Altered Formalin-Induced Pain and Fos Induction in the Periaqueductal Grey of Preadolescent Rats following Neonatal LPS Exposure

Animal and human studies have demonstrated that early pain experiences can produce alterations in the nociceptive systems later in life including increased sensitivity to mechanical, thermal, and chemical stimuli. However, less is known about the impact of neonatal immune challenge on future responses to noxious stimuli and the reactivity of neural substrates involved in analgesia. Here we demonstrate that rats exposed to Lipopolysaccharide (LPS; 0.05 mg/kg IP, Salmonella enteritidis) during postnatal day (PND) 3 and 5 displayed enhanced formalin-induced flinching but not licking following formalin injection at PND 22. This LPS-induced hyperalgesia was accompanied by distinct recruitment of supra-spinal regions involved in analgesia as indicated by significantly attenuated Fos-protein induction in the rostral dorsal periaqueductal grey (DPAG) as well as rostral and caudal axes of the ventrolateral PAG (VLPAG). Formalin injections were associated with increased Fos-protein labelling in lateral habenula (LHb) as compared to medial habenula (MHb), however the intensity of this labelling did not differ as a result of neonatal immune challenge. These data highlight the importance of neonatal immune priming in programming inflammatory pain sensitivity later in development and highlight the PAG as a possible mediator of this process.     

Top-Down Proteomic Identification of Shiga Toxin 2 Subtypes from Shiga Toxin-Producing Escherichia coli by Matrix-Assisted Laser Desorption Ionization–Tandem Time of Flight Mass Spectrometry

We have analyzed 26 Shiga toxin-producing Escherichia coli (STEC) strains for Shiga toxin 2 (Stx2) production using matrix-assisted laser desorption ionization (MALDI)–tandem time of flight (TOF-TOF) tandem mass spectrometry (MS/MS) and top-down proteomic analysis. STEC strains were induced to overexpress Stx2 by overnight culturing on solid agar supplemented with either ciprofloxacin or mitomycin C. Harvested cells were lysed by bead beating, and unfractionated bacterial cell lysates were ionized by MALDI. The A2 fragment of the A subunit and the mature B subunit of Stx2 were analyzed by MS/MS. Sequence-specific fragment ions were used to identify amino acid subtypes of Stx2 using top-down proteomic analysis using software developed in-house at the U.S. Department of Agriculture (USDA). Stx2 subtypes (a, c, d, f, and g) were identified on the basis of the mass of the A2 fragment and the B subunit as well as from their sequence-specific fragment ions by MS/MS (postsource decay). Top-down proteomic identification was in agreement with DNA sequencing of the full Stx2 operon (stx₂) for all strains. Top-down results were also compared to a bioassay using a Vero-d2EGFP cell line. Our results suggest that top-down proteomic identification is a rapid, highly specific technique for distinguishing Stx2 subtypes.     

Development of a deer mouse whole-genome radiation hybrid panel and comparative mapping of Mus chromosome 11 loci

A 5000-rad whole-genome radiation hybrid cell panel (BW5000) was developed for mapping the deer mouse (Peromyscus maniculatus bairdii) genome. The panel consists of 103 cell lines and has an estimated marker retention frequency of 63.9% (range, 28%–88%) based on PCR typing of 30 Type I (coding gene) and 25 Type II (microsatellite) markers. Using the composite Mus map, Type I markers were selected from six Mus chromosomes, 22 of which are on Mus Chr 11. Fifteen of the Mus Chr 11 markers were simultaneously mapped on an interspecific (P. maniculatus × P. polionotus) backcross panel to test the utility of the radiation hybrid panel, create a framework map, and help establish gene order. The radiation hybrids have effectively detected linkage in the deer mouse genome between markers as far apart as 6.7 cM and resolved markers that are, in the Mus genome, as close as 0.2 Mb. Combined results from both panels have indicated a high degree of gene order conservation of the telomeric 64 cM of Mus Chr 11 in the deer mouse genome. The remaining centromeric portion also shows gene order conservation with the deer mouse but as a separate linkage group. This indicates a translocation of that portion of Mus Chr 11 in P. maniculatus and is consistent with rearrangement breakpoints observed between Mus and other mammalian genomes, including rat and human. Furthermore, this separate linkage group is likely to reside in a chromosomal region of inversion polymorphism between P. maniculatus and P. polionotus.     

