We cordially thank the ITS2 group, Biocenter, University of W&uuml;rzburg, for rich and valuable feedback. We also thank the Deutsche Forschungsgemeinschaft (DFG; grant Mu-2831/1-1) for funding.

1. Correct Annotation of ITS2 Sequence
<ol>
 <li> Access the ITS2 Database phylogeny workbench here: <a href="http://its2.bioapps.biozentrum.uni-wuerzburg.de" target="_blank">http://its2.bioapps.biozentrum.uni-wuerzburg.de</a> </li>
 <li> Begin your analysis by clicking the "Annotate" icon in the section "Tools." Then, type or paste your sequence into the sequence editor at the top of the website. The sequence editor automatically checks, whether your ITS2 sequences are valid. </li>
 <li> Choose an HMM model suitable for your sequences (e.g. Viridiplantae for plants). </li>
 <li> Start the process by clicking "Annotate." </li>
 <li> By hovering over the "Hybridize" icon you can view an image of the 5.8S and 28S rRNA hybrid as a confirmation of the HMM annotation&#x2019;s accuracy. </li>
 <li> Click on the green plus sign of the resulting ITS2 sequence to select your way of secondary structure prediction: To predict the structure without a known template, click on "Predict structure." If you want to use your own template for the Homology Modeling, click "Model structure." </li>
</ol>
2. Secondary Structure Prediction
<ol>
 <li>Predict
 <ol>
 <li> The annotated ITS2 sequence is automatically pasted into the sequence editor. </li>
 <li> To start the secondary structure prediction with default settings, click the "Predict structures" button. </li>
 <li>Save the resulting ITS2 sequence including the modeled secondary structure into the data pool by clicking on the green plus sign and then "Add to pool." Alternatively, you can add it to your data pool via drag and drop (Figure 1). </li>
 <li>If the sequence could not fold directly, the best results of the homology modeling are shown. Save the most suitable sequence-structure via drag and drop to the data pool. Alternatively, save the sequence-structure into the data pool with a right click and then a click on "Add to pool." </li>
 </ol>
 </li>
 <li> Custom Modeling
 <ol>
 <li> Type or paste one or multiple templates (with known structure) into the upper sequence editor. </li>
 <li> Type or paste one or multiple target sequences (without structure) into the lower sequence editor. </li>
 <li> Click on "Predict best template(s)" to start the Homology Modeling with default settings. </li>
 <li> The best template-target combinations are shown in the resulting list. </li>
 <li> Save the modeled sequence-structure(s) of your choice either via drag and drop to the data pool or by a right click and a click on "Add to pool." </li>
 </ol>
 </li>
</ol>
3. Motif Search
<ol>
 <li> Type or paste your query sequence(s) into the sequence editor at the top of the website. </li>
 <li> Choose the correct HMM model (e.g. Viridiplantae for plants).
 3.3. Click on "Motif search" to start the process. </li>
 <li> ITS2 sequences with highlighted motifs are illustrated at the bottom of the website.</li>
 <li> Click on the icon beside the sequence header to display the motifs highlighted in the secondary structure. </li>
</ol>
4. Search and Browse
<ol>
 <li> Search
 <ol>
 <li> Type either a taxon name or a GenBank Identifier (GI) into the search field at the top of the website.</li>
 <li> A search by taxon name is supported by an appearing live-search box. </li>
 <li> You can perform a multiple search by comma-separating your queries. </li>
 <li> Click the "Search" button to execute the search. </li>
 <li> Your results appear listed in a new tab. </li>
 <li> Click on a column name to sort your results according to the particular column. You can also add or remove columns of your choice with the column menu. The column menu can be entered with a click on the appearing arrow icon within a column name. </li>
 <li> Click on "Show details" to view the details of a sequence-structure. </li>
 <li> Save the sequence-structure(s) of your choice either via drag and drop to the data pool or by a right click and a click on "Add to pool."</li>
 <li> To save your results to an external file, click on "Save selection" or "Save all." </li>
 </ol>
 </li>
 <li> Browse
 <ol>
 <li> Browse the ITS2 Database by navigating through the tree-like structure at the left of the website. </li>
 <li> Click on a plus-sign to view the taxa one level lower.</li>
 <li> Click on a taxon name to open a new tab containing each sequence-structure of the taxon.</li>
 <li> Click on "Show details" to view the details of a sequence-structure pair. </li>
 <li> Save the sequence-structure(s) of your choice either via drag and drop to the data pool or by a right click and a click on "Add to pool." </li>
 <li> To save your results to an external file, click on "Save selection" or "Save all." </li>
 </ol>
 </li>
</ol>
5. ITS2 Blast
<ol>
 <li> Type or paste one or multiple query sequences into the sequence editor. Your sequences may either be plain nucleotide sequences or sequence-structure pairs. You can also type several secondary structures below one sequence. By checking the box "Serialize XXFASTA sequences" these structures are used subsequently as individual queries. </li>
