BacteriaMS

Identification and assessment for MALDI-MS based bacterial analysis. It combines new measures for spectra similarity and a novel bootstrapping assessment that could lead to more reliable bacterial typing.

Requirement

• [R] (https://www.r-project.org/). As an alternative, the latest version of [Microsoft R Open] (https://mran.microsoft.com/open/) should be fine.

• [RStudio] (https://www.rstudio.com/) is recommended but optional.

Database

BacteriaMS uses peak lists for bacteria identification. A peak list is stored in a space-separated text (.txt) file including the m/z and intensity of all the peaks from a mass spectrum of a strain of bacteria with the first column as m/z and the second column as intensity, e.g.:

4376.517617 6369.468
4545.36698 14923.287008
4616.504007 3381.736378
4778.424564 6757.753407
4830.992604 10117.37512
……
9899.339424 4964.88939
10159.44407 1130.018489
10323.81304 5016.852179
10707.91308 1477.481354
11240.44102 1693.14288

Some example peak lists are provided in this repo.

In addition, below are some accessible databases where users can download MALDI-TOF spectra of bacteria, under their terms of usage.

• European Consortium of Microbial Resources Centres (EM-baRC): [http://www.embarc.eu/deliverables/EMbaRC_D.JRA2.1.4_D15.33_MALDI-TOF_DB.pdf]

• Robert Koch-Institute: [http://www.microbe-ms.com/]

• The Public Health Agency of Sweden: [http://spectra.folkhalsomyndigheten.se/spectra/]

The spectra are only compatible with the analysis software Biotyper (Bruker), but can be converted to peak list files using Bruker's software.

Usage

If you have everything installed, you can run identification for a sample spectrum as follows:

1. Run [main.R] (main.R) to load the functions.

2. Load the reference peak lists.

setwd(REF_PATH) 
# REF_PATH is the path of the directory that contains the reference peak list files.

reference.peaklists = local({
  filenames = list.files(pattern = '.txt')
  peaklists = lapply(filenames, read.table)
  names(peaklists) = sub('.txt', '', filenames)
  lapply(peaklists, normalize.intensity)
})

3. Load the sample peak list.

sample.peaklist = read.table(SAMPLE_PATH)
# SAMPLE_PATH is the path of the sample peak list file.
sample.peaklist = normalize.intensity(sample.peaklist)

4. Search database.

result = search.datebase.bootstrap(
  sample.peaklist,
  reference.peaklists,
  tolerance = 2000, # Unit: ppm
  method = c('eu', 'ieu', 'cosine'), # Similarity scoring method(s)
  bootstrap.times = 1000
)

result = lapply(result, function(res) {
  list(
    res$sample,
    genus = get.bootstrap.score(
      res$bootstrap, 
      function(x) sapply(strsplit(x, ' '), function(x) paste(x[1]))
    ),
    species = get.bootstrap.score(
      res$bootstrap, 
      function(x) sapply(strsplit(x, ' '), function(x) paste(x[1], x[2]))
    )      
  )
})

# Print the results (cosine as an example)
result$cosine[[1]]    # Print the matches ranked by the cosine scores.
result$cosine$species # Print the confidence scores at the species level.
result$cosine$genus   # Print the confidence scores at the species level.

The script [bootstrapping.R] (scripts/bootstrapping.R) runs a cross-validation test on a set of spectra. Each spectrum in the dataset was selected as the sample spectrum, and the other spectra were used to construct a reference database, respectively. Plots receiver operating characteristic (ROC) curves for identification.

Publications

Yang, Y., Lin, Y., Chen, Z., Gong, T., Yang, P., Girault, H., Liu, B., Qiao, L. Bacterial whole cell typing by mass spectra pattern matching with bootstrapping assessment. Anal Chem 89, 12556–12561 (2017). https://doi.org/10.1021/acs.analchem.7b03820.

License

BacteriaMS is distributed under a BSD license. See the LICENSE file for details.

Contacts

Please report any problems directly to the github issue tracker. Also, you can send feedback to liang_qiao@fudan.edu.cn