in Python and Cython and uses NumPy arrays for easy interoperability with the wider scientific Python ecosystem. It is widely used and forms the foundation for more specialized biomolecular simulation tools.

This review presents recommended nomenclature for the biosynthesis of ribosomally synthesized and post-translationally modified peptides (RiPPs), a rapidly growing class of natural products. The current knowledge regarding the biosynthesis of the >20 distinct compound classes is also reviewed, and commonalities are discussed.

Anopheles gambiae is the principal vector of malaria, a disease that afflicts more than 500 million people and causes more than 1 million deaths each year. Tenfold shotgun sequence coverage was obtained from the PEST strain of A. gambiae and assembled into scaffolds that span 278 million base pairs. A total of 91% of the genome was organized in 303 scaffolds; the largest scaffold was 23.1 million base pairs. There was substantial genetic variation within this strain, and the apparent existence of two haplotypes of approximately equal frequency ("dual haplotypes") in a substantial fraction of the genome likely reflects the outbred nature of the PEST strain. The sequence produced a conservative inference of more than 400,000 single-nucleotide polymorphisms that showed a markedly bimodal density distribution. Analysis of the genome sequence revealed strong evidence for about 14,000 protein-encoding transcripts. Prominent expansions in specific families of proteins likely involved in cell adhesion and immunity were noted. An expressed sequence tag analysis of genes regulated by blood feeding provided insights into the physiological adaptations of a hematophagous insect.

Many studies have examined the role of mean climate change in agriculture, but an understanding of the influence of inter-annual climate variations on crop yields in different regions remains elusive. We use detailed crop statistics time series for ~13,500 political units to examine how recent climate variability led to variations in maize, rice, wheat and soybean crop yields worldwide. While some areas show no significant influence of climate variability, in substantial areas of the global breadbaskets, >60% of the yield variability can be explained by climate variability. Globally, climate variability accounts for roughly a third (~32-39%) of the observed yield variability. Our study uniquely illustrates spatial patterns in the relationship between climate variability and crop yield variability, highlighting where variations in temperature, precipitation or their interaction explain yield variability. We discuss key drivers for the observed variations to target further research and policy interventions geared towards buffering future crop production from climate variability.

Bacteria able to transfer electrons to metals are key agents in biogeochemical metal cycling, subsurface bioremediation, and corrosion processes. More recently, these bacteria have gained attention as the transfer of electrons from the cell surface to conductive materials can be used in multiple applications. In this work, we adapted electrochemical techniques to probe intact biofilms of Shewanella oneidensis MR-1 and Shewanella sp. MR-4 grown by using a poised electrode as an electron acceptor. This approach detected redox-active molecules within biofilms, which were involved in electron transfer to the electrode. A combination of methods identified a mixture of riboflavin and riboflavin-5'-phosphate in supernatants from biofilm reactors, with riboflavin representing the dominant component during sustained incubations (>72 h). Removal of riboflavin from biofilms reduced the rate of electron transfer to electrodes by >70%, consistent with a role as a soluble redox shuttle carrying electrons from the cell surface to external acceptors. Differential pulse voltammetry and cyclic voltammetry revealed a layer of flavins adsorbed to electrodes, even after soluble components were removed, especially in older biofilms. Riboflavin adsorbed quickly to other surfaces of geochemical interest, such as Fe(III) and Mn(IV) oxy(hydr)oxides. This in situ demonstration of flavin production, and sequestration at surfaces, requires the paradigm of soluble redox shuttles in geochemistry to be adjusted to include binding and modification of surfaces. Moreover, the known ability of isoalloxazine rings to act as metal chelators, along with their electron shuttling capacity, suggests that extracellular respiration of minerals by Shewanella is more complex than originally conceived.