 <li> To start BLAST with default settings, click on "Blast." Depending on the nature of your query, either a common BLASTN or the ITS2 sequence-structure BLAST is performed. </li>
 <li> A sub-tab is opened for each query sequence within the appearing tab "BLAST Results," as well as an overview of the executed searches. </li>
 <li> Click on "Show Alignments" to view the calculated BLAST alignments. </li>
 <li> Save the BLAST hits of your choice either via drag and drop to the data pool or by a right click and a click on "Add to pool." </li>
 <li> To save your results to an external file, click on "Save selection" or "Save all." </li>
</ol>
6. Multiple Sequence-structure Alignment
<ol>
 <li> Take a look at your data pool by clicking "Manage dataset" and then the magnifying glass symbol right next to the number of sequences in your pool. Alternatively, you can click on the data pool sign at the bottom left of the website. </li>
 <li> Click on a sequence-structure pair in your data pool to view its details. </li>
 <li> To create a multiple sequence-structure alignment of all sequence-structure pairs in your pool, click on "Analyze dataset" and then "Sequence &amp; Structure." </li>
 <li> Now you are asked to select the graphic mode of your alignment. If your alignment contains only a few sequences, decline the slim mode by clicking "No." Otherwise choose the slim graphic mode by clicking "Yes." </li>
 <li> In a few moments, your alignment is shown in a new tab (Figure 2). Moreover, it is automatically saved to the data pool. </li>
 <li> To save your alignment to an external file, click on "Save alignment." </li>
</ol>
7. Phylogenetic Tree
<ol>
 <li>To calculate a sequence-structure based Neighbor Joining tree of your multiple alignment, click on "Analyze Dataset" and then "Neighbor Joining." </li>
 <li> The resulting tree is illustrated in a new tab (Figure 3). </li>
 <li> Scale your tree freely with the scroll bar "Zoom tree." </li>
 <li> Reroot your tree by clicking on a node or leaf of the tree and then "Reroot at this node." </li>
 <li> If you want to remove a taxon from your data pool, click on the leaf and choose "Remove this node from pool." Now you can recalculate your alignment and tree with the reduced taxon sampling. </li>
 <li> Click on "Save tree" to save your phylogenetic tree as a final result of your analysis to an external NEWICK file. </li>
</ol>
8. Additional Software
<ol>
 <li>Click on "About this website"-"Tools" to find additional information about the stand-alone tools 4SALE and ProfDistS.</li>
 <li>Beside the alignment and Neighbor Joining function provided by the ITS2 Database web interface, you can now access several new functions, e.g. species delimitation based on compensatory base changes (CBCs). </li>
</ol>
9. Representative Results
The workflow as described above has successfully been applied in several open access surveys3,4. Examples can be viewed through the following links:
<ul>
 <li><a href="http://www.plosone.org/article/info%3Adoi/10.1371/journal.pone.0016931" target="_blank"> http://www.plosone.org/article/info%3Adoi%2F10.1371%2Fjournal.pone.0016931</a></li>
 <li><a href="http://www.biomedcentral.com/1756-0500/3/320" target="_blank"> http://www.biomedcentral.com/1756-0500/3/320</a> </li>
</ul>
In these large scale studies, we were able to resolve the phylogeny of Chlorophyta as well as Hypnales (Bryophyta) with high resolution. In both cases, an exhaustive taxon sampling was gathered from the ITS2 Database9, automatically aligned with 4SALE15,16 and lastly processed by ProfDistS17 into a phylogenetic tree. In all these steps, sequence and structure information were used simultaneously. Bootstrap support for the phylogenetic backbone was achieved using Profile Neighbor Joining (PNJ)19, which is available in the stand-alone version of ProfDistS.
For a smaller set of sequence-structure pairs, figures 1 to 3 describe the key steps of this automated workflow5 directly on the new ITS2 Database workbench: taxon sampling, the multiple sequence-structure alignment and eventually the phylogenetic tree calculation.
<img src="/files/ftp_upload/3806/3806fig1.jpg" alt="Figure 1" /> 
Figure 1. Taxon sampling per drag and drop. At any time sequences or sequence-structure pairs can be added to the data pool, for instance via drag and drop. Here a sequence-structure is added using drag and drop after secondary structure prediction. The blue ellipse marks the area where the sequence-structure is dropped into the data pool. <a href="https://www.jove.com/files/ftp_upload/3806/3806fig1large.jpg" target="_blank">Click here to view the full-sized version of this image.</a>
<img src="/files/ftp_upload/3806/3806fig2.jpg" alt="Figure 2" /> 
Figure 2. Multiple sequence-structure alignment in full graphic mode. For the few sequences in the data pool, the full graphic mode was chosen. Bases are colored; base pairs can be highlighted with red circles by clicking on one base or bracket of a base pair. <a href="https://www.jove.com/files/ftp_upload/3806/3806fig2large.jpg" target="_blank">Click here to view the full-sized version of this image.</a> 
<img src="/files/ftp_upload/3806/3806fig3.jpg" alt="Figure 3" /> 
Figure 3. Sequence-structure Neighbor Joining tree. The freely scalable tree calculated of a seven taxa multiple sequence-structure alignment can be saved in the NEWICK format.

