During spermatogenesis in mammals and in Drosophila melanogaster, male germ cells develop in a series of essential developmental processes. This includes differentiation from a stem cell population, mitotic amplification, and meiosis. In addition, post-meiotic germ cells undergo a dramatic morphological reshaping process as well as a global epigenetic reconfiguration of the germ line chromatin—the histone-to-protamine switch.
Studying the role of a protein in post-meiotic spermatogenesis using mutagenesis or other genetic tools is often impeded by essential embryonic, pre-meiotic, or meiotic functions of the protein under investigation. The post-meiotic phenotype of a mutant of such a protein could be obscured through an earlier developmental block, or the interpretation of the phenotype could be complicated. The model organism Drosophila melanogaster offers a bypass to this problem: intact testes and even cysts of germ cells dissected from early pupae are able to develop ex vivo in culture medium. Making use of such cultures allows microscopic imaging of living germ cells in testes and of germ-line cysts. Importantly, the cultivated testes and germ cells also become accessible to pharmacological inhibitors, thereby permitting manipulation of enzymatic functions during spermatogenesis, including post-meiotic stages.
The protocol presented describes how to dissect and cultivate pupal testes and germ-line cysts. Information on the development of pupal testes and culture conditions are provided alongside microscope imaging data of live testes and germ-line cysts in culture. We also describe a pharmacological assay to study post-meiotic spermatogenesis, exemplified by an assay targeting the histone-to-protamine switch using the histone acetyltransferase inhibitor anacardic acid. In principle, this cultivation method could be adapted to address many other research questions in pre- and post-meiotic spermatogenesis.
15 Related JoVE Articles!
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
The ChroP Approach Combines ChIP and Mass Spectrometry to Dissect Locus-specific Proteomic Landscapes of Chromatin
Institutions: European Institute of Oncology.
Chromatin is a highly dynamic nucleoprotein complex made of DNA and proteins that controls various DNA-dependent processes. Chromatin structure and function at specific regions is regulated by the local enrichment of histone post-translational modifications (hPTMs) and variants, chromatin-binding proteins, including transcription factors, and DNA methylation. The proteomic characterization of chromatin composition at distinct functional regions has been so far hampered by the lack of efficient protocols to enrich such domains at the appropriate purity and amount for the subsequent in-depth analysis by Mass Spectrometry (MS). We describe here a newly designed chromatin proteomics strategy, named ChroP (Chromatin Proteomics
), whereby a preparative chromatin immunoprecipitation is used to isolate distinct chromatin regions whose features, in terms of hPTMs, variants and co-associated non-histonic proteins, are analyzed by MS. We illustrate here the setting up of ChroP for the enrichment and analysis of transcriptionally silent heterochromatic regions, marked by the presence of tri-methylation of lysine 9 on histone H3. The results achieved demonstrate the potential of ChroP
in thoroughly characterizing the heterochromatin proteome and prove it as a powerful analytical strategy for understanding how the distinct protein determinants of chromatin interact and synergize to establish locus-specific structural and functional configurations.
Biochemistry, Issue 86, chromatin, histone post-translational modifications (hPTMs), epigenetics, mass spectrometry, proteomics, SILAC, chromatin immunoprecipitation , histone variants, chromatome, hPTMs cross-talks
Specificity Analysis of Protein Lysine Methyltransferases Using SPOT Peptide Arrays
Institutions: Stuttgart University.
Lysine methylation is an emerging post-translation modification and it has been identified on several histone and non-histone proteins, where it plays crucial roles in cell development and many diseases. Approximately 5,000 lysine methylation sites were identified on different proteins, which are set by few dozens of protein lysine methyltransferases. This suggests that each PKMT methylates multiple proteins, however till now only one or two substrates have been identified for several of these enzymes. To approach this problem, we have introduced peptide array based substrate specificity analyses of PKMTs. Peptide arrays are powerful tools to characterize the specificity of PKMTs because methylation of several substrates with different sequences can be tested on one array. We synthesized peptide arrays on cellulose membrane using an Intavis SPOT synthesizer and analyzed the specificity of various PKMTs. Based on the results, for several of these enzymes, novel substrates could be identified. For example, for NSD1 by employing peptide arrays, we showed that it methylates K44 of H4 instead of the reported H4K20 and in addition H1.5K168 is the highly preferred substrate over the previously known H3K36. Hence, peptide arrays are powerful tools to biochemically characterize the PKMTs.
