File Name: phylogenetic classification and identification of bacteria by mass spectrometry .zip
In general, the definite determination of bacterial species is a tedious process and requires extensive manual labour. Novel technologies for bacterial detection and analysis can therefore help microbiologists in minimising their efforts in developing a number of microbiological applications.
- Classification and Identification of Bacteria by Mass Spectrometry and Computational Analysis
- Phylogenetic classification and identification of bacteria by mass spectrometry
- Bacterial Taxonomics
Classification and Identification of Bacteria by Mass Spectrometry and Computational Analysis
Identification of these isolates was routinely performed by sequencing the 16S rRNA gene. Although this technique is an industry standard, it is time consuming and has poor resolving power for some closely related taxa. However, manufacturer-provided databases lack the bacterial diversity found in spacecraft-assembly cleanrooms.
With the use of this in-house database, bacterial isolates were successfully identified in concurrence with their 16S rRNA sequence-based classifications. The Committee on Space Research maintains the planetary protection policy for the protection of Earth and other planets from biological contamination. It is important to preserve planetary conditions for future exploration by preventing terrestrial microorganisms from contaminating other planetary bodies, including Mars and Europa, which are of particular interest for life-detection experiments.
When assembling spacecraft, microbial bioburden requirements must be met to minimize forward contamination. The NASA Standard Assay NSA is the method employed to continually monitor the microbial bioburden present on spacecraft hardware and associated surfaces throughout the assembly, testing, and launch operations of the flight project.
Surface samples obtained from spacecraft and spacecraft-assembly cleanrooms are heat-shocked, and bacterial survivors of this assay are used as a proxy for total microbial bioburden. Survivors of the NSA are often more resistant to sterilization techniques, making them more useful in understanding the potential of microbes to survive in the extreme conditions of space. Planetary protection engineers archive these isolated microorganisms for long-term storage to be used in research studies that may better assess forward contamination concerns.
Proper taxonomic characterization of spacecraft-associated microbes is crucial to understanding their metabolic capabilities and survivability under various conditions. Ultimately, understanding the microbial communities on spacecraft surfaces will allow researchers to better minimize the probability of forward contamination by improving sterilization procedures Moissl et al.
Although 16S rRNA sequence-based bacterial identification is the current industry standard, it is time consuming and has low phylogenetic resolution at the species level and poor discriminatory power for some genera Case et al. MALDI-TOF MS produces mass spectral peaks by generating ions from proteins, peptides, and oligonucleotides without fragmentation, allowing them to travel through a flight tube within a specific time based on their mass to charge ratio Vargha et al.
These protein profiles, which are primarily based on ribosomal proteins, can be used for microbial identification by generating a database of mass spectral profiles from known bacterial species Ryzhov and Fenselau, The slow progression in use of this technique for bacterial identification in other industries is due to the limited availability of relevant mass spectral libraries for use, and the bias of existing libraries towards clinical isolates Vargha et al.
Because of rigorous microbial reduction techniques and the selective nature of the NSA, the diversity of microbial communities found on spacecraft and associated surfaces is extremely limited and mainly contains spore-forming bacterial species belonging to the Bacillus genus. Samples were collected from flight hardware and associated surfaces from spacecraft-assembly cleanrooms during various NASA missions using Texwipe TX wipes and Puritan WC cotton swabs.
Colony PCR was performed on bacterial isolates. A distance matrix was produced using dist. A representative for each cluster OTU was chosen using the get. Eighty four unique OTUs were generated.
Isolates for MSP creation received eight biological replicates on the target plate and were prepared as previously described, and spectra were obtained in three separate intervals per target spot Zhang et al. Processing of raw spectral data, including baseline subtraction, smoothing, and outlier and flat line elimination was performed using flexAnalysis software Bruker Daltonics, Billerica, MA, United States.
