what three main approaches can be used by microbiologists to identify microorganisms
Microbial Identification
Microbial identification can exist defined as "microbial characterization by a express spectrum of tests pre-chosen and appropriate to the problem being studied" [1].
From: Pharmaceutical Microbiology , 2016
Microbial identification
Tim Sandle , in Pharmaceutical Microbiology, 2016
9.7 Conclusion
This affiliate has outlined some of the microbial identification techniques undertaken. The techniques described have been divided between phenotypic and genotypic methods. It is of import to note that groupings established past phenetic and phylogenetic systems practice non e'er concur and within each grouping the methodological differences and varying contents of unlike databases will sometimes lead to conflicting analyses.
It is additionally important to understand that any systems used to place leaner, whether phenotypic or genotypic, volition have limitations, because no single test methodology will provide results that are 100% authentic.
In terms of selecting between methods, this will depend on costs and resources, the time that the microbiologist is prepared to expect for and what level of identification is required. Some microbiologists are of the view that the only way to characterize a microorganism correctly is through a "polyphasic arroyo" that is a combination of phenotypic testing methods and genotypic testing methods. This is, however, far too time consuming and too prohibitively expensive for standard laboratories. Most routine testing laboratories select phenotypic examination kits and use established contract test facilities where genotypic testing is required.
What is important, when making a option, is to go back to basics and consider: what is the purpose of the identification? what does the microbiologist need to know? and what does the consequence tell the microbiologist? These questions can help with selecting and implementing the appropriate microbial identification examination.
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Microbiology in Clinical Pathology
K.Chiliad. Frank , in Pathobiology of Human Disease, 2014
In situ hybridization, PCR, and sequencing
The use of molecular techniques in microbial identification has increased dramatically over the by decade and at that place is still a rapid charge per unit of introduction of new and revised methods and applications. Detection of an organism's nucleic acrid does not require a viable organism, which is a big advantage. Molecular methods overall tend to exist very sensitive and specific. Fluorescence in situ hybridization (FISH) is a technique using a tagged nucleic acrid probe on cultures or fixed tissue to identify the DNA of the suspected organism ( Figure 34 ). PCR is a powerful method and is used in a number of means. PCR uses a heat-stable Deoxyribonucleic acid polymerase combined with Deoxyribonucleic acid oligomers (primers) of a specific sequence designed to amplify a specific target. Multiple cycles of heating denature the Dna, followed past cooling to allow specific hybridization of primers, and and then extension of synthesized product by the polymerase enzyme can result in a millionfold increase in the DNA of interest. The process can be completed in several hours or shorter with new fast instruments ( Figure 35 ). Multiple adaptations of PCR include contrary-transcription PCR, which includes an initial step to convert RNA into DNA, followed by Deoxyribonucleic acid amplification, or real-fourth dimension PCR that permits quantification of the starting nucleic acid. The Dna production is measured in each bike, often by a fluorescent Dna probe, and the amount of indicate on each bicycle is proportional to the starting material ( Figure 36 ). Real-time PCR is used for cytomegalovirus, Epstein–Barr virus, BK and JC polyomaviruses, herpesviruses, and quite a few more than targets. The conversion of viral testing from viral culture techniques to molecular methods had a huge impact on test turnaround fourth dimension. Some viral cultures previously took fourteen–21 days, but results can now be obtained in a few hours. Most of virology testing has moved from viral culture, shell-vial culture, rapid immunochromatographic assays, and DFA assays to real-fourth dimension PCR assays. Multiplex PCR includes multiple primer sets in a single reaction with a number of ingenious ways to separate and observe the signal of the specific pathogens. Assays currently may have sixteen or more targets in an individual analysis. Respiratory virus detection was greatly improved past multiplex methods compared to culture, DFA assays, antigen detection, and single-target PCR assays. Deoxyribonucleic acid sequencing of the gene for the 16S ribosomal subunit, a component of the cellular poly peptide synthesis car, is used to place bacteria that may not be identified by phenotypic methods described earlier. Sequencing ribosomal or other genes may also be used for identification of fungi, mycobacteria, and viruses.