Proteomic characterization of inter-alpha inhibitor proteins from human plasma

Inter-alpha inhibitor proteins (IaIp) are a family of structurally related serine protease inhibitors found in relatively high concentrations in human plasma. Recent studies have implicated a role for IaIp in sepsis, and have demonstrated their potential as biomarkers in sepsis and cancer. For characterization of isolated IaI proteins and contaminating proteins during the last steps of the purification process, SELDI-TOF MS and HPLC-ESI-MS/MS were used. After separation by SDS-PAGE or 2-DE, polypeptide bands of 80, 125 and 250 kDa were excised from gels and digested by trypsin. The tryptic peptides were analyzed by both MS methods. The main contamination during the purification process, a band of 80 kDa, contains mainly IaIp heavy chain (HC) H3. HC H1 and H2 were also found in this band. In addition, some vitamin K-dependent clotting factors and inhibitors and other plasma proteins were identified. The 125-kDa band, representing the pre-alpha inhibitor, was found to contain both bikunin and HC H3. The presence of other HC H1, H2 and the recently described HC H4 was also detected by SELDI-TOF MS. The presence of HC H1, H2, and H3 in the 125-kDa band was confirmed by ESI-MS/MS, but not the presence of the H4. Three polypeptides, H1 and H2 together with bikunin, were identified in the 250-kDa band, representing the ITI, by both MS techniques. Once again, the presence of H4 was detected in this band only by SELDI-TOF MS, but the number of corresponding peptides was still not sufficient for final identification of this polypeptide. The importance of the application of proteomic methods for the proper evaluation of therapeutic drugs based on human plasma is discussed.     

Sub-speciating Campylobacter jejuni by proteomic analysis of its protein biomarkers and their post-translational modifications

We have identified several protein biomarkers of three Campylobacter jejuni strains (RM1221, RM1859, and RM3782) by proteomic techniques. The protein biomarkers identified are prominently observed in the time-of-flight mass spectra (TOF MS) of bacterial cell lysate supernatants ionized by matrix-assisted laser desorption/ionization (MALDI). The protein biomarkers identified were: DNA-binding protein HU, translation initiation factor IF-1, cytochrome c553, a transthyretin-like periplasmic protein, chaperonin GroES, thioredoxin Trx, and ribosomal proteins: L7/L12 (50S), L24 (50S), S16 (30S), L29 (50S), and S15 (30S), and conserved proteins similar to strain NCTC 11168 proteins Cj1164 and Cj1225. The protein biomarkers identified appear to represent high copy, intact proteins. The significant findings are as follows: (1) Biomarker mass shifts between these strains were due to amino acid substitutions of the primary polypeptide sequence and not due to changes in post-translational modifications (PTMs). (2) If present, a PTM of a protein biomarker appeared consistently for all three strains, which supported that the biomarker mass shifts observed between strains were not due to PTM variability. (3) The PTMs observed included N-terminal methionine (N-Met) cleavage as well as a number of other PTMs. (4) It was discovered that protein biomarkers of C. jejuni (as well as other thermophilic Campylobacters) appear to violate the N-Met cleavage rule of bacterial proteins, which predicts N-Met cleavage if the penultimate residue is threonine. Two protein biomarkers (HU and 30S ribosomal protein S16) that have a penultimate threonine residue do not show N-Met cleavage. In all other cases, the rule correctly predicted N-Met cleavage among the biomarkers analyzed. This exception to the N-Met cleavage rule has implications for the development of bioinformatics algorithms for protein/pathogen identification. (5) There were fewer biomarker mass shifts between strains RM1221 and RM1859 compared to strain RM3782. As the mass shifts were due to the frequency of amino acid substitutions (and thus underlying genetic variations), this suggested that strains RM1221 and RM1859 were phylogenetically closer to one another than to strain RM3782 (in addition, a protein biomarker prominent in the spectra of RM1221 and RM1859 was absent from the RM3782 spectrum due to a nonsense mutation in the gene of the biomarker). These observations were confirmed by a nitrate reduction test, which showed that RM1221 and RM1859 were C. jejuni subsp. jejuni whereas RM3782 was C. jejuni subsp. doylei. This result suggests that detection/identification of protein biomarkers by pattern recognition and/or bioinformatics algorithms may easily subspeciate bacterial microorganisms. (6) Finally, the number and variation of PTMs detected in this relatively small number of protein biomarkers suggest that bioinformatics algorithms for pathogen identification may need to incorporate many more possible PTMs than suggested previously in the literature.     

Web-Based Software for Rapid Top-Down Proteomic Identification of Protein Biomarkers,with Implications for Bacterial Identification

