The Experts below are selected from a list of 379638 Experts worldwide ranked by ideXlab platform
Michael Buckley - One of the best experts on this subject based on the ideXlab platform.
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semi supervised machine learning for automated Species Identification by collagen peptide mass fingerprinting
BMC Bioinformatics, 2018Co-Authors: Michael BuckleyAbstract:Biomolecular methods for Species Identification are increasingly being utilised in the study of changing environments, both at the microscopic and macroscopic levels. High-throughput peptide mass fingerprinting has been largely applied to bacterial Identification, but increasingly used to identify archaeological and palaeontological skeletal material to yield information on past environments and human-animal interaction. However, as applications move away from predominantly domesticate and the more abundant wild fauna to a much wider range of less common taxa that do not yet have genetically-derived sequence information, robust methods of Species Identification and biomarker selection need to be determined. Here we developed a supervised machine learning algorithm for classifying the Species of ancient remains based on collagen fingerprinting. The aim was to minimise requirements on prior knowledge of known Species while yielding satisfactory sensitivity and specificity. The algorithm uses iterations of a modified random forest classifier with a similarity scoring system to expand its identified samples. We tested it on a set of 6805 spectra and found that a high level of accuracy can be achieved with a training set of five identified specimens per taxon. This method consistently achieves higher accuracy than two-dimensional principal component analysis and similar accuracy with hierarchical clustering using optimised parameters, which greatly reduces requirements for human input. Within the vertebrata, we demonstrate that this method was able to achieve the taxonomic resolution of family or sub-family level whereas the genus- or Species-level Identification may require manual interpretation or further experiments. In addition, it also identifies additional Species biomarkers than those previously published.
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Semi-supervised machine learning for automated Species Identification by collagen peptide mass fingerprinting
BMC, 2018Co-Authors: Michael BuckleyAbstract:Abstract Background Biomolecular methods for Species Identification are increasingly being utilised in the study of changing environments, both at the microscopic and macroscopic levels. High-throughput peptide mass fingerprinting has been largely applied to bacterial Identification, but increasingly used to identify archaeological and palaeontological skeletal material to yield information on past environments and human-animal interaction. However, as applications move away from predominantly domesticate and the more abundant wild fauna to a much wider range of less common taxa that do not yet have genetically-derived sequence information, robust methods of Species Identification and biomarker selection need to be determined. Results Here we developed a supervised machine learning algorithm for classifying the Species of ancient remains based on collagen fingerprinting. The aim was to minimise requirements on prior knowledge of known Species while yielding satisfactory sensitivity and specificity. The algorithm uses iterations of a modified random forest classifier with a similarity scoring system to expand its identified samples. We tested it on a set of 6805 spectra and found that a high level of accuracy can be achieved with a training set of five identified specimens per taxon. Conclusions This method consistently achieves higher accuracy than two-dimensional principal component analysis and similar accuracy with hierarchical clustering using optimised parameters, which greatly reduces requirements for human input. Within the vertebrata, we demonstrate that this method was able to achieve the taxonomic resolution of family or sub-family level whereas the genus- or Species-level Identification may require manual interpretation or further experiments. In addition, it also identifies additional Species biomarkers than those previously published
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Species Identification by analysis of bone collagen using matrix assisted laser desorption ionisation time of flight mass spectrometry
Rapid Communications in Mass Spectrometry, 2009Co-Authors: Michael Buckley, Matthew J Collins, Jane Thomasoates, Julie WilsonAbstract:Species Identification of fragmentary bone, such as in rendered meat and bone meal or from archaeological sites, is often difficult in the absence of clear morphological markers. Here we present a robust method of analysing genus-specific collagen peptides by mass spectrometry simply by using solid-phase extraction (a C18 ZipTip) for peptide purification, rather than liquid chromatography/mass spectrometry (LC/MS). Analysis of the collagen from 32 different mammal Species identified a total of 92 peptide markers that could be used for Species Identification, for example, in processed food and animal feed. A set of ancient (>100 ka@10 degrees C) bone samples was also analysed to show that the proposed method has applications to archaeological bone Identification.
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Species Identification by analysis of bone collagen using matrix assisted laser desorption ionisation time of flight mass spectrometry
Rapid Communications in Mass Spectrometry, 2009Co-Authors: Michael Buckley, Matthew J Collins, Jane Thomasoates, Julie WilsonAbstract:Species Identification of fragmentary bone, such as in rendered meat and bone meal or from archaeological sites, is often difficult in the absence of clear morphological markers. Here we present a robust method of analysing genus-specific collagen peptides by mass spectrometry simply by using solid-phase extraction (a C18 ZipTip®) for peptide purification, rather than liquid chromatography/mass spectrometry (LC/MS). Analysis of the collagen from 32 different mammal Species identified a total of 92 peptide markers that could be used for Species Identification, for example, in processed food and animal feed. A set of ancient (>100 ka@10°C) bone samples was also analysed to show that the proposed method has applications to archaeological bone Identification. Copyright © 2009 John Wiley & Sons, Ltd.
