Many researchers, across incredibly diverse foci, are applying phylogenetics to their research question(s). However, many researchers are new to this topic and so it presents inherent problems. Here we compile a practical introduction to phylogenetics for nonexperts. We outline in a step-by-step manner, a pipeline for generating reliable phylogenies from gene sequence datasets. We begin with a user-guide for similarity search tools via online interfaces as well as local executables. Next, we explore programs for generating multiple sequence alignments followed by protocols for using software to determine best-fit models of evolution. We then outline protocols for reconstructing phylogenetic relationships via maximum likelihood and Bayesian criteria and finally describe tools for visualizing phylogenetic trees. While this is not by any means an exhaustive description of phylogenetic approaches, it does provide the reader with practical starting information on key software applications commonly utilized by phylogeneticists. The vision for this article would be that it could serve as a practical training tool for researchers embarking on phylogenetic studies and also serve as an educational resource that could be incorporated into a classroom or teaching-lab.
19 Related JoVE Articles!
The ITS2 Database
Institutions: University of Würzburg, University of Würzburg.
The internal transcribed spacer 2 (ITS2) has been used as a phylogenetic marker for more than two decades. As ITS2 research mainly focused on the very variable ITS2 sequence, it confined this marker to low-level phylogenetics only. However, the combination of the ITS2 sequence and its highly conserved secondary structure improves the phylogenetic resolution1
and allows phylogenetic inference at multiple taxonomic ranks, including species delimitation2-8
The ITS2 Database9
presents an exhaustive dataset of internal transcribed spacer 2 sequences from NCBI GenBank11
. Following an annotation by profile Hidden Markov Models (HMMs), the secondary structure of each sequence is predicted. First, it is tested whether a minimum energy based fold12
(direct fold) results in a correct, four helix conformation. If this is not the case, the structure is predicted by homology modeling13
. In homology modeling, an already known secondary structure is transferred to another ITS2 sequence, whose secondary structure was not able to fold correctly in a direct fold.
The ITS2 Database is not only a database for storage and retrieval of ITS2 sequence-structures. It also provides several tools to process your own ITS2 sequences, including annotation, structural prediction, motif detection and BLAST14
search on the combined sequence-structure information. Moreover, it integrates trimmed versions of 4SALE15,16
for multiple sequence-structure alignment calculation and Neighbor Joining18
tree reconstruction. Together they form a coherent analysis pipeline from an initial set of sequences to a phylogeny based on sequence and secondary structure.
In a nutshell, this workbench simplifies first phylogenetic analyses to only a few mouse-clicks, while additionally providing tools and data for comprehensive large-scale analyses.
Genetics, Issue 61, alignment, internal transcribed spacer 2, molecular systematics, secondary structure, ribosomal RNA, phylogenetic tree, homology modeling, phylogeny
Creating Objects and Object Categories for Studying Perception and Perceptual Learning
Institutions: Georgia Health Sciences University, Georgia Health Sciences University, Georgia Health Sciences University, Palo Alto Research Center, Palo Alto Research Center, University of Minnesota .
In order to quantitatively study object perception, be it perception by biological systems or by machines, one needs to create objects and object categories with precisely definable, preferably naturalistic, properties1
. Furthermore, for studies on perceptual learning, it is useful to create novel objects and object categories (or object classes
) with such properties2
Many innovative and useful methods currently exist for creating novel objects and object categories3-6
(also see refs. 7,8). However, generally speaking, the existing methods have three broad types of shortcomings.
First, shape variations are generally imposed by the experimenter5,9,10
, and may therefore be different from the variability in natural categories, and optimized for a particular recognition algorithm. It would be desirable to have the variations arise independently of the externally imposed constraints.
Second, the existing methods have difficulty capturing the shape complexity of natural objects11-13
. If the goal is to study natural object perception, it is desirable for objects and object categories to be naturalistic, so as to avoid possible confounds and special cases.
Third, it is generally hard to quantitatively measure the available information in the stimuli created by conventional methods. It would be desirable to create objects and object categories where the available information can be precisely measured and, where necessary, systematically manipulated (or 'tuned'). This allows one to formulate the underlying object recognition tasks in quantitative terms.
Here we describe a set of algorithms, or methods, that meet all three of the above criteria. Virtual morphogenesis (VM) creates novel, naturalistic virtual 3-D objects called 'digital embryos' by simulating the biological process of embryogenesis14
. Virtual phylogenesis (VP) creates novel, naturalistic object categories by simulating the evolutionary process of natural selection9,12,13
. Objects and object categories created by these simulations can be further manipulated by various morphing methods to generate systematic variations of shape characteristics15,16
. The VP and morphing methods can also be applied, in principle, to novel virtual objects other than digital embryos, or to virtual versions of real-world objects9,13
. Virtual objects created in this fashion can be rendered as visual images using a conventional graphical toolkit, with desired manipulations of surface texture, illumination, size, viewpoint and background. The virtual objects can also be 'printed' as haptic objects using a conventional 3-D prototyper.
