Differentiation of Streptococcus pneumoniae Conjunctivitis Outbreak Isolates by Matrix-Assisted Laser Desorption Ionization-Time of Flight Mass Spectrometry Yulanda M. Williamson, Hercules Moura, Adrian R. Woolfitt, James L. Pirkle, John R. Barr, Maria Da Gloria Carvalho, Edwin P. Ades, George M. Carlone and Jacquelyn S. Sampson Appl. Environ. Microbiol. 2008, 74(19):5891. DOI: 10.1128/AEM.00791-08. Downloaded from http://aem.asm.org/ on March 24, 2012 by guest Published Ahead of Print 15 August 2008. Updated information and services can be found at: http://aem.asm.org/content/74/19/5891 These include: REFERENCES This article cites 25 articles, 7 of which can be accessed free at: http://aem.asm.org/content/74/19/5891#ref-list-1 CONTENT ALERTS Receive: RSS Feeds, eTOCs, free email alerts (when new articles cite this article), more» Information about commercial reprint orders: http://aem.asm.org/site/misc/reprints.xhtml To subscribe to to another ASM Journal go to: http://journals.asm.org/site/subscriptions/ APPLIED AND ENVIRONMENTAL MICROBIOLOGY, Oct. 2008, p. 5891–5897 Vol. 74, No. 19 0099-2240/08/$08.00 0 doi:10.1128/AEM.00791-08 Differentiation of Streptococcus pneumoniae Conjunctivitis Outbreak Isolates by Matrix-Assisted Laser Desorption Ionization–Time of Flight Mass Spectrometry Yulanda M. Williamson,1,2 Hercules Moura,2 Adrian R. Woolﬁtt,2 James L. Pirkle,2 John R. Barr,2* Maria Da Gloria Carvalho,1 Edwin P. Ades,1 George M. Carlone,1 and Jacquelyn S. Sampson1 National Center for Immunizations and Respiratory Diseases1 and National Center for Environmental Health,2 Centers for Disease Control and Prevention, Atlanta, Georgia 30333 Received 7 April 2008/Accepted 6 August 2008 Streptococcus pneumoniae (pneumococcus [Pnc]) is a causative agent of many infectious diseases, including Downloaded from http://aem.asm.org/ on March 24, 2012 by guest pneumonia, septicemia, otitis media, and conjunctivitis. There have been documented conjunctivitis outbreaks in which nontypeable (NT), nonencapsulated Pnc has been identiﬁed as the etiological agent. The use of mass spectrometry to comparatively and differentially analyze protein and peptide proﬁles of whole-cell microor- ganisms remains somewhat uncharted. In this report, we discuss a comparative proteomic analysis between NT S. pneumoniae conjunctivitis outbreak strains (cPnc) and other known typeable or NT pneumococcal and streptococcal isolates (including Pnc TIGR4 and R6, Streptococcus oralis, Streptococcus mitis, Streptococcus pseudopneumoniae, and Streptococcus pyogenes) and nonstreptococcal isolates (including Escherichia coli, En- terococcus faecalis, and Staphylococcus aureus) as controls. cPnc cells and controls were grown to mid-log phase, harvested, and subsequently treated with a 10% triﬂuoroacetic acid–sinapinic acid matrix mixture. Protein and peptide fragments of the whole-cell bacterial isolate-matrix combinations ranging in size from 2 to 14 kDa were evaluated by matrix-assisted laser desorption ionization–time of ﬂight mass spectrometry. Additionally Ran- dom Forest analytical tools and dendrogramic representations (Genesis) suggested similarities and clustered the isolates into distinct clonal groups, respectively. Also, a peak list of protein and peptide masses was obtained and compared to a known Pnc protein mass library, in which a peptide common and unique to cPnc isolates was tentatively identiﬁed. Information gained from this study will lead to the identiﬁcation and validation of proteins that are commonly and exclusively expressed in cPnc strains which could potentially be used as a biomarker in the rapid diagnosis of pneumococcal conjunctivitis. Streptococcus pneumoniae (pneumococcus [Pnc]) is a facul- shire, New Jersey, and Maine. Martin et al. (15) and Carvalho et tative anaerobic bacterium that is an important human patho- al. (3) reported microbiological, biochemical or genetic evi- gen worldwide. The microorganism is a causative agent of dence that all of the Pnc strains from these outbreaks lacked a many infections, including community-acquired pneumonia, detectable polysaccharide capsule. Lack of a capsule, as well as meningitis, septicemia, bacteremia, otitis media, and conjunc- the insensitivity of pneumococcal culture and diagnostic assays, tivitis (8, 10, 17). Pnc contains many virulence factors, includ- presents a challenge to correctly diagnose pneumococcal con- ing a polysaccharide capsule that is antiphagocytic, enabling junctivitis. the organism to avoid being engulfed and thus escape immune Molecular and immunological technologies (real-time PCR detection. Based on capsular polysaccharides, 91 serotypes of and enzyme-linked immunosorbent assays) detecting expres- Pnc are known. However, there are strains that do not react sion of Pnc genes or antibodies in bodily ﬂuids have been used with Pnc typing antisera and thus are nontypeable (NT) or with a limited degree of sensitivity for detection and diagnosis nonencapsulated (3), although they meet the identiﬁcation cri- of pneumococcal disease (4, 23). However, advances in the teria (optochin sensitivity, bile solubility, and being GenProbe ﬁeld of proteomics and bioinformatics have now made it pos- positive) as being Pnc. Moreover, many NT strains are actually sible to identify novel diagnostic targets or biomarkers aimed just variants of normally encapsulated strains. at improved detection. These expressed-gene or protein tar- Pneumococcal conjunctivitis, an infection of the conjunctiva, gets could prove useful in differentiating infectious strains that is of signiﬁcant public health concern in highly populated en- have been associated with previous conjunctivitis outbreaks vironments such as college campuses, nursing homes, and day and could reduce transmission of this infection. care centers. Through the years, there have been large out- Mass spectrometry (MS), a rapid, powerful, and sensitive breaks of conjunctivitis that have occurred in various regions of analytical tool has been used recently for the differentiation, the United States, including New York, California, New Hamp- identiﬁcation, and characterization of microbial pathogens. In particular, MS techniques such as matrix-assisted laser desorp- tion ionization–time of ﬂight (MALDI-TOF) MS have been * Corresponding author. Mailing address: Centers for Disease Con- used to analyze whole bacterial cells that have not been mod- trol and Prevention, 4770 Buford Highway, Building 110, MS-F50, Chamblee, GA 30341. Phone: (770) 488-7848. Fax: (770) 488-0509. iﬁed chemically or by mechanical disruption (6). In recent E-mail: firstname.lastname@example.org. years, MALDI-TOF MS has been used to differentiate signif- Published ahead of print on 15 August 2008. icant human pathogens such as Helicobacter pylori, Bacillus 5891 5892 WILLIAMSON ET AL. APPL. ENVIRON. MICROBIOL. cereus, Escherichia coli, and Coxiella burnetii (1, 6, 9, 11–14, 16, TABLE 1. Bacterial strains used in this study 20, 21, 24, 25). Studies by Friedrich and colleagues employed Straina Source MALDI-TOF MS for rapid identiﬁcation of 10 different spe- Sp 165 (1138-80)............................1980, New York conjunctivitis, NT cies of viridans streptococci (7). Additionally, the MALDI Sp 166 (1139-80)............................1980, New York conjunctivitis, NT technology has been used to identify Mycobacterium and more- Sp 168 (61-81)................................1981, California conjunctivitis, NT over distinguish between multiple strains within a species (18). Sp 169 (62-81)................................1981, California conjunctivitis, NT By use of high-throughput measures such as MALDI-TOF, Sp 170 (63-81)................................1981, California conjunctivitis, NT Sp 245 (1852-02)............................2002, New Hampshire protein/peptide ﬁngerprints can be generated based on a pro- conjunctivitis, NT teomic proﬁle. These proteins or patterns could serve as Sp 246 (1853-02)............................2002, New Hampshire uniquely expressed pathogen-speciﬁc peptide or protein bio- conjunctivitis, NT markers that may prove useful for diagnostic purposes. Sp 247 (2136-02)............................2002, New Jersey conjunctivitis, NT In this report, we describe a differential proteomic analysis Sp 248 (2136-02)............................2002, New Jersey conjunctivitis, NT Sp 263 (71-03)................................2003, Maine conjunctivitis, NT using MALDI-TOF MS of representative Pnc conjunctival Sp 264 (72-03)................................2003, Maine conjunctivitis, NT (cPnc) U.S. outbreak isolates. The unique cPnc outbreak iso- Sp 265 (73-03)................................2003, Maine conjunctivitis, NT lates were compared with other nonconjunctival, pneumococ- Sp 266 (74-03)................................2003, Maine conjunctivitis, NT Downloaded from http://aem.asm.org/ on March 24, 2012 by guest cal and streptococcal isolates and a limited number of non- R6 (BAA-228) ...............................Derivative of D39, nonencapsulated TIGR4 (BAA-344) ........................Encapsulated, serotype 4 streptococcal strains and species. Additionally, statistical (M) ..................................................S. mitis algorithms as well as traditional cluster analysis were used to (3) SS1246/NCTC 10712...............S. mitis identify similarities among these isolates, in particular the cPnc (35) 1165/Mitis 26 .........................S. mitis isolates. A list of peptides/proteins found among the isolates (40) SS1059/JC67...........................S. mitis was compiled in which at least one peptide/protein was com- (67) SS1303/NCTC 12261.............S. mitis (O)...................................................S. oralis mon and exclusively expressed in the cPnc isolates. These cPnc (6) SS1236/ATCC 35037...............S. oralis proteomic signatures or biomarkers could ultimately be useful (7) SS900/ATCC 15914.................S. oralis in the diagnosis of this infection. (21) SS911/ATCC 10557...............S. oralis Sp 83 ...............................................Pnc serotype 4, encapsulated 7-valent vaccine MATERIALS AND METHODS Sp 86 ...............................................Pnc serotype 6B, encapsulated Materials and reagents. All chemicals used during this study were purchased 7-valent vaccine from Sigma-Aldrich (St. Louis, MO), except where indicated. Culture medium Sp 95 ...............................................Pnc serotype 9V, encapsulated (Todd-Hewitt broth) was obtained from the Scientiﬁc Resources Program at the 7-valent vaccine Centers for Disease Control and Prevention (CDC). Sp 105 .............................................Pnc serotype 14, encapsulated Bacterial strains. All strains were from the CDC Streptococcus Reference 7-valent vaccine Laboratory. Study strains consisted of 13 cPnc outbreak isolates as well as Sp 116 .............................................Pnc serotype 18C, encapsulated controls Streptococcus pneumoniae serotype 4, Pnc TIGR4, and Streptococcus 7-valent vaccine pneumoniae unencapsulated strain R6; other streptococcal species, including Sp 117 .............................................Pnc serotype 19F, encapsulated Streptococcus oralis, Streptococcus mitis, Streptococcus pseudopneumoniae, and 7-valent vaccine Streptococcus pyogenes (group A); and strains from heterologous genera Esche- Sp 125 .............................................Pnc serotype, 23F, encapsulated richia coli (group B), Staphylococcus aureus (group C), and Enterococcus faecalis 7-valent vaccine (group D). In addition, pneumococcal serotypes contained within the 7-valent (P)....................................................S. pseudopneumoniae pneumococcal conjugate vaccine and NT pneumococcal sterile-site isolates were ATCC BAA-960 (65)....................CDC-RC, S. pseudopneumoniae also used in the study for comparison (Table 1). The controls used in the study 290-03 (72) .....................................CDC-RC, S. pseudopneumoniae were not associated with the conjunctivitis outbreaks and were used to validate 288-03 (74) .....................................CDC-RC, S. pseudopneumoniae the methods’ abilities to differentiate at the species and genus level. Groups A, 276-03 (77) .....................................CDC-RC, S. pseudopneumoniae B, C, and D were included as outgroups for statistical purposes. The 13 cPnc 253-03 (83) .....................................CDC-RC, S. pseudopneumoniae isolates described in this study are a limited sampling population and are con- 844-00..............................................Sterile site (blood), NT sidered representatives of all the clinical conjunctival isolates from the afore- 5094-02............................................Sterile site (blood or cerebrospinal mentioned U.S. outbreaks (New York in 1980, California in 1981, New Hamp- ﬂuid), NT shire in 2002, New Jersey in 2002, and Maine in 2003). 6024-01............................................Sterile site (blood or cerebrospinal Bacterial cell growth and harvest for MS analysis. Bacterial isolates stored at ﬂuid), NT 70°C were initially streaked on Trypticase soy agar (BBL, Becton Dickinson, 7232-99............................................Sterile site (blood or cerebrospinal Franklin Lakes, NJ) with 5% deﬁbrinated sheep’s blood plates and incubated ﬂuid), NT overnight at 37°C with 5% CO2. After conﬂuent growth, a full loop of bacteria Streptococcus pyogenes...................Gram-positive, capsulated, was inoculated in 10 ml of Todd-Hewitt broth (with 5% yeast extract) and grown respiratory pathogen to mid-log phase (optical density at 420 nm [OD420] of 0.4) at 37°C with 5% Escherichia coli...............................Gram-negative intestinal pathogen CO2 for 4 to 5 h. The bacterial suspension was centrifuged at 4,600 g for 10 min Enterococcus faecalis .....................Gram-positive intestinal pathogen at 4°C. The supernatant was decanted, and the pellet was washed twice in sterile Staphylococcus aureus....................Gram-positive human pathogen distilled water, followed by centrifugation at 10,000 g at room temperature for a 10 min. The pellet ( 1012 cells) was resuspended in 50 l of water, aliquoted (2 The “SS” designations and the numbers and letters in parentheses are strain identity codes from the CDC catalog for Streptococcus. l) in microcentrifuge tubes, and stored at 70°C until further use. To ensure purity among the isolates, the resuspended bacterial inoculum was streaked on a Trypticase soy agar blood plate and incubated overnight at 37°C with 5% CO2. All strains were cultured and grown three separate times over a 3-day period. well stainless steel MALDI target plate (Applied Biosystems [AB], Framingham, The strains were grown to the same OD (mid-log phase at OD420 of 0.4) to MA) was used in the study. The plates were washed with Milli-Q-grade water, ensure consistency in growth. treated with methanol, and allowed to dry at room temperature. When dry, 0.5 Preparing bacterial cell suspensions for MALDI-TOF analysis. The MALDI l of premixed suspensions containing matrices and whole bacterial forms or matrix consisted of saturated solutions (20 mg/ml) of 3,5-dimethoxy-4-hydroxy- mass standards for calibration (Sequazyme peptide mass standards kit; AB) were cinnaminic acid (sinapinic acid [SA]) (Sigma-Aldrich). SA was mixed with 50% spotted in four separate wells to create quadruplicates of samples and controls. acetonitrile and Milli-Q-grade water containing 10% triﬂuoroacetic acid. A 192- In addition, 0.5 l of bovine cytochrome c (1 mM) was added to one well of each VOL. 74, 2008 MALDI-TOF MS ANALYSIS OF PNEUMOCOCCAL CONJUNCTIVITIS 5893 sample and used as an internal standard. After air drying, the plates were RESULTS inserted into the instrument for MALDI-TOF MS analysis. MALDI-TOF MS analysis. Mass spectra were acquired using a MALDI-TOF/ MALDI-TOF MS spectra of cPnc isolates. MALDI-TOF TOF mass spectrometer (AB 4700 Proteomics Analyzer) equipped with a nitro- MS ﬁngerprinting revealed similarities among representative gen laser (Nd:YAG) at 337 nm and a 200-Hz repetition rate. Analyses were U.S. cPnc outbreak isolates. Summed, smoothed, and normal- performed at least 3 different days in linear delayed-extraction positive-ion mode at an accelerating voltage of 20 kV. The instrument was calibrated and checked ized MALDI-TOF MS spectra from bacterial samples grown before analysis with several calibration mixtures from either the peptide mass on three separate occasions revealed that the outbreaks share standards kit or the 4700 standard kit (AB), depending on the analysis mass commonalities within the 2- to 14-kDa mass range. In partic- range. Mass accuracy for each standard was within 0.05% of the corresponding ular, 11 major ion signals were observed in the region between average molecular weight. After initial manual laser intensity optimization and baseline data acquisition, spectra were acquired in automatic control mode, 4,000 and 10,000 Da, including a peak at m/z 4,425 (Fig. 1). In using uniform parameters to improve consistency and reproducibility. For opti- this mass range, it is reasonable to assume that almost all mum data quality of mass spectra in the m/z range of 2,000 to 14,000, SA was signals originate from small proteins, and as is typical for used as the matrix. The instrument was programmed to examine signals from at MALDI-TOF spectra that in the absence of evidence to the least 12 to a maximum of 100 randomly positioned nonoverlapping locations in each sample well, and the signals from the ﬁrst 10 acquisitions for each spot that contrary, these are singly charged ([M H] forms). Among met the acceptance criteria were accumulated into one ﬁnal-proﬁle mass spec- the cPnc outbreak isolates themselves, there were also minor Downloaded from http://aem.asm.org/ on March 24, 2012 by guest trum. A minimum of 11 individual spectra representing 10 accumulated subspec- differences in which several of the isolates, including NH Sp tra were obtained from each well. The acceptance criteria, based on 1,000 laser 246 (Fig. 2), lacked some protein peaks. Moreover, there are shots per spot, were signal intensities between 2,000 and 55,000 counts and a also visual differences among spectra found in conjunctival signal/noise ratio of 10 or greater. Data processing. Mass spectra from three harvestings were processed in the outbreak isolates that are not observed in the controls Pnc following manner. Spectral data were exported as text format m/z-intensity TIGR4 and R6. As would be expected, the E. coli, S. aureus, E. lists with a uniﬁed m/z scale, using custom Microsoft Visual Basic for Appli- faecalis, and S. pyogenes isolates are very different (Fig. 1). cations (VBA) macros in Data Explorer, the AB viewing application. The text A peak ion list (Table 2) of 16 peak masses, but not inclusive data were further processed and viewed by use of a suite of custom Microsoft Visual Basic .NET (VB.NET) programs. One custom program, MultiSpec of all 487 separate protein and peptide masses, generated from Viewer, was designed to display hundreds of spectra at once in a number of a manual visual peak comparison was obtained from all 45 formats, including a simulated gel view for visual analysis of the data set, isolates and compared to a UniProt Pnc protein mass library. which comprised several thousand individual spectra. Spectra failing to meet Two percent (9/487) of the data queried resulted in similarities the quality requirements (usually containing no recognizable peaks due to failures of the automatic acquisition algorithms [approximately 10% of the to known ribosomal proteins. A ribosomal spectrum overlay, total]) were discarded. The remaining spectra were subjected to background from the same Pnc database, using the MultiSpec Viewer, also subtraction and then were summed by MALDI by well or by organism (to give suggested the tentative identiﬁcation of ribosomal proteins 12 spectra or 1 representative high-quality spectrum, respectively); normal- among the conjunctival outbreak isolates as well as among Pnc ized to the base peak; smoothed using a 21-point, 2-pass Gaussian algorithm; TIGR4 and R6. The overlay constituted 11 ion peaks, within and ﬁnally standardized and denoised using a custom Fortran program (22). The output of the