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Forensic Microbiology
S.Y. Hunt , ... Southward. Morse , in Encyclopedia of Microbiology (Third Edition), 2009
Nucleic acrid-based assays
Nucleic acrid-based assays for microbial identification, label, and attribution purposes are widely used in the forensic loonshit to associate (and exclude) DNA-containing biological bear witness with suspected sources. Ideally, for attribution, the forensic scientist attempts to narrow the possible sources of a sample while excluding nigh if not all other sources. This level of individualization may non ever be achievable. To enhance attribution capabilities, a major thrust of microbial forensics is the use of nucleic acid-based assays that enable association (or elimination) of a pathogen with specific sources on the basis of genetic information from the total or partial genome of that pathogen. The use of these assays is coordinating to the role they play in human Deoxyribonucleic acid forensic analysis, where they are used on biological evidence to associate or exclude suspected individuals. Even so, the nucleic acid-based methods currently used in microbial forensics cannot routinely achieve the level of attribution that is achieved with human Deoxyribonucleic acid forensics. The vast numbers of microorganisms, their complex biological and ecological diversities, and their capacity for genetic exchange complicate the analysis and estimation of evidence in ways that exercise not impact homo DNA forensics.
Prior to the introduction of the polymerase chain reaction (PCR), nucleic acid-based microbial identification was express to techniques such equally hybridization and typing by brake fragment length polymorphism (RFLP) analysis. Such techniques required relatively large amounts of nucleic acid and were laborious, fourth dimension-consuming, and not amenable to automation. The advent of PCR led to the development of sequence-specific amplification methods and a broad range of techniques that may ultimately meet the needs of the microbial forensics community.
PCR is typically thought of equally a forepart-end assay component, whereby the PCR stop products are assayed to decide the genetic profile of the sample. This notion changed with the appearance of real-time PCR, which has become the genetic typing method of choice for characterizing microbes. The main benefits of real-time PCR assays are the extremely low limits of detection (budgeted unmarried copy detection) and inherent specificity that enables the blueprint of highly discriminating assays that are capable of distinguishing closely related molecular species. Farther advantages of using this technique include (1) a broad dynamic range of quantification (up to vii orders of magnitude); (2) a brusk turnaround time (every bit little as thirty min); and (3) a reduction in laboratory contagion (analysis is independent within a closed tube). The capacity to achieve unambiguous pathogen identification in as brusk a fourth dimension as possible is broadly recognized as a fundamental component in microbial forensic applications, public wellness investigations, and biodefense.
Various methods are used to identify markers that are targeted in real-time PCR assays. The most constructive approach for comprehensive genetic variation discovery is high-throughput shotgun sequencing used by large genome centers. Whole genome sequencing is the preferred method for discovering genetic variation of value to forensic analysis. The ability of this approach was demonstrated by a comparing of the genome sequence of B. anthracis Ames isolated from ane of the victims of the 2001 bioterrorist anthrax attack to the genome sequence of a reference B. anthracis Ames strain. This comparison led to the identification of sixty polymorphic loci within the B. anthracis Ames genome that were comprised of SNPs, INDELS, and tandem repeat motifs. A number of these markers were found to separate a collection of anthrax isolates into singled-out families. Although several genomes were sequenced to discover variants of the Ames strain of B. anthracis in the ongoing FBI investigation, it was a very costly process. Thus, current whole genome sequencing methodology is unlikely to be used routinely in biocrime cases. The relatively high costs of genome sequencing will limit its use for screening large repositories and population studies, until some of the newer high-throughput sequencing technology capabilities are realized.
If a reference sequence is available, resequencing using microarrays is an inexpensive, high-throughput alternative to whole genome sequencing. With proper microarray design, a large number of parallel analyses can be carried out simultaneously, and thousands of assays tin can be run at i fourth dimension. Thus, a substantial increment in throughput can be realized, and genomes of many samples can be scanned speedily. High-density array chips are being used to discover microbial polymorphisms, define population multifariousness, map virulence and antimicrobial resistance genes, and identify pathogens of consequence. The problem has been that mobile genetic elements and genes (including plasmids) can move horizontally between species and perhaps confound species identification. However, because of the high-density oligonucleotide assortment on a bit surface, multiple 'unique' regions of whatsoever species, strain, or isolate can be typed so that confidence in a correct identification is increased over results from assays that type only ane or a few regions of a genome.