Here we determine the complete genomic sequence of the gram negative, gamma-Proteobacterium Vibrio cholerae El Tor N16961 to be 4,033,460 base pairs (bp). The genome consists of two circular chromosomes of 2,961,146 bp and 1,072,314 bp that together encode 3,885 open reading frames. The vast majority of recognizable genes for essential cell functions (such as DNA replication, transcription, translation and cell-wall biosynthesis) and pathogenicity (for example, toxins, surface antigens and adhesins) are located on the large chromosome. In contrast, the small chromosome contains a larger fraction (59%) of hypothetical genes compared with the large chromosome (42%), and also contains many more genes that appear to have origins other than the gamma-Proteobacteria. The small chromosome also carries a gene capture system (the integron island) and host 'addiction' genes that are typically found on plasmids; thus, the small chromosome may have originally been a megaplasmid that was captured by an ancestral Vibrio species. The V. cholerae genomic sequence provides a starting point for understanding how a free-living, environmental organism emerged to become a significant human bacterial pathogen.

Mass mortalities due to disease outbreaks have recently affected major taxa in the oceans. For closely monitored groups like corals and marine mammals, reports of the frequency of epidemics and the number of new diseases have increased recently. A dramatic global increase in the severity of coral bleaching in 1997-98 is coincident with high El Niño temperatures. Such climate-mediated, physiological stresses may compromise host resistance and increase frequency of opportunistic diseases. Where documented, new diseases typically have emerged through host or range shifts of known pathogens. Both climate and human activities may have also accelerated global transport of species, bringing together pathogens and previously unexposed host populations.

The Na+/Ca2+ exchanger, an ion transport protein, is expressed in the plasma membrane (PM) of virtually all animal cells. It extrudes Ca2+ in parallel with the PM ATP-driven Ca2+ pump. As a reversible transporter, it also mediates Ca2+ entry in parallel with various ion channels. The energy for net Ca2+ transport by the Na+/Ca2+ exchanger and its direction depend on the Na+, Ca2+, and K+ gradients across the PM, the membrane potential, and the transport stoichiometry. In most cells, three Na+ are exchanged for one Ca2+. In vertebrate photoreceptors, some neurons, and certain other cells, K+ is transported in the same direction as Ca2+, with a coupling ratio of four Na+ to one Ca2+ plus one K+. The exchanger kinetics are affected by nontransported Ca2+, Na+, protons, ATP, and diverse other modulators. Five genes that code for the exchangers have been identified in mammals: three in the Na+/Ca2+ exchanger family (NCX1, NCX2, and NCX3) and two in the Na+/Ca2+ plus K+ family (NCKX1 and NCKX2). Genes homologous to NCX1 have been identified in frog, squid, lobster, and Drosophila. In mammals, alternatively spliced variants of NCX1 have been identified; dominant expression of these variants is cell type specific, which suggests that the variations are involved in targeting and/or functional differences. In cardiac myocytes, and probably other cell types, the exchanger serves a housekeeping role by maintaining a low intracellular Ca2+ concentration; its possible role in cardiac excitation-contraction coupling is controversial. Cellular increases in Na+ concentration lead to increases in Ca2+ concentration mediated by the Na+/Ca2+ exchanger; this is important in the therapeutic action of cardiotonic steroids like digitalis. Similarly, alterations of Na+ and Ca2+ apparently modulate basolateral K+ conductance in some epithelia, signaling in some special sense organs (e.g., photoreceptors and olfactory receptors) and Ca2+-dependent secretion in neurons and in many secretory cells. The juxtaposition of PM and sarco(endo)plasmic reticulum membranes may permit the PM Na+/Ca2+ exchanger to regulate sarco(endo)plasmic reticulum Ca2+ stores and influence cellular Ca2+ signaling.