We also describe some implementations of these computational algorithms to help illustrate the potential utility of the algorithms. It is important to distinguish the algorithms from their implementations. The implementations are demonstrations offered solely as a 'proof of principle' of the underlying algorithms. It is important to note that, in general, an implementation of a computational algorithm often has limitations that the algorithm itself does not have.
Together, these methods represent a set of powerful and flexible tools for studying object recognition and perceptual learning by biological and computational systems alike. With appropriate extensions, these methods may also prove useful in the study of morphogenesis and phylogenesis.
Neuroscience, Issue 69, machine learning, brain, classification, category learning, cross-modal perception, 3-D prototyping, inference
Setting Limits on Supersymmetry Using Simplified Models
Institutions: University College London, CERN, Lawrence Berkeley National Laboratories.
Experimental limits on supersymmetry and similar theories are difficult to set because of the enormous available parameter space and difficult to generalize because of the complexity of single points. Therefore, more phenomenological, simplified models are becoming popular for setting experimental limits, as they have clearer physical interpretations. The use of these simplified model limits to set a real limit on a concrete theory has not, however, been demonstrated. This paper recasts simplified model limits into limits on a specific and complete supersymmetry model, minimal supergravity. Limits obtained under various physical assumptions are comparable to those produced by directed searches. A prescription is provided for calculating conservative and aggressive limits on additional theories. Using acceptance and efficiency tables along with the expected and observed numbers of events in various signal regions, LHC experimental results can be recast in this manner into almost any theoretical framework, including nonsupersymmetric theories with supersymmetry-like signatures.
Physics, Issue 81, high energy physics, particle physics, Supersymmetry, LHC, ATLAS, CMS, New Physics Limits, Simplified Models
A Novel Bayesian Change-point Algorithm for Genome-wide Analysis of Diverse ChIPseq Data Types
Institutions: Stony Brook University, Cold Spring Harbor Laboratory, University of Texas at Dallas.
ChIPseq is a widely used technique for investigating protein-DNA interactions. Read density profiles are generated by using next-sequencing of protein-bound DNA and aligning the short reads to a reference genome. Enriched regions are revealed as peaks, which often differ dramatically in shape, depending on the target protein1
. For example, transcription factors often bind in a site- and sequence-specific manner and tend to produce punctate peaks, while histone modifications are more pervasive and are characterized by broad, diffuse islands of enrichment2
. Reliably identifying these regions was the focus of our work.
Algorithms for analyzing ChIPseq data have employed various methodologies, from heuristics3-5
to more rigorous statistical models, e.g.
Hidden Markov Models (HMMs)6-8
. We sought a solution that minimized the necessity for difficult-to-define, ad hoc parameters that often compromise resolution and lessen the intuitive usability of the tool. With respect to HMM-based methods, we aimed to curtail parameter estimation procedures and simple, finite state classifications that are often utilized.
Additionally, conventional ChIPseq data analysis involves categorization of the expected read density profiles as either punctate or diffuse followed by subsequent application of the appropriate tool. We further aimed to replace the need for these two distinct models with a single, more versatile model, which can capably address the entire spectrum of data types.
To meet these objectives, we first constructed a statistical framework that naturally modeled ChIPseq data structures using a cutting edge advance in HMMs9
, which utilizes only explicit formulas-an innovation crucial to its performance advantages. More sophisticated then heuristic models, our HMM accommodates infinite hidden states through a Bayesian model. We applied it to identifying reasonable change points in read density, which further define segments of enrichment. Our analysis revealed how our Bayesian Change Point (BCP) algorithm had a reduced computational complexity-evidenced by an abridged run time and memory footprint. The BCP algorithm was successfully applied to both punctate peak and diffuse island identification with robust accuracy and limited user-defined parameters. This illustrated both its versatility and ease of use. Consequently, we believe it can be implemented readily across broad ranges of data types and end users in a manner that is easily compared and contrasted, making it a great tool for ChIPseq data analysis that can aid in collaboration and corroboration between research groups. Here, we demonstrate the application of BCP to existing transcription factor10,11
and epigenetic data12
to illustrate its usefulness.
Genetics, Issue 70, Bioinformatics, Genomics, Molecular Biology, Cellular Biology, Immunology, Chromatin immunoprecipitation, ChIP-Seq, histone modifications, segmentation, Bayesian, Hidden Markov Models, epigenetics
Extracting DNA from the Gut Microbes of the Termite (Zootermopsis Angusticollis) and Visualizing Gut Microbes
Institutions: California Institute of Technology - Caltech.