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No conflicts of interest declared.

The ITS2 Database is a complete and fully functional workbench for internal transcribed spacer 2 sequence-structure-based phylogenetics. The website can be operated very fast and intuitively. While other web-based phylogeny workbenches like ARB20 or Mobyle21 are only able to work on sequence and/or consensus structure information, the ITS2 Database9 considers sequences and individual secondary structures for each taxon simultaneously. However, due to limitations in the computational capacity of the web server, it is highly recommended to use the stand-alone tools for multiple alignment and Neighbor Joining18 calculation, 4SALE15,16 and ProfDistS17, respectively, for large datasets. Beside the basic ITS2 sequence-structure phylogeny workflow5, these tools feature several additional functions, like calculating bootstrap replicates, Profile Neighbor Joining (PNJ)19 or species delimitation based on compensatory base changes (CBCs)8. They can be accessed through the "About this website"-"Tools" section for download and detailed information. To use 4SALE and ProfDistS, it is necessary to always bring files into the correct format. A taxon sampling to be processed by 4SALE must have the ending .fasta or .txt, whereas the sequence-structure alignment as an input for ProfDistS must end with .xfasta.
We are currently implementing alternative methods for phylogenetic tree reconstruction in the ITS2 database as well as in the related tools. Thus, methods like sequence-structure-based Maximum Parsimony22 and/or Maximum Likelihood23 will be accessible in the future.

