Societies of highly social animals feature vast lifespan differences between closely related individuals. Among social insects, the honey bee is the best established model to study how plasticity in lifespan and aging is explained by social factors.
The worker caste of honey bees includes nurse bees, which tend the brood, and forager bees, which collect nectar and pollen. Previous work has shown that brain functions and flight performance senesce more rapidly in foragers than in nurses. However, brain functions can recover, when foragers revert back to nursing tasks. Such patterns of accelerated and reversed functional senescence are linked to changed metabolic resource levels, to alterations in protein abundance and to immune function. Vitellogenin, a yolk protein with adapted functions in hormonal control and cellular defense, may serve as a major regulatory element in a network that controls the different aging dynamics in workers.
Here we describe how the emergence of nurses and foragers can be monitored, and manipulated, including the reversal from typically short-lived foragers into longer-lived nurses. Our representative results show how individuals with similar chronological age differentiate into foragers and nurse bees under experimental conditions. We exemplify how behavioral reversal from foragers back to nurses can be validated. Last, we show how different cellular senescence can be assessed by measuring the accumulation of lipofuscin, a universal biomarker of senescence.
For studying mechanisms that may link social influences and aging plasticity, this protocol provides a standardized tool set to acquire relevant sample material, and to improve data comparability among future studies.
19 Related JoVE Articles!
Protein WISDOM: A Workbench for In silico De novo Design of BioMolecules
Institutions: Princeton University.
The aim of de novo
protein design is to find the amino acid sequences that will fold into a desired 3-dimensional structure with improvements in specific properties, such as binding affinity, agonist or antagonist behavior, or stability, relative to the native sequence. Protein design lies at the center of current advances drug design and discovery. Not only does protein design provide predictions for potentially useful drug targets, but it also enhances our understanding of the protein folding process and protein-protein interactions. Experimental methods such as directed evolution have shown success in protein design. However, such methods are restricted by the limited sequence space that can be searched tractably. In contrast, computational design strategies allow for the screening of a much larger set of sequences covering a wide variety of properties and functionality. We have developed a range of computational de novo
protein design methods capable of tackling several important areas of protein design. These include the design of monomeric proteins for increased stability and complexes for increased binding affinity.
To disseminate these methods for broader use we present Protein WISDOM (https://www.proteinwisdom.org), a tool that provides automated methods for a variety of protein design problems. Structural templates are submitted to initialize the design process. The first stage of design is an optimization sequence selection stage that aims at improving stability through minimization of potential energy in the sequence space. Selected sequences are then run through a fold specificity stage and a binding affinity stage. A rank-ordered list of the sequences for each step of the process, along with relevant designed structures, provides the user with a comprehensive quantitative assessment of the design. Here we provide the details of each design method, as well as several notable experimental successes attained through the use of the methods.
Genetics, Issue 77, Molecular Biology, Bioengineering, Biochemistry, Biomedical Engineering, Chemical Engineering, Computational Biology, Genomics, Proteomics, Protein, Protein Binding, Computational Biology, Drug Design, optimization (mathematics), Amino Acids, Peptides, and Proteins, De novo protein and peptide design, Drug design, In silico sequence selection, Optimization, Fold specificity, Binding affinity, sequencing
Cortical Source Analysis of High-Density EEG Recordings in Children
Institutions: UCL Institute of Child Health, University College London.
EEG is traditionally described as a neuroimaging technique with high temporal and low spatial resolution. Recent advances in biophysical modelling and signal processing make it possible to exploit information from other imaging modalities like structural MRI that provide high spatial resolution to overcome this constraint1
. This is especially useful for investigations that require high resolution in the temporal as well as spatial domain. In addition, due to the easy application and low cost of EEG recordings, EEG is often the method of choice when working with populations, such as young children, that do not tolerate functional MRI scans well. However, in order to investigate which neural substrates are involved, anatomical information from structural MRI is still needed. Most EEG analysis packages work with standard head models that are based on adult anatomy. The accuracy of these models when used for children is limited2
, because the composition and spatial configuration of head tissues changes dramatically over development3
In the present paper, we provide an overview of our recent work in utilizing head models based on individual structural MRI scans or age specific head models to reconstruct the cortical generators of high density EEG. This article describes how EEG recordings are acquired, processed, and analyzed with pediatric populations at the London Baby Lab, including laboratory setup, task design, EEG preprocessing, MRI processing, and EEG channel level and source analysis.
