We acknowledge the financial support for the project from the French grant REPLIPOX ANR-13-BSV8-0014 and by research grants from the Service de Sant&#233; des Arm&#233;es and the D&#233;l&#233;gation G&#233;n&#233;rale pour l&#39;Armement. We are thankful to the ESRF for the SAXS beam time. This work used the platforms of the Grenoble Instruct-ERIC center (ISBG; UMS 3518 CNRS-CEA-UGA-EMBL) within the Grenoble Partnership for Structural Biology (PSB), supported by FRISBI (ANR-10-INBS-05-02) and GRAL, financed within the University Grenoble Alpes graduate school (Ecoles Universitaires de Recherche) CBH-EUR-GS (ANR-17-EURE-0003). IBS acknowledges integration into the Interdisciplinary Research Institute of Grenoble (IRIG, CEA). We thank Wim P. Burmeister and Fr&#233;d&#233;ric Iseni for financial and scientific support and we also thank Dr. Jesse Hopkins from BioCAT at the APS for his help and for developing BioXTAS RAW.

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W., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Methods+for+analysis+of+size-exclusion+chromatography-small-angle+X-ray+scattering+and+reconstruction+of+protein+scattering.">Methods for analysis of size-exclusion chromatography-small-angle X-ray scattering and reconstruction of protein scattering.</a> Journal of Applied Crystallography. 48 (4), 1102-1113 (2015).</li><li>Hopkins, J. B., Gillilan, R. 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E., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Online+data+analysis+at+the+ESRF+bioSAXS+beamline,+BM29.">Online data analysis at the ESRF bioSAXS beamline, BM29.</a> Journal of Applied Crystallography. 49 (1), 203-212 (2016).</li><li>Kirby, N., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Improved+radiation+dose+efficiency+in+solution+SAXS+using+a+sheath+flow+sample+environment.">Improved radiation dose efficiency in solution SAXS using a sheath flow sample environment.</a> Acta Crystallographica Section D Structural Biology. 72 (12), 1254-1266 (2016).</li><li>Rambo, R. P., Tainer, J. 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The authors have nothing to disclose.

It is desired to have a monodisperse sample before starting a SAXS experiment, but in reality, many data collections do not satisfy this and must be improved by combining the measurement with inline chromatography&#8212;SEC in most cases. However, even the shortage of time between purification and data acquisition monodispersity of the sample is not guaranteed. Most commonly, this applies to experiments where components are too close in size or in their physical properties to be separated or are prone to fast dynamics. Here, we have provided a protocol combining single value decomposition with evolving factor analysis to remove the influence of DNAbound E9 exominus from its unboundform creating a monodisperse scattering profile that we were then able to analyze with the SAXS package Scatter IV.
SVD with EFA of SEC-SAXS data are very powerful methods developed to deconvolute SAXS data and improve analysis, but they do have limitations. They require that noise or drift in the buffer baseline of the SEC-SAXS is kept to a minimum. This may involve extra column equilibration (better to use more than 3 column volumes, depending on the buffer) before sample loading. However, the most critical step is the choice of the number of the singular values and the range of data used, as this will greatly affect the accuracy of the deconvolution. It is for this reason that the results should not be taken on their own but further analyzed using techniques such as analytical ultracentrifugation (AUC) or multi-angle-laser-light-scattering (MALLS) for biological interpretation.
Scatter IV is a new, software package, free for research and industrial use with an intuitive user interface that allows even non-experts to analyze their data. Scatter IV has several new features that help to improve the analysis of SEC-SAXS data, such as the heat map linked to the signal plot, enabling greater accuracy with choice of frame selection. In primary data analysis, the Guinier Peak analysis and the cross-validation plot associated with the P(r) analysis offer an integrated troubleshooting ability in the software.
It should be mentioned that many other programs can be used for primary data analysis; these contain the same basic features and are also updated regularly such as BioXTAS RAW17 ATSAS package24 and US-SOMO15 to name a few.
But regardless of which SAXS package is used for analysis, the major limitations are common: the sample preparation, before collection and analysis. In the E9 exominus example shown, it is clear to see the improvement in the signal to noise ratio and with a reduction in the Rg the dmax associated with a monodisperse sample. This will greatly aid further processing of the data such as fitting or modeling with known high-resolution structures.