<table border="1">
	<tbody>
		<tr>
			<td>Name of the reagent</td>
			<td>Company</td>
			<td>Comments</td>
		</tr>
		<tr>
			<td>Internet access</td>
			<td>&nbsp;</td>
			<td>Preferably high-speed</td>
		</tr>
		<tr>
			<td>ITS2 Database9</td>
			<td>Department of Bioinformatics, University of W&uuml;rzburg</td>
			<td>Website: <a href="http://its2.bioapps.biozentrum.uni-wuerzburg.de" target="_blank">http://its2.bioapps.biozentrum.uni-wuerzburg.de</a></td>
		</tr>
		<tr>
			<td>Software: 4SALE15,16</td>
			<td>Department of Bioinformatics, University of W&uuml;rzburg</td>
			<td>Download: <a href="http://4sale.bioapps.biozentrum.uni-wuerzburg.de/" target="_blank">http://4sale.bioapps.biozentrum.uni-wuerzburg.de/</a></td>
		</tr>
		<tr>
			<td>Software: ProfDistS17</td>
			<td>Department of Bioinformatics, University of W&uuml;rzburg</td>
			<td>Download: <a href="http://profdist.bioapps.biozentrum.uni-wuerzburg.de/" target="_blank">http://profdist.bioapps.biozentrum.uni-wuerzburg.de/</a></td>
		</tr>
	</tbody>
</table>

the its2 database

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 accurately reannotated10. 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 and ProfDistS17 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.

Watch this Scientific Journal Video about The ITS2 Database at JoVE.com

The ITS2 Database

The ITS2 Database is a workbench for phylogenetic inference simultaneously considering sequence and secondary structure of the internal transcribed spacer 2. This includes data collection with accurate annotation, structure prediction, multiple sequence-structure alignment and fast tree calculation. In a nutshell, this workbench simplifies first phylogenetic analyses to a few clicks.

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 ...

Research

JoVE Journal

Biology

30.4K Views.  University of Würzburg. The ITS2 Database is a workbench for phylogenetic inference simultaneously considering sequence and secondary structure of the internal transcribed spacer 2. This includes data collection with accurate annotation, structure prediction, multiple sequence-structure alignment and fast tree calculation. In a nutshell, this workbench simplifies first phylogenetic analyses to a few clicks.

Video: The ITS2 Database

Photobleaching Assays (FRAP &amp; FLIP) to Measure Chromatin Protein Dynamics in Living Embryonic Stem Cells

Fluorescence Recovery After Photobleaching (FRAP) and Fluorescence Loss In Photobleaching (FLIP) enable the study of protein dynamics in living cells with good spatial and temporal resolution. Here we describe how to perform FRAP and FLIP assays of chromatin proteins, including H1 and HP1, in mouse embryonic stem (ES) cells. In a FRAP experiment, cells are transfected, either transiently or stably, with a protein of interest fused with the green fluorescent protein (GFP) or derivatives thereof (YFP, CFP, Cherry, etc.). In the transfected, fluorescing cells, an intense focused laser beam bleaches a relatively small region of interest (ROI). The laser wavelength is selected according to the fluorescent protein used for fusion. The laser light irreversibly bleaches the fluorescent signal of molecules in the ROI and, immediately following bleaching, the recovery of the fluorescent signal in the bleached area - mediated by the replacement of the bleached molecules with the unbleached molecules - is monitored using time lapse imaging. The generated fluorescence recovery curves provide information on the protein's mobility. If the fluorescent molecules are immobile, no fluorescence recovery will be observed. In a complementary approach, Fluorescence Loss in Photobleaching (FLIP), the laser beam bleaches the same spot repeatedly and the signal intensity is measured elsewhere in the fluorescing cell. FLIP experiments therefore measure signal decay rather than fluorescence recovery and are useful to determine protein mobility as well as protein shuttling between cellular compartments. Transient binding is a common property of chromatin-associated proteins. Although the major fraction of each chromatin protein is bound to chromatin at any given moment at steady state, the binding is transient and most chromatin proteins have a high turnover on chromatin, with a residence time in the order of seconds. These properties are crucial for generating high plasticity in genome expression1. Photobleaching experiments are therefore particularly useful to determine chromatin plasticity using GFP-fusion versions of chromatin structural proteins, especially in ES cells, where the dynamic exchange of chromatin proteins (including heterochromatin protein 1 (HP1), linker histone H1 and core histones) is higher than in differentiated cells2,3.