Termites are among the few animals known to have the capacity to subsist solely by consuming wood. The termite gut tract contains a dense and species-rich microbial population that assists in the degradation of lignocellulose predominantly into acetate, the key nutrient fueling termite metabolism (Odelson & Breznak, 1983). Within these microbial populations are bacteria, methanogenic archaea and, in some ("lower") termites, eukaryotic protozoa. Thus, termites are excellent research subjects for studying the interactions among microbial species and the numerous biochemical functions they perform to the benefit of their host. The species composition of microbial populations in termite guts as well as key genes involved in various biochemical processes has been explored using molecular techniques (Kudo et al., 1998; Schmit-Wagner et al., 2003; Salmassi & Leadbetter, 2003). These techniques depend on the extraction and purification of high-quality nucleic acids from the termite gut environment. The extraction technique described in this video is a modified compilation of protocols developed for extraction and purification of nucleic acids from environmental samples (Mor et al., 1994; Berthelet et al., 1996; Purdy et al., 1996; Salmassi & Leadbetter, 2003; Ottesen et al. 2006) and it produces DNA from termite hindgut material suitable for use as template for polymerase chain reaction (PCR).
Microbiology, issue 4, microbial community, DNA, extraction, gut, termite
Establishment of Microbial Eukaryotic Enrichment Cultures from a Chemically Stratified Antarctic Lake and Assessment of Carbon Fixation Potential
Institutions: Miami University .
Lake Bonney is one of numerous permanently ice-covered lakes located in the McMurdo Dry Valleys, Antarctica. The perennial ice cover maintains a chemically stratified water column and unlike other inland bodies of water, largely prevents external input of carbon and nutrients from streams. Biota are exposed to numerous environmental stresses, including year-round severe nutrient deficiency, low temperatures, extreme shade, hypersalinity, and 24-hour darkness during the winter 1
. These extreme environmental conditions limit the biota in Lake Bonney almost exclusively to microorganisms 2
Single-celled microbial eukaryotes (called "protists") are important players in global biogeochemical cycling 3
and play important ecological roles in the cycling of carbon in the dry valley lakes, occupying both primary and tertiary roles in the aquatic food web. In the dry valley aquatic food web, protists that fix inorganic carbon (autotrophy) are the major producers of organic carbon for organotrophic organisms 4, 2
. Phagotrophic or heterotrophic protists capable of ingesting bacteria and smaller protists act as the top predators in the food web 5
. Last, an unknown proportion of the protist population is capable of combined mixotrophic metabolism 6, 7
. Mixotrophy in protists involves the ability to combine photosynthetic capability with phagotrophic ingestion of prey microorganisms. This form of mixotrophy differs from mixotrophic metabolism in bacterial species, which generally involves uptake dissolved carbon molecules. There are currently very few protist isolates from permanently ice-capped polar lakes, and studies of protist diversity and ecology in this extreme environment have been limited 8, 4, 9, 10, 5
. A better understanding of protist metabolic versatility in the simple dry valley lake food web will aid in the development of models for the role of protists in the global carbon cycle.
We employed an enrichment culture approach to isolate potentially phototrophic and mixotrophic protists from Lake Bonney. Sampling depths in the water column were chosen based on the location of primary production maxima and protist phylogenetic diversity 4, 11
, as well as variability in major abiotic factors affecting protist trophic modes: shallow sampling depths are limited for major nutrients, while deeper sampling depths are limited by light availability. In addition, lake water samples were supplemented with multiple types of growth media to promote the growth of a variety of phototrophic organisms.
RubisCO catalyzes the rate limiting step in the Calvin Benson Bassham (CBB) cycle, the major pathway by which autotrophic organisms fix inorganic carbon and provide organic carbon for higher trophic levels in aquatic and terrestrial food webs 12
. In this study, we applied a radioisotope assay modified for filtered samples 13
to monitor maximum carboxylase activity as a proxy for carbon fixation potential and metabolic versatility in the Lake Bonney enrichment cultures.
Microbiology, Issue 62, Antarctic lake, McMurdo Dry Valleys, Enrichment cultivation, Microbial eukaryotes, RubisCO
Optimization and Utilization of Agrobacterium-mediated Transient Protein Production in Nicotiana
Institutions: Fraunhofer USA Center for Molecular Biotechnology.