Biological macromolecules are too small to be seen even with the best light microscopes. Current methods to determine their structures generally involve crystallizing the protein or measurements on vast numbers of identical molecules at the same time. While crystallography provides information on the atomic level, it represents an artificial sample environment, given that most macromolecules are not presented in a crystalline form in the cell. During the last couple of years cryo-electron microscopy delivered similar high-resolution structures of large macromolecules / macromolecular complexes, but although the samples are closer to physiological condition, they are still frozen, hence immobile and static. Bio-small angle X-ray scattering (BioSAXS) provides a structural measurement of the macromolecule, in conditions that are relevant to biology. This state can be visualized as a low resolution 3-D shape determined on nanometer scale and captures the entire conformational space of the macromolecule in solution. BioSAXS experiments efficiently assess oligomeric state, domain and complex arrangements as well as flexibility between domains1,2,3. The method is accurate, mostly non-destructive and usually requires only a minimum of sample preparation and time. However, for the best interpretation of the data, the samples need to be monodisperse. This is challenging; biological molecules are often susceptible to contaminations, poor purification and aggregation, for example from freeze thawing4. The development of inline chromatography followed by immediate SAXS measurement helps mitigate these effects. Size-exclusion chromatography separates the samples by size thus excluding most contaminants and aggregations5,6,7,8,9,10. However, in some cases even SEC-SAXS is not sufficient to produce a monodisperse sample, because the mixture may consist of components that are too close in size or their physical properties or their fast dynamics lead to overlapping peaks in the SEC UV trace. In these cases, a software-based deconvolution step of the obtained SAXS data might lead to an idealized SAXS curve of the individual component5,11,12. As an example, in protocol section 2, we show the standard SEC-SAXS analysis of the vaccinia E9 DNA polymerase exonuclease minus mutant (E9 exominus) in complex with DNA. Vaccinia represents the model organism of the Poxviridae, a family containing several pathogens, for example the human smallpox virus. The polymerase was shown to bind tightly to DNA in biochemical approaches, with the structure of the complex recently solved by X-ray crystallography13.
Most synchrotron facilities will provide an automated data processing pipeline that will perform data normalization and integration producing a set of unsubtracted frames. But the approach described in this manuscript could also be use with a lab source provided SEC-SAXS is performed. Furthermore, additional automation may be available that will reject radiation-damaged frames and perform the buffer subtraction14. We will show how to perform primary data analysis on pre-processed data and make the most of the available data in section 2.
In section 3, we show how to deconvolute SEC-SAXS data and analyze the curves efficiently. While there are several deconvolution methods such as the Gaussian peak deconvolution, implemented in US-SOMO15 and the Guinier optimized maximum likelihood method, implemented in the DELA software16, these generally require a model for the peak shape12. The finite size of individual peaks we are investigating allows the use of evolving factor analysis (EFA), as an enhanced form of singular value decomposition (SVD) to deconvolute overlapping peaks, without relying on the peak shape or scattering profile5,11. A SAXS-specific implementation can be found in BioXTAS RAW17. EFA was first used on chromatography data when 2D diode array data allowed matrices to be formed from absorbance against retention time and wavelength data18. Where EFA excels is that it focuses on the evolving character of singular values, how they change with the appearance of new components, with the caveat that there is an inherent order in the acquisition10. Fortunately, SEC-SAXS data provides all the necessary ordered acquisition data in organized 2D data arrays, lending itself nicely to the EFA technique.
In section 4, we will demonstrate the basics of model-independent SAXS analysis from the buffer-background subtracted SAXS curve. Model-independent analysis determines the particle&#8217;s radius-of-gyration (Rg), volume-of-correlation (Vc), Porod Volume (Vp), and Porod-Debye Exponent (PE). The analysis provides a semi-quantitative assessment of the particle&#8217;s thermodynamic state in terms of compactness or flexibility via the dimensionless Kratky plot2,4,19.
Finally, SAXS data are measured in reciprocal space units and we will show how to transform the SAXS data to real-space to recover the pair-distance, P(r), distribution function. The P(r)-distribution is the set of all distances found within the particle and includes the particle&#8217;s maximum dimension, dmax. Since this is a thermodynamic measurement, the P(r)-distribution represents the physical space occupied by the particles&#8217; conformational space. Proper analysis of a SAXS dataset can provide solution-state insights that complement high-resolution information from crystallography and cryo-EM.