T Maier - One of the best experts on this subject based on the ideXlab platform.
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high interlaboratory reproducibility of matrix assisted laser desorption ionization time of flight mass spectrometry based Species Identification of nonfermenting bacteria
Journal of Clinical Microbiology, 2009Co-Authors: Alexander Mellmann, Markus Kostrzewa, Francois Bimet, Chantal Bizet, Alexandra D Borovskaya, R R Drake, U Eigner, A M Fahr, E N Ilina, T MaierAbstract:Matrix-assisted laser desorption ionization-time of flight mass spectrometry has emerged as a rapid, cost-effective alternative for bacterial Species Identification. Identifying 60 blind-coded nonfermenting bacteria samples, this international study (using eight laboratories) achieved 98.75% interlaboratory reproducibility. Only 6 of the 480 samples were misidentified due to interchanges (4 samples) or contamination (1 sample) or not identified because of insufficient signal intensity (1 sample).
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Species Identification of clinical isolates of bacteroides by matrix assisted laser desorption ionization time of flight mass spectrometry
Clinical Microbiology and Infection, 2009Co-Authors: Elisabeth Nagy, T Maier, E Urban, Gabriella Terhes, Markus KostrzewaAbstract:Bacteroides fragilis and related Species are important human pathogens involved in mixed infections of different origins. The B. fragilis group isolates are phenotypically very similar, grow more slowly than aerobic bacteria and, accordingly, are frequently misidentifed with classical or automated phenotypical Identification methods. Recent taxonomic changes and new Species accepted as members of the Bacteroides genus are not included in the different databases of commercially available Identification kits. The use of matrix-assisted laser-desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) was therefore evaluated for the Species Identification of 277 clinical isolates of the Bacteroides genus. Species Identification was carried out with MALDI Bruker Daltonik Biotyper software (Bruker Daltonik GmbH, Bremen, Germany) by comparing the mass spectrum of each strain with the mass spectra of the 3260 reference strains currently available. The results of conventional phenotypical Identification of the isolates were used as a reference. 16S rRNA gene sequencing was performed for a selection of the strains that gave discrepant results and for all those inconclusively identified by MALDI-TOF MS; 270 isolates (97.5%) were unequivocally identified [log(score) >/=2.0] by comparison with the reference strains present in the MALDI Biotyper database. Of the 23 isolates for which the MALDI-TOF MS Species Identification differed from the conventional phenotypical Identification, 11 were sequenced. The sequencing data confirmed the MALDI-TOF MS result in ten cases and, for the remaining isolate, the sequencing data did not lead to the determination of the Species, but only to that of the genus (Bacteroides sp.). The discriminating power and Identification accuracy of MALDI-TOF MS proved to be superior to that of biochemical testing for Bacteroides thetaiotaomicron, Bacteroides ovatus and Bacteroides uniformis.
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evaluation of matrix assisted laser desorption ionization time of flight mass spectrometry in comparison to 16s rrna gene sequencing for Species Identification of nonfermenting bacteria
Journal of Clinical Microbiology, 2008Co-Authors: Alexander Mellmann, T Maier, Joann L Cloud, Ursula Keckevoet, I Ramminger, Peter C Iwen, James J Dunn, Gerri S Hall, Deborah A Wilson, P LasalaAbstract:Nonfermenting bacteria are ubiquitous environmental opportunists that cause infections in humans, especially compromised patients. Due to their limited biochemical reactivity and different morphotypes, misIdentification by classical phenotypic means occurs frequently. Therefore, we evaluated the use of matrix-assisted laser desorption ionization-time-of-flight mass spectrometry (MALDI-TOF MS) for Species Identification. By using 248 nonfermenting culture collection strains composed of 37 genera most relevant to human infections, a reference database was established for MALDI-TOF MS-based Species Identification according to the manufacturer's recommendations for microflex measurement and MALDI BioTyper software (Bruker Daltonik GmbH, Leipzig, Germany), i.e., by using a mass range of 2,000 to 20,000 Da and a new pattern-matching algorithm. To evaluate the database, 80 blind-coded clinical nonfermenting bacterial strains were analyzed. As a reference method for Species designation, partial 16S rRNA gene sequencing was applied. By 16S rRNA gene sequencing, 57 of the 80 isolates produced a unique Species Identification (>or=99% sequence similarity); 11 further isolates gave ambiguous results at this threshold and were rated as identified to the genus level only. Ten isolates were identified to the genus level (>or=97% similarity); and two isolates had similarity values below this threshold, were counted as not identified, and were excluded from further analysis. MALDI-TOF MS identified 67 of the 78 isolates (85.9%) included, in agreement with the results of the reference method; 9 were misidentified and 2 were unidentified. The identities of 10 randomly selected strains were 100% correct when three different mass spectrometers and four different cultivation media were used. Thus, MALDI-TOF MS-based Species Identification of nonfermenting bacteria provided accurate and reproducible results within 10 min without any substantial costs for consumables.
