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by Charles H. Wick

Download Identifying Microbes by Mass Spectrometry Proteomics fb2, epub

ISBN: 1466504943
Author: Charles H. Wick
Language: English
Publisher: CRC Press; 1 edition (September 10, 2013)
Pages: 289
Category: Biological Sciences
Subcategory: Science
Rating: 4.7
Votes: 306
Size Fb2: 1162 kb
Size ePub: 1986 kb
Size Djvu: 1580 kb
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Detection and Identification of Microbes Using Mass Spectrometry Proteomics Charles H. Wick. Dr. Charles H. Wick, P. is a retired senior scientist from the .

Detection and Identification of Microbes Using Mass Spectrometry Proteomics Charles H. Mass Analyzers and MS/MS Methods for Microbial Detection and Identification Michael F. Stanford. Although his 40-year professional career has spanned both the public sector and the military, his better-known work in the area of forensic science has occurred in concert with the Department of Defense. Wick Mass Analyzers and MS/MS Methods for Microbial Detection and Identification Michael F. Stanford Matching Mass. source: Nielsen Book Data).

Detection and Identification of Microbes Using Mass Spectrometry Proteomics.

The text also discusses diverse processing methods, which are used to analyze MS files for matching mass spectral profiles, and examines protein and nucleic acid sequence-based methods capable of classification and identification of microbial agents. Detection and Identification of Microbes Using Mass Spectrometry Proteomics. Mass Analyzers and MS/MS Methods for Microbial Detection and Identification.

Identifying Microbes by Mass Spectrometry Proteomics.

Mass spectrometry-based proteomics combined with bioinformatic tools for bacterial classification. Identifying Microbes by Mass Spectrometry Proteomics.

by: Wick, Charles H. Publisher: CRC Press. Print ISBN: 9781466504943, 1466504943. Save up to 80% by choosing the eTextbook option for ISBN: 9781466504967, 146650496X. The print version of this textbook is ISBN: 9781466504943, 1466504943. The world’s eTextbook reader for students.

All microbes, including bacteria, viruses, and fungi, can be classified and identified by matching a few peptides known to be unique to each organism. Identifying Microbes by Mass Spectrometry Proteomics describes ways to identify microorganisms using powerful new techniques combining hardware and software and yielding highly accurate methods for detection, identification, and classification of microbes. This straightforward technology can be used to detect unknown and unsequenced microorganisms as well as microbes in complex environmental samples.

New advances in proteomics, driven largely by developments in mass spectrometry, continue to reveal the complexity and diversity of pathogenic mechanisms among microbes that underpin infectious diseases. This book covers the broad microbiological applications of proteomics and mass spectrometry.

Mass spectrometry-based proteomics, an unbiased method to identify candidate proteins, was used to test the serum of the patients for biomarkers of cerebral ischemia. The Student's t-test was used for comparison. The Benjamini-Hochberg false discovery rate controlling procedure for multiple comparison adjustments determined significance for the proteomic screen.

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All microbes, including bacteria, viruses, and fungi, can be classified and identified by matching a few peptides known to be unique to each organism. Identifying Microbes by Mass Spectrometry Proteomics describes ways to identify microorganisms using powerful new techniques combining hardware and software and yielding highly accurate methods for detection, identification, and classification of microbes. This straightforward technology can be used to detect unknown and unsequenced microorganisms as well as microbes in complex environmental samples.This book reviews various mass analyzers used for detection and describes ionization methods frequently used for analysis of microbial constituents, a necessary step in the preparation of mass spectrometry (MS) samples. The text also discusses diverse processing methods, which are used to analyze MS files for matching mass spectral profiles, and examines protein and nucleic acid sequence-based methods capable of classification and identification of microbial agents. The book also covers sample collection methods and specific sample preparation techniques.The text addresses using computer software and bioinformatics approaches for data mining to discriminate microbes using mass spectrometry proteomics (MSP). It also discusses historical pattern recognition-based methods and other approaches such as analysis of pyrolysis products, chemical ionization (CI) of fatty acid methyl esters, and MALDI-MS. The text contains examples of the application of the MSP technique for microbe detection and includes a survey of suitable and commercially available MS-based platforms. Successful applications include the identification of unknown microbes in honey bees associated with colony collapse disorder and the analysis of virus strains from the 2009 influenza pandemic. The final chapter outlines future trends in these groundbreaking uses of MS techniques, which are fast, not limited by sample type, and show potential in answering complex environmental questions.