The chip approach provides the capability to screen simultaneously a large number of microorganisms and affords a sensitivity level desirable for forensic demands. Resequencing arrays were designed to analyze over three million bases of the B. anthracis genome based on a panel of 56 strains. Replication studies showed very loftier sequence quality that was comparable to that obtained by shotgun sequencing. Chip applied science will enable resequencing in a short menstruation of fourth dimension while screening multiple pathogens with high sensitivity, specificity, and nearly complete genome coverage. Not only will species and strain detection be possible, but chips also offer the possibility of detecting genetically engineered or modified strains through the detection of genes encoding antibody resistance or toxins as well every bit other heterologous genes. This awarding is evidently valuable for forensic attribution, but also has tremendous public wellness and homeland security applications.
The genotyping of biothreat agents presents a challenge when compared with other infectious disease-causing microorganisms in that the genetic human relationship betwixt many medically of import microorganisms has been determined based on SNPs, the presence of known virulence factors, and macro restriction patterns of the genomic Deoxyribonucleic acid. However, agents such as B. anthracis, F. tularensis, Yersinia pestis, and Brucella spp. are relatively monomorphic and exhibit little molecular variation amid isolates from like geographic areas. Thus, the identification and use of rare variants will be meaning for obtaining the deepest resolution possible. Ongoing efforts to sequence multiple strains of these biothreat agents volition facilitate the development of nucleic acid-based assays for attribution purposes.
A nested hierarchal strategy for subtyping these agents has been proposed. Progressive hierarchical resolving assays type genetic markers based on stability. SNPs are more often than not very stable and good for lineage studies, but tend to have a lower power of resolution for isolate individualization. Variable number tandem repeat (VNTR) loci (including microsatellites) are less stable and tend to evolve more than chop-chop; therefore, these loci (similar to human Dna forensic typing) volition be more useful for distinguishing between similarly related samples.
A popular sequence-based bioinformatics approach that is used in attempts to establish the history and 'uniqueness' of a bacterial strain is the analysis of phylogenetic relationships. Bacterial phylogenies can exist elucidated via the comparison of conserved regions of the genome. Phylogenetically informative gene sets include the ribosomal RNA genes that encode the 5S, 16S, and 23S rRNA genes and the intergenic spacer regions betwixt these genes. The most widely used universal gene for phylogenetically positioning a sample (or for speciation) is the 16S rRNA gene. Yet, relying on a single region for speciation may not be sufficient and oftentimes is incapable of strain-level resolution. To gain further resolution, other conserved or universal genomic regions tin can be examined.
Multilocus sequence typing (MLST) analyzes 450–500 bp internal fragments of a minimum of five to seven housekeeping genes common to many bacteria. Most, if not all, bacterial species studied to appointment tin be uniquely characterized using MLST. Data profiles of isolates are compared with those housed in a database. With proper design, many strains within a given species are distinguishable. For example, MLST has been useful in differentiating B. anthracis from its most-neighbors and in validating assays capable of differentiating virulent, vaccine, and avirulent B. anthracis strains. The real-time PCR assays used in these analyses are as well capable of detecting B. anthracis pXO1 or pXO2 virulence plasmid markers that may reside in near-neighbor Bacillus cereus clade members. The advantage of MLST is that sequence data are readily exchangeable among laboratories. Thus, standards and databases, much like those for human forensic Deoxyribonucleic acid analyses, can be generated.