Behavior, Issue 88, EEG, electroencephalogram, development, source analysis, pediatric, minimum-norm estimation, cognitive neuroscience, event-related potentials
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
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
Generation of Enterobacter sp. YSU Auxotrophs Using Transposon Mutagenesis
Institutions: Youngstown State University.
Prototrophic bacteria grow on M-9 minimal salts medium supplemented with glucose (M-9 medium), which is used as a carbon and energy source. Auxotrophs can be generated using a transposome. The commercially available, Tn5
-derived transposome used in this protocol consists of a linear segment of DNA containing an R6Kγ
replication origin, a gene for kanamycin resistance and two mosaic sequence ends, which serve as transposase binding sites. The transposome, provided as a DNA/transposase protein complex, is introduced by electroporation into the prototrophic strain, Enterobacter
sp. YSU, and randomly incorporates itself into this host’s genome. Transformants are replica plated onto Luria-Bertani agar plates containing kanamycin, (LB-kan) and onto M-9 medium agar plates containing kanamycin (M-9-kan). The transformants that grow on LB-kan plates but not on M-9-kan plates are considered to be auxotrophs. Purified genomic DNA from an auxotroph is partially digested, ligated and transformed into a pir+ Escherichia coli
) strain. The R6Kγ
replication origin allows the plasmid to replicate in pir+ E. coli
strains, and the kanamycin resistance marker allows for plasmid selection. Each transformant possesses a new plasmid containing the transposon flanked by the interrupted chromosomal region. Sanger sequencing and the Basic Local Alignment Search Tool (BLAST) suggest a putative identity of the interrupted gene. There are three advantages to using this transposome mutagenesis strategy. First, it does not rely on the expression of a transposase gene by the host. Second, the transposome is introduced into the target host by electroporation, rather than by conjugation or by transduction and therefore is more efficient. Third, the R6Kγ
replication origin makes it easy to identify the mutated gene which is partially recovered in a recombinant plasmid. This technique can be used to investigate the genes involved in other characteristics of Enterobacter
sp. YSU or of a wider variety of bacterial strains.
Microbiology, Issue 92, Auxotroph, transposome, transposon, mutagenesis, replica plating, glucose minimal medium, complex medium, Enterobacter
Mouse Genome Engineering Using Designer Nucleases
Institutions: University of Zurich, University of Minnesota.
Transgenic mice carrying site-specific genome modifications (knockout, knock-in) are of vital importance for dissecting complex biological systems as well as for modeling human diseases and testing therapeutic strategies. Recent advances in the use of designer nucleases such as zinc finger nucleases (ZFNs), transcription activator-like effector nucleases (TALENs), and the clustered regularly interspaced short palindromic repeats (CRISPR)/CRISPR-associated (Cas) 9 system for site-specific genome engineering open the possibility to perform rapid targeted genome modification in virtually any laboratory species without the need to rely on embryonic stem (ES) cell technology. A genome editing experiment typically starts with identification of designer nuclease target sites within a gene of interest followed by construction of custom DNA-binding domains to direct nuclease activity to the investigator-defined genomic locus. Designer nuclease plasmids are in vitro
transcribed to generate mRNA for microinjection of fertilized mouse oocytes. Here, we provide a protocol for achieving targeted genome modification by direct injection of TALEN mRNA into fertilized mouse oocytes.
Genetics, Issue 86, Oocyte microinjection, Designer nucleases, ZFN, TALEN, Genome Engineering
Detecting Somatic Genetic Alterations in Tumor Specimens by Exon Capture and Massively Parallel Sequencing
Institutions: Memorial Sloan-Kettering Cancer Center, Memorial Sloan-Kettering Cancer Center.
Efforts to detect and investigate key oncogenic mutations have proven valuable to facilitate the appropriate treatment for cancer patients. The establishment of high-throughput, massively parallel "next-generation" sequencing has aided the discovery of many such mutations. To enhance the clinical and translational utility of this technology, platforms must be high-throughput, cost-effective, and compatible with formalin-fixed paraffin embedded (FFPE) tissue samples that may yield small amounts of degraded or damaged DNA. Here, we describe the preparation of barcoded and multiplexed DNA libraries followed by hybridization-based capture of targeted exons for the detection of cancer-associated mutations in fresh frozen and FFPE tumors by massively parallel sequencing. This method enables the identification of sequence mutations, copy number alterations, and select structural rearrangements involving all targeted genes. Targeted exon sequencing offers the benefits of high throughput, low cost, and deep sequence coverage, thus conferring high sensitivity for detecting low frequency mutations.