<table>
	<tbody>
		<tr>
			<td>Beamline control software BsXCuBE</td>
			<td>ESRF</td>
			<td>Pernot et al. (2013), J. Synchrotron Rad. 20, 660-664</td>
			<td>local development</td>
		</tr>
		<tr>
			<td>BioXTAS Raw 1.2.3.</td>
			<td>MacCHESS</td>
			<td>http://bioxtas-raw.readthedocs.io/en/latest/index.html</td>
			<td>First developed in 2008 by Soren Skou as part of the biological x-ray total analysis system (BioXTAS) project. Since then it has been extensively developed, with recent work being done by Jesse B. Hopkins</td>
		</tr>
		<tr>
			<td>HPLC program LabSolutions</td>
			<td>Shimadzu</td>
			<td>n.a.</td>
			<td></td>
		</tr>
		<tr>
			<td>ISPyB</td>
			<td>ESRF</td>
			<td>De Maria Antolinos et al. (2015). Acta Cryst. D71, 76-85.</td>
			<td>local development</td>
		</tr>
		<tr>
			<td>NaCl</td>
			<td>VWR Chemicals (BDH Prolabo)</td>
			<td>27808.297</td>
			<td></td>
		</tr>
		<tr>
			<td>Scatter</td>
			<td>Diamond Light Source Ltd</td>
			<td>http://www.bioisis.net/tutorial/9</td>
			<td>Supported by SIBYLS beamline (ALS berkeley, Ca) and Bruker Cororation (Karlsruhe, Germany)</td>
		</tr>
		<tr>
			<td>Superdex 200 Increase 5/150 GL column</td>
			<td>GE Healthcare</td>
			<td>28990945</td>
			<td>SEC-SAXS column used</td>
		</tr>
		<tr>
			<td>Tris base</td>
			<td>Euromedex</td>
			<td>26-128-3094-B</td>
			<td></td>
		</tr>
	</tbody>
</table>

analysis of sec-saxs data via efa deconvolution and scatter

BioSAXS is a popular technique used in molecular and structural biology to determine the solution structure, particle size and shape, surface-to-volume ratio and conformational changes of macromolecules and macromolecular complexes. A high quality SAXS dataset for structural modeling must be from monodisperse, homogeneous samples and this is often only reached by a combination of inline chromatography and immediate SAXS measurement. Most commonly, size-exclusion chromatography is used to separate samples and exclude contaminants and aggregations from the particle of interest allowing SAXS measurements to be made from a well-resolved chromatographic peak of a single protein species. Still, in some cases, even inline purification is not a guarantee of monodisperse samples, either because multiple components are too close to each other in size or changes in shape induced through binding alter perceived elution time. In these cases, it may be possible to deconvolute the SAXS data of a mixture to obtain the idealized SAXS curves of individual components. Here, we show how this is achieved and the practical analysis of SEC-SAXS data is performed on ideal and difficult samples. Specifically, we show the SEC-SAXS analysis of the vaccinia E9 DNA polymerase exonuclease minus mutant.