Interpretations of genetic data from a clinical isolate, a laboratory-derived strain, or a reference database and its similarity to an evidence sample can be fabricated quantitatively or qualitatively. Quantitative assessments convey the significance of an analytical result and rely on extant diverseness data. Because of the lack of diversity data and limited knowledge of worldwide diversity in many cases, there can be a high degree of dubiety associated with findings of a 'matched' (or similar) sample with some reference sample. While most scientists are becoming accepted to statistical assessments of their data, this dubiousness will limit the utilise of some quantitative interpretations of microbial forensics results. However, qualitative assessments are also useful. They can provide direction for an investigation or indicate those samples that are dissimilar and could not be recently related to the prove in question.
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Clinical microbiology
Morgan A. Pence , Rachael Liesman , in Gimmicky Practice in Clinical Chemistry (Fourth Edition), 2020
DNA sequencing
Dna sequencing is the gold standard for microorganism identification. The 16S ribosomal RNA (rRNA) cistron is the about common sequencing target for leaner and is 1542 base of operations pairs (bp) in length. Sequencing the get-go 500 bp often provides enough differentiation for identification purposes, but sure organism groups require sequencing of the total-length 16S rRNA cistron for differentiation, while other genera are homologous across the entire factor and require sequencing of boosted genes for differentiation. The additional gene(southward) required depends on the genus, and examples include rpoB, recA, tuf, gyrA gyrB, and cpn60. Many clinical laboratories that perform 16S sequencing only sequence a portion of the 16S rRNA cistron, while few sequence the entire 1542 bp. Most clinical laboratories practice not perform sequencing of the supplemental genes. Once a sequence is obtained, it is compared with a public or private database for organism identification. Database choice is critical, as some databases are curated and routinely updated and others are static. For more information on selecting an advisable database, refer to the Clinical and Laboratory Standards Institute (CLSI) MM18 document (Interpretive Criteria for Identification of Bacteria and Fungi by Targeted DNA Sequencing, second edition) [sixteen].
Interpretive criteria are based on the aforementioned CLSI MM18 certificate [16]; ≥97% homology is required for genus-level identification of bacteria, while ≥99% homology is required for species-level identification. Less than 95% homology indicates an incomplete database or potentially a novel species. Although 16S rRNA sequencing is the virtually common, information technology does not provide sufficient differentiation for particular groups of bacteria, such as Escherichia coli and Shigella spp., which are substantially the aforementioned organism, and Bordetella spp. In such cases, sequencing of additional genes or biochemical reactions is required for consummate identification.
For yeast and filamentous molds, the well-nigh common sequencing targets are the internal transcribed spacer regions (ITS), ITS1 and ITS2. ITS1 and ITS2 are variable regions located between the conserved rRNA genes. ITS2 alone is sufficient for discriminating multiple Candida spp. but not for other yeasts or molds. In improver to ITS1 and ITS2, the D1/D2 region of the 28S rRNA gene may be used. A consensus has non been reached in regard to cutoff values for genus- and species-level identification of fungi.
Although Deoxyribonucleic acid sequencing is the gold standard, the methodology is technologically challenging, has a slow turnaround time, is not widely bachelor, and is relatively expensive. Because of these drawbacks, information technology is not routinely used to identify microorganisms and is more commonly used every bit a backup or secondary method to other identification methods.
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Raman spectroscopy for biological identification
T.J. Ronningen , ... A.P. Bartko , in Biological Identification, 2014
11.v Conclusions
Battelle Memorial Institute has adult and tested a microbial identification system that is based on Raman spectroscopy (REBS) and has proved that it is well suited to notice and identify closely related individual Bacillus cells with greater than 96% probability of correct identification at the species level. Detailed assessments of Battelle'southward approach have shown its applicability to security, defence force and industrial applications, because results have shown that differentiation between nigh-neighbor Bacillus species is possible through Raman spectroscopic methods. Experimental studies likewise show that the technology can provide identification information faster than currently available technologies that use reagents or consumables. Having actionable information, in minutes rather than hours, will enable faster decisions well-nigh local environmental threats in security applications and provide heightened manufacturing procedure awareness in industrial applications. Ultimately, decreasing the time to an actionable result volition atomic number 82 to a safer society and more economical products.
