Name: using the open-source maldi tof-ms idbac pipeline for analysis of microbial protein and specialized metabolite data
Uploaded: 2019-05-15T13:00:00
Duration: 9 min 29 s
Description: Watch this Scientific Journal Video about Using the Open-Source MALDI TOF-MS IDBac Pipeline for Analysis of Microbial Protein and Specialized Metabolite Data at JoVE.com

This work was supported by National Institute of General Medical Sciences Grant R01 GM125943, National Geographic Grant CP-044R-17; Icelandic Research Fund Grant 152336-051; and University of Illinois at Chicago startup funds. Also, we thank the following contributors: Dr. Amanda Bulman for assistance with MALDI-TOF MS protein acquisition parameters; Dr. Terry Moore and Dr. Atul Jain for recrystallizing alpha-cyano-4-hydroxycinnamic acid matrix (CHCA).

<ol>
	<li>Sandrin, T. R., Goldstein, J. E., Schumaker, S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=MALDI+TOF+MS+profiling+of+bacteria+at+the+strain+level:+A+review.">MALDI TOF MS profiling of bacteria at the strain level: A review.</a> Mass Spectrometry Reviews. 32 (3), 188-217 (2013).</li><li>Cain, T. C., Lubman, D. M., Weber, W. J., Vertes, A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Differentiation+of+bacteria+using+protein+profiles+from+matrix-assisted+laser+desorption/ionization+time-of-flight+mass+spectrometry.">Differentiation of bacteria using protein profiles from matrix-assisted laser desorption/ionization time-of-flight mass spectrometry.</a> Rapid Communications in Mass Spectrometry. 8 (12), 1026-1030 (1994).</li><li>Holland, R. D., Wilkes, J. G., 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=Rapid+identification+of+intact+whole+bacteria+based+on+spectral+patterns+using+matrix-assisted+laser+desorption/ionization+with+time-of-flight+mass+spectrometry.">Rapid identification of intact whole bacteria based on spectral patterns using matrix-assisted laser desorption/ionization with time-of-flight mass spectrometry.</a> Rapid Communications in Mass Spectrometry. 10 (10), 1227-1232 (1996).</li><li>Rahi, P., Prakash, O., Shouche, Y. S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Matrix-assisted+laser+desorption/ionization+time-of-flight+mass-spectrometry+(MALDI-TOF+MS)+based+microbial+identifications:+challenges+and+scopes+for+microbial+ecologists.">Matrix-assisted laser desorption/ionization time-of-flight mass-spectrometry (MALDI-TOF MS) based microbial identifications: challenges and scopes for microbial ecologists.</a> Frontiers in Microbiology. 7, 1359 (2016).</li><li>Silva, R., Lopes, N. P., Silva, D. B. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Application+of+MALDI+mass+spectrometry+in+natural+products+analysis.">Application of MALDI mass spectrometry in natural products analysis.</a> Planta Medica. 82, 671-689 (2016).</li><li>Clark, C. M., Costa, M. S., Sanchez, L. M., Murphy, B. T. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Coupling+MALDI-TOF+mass+spectrometry+protein+and+specialized+metabolite+analyses+to+rapidly+discriminate+bacterial+function.">Coupling MALDI-TOF mass spectrometry protein and specialized metabolite analyses to rapidly discriminate bacterial function.</a> Proceedings of the National Academy of Sciences of the United States of America. 115 (19), 4981-4986 (2018).</li><li>Freiwald, A., Sauer, S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Phylogenetic+classification+and+identification+of+bacteria+by+mass+spectrometry.">Phylogenetic classification and identification of bacteria by mass spectrometry.</a> Nature Protocols. 4 (5), 732-742 (2009).</li><li>Schulthess, B., Bloemberg, G. V., Zbinden, R., B&#246;ttger, E. C., Hombach, M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Evaluation+of+the+Bruker+MALDI+Biotyper+for+identification+of+Gram-positive+rods:+development+of+a+diagnostic+algorithm+for+the+clinical+laboratory.">Evaluation of the Bruker MALDI Biotyper for identification of Gram-positive rods: development of a diagnostic algorithm for the clinical laboratory.</a> Journal of Clinical Microbiology. 52 (4), 1089-1097 (2014).</li><li>Schumann, P., Maier, T. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=MALDI-TOF+mass+spectrometry+applied+to+classification+and+identification+of+bacteria.">MALDI-TOF mass spectrometry applied to classification and identification of bacteria.</a> Methods in Microbiology. 41, 275-306 (2014).</li><li>Chambers, M. C., Maclean, B., 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=A+cross-platform+toolkit+for+mass+spectrometry+and+proteomics.">A cross-platform toolkit for mass spectrometry and proteomics.</a> Nature Biotechnology. 30 (10), 918-920 (2012).</li><li>Kessner, D., Chambers, M., Burke, R., Agus, D., Mallick, P. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=ProteoWizard:+open+source+software+for+rapid+proteomics+tools+development.">ProteoWizard: open source software for rapid proteomics tools development.</a> Bioinformatics. 24 (21), 2534 (2008).</li><li>Martens, L., Chambers, M., 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=mzML-a+community+standard+for+mass+spectrometry+data.">mzML-a community standard for mass spectrometry data.</a> Molecular &#38; Cellular Proteomics. 10 (1), (2011).</li></ol>