Photobleaching Assays FRAP & FLIP to Measure Chromatin Protein Dynamics in Living Embryonic Stem Cells

We describe photobleaching methods including Fluorescence Recovery After Photobleaching (FRAP) and Fluorescence Loss In Photobleaching (FLIP) to monitor chromatin protein dynamics in embryonic stem (ES) cells. Chromatin protein dynamics, which is considered to be one of the means to study chromatin plasticity, is enhanced in pluripotent cells.

Fluorescence Recovery After Photobleaching (FRAP) and Fluorescence Loss In Photobleaching (FLIP) enable the study of protein dynamics in living cells with ...

Detection of Nitric Oxide and Superoxide Radical Anion by Electron Paramagnetic Resonance Spectroscopy from Cells using Spin Traps

Reactive nitrogen/oxygen species (ROS/RNS) at low concentrations play an important role in regulating cell function, signaling, and immune response but in unregulated concentrations are detrimental to cell viability1, 2. While living systems have evolved with endogenous and dietary antioxidant defense mechanisms to regulate ROS generation, ROS are produced continuously as natural by-products of normal metabolism of oxygen and can cause oxidative damage to biomolecules resulting in loss of protein function, DNA cleavage, or lipid peroxidation3, and ultimately to oxidative stress leading to cell injury or death4. 
Superoxide radical anion (O2&bull;-) is the major precursor of some of the most highly oxidizing species known to exist in biological systems such as peroxynitrite and hydroxyl radical. The generation of O2&bull;- signals the first sign of oxidative burst, and therefore, its detection and/or sequestration in biological systems is important. In this demonstration, O2&bull;- was generated from polymorphonuclear neutrophils (PMNs). Through chemotactic stimulation with phorbol-12-myristate-13-acetate (PMA), PMN generates O2&bull;- via activation of nicotinamide adenine dinucleotide phosphate (NADPH) oxidase5. 
Nitric oxide (NO) synthase which comes in three isoforms, as inducible-, neuronal- and endothelial-NOS, or iNOS, nNOS or eNOS, respectively, catalyzes the conversion of L- arginine to L-citrulline, using NADPH to produce NO6. Here, we generated NO from endothelial cells. Under oxidative stress conditions, eNOS for example can switch from producing NO to O2&bull;- in a process called uncoupling, which is believed to be caused by oxidation of heme7 or the co-factor, tetrahydrobiopterin (BH4)8.
There are only few reliable methods for the detection of free radicals in biological systems but are limited by specificity and sensitivity. Spin trapping is commonly used for the identification of free radicals and involves the addition reaction of a radical to a spin trap forming a persistent spin adduct which can be detected by electron paramagnetic resonance (EPR) spectroscopy. The various radical adducts exhibit distinctive spectrum which can be used to identify the radicals being generated and can provide a wealth of information about the nature and kinetics of radical production9.
The cyclic nitrones, 5,5-dimethyl-pyrroline-N-oxide, DMPO10, the phosphoryl-substituted DEPMPO11, and the ester-substituted, EMPO12 and BMPO13, have been widely employed as spin traps--the latter spin traps exhibiting longer half-lives for O2&bull;- adduct. Iron (II)-N-methyl-D-glucamine dithiocarbamate, Fe(MGD)2 is commonly used to trap NO due to high rate of adduct formation and the high stability of the spin adduct14.

Electron paramagnetic resonance (EPR) spectroscopy was employed to detect nitric oxide from bovine aortic endothelial cells and superoxide radical anion from human neutrophils using iron (II)-N-methyl-D-glucamine dithiocarbamate, Fe(MGD)2 and 5,5-dimethyl-1-pyroroline-N-oxide, DMPO, respectively.

Reactive nitrogen/oxygen species (ROS/RNS) at low concentrations play an important role in regulating cell function, signaling, and immune response but in ...