-mediated transient protein production in plants is a promising approach to produce vaccine antigens and therapeutic proteins within a short period of time. However, this technology is only just beginning to be applied to large-scale production as many technological obstacles to scale up are now being overcome. Here, we demonstrate a simple and reproducible method for industrial-scale transient protein production based on vacuum infiltration of Nicotiana
plants with Agrobacteria
carrying launch vectors. Optimization of Agrobacterium
cultivation in AB medium allows direct dilution of the bacterial culture in Milli-Q water, simplifying the infiltration process. Among three tested species of Nicotiana
, N. excelsiana
× N. excelsior
) was selected as the most promising host due to the ease of infiltration, high level of reporter protein production, and about two-fold higher biomass production under controlled environmental conditions. Induction of Agrobacterium
harboring pBID4-GFP (Tobacco mosaic virus
-based) using chemicals such as acetosyringone and monosaccharide had no effect on the protein production level. Infiltrating plant under 50 to 100 mbar for 30 or 60 sec resulted in about 95% infiltration of plant leaf tissues. Infiltration with Agrobacterium
laboratory strain GV3101 showed the highest protein production compared to Agrobacteria
laboratory strains LBA4404 and C58C1 and wild-type Agrobacteria
strains at6, at10, at77 and A4. Co-expression of a viral RNA silencing suppressor, p23 or p19, in N. benthamiana
resulted in earlier accumulation and increased production (15-25%) of target protein (influenza virus hemagglutinin).
Plant Biology, Issue 86, Agroinfiltration, Nicotiana benthamiana, transient protein production, plant-based expression, viral vector, Agrobacteria
VIGS-Mediated Forward Genetics Screening for Identification of Genes Involved in Nonhost Resistance
Institutions: The Samuel Roberts Noble Foundation.
Nonhost disease resistance of plants against bacterial pathogens is controlled by complex defense pathways. Understanding this mechanism is important for developing durable disease-resistant plants against wide range of pathogens. Virus-induced gene silencing (VIGS)-based forward genetics screening is a useful approach for identification of plant defense genes imparting nonhost resistance. Tobacco rattle virus
(TRV)-based VIGS vector is the most efficient VIGS vector to date and has been efficiently used to silence endogenous target genes in Nicotiana benthamiana
In this manuscript, we demonstrate a forward genetics screening approach for silencing of individual clones from a cDNA library in N. benthamiana
and assessing the response of gene silenced plants for compromised nonhost resistance against nonhost pathogens, Pseudomonas syringae
T1, P. syringae
, and X. campestris
. These bacterial pathogens are engineered to express GFPuv protein and their green fluorescing colonies can be seen by naked eye under UV light in the nonhost pathogen inoculated plants if the silenced target gene is involved in imparting nonhost resistance. This facilitates reliable and faster identification of gene silenced plants susceptible to nonhost pathogens. Further, promising candidate gene information can be known by sequencing the plant gene insert in TRV vector. Here we demonstrate the high throughput capability of VIGS-mediated forward genetics to identify genes involved in nonhost resistance. Approximately, 100 cDNAs can be individually silenced in about two to three weeks and their relevance in nonhost resistance against several nonhost bacterial pathogens can be studied in a week thereafter. In this manuscript, we enumerate the detailed steps involved in this screening. VIGS-mediated forward genetics screening approach can be extended not only to identifying genes involved in nonhost resistance but also to studying genes imparting several biotic and abiotic stress tolerances in various plant species.
Virology, Issue 78, Plant Biology, Infection, Genetics, Molecular Biology, Cellular Biology, Physiology, Genomics, Pathology, plants, Nonhost Resistance, Virus-induced gene silencing, VIGS, disease resistance, gene silencing, Pseudomonas, GFPuv, sequencing, virus, Nicotiana benthamiana, plant model
Mapping Bacterial Functional Networks and Pathways in Escherichia Coli using Synthetic Genetic Arrays
Institutions: University of Toronto, University of Toronto, University of Regina.
Phenotypes are determined by a complex series of physical (e.g.
protein-protein) and functional (e.g.
gene-gene or genetic) interactions (GI)1
. While physical interactions can indicate which bacterial proteins are associated as complexes, they do not necessarily reveal pathway-level functional relationships1. GI screens, in which the growth of double mutants bearing two deleted or inactivated genes is measured and compared to the corresponding single mutants, can illuminate epistatic dependencies between loci and hence provide a means to query and discover novel functional relationships2
. Large-scale GI maps have been reported for eukaryotic organisms like yeast3-7
, but GI information remains sparse for prokaryotes8
, which hinders the functional annotation of bacterial genomes. To this end, we and others have developed high-throughput quantitative bacterial GI screening methods9, 10
Here, we present the key steps required to perform quantitative E. coli
Synthetic Genetic Array (eSGA) screening procedure on a genome-scale9
, using natural bacterial conjugation and homologous recombination to systemically generate and measure the fitness of large numbers of double mutants in a colony array format.