The advantage of using deconvolution over classical frame selection13 is to remove the influence of species on one another, producing a monodisperse scattering signal. This is also often followed with a better signal to noise ratio. When E9 exominus is bound to DNA and run using SEC-SAXS, two peaks are observed (Figure 1). The first, large peak (approximately frames 420&#8210;475) is the E9 exominus-DNA complex the second (approximately frames 475&#8210;540), the unbound state (see Supplementary Data: Figure 2). While the classical approach of selecting frames provides a stable Rg of the complex in the first peak (see Supplementary Data: Figure 3), the second peak is clearly merged and the Rg across the plot shows that the second peak of interest does not have a stable Rg, due to cross-peak contamination. Only 5 frames could be used that showed a semi-stable Rg, when subtracted they gave an Rg = 36.3&#160;&#197; (Figure 2, green). When the peaks were deconvoluted using EFA the corresponding curve for the second peak (Figure 2, blue) was overlaid with the original and showed a clear decrease in signal to noise, and a lower Rg, 34.1 &#197; was recorded. The Kratky plot (Figure 3) shows the complex with the deconvoluted peak (blue) is more globular. This is confirmed by the P(r) curve (Figure 4) which gives a dmax 108.5&#160;&#197; for the deconvoluted curve (blue) while the non-deconvoluted is more elongated with a dmax 120&#160;&#197; (green), this is most likely due to heterogeneity arising from the unbound E9 exominus.
<img alt="Figure 1" class="xfigimg" src="/files/ftp_upload/61578/61578fig01.jpg" /> 
Figure 1: Signal plot of E9 exominus alone and with DNA in complex. 
The top panel shows a plot of the integral ratio to the background for each frame of a SEC-SAXS run (light blue). The red points show the Rg at each frame over the peak. The bottom panel shows the corresponding heat map showing the residuals for each frame colored according to the Durbin-Watson auto-correlation analysis, regions of high similarity are colored cyan while dissimilar frames follow darker blues to pinks and finally to red depending on the severity of the dissimilarity. <a href="https://www.jove.com/files/ftp_upload/61578/61578fig01large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 2" class="xfigimg" src="/files/ftp_upload/61578/61578fig02.jpg" /> 
Figure 2: Plot of intensity versus scattering vector. 
An overlay of the subtracted SAXS data form the E9 exominus . In green 5 frames (frame 517&#8210;522) averaged and subtracted from an area of semi-stable Rg and in blue the representative scattering curve derived from the EFA deconvolution of the SEC-SAXS peak. <a href="https://www.jove.com/files/ftp_upload/61578/61578fig02large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 3" class="xfigimg" src="/files/ftp_upload/61578/61578fig03.jpg" /> 
Figure 3: Dimensionless Kratky curve. 
Overlay of the deconvoluted (blue) and non-deconvoluted (green) Kratky curve showing E9 exominus is globular. <a href="https://www.jove.com/files/ftp_upload/61578/61578fig03large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 4" class="xfigimg" src="/files/ftp_upload/61578/61578fig04.jpg" /> 
Figure 4: P(r) curve. 
The overlay of the deconvoluted (blue) and non-deconvoluted (green) curves for the E9 exominus. <a href="https://www.jove.com/files/ftp_upload/61578/61578fig04large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
Supplementary Data.&#160;<a href="https://www.jove.com/files/ftp_upload/61578/Supplementary data.docx" target="_blank">Please click here to download this file</a>

Watch this Scientific Journal Video about Analysis of SEC-SAXS data via EFA deconvolution and Scatter at JoVE.com

Analysis of SEC-SAXS data via EFA deconvolution and Scatter

SEC-BioSAXS measurements of biological macromolecules are a standard approach for determining solution structure of macromolecules and their complexes. Here, we analyze SEC-BioSAXS data from two types of commonly encountered SEC traces&#8212;chromatograms with fully resolved and partially resolved peaks. We demonstrate the analysis and deconvolution using scatter and BioXTAS RAW.

BioSAXS is a popular technique used in molecular and structural biology to determine the solution structure, particle size and shape, surface-to-volume ...

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Biochemistry

8.7K Views.  Structural Biology Group. SEC-BioSAXS measurements of biological macromolecules are a standard approach for determining solution structure of macromolecules and their complexes. Here, we analyze SEC-BioSAXS data from two types of commonly encountered SEC traces—chromatograms with fully resolved and partially resolved peaks. We demonstrate the analysis and deconvolution using scatter and BioXTAS RAW.

Video: Analysis of SEC-SAXS data via EFA deconvolution and Scatter

Production, Crystallization and Structure Determination of C. difficile PPEP-1 via Microseeding and Zinc-SAD

New therapies are needed to treat Clostridium difficile infections that are a major threat to human health. The C. difficile metalloprotease PPEP-1 is a target for future development of inhibitors to decrease the virulence of the pathogen. To perform biophysical and structural characterization as well as inhibitor screening, large amounts of pure and active protein will be needed. We have developed a protocol for efficient production and purification of PPEP-1 by the use of E. coli as the expression host yielding sufficient amounts and purity of protein for crystallization and structure determination. Additionally, using microseeding, highly intergrown crystals of PPEP-1 can be grown to well-ordered crystals suitable for X-ray diffraction analysis. The methods could also be used to produce other recombinant proteins and to study the structures of other proteins producing intergrown crystals.