Julie Wilson - One of the best experts on this subject based on the ideXlab platform.
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Species Identification by peptide mass fingerprinting pmf in fibre products preserved by association with copper alloy artefacts
Journal of Archaeological Science, 2014Co-Authors: Caroline Solazzo, Penelope Walton Rogers, Leslie Weber, Harriet F Beaubien, Julie Wilson, Matthew J CollinsAbstract:Fibre products, such as textiles and animal pelts, are often recovered in the corrosion crust of archaeological metal artefacts. Because clothed burials are an important resource for the study of past societies, accurate fibre Identification is important. However, extreme mineralisation of animal fibres can render microscopic visualisation difficult for Species Identification. Peptide mass fingerprinting (PMF) has been successfully used to identify the Species origin in both collagen and keratin-made archaeological artefacts. The approach requires little material but the state of degradation (protein hydrolysis) is a limiting factor as it might impact on the Identification of key markers. In this study we analysed pelt and textile fragments found in association with copper-alloy objects with different degrees of mineralisation; samples were obtained from a Viking-Age (10th c.) grave in Britain and from a burial in Mongolia (3rd c. BC to 2nd c. AD). Species Identification was possible in all but one sample, revealing PMF can be applied to corrosion products, thereby further expanding the value of these objects for textile research.
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Species Identification by analysis of bone collagen using matrix assisted laser desorption ionisation time of flight mass spectrometry
Rapid Communications in Mass Spectrometry, 2009Co-Authors: Michael Buckley, Matthew J Collins, Jane Thomasoates, Julie WilsonAbstract:Species Identification of fragmentary bone, such as in rendered meat and bone meal or from archaeological sites, is often difficult in the absence of clear morphological markers. Here we present a robust method of analysing genus-specific collagen peptides by mass spectrometry simply by using solid-phase extraction (a C18 ZipTip) for peptide purification, rather than liquid chromatography/mass spectrometry (LC/MS). Analysis of the collagen from 32 different mammal Species identified a total of 92 peptide markers that could be used for Species Identification, for example, in processed food and animal feed. A set of ancient (>100 ka@10 degrees C) bone samples was also analysed to show that the proposed method has applications to archaeological bone Identification.
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Species Identification by analysis of bone collagen using matrix assisted laser desorption ionisation time of flight mass spectrometry
Rapid Communications in Mass Spectrometry, 2009Co-Authors: Michael Buckley, Matthew J Collins, Jane Thomasoates, Julie WilsonAbstract:Species Identification of fragmentary bone, such as in rendered meat and bone meal or from archaeological sites, is often difficult in the absence of clear morphological markers. Here we present a robust method of analysing genus-specific collagen peptides by mass spectrometry simply by using solid-phase extraction (a C18 ZipTip®) for peptide purification, rather than liquid chromatography/mass spectrometry (LC/MS). Analysis of the collagen from 32 different mammal Species identified a total of 92 peptide markers that could be used for Species Identification, for example, in processed food and animal feed. A set of ancient (>100 ka@10°C) bone samples was also analysed to show that the proposed method has applications to archaeological bone Identification. Copyright © 2009 John Wiley & Sons, Ltd.
Markus Kostrzewa - One of the best experts on this subject based on the ideXlab platform.
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high interlaboratory reproducibility of matrix assisted laser desorption ionization time of flight mass spectrometry based Species Identification of nonfermenting bacteria
Journal of Clinical Microbiology, 2009Co-Authors: Alexander Mellmann, Markus Kostrzewa, Francois Bimet, Chantal Bizet, Alexandra D Borovskaya, R R Drake, U Eigner, A M Fahr, E N Ilina, T MaierAbstract:Matrix-assisted laser desorption ionization-time of flight mass spectrometry has emerged as a rapid, cost-effective alternative for bacterial Species Identification. Identifying 60 blind-coded nonfermenting bacteria samples, this international study (using eight laboratories) achieved 98.75% interlaboratory reproducibility. Only 6 of the 480 samples were misidentified due to interchanges (4 samples) or contamination (1 sample) or not identified because of insufficient signal intensity (1 sample).