Testing and evaluation strategies for rapid spectroscopic biological identification of systems typically use adulterate or deactivated pathogens, primarily for safe and convenience. Until recently, rut-killed or gamma-irradiated biological agentlike organisms have been used in testing and evaluation considering the states of the killed material seldom change the upshot of genomic-based identification processes. Genomic-based identification processes target genomic content rather than organism integrity or abyss. Phenotypic-based identification systems rely on the pathogen's structural integrity, which is often lost during neutralization. Therefore, rut-killed or gamma-irradiated organisms are not ideal for testing phenotypic methods such as spectroscopic identification. Nonetheless, phenotypic identification of irradiated organisms remains possible; however, the results of the testing and evaluation should be interpreted carefully, and a stardom made between viable and dead organisms.
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Evolving platforms for clinical mass spectrometry
J.Y. Yang , D.A. Herold , in Mass Spectrometry for the Clinical Laboratory, 2017
five MALDI-TOF
Afterwards receiving FDA clearance in the U.s. for microbial identification in 2013, the utility of MALDI-TOF MS, expanded to identification of yeasts, fungi, and antibiotic resistance [24–30]. The potential for the utilize of MALDI-TOF platforms in other sections of the clinical lab has nonetheless to be exploited [31]. MALDI-TOF mass spectrometers possess a large dynamic range and between all configurations, TOF can analyze well-nigh analytes of involvement. 1 limitation of MALDI is considered to be matrix interference, matrix referring to the small organic acid used to help the laser desorption and ionization process. Notwithstanding, with the precision and accuracy of electric current MALDI-TOF mass spectrometers, this is less of a limitation for the analysis of larger biomolecules. For MALDI-TOF, the sample preparation can be uncomplicated and sample requirement minimal. Sample deposition on the target plate is automatable and data conquering can exist batched to yield rapid results (lxxx spectra, each an average of 25,000 light amplification by stimulated emission of radiation shots, in less than 30 min with a laser operating at 1 kHz).
MALDI-TOF, an approach that harbors a stigma of being solely qualitative, has been shown to be quantitative. In conjunction with immunoaffinity capture engineering science, such as stable isotope standards and capture by anti-peptide antibodies (SISCAPA Assay Technologies), MALDI-TOF was used to quantify proteins [32], such as cardiac marker BNP [33], for biomarker evaluation for quantitative proteomics [33–36], to differentiate different subtypes of flu A virus within one hr of sample preparation [37], for accented quantitation of CRP [38], and to quantitate a poly peptide C inhibitor peptide with CV two.ii% over a 100-fold dynamic range [39]. Percentage Hemoglobin A1c (HbA1c) a diagnostic and therapeutic mark for diabetes, is a relative quantitation with a strong linear correlation with total glycated beta chain. MALDI-TOF MS of diluted whole claret detects total glycated beta chain of hemoglobin, which linearly correlates with HbA1c determined by cation exchange HPLC [40].
Other applications of MALDI-TOF include detection of human herpesvirus [41], oligonucleotide analysis to discover genomic single nucleotide polymorphisms [42], and imaging MS, which is discussed later in this chapter.
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Techniques for Oral Microbiology
In Atlas of Oral Microbiology, 2015
2.2.four.2 Biochemical Tests
Biochemical tests are among the most important methods for microbial identification. Routine biochemical tests include tests for carbohydrate fermentation (Effigy ii.xviii(A)), methyl red (Figure 2.18(B)), citric acid utilization (Figure 2.18(C)), and hydrogen sulfide production (Figure 2.18(D)).
Microbial biochemistry tests shorten the fourth dimension required to place microbes, reduce costs, and ensure or enhance the accuracy of identification of an unknown sample. It is the fastest developing trend in microbial identification. In recent years, the rapid commercial test kits for anaerobic leaner accept go available.
The nearly representative biochemical test kits are the Minitek identification organisation using paper substrates, API-20A system using dry powder substrates, PIZYMAN-IDENT rapid enzyme activity assay system using main materials, RaPID-ANA systems, and fully automated microbial identification systems.