Briefly, a robot is used to transfer, through conjugation, chloramphenicol (Cm) - marked mutant alleles from engineered Hfr (High frequency of recombination) 'donor strains' into an ordered array of kanamycin (Kan) - marked F- recipient strains. Typically, we use loss-of-function single mutants bearing non-essential gene deletions (e.g.
the 'Keio' collection11
) and essential gene hypomorphic mutations (i.e.
alleles conferring reduced protein expression, stability, or activity9, 12, 13
) to query the functional associations of non-essential and essential genes, respectively. After conjugation and ensuing genetic exchange mediated by homologous recombination, the resulting double mutants are selected on solid medium containing both antibiotics. After outgrowth, the plates are digitally imaged and colony sizes are quantitatively scored using an in-house automated image processing system14
. GIs are revealed when the growth rate of a double mutant is either significantly better or worse than expected9
. Aggravating (or negative) GIs often result between loss-of-function mutations in pairs of genes from compensatory pathways that impinge on the same essential process2
. Here, the loss of a single gene is buffered, such that either single mutant is viable. However, the loss of both pathways is deleterious and results in synthetic lethality or sickness (i.e.
slow growth). Conversely, alleviating (or positive) interactions can occur between genes in the same pathway or protein complex2
as the deletion of either gene alone is often sufficient to perturb the normal function of the pathway or complex such that additional perturbations do not reduce activity, and hence growth, further. Overall, systematically identifying and analyzing GI networks can provide unbiased, global maps of the functional relationships between large numbers of genes, from which pathway-level information missed by other approaches can be inferred9
Genetics, Issue 69, Molecular Biology, Medicine, Biochemistry, Microbiology, Aggravating, alleviating, conjugation, double mutant, Escherichia coli, genetic interaction, Gram-negative bacteria, homologous recombination, network, synthetic lethality or sickness, suppression
Isolation of Fidelity Variants of RNA Viruses and Characterization of Virus Mutation Frequency
Institutions: Institut Pasteur .
RNA viruses use RNA dependent RNA polymerases to replicate their genomes. The intrinsically high error rate of these enzymes is a large contributor to the generation of extreme population diversity that facilitates virus adaptation and evolution. Increasing evidence shows that the intrinsic error rates, and the resulting mutation frequencies, of RNA viruses can be modulated by subtle amino acid changes to the viral polymerase. Although biochemical assays exist for some viral RNA polymerases that permit quantitative measure of incorporation fidelity, here we describe a simple method of measuring mutation frequencies of RNA viruses that has proven to be as accurate as biochemical approaches in identifying fidelity altering mutations. The approach uses conventional virological and sequencing techniques that can be performed in most biology laboratories. Based on our experience with a number of different viruses, we have identified the key steps that must be optimized to increase the likelihood of isolating fidelity variants and generating data of statistical significance. The isolation and characterization of fidelity altering mutations can provide new insights into polymerase structure and function1-3
. Furthermore, these fidelity variants can be useful tools in characterizing mechanisms of virus adaptation and evolution4-7
Immunology, Issue 52, Polymerase fidelity, RNA virus, mutation frequency, mutagen, RNA polymerase, viral evolution
Characterization of Complex Systems Using the Design of Experiments Approach: Transient Protein Expression in Tobacco as a Case Study
Institutions: RWTH Aachen University, Fraunhofer Gesellschaft.
Plants provide multiple benefits for the production of biopharmaceuticals including low costs, scalability, and safety. Transient expression offers the additional advantage of short development and production times, but expression levels can vary significantly between batches thus giving rise to regulatory concerns in the context of good manufacturing practice. We used a design of experiments (DoE) approach to determine the impact of major factors such as regulatory elements in the expression construct, plant growth and development parameters, and the incubation conditions during expression, on the variability of expression between batches. We tested plants expressing a model anti-HIV monoclonal antibody (2G12) and a fluorescent marker protein (DsRed). We discuss the rationale for selecting certain properties of the model and identify its potential limitations. The general approach can easily be transferred to other problems because the principles of the model are broadly applicable: knowledge-based parameter selection, complexity reduction by splitting the initial problem into smaller modules, software-guided setup of optimal experiment combinations and step-wise design augmentation. Therefore, the methodology is not only useful for characterizing protein expression in plants but also for the investigation of other complex systems lacking a mechanistic description. The predictive equations describing the interconnectivity between parameters can be used to establish mechanistic models for other complex systems.