Production, Crystallization and Structure Determination of C. difficile PPEP-1 via Microseeding and Zinc-SAD

Proline-proline endopeptidase-1 (PPEP-1) is a secreted metalloprotease and promising drug-target from the human pathogen Clostridium difficile. Here we describe all methods necessary for the production and structure determination of this protein.

New therapies are needed to treat Clostridium difficile infections that are a major threat to human health. The C. difficile metalloprotease PPEP-1 is a ...

Anaerobic Protein Purification and Kinetic Analysis via Oxygen Electrode for Studying DesB Dioxygenase Activity and Inhibition

Oxygen-sensitive proteins, including those enzymes which utilize oxygen as a substrate, can have reduced stability when purified using traditional aerobic purification methods. This manuscript illustrates the technical details involved in the anaerobic purification process, including the preparation of buffers and reagents, the methods for column chromatography in a glove box, and the desalting of the protein prior to kinetics. Also described are the methods for preparing and using an oxygen electrode to perform kinetic characterization of an oxygen-utilizing enzyme. These methods are illustrated using the dioxygenase enzyme DesB, a gallate dioxygenase from the bacterium Sphingobium sp. strain SYK-6.

Here we present a protocol for anaerobic protein purification, anaerobic protein concentration, and subsequent kinetic characterization using an oxygen electrode system. The method is illustrated using the enzyme DesB, a dioxygenase enzyme which is more stable and active when purified and stored in an anaerobic environment.

Oxygen-sensitive proteins, including those enzymes which utilize oxygen as a substrate, can have reduced stability when purified using traditional aerobic ...

Fully Autonomous Characterization and Data Collection from Crystals of Biological Macromolecules

High-brilliance X-ray beams coupled with automation have&#160;led to the use of synchrotron-based macromolecular X-ray crystallography (MX) beamlines for even the most challenging projects in structural biology. However, most facilities still require the presence of a scientist on site to perform the experiments. A new generation of automated beamlines dedicated to the fully automatic characterization of, and data collection from, crystals of biological macromolecules has recently been developed. These beamlines represent a new tool for structural biologists to screen the results of initial crystallization trials and/or the collection of large numbers of diffraction data sets, without users having to control the beamline themselves. Here we show how to set up an experiment for automatic screening and data collection, how an experiment is performed at the beamline, how the resulting data sets are processed, and how, when possible, the crystal structure of the biological macromolecule is solved.

Here, we describe how to use the automated screening and data collection options available at some synchrotron beamlines. Scientists send cryocooled samples to the synchrotron, and the diffraction properties are screened, the data sets are collected and processed and, where possible, a structure solution is carried out&#8212;all without human intervention.

High-brilliance X-ray beams coupled with automation have&#160;led to the use of synchrotron-based macromolecular X-ray crystallography (MX) beamlines for ...

Using the Open-Source MALDI TOF-MS IDBac Pipeline for Analysis of Microbial Protein and Specialized Metabolite Data

In order to visualize the relationship between bacterial phylogeny and specialized metabolite production of bacterial colonies growing on nutrient agar, we developed IDBac&#8212;a low-cost and high-throughput matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) bioinformatics pipeline. IDBac software is designed for non-experts, is freely available, and capable of analyzing a few to thousands of bacterial colonies. Here, we present procedures for the preparation of bacterial colonies for MALDI-TOF MS analysis, MS instrument operation, and data processing and visualization in IDBac. In particular, we instruct users how to cluster bacteria into dendrograms based on protein MS fingerprints and interactively create Metabolite Association Networks (MANs) from specialized metabolite data.

IDBac is an open-source mass spectrometry-based bioinformatics pipeline that integrates data from both intact protein and specialized metabolite spectra, collected on cell material scraped from bacterial colonies. The pipeline allows researchers to rapidly organize hundreds to thousands of bacterial colonies into putative taxonomic groups, and further differentiate them based on specialized metabolite production.

In order to visualize the relationship between bacterial phylogeny and specialized metabolite production of bacterial colonies growing on nutrient agar, ...