The same microbial biochemistry reaction plate includes 30 biochemical matrices and their related biochemical test indicators, phosphate buffered saline (PBS), bacterial turbidity standard tube, and viii identification serial (Tabular array 2.1).
Master nomenclature series | Sub-classification serial |
---|---|
Gram-positive anaerobic cocci | I. Staphylococci and micrococci Two. Streptococcus |
Gram-negative anaerobic cocci Gram-positive anaerobic nonspore bacillus | |
Gram-negative anaerobic nonspore bacillus | I. Does not produce black pigment II. Produces black pigment |
Gram-negative anaerobic Clostridium or Enterobacter Gram-negative facultative anaerobic bacillus Gram-negative Campylobacter Clostridium |
Due to the unlike types of experiments performed, the readouts for results are different. For example, esculin hydrolysis can be directly observed: black is positive, while colorless is negative. For sugar and alcohol fermentation acid test, BM (bromothymol bluish-methyl red, BTB-MR) must be added to the result as a pH indicator. Cherry-red or yellowish indicates a positive reaction, while light-green or blue indicates a negative reaction (Figure 2.eighteen(E) and (F)).
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Anaerobic Infections
Hannah M. Wexler , in Molecular Medical Microbiology (Second Edition), 2015
Specimen Collection and Transport
If classical microbiological techniques are to be used for diagnosis and microbial identification, proper drove and send of specimens are critical. Proper transport will require the use of an oxygen-free environment for the time of transport. Care must be taken non to contaminate the specimens with normal flora. This is highlighted in the case of suspected aspiration pneumonia; expectorated sputum cannot exist used because it will exist contaminated with the big numbers of anaerobic isolates in saliva. In this case, needle aspiration or bronchoalveolar lavage tin can exist used. A detailed description of specimen drove for subsequent anaerobic culture may be found in the Wadsworth Anaerobe Lab manual [112], too as other microbiology textbooks. Anaerobic jars or numberless should exist used to transport the sample from the site of drove or operating room followed by anaerobic processing for samples. If this is done correctly, the proportion of anaerobes that will exist isolated will be significantly higher than if the specimen is but processed unremarkably [113].
If identification by DNA sequencing is to exist used, and so viability of the organisms will not be important but avoidance of normal flora, which is not part of the infection, is still crucial, so specimen collection requirements that avoid normal flora volition be the same.
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Current and Emerging Technologies for the Diagnosis of Microbial Infections
Lori Bourassa , Susan M. Butler-Wu , in Methods in Microbiology, 2015
1.ii Commercially Available MALDI-TOF MS Platforms
There are currently three commercial MALDI-TOF MS platforms being used for microbial identification: the MALDI Biotyper (Bruker Daltonics), the VITEK MS (bioMérieux) and the Andromas MS (Andromas SAS) systems. The latter system is predominately used in Europe and is not bachelor in the United states of america. There are differences between the 3 systems with respect to instrumentation, software, identification algorithms and the proprietary reference databases used for identification (summarised in Tabular array i).
MALDI-TOF MS System | Manufacturer | Instrumentation | Identification Algorithm | Currently Available Databases | Organisms Included in Database | Depth of Spectral Coverage | Regulatory Status |
---|---|---|---|---|---|---|---|
Bruker MALDI Biotyper MS | Bruker Daltonics, Billerica, MA | Desktop system | Algorithm: Spectral comparisons between the unknown organism and reference spectra | CA System | Aerobic and anaerobic bacteria, yeast | Spectra for > 280 species | FDA canonical |
Biotyper—RUO | Gram-positive and Gram-negative bacterial spectra (not-mycobacterial) anaerobes and yeast | Spectra for 2200 species of > 300 genera | Not FDA approved | ||||
Output: Log score values ranging from 0.000 to iii.000 | Mycobacteria Library v2.0-RUO | Mycobacteria | 131 species | Not FDA approved | |||
Filamentous Fungi Library 1.0—RUO | Fungi | 124 species, 30 genera | Not FDA approved | ||||
Security-Relevant Database | Select agents | Non FDA canonical | |||||
VITEK MS | bioMérieux, Durham, NC | Floor model | Algorithm: Advanced Spectral Classifier | VITEK MS | Aerobic and anaerobic bacteria, yeast | 193 species | FDA approved |
Output: Conviction value that ranges from 0% to 100%. | SARAMIS v4.12 database—RUO | Gram-positive and Gram-negative bacterial spectra, anaerobes, yeast, mycobacteria, some select agents and moulds | > 1300 species | Non FDA canonical | |||
Andromas | Andromas SAS, Paris, French republic | Flooring or desktop organisation | Algorithm: Spectra from unknown organism queried against database | Bacteria | Non FDA approved | ||
Yeast, Aspergillus species | Not FDA approved | ||||||
Output: Conserved species-specific peaks. Minimum relative intensity must be above threshold | Mycobacteria | Not FDA approved |
RUO, research use only.