Bioengineering, Issue 83, design of experiments (DoE), transient protein expression, plant-derived biopharmaceuticals, promoter, 5'UTR, fluorescent reporter protein, model building, incubation conditions, monoclonal antibody
An Affordable HIV-1 Drug Resistance Monitoring Method for Resource Limited Settings
Institutions: University of KwaZulu-Natal, Durban, South Africa, Jembi Health Systems, University of Amsterdam, Stanford Medical School.
HIV-1 drug resistance has the potential to seriously compromise the effectiveness and impact of antiretroviral therapy (ART). As ART programs in sub-Saharan Africa continue to expand, individuals on ART should be closely monitored for the emergence of drug resistance. Surveillance of transmitted drug resistance to track transmission of viral strains already resistant to ART is also critical. Unfortunately, drug resistance testing is still not readily accessible in resource limited settings, because genotyping is expensive and requires sophisticated laboratory and data management infrastructure. An open access genotypic drug resistance monitoring method to manage individuals and assess transmitted drug resistance is described. The method uses free open source software for the interpretation of drug resistance patterns and the generation of individual patient reports. The genotyping protocol has an amplification rate of greater than 95% for plasma samples with a viral load >1,000 HIV-1 RNA copies/ml. The sensitivity decreases significantly for viral loads <1,000 HIV-1 RNA copies/ml. The method described here was validated against a method of HIV-1 drug resistance testing approved by the United States Food and Drug Administration (FDA), the Viroseq genotyping method. Limitations of the method described here include the fact that it is not automated and that it also failed to amplify the circulating recombinant form CRF02_AG from a validation panel of samples, although it amplified subtypes A and B from the same panel.
Medicine, Issue 85, Biomedical Technology, HIV-1, HIV Infections, Viremia, Nucleic Acids, genetics, antiretroviral therapy, drug resistance, genotyping, affordable
Identification of Metabolically Active Bacteria in the Gut of the Generalist Spodoptera littoralis via DNA Stable Isotope Probing Using 13C-Glucose
Institutions: Max Planck Institute for Chemical Ecology.
Guts of most insects are inhabited by complex communities of symbiotic nonpathogenic bacteria. Within such microbial communities it is possible to identify commensal or mutualistic bacteria species. The latter ones, have been observed to serve multiple functions to the insect, i.e.
helping in insect reproduction1
, boosting the immune response2
, pheromone production3
, as well as nutrition, including the synthesis of essential amino acids4,
Due to the importance of these associations, many efforts have been made to characterize the communities down to the individual members. However, most of these efforts were either based on cultivation methods or relied on the generation of 16S rRNA gene fragments which were sequenced for final identification. Unfortunately, these approaches only identified the bacterial species present in the gut and provided no information on the metabolic activity of the microorganisms.
To characterize the metabolically active bacterial species in the gut of an insect, we used stable isotope probing (SIP) in vivo
C-glucose as a universal substrate. This is a promising culture-free technique that allows the linkage of microbial phylogenies to their particular metabolic activity. This is possible by tracking stable, isotope labeled atoms from substrates into microbial biomarkers, such as DNA and RNA5
. The incorporation of 13
C isotopes into DNA increases the density of the labeled DNA compared to the unlabeled (12
C) one. In the end, the 13
C-labeled DNA or RNA is separated by density-gradient ultracentrifugation from the 12
C-unlabeled similar one6
. Subsequent molecular analysis of the separated nucleic acid isotopomers provides the connection between metabolic activity and identity of the species.
Here, we present the protocol used to characterize the metabolically active bacteria in the gut of a generalist insect (our model system), Spodoptera littoralis
). The phylogenetic analysis of the DNA was done using pyrosequencing, which allowed high resolution and precision in the identification of insect gut bacterial community. As main substrate, 13
C-labeled glucose was used in the experiments. The substrate was fed to the insects using an artificial diet.
Microbiology, Issue 81, Insects, Sequence Analysis, Genetics, Microbial, Bacteria, Lepidoptera, Spodoptera littoralis, stable-isotope-probing (SIP), pyro-sequencing, 13C-glucose, gut, microbiota, bacteria
Annotation of Plant Gene Function via Combined Genomics, Metabolomics and Informatics
Given the ever expanding number of model plant species for which complete genome sequences are available and the abundance of bio-resources such as knockout mutants, wild accessions and advanced breeding populations, there is a rising burden for gene functional annotation. In this protocol, annotation of plant gene function using combined co-expression gene analysis, metabolomics and informatics is provided (Figure 1
). This approach is based on the theory of using target genes of known function to allow the identification of non-annotated genes likely to be involved in a certain metabolic process, with the identification of target compounds via metabolomics. Strategies are put forward for applying this information on populations generated by both forward and reverse genetics approaches in spite of none of these are effortless. By corollary this approach can also be used as an approach to characterise unknown peaks representing new or specific secondary metabolites in the limited tissues, plant species or stress treatment, which is currently the important trial to understanding plant metabolism.