Comments:

Bremar
I recently read “Identifying Microbes by Mass Spectrometry Proteomics” and found that—despite the term ‘proteomics’ in its title—this book essentially reviews MS-based analysis methods of diverse microbial constituents isolated from cell lysates and complex mixtures of products obtained by direct desorption from microbial cells or their pyrolysis.

I also found that 95% of the entire book was copied word-for-word from two type of sources:

(i) 25% (or 24,197 of book words) from five journal articles authored by twenty (20) different researchers and published in years 2009/11 (sections 5.6 – 5.11[ref. 1]; 6.6 [ref. 2]; 7.2 [ref.3]; 7.3 [ref.4]; and 7.4 [ref. 5]), and

(ii) 70% (68,187 words) from an In-House Technical Report written mostly by other authors in 2007 (all other chapters and sections). Consequently, the named authors of this book contributed only 5% words (or 5,023); essentially written as opening and closing paragraphs of each chapter.
The journal articles were reprinted in their entireties without showing proper permissions to do so and without crediting the original authors and sources, both copyrighted and open access, as required by copyright law and the Creative Commons Attribution License, respectively. Although figure captions in sections 5.6 – 5.11; 6.6; 7.2; 7.3; and 7.4 usually acknowledge the source articles, the reader may not suspect that practically all words in these sections were copied verbatim as well.

More interestingly, the text in Chapters 1 through 4, 8, and 9; Sections 5.1 through 5.5 and 6.1 through 6.5 was quite familiar because it originates from an In-House Technical Report I co-authored. Furthermore, after careful word counting, I determined that 74.2% words in the above chapters and sections were copied word-for-word from my contribution to that In-House Technical Report while my former colleagues, Drs. RE Jabbour and AP Snyder, contributed the majority of the remaining words (11.1% and 6.2%, respectively). For example, Dr. MF Stanford, the single author of Chapters 2, 3 and 8 contributed only 5.87%, 1.57%, and 4.2% words, respectively, while the single author of Chapters 4 and 5 (Dr. SV Deshpande) added only 2.39% and 0.94%, words, respectively.

The book Editor and the single author of Chapter 7 (Dr. CH Wick) added only 495 words (or 3.06%) to a 16,181 words long text composed of three journal articles reprinted there in their entirety, while his contribution to the last chapter of the book (Chapter 9) reached 508 words and he closed the book with two paragraphs (295 words) copied verbatim from the ‘Expert commentary & five-year view’ section of an Expert Review of Proteomics article by JP Dworzanski & AP Snyder [6]. Hence, the reader will find there outdated statements, such as “… currently more than 725 full genome-sequencing projects are in progress” that were correct 11 years ago. Large fragments copied word-for-word from this Expert Review of Proteomics article can be also found in Chapter 3 which is authored by MF Stanford (3,132 words, 32 references) and two chapters authored by SV Deshpande, that is, Chapter 4 (4,492 words, 3 figures, and 40 references) and Chapter 5 (1,043 words, 11 references). They constitute substantial chunks of these chapters (e.g.. 37% words of Chapter 4).