Molecular Biology, Issue 80, Molecular Diagnostic Techniques, High-Throughput Nucleotide Sequencing, Genetics, Neoplasms, Diagnosis, Massively parallel sequencing, targeted exon sequencing, hybridization capture, cancer, FFPE, DNA mutations
Test Samples for Optimizing STORM Super-Resolution Microscopy
Institutions: National Physical Laboratory.
STORM is a recently developed super-resolution microscopy technique with up to 10 times better resolution than standard fluorescence microscopy techniques. However, as the image is acquired in a very different way than normal, by building up an image molecule-by-molecule, there are some significant challenges for users in trying to optimize their image acquisition. In order to aid this process and gain more insight into how STORM works we present the preparation of 3 test samples and the methodology of acquiring and processing STORM super-resolution images with typical resolutions of between 30-50 nm. By combining the test samples with the use of the freely available rainSTORM processing software it is possible to obtain a great deal of information about image quality and resolution. Using these metrics it is then possible to optimize the imaging procedure from the optics, to sample preparation, dye choice, buffer conditions, and image acquisition settings. We also show examples of some common problems that result in poor image quality, such as lateral drift, where the sample moves during image acquisition and density related problems resulting in the 'mislocalization' phenomenon.
Molecular Biology, Issue 79, Genetics, Bioengineering, Biomedical Engineering, Biophysics, Basic Protocols, HeLa Cells, Actin Cytoskeleton, Coated Vesicles, Receptor, Epidermal Growth Factor, Actins, Fluorescence, Endocytosis, Microscopy, STORM, super-resolution microscopy, nanoscopy, cell biology, fluorescence microscopy, test samples, resolution, actin filaments, fiducial markers, epidermal growth factor, cell, imaging
A Practical Guide to Phylogenetics for Nonexperts
Institutions: The George Washington University.
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.
Basic Protocol, Issue 84, phylogenetics, multiple sequence alignments, phylogenetic tree, BLAST executables, basic local alignment search tool, Bayesian models
Identification of Key Factors Regulating Self-renewal and Differentiation in EML Hematopoietic Precursor Cells by RNA-sequencing Analysis
Institutions: The University of Texas Graduate School of Biomedical Sciences at Houston.
Hematopoietic stem cells (HSCs) are used clinically for transplantation treatment to rebuild a patient's hematopoietic system in many diseases such as leukemia and lymphoma. Elucidating the mechanisms controlling HSCs self-renewal and differentiation is important for application of HSCs for research and clinical uses. However, it is not possible to obtain large quantity of HSCs due to their inability to proliferate in vitro
. To overcome this hurdle, we used a mouse bone marrow derived cell line, the EML (Erythroid, Myeloid, and Lymphocytic) cell line, as a model system for this study.
RNA-sequencing (RNA-Seq) has been increasingly used to replace microarray for gene expression studies. We report here a detailed method of using RNA-Seq technology to investigate the potential key factors in regulation of EML cell self-renewal and differentiation. The protocol provided in this paper is divided into three parts. The first part explains how to culture EML cells and separate Lin-CD34+ and Lin-CD34- cells. The second part of the protocol offers detailed procedures for total RNA preparation and the subsequent library construction for high-throughput sequencing. The last part describes the method for RNA-Seq data analysis and explains how to use the data to identify differentially expressed transcription factors between Lin-CD34+ and Lin-CD34- cells. The most significantly differentially expressed transcription factors were identified to be the potential key regulators controlling EML cell self-renewal and differentiation. In the discussion section of this paper, we highlight the key steps for successful performance of this experiment.
In summary, this paper offers a method of using RNA-Seq technology to identify potential regulators of self-renewal and differentiation in EML cells. The key factors identified are subjected to downstream functional analysis in vitro
and in vivo
Genetics, Issue 93, EML Cells, Self-renewal, Differentiation, Hematopoietic precursor cell, RNA-Sequencing, Data analysis
RNA-seq Analysis of Transcriptomes in Thrombin-treated and Control Human Pulmonary Microvascular Endothelial Cells
Institutions: Children's Mercy Hospital and Clinics, School of Medicine, University of Missouri-Kansas City.