The genome of Phytophthora infestans, the pathogen that triggered the Irish potato famine in the nineteenth century, has been sequenced. It remains a devastating pathogen, with late blight destroying crops worth billions of dollars each year. Blight is difficult to control, in part because it adapts so quickly to genetically resistant potato strains. Comparison with two other Phytophthora genomes shows rapid turnover and extensive expansion of specific families of secreted disease effector proteins, including many genes induced during infection that have activities thought to alter host physiology. These fast evolving effector genes are found in highly dynamic and expanded regions of the genome, a factor that may contribute to its rapid adaptability to host plants. The P. infestans genome is the biggest so far sequenced, at about 240 megabases, with an extremely high repeat content of close to 75%. It is a model organism for the oomycetes, a distinct lineage of fungus-like eukaryotes related to organisms such as brown algae and diatoms. Phytophthora infestans is a fungus-like eukaryote and the most destructive pathogen of potato, with current annual worldwide potato crop losses due to late blight estimated at $6.7 billion. Here, the sequence of the P. infestans genome is reported. Comparison with two other Phytophthora genomes showed rapid turnover and extensive expansion of certain secreted disease effector proteins, probably explaining the rapid adaptability of the pathogen to host plants. Phytophthora infestans is the most destructive pathogen of potato and a model organism for the oomycetes, a distinct lineage of fungus-like eukaryotes that are related to organisms such as brown algae and diatoms. As the agent of the Irish potato famine in the mid-nineteenth century, P. infestans has had a tremendous effect on human history, resulting in famine and population displacement1. To this day, it affects world agriculture by causing the most destructive disease of potato, the fourth largest food crop and a critical alternative to the major cereal crops for feeding the world’s population1. Current annual worldwide potato crop losses due to late blight are conservatively estimated at $6.7 billion2. Management of this devastating pathogen is challenged by its remarkable speed of adaptation to control strategies such as genetically resistant cultivars3,4. Here we report the sequence of the P. infestans genome, which at ∼240 megabases (Mb) is by far the largest and most complex genome sequenced so far in the chromalveolates. Its expansion results from a proliferation of repetitive DNA accounting for ∼74% of the genome. Comparison with two other Phytophthora genomes showed rapid turnover and extensive expansion of specific families of secreted disease effector proteins, including many genes that are induced during infection or are predicted to have activities that alter host physiology. These fast-evolving effector genes are localized to highly dynamic and expanded regions of the P. infestans genome. This probably plays a crucial part in the rapid adaptability of the pathogen to host plants and underpins its evolutionary potential.

BACKGROUND: bacteria in the human intestines, have been implicated because children with ASD often suffer gastrointestinal (GI) problems that correlate with ASD severity. Several previous studies have reported abnormal gut bacteria in children with ASD. The gut microbiome-ASD connection has been tested in a mouse model of ASD, where the microbiome was mechanistically linked to abnormal metabolites and behavior. Similarly, a study of children with ASD found that oral non-absorbable antibiotic treatment improved GI and ASD symptoms, albeit temporarily. Here, a small open-label clinical trial evaluated the impact of Microbiota Transfer Therapy (MTT) on gut microbiota composition and GI and ASD symptoms of 18 ASD-diagnosed children. RESULTS: MTT involved a 2-week antibiotic treatment, a bowel cleanse, and then an extended fecal microbiota transplant (FMT) using a high initial dose followed by daily and lower maintenance doses for 7-8 weeks. The Gastrointestinal Symptom Rating Scale revealed an approximately 80% reduction of GI symptoms at the end of treatment, including significant improvements in symptoms of constipation, diarrhea, indigestion, and abdominal pain. Improvements persisted 8 weeks after treatment. Similarly, clinical assessments showed that behavioral ASD symptoms improved significantly and remained improved 8 weeks after treatment ended. Bacterial and phagedeep sequencing analyses revealed successful partial engraftment of donor microbiota and beneficial changes in the gut environment. Specifically, overall bacterial diversity and the abundance of Bifidobacterium, Prevotella, and Desulfovibrio among other taxa increased following MTT, and these changes persisted after treatment stopped (followed for 8 weeks). CONCLUSIONS: This exploratory, extended-duration treatment protocol thus appears to be a promising approach to alter the gut microbiome and virome and improve GI and behavioral symptoms of ASD. Improvements in GI symptoms, ASD symptoms, and the microbiome all persisted for at least 8 weeks after treatment ended, suggesting a long-term impact. TRIAL REGISTRATION: This trial was registered on the ClinicalTrials.gov, with the registration number NCT02504554.