The Bruker MALDI Biotyper system compares the spectra of the examination microorganism to a database of reference spectra which are generated past repeated measurements of a particular strain consolidated into a 'primary spectral contour' (MSP) (Bruker, 2008). Spectral comparisons are made based on the position, intensity and frequency of the component peaks. The database can also be supplemented with additional MSPs by the user for the Research Use Only (RUO) system (Bruker, 2011). Separate RUO databases are also available from the manufacturer for mycobacteria and filamentous fungi, respectively. The MALDI Biotyper produces log score values ranging from 0.000 to 3.000. A score ≥ 2.0 indicates probable identification to the species level; scores betwixt 1.700 and 1.999 indicate probable genus-level identification and scores < 1.700 are not considered reliable for identification (Clark et al., 2013; Patel, 2013). For the MALDI Biotyper CA system, which is approved for in vitro diagnostic (IVD) use in the Us, a score value ≤ 1.999 represents no identification. In the United States, the database composition varies betwixt RUO and IVD systems, although this is not the case in Europe. Importantly, some laboratories take validated the use of lower score thresholds for the identification of certain microorganisms. Some published studies documenting operation of the organization for certain microorganism groups therefore use alternative score thresholds rather than those specifically recommended by the manufacturer.
As with the MALDI Biotyper, the bioMérieux VITEK MS system is available in both RUO- and IVD-cleared formats (VITEK MS RUO and VITEK MS, respectively). For the former, the SARAMIS database (previously office of the Shimadzu Axima-iD Plus system) is queried using one of two algorithms. While the get-go algorithm matches spectra, the 2nd converts the spectra into a list of peaks and intensities that are then compared against 'SuperSpectra', derived from at least 15 individual isolates grown nether a variety of civilization media and growth atmospheric condition. The peaks are weighted according to their specificity for organism identification with the output beingness a confidence value that ranges from 0% to 100%. Scores > ninety% are indicative of species-level identification (Clark et al., 2013; Kok, Chen, Dwyer, & Iredell, 2013; Patel, 2013). The VITEK MS uses an 'Advanced Spectra Classifier', whereby the spectral peaks of the test microorganism are detected and sorted by mass and intensity into a serial of 1300 bins that are weighted according to their importance for identification. Output is colour coded to reverberate high (green), medium (yellowish) or low (red) conviction, respectively. Entries from both mycobacteria and filamentous fungi are present in the Saramis and in the upcoming IVD v3.0 databases (Mather, Rivera, & Butler-Wu, 2014; Panagea et al., 2015).
The Andromas system uses iii different databases (bacteria, yeasts + Aspergillus species and mycobacteria) and is predominantly used in Europe. At that place are multiple spectral profiles corresponding to each microorganism in the database with the comprising spectra generated after growth on different types of culture media without extraction. Later query of the appropriate database with spectra from an unknown microorganism, a percent similarity between the reference spectra in the database and the unknown organism is produced. Results are then interpreted as a 'practiced identification', 'identification to be confirmed' or 'no identification' based on manufacturer-defined thresholds (Bille et al., 2012; Kok et al., 2013).