The characterization of gene expression in cells via measurement of mRNA levels is a useful tool in determining how the transcriptional machinery of the cell is affected by external signals (e.g.
drug treatment), or how cells differ between a healthy state and a diseased state. With the advent and continuous refinement of next-generation DNA sequencing technology, RNA-sequencing (RNA-seq) has become an increasingly popular method of transcriptome analysis to catalog all species of transcripts, to determine the transcriptional structure of all expressed genes and to quantify the changing expression levels of the total set of transcripts in a given cell, tissue or organism1,2
. RNA-seq is gradually replacing DNA microarrays as a preferred method for transcriptome analysis because it has the advantages of profiling a complete transcriptome, providing a digital type datum (copy number of any transcript) and not relying on any known genomic sequence3
Here, we present a complete and detailed protocol to apply RNA-seq to profile transcriptomes in human pulmonary microvascular endothelial cells with or without thrombin treatment. This protocol is based on our recent published study entitled "RNA-seq Reveals Novel Transcriptome of Genes and Their Isoforms in Human Pulmonary Microvascular Endothelial Cells Treated with Thrombin,"4
in which we successfully performed the first complete transcriptome analysis of human pulmonary microvascular endothelial cells treated with thrombin using RNA-seq. It yielded unprecedented resources for further experimentation to gain insights into molecular mechanisms underlying thrombin-mediated endothelial dysfunction in the pathogenesis of inflammatory conditions, cancer, diabetes, and coronary heart disease, and provides potential new leads for therapeutic targets to those diseases.
The descriptive text of this protocol is divided into four parts. The first part describes the treatment of human pulmonary microvascular endothelial cells with thrombin and RNA isolation, quality analysis and quantification. The second part describes library construction and sequencing. The third part describes the data analysis. The fourth part describes an RT-PCR validation assay. Representative results of several key steps are displayed. Useful tips or precautions to boost success in key steps are provided in the Discussion section. Although this protocol uses human pulmonary microvascular endothelial cells treated with thrombin, it can be generalized to profile transcriptomes in both mammalian and non-mammalian cells and in tissues treated with different stimuli or inhibitors, or to compare transcriptomes in cells or tissues between a healthy state and a disease state.
Genetics, Issue 72, Molecular Biology, Immunology, Medicine, Genomics, Proteins, RNA-seq, Next Generation DNA Sequencing, Transcriptome, Transcription, Thrombin, Endothelial cells, high-throughput, DNA, genomic DNA, RT-PCR, PCR
Detection of Rare Genomic Variants from Pooled Sequencing Using SPLINTER
Institutions: Washington University School of Medicine, Washington University School of Medicine, Washington University School of Medicine.
As DNA sequencing technology has markedly advanced in recent years2
, it has become increasingly evident that the amount of genetic variation between any two individuals is greater than previously thought3
. In contrast, array-based genotyping has failed to identify a significant contribution of common sequence variants to the phenotypic variability of common disease4,5
. Taken together, these observations have led to the evolution of the Common Disease / Rare Variant hypothesis suggesting that the majority of the "missing heritability" in common and complex phenotypes is instead due to an individual's personal profile of rare or private DNA variants6-8
. However, characterizing how rare variation impacts complex phenotypes requires the analysis of many affected individuals at many genomic loci, and is ideally compared to a similar survey in an unaffected cohort. Despite the sequencing power offered by today's platforms, a population-based survey of many genomic loci and the subsequent computational analysis required remains prohibitive for many investigators.
To address this need, we have developed a pooled sequencing approach1,9
and a novel software package1
for highly accurate rare variant detection from the resulting data. The ability to pool genomes from entire populations of affected individuals and survey the degree of genetic variation at multiple targeted regions in a single sequencing library provides excellent cost and time savings to traditional single-sample sequencing methodology. With a mean sequencing coverage per allele of 25-fold, our custom algorithm, SPLINTER, uses an internal variant calling control strategy to call insertions, deletions and substitutions up to four base pairs in length with high sensitivity and specificity from pools of up to 1 mutant allele in 500 individuals. Here we describe the method for preparing the pooled sequencing library followed by step-by-step instructions on how to use the SPLINTER package for pooled sequencing analysis (https://www.ibridgenetwork.org/wustl/splinter). We show a comparison between pooled sequencing of 947 individuals, all of whom also underwent genome-wide array, at over 20kb of sequencing per person. Concordance between genotyping of tagged and novel variants called in the pooled sample were excellent. This method can be easily scaled up to any number of genomic loci and any number of individuals. By incorporating the internal positive and negative amplicon controls at ratios that mimic the population under study, the algorithm can be calibrated for optimal performance. This strategy can also be modified for use with hybridization capture or individual-specific barcodes and can be applied to the sequencing of naturally heterogeneous samples, such as tumor DNA.