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Species Identification of clinical isolates of bacteroides by matrix assisted laser desorption ionization time of flight mass spectrometry
Clinical Microbiology and Infection, 2009Co-Authors: Elisabeth Nagy, T Maier, E Urban, Gabriella Terhes, Markus KostrzewaAbstract:Bacteroides fragilis and related Species are important human pathogens involved in mixed infections of different origins. The B. fragilis group isolates are phenotypically very similar, grow more slowly than aerobic bacteria and, accordingly, are frequently misidentifed with classical or automated phenotypical Identification methods. Recent taxonomic changes and new Species accepted as members of the Bacteroides genus are not included in the different databases of commercially available Identification kits. The use of matrix-assisted laser-desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) was therefore evaluated for the Species Identification of 277 clinical isolates of the Bacteroides genus. Species Identification was carried out with MALDI Bruker Daltonik Biotyper software (Bruker Daltonik GmbH, Bremen, Germany) by comparing the mass spectrum of each strain with the mass spectra of the 3260 reference strains currently available. The results of conventional phenotypical Identification of the isolates were used as a reference. 16S rRNA gene sequencing was performed for a selection of the strains that gave discrepant results and for all those inconclusively identified by MALDI-TOF MS; 270 isolates (97.5%) were unequivocally identified [log(score) >/=2.0] by comparison with the reference strains present in the MALDI Biotyper database. Of the 23 isolates for which the MALDI-TOF MS Species Identification differed from the conventional phenotypical Identification, 11 were sequenced. The sequencing data confirmed the MALDI-TOF MS result in ten cases and, for the remaining isolate, the sequencing data did not lead to the determination of the Species, but only to that of the genus (Bacteroides sp.). The discriminating power and Identification accuracy of MALDI-TOF MS proved to be superior to that of biochemical testing for Bacteroides thetaiotaomicron, Bacteroides ovatus and Bacteroides uniformis.
Alexander Mellmann - One of the best experts on this subject based on the ideXlab platform.
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high interlaboratory reproducibility of matrix assisted laser desorption ionization time of flight mass spectrometry based Species Identification of nonfermenting bacteria
Journal of Clinical Microbiology, 2009Co-Authors: Alexander Mellmann, Markus Kostrzewa, Francois Bimet, Chantal Bizet, Alexandra D Borovskaya, R R Drake, U Eigner, A M Fahr, E N Ilina, T MaierAbstract:Matrix-assisted laser desorption ionization-time of flight mass spectrometry has emerged as a rapid, cost-effective alternative for bacterial Species Identification. Identifying 60 blind-coded nonfermenting bacteria samples, this international study (using eight laboratories) achieved 98.75% interlaboratory reproducibility. Only 6 of the 480 samples were misidentified due to interchanges (4 samples) or contamination (1 sample) or not identified because of insufficient signal intensity (1 sample).
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evaluation of matrix assisted laser desorption ionization time of flight mass spectrometry in comparison to 16s rrna gene sequencing for Species Identification of nonfermenting bacteria
Journal of Clinical Microbiology, 2008Co-Authors: Alexander Mellmann, T Maier, Joann L Cloud, Ursula Keckevoet, I Ramminger, Peter C Iwen, James J Dunn, Gerri S Hall, Deborah A Wilson, P LasalaAbstract:Nonfermenting bacteria are ubiquitous environmental opportunists that cause infections in humans, especially compromised patients. Due to their limited biochemical reactivity and different morphotypes, misIdentification by classical phenotypic means occurs frequently. Therefore, we evaluated the use of matrix-assisted laser desorption ionization-time-of-flight mass spectrometry (MALDI-TOF MS) for Species Identification. By using 248 nonfermenting culture collection strains composed of 37 genera most relevant to human infections, a reference database was established for MALDI-TOF MS-based Species Identification according to the manufacturer's recommendations for microflex measurement and MALDI BioTyper software (Bruker Daltonik GmbH, Leipzig, Germany), i.e., by using a mass range of 2,000 to 20,000 Da and a new pattern-matching algorithm. To evaluate the database, 80 blind-coded clinical nonfermenting bacterial strains were analyzed. As a reference method for Species designation, partial 16S rRNA gene sequencing was applied. By 16S rRNA gene sequencing, 57 of the 80 isolates produced a unique Species Identification (>or=99% sequence similarity); 11 further isolates gave ambiguous results at this threshold and were rated as identified to the genus level only. Ten isolates were identified to the genus level (>or=97% similarity); and two isolates had similarity values below this threshold, were counted as not identified, and were excluded from further analysis. MALDI-TOF MS identified 67 of the 78 isolates (85.9%) included, in agreement with the results of the reference method; 9 were misidentified and 2 were unidentified. The identities of 10 randomly selected strains were 100% correct when three different mass spectrometers and four different cultivation media were used. Thus, MALDI-TOF MS-based Species Identification of nonfermenting bacteria provided accurate and reproducible results within 10 min without any substantial costs for consumables.