standardizing and denoising programs was a set of proﬁle the mass range of 4,000 to 8,000 Da (Fig. 2). spectra containing relative intensities of only the statistically signiﬁcant peaks Cluster analysis of cPnc outbreak isolates. The hierarchal (22), with zeros at all other m/z values. Thus, these data sets were in an ideal cluster analysis using the PAST program with a Jaccard simi- format for further analysis by a range of commercial statistical and data- larity coefﬁcient indicated that 12 of the 13 conjunctival iso- mining applications. To decrease the time required for statistical analyses, the summed spectra were typically compressed by a factor of 20, reducing lates are clustered together and share 76 to 86% similarity 18,000 points to 900 for a typical m/z 2,000 to 14,000 spectrum. We used (Fig. 3), while cPnc NH Sp 245 exhibited only 70% similarity PAST software v1.34 (http://folk.uio.no/ohammer/past/doc1.html) for hierar- with respect to the other conjunctival isolates. In addition, the chical cluster analysis, with the single summed spectra (one summed spec- cPnc isolates displayed 58, 58, 45, and 45% similarity to Pnc trum representing each organism) for input. We used a Fortran program, Random Forest (RF) v 5.1 (2; http://www.stat.berkeley.edu/users/breiman R6, Pnc TIGR4, NT Pnc sterile condition-isolated strains, and /RandomForests/cc_home.htm) for classiﬁcation and identiﬁcation, in this Pnc vaccine serotype strains, respectively. The dendrogram case with 9 summed spectra from three harvestings of each organism as a suggests that the conjunctival isolates are distantly related to S. training set and 3 separate summed spectra as unknowns. Recompiling the mitis, S. oralis, and S. pseudopneumoniae (45 to 48%), and Fortran RF code for each experimental condition was automatically driven by VB.NET programs, and custom viewing applications were developed to aid in there was little relationship to S. aureus, E. coli, E. faecalis, and interpreting the RF results. S. pyogenes (10 to 12%) (Fig. 3). Tentative peak matching and database searching. A tentative identiﬁcation of RF analysis of cPnc isolates. RF, a statistical algorithm that prominent peaks was done using the Tag-ident proteomics tool or ExPASy computes proximities between data sets, locates outliers, and sequence retrieval system (http://us.expasy.org). In addition, “MS DB Filter,” a computes error rates by bootstrapping (2), was performed. custom VB.NET algorithm, was used to construct a CDC-modiﬁed database ﬁltered from UniProt (http://www.ebi.ac.uk/uniprot/index.html). MS DB Filter Initially, a total of 900 spectra from the 45 isolates or classes excludes any Swiss-Prot and TrEMBL or UniProt entry described as a fragment, were analyzed, with an overall error rate of 8.33%. Outlier and strips out signal and prepeptide sequences, and applies a rule to add or remove misclassiﬁed spectra were then identiﬁed by RF by running the initial methionine as described by Pineda (19). The CDC-modiﬁed ﬁltered da- analysis 200 times using subsets of randomly selected spectra tabase was used for data mining the deduced proteome from several bacterial species used in this study which have had the whole genome sequenced. As of (68% of each class); this number of repeats was chosen so as to April 2008, information for TIGR4 and R6 species/isolates used in this study give reliable statistics on each spectrum. Outliers (with an RF could be found in the Swiss-Prot and TrEMBL databases (UniProt). Custom outlier distance of 5 or above) and consistently misclassiﬁed algorithms within MultiSpec Viewer were also used to generate peak lists from spectra (incorrect identiﬁcation rate of 25% or above) were the acquired mass spectra. In addition a manual screen of an extensive Microsoft Excel spreadsheet consisting of the 45 isolates from 2 to 14 kDa was used to excluded, and the randomized RF analysis was repeated with correlate generated peaks with the CDC-modiﬁed database in order to provide the new data set a total of three times. A total of 125 spectra tentative protein identiﬁcations. were excluded, and the overall error rate was reduced to 3.18% 5894 WILLIAMSON ET AL. APPL. ENVIRON. MICROBIOL. Downloaded from http://aem.asm.org/ on March 24, 2012 by guest FIG. 1. Differentiation of cPnc outbreak isolates and nonconjunctival bacterial controls by MALDI MS. The mass spectrum (A) and simulated- gel (B) views were prepared using a custom program, MultiSpec Viewer. The peak masses (2,000 to 14,000) in the spectrum and simulated-gel views are represented as m/z, and the relative intensity (0 to 100 [white to blue]) is expressed as a percentage. The three distinct colored lines along the right y axis are illustrated to easily distinguish the three main groups in the study (cPnc isolates, red; pneumococcal and streptococcal control isolates, green; control isolates for heterologous genera, blue). Lanes 1 to 13, cPnc outbreak isolates Sp 165, Sp 166, Sp 168, Sp 169, Sp 170, Sp 245, Sp 246, Sp 247, Sp 248, Sp 263, Sp 264, Sp 265, and Sp 266, respectively. Lanes 14 to 22, Pnc TIGR4, Pnc