Genetics, Issue 64, Genomics, Cancer Biology, Bioinformatics, Pooled DNA sequencing, SPLINTER, rare genetic variants, genetic screening, phenotype, high throughput, computational analysis, DNA, PCR, primers
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
A Protocol for Computer-Based Protein Structure and Function Prediction
Institutions: University of Michigan , University of Kansas.
Genome sequencing projects have ciphered millions of protein sequence, which require knowledge of their structure and function to improve the understanding of their biological role. Although experimental methods can provide detailed information for a small fraction of these proteins, computational modeling is needed for the majority of protein molecules which are experimentally uncharacterized. The I-TASSER server is an on-line workbench for high-resolution modeling of protein structure and function. Given a protein sequence, a typical output from the I-TASSER server includes secondary structure prediction, predicted solvent accessibility of each residue, homologous template proteins detected by threading and structure alignments, up to five full-length tertiary structural models, and structure-based functional annotations for enzyme classification, Gene Ontology terms and protein-ligand binding sites. All the predictions are tagged with a confidence score which tells how accurate the predictions are without knowing the experimental data. To facilitate the special requests of end users, the server provides channels to accept user-specified inter-residue distance and contact maps to interactively change the I-TASSER modeling; it also allows users to specify any proteins as template, or to exclude any template proteins during the structure assembly simulations. The structural information could be collected by the users based on experimental evidences or biological insights with the purpose of improving the quality of I-TASSER predictions. The server was evaluated as the best programs for protein structure and function predictions in the recent community-wide CASP experiments. There are currently >20,000 registered scientists from over 100 countries who are using the on-line I-TASSER server.
Biochemistry, Issue 57, On-line server, I-TASSER, protein structure prediction, function prediction
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
Genomic MRI - a Public Resource for Studying Sequence Patterns within Genomic DNA
Institutions: University of Toledo Health Science Campus.
Non-coding genomic regions in complex eukaryotes, including intergenic areas, introns, and untranslated segments of exons, are profoundly non-random in their nucleotide composition and consist of a complex mosaic of sequence patterns. These patterns include so-called Mid-Range Inhomogeneity (MRI) regions -- sequences 30-10000 nucleotides in length that are enriched by a particular base or combination of bases (e.g. (G+T)-rich, purine-rich, etc.). MRI regions are associated with unusual (non-B-form) DNA structures that are often involved in regulation of gene expression, recombination, and other genetic processes (Fedorova & Fedorov 2010). The existence of a strong fixation bias within MRI regions against mutations that tend to reduce their sequence inhomogeneity additionally supports the functionality and importance of these genomic sequences (Prakash et al.
Here we demonstrate a freely available Internet resource -- the Genomic MRI
program package -- designed for computational analysis of genomic sequences in order to find and characterize various MRI patterns within them (Bechtel et al.
2008). This package also allows generation of randomized sequences with various properties and level of correspondence to the natural input DNA sequences. The main goal of this resource is to facilitate examination of vast regions of non-coding DNA that are still scarcely investigated and await thorough exploration and recognition.
Genetics, Issue 51, bioinformatics, computational biology, genomics, non-randomness, signals, gene regulation, DNA conformation
Multiple-mouse Neuroanatomical Magnetic Resonance Imaging
Institutions: Hospital for Sick Children, University of Toronto.
The field of mouse phenotyping with magnetic resonance imaging (MRI) is rapidly growing, motivated by the need for improved tools for characterizing and evaluating mouse models of human disease. MRI is an excellent modality for investigating genetically altered animals. It is capable of whole brain coverage, can be used in vivo
, and provides multiple contrast mechanisms for investigating different aspects of neuranatomy and physiology. The advent of high-field scanners along with the ability to scan multiple mice simultaneously allows for rapid phenotyping of novel mutations.
Effective mouse MRI studies require attention to many aspects of experiment design. In this article, we will describe general methods to acquire quality images for mouse phenotyping using a system that images mice concurrently in shielded transmit/receive radio frequency (RF) coils in a common magnet (Bock et al.
, 2003). We focus particularly on anatomical phenotyping, an important and accessible application that has shown a high potential for impact in many mouse models at our imaging centre. Before we can provide the detailed steps to acquire such images, there are important practical considerations for both in vivo
brain imaging (Dazai et al.
, 2004) and ex vivo
brain imaging (Spring et al.
, 2007) that should be noted. These are discussed below.