Plant Biology, Issue 64, Genetics, Bioinformatics, Metabolomics, Plant metabolism, Transcriptome analysis, Functional annotation, Computational biology, Plant biology, Theoretical biology, Spectroscopy and structural analysis
From Voxels to Knowledge: A Practical Guide to the Segmentation of Complex Electron Microscopy 3D-Data
Institutions: Lawrence Berkeley National Laboratory, Lawrence Berkeley National Laboratory, Lawrence Berkeley National Laboratory.
Modern 3D electron microscopy approaches have recently allowed unprecedented insight into the 3D ultrastructural organization of cells and tissues, enabling the visualization of large macromolecular machines, such as adhesion complexes, as well as higher-order structures, such as the cytoskeleton and cellular organelles in their respective cell and tissue context. Given the inherent complexity of cellular volumes, it is essential to first extract the features of interest in order to allow visualization, quantification, and therefore comprehension of their 3D organization. Each data set is defined by distinct characteristics, e.g.
, signal-to-noise ratio, crispness (sharpness) of the data, heterogeneity of its features, crowdedness of features, presence or absence of characteristic shapes that allow for easy identification, and the percentage of the entire volume that a specific region of interest occupies. All these characteristics need to be considered when deciding on which approach to take for segmentation.
The six different 3D ultrastructural data sets presented were obtained by three different imaging approaches: resin embedded stained electron tomography, focused ion beam- and serial block face- scanning electron microscopy (FIB-SEM, SBF-SEM) of mildly stained and heavily stained samples, respectively. For these data sets, four different segmentation approaches have been applied: (1) fully manual model building followed solely by visualization of the model, (2) manual tracing segmentation of the data followed by surface rendering, (3) semi-automated approaches followed by surface rendering, or (4) automated custom-designed segmentation algorithms followed by surface rendering and quantitative analysis. Depending on the combination of data set characteristics, it was found that typically one of these four categorical approaches outperforms the others, but depending on the exact sequence of criteria, more than one approach may be successful. Based on these data, we propose a triage scheme that categorizes both objective data set characteristics and subjective personal criteria for the analysis of the different data sets.
Bioengineering, Issue 90, 3D electron microscopy, feature extraction, segmentation, image analysis, reconstruction, manual tracing, thresholding
Unraveling the Unseen Players in the Ocean - A Field Guide to Water Chemistry and Marine Microbiology
Institutions: San Diego State University, University of California San Diego.
Here we introduce a series of thoroughly tested and well standardized research protocols adapted for use in remote marine environments. The sampling protocols include the assessment of resources available to the microbial community (dissolved organic carbon, particulate organic matter, inorganic nutrients), and a comprehensive description of the viral and bacterial communities (via direct viral and microbial counts, enumeration of autofluorescent microbes, and construction of viral and microbial metagenomes). We use a combination of methods, which represent a dispersed field of scientific disciplines comprising already established protocols and some of the most recent techniques developed. Especially metagenomic sequencing techniques used for viral and bacterial community characterization, have been established only in recent years, and are thus still subjected to constant improvement. This has led to a variety of sampling and sample processing procedures currently in use. The set of methods presented here provides an up to date approach to collect and process environmental samples. Parameters addressed with these protocols yield the minimum on information essential to characterize and understand the underlying mechanisms of viral and microbial community dynamics. It gives easy to follow guidelines to conduct comprehensive surveys and discusses critical steps and potential caveats pertinent to each technique.
Environmental Sciences, Issue 93, dissolved organic carbon, particulate organic matter, nutrients, DAPI, SYBR, microbial metagenomics, viral metagenomics, marine environment
A PCR-based Genotyping Method to Distinguish Between Wild-type and Ornamental Varieties of Imperata cylindrica
Institutions: The University of Alabama, Huntsville, Center for Plant Health Science and Technology.