R6, S. mitis, S. oralis, S. pseudopneumoniae, E. coli, S. pyogenes, S. aureus, and E. faecalis, respectively. Each trace is the sum of all individual spectra (typically 10 to 20) for that organism, after background subtraction and smoothing. among the individual classes. In essence, the RF clusters the whole-organism MS ﬁngerprinting coupled with high-perfor- conjunctival isolates and controls into distinct clonal groups. mance statistical algorithm is a promising tool capable of dis- tinguishing unique and sample-limited NT cPnc outbreak strains from other pneumococcal, streptococcal, and nonstrep- DISCUSSION tococcal species. Pneumococcal conjunctivitis, usually a self-limiting infection Previous studies using molecular techniques, such as pulse- of the ocular mucosal surface, poses serious public health con- ﬁeld gel electrophoresis, multilocus sequence tagging, and sequences if not diagnosed early. The ease with which the PCR, have revealed that the cPnc isolates are similar genotyp- infection spreads among individuals warrants the need for ically (3, 15). Using MS, proteins are the most characteristic more rapid and improved detection methodologies. The sim- macromolecule that can be assessed without extraction, sepa- plicity and feasibility of generating mass spectra from whole- ration, or ampliﬁcation (6), as required by the aforementioned cell bacteria, the reproducibility of the sample preparation, technologies. In this proteomic study, albeit conﬁrmatory with and the ability to differentiate among genera, species, and previous genetics-based investigations (3, 15), MALDI-TOF strains makes MALDI-TOF MS a powerful methodology to be MS analysis as evident by visual spectrum analyses and hier- applied to the ﬁeld of clinical diagnostics. MALDI-TOF archal cluster analysis also demonstrated that the cPnc out- VOL. 74, 2008 MALDI-TOF MS ANALYSIS OF PNEUMOCOCCAL CONJUNCTIVITIS 5895 Downloaded from http://aem.asm.org/ on March 24, 2012 by guest FIG. 2. Strain differentiation among cPnc isolates and identiﬁcation of tentative ribosomal proteins present in cPnc isolates by MALDI MS. The spectrum view was prepared using a custom program, MultiSpec Viewer. The peak masses (2,000 to 14,000) in the spectrum are represented as m/z, and the relative intensity (0 to 100) is expressed as a percentage. Black arrows indicate the absence of ion peaks in isolate Sp 246. In addition, an overlay representing ribosomal proteins, obtained from a UniProt Pnc protein mass library, is illustrated (orange lines). Lanes 1 to 8, cPnc outbreak isolates Sp 165, Sp 169, Sp 170, Sp 246, Sp 247, Sp 248, Sp 263, and Sp 265, respectively. Each trace is the sum of all individual spectra (typically 10 to 20) for that organism, after smoothing. break isolates are very similar. The conjunctival isolate clus- tering is a reﬂection of unique strain characteristics of cPnc within the subset of proteins being examined in this study. TABLE 2. Tentative peak list (representatives) of conjunctival and Moreover, uniquely expressed genes that are identiﬁed will nonconjunctival isolatesa make ideal candidates for biomarker evaluation. Observed Additionally, RF was able to separate the strains in this Strain(s) mass (Da Putative protein or peptide approximate )b study into groups at the genus, species, and, to a certain extent, strain level (Sp 246) with minimal error. The low error rate of Sp 165, Sp 166, Sp 168, 2,424 ? 3.13% among the cPnc isolates indicates that the RF algorithm Sp 169, Sp 170 Sp 169, Sp 170 2,610 ? is able to correctly identify and categorize mass spectra to the Sp 165, Sp 166, Sp 168, 2,943–2,945 ? given appropriate class (individual strains or isolates) or group Sp 169, Sp 170, Sp (similar strains, i.e., speciﬁc cPnc outbreaks). The spectra that 245, Sp 246, Sp 247, are consistently being misclassiﬁed after successive screenings Sp 248, Sp 263, Sp resulting in error rates may be due to low-quality spectra that 264, Sp 265, Sp 266 Sp 166, Sp 168 3,465 ? were not ﬁltered appropriately. Interestingly, from a biological TIGR4 4,003 ? perspective, error rates may not necessarily be a negative. In TIGR4 4,218 ? our case, mismatched spectra which resulted in low error rates R6 4,741 ? can simply imply that the cPnc isolates are biologically related TIGR4, R6 5,481–5483 50S ribosomal protein L33 Sp 245, Sp 247, Sp 263, 5,495–5,499 ? and are too similar for the algorithm to distinguish. Sp 264, Sp 266 MALDI-TOF MS is a tool with great promise for the med- TIGR4 6,276 Ribosomal protein L30 ical, public health, and scientiﬁc communities. Mass spectral R6 6,648 Ribosomal protein L32 ﬁngerprinting using MALDI-MS has been used to detect bio- Sp 165, Sp 166, Sp 168, 6,872–6,875 30S ribosomal protein S21 markers from whole unfractionated microorganisms, including Sp 169, Sp 170, Sp 245, Sp 246, Sp 247, viruses, prokaryotes, and a few unicellular eukaryotes (1, 6, 9, Sp 248, Sp 263, Sp 11–14, 16, 20, 21, 24, 25). These biomarkers have proven useful 264, Sp 265, Sp 266 for rapidly identifying and differentiating microbial pathogens. TIGR4, R6 6,877 30S ribosomal