Honghui Wang1, Steven K Drake1, Chen Yong2, Marjan Gucek2, Margaret Tropea1, Avi Z Rosenberg3, John P Dekker4, Anthony F Suffredini5. 1. Critical Care Medicine Department, Clinical Center. 2. Proteomic Core Facility, National Heart Lung and Blood Institute. 3. Kidney Disease Section, National Institute of Diabetes and Digestive and Kidney Diseases. 4. Microbiology Service, Department of Laboratory Medicine, Clinical Center, National Institutes of Health, Bethesda, MD. 5. Critical Care Medicine Department, Clinical Center, asuffredini@cc.nih.gov.
Abstract
BACKGROUND: Acinetobacter baumannii is a common nosocomial pathogen and strain-typing methods play an important role in hospital outbreak investigations and epidemiologic surveillance. We describe a method for identifying strain-specific peptide markers based on LC-MS/MS profiling of digested peptides. This method classified a test set of A. baumannii isolates collected from a hospital outbreak with discriminatory performance exceeding that of MALDI-TOF mass spectrometry. METHODS: Following the construction of a species "pan-peptidome" by in silico translation and digestion of whole genome sequences, a hypothetical set of genome-specific peptides for an isolate was constructed from the disjoint set of the pan-peptidome and the isolate's calculated peptidome. The genome-specific peptidome guided selection of highly expressed genome-specific peptides from LC-MS/MS experimental profiles as potential peptide markers. The species specificity of each experimentally identified genome-specific peptide was confirmed through a Unipept lowest common ancestor analysis. RESULTS: Fifteen A. baumannii isolates were analyzed to derive a set of genome- and species-specific peptides that could be used as peptide markers. Identified peptides were cross-checked with protein BLAST against a set of 22 A. baumannii whole genome sequences. A subset of these peptide markers was confirmed to be present in the actual peptide profiles generated by multiple reaction monitoring and targeted LC-MS/MS. The experimentally identified peptides separated these isolates into 6 strains that agreed with multilocus sequence typing analysis performed on the same isolates. CONCLUSIONS: This approach may be generalizable to other bacterial species, and the peptides may be useful for rapid MS strain tracking of isolates with broad application to infectious disease diagnosis.
BACKGROUND:Acinetobacter baumannii is a common nosocomial pathogen and strain-typing methods play an important role in hospital outbreak investigations and epidemiologic surveillance. We describe a method for identifying strain-specific peptide markers based on LC-MS/MS profiling of digested peptides. This method classified a test set of A. baumannii isolates collected from a hospital outbreak with discriminatory performance exceeding that of MALDI-TOF mass spectrometry. METHODS: Following the construction of a species "pan-peptidome" by in silico translation and digestion of whole genome sequences, a hypothetical set of genome-specific peptides for an isolate was constructed from the disjoint set of the pan-peptidome and the isolate's calculated peptidome. The genome-specific peptidome guided selection of highly expressed genome-specific peptides from LC-MS/MS experimental profiles as potential peptide markers. The species specificity of each experimentally identified genome-specific peptide was confirmed through a Unipept lowest common ancestor analysis. RESULTS: Fifteen A. baumannii isolates were analyzed to derive a set of genome- and species-specific peptides that could be used as peptide markers. Identified peptides were cross-checked with protein BLAST against a set of 22 A. baumannii whole genome sequences. A subset of these peptide markers was confirmed to be present in the actual peptide profiles generated by multiple reaction monitoring and targeted LC-MS/MS. The experimentally identified peptides separated these isolates into 6 strains that agreed with multilocus sequence typing analysis performed on the same isolates. CONCLUSIONS: This approach may be generalizable to other bacterial species, and the peptides may be useful for rapid MS strain tracking of isolates with broad application to infectious disease diagnosis.
Authors: Anna F Lau; Honghui Wang; Rebecca A Weingarten; Steven K Drake; Anthony F Suffredini; Mark K Garfield; Yong Chen; Marjan Gucek; Jung-Ho Youn; Frida Stock; Hanna Tso; Jim DeLeo; James J Cimino; Karen M Frank; John P Dekker Journal: J Clin Microbiol Date: 2014-05-21 Impact factor: 5.948
Authors: Sébastien Spinali; Alex van Belkum; Richard V Goering; Victoria Girard; Martin Welker; Marc Van Nuenen; David H Pincus; Maud Arsac; Géraldine Durand Journal: J Clin Microbiol Date: 2014-07-23 Impact factor: 5.948
Authors: Evan S Snitkin; Adrian M Zelazny; Jyoti Gupta; Tara N Palmore; Patrick R Murray; Julia A Segre Journal: Genome Res Date: 2013-04-05 Impact factor: 9.043
Authors: Jeffrey R Strich; Honghui Wang; Ousmane H Cissé; Jung-Ho Youn; Steven K Drake; Yong Chen; Avi Z Rosenberg; Marjan Gucek; Patrick T McGann; John P Dekker; Anthony F Suffredini Journal: J Clin Microbiol Date: 2019-04-26 Impact factor: 5.948
Authors: John P Dekker; Anthony F Suffredini; Honghui Wang; Jeffrey R Strich; Steven K Drake; Yong Chen; Jung-Ho Youn; Avi Z Rosenberg; Marjan Gucek Journal: Antimicrob Agents Chemother Date: 2019-08-23 Impact factor: 5.191
Authors: Honghui Wang; Ousmane H Cissé; Anthony F Suffredini; John P Dekker; Thomas Bolig; Steven K Drake; Yong Chen; Jeffrey R Strich; Jung-Ho Youn; Uchenna Okoro; Avi Z Rosenberg; Junfeng Sun; John J LiPuma Journal: J Clin Microbiol Date: 2020-10-21 Impact factor: 5.948
Authors: Honghui Wang; Yong Chen; Jeffrey R Strich; Steven K Drake; Jung-Ho Youn; Avi Z Rosenberg; Marjan Gucek; Patrick T McGann; Anthony F Suffredini; John P Dekker Journal: Clin Proteomics Date: 2019-02-26 Impact factor: 3.988
Authors: Roger Karlsson; Lucia Gonzales-Siles; Margarita Gomila; Antonio Busquets; Francisco Salvà-Serra; Daniel Jaén-Luchoro; Hedvig E Jakobsson; Anders Karlsson; Fredrik Boulund; Erik Kristiansson; Edward R B Moore Journal: PLoS One Date: 2018-12-10 Impact factor: 3.240
Authors: Honghui Wang; Steven K Drake; Jung-Ho Youn; Avi Z Rosenberg; Yong Chen; Marjan Gucek; Anthony F Suffredini; John P Dekker Journal: Sci Rep Date: 2017-05-31 Impact factor: 4.379