Isolation of Neonatal Extrahepatic Cholangiocytes

The intra and extrahepatic bile ducts of the liver are developmentally distinct, and may be differentially affected by certain diseases. However, differences between intra and extrahepatic cholangiocytes, and between neonatal and adult cells, are not well understood.
Methods for the isolation of cholangiocytes from intrahepatic bile ducts are well established1-4. Isolation of extrahepatic ductal cells, especially from the neonate, has not yet been described, although this would be of great benefit in understanding the differences between distinct cholangiocyte populations and in studying diseases such as biliary atresia that appear to target the extrahepatic ducts. Described here is an optimized technique to isolate both neonatal and adult mouse extrahepatic bile duct cells. This technique yields a pure cell population with minimal contamination from mesenchymal cells like fibroblasts.
This method is based on the removal of the extrahepatic ducts and gallbladder, followed by meticulous dissection and scraping to remove fat and fibroblast layers. Structures are embedded in thick layers of collagen and cultured for approximately 3 weeks to allow outgrowth of cholangiocytes in monolayers, which can then be trypsinized and re plated for experimental use.

A technique to isolate cholangiocytes from the extrahepatic bile ducts of neonatal mice is described. The ducts are meticulously dissected, and then cells are isolated by outgrowth in thick collagen gels. This method provides a useful tool for studying extrahepatic bile duct development and pathology.

The intra and extrahepatic bile ducts of the liver are developmentally distinct, and may be differentially affected by certain diseases. However, ...

Isolation of Murine Valve Endothelial Cells

Normal valve structures consist of stratified layers of specialized extracellular matrix (ECM) interspersed with valve interstitial cells (VICs) and surrounded by a monolayer of valve endothelial cells (VECs). VECs play essential roles in establishing the valve structures during embryonic development, and are important for maintaining life-long valve integrity and function. In contrast to a continuous endothelium over the surface of healthy valve leaflets, VEC disruption is commonly observed in malfunctioning valves and is associated with pathological processes that promote valve disease and dysfunction. Despite the clinical relevance, focused studies determining the contribution of VECs to development and disease processes are limited. The isolation of VECs from animal models would allow for cell-specific experimentation. VECs have been isolated from large animal adult models but due to their small population size, fragileness, and lack of specific markers, no reports of VEC isolations in embryos or adult small animal models have been reported. Here we describe a novel method that allows for the direct isolation of VECs from mice at embryonic and adult stages. Utilizing the Tie2-GFP reporter model that labels all endothelial cells with Green Fluorescent Protein (GFP), we have been successful in isolating GFP-positive (and negative) cells from the semilunar and atrioventricular valve regions using fluorescence activated cell sorting (FACS). Isolated GFP-positive VECs are enriched for endothelial markers, including CD31 and von Willebrand Factor (vWF), and retain endothelial cell expression when cultured; while, GFP-negative cells exhibit molecular profiles and cell shapes consistent with VIC phenotypes. The ability to isolate embryonic and adult murine VECs allows for previously unattainable molecular and functional studies to be carried out on a specific valve cell population, which will greatly improve our understanding of valve development and disease mechanisms.

The ability to isolate heart valve endothelial cells (VECs) is critical for understanding mechanisms of valve development, maintenance, and disease. Here we describe the isolation of VECs from embryonic and adult Tie2-GFP mice using FACS that will allow for studies determining the contribution of VECs in developmental and disease processes.

Normal valve structures consist of stratified layers of specialized extracellular matrix (ECM) interspersed with valve interstitial cells (VICs) and ...

Use of MALDI-TOF Mass Spectrometry and a Custom Database to Characterize Bacteria Indigenous to a Unique Cave Environment (Kartchner Caverns, AZ, USA)

MALDI-TOF mass spectrometry has been shown to be a rapid and reliable tool for identification of bacteria at the genus and species, and in some cases, strain levels. Commercially available and open source software tools have been developed to facilitate identification; however, no universal/standardized data analysis pipeline has been described in the literature. Here, we provide a comprehensive and detailed demonstration of bacterial identification procedures using a MALDI-TOF mass spectrometer. Mass spectra were collected from 15 diverse bacteria isolated from Kartchner Caverns, AZ, USA, and identified by 16S rDNA sequencing. Databases were constructed in BioNumerics 7.1. Follow-up analyses of mass spectra were performed, including cluster analyses, peak matching, and statistical analyses. Identification was performed using blind-coded samples randomly selected from these 15 bacteria. Two identification methods are presented: similarity coefficient-based and biomarker-based methods. Results show that both identification methods can identify the bacteria to the species level.