Perturbing Endothelial Biomechanics via Connexin 43 Structural Disruption

Endothelial cells have been established to generate intercellular stresses and tractions, but the role gap junctions play in endothelial intercellular stress and traction generation is currently unknown. Therefore, we present here a mechanics-based protocol to probe the influence of gap junction connexin 43 (Cx43) has on endothelial biomechanics by exposing confluent endothelial monolayers to a known Cx43 inhibitor 2,5-dihydroxychalcone (chalcone) and measuring the impact this inhibitor has on tractions and intercellular stresses. We present representative results, which show a decrease in both tractions and intercellular stresses under a high chalcone dosage (2 &#181;g/mL) when compared to control. This protocol can be applied to not just Cx43, but also other gap junctions as well, assuming the appropriate inhibitor is used. We believe this protocol will be useful in the fields of cardiovascular and mechanobiology research.

Here, we present a mechanics-based protocol to disrupt the gap junction connexin 43 and measure the subsequent impact this has on endothelial biomechanics via observation of tractions and intercellular stresses.

Endothelial cells have been established to generate intercellular stresses and tractions, but the role gap junctions play in endothelial intercellular ...

TMT Sample Preparation for Proteomics Facility Submission and Subsequent Data Analysis

Proteomic technologies are powerful methodologies that can aid our understanding of mechanisms of action in biological systems by providing a global view of the impact of a disease, treatment, or other condition on the proteome as a whole. This report provides a detailed protocol for the extraction, quantification, precipitation, digestion, labeling, and subsequent data analysis of protein samples. Our optimized TMT labeling protocol requires a lower tag-label concentration and achieves consistently reliable data. We have used this protocol to evaluate protein expression profiles in a variety of mouse tissues (i.e., heart, skeletal muscle, and brain) as well as cells cultured in vitro. In addition, we demonstrate how to evaluate thousands of proteins from the resulting dataset.

We present an optimized tandem mass tag (TMT) labeling protocol that includes detailed information for each of the following steps: protein extraction, quantification, precipitation, digestion, labeling, submission to a proteomics facility, and data analyses.

Proteomic technologies are powerful methodologies that can aid our understanding of mechanisms of action in biological systems by providing a global view ...

Proteomic Profile of EPS-Urine through FASP Digestion and Data-Independent Analysis

Filter-aided sample protocol (FASP) is widely used for proteomics sample preparation because it allows to concentrate diluted samples and it is compatible with a wide variety of detergents. Bottom-up proteomics workflows like FASP increasingly rely on LC-MS/MS methods performed in data-independent analysis (DIA) mode, a scanning method that allows deep proteome coverage and low incidence of missing values. 
In this report, we will provide the details of a workflow that combines a FASP protocol, a double StageTip purification step and LC-MS/MS in DIA mode for urinary proteome mapping. As a model sample, we analyzed expressed prostatic secretions (EPS)-urine, a sample collected after a digital rectal exam (DRE), which is of interest in prostate cancer biomarker discovery studies.

Here, we present an optimized on-filter digestion protocol with detailed information about the following: protein digestion, peptide purification and data independent acquisition analysis. This strategy is applied to the analysis of expressed prostatic secretions-urine samples and allows high proteome coverage and low missing value label-free profiling of the urinary proteome.

Filter-aided sample protocol (FASP) is widely used for proteomics sample preparation because it allows to concentrate diluted samples and it is compatible ...

Routine Collection of High-Resolution cryo-EM Datasets Using 200 KV Transmission Electron Microscope

Cryo-electron microscopy (cryo-EM) has been established as a routine method for protein structure determination during the past decade, taking an ever-increasing share of published structural data. Recent advances in TEM technology and automation have boosted both the speed of data collection and quality of acquired images while simultaneously decreasing the required level of expertise for obtaining cryo-EM maps at sub-3 &#197; resolutions. While most of such high-resolution structures have been obtained using state-of-the-art 300 kV cryo-TEM systems, high-resolution structures can be also obtained with 200 kV cryo-TEM systems, especially when equipped with an energy filter. Additionally, automation of microscope alignments and data collection with real-time image quality assessment reduces system complexity and assures optimal microscope settings, resulting in increased yield of high-quality images and overall throughput of data collection. This protocol demonstrates the implementation of recent technological advances and automation features on a 200 kV cryo-transmission electron microscope and shows how to collect data for the reconstruction of 3D maps that are sufficient for de novo atomic model building. We focus on best practices, critical variables, and common issues that must be considered to enable the routine collection of such high-resolution cryo-EM datasets. Particularly the following essential topics are reviewed in detail: i) automation of microscope alignments, ii) selection of suitable areas for data acquisition, iii) optimal optical parameters for high-quality, high-throughput data collection, iv) energy filter tuning for zero-loss imaging, and v) data management and quality assessment. Application of the best practices and improvement of achievable resolution using an energy filter will be demonstrated on the example of apo-ferritin that was reconstructed to 1.6 &#197;, and Thermoplasma acidophilum 20S proteasome reconstructed to 2.1-&#197; resolution using a 200 kV TEM equipped with an energy filter and a direct electron detector.