Biochemistry, Issue 93, Peptide arrays, solid phase peptide synthesis, SPOT synthesis, protein lysine methyltransferases, substrate specificity profile analysis, lysine methylation
Double Fluorescence in situ Hybridization in Fresh Brain Sections
Institutions: University of Rochester, University of Rochester.
Here we describe a modified version of a double fluorescence in situ
hybridization (dFISH) method optimized for detecting two mRNAs of interest in fresh frozen brain sections. Our group has successfully used this approach to study gene co-regulation. More specifically, we have used this dFISH method to explore the anatomical organization, neurochemical properties, and the impact of sensory experience in central sensory circuits, at single cell resolution. This protocol has been validated in brain tissue from mice, rats and songbirds but is expected to be easily adaptable to other vertebrate species, as well as to an array of non-neural tissues. In this film we provide a detailed demonstration of the main steps of this procedure.
Neuroscience, Issue 42, Fluorescence in situ hybridization (FISH), double FISH (dFISH), digoxigenin, biotin, non-radioactive riboprobes, vertebrate brain
Detection of Post-translational Modifications on Native Intact Nucleosomes by ELISA
Institutions: Stanford University , University of Connecticut, University of Connecticut.
The genome of eukaryotes exists as chromatin which contains both DNA and proteins. The fundamental unit of chromatin is the nucleosome, which contains 146 base pairs of DNA associated with two each of histones H2A, H2B, H3, and H41
. The N-terminal tails of histones are rich in lysine and arginine and are modified post-transcriptionally by acetylation, methylation, and other post-translational modifications (PTMs). The PTM configuration of nucleosomes can affect the transcriptional activity of associated DNA, thus providing a mode of gene regulation that is epigenetic in nature 2,3
. We developed a method called nucleosome ELISA (NU-ELISA) to quantitatively determine global PTM signatures of nucleosomes extracted from cells. NU-ELISA is more sensitive and quantitative than western blotting, and is useful to interrogate the epiproteomic state of specific cell types. This video journal article shows detailed procedures to perform NU-ELISA analysis.
Cellular Biology, Issue 50, Chromatin, Nucleosome, Epigenetics, ELISA, Histone, Modification, Methylation, Acetylation
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
Detection of Architectural Distortion in Prior Mammograms via Analysis of Oriented Patterns
Institutions: University of Calgary , University of Calgary .
We demonstrate methods for the detection of architectural distortion in prior mammograms of interval-cancer cases based on analysis of the orientation of breast tissue patterns in mammograms. We hypothesize that architectural distortion modifies the normal orientation of breast tissue patterns in mammographic images before the formation of masses or tumors. In the initial steps of our methods, the oriented structures in a given mammogram are analyzed using Gabor filters and phase portraits to detect node-like sites of radiating or intersecting tissue patterns. Each detected site is then characterized using the node value, fractal dimension, and a measure of angular dispersion specifically designed to represent spiculating patterns associated with architectural distortion.
Our methods were tested with a database of 106 prior mammograms of 56 interval-cancer cases and 52 mammograms of 13 normal cases using the features developed for the characterization of architectural distortion, pattern classification via
quadratic discriminant analysis, and validation with the leave-one-patient out procedure. According to the results of free-response receiver operating characteristic analysis, our methods have demonstrated the capability to detect architectural distortion in prior mammograms, taken 15 months (on the average) before clinical diagnosis of breast cancer, with a sensitivity of 80% at about five false positives per patient.
Medicine, Issue 78, Anatomy, Physiology, Cancer Biology, angular spread, architectural distortion, breast cancer, Computer-Assisted Diagnosis, computer-aided diagnosis (CAD), entropy, fractional Brownian motion, fractal dimension, Gabor filters, Image Processing, Medical Informatics, node map, oriented texture, Pattern Recognition, phase portraits, prior mammograms, spectral analysis
Methods to Identify the NMR Resonances of the 13C-Dimethyl N-terminal Amine on Reductively Methylated Proteins
Institutions: Louisiana State University.