protein S21 For instance, small acid-soluble proteins have been used to R6 7,998 50S ribosomal protein L29 TIGR4 10,414 30S ribosomal protein S15 characterize Bacillus species (5). Additionally, Shaw et al. re- Sp 165, Sp 248, Sp 265 11,001 50S ribosomal protein L24 ported the identiﬁcation of biomarkers in unfractionated C. a burnetii cells phase I puriﬁed from embryonic egg yolk sac Boldface indicates that the results are unique in all cPnc outbreak isolates. b Observed masses are derived from peak tops of unresolved isotopic clusters 1 Da, preparations (24). Furthermore, spectral markers in the mass assuming all ions were M H . range of 2,000 to 8,000 Da were obtained from MALDI-TOF 5896 WILLIAMSON ET AL. APPL. ENVIRON. MICROBIOL. Downloaded from http://aem.asm.org/ on March 24, 2012 by guest FIG. 3. Hierarchal cluster analysis of cPnc outbreak isolates and nonconjunctival bacterial controls. The PAST program, using the Jaccard similarity coefﬁcient (expressed as a percentage), was used to assess the relatedness of the cPnc outbreak isolates and controls. A dendrogram of cPnc outbreak isolates compared with pneumococcal, streptococcal, and nonstreptococcal species is presented. Input data had been summed (all spectra for each organism), background subtracted, smoothed, standardized, and denoised. Shown are results for cPnc outbreak isolates (group 1), S. mitis (group 2), S. oralis (group 3), S. pseudopneumoniae (S. pseudopn. [group 4]), Pnc R6 and TIGR4 (group 5), Pnc sterile-site isolated strains (group 6), and Pnc 7-valent vaccine serotypes (group 7) and heterologous genera, including, E. coli, S. pyogenes (SMIC), S. aureus, and E. faecalis (group 8). MS analysis of four human microsporidian isolates (16). Bio- ﬁed, one of which was common and exclusively expressed in markers for Mycobacterium species have also been detected by cPnc isolates. These cPnc proteomic signatures or biomarker MALDI primarily in the 500- to 2,000-Da range, most likely candidates could ultimately be fruitful in the diagnosis of this representing lipid molecules or small polypeptides (18). infection. These expressed biomarkers are advantageous com- Protein biomarkers identiﬁed by MALDI-TOF MS are often pared to genetic markers that would provide only information basic, such as the highly conserved and abundant ribosomal based on their expressive potential. Conjunctival isolate pro- protein families (19). In the present study, several ribosomal tein biomarkers would be a true indication of the organisms’ proteins, as illustrated in Fig. 2, were tentatively identiﬁed in ability to cause disease. Moreover, MALDI-TOF MS, with its the range of 2,000 to 14,000 Da by database searching and high sensitivity, may also prove useful in gaining insight into spectrum overlay. The tentative proteins appeared to be con- the pathogenic mechanisms of disease, in particular mecha- served, based on mass, among the cPnc isolates as well as in nisms by which these NT cPnc strains cause large sporadic other penumococcal strains. In addition, there was a peak at outbreaks. For instance, cPnc surface proteins associated with m/z 2,944 that was common to and uniquely expressed in the adherence or attachment to host cells that would subsequently cPnc isolates relative to other strains tested. This biomarker initiate infection could be used as biomarkers. Furthermore, candidate will require amino acid sequencing for validation as understanding how and why these cPnc strains cause disease a clinical diagnostic marker. can aid in the development of better treatments and even In conclusion, MALDI-TOF MS, a rapid and sensitive meth- prophylactic measures to minimize the spread of infection dur- odology, was successfully utilized for differentiating cPnc U.S. ing future outbreaks. outbreak isolates. Through statistical algorithms and hierar- chal clustering, it was demonstrated that the cPnc outbreak isolates from California and the northeastern United States ACKNOWLEDGMENTS are very similar. Based on their MALDI-TOF MS ﬁngerprints, This work was supported in part by an Emerging Infectious Diseases putative peptide/protein biomarkers were tentatively identi- Research Fellowship sponsored by the Association of Public Health VOL. 74, 2008 MALDI-TOF MS ANALYSIS OF PNEUMOCOCCAL CONJUNCTIVITIS 5897 Laboratories and the National Center for Infectious Diseases at the K. L. Wahl. 2000. Extracting and visualizing matrix-assisted laser desorption/ Centers for Disease Control and Prevention. ionization time–of-ﬂight mass spectral ﬁngerprints. Rapid Commun. Mass We thank Rickard Facklam for insight. Spectrom. 13:1586–1594. The ﬁndings and conclusions in this report are those of the authors 13. Krader, P., and D. Emerson. 2004. Identiﬁcation of archaea and some extremophilic bacteria using matrix-assisted laser desorption/ionization and do not necessarily represent the ofﬁcials of the Centers for Disease time-of-ﬂight (MALDI-TOF) mass spectrometry. Extremophiles 8:259–268. Control and Prevention. 14. Lay, J. O., Jr. 2001. MALDI-TOF mass spectrometry of bacteria. Mass REFERENCES Spectrom. Rev. 20:172–194. 