The authors have nothing to disclose.

The IDBac protocol details bacterial protein and specialized metabolite data acquisition and analysis of up to 384 bacterial isolates in 4 h by a single researcher. With IDBac there is no need to extract DNA from bacterial isolates or generate specialized metabolite extracts from liquid fermentation broths and analyze them using chromatographic methods. Instead, protein and specialized metabolite data are gathered by simply spreading material from bacterial colonies directly onto a MALDI target plate. This greatly reduces the time and cost associated with alternative techniques such as 16S rRNA gene sequencing and LCMS9.
It is important to add a matrix blank and calibration spots to the MALDI plate, and we recommend using an appropriate number of replicates to ensure reproducibility and statistical confidence. The numbers of replicates will be experiment-dependent. For example, if a user intends to differentiate thousands of colonies from a collection of environmental diversity plates, fewer replicates may be necessary (our lab collects three technical replicates per colony). Alternatively, if a user wishes to create a custom database of strains from specific bacterial taxa to rapidly determine sub-species classifications of unknown isolates, then more replicates are appropriate (our lab collects eight biological replicates per strain).
IDBac is a tool for rapidly differentiating highly-related bacterial isolates based on putative taxonomic information and specialized metabolite production. It can complement or serve as a precursor to orthogonal methods such as in-depth genetic analyses, studies involving metabolite production and function, or characterization of specialized metabolite structure by Nuclear Magnetic Resonance spectroscopy and/or LC-MS/MS.
Specialized metabolite production (IDBac MANs) is highly susceptible to bacterial growth conditions, especially using different media, which is a potential limitation of the method. However these traits may be exploited by the user, as IDBac can readily generate MANs showing the differences in specialized metabolite production under a variety of growth conditions. It is important to note that while specialized metabolite fingerprints may vary by growth condition, we have previously shown that protein fingerprints remain relatively stable across these variables (see Clark et al.6). When dealing with environmental diversity plates, we recommend purifying bacterial isolates prior to analysis in order to reduce possible contributions from neighboring bacterial cross-talk.
Finally, the lack of a searchable public database of protein MS fingerprints is a major shortcoming in the use of this method to classify unknown environmental bacteria. We created IDBac with this in mind, and included automated conversion of data into a community-accepted open-source format (mzML)10,11,12 and designed the software to allow searching, sharing, and creation of custom databases. We are in the process of creating a large public database (&#62;10,000 fully characterized strains), which will allow for the classification of some isolates to the species-level, including links to GenBank accession numbers when available.
IDBac is open source and the code is available for anyone to customize their data analysis and visualization needs. We recommend that users consult an extensive body of literature (Sauer et al.7, Silva et al.5) to help support and design their experimental goals. We host a forum for discussion at: https://groups.google.com/forum/#!forum/idbac and a means to report issues with the software at: https://github.com/chasemc/IDBacApp/issues.