BACKGROUND As global climate change accelerates, one of the most urgent tasks for the coming decades is to develop accurate predictions about biological responses to guide the effective protection of biodiversity. Predictive models in biology provide a means for scientists to project changes to species and ecosystems in response to disturbances such as climate change. Most current predictive models, however, exclude important biological mechanisms such as demography, dispersal, evolution, and species interactions. These biological mechanisms have been shown to be important in mediating past and present responses to climate change. Thus, current modeling efforts do not provide sufficiently accurate predictions. Despite the many complexities involved, biologists are rapidly developing tools that include the key biological processes needed to improve predictive accuracy. The biggest obstacle to applying these more realistic models is that the data needed to inform them are almost always missing. We suggest ways to fill this growing gap between model sophistication and information to predict and prevent the most damaging aspects of climate change for life on Earth. ADVANCES On the basis of empirical and theoretical evidence, we identify six biological mechanisms that commonly shape responses to climate change yet are too often missing from current predictive models: physiology; demography, life history, and phenology; species interactions; evolutionary potential and population differentiation; dispersal, colonization, and range dynamics; and responses to environmental variation. We prioritize the types of information needed to inform each of these mechanisms and suggest proxies for data that are missing or difficult to collect. We show that even for well-studied species, we often lack critical information that would be necessary to apply more realistic, mechanistic models. Consequently, data limitations likely override the potential gains in accuracy of more realistic models. Given the enormous challenge of collecting this detailed information on millions of species around the world, we highlight practical methods that promote the greatest gains in predictive accuracy. Trait-based approaches leverage sparse data to make more general inferences about unstudied species. Targeting species with high climate sensitivity and disproportionate ecological impact can yield important insights about future ecosystem change. Adaptive modeling schemes provide a means to target the most important data while simultaneously improving predictive accuracy. OUTLOOK Strategic collections of essential biological information will allow us to build generalizable insights that inform our broader ability to anticipate species’ responses to climate change and other human-caused disturbances. By increasing accuracy and making uncertainties explicit, scientists can deliver improved projections for biodiversity under climate change together with characterizations of uncertainty to support more informed decisions by policymakers and land managers. Toward this end, a globally coordinated effort to fill data gaps in advance of the growing climate-fueled biodiversity crisis offers substantial advantages in efficiency, coverage, and accuracy. Biologists can take advantage of the lessons learned from the Intergovernmental Panel on Climate Change’s development, coordination, and integration of climate change projections. Climate and weather projections were greatly improved by incorporating important mechanisms and testing predictions against global weather station data. Biology can do the same. We need to adopt this meteorological approach to predicting biological responses to climate change to enhance our ability to mitigate future changes to global biodiversity and the services it provides to humans. Emerging models are beginning to incorporate six key biological mechanisms that can improve predictions of biological responses to climate change. Models that include biological mechanisms have been used to project (clockwise from top) the evolution of disease-harboring mosquitoes, future environments and land use, physiological responses of invasive species such as cane toads, demographic responses of penguins to future climates, climate-dependent dispersal behavior in butterflies, and mismatched interactions between butterflies and their host plants. Despite these modeling advances, we seldom have the detailed data needed to build these models, necessitating new efforts to collect the relevant data to parameterize more biologically realistic predictive models.

Electrospun fibers were produced using a variety of solvents to investigate the influence of polymer/solvent properties on the fiber surface morphology. Electrospinning is a novel processing technique for the production of fibers with diameters in the range of a few nanometers to tens of micrometers. We have been able to produce polymeric fibers with a high surface area through the introduction of a micro- and nanostructured surface structure, which we refer to as a “porous” morphology. These features could be introduced in several different polymeric fibers increasing their range of application significantly. The pores vary from densely packed, well-formed nanopores with diameters in the range 20−350 nm to larger flat pores of about 1 μm. The increased surface area of polymeric fibers was correlated with high volatility solvents used in the electrospinning process. The effect of processing parameters on the fiber surface morphology was also investigated using optical microscopy, field emission scanning electron microscopy (FESEM), transmission electron microscopy (TEM), and atomic force microscopy (AFM).