Although a buyer may not be interested in ethical or legal aspects of this gross authorship misrepresentation, nevertheless, I think the problem for the reader is that In-House Technical Report-based chapters (75% of the book) were written more than 9 years ago and the most recent references are from spring of 2007. Consequently, too many statements about the instruments, software, and laboratory methods used or genomic/proteomic databases are now outdated. In addition, the reader will find also many awkward and even incomprehensible statements and plain errors (both typographical and factual). Some of them originated from not-thought-out copying and efforts aimed to differentiate the text appearance in the book versus original articles. Therefore, without reading the original journal versions it is impossible to understand them. A few examples of nonsensical sentences (e.g., created by setting together words copied along one line of a two-column text of an original article, etc.) and countless typos are exemplified below.

Section 1.2 (p. 3; lines 1-3): ”These tests can be performed by means of miniaturized and automated substrates that utilize screening methods to classify/identify the isolate.” [The author attempted to paraphrase my sentence about systems performing automated substrate utilization tests for identification of isolates (where ‘substrate’ means a substrate of a biochemical reaction)].

Chapter 2 describes basics about the ionization methods, mass analyzers and tandem MS techniques and MF Stanford, who contributed only a few introductory paragraphs (all the remaining 94.13% words were written by RE Jabbour & JP Dworzanski), punctuates his text with statements as plain as the nose on your face, or quite surprising like “… sample preparation time may be reflected in the dynamic range of the instrument.” Unfortunately, the latter sentence only indicates that the author does not understand what the term “dynamic range” means; and he continues this nonsensical story about relationships between sample preparation time and the dynamic range of MS instruments throughout the whole 5th paragraph (p. 12).

Sections 5.6-5.11. The author (SV Deshpande) replaced the expression ‘one-pot’ method used by Jabbour and Snyder in the original article [1] and referring to multi-step operations performed in the same “pot” of the ultra-filtration device, by ‘one-step’ because to SV Deshpande, as an IT specialist, these two terms probably seem equivalent. Little wonder that on other occasions he substituted “one-pot” by other terms, like “one-system” (e.g. the last paragraph on p. 121), and finally, he titled paragraphs (copied from the article “Conclusion” section) and summarizing advantages of multiple processing and concentration steps performed in one “pot” as Multiple Processes for Protein Mixtures Discussed (Section 5.11; p. 129).

Section 5.6. 3 (p. 122): “These compounds and components were directed away and where equal volumes of 10 × 107 cfu/mL suspensions of E. coli upstream from the analytical peptide separation and detection LC-MS/MS system”. A collage-like sentence created by mixing lines from the left column (Introduction) of the original article [Jabbour et al., 2011, p. 908 ] with lines from the section Methods: Bacteria Mixture Analysis (the underlined words ) which are set in the article’s PDF version on the right-hand column.

Section 5.8, pp. 125 (last two lines) &126:“As predicted, as the amount of lysed bacterial protein preparation (Figure 5.11), the number of unique peptides possessing >95% probability score from PeptideProphet using two sample … the experimental bacterial mixture decreased, fewer peptides were observed.” It originates from indiscriminate text copying from the article by Jabbour et al. 2011 (pp. 909-910); where the last word on p. 909 in its PDF format is “preparation” and the remaining part of its source sentence ends on p. 910 (see underlined words above). However, the graphic element on p. 910 (and its legend) is set before the word “decreased” so by mechanical copying the figure legend ended up, in the book edition, in the middle of the original sentence.

Sub-section 8.7.4 (pp. 208-210) does not belong to section 8.7 describing the TOF-MS–based system because it originates from a separate section, describing the atmospheric pressure MALDI-Ion Trap MS system. Unfortunately, the title and the introductory paragraph describing this system are missing in the book, so the reader will be completely confused by reading this incoherent text.
In section 9.2.1 the Editor created a couple nonsensical sentences by inserting the word “conformation” instead of “confirmation”.

Editorial Errors:
The last paragraph on p. 9 (section 1.7 authored by CH Wick) is identical with the penultimate paragraph on p. 13 (section 2.1) authored by MF Stanford. However, the latter author did not plagiarize this paragraph from Ch. 1, in fact, both of them copied this paragraph from the In-House Technical Report and forgot to check notes who will use my old text.