A major barrier to researchers who study bacterial function is the ability to quickly and simultaneously assess the taxonomic identity of a microorganism and its capacity to produce specialized metabolites. This has prevented significant advances in understanding the relationship between bacterial phylogeny and specialized metabolite production in the majority of bacteria isolated from the environment. Although MS-based methods that use protein fingerprints to group and identify bacteria are well described1,2,3,4, these studies have generally been performed on small groups of isolates, in a species-specific manner. Importantly, information on specialized metabolite production, a major driver of microbial function in the environment, has remained unincorporated in these studies. Silva et al.5 recently provided a comprehensive history detailing the underuse of MALDI-TOF MS to analyze specialized metabolites and the shortage of software to relieve current bioinformatics bottlenecks. In order to address these shortcomings, we created IDBac, a bioinformatics pipeline that integrates both linear and reflectron modes of MALDI-TOF MS6. This allows users to rapidly visualize and differentiate bacterial isolates based on both protein and specialized metabolite MS fingerprints, respectively.
IDBac is cost-effective, high-throughput, and designed for the lay user. It is freely available (chasemc.github.io/IDBac), and only requires access to a MALDI-TOF mass spectrometer (reflectron mode will be required for specialized metabolite analysis). Sample preparation relies on the simple &#8220;extended direct transfer&#8221; method7,8 and data are collected with consecutive linear and reflectron acquisitions on a single MALDI-target spot. With IDBac, it is possible to analyze the putative phylogeny and specialized metabolite production of hundreds of colonies in under four hours, including sample preparation, data acquisition, and data visualization. This presents a significant time and cost advantage over traditional methods of identifying bacteria (such as gene sequencing), and analyzing metabolic output (liquid chromatography-mass spectrometry [LCMS] and similar chromatographic methods).
Using data obtained in linear mode analysis, IDBac employs hierarchical clustering to represent the relatedness of protein spectra. Since the spectra mostly represent ionized ribosomal proteins, they provide a representation of the phylogenetic diversity present in a sample. In addition, IDBac incorporates reflectron mode data to display specialized metabolite fingerprints as Metabolite Association Networks (MANs). MANs are bipartite networks that allow for easy visualization of shared and unique metabolite production between bacterial isolates. The IDBac platform allows researchers to analyze both protein and specialized metabolite data in tandem but also individually if only one data-type is acquired. Importantly, IDBac processes raw data from Bruker and Xiamen instruments, as well as txt, tab, csv, mzXML, and mzML. This eliminates the need for manual conversion and formatting of data sets, and significantly reduces the risk of user error or mishandling of MS data.&#160;

<table>
	<tbody>
		<tr>
			<td>Acetonitrile</td>
			<td>Fisher</td>
			<td>60-002-65</td>
			<td>LC-MS Ultra CHROMASOLV</td>
		</tr>
		<tr>
			<td>Autoflex Speed LEF MALDI-TOF instrument</td>
			<td>Bruker Daltonics</td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>Bruker Daltonics Bacterial test standard</td>
			<td>Fisher</td>
			<td>NC0884024</td>
			<td>Bruker Daltonics 8604530</td>
		</tr>
		<tr>
			<td>Bruker Peptide Calibration standard</td>
			<td>Fisher</td>
			<td>NC9846988</td>
			<td>Bruker Daltonics 8206195</td>
		</tr>
		<tr>
			<td>Formic Acid</td>
			<td>Fisher Chemical</td>
			<td>A117-50</td>
			<td>99.5+%, Optima LC/MS Grade</td>
		</tr>
		<tr>
			<td>MALDI-TOF target Plate</td>
			<td>Bruker Daltonics</td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>Methanol</td>
			<td>Fisher Chemical</td>
			<td>A456-500</td>
			<td>Optima LC/MS Grade</td>
		</tr>
		<tr>
			<td>Toothpicks</td>
			<td></td>
			<td></td>
			<td>any is ok</td>
		</tr>
		<tr>
			<td>Trifluoroacetic acid</td>
			<td>Fisher</td>
			<td>AC293810010</td>
			<td>99.5%, for biochemistry, ACROS Organics</td>
		</tr>
		<tr>
			<td>Water</td>
			<td>VWR</td>
			<td>7732-18-5</td>
			<td>LC-MS</td>
		</tr>
		<tr>
			<td>&#945;-Cyano-4-hydroxycinnamic acid</td>
			<td>Sigma</td>
			<td>28166-41-8</td>
			<td>(C2020-25G) &#8805;98% (TLC), powder</td>
		</tr>
	</tbody>
</table>

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.