High-resolution cryo-EM maps of macromolecules can be also achieved by using 200 kV TEM microscopes. This protocol shows the best practices for setting accurate optics alignments, data acquisition schemes, and selection of imaging areas that are all essential for the successful collection of high-resolution datasets using a 200 kV TEM.

Cryo-electron microscopy (cryo-EM) has been established as a routine method for protein structure determination during the past decade, taking an ...

Generation of Tissue Spheroids via a 3D Printed Stamp-Like Device

Advances in 3D cell culture have developed more physiologically relevant in vitro models, such as tissue spheroids. Cells cultivated as spheroids have more realistic biological responses that resemble the in vivo environment. Due to their advantages, tissue spheroids represent an emerging trend toward superior, more reliable, and more predictive study models with a broad range of biotechnological applicability. However, reproducible platforms that can achieve large-scale production of tissue spheroids have become an unmet need in fully exploring and boosting their potential. Herein, the large-scale production of homogeneous tissue spheroids is reported using a low-cost and time-effective methodology. A 3D printed stamp-like device is developed to generate up to 4,716 spheroids per 6-well plate. The device is fabricated by the stereolithography method using a photocurable resin. The final device is composed of cylindrical micropins, with a height of 1.3 mm and a width of 650 &#181;m. This approach allows the fast generation of homogeneous spheroids and co-cultured spheroids with uniform shape and size and &gt;95% cell viability. Moreover, the stamp-like device is tunable for different sizes of well plates and Petri dishes. It is easily sterilized and can be reused for long periods. The efficient large-scale production of homogeneous tissue spheroids is essential to leverage their translation for multiple areas of industry, such as tissue engineering, drug development, disease modeling, and on-demand personalized medicine.

Generation of Tissue Spheroids via a 3D Printed Stamp-Like Device

The present protocol describes a technique to produce tissue spheroids on a large scale cost-effectively using a 3D printed stamp-like device.

Advances in 3D cell culture have developed more physiologically relevant in vitro models, such as tissue spheroids. Cells cultivated as spheroids have ...

Investigation of Microbial Cooperation via Imaging Mass Spectrometry Analysis of Bacterial Colonies Grown on Agar and in Tissue During Infection

Understanding the metabolic consequences of microbial interactions that occur during infection presents a unique challenge to the field of biomedical imaging. Matrix-assisted laser desorption/ionization (MALDI) imaging mass spectrometry represents a label-free, in situ imaging modality capable of generating spatial maps for a wide variety of metabolites. While thinly sectioned tissue samples are now routinely analyzed via this technology, imaging mass spectrometry analyses of non-traditional substrates, such as bacterial colonies commonly grown on agar in microbiology research, remain challenging due to the high water content and uneven topography of these samples. This paper demonstrates a sample preparation workflow to allow for imaging mass spectrometry analyses of these sample types. This process is exemplified using bacterial co-culture macrocolonies of two gastrointestinal pathogens: Clostridioides difficile and Enterococcus faecalis. Studying microbial interactions in this well-defined agar environment is also shown to complement tissue studies aimed at understanding microbial metabolic cooperation between these two pathogenic organisms in mouse models of infection. Imaging mass spectrometry analyses of the amino acid metabolites arginine and ornithine are presented as representative data. This method is broadly applicable to other analytes, microbial pathogens or diseases, and tissue types where a spatial measure of cellular or tissue biochemistry is desired.

Investigation of Microbial Cooperation via Imaging Mass Spectrometry Analysis of Bacterial Colonies Grown on Agar and in Tissue During Infection

A novel sample preparation method is demonstrated for the analysis of agar-based, bacterial macrocolonies via matrix-assisted laser desorption/ionization imaging mass spectrometry.

Understanding the metabolic consequences of microbial interactions that occur during infection presents a unique challenge to the field of biomedical ...