Use of MALDI-TOF Mass Spectrometry and a Custom Database to Characterize Bacteria Indigenous to a Unique Cave Environment Kartchner Caverns, AZ, USA

This work details procedures for rapid identification of bacteria using MALDI-TOF MS. The identification procedures include spectrum acquisition, database construction, and follow up analyses. Two identification methods, similarity coefficient-based and biomarker-based methods, are presented.

MALDI-TOF mass spectrometry has been shown to be a rapid and reliable tool for identification of bacteria at the genus and species, and in some cases, ...

Imaging Spatial Reorganization of a MAPK Signaling Pathway Using the Tobacco Transient Expression System

Visualization of dynamic signaling events in live cells has been a challenge. We expanded an established transient expression system, the biomolecular fluorescent complementation (BiFC) assay in tobacco epidermal cells, from testing protein-protein interaction to monitoring spatial distribution of signal transduction in plant cells. In this protocol, we used the BiFC assay to show that the interaction and the signaling between the Arabidopsis MAPKKK YODA and MAPK6 occur at the plasma membrane. When the scaffold protein BASL was co-expressed, the YODA-MAPK interaction redistributed and spatially co-polarized with CFP-BASL. This modified tobacco expression system allows for quick examination of signaling localization and dynamic changes (less than 4 days) and can accommodate multiple of fluorescent protein colors (at least three). We also presented detailed methods to quantify protein distribution (asymmetric spatial localization, or &#34;polarization&#34;) in tobacco cells. This advanced tobacco expression system has a potential to be used widely for quick testing of dynamic signaling events in live plant cells.

At the subcellular level, signaling events are dynamically modulated by developmental and environmental cues. Here we describe a protocol that employs the tobacco transient expression system to monitor dynamic protein-protein interaction and to disclose spatial organization of signal transduction in plant cells.

Visualization of dynamic signaling events in live cells has been a challenge. We expanded an established transient expression system, the biomolecular ...

Visualization and Quantification of Mesenchymal Cell Adipogenic Differentiation Potential with a Lineage Specific Marker

Several dyes are currently available for use in detecting differentiation of mesenchymal cells into adipocytes. Dyes, such as Oil Red O, are cheap, easy to use and widely utilized by laboratories analyzing the adipogenic potential of mesenchymal cells. However, they are not specific to changes in gene transcription. We have developed a gene-specific differentiation assay to analyze when a mesenchymal cell has switched its fate to an adipogenic lineage. Immuno-labelling against fatty acid binding protein-4 (FABP4), a lineage-specific marker of adipogenic differentiation, enabled visualization and quantification of differentiated cells. The ability to quantify adipogenic differentiation potential of mesenchymal cells in a 96 well microplate format has promising implications for a number of applications. Hundreds of clinical trials involve the use of adult mesenchymal stromal cells and it is currently difficult to correlate therapeutic outcomes within and especially between such clinical trials. This simple high-throughput FABP4 assay provides a quantitative assay for assessing the differentiation potential of patient-derived cells and is a robust tool for comparing different isolation and expansion methods. This is particularly important given the increasing recognition of the heterogeneity of the cells being administered to patients in mesenchymal cell products. The assay also has potential utility in high throughput drug screening, particularly in obesity and pre-diabetes research.

Traditional methods of assessing adipogenic differentiation are cheap and easy to use, but are not specific to changes in gene expression. We have developed an assay to quantify mesenchymal cell differentiation into mature adipocytes using a lineage specific marker. This assay has diverse applications across basic research and clinical medicine.

Several dyes are currently available for use in detecting differentiation of mesenchymal cells into adipocytes. Dyes, such as Oil Red O, are cheap, easy ...