The text in Ch.1 was extensively copied from the In-House Technical Report (with a different chapter order in comparison to the book version) so there are many errors in regard to the chapter content. For example, on p. 10 (1st paragraph) the text should read ‘Chapter 5’ instead of ‘Chapter 3’and in the 2nd paragraph ’Chapter 6’ instead of ‘Chapter 3’.

Section 6.6.1 (pp.146/147) 11 lines (130 words) of the1st paragraph are repeated in the 3rd paragraph.

Lots of typographical errors:
For instance: on p. 159:“µL” was five times incorrectly set as “I-l” (lines: 21, 24 (twice); 25, and 28). On pp. 188-189 ”µC” was used instead of degree Celsius (ºC); “mL” instead of ‘µL’; etc., giving rise to completely misleading statements, such as, “...bees were … frozen at 280 µC” instead of “at – 80 ºC”; or “Using a 10 mL pipette, each bee was inoculated by feeding it a total of 2 mL in sugar water containing one of four treatments”(p.189); or “… tubes were… spun down at 141,000g” instead of “… spun down at 14,100 × g” and many more.

Figures 8.4 and 8.5 are the same (the correct picture that supposed to be inserted from the In-House Technical Report as Figure 8.4 is missing);
The above errors seem to indicate that nobody read this text, including the “authors”, the editor, and there were “no” Reviewers involved.

Overall, this book leaves the reader with an incomplete coverage of mass spectrometry proteomics for identifying microbes by providing a review that is based on outdated references and facts supplemented with reprints of a few journal articles peppered with plenty of editorial errors and awkward commentaries. So, reading it is NOT worth your time! With all that it minds, I think 1 star is fair.

Jacek P. Dworzanski
Bel Air, Maryland

REFERENCES
[1] RE Jabbour et al. (2011) A protein processing filter method for bacterial identification by mass spectrometry-based proteomics; J Proteome Res 10: 907-912; doi: 10.1021/pr101086a.
[2] SV Deshpande et al. (2011) ABOid: A Software for Automated Identification and Phyloproteomics Classification of Tandem Mass Spectrometric Data; J Chromatograph Separat Techniq S5:001; doi:10.4172/2157-7064.S5-001 [licensed to the public under the Creative Commons Attribution 3.0 License].
[3] RE Jabbour et al.(2010) Double-Blind Characterization of Non-Genome-Sequenced Bacteria by Mass Spectrometry-Based Proteomics ; Applied and Environmental Microbiology 76 (11), 3637–3644; doi:10.1128/AEM.00055-10.
[4] C Wick et al. (2009) Pandemic (H1N1) 2009 Cluster Analysis: A Preliminary Assessment. Available from Nature Precedings <[...]> (2009) [licensed to the public under the Creative Commons Attribution 3.0 License].
[5] JJ Bromenshenk et al. (2010) Iridovirus and Microsporidian Linked to Honey Bee Colony Decline. PLoS ONE 5(10): e13181. doi:10.1371/journal.pone.0013181[licensed to the public under the Creative Commons Attribution 3.0 License].
[6] JP Dworzanski & AP Snyder (2005) Classification and identification of bacteria using mass spectrometry-based proteomics; Expert Review of Proteomics, 2:863-878 (2005); doi: 10.1586/14789450.2.6.863.
Na
This is groundbreaking technology for identifying microbes such as bacteria, fungi, and viruses within a response time of a few hours rather than days. This short response time will be vital in the case of a bioterrorist attack. Mass Spectrometry Proteomics may result in saving hundreds of thousands of lives. It also has a myriad of other applications such as medicine, biology, and environmental chemistry. This is a "must read" for those in all fields of science.

Richard M. Stanford, Ph.D., Retired conservationist and environmental chemist

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