Wild-type I. cylindrica
(cogongrass) is one of the top ten worst invasive plants in the world, negatively impacting agricultural and natural resources in 73 different countries throughout Africa, Asia, Europe, New Zealand, Oceania and the Americas1-2
. Cogongrass forms rapidly-spreading, monodominant stands that displace a large variety of native plant species and in turn threaten the native animals that depend on the displaced native plant species for forage and shelter. To add to the problem, an ornamental variety [I. cylindrica
(Retzius)] is widely marketed under the names of Imperata cylindrica
'Rubra', Red Baron, and Japanese blood grass (JBG). This variety is putatively sterile and noninvasive and is considered a desirable ornamental for its red-colored leaves. However, under the correct conditions, JBG can produce viable seed (Carol Holko, 2009 personal communication) and can revert to a green invasive form that is often indistinguishable from cogongrass as it takes on the distinguishing characteristics of the wild-type invasive variety4
). This makes identification using morphology a difficult task even for well-trained plant taxonomists. Reversion of JBG to an aggressive green phenotype is also not a rare occurrence. Using sequence comparisons of coding and variable regions in both nuclear and chloroplast DNA, we have confirmed that JBG has reverted to the green invasive within the states of Maryland, South Carolina, and Missouri. JBG has been sold and planted in just about every state in the continental U.S. where there is not an active cogongrass infestation. The extent of the revert problem in not well understood because reverted plants are undocumented and often destroyed.
Application of this molecular protocol provides a method to identify JBG reverts and can help keep these varieties from co-occurring and possibly hybridizing. Cogongrass is an obligate outcrosser and, when crossed with a different genotype, can produce viable wind-dispersed seeds that spread cogongrass over wide distances5-7
. JBG has a slightly different genotype than cogongrass and may be able to form viable hybrids with cogongrass. To add to the problem, JBG is more cold and shade tolerant than cogongrass8-10
, and gene flow between these two varieties is likely to generate hybrids that are more aggressive, shade tolerant, and cold hardy than wild-type cogongrass. While wild-type cogongrass currently infests over 490 million hectares worldwide, in the Southeast U.S. it infests over 500,000 hectares and is capable of occupying most of the U.S. as it rapidly spreads northward due to its broad niche and geographic potential3,7,11
. The potential of a genetic crossing is a serious concern for the USDA-APHIS Federal Noxious Week Program. Currently, the USDA-APHIS prohibits JBG in states where there are major cogongrass infestations (e.g., Florida, Alabama, Mississippi). However, preventing the two varieties from combining can prove more difficult as cogongrass and JBG expand their distributions. Furthermore, the distribution of the JBG revert is currently unknown and without the ability to identify these varieties through morphology, some cogongrass infestations may be the result of JBG reverts. Unfortunately, current molecular methods of identification typically rely on AFLP (Amplified Fragment Length Polymorphisms) and DNA sequencing, both of which are time consuming and costly. Here, we present the first cost-effective and reliable PCR-based molecular genotyping method to accurately distinguish between cogongrass and JBG revert.
Molecular Biology, Issue 60, Molecular genotyping, Japanese blood grass, Red Baron, cogongrass, invasive plants
Choice and No-Choice Assays for Testing the Resistance of A. thaliana to Chewing Insects
Institutions: Cornell University.
Larvae of the small white cabbage butterfly are a pest in agricultural settings. This caterpillar species feeds from plants in the cabbage family, which include many crops such as cabbage, broccoli, Brussel sprouts etc. Rearing of the insects takes place on cabbage plants in the greenhouse. At least two cages are needed for the rearing of Pieris rapae. One for the larvae and the other to contain the adults, the butterflies. In order to investigate the role of plant hormones and toxic plant chemicals in resistance to this insect pest, we demonstrate two experiments. First, determination of the role of jasmonic acid (JA - a plant hormone often indicated in resistance to insects) in resistance to the chewing insect Pieris rapae. Caterpillar growth can be compared on wild-type and mutant plants impaired in production of JA. This experiment is considered "No Choice", because larvae are forced to subsist on a single plant which synthesizes or is deficient in JA. Second, we demonstrate an experiment that investigates the role of glucosinolates, which are used as oviposition (egg-laying) signals. Here, we use WT and mutant Arabidopsis impaired in glucosinolate production in a "Choice" experiment in which female butterflies are allowed to choose to lay their eggs on plants of either genotype. This video demonstrates the experimental setup for both assays as well as representative results.
Plant Biology, Issue 15, Annual Review, Plant Resistance, Herbivory, Arabidopsis thaliana, Pieris rapae, Caterpillars, Butterflies, Jasmonic Acid, Glucosinolates
Testing Nicotine Tolerance in Aphids Using an Artificial Diet Experiment
Institutions: Cornell University.
Plants may upregulate the production of many different seconday metabolites in response to insect feeding. One of these metabolites, nicotine, is well know to have insecticidal properties. One response of tobacco plants to herbivory, or being gnawed upon by insects, is to increase the production of this neurotoxic alkaloid. Here, we will demonstrate how to set up an experiment to address this question of whether a tobacco-adapted strain of the green peach aphid, Myzus persicae, can tolerate higher levels of nicotine than the a strain of this insect that does not infest tobacco in the field.
Plant Biology, Issue 15, Annual Review, Nicotine, Aphids, Plant Feeding Resistance, Tobacco