Adipo-Clear: A Tissue Clearing Method for Three-Dimensional Imaging of Adipose Tissue

Adipose tissue plays a central role in energy homeostasis and thermoregulation. It is composed of different types of adipocytes, as well as adipocyte precursors, immune cells, fibroblasts, blood vessels, and nerve projections. Although the molecular control of cell type specification and how these cells interact have been increasingly delineated, a more comprehensive understanding of these adipose-resident cells can be achieved by visualizing their distribution and architecture throughout the whole tissue. Existing immunohistochemistry and immunofluorescence approaches to analyze adipose histology rely on thin paraffin-embedded sections. However, thin sections capture only a small portion of tissue; as a result, the conclusions can be biased by what portion of tissue is analyzed. We have therefore developed an adipose tissue clearing technique, Adipo-Clear, to permit comprehensive three-dimensional visualization of molecular and cellular patterns in whole adipose tissues. Adipo-Clear was adapted from iDISCO/iDISCO+, with specific modifications made to completely remove the lipid stored in the tissue while preserving native tissue morphology. In combination with light-sheet fluorescence microscopy, we demonstrate here the use of the Adipo-Clear method to obtain high-resolution volumetric images&#160;of an entire adipose tissue.

Due to the high lipid content, adipose tissue has been challenging to visualize using traditional histological methods. Adipo-Clear is a tissue clearing technique that allows robust labeling and high-resolution volumetric fluorescent imaging of adipose tissue. Here, we describe the methods for sample preparation, pretreatment, staining, clearing, and mounting for imaging.

Adipose tissue plays a central role in energy homeostasis and thermoregulation. It is composed of different types of adipocytes, as well as adipocyte ...

Pupal and Adult Injections for RNAi and CRISPR Gene Editing in Nasonia vitripennis

The jewel wasp, Nasonia vitripennis, has become an efficient model system to study epigenetics of haplo-diploid sex determination, B-chromosome biology, host-symbiont interactions, speciation, and venom synthesis. Despite the availability of several molecular tools, including CRISPR/Cas9, functional genetic studies are still limited in this organism. The major limitation of applying CRISPR/Cas9 technology in N. vitripennis stems from the challenges of embryonic microinjections. Injections of embryos are particularly difficult in this organism and in general in many parasitoid wasps, due to small embryo size and the requirement of a host pupa for embryonic development. To address these challenges, Cas9 ribonucleoprotein complex delivery into female&#160;ovaries by adult injection, rather than embryonic microinjection, was optimized, resulting in both somatic and heritable germline edits. The injection procedures were optimized in pupae and female wasps using either ReMOT Control (Receptor-Mediated Ovary Transduction of Cargo) or BAPC (Branched Amphiphilic Peptide Capsules). These methods are shown to be effective alternatives to embryo injection, enabling site-specific and heritable germline mutations.

Pupal and Adult Injections for RNAi and CRISPR Gene Editing in Nasonia vitripennis

Here, we describe methods for efficient pupal and adult injections in Nasonia vitripennis as accessible alternatives to embryo microinjection, enabling functional analysis of genes of interest using either RNA-silencing via RNA interference (RNAi) or gene knockout via CRISPR/Cas9 genome editing.

The jewel wasp, Nasonia vitripennis, has become an efficient model system to study epigenetics of haplo-diploid sex determination, B-chromosome biology, ...

Sample Preparation for Metabolic Profiling using MALDI Mass Spectrometry Imaging

Metabolomics, the study to identify and quantify small molecules and metabolites present in an experimental sample, has emerged as an important tool to investigate the biological activities during development and diseases. Metabolomics approaches&#160;are widely employed in the study of cancer, nutrition/diet, diabetes, and other physiological and pathological conditions involving metabolic processes. An advantageous tool that aids in metabolomic profiling advocated in this paper is matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI MSI). Its ability to detect metabolites in situ without labeling, structural modifications, or other specialized reagents, such as those used in immunostaining, makes MALDI MSI a unique tool in advancing methodologies relevant in the field of metabolomics. An appropriate sample preparation process is critical to yield optimal results and will be the focus of this paper.

The goal of this protocol is to provide detailed guidance on the sample preparation when planning for experiments using MALDI MSI to maximize metabolic and molecular detection in biological samples.

Metabolomics, the study to identify and quantify small molecules and metabolites present in an experimental sample, has emerged as an important tool to ...