We analyzed six strains of Micromonospora chokoriensis and two strains of Bacillus subtilis, which were previously characterized6, using data available at DOI: 10.5281/zenodo.2574096. Following directions in the Starting with Raw Data tab, we selected the option Click here to convert Bruker files and followed the IDBac-provided instructions for each dataset (Figure 14).
After the automated conversion and preprocessing/peak-peaking steps were completed, we proceeded to create a new combined IDBac experiment by transferring samples from the two experiments into a single experiment containing both Bacillus and Micromonosopora samples (Figure 15). The resulting analysis involved comparing protein spectra using mirror plots, as pictured in Figure 16, which was useful for evaluating spectra quality and adjusting peak-picking settings. Figure 17 displays a screenshot of the protein clustering results with default settings selected. The dendrogram was colored by adjusting the threshold on the plot (appears as a dotted line). Of note is the clear separation between genera, with both M. chokoriensis and B. subtilis isolates clustering separately.
Figure 18, Figure 19, and Figure 20 highlight the ability to generate MANs of user-selected regions by clicking and dragging across the protein dendrogram. With this we were able to rapidly create MANs to compare only the B. subtilis strains (Figure 18), only the M. chokoriensis strains (Figure 19), and all the strains simultaneously (Figure 20). The primary function of these networks is to provide researchers with a broad overview of the degree of specialized metabolite overlap between bacteria. With these data in hand, researchers now have the capacity to make informed decisions from only a small amount of material scraped from a bacterial colony.
<img alt="Figure 14" class="xfigimg" src="/files/ftp_upload/59219/59219fig14v2.jpg" /> 
Figure 14: Spectra processing. Downloaded Bruker autoFlex spectra were converted and processed using IDBac. <a href="https://www.jove.com/files/ftp_upload/59219/59219fig14v2large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 15" class="xfigimg" src="/files/ftp_upload/59219/59219fig15v2.jpg" /> 
Figure 15: Combined IDBac experiment. Because the Micromonospora and Bacillus spectra were collected on different MALDI target plates, the two experiments were subsequently combined into a single experiment-&#8220;Bacillus_Micromonsopora&#8221;. This was done within the &#8220;Work with Previous Experiments&#8221; tab, following directions within the menu &#8220;Transfer samples from previous experiments to new/other experiments&#8221;. <a href="https://www.jove.com/files/ftp_upload/59219/59219fig15v2large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 16" class="xfigimg" src="/files/ftp_upload/59219/59219fig16v2.jpg" /> 
Figure 16: Comparison. Micromonspora and Bacillus spectra were compared using the mirror plots within the &#8220;Protein Data Analysis&#8221; page. Ultimately, default peak settings were chosen. <a href="https://www.jove.com/files/ftp_upload/59219/59219fig16v2large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 17" class="xfigimg" src="/files/ftp_upload/59219/59219fig17v2.jpg" /> 
Figure 17: Hierarchical clustering. Hierarchical clustering, using default settings, correctly grouped Bacillus and Micromonospora isolates. The dendrogram was colored by &#8220;cutting&#8221; the dendrogram at an arbitrary height (displayed as a dashed-line) and 100 bootstraps used to show confidence in branching. <a href="https://www.jove.com/files/ftp_upload/59219/59219fig17v2large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 18" class="xfigimg" src="/files/ftp_upload/59219/59219fig18v2.jpg" /> 
Figure 18: MAN created by selecting the Bacillus sp. strains from the protein dendrogram showed differential production of specialized metabolites. <a href="https://www.jove.com/files/ftp_upload/59219/59219fig18v2large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 19" class="xfigimg" src="/files/ftp_upload/59219/59219fig19v2.jpg" /> 
Figure 19: MAN created by selecting the six Micromonospora sp. strains from the protein dendrogram showed differential production of specialized metabolites. <a href="https://www.jove.com/files/ftp_upload/59219/59219fig19v2large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 20" class="xfigimg" src="/files/ftp_upload/59219/59219fig20v2.jpg" /> 
Figure 20: MAN of Bacillus sp. and Micromonospora sp. strains showing a differential production of specialized metabolites. <a href="https://www.jove.com/files/ftp_upload/59219/59219fig20v2large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>

Watch this Scientific Journal Video about Using the Open-Source MALDI TOF-MS IDBac Pipeline for Analysis of Microbial Protein and Specialized Metabolite Data at JoVE.com

Using the Open-Source MALDI TOF-MS IDBac Pipeline for Analysis of Microbial Protein and 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, ...

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