MALDI BioTyper software was used to calculate a main spectrum using at least 10 spectra for each isolate a minimum of five spectra is recommended by Bruker. Each spectral line that constituted the MSP was verified to have a log score greater than 2. Isolates were prepared using a direct transfer technique and were identified in four biological replicates. Real Time Classification results were analyzed based on the log scores they received.
Build CCI parameter intervals were set at 10, and the mass lower bound and upper bound were 3, and 12, kDa, respectively. Dendrograms were constructed using a Euclidean distance measure and an average linkage algorithm. An MSP was generated for a single representative isolate from all 84 OTUs, and validated using real-time classification.
Mass spectra of these isolates clustered with their corresponding type-strain MSPs. Although the overall formation of clades is equivalent, the tree topology is not identical. These differences are due to differences in algorithms used to construct the phylogenetic tree and dendrogram.
This allows for the detection of proteomic differences across bacterial cells not considered by 16S rRNA sequencing. Neighbor-joining tree based on nearly complete 16S rRNA gene sequences A and Hierarchical clustering using Euclidean distance and average linkage algorithm of mass spectra B of 10 isolates from the PP archive and corresponding type strains.
This was demonstrated using the most highly-represented species present in this study, Bacillus firmus. A total of 29 representative strains of B. Scores of 0, shown in blue, indicate no correlation between isolates. Distances between mass spectra are represented as a color spectrum ranging from red, high similarity, to blue, low similarity. All members of the Bacillus pumilus taxonomic group, which is comprised of B.
The taxonomic identifications of 10 bacterial isolates from the B. Four of the ten isolates PF TABLE 1. Comparative taxonomic identification of 10 bacterial isolates belonging to the Bacillus pumilus taxonomic group comprised of B. Both identification methods indicate 34 strains belonging to potentially novel species.
The remaining isolates belong to taxonomic groups and were identified to closely related microbial species within the same genera based on 16S rRNA sequencing and were difficult to resolve taxonomically in the absence of type strain spectra. Bioburden levels on spacecraft surfaces are assessed using the NSA, and survivors from this assay are identified and archived.
In the past, 16S rRNA-based bacterial identification was implemented to identify archived microbial isolates. Though it is a gold standard, 16S rRNA sequencing has several intrinsic disadvantages, including time and inadequate resolution of closely related microbial taxa.
The success of this identification technique, however, is dependent on the reference strains found in the mass spectral database van Veen et al. Due to the clinical bias of available MALDI-TOF MS databases, it has been necessary for other researchers to establish custom reference databases of bacterial strains relevant to their studies Mellmann et al.
Since most of these other databases are inaccessible, proprietary and often costly to access, little spectral information is shared among researchers. The ability to accurately characterize strain-level differences is useful in understanding differences across redundantly isolated strains identified as the same species across multiple missions, such as those isolated from spacecraft hardware and associated surfaces. Although 16S rRNA gene sequencing is the gold standard of bacterial identification, it has poor resolving power at the species level due to its limited genomic representation.
Some bacterial species yield ambiguous taxonomic identifications using 16S sequencing due to their high sequence similarity to other species. These species are referred to as taxonomic groups, and cannot be differentiated solely by their 16S rRNA sequences Stackebrandt and Goebel, ; Venkateswaran et al. For example, Bacillus safensis, B. In other cases, such as the species Aeromonas veronii , the bacterial genome can contain up to six different copies of the 16S gene that all differ by up to 1.
This can yield different identifications depending on which copy was amplified, thus making 16S rRNA sequence identification ambiguous and inaccurate. This limited resolution and uncertainty in 16S rRNA-based bacterial identification has been resolved by sequencing other house-keeping genes such as rpoB or gyrB , which can have higher phylogenetic resolution than the 16S rRNA gene Case et al.
However, these techniques still employ the lengthy, labor-intensive processes of cultivation and isolation, cell harvesting, DNA extraction, PCR, gel electrophoresis, amplicon purification, sequencing, and sequence analysis. While 16S rRNA sequence identification is based only on a gene of 1, or fewer base-pairs, MALDI-TOF MS captures unique molecular signatures that are representative of a larger range of proteins and can clearly distinguish differences between two closely related species.