15. Martin, M., J. H. Turco, M. E. Zegans, et al. 2003. An outbreak of conjunc- 1. Amiri-Eliasi, B., and C. Fenselau. 2001. Characterization of protein biomar- tivitis due to atypical Streptococcus pneumoniae. N. Engl. J. Med. 348:1112– kers desorbed by MALDI from whole fungal cells. Anal. Chem. 73:5228– 1121. 5231. 2. Breiman, L. 2001. Random Forests. Machine Learning 45:5–32. 16. Moura, H. M., M. Ospina, A. R. Woolﬁtt, J. R. Barr, and G. S. Visvesvara. 3. Carvalho, M. G. S., A. G. Steigerwalt, T. Thompson, D. Jackson, and R. R. 2003. Analysis of four human microsporidian isolates by MALDI-TOF. J. Facklam. 2003. Conﬁrmation of nontypeable Streptococcus pneumoniae-like Eukaryot. Microbiol. 50:156–163. organisms isolated from outbreaks of epidemic conjunctivitis as Streptococ- 17. Perkins, R. E., R. B. Kundsin, M. V. Pratt, I. Abrahamsen, and H. M. cus pneumoniae. J. Clin. Microbiol. 41:4415–4417. Leibowitz. 1975. Bacteriology of normal and infected conjunctiva. J. Clin. 4. Carvalho, M. G. S., M. L. Tondella, K. McCaustland, L. Weidlich, L. McGee, Microbiol. 1:147–149. L. W. Mayer, A. Steigerwalt, M. Whaley, R. R. Facklam, B. Fields, G. 18. Pignone, M., K. M. Greth, J. Cooper, D. Emerson, and J. Tang. 2006. Carlone, E. W. Ades, R. Dagan, and J. S. Sampson. 2007. Evaluation and Identiﬁcation of mycobacteria by matrix-assisted laser desorption ioniza- improvement of real-time PCR assays targeting lytA, ply, and psaA genes for tion–time-of-ﬂight mass spectrometry. J. Clin. Microbiol. 44:1963–1970. Downloaded from http://aem.asm.org/ on March 24, 2012 by guest detection of pneumococcal DNA. J. Clin. Microbiol. 45:2460–2466. 19. Pineda, F. J., M. D. Antoine, P. A. Demirev, A. B. Feldman, J. Jackman, M. 5. Castahna, E., A. Fox, and K. F. Fox. 2006. Rapid discrimination of Bacillus Longenecker, and J. S. Lin. 2003. Microorganism identiﬁcation by matrix- anthracis from other members of the B. cereus group by mass and sequence assisted laser/desorption ionization mass spectrometry and model-derived of “intact” small acid soluble proteins (SASPs) using mass spectrometry. J. ribosomal protein biomarkers. Anal. Chem. 75:3817–3822. Microbiol. Methods 67:230–240. 20. Pribil, P. A., and C. Fenselau. 2005. Characterization of enterobacteria using 6. Fenselau, C., and P. A. Demirev. 2001. Characterization of intact microor- MALDI-TOF mass spectrometry. Anal. Chem. 77:6092–6095. ganisms by MALDI mass spectrometry. Mass Spectrom. Rev. 20:157–171. 21. Pribil, P. A., E. Patton, G. Black, V. Doroshenko, and C. Fenselau. 2005. 7. Friedrichs, C., A. C. Rodloff, G. S. Chhatwal, W. Schellenberger, and K. Rapid characterization of Bacillus spores targeting species-unique peptides Eschrich. 2007. Rapid identiﬁcation of viridans streptococci by mass spec- produced with an atmospheric pressure matrix-assisted laser desorption/ trometric discrimination. J. Clin. Microbiol. 45:2392–2397. ionization source. J. Mass Spectrom. 40:464–474. 8. Giglotti, F., W. T. Williams, F. G. Hayden, J. O. Hendley, J. Benjamin, M. 22. Satten, G. A., S. Datta, H. Moura, A. R. Woolﬁtt, M. G. Carvalho, G. M. Dickens, M. Gleason, V. A. Perriello, and J. Wood. 1981. Etiology of acute Carlone, B. K. De, A. Pavlopoulus, and J. R. Barr. 2004. Standardization and conjunctivitis in children. J. Pediatr. 98:531–536. denoising algorithms for mass spectra to classify whole-organism bacterial 9. Holland, R. D., J. G. Wilkes, F. Raﬁi, J. B. Sutherland, C. C. Persons, K. J. specimens. Bioinformatics 20:3128–3136. Voorhees, and J. O. Lay, Jr. 1996. Rapid identiﬁcation of intact whole 23. Scott, J. A. G., Z. Mlacha, J. Nyiro, S. Njenga, P. Lewa, J. Obiero, H. Otieno, bacteria based on spectral patterns using matrix-laser desorption/ionization J. S. Sampson, and G. M. Carlone. 2005. Diagnosis of invasive pneumococ- with time-of-ﬂight mass spectrometry. Rapid Commun. Mass Spectrom. cal disease among children in Kenya with enzyme-linked immunosorbent 10:1227–1232. assay for immunoglobulin G antibodies to pneumococcal surface adhesin A. 10. Hoskins, J., W. E. Aborn, Jr., J. Arnold, et al. 2001. Genome of the bacte- Clin. Diagn. Lab. Immunol. 12:1195–1201. rium Streptococcus pneumoniae strain R6. J. Bacteriol. 183:5709–5717. 24. Shaw, E. I., H. Moura, A. R. Woolﬁtt, M. Ospina, H. A. Thompson, and J. R. 11. Jarman, K. H., S. T. Cebula, A. J. Saenz, C. E. Peterson, N. B. Valentine, Barr. 2004. Identiﬁcation of biomarkers of whole Coxiella burnetti phase I by M. T. Kingsley, and K. L. Wahl. 2000. An algorithm for automated bacterial MALDI-TOF mass spectrometry. Anal. Chem. 76:4017–4022. identiﬁcation using matrix-assisted laser desorption/ionization time-of-ﬂight/ 25. van Baar, B. L. 2000. Characterization of bacteria by matrix-assisted laser mass spectrometry. Anal. Chem. 72:1217–1223. desorption/ionization and electrospray mass spectrometry. FEMS Microbiol. 12. Jarman, K. H., D. S. Daly, C. E. Peterson, A. J. Saen, N. B. Valentine, and Rev. 24:193–219.
Pages to are hidden for
"Differentiation of Streptococcus pneumoniae Conjunctivitis Outbreak"Please download to view full document