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09:29 min
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May 15th, 2019
DOI :
May 15th, 2019
•0:04
Title
1:10
Preparation of MALDI Target Plates and Data Acquisition
2:02
Installing the IDBac Software and Starting with Raw Data
2:47
Work with Previous Experiments
3:22
Setting up Protein Data Analysis and Creating Mirror Plots
4:07
Clustering Samples Using Protein Data
4:49
Customizing the Protein Dendrogram and Inserting Samples from a Separate Experiment into the Dendrogram
5:32
Analyzing Specialized Metabolite Data and Metabolite Association Networks (MANs)
6:51
Results: Analysis of Microbial Protein and Specialized Metabolite Data by IDBac
8:28
Conclusion
Transcript
IDBac couples mass spec data from protein and specialized metabolite regions of unknown bacterial isolates to rapidly discriminate between isolates based on both their identity and their potential environmental function. Our office source software extends the utility of existing MALDI TOF based microbial identification strategies. This extension includes analysis of specialized metabolism as an additional way to differentiate between colonies with similar phenotypes.
A major challenge in characterizing unknown microorganisms is distinguishing closely related isolates. IDBac provides researchers an easy and fast way to characterize isolates through protein and small molecule profiling. IDBac provides a visual comparison of specialized metabolite production within a bacterial sample and can provide insight into a broad range of research topics from ecological studies to drug lead discovery.
There are many ways that MALDI data can be saved between and among instruments. If you have trouble getting files to work with IDBac, submit an issue to IDBac's GitHub. Using a sterile toothpick, transfer a small portion of a bacterial colony to the appropriate spot on a clean MALDI plate.
Spread the bacterial colony evenly over the spot so the spot appears as flat as possible. Overlay one microliter of 70%mass spectrometry grade formic acid onto the sample and matrix control spots and allow the acid to air dry in a chemical fume hood. Next, add one microliter of previously prepared MALDI matrix solution to the sample and matrix media control spots and allow to air dry completely.
After setting up the MALDI TOF mass spectrometer, acquire the spectra. Save the protein spectra in one folder and the specialized metabolite spectra in a second separate folder. To begin this procedure, download the IDBac software.
Double-click the downloaded install_idbac to initiate the installer. Next double-click the IDBac desktop shortcut to launch IDBac which will open on the introduction tab by default. Click on the Starting with Raw Data tab and choose from the create an IDBac experiment menu the type of data to be used with IDBac.
When setting up the conversion and processing of data files, input a descriptive name for the experiment where prompted and click on raw data folder and select the appropriate folder. Then click on Process Data. After converting the files and processing them with IDBac, navigate to the work with previous experiments page and select an experiment to work with.
Add information about samples using the menu click here to modify the selected experiment. Input information into the autopopulated spreadsheet and press Save. When ready to begin the analysis, ensure the experiment to work with is selected.
Then select protein data analysis. In the protein data analysis page, choose the peak peaking settings and evaluate the protein spectra of samples via the displayed mirror plots. Adjust the percentage of replicates in which a peak must be present in order for it to be included for analysis.
Using the mirror plots as visual guidance, adjust the signal to noise cutoff that retains the most genuine peaks and the least noise noting that more replicates in a higher percentage peak presence value will allow selection of a lower signal to noise cutoff. Following this, specify the lower and upper mass to charge cutoffs dictating the range of mass values within each spectrum to be used in further analysis by IDBac. Within the protein data analysis page, select the Dendrogram tab for allow for grouping samples into a dendrogram according to user selected distance measures and clustering algorithms.
Click select samples on the menu and follow the instructions to select samples to include in the analysis. Only samples that contain protein spectra will be displayed within the available samples box. Use the default values for the distance and clustering algorithms and select intensities as the input.
To display bootstrap values on the dendrogram, enter a number between two and 1, 000 under bootstraps. To begin customizing the dendrogram, open the adjust the dendrogram menu. To color the dendrogram's lines, select click to modify lines and select the desired options.
To plot information from the spreadsheet next to the dendrogram, select the button incorporate info about samples. This will open a panel where a category will self-populate based on the entered values. To insert samples from another experiment, select the menu button insert samples from another experiment and follow the directions in the newly opened panel.
Proceed to the small molecule data analysis page to enable data visualization by principle components analysis and metabolic association networks which use bipartite networks to display the correlation of small molecule mass to charge values with samples. Click and drag on the dendrogram to highlight select samples of interest to be analyzed. If no samples are highlighted or no protein dendrogram was created, a metabolite association network of either a random subset or all samples will appear respectively.
To subtract a matrix media blank in the metabolite association network, open the menu select a sample to subtract and choose the appropriate sample to use as a blank. Open the menu show/hide MAN settings to select the desired values for a percentage of peak presence and replicate, signal to noise and upper and lower mass cutoffs. Use the small molecule mirror plots to guide the selection of these settings.
For reporting results, copy the text within the suggestions for reporting MAN analysis paragraph to provide the user defined settings used to generate created metabolic association network. Six strains of Micromonospora chokoriensis and two stains of Bacillus subtilis were analyzed using data in the IDBac software. Following directions in the starting with raw data tab, the option click here to convert Bruker files was selected and the IDBac provided instructions were followed for each data set.
To the automated conversion and pre-processing peak peaking steps, a combined IDBac experiment was created by transferring Bacillus and Micromonospora samples from the two experiments into a single experiment. The resulting analysis involved comparing protein spectra using mirror plots which was useful for evaluating spectra quality and adjusting peak peaking settings. A screenshot of the protein clustering results with default settings selected is shown here.
The dendrogram was colored by adjusting the threshold on the plot. Of note is the clear separation between genera with both M.chokoriensis and B.subtilis isolates clustering separately. By clicking and dragging across the protein dendrogram, it was possible to rapidly create metabolic association networks to compare only the B.subtilis strains, only the M.chokoriensis strains, and all of the strains simultaneously.
The primary function of these networks is to provide researchers with a broad overview of the degree of specialized metabolite overlap between bacteria. When working with new data, use IDBac's mirror plots to ensure your data makes sense and spectra are high quality. Critically evaluate your experimental design and results at every step.
IDBac allows researchers to build small and diverse libraries of microorganisms for further investigation. This greatly reduces costs associated with traditionally large and redundant microbial libraries. Because IDBac allows you to visualize specialized metabolite overlap within highly similar phylogenetic groups, it can be used to generate research questions and hypotheses that link two typically disconnected fields.
Formic acid is caustic and should be handled in a chemical fume hood. Some environmental isolates may pose potential health hazards and all strains should be treated as biosafety level two.
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.