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Systems Biology of Bacteria
J.S. Hallinan , in Methods in Microbiology, 2012
5.3 Decision copse
Decision trees are visually like to the graphical representation of HMMs, merely operate on very different principles. A determination tree is a type of classifier, which takes a prepare of inputs describing individual information items, and classifies each detail into one of a set of categories. Determination tree algorithms are trained using a set of input examples, each labelled with the category to which it belongs. The algorithms examine the input data to determine which variable best distinguishes between the categories, and which values of this variable are informative. This variable forms the root of the tree. The remaining variables are scrutinised for the next-almost-informative variable, which generates the 2nd level of the tree. The process continues until maximum separation between the output categories is accomplished. Not all input variables will be included in the tree, and so the decision trees also provide a means of feature option.
For example, (Dieckmann and Malorny, 2011) used a determination tree to classify serovars of Salmonella enterica subsp. enterica using data from MALDI-TOF MS. Role of the resulting tree is redrawn beneath (Effigy 2.viii).
In that location are many decision tree algorithms, each of which uses different ways of identifying informative variables. I of the nigh widely used algorithms is C4.5 (Quinlan, 1993). C4.5 is freely bachelor, although it is no longer supported. The successor of C4.5, C5.0 is simply available as source lawmaking, which requires a compiler for the C linguistic communication, and is therefore less accessible to the casual user.
The C4.v algorithm uses a metric chosen entropy, which is derived from information theory (Shannon, 1948). Claude Shannon was an American mathematician and electrical engineer who worked on communications theory. Amongst many other achievements, he produced a fix of metrics that are widely used in many different fields. One of these metrics is entropy, which is essentially a measure out of the randomness of a system (Figure two.nine). Entropy is the expected number of bits required to encode the classes, C1 or C2, of a randomly drawn member of a betoken, S, under the optimal, shortest-length code:
where p C1 is the proportion of South having blazon Cone, and p C2 is the proportion of type C2 (Figure 2.9). The information value of a variable, A, is calculated based upon its information gain: the expected reduction in entropy due to sorting on A.
At each iteration of the algorithm, the information gain is calculated for each variable A in turn, and the variable which provides maximum information gain is selected as the best conclusion attribute for that node. For each value of A, a new descendant node is created, and the training examples are sorted to the nodes. If the preparation examples are perfectly sorted, the algorithm terminates; otherwise the same procedure is carried out for each of the new nodes.
The C4.5 algorithm has the advantage of producing a single classification for each information item, and considering of its statistical basis, information technology is relatively robust to noisy data. It tends to produce short trees, with loftier information gain almost the root, a more often than not desirable feature. Decision copse also carry out a form of feature pick, since simply the most informative variables are included in the tree. From a applied bespeak of view, the algorithm is easy to employ, one time the requisite data has been prepared, and it produces results that are piece of cake to understand. Other widely used decision tree algorithms include the Chi-squared Automated Interaction Detector (Kass, 1980), and Multivariate Adaptive Regression Splines (Friedman, 1991).
Decision copse are useful for data where the input variables are either continuous or categorical, and the outputs are categorical. They have the advantage of being able to classify information into any one of multiple categories, merely they practise require a relatively large amount of data. Decision copse can be turned into sets of rules, which can then be incorporated into computer programmes, allowing the automated application of a trained decision tree to new data equally it is generated.
Decision trees have been widely used in microbiology inquiry, in areas such every bit microbial identification ( Rattray et al., 1999; Ferdinand et al., 2004; Dieckmann and Malorny, 2011), conclusion of the phylogenetic group of Escherichia coli (Clermont et al., 2000), protein functional notation (Azé et al., 2007), nomenclature of regulatory phenotype (Bachmann et al., 2009), ecology monitoring and tracking the source of medically important microbes (Lyautey et al., 2007, 2010; Ballesté et al., 2010) and understanding transcriptional command (Singh et al., 2005; Nannapaneni et al., 2012).
Software Availability
C4.5: http://www.rulequest.com/Personal/.
C5.0: http://rulequest.com/download.html (source lawmaking in C; will demand to be compiled).
Simple Determination Tree: http://sourceforge.net/projects/decisiontree/.
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