Since type strains are thoroughly characterized using multiple techniques i. The B. Strains that are potentially novel species and novel taxonomic group members will be falsely identified using 16S rRNA gene sequencing because they will often match to other closely related species with high sequence similarities. Storing and re-analyzing spectra using Bruker software will facilitate periodic screening of previously unidentified strains against an updated database.
Bacillus cereus is commonly found in the cleanroom environment, and is part of a taxonomic group that also includes Bacillus thuringiensis and the pathogenic Bacillus anthracis. The ability to rapidly and accurately identify isolates belonging to either of these species is not only beneficial to the medical community, but can result in a quicker response to a potential pathogen threat to engineers working in cleanroom environments.
We will continue to update and curate this database as more unknown bacterial strains are isolated, which will increase the accuracy and spectrum of species we are able to identify using this technique Rahi et al. The continual addition of type strains to the custom database will allow for increased confidence in identifying members of taxonomic groups.
This custom database will aid in the detection of potentially novel species within our archived microbial collection. The rapid high throughput nature of MALDI-TOF MS will allow for the identification of potential contaminants and dangerous pathogens which will directly feed into better alerting engineers through the spacecraft assembly process. MALDI-TOF MS-based bacterial identification will be extremely cost-effective in performing high throughput screening of bacterial isolates for selection of unique bacterial strains for long-term preservation.
We are willing to share our custom database upon request for research purposes, which will benefit other researchers working with similar microbial communities.
PV designed the project. HA and AS contributed equally to carrying out the research, performing the analysis, designing figures, and drafting the manuscript. The research described in this publication was carried out at the Jet Propulsion Laboratory, California Institute of Technology, under a contract with the National Aeronautics and Space Administration. The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
We are grateful to Dr. James N. Benardini for his support and encouragement. Bessede, E. Bizzini, A. Matrix-assisted laser desorption ionization-time of flight mass spectrometry as an alternative to 16S rRNA gene sequencing for identification of difficult-to-identify bacterial strains.
Bohme, K. Electrophoresis 33, — Bosshard, P. Calderaro, A. PLoS One 9:e Carbonnelle, E. Methods 89, — Case, R. Dieckmann, R. Rapid screening of epidemiologically important Salmonella enterica subsp.
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Phylogenetic classification and identification of bacteria by mass spectrometry
Angolini a. Eduardo J. Pilau a. Lopes-Oliveira b. Isabel N. Garcia b. Gozzo a.
In this study, we tested two recently published protocols for inactivation and disruption of mycobacteria, and we also examined the influence of different culture conditions four culture media and five cultivation times on mass spectral quality and the discriminatory power of the method. We found a significant influence of sample pretreatment method and culture medium on species identification and differentiation for a total of 10 strains belonging to Mycobacterium phlei and Mycobacterium smegmatis. Optimum culture conditions yielding the highest identification success rate against the BioTyper database Bruker Daltonics and permitting the possibility of automatic acquisition of mass spectra were found to be distinct for the two mycobacterial species examined. Similarly, individual changes in growth conditions had diverse effects on the two species. Most of them are nonpathogenic microorganisms living in the environment; however, some species cause dangerous contagious infections. Conventional methods for mycobacterial identification and species differentiation rely on their biochemical profiles and phenotypic traits, such as morphological features and growth rates. However, identification based on these phenotypic features may, quite often, result in erroneous identification Springer et al.
Overview DOI: Bacterial taxonomy comprises systematics theory of classification , nomenclature formal process of naming , and identification. There are two basic approaches to classification. Similarities may be derived between microorganisms by numerical.
Skip to search form Skip to main content You are currently offline. Some features of the site may not work correctly. DOI: Freiwald and S. Freiwald , S.
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A bacterial sample is subjected to a protein extraction method and then analyzed by mass spectrometry. Pattern-matching analysis software of.
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