Nuclear magnetic resonance (NMR) spectroscopy is a proven technique for protein structure and dynamic studies. To study proteins with NMR, stable magnetic isotopes are typically incorporated metabolically to improve the sensitivity and allow for sequential resonance assignment. Reductive 13
C-methylation is an alternative labeling method for proteins that are not amenable to bacterial host over-expression, the most common method of isotope incorporation. Reductive 13
C-methylation is a chemical reaction performed under mild conditions that modifies a protein's primary amino groups (lysine ε-amino groups and the N
-terminal α-amino group) to 13
C-dimethylamino groups. The structure and function of most proteins are not altered by the modification, making it a viable alternative to metabolic labeling. Because reductive 13
C-methylation adds sparse, isotopic labels, traditional methods of assigning the NMR signals are not applicable. An alternative assignment method using mass spectrometry (MS) to aid in the assignment of protein 13
C-dimethylamine NMR signals has been developed. The method relies on partial and different amounts of 13
C-labeling at each primary amino group. One limitation of the method arises when the protein's N
-terminal residue is a lysine because the α- and ε-dimethylamino groups of Lys1 cannot be individually measured with MS. To circumvent this limitation, two methods are described to identify the NMR resonance of the 13
C-dimethylamines associated with both the N
-terminal α-amine and the side chain ε-amine. The NMR signals of the N
-terminal α-dimethylamine and the side chain ε-dimethylamine of hen egg white lysozyme, Lys1, are identified in 1
C heteronuclear single-quantum coherence spectra.
Chemistry, Issue 82, Boranes, Formaldehyde, Dimethylamines, Tandem Mass Spectrometry, nuclear magnetic resonance, MALDI-TOF, Reductive methylation, lysozyme, dimethyllysine, mass spectrometry, NMR
Detection of Histone Modifications in Plant Leaves
Institutions: RWTH Aachen University, RWTH Aachen University, Leibniz University.
Chromatin structure is important for the regulation of gene expression in eukaryotes. In this process, chromatin remodeling, DNA methylation, and covalent modifications on the amino-terminal tails of histones H3 and H4 play essential roles1-2
. H3 and H4 histone modifications include methylation of lysine and arginine, acetylation of lysine, and phosphorylation of serine residues1-2
. These modifications are associated either with gene activation, repression, or a primed state of gene that supports more rapid and robust activation of expression after perception of appropriate signals (microbe-associated molecular patterns, light, hormones, etc.)3-7
Here, we present a method for the reliable and sensitive detection of specific chromatin modifications on selected plant genes. The technique is based on the crosslinking of (modified) histones and DNA with formaldehyde8,9
, extraction and sonication of chromatin, chromatin immunoprecipitation (ChIP) with modification-specific antibodies9,10
, de-crosslinking of histone-DNA complexes, and gene-specific real-time quantitative PCR. The approach has proven useful for detecting specific histone modifications associated with C4
photosynthesis in maize5,11
and systemic immunity in Arabidopsis3
Molecular Biology, Issue 55, chromatin, chromatin immunoprecipitation, ChIP, histone modifications, PCR, plant molecular biology, plant promoter control, gene regulation
Perceptual and Category Processing of the Uncanny Valley Hypothesis' Dimension of Human Likeness: Some Methodological Issues
Institutions: University of Zurich.
Mori's Uncanny Valley Hypothesis1,2
proposes that the perception of humanlike characters such as robots and, by extension, avatars (computer-generated characters) can evoke negative or positive affect (valence) depending on the object's degree of visual and behavioral realism along a dimension of human likeness
) (Figure 1
). But studies of affective valence of subjective responses to variously realistic non-human characters have produced inconsistent findings 3, 4, 5, 6
. One of a number of reasons for this is that human likeness is not perceived as the hypothesis assumes. While the DHL can be defined following Mori's description as a smooth linear change in the degree of physical humanlike similarity, subjective perception of objects along the DHL can be understood in terms of the psychological effects of categorical perception (CP) 7
. Further behavioral and neuroimaging investigations of category processing and CP along the DHL and of the potential influence of the dimension's underlying category structure on affective experience are needed. This protocol therefore focuses on the DHL and allows examination of CP. Based on the protocol presented in the video as an example, issues surrounding the methodology in the protocol and the use in "uncanny" research of stimuli drawn from morph continua to represent the DHL are discussed in the article that accompanies the video. The use of neuroimaging and morph stimuli to represent the DHL in order to disentangle brain regions neurally responsive to physical human-like similarity from those responsive to category change and category processing is briefly illustrated.