Neuroscience, Issue 48, magnetic resonance imaging, mouse, phenotyping, mouse handling, monitoring, brain, multiple mouse imaging
Using SCOPE to Identify Potential Regulatory Motifs in Coregulated Genes
Institutions: Dartmouth College.
SCOPE is an ensemble motif finder that uses three component algorithms in parallel to identify potential regulatory motifs by over-representation and motif position preference1
. Each component algorithm is optimized to find a different kind of motif. By taking the best of these three approaches, SCOPE performs better than any single algorithm, even in the presence of noisy data1
. In this article, we utilize a web version of SCOPE2
to examine genes that are involved in telomere maintenance. SCOPE has been incorporated into at least two other motif finding programs3,4
and has been used in other studies5-8
The three algorithms that comprise SCOPE are BEAM9
, which finds non-degenerate motifs (ACCGGT), PRISM10
, which finds degenerate motifs (ASCGWT), and SPACER11
, which finds longer bipartite motifs (ACCnnnnnnnnGGT). These three algorithms have been optimized to find their corresponding type of motif. Together, they allow SCOPE to perform extremely well.
Once a gene set has been analyzed and candidate motifs identified, SCOPE can look for other genes that contain the motif which, when added to the original set, will improve the motif score. This can occur through over-representation or motif position preference. Working with partial gene sets that have biologically verified transcription factor binding sites, SCOPE was able to identify most of the rest of the genes also regulated by the given transcription factor.
Output from SCOPE shows candidate motifs, their significance, and other information both as a table and as a graphical motif map. FAQs and video tutorials are available at the SCOPE web site which also includes a "Sample Search" button that allows the user to perform a trial run.
Scope has a very friendly user interface that enables novice users to access the algorithm's full power without having to become an expert in the bioinformatics of motif finding. As input, SCOPE can take a list of genes, or FASTA sequences. These can be entered in browser text fields, or read from a file. The output from SCOPE contains a list of all identified motifs with their scores, number of occurrences, fraction of genes containing the motif, and the algorithm used to identify the motif. For each motif, result details include a consensus representation of the motif, a sequence logo, a position weight matrix, and a list of instances for every motif occurrence (with exact positions and "strand" indicated). Results are returned in a browser window and also optionally by email. Previous papers describe the SCOPE algorithms in detail1,2,9-11
Genetics, Issue 51, gene regulation, computational biology, algorithm, promoter sequence motif
Molecular Evolution of the Tre Recombinase
Institutions: Max Plank Institute for Molecular Cell Biology and Genetics, Dresden.
Here we report the generation of Tre recombinase through directed, molecular evolution. Tre recombinase recognizes a pre-defined target sequence within the LTR sequences of the HIV-1 provirus, resulting in the excision and eradication of the provirus from infected human cells.
We started with Cre, a 38-kDa recombinase, that recognizes a 34-bp double-stranded DNA sequence known as loxP. Because Cre can effectively eliminate genomic sequences, we set out to tailor a recombinase that could remove the sequence between the 5'-LTR and 3'-LTR of an integrated HIV-1 provirus. As a first step we identified sequences within the LTR sites that were similar to loxP and tested for recombination activity. Initially Cre and mutagenized Cre libraries failed to recombine the chosen loxLTR sites of the HIV-1 provirus. As the start of any directed molecular evolution process requires at least residual activity, the original asymmetric loxLTR sequences were split into subsets and tested again for recombination activity. Acting as intermediates, recombination activity was shown with the subsets. Next, recombinase libraries were enriched through reiterative evolution cycles. Subsequently, enriched libraries were shuffled and recombined. The combination of different mutations proved synergistic and recombinases were created that were able to recombine loxLTR1 and loxLTR2. This was evidence that an evolutionary strategy through intermediates can be successful. After a total of 126 evolution cycles individual recombinases were functionally and structurally analyzed. The most active recombinase -- Tre -- had 19 amino acid changes as compared to Cre. Tre recombinase was able to excise the HIV-1 provirus from the genome HIV-1 infected HeLa cells (see "HIV-1 Proviral DNA Excision Using an Evolved Recombinase", Hauber J., Heinrich-Pette-Institute for Experimental Virology and Immunology, Hamburg, Germany). While still in its infancy, directed molecular evolution will allow the creation of custom enzymes that will serve as tools of "molecular surgery" and molecular medicine.
Cell Biology, Issue 15, HIV-1, Tre recombinase, Site-specific recombination, molecular evolution