Behavior, Issue 76, Neuroscience, Neurobiology, Molecular Biology, Psychology, Neuropsychology, uncanny valley, functional magnetic resonance imaging, fMRI, categorical perception, virtual reality, avatar, human likeness, Mori, uncanny valley hypothesis, perception, magnetic resonance imaging, MRI, imaging, clinical techniques
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
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
Fluorescence-based Monitoring of PAD4 Activity via a Pro-fluorescence Substrate Analog
Institutions: Lehigh University.
Post-translational modifications may lead to altered protein functional states by increasing the covalent variations on the side chains of many protein substrates. The histone tails represent one of the most heavily modified stretches within all human proteins. Peptidyl-arginine deiminase 4 (PAD4) has been shown to convert arginine residues into the non-genetically encoded citrulline residue. Few assays described to date have been operationally facile with satisfactory sensitivity. Thus, the lack of adequate assays has likely contributed to the absence of potent non-covalent PAD4 inhibitors. Herein a novel fluorescence-based assay that allows for the monitoring of PAD4 activity is described. A pro-fluorescent substrate analog was designed to link PAD4 enzymatic activity to fluorescence liberation upon the addition of the protease trypsin. It was shown that the assay is compatible with high-throughput screening conditions and has a strong signal-to-noise ratio. Furthermore, the assay can also be performed with crude cell lysates containing over-expressed PAD4.
Chemistry, Issue 93, PAD4, PADI4, citrullination, arginine, post-translational modification, HTS, assay, fluorescence, citrulline
Preparation of Primary Neurons for Visualizing Neurites in a Frozen-hydrated State Using Cryo-Electron Tomography
Institutions: Baylor College of Medicine, Baylor College of Medicine, University of California at San Diego, Baylor College of Medicine.
Neurites, both dendrites and axons, are neuronal cellular processes that enable the conduction of electrical impulses between neurons. Defining the structure of neurites is critical to understanding how these processes move materials and signals that support synaptic communication. Electron microscopy (EM) has been traditionally used to assess the ultrastructural features within neurites; however, the exposure to organic solvent during dehydration and resin embedding can distort structures. An important unmet goal is the formulation of procedures that allow for structural evaluations not impacted by such artifacts.
Here, we have established a detailed and reproducible protocol for growing and flash-freezing whole neurites of different primary neurons on electron microscopy grids followed by their examination with cryo-electron tomography (cryo-ET). This technique allows for 3-D visualization of frozen, hydrated neurites at nanometer resolution, facilitating assessment of their morphological differences. Our protocol yields an unprecedented view of dorsal root ganglion (DRG) neurites, and a visualization of hippocampal neurites in their near-native state. As such, these methods create a foundation for future studies on neurites of both normal neurons and those impacted by neurological disorders.
Neuroscience, Issue 84, Neurons, Cryo-electron Microscopy, Electron Microscope Tomography, Brain, rat, primary neuron culture, morphological assay
Automated Midline Shift and Intracranial Pressure Estimation based on Brain CT Images
Institutions: Virginia Commonwealth University, Virginia Commonwealth University Reanimation Engineering Science (VCURES) Center, Virginia Commonwealth University, Virginia Commonwealth University, Virginia Commonwealth University.
In this paper we present an automated system based mainly on the computed tomography (CT) images consisting of two main components: the midline shift estimation and intracranial pressure (ICP) pre-screening system. To estimate the midline shift, first an estimation of the ideal midline is performed based on the symmetry of the skull and anatomical features in the brain CT scan. Then, segmentation of the ventricles from the CT scan is performed and used as a guide for the identification of the actual midline through shape matching. These processes mimic the measuring process by physicians and have shown promising results in the evaluation. In the second component, more features are extracted related to ICP, such as the texture information, blood amount from CT scans and other recorded features, such as age, injury severity score to estimate the ICP are also incorporated. Machine learning techniques including feature selection and classification, such as Support Vector Machines (SVMs), are employed to build the prediction model using RapidMiner. The evaluation of the prediction shows potential usefulness of the model. The estimated ideal midline shift and predicted ICP levels may be used as a fast pre-screening step for physicians to make decisions, so as to recommend for or against invasive ICP monitoring.
Medicine, Issue 74, Biomedical Engineering, Molecular Biology, Neurobiology, Biophysics, Physiology, Anatomy, Brain CT Image Processing, CT, Midline Shift, Intracranial Pressure Pre-screening, Gaussian Mixture Model, Shape Matching, Machine Learning, traumatic brain injury, TBI, imaging, clinical techniques