We have developed web-based software for the rapid identification of protein biomarkers of bacterial microorganisms. Proteins from bacterial cell lysates were ionized by matrix-assisted laser desorption ionization (MALDI), mass isolated, and fragmented using a tandem time of flight (TOF-TOF) mass spectrometer. The sequence-specific fragment ions generated were compared to a database of in silico fragment ions derived from bacterial protein sequences whose molecular weights are the same as the nominal molecular weights of the protein biomarkers. A simple peak-matching and scoring algorithm was developed to compare tandem mass spectrometry (MS-MS) fragment ions to in silico fragment ions. In addition, a probability-based significance-testing algorithm (P value), developed previously by other researchers, was incorporated into the software for the purpose of comparison. The speed and accuracy of the software were tested by identification of 10 protein biomarkers from three Campylobacter strains that had been identified previously by bottom-up proteomics techniques. Protein biomarkers were identified using (i) their peak-matching scores and/or P values from a comparison of MS-MS fragment ions with all possible in silico N and C terminus fragment ions (i.e., ions a, b, b-18, y, y-17, and y-18), (ii) their peak-matching scores and/or P values from a comparison of MS-MS fragment ions to residue-specific in silico fragment ions (i.e., in silico fragment ions resulting from polypeptide backbone fragmentation adjacent to specific residues [aspartic acid, glutamic acid, proline, etc.]), and (iii) fragment ion error analysis, which distinguished the systematic fragment ion error of a correct identification (caused by calibration drift of the second TOF mass analyzer) from the random fragment ion error of an incorrect identification.Food-borne illness is a serious and continuing problem, with an estimated 76 million cases in the United States per year (http://www.cdc.gov). It is often caused by bacteria and viruses that are often ubiquitous in the environment and are difficult to eliminate due to their ability to adapt. In addition to the resulting morbidity, food-borne illness also has enormous societal costs, including losses in worker productivity due to illness, recall of food products determined (or suspected) to be contaminated, etc. Consequently, there is a critical need to develop rapid and sensitive methods for detection and accurate identification of food-borne pathogens.A number of techniques have been developed for detection and identification of food-borne pathogens. A relatively recent technique for bacterial identification involves the use of mass spectrometry (MS). Because of its sensitivity and high specificity, MS has become a popular technique for chemicotaxonomic classification of microorganisms (16, 27). The use of MS in the analysis of microorganisms is a relatively recent application that was dramatically accelerated by the development of two ionization techniques in the late 1980s and early 1990s: electrospray ionization (15) and matrix-assisted laser desorption ionization (MALDI) (24, 37). When coupled with time of flight (TOF) MS, MALDI has been demonstrated to be a powerful tool for “fingerprinting” microorganisms by ionization and detection of proteins from intact bacterial cells or extracts resulting from bacterial cell lysis (1, 2, 3, 8-12, 19, 21, 25, 26, 29, 34, 40, 41, 42). Typically, MALDI-TOF MS “fingerprinting” of microorganisms involves analysis using either pattern recognition or bioinformatic algorithms.Pattern recognition analysis compares MALDI-TOF MS spectra of samples of unknown microorganisms to spectra of known microorganisms. A high degree of similarity between the MS spectrum of an unknown microorganism and an MS spectrum of a known microorganism strongly suggests the identity of the unknown microorganism (22, 39, 43). It should be noted that pattern recognition analysis does not rely on actual identification of the biomarker ion peaks in an MS spectrum. It is the pattern generated by multiple ion peaks that constitutes a microorganism''s “fingerprint.” The actual identities of individual ion peaks are not specified, and the peaks could be peaks for any of a number of possible biological molecules generated by a microorganism, including proteins, nucleic acids, lipids, etc.Microorganism identification by bioinformatic analysis of MALDI-TOF MS data involves using the protein molecular weights (MWs) in bacterial genomic databases to assign biomarker ion peaks in a mass spectrum to specific proteins (4, 5, 32, 33, 45). If a significant number of biomarker ion peaks in a mass spectrum correspond to protein MWs for the open reading frames of a microorganism''s genome, then the microorganism is considered identified. Such an analysis has also incorporated the simplest and most common posttranslational modification (PTM) observed for bacterial proteins, N-terminal methionine cleavage (5). It should be noted, however, that “identification” of a microorganism relies solely on a sufficient number of protein MWs derived from open reading frames of its genome corresponding to the m/z of biomarker ions in a MALDI-TOF MS spectrum. However, the protein MW alone is not sufficient to definitively identify a biomarker ion as a specific protein. Protein biomarkers are considered to be tentatively assigned instead of definitively identified.Analysis of samples containing multiple bacterial organisms presents increased challenges for MALDI-TOF MS when protein MW is the sole criterion for protein biomarker identification. Clearly, it would be advantageous if researchers could obtain more information about a biomarker in addition to its MW. In the case of protein biomarkers, this can be accomplished by enzymatically digesting a protein in solution and analyzing its tryptic peptides by MS (peptide mass mapping) or by tandem MS (MS-MS) (sequence tags) (45). Alternatively, it is possible to fragment mature, intact proteins (without digestion) in the gas phase to obtain sequence-specific and PTM information. This approach is referred to as top-down proteomics. Until recently, top-down proteomics was possible only if Fourier transform ion cyclotron resonance MS involving complicated gas phase ion dissociation techniques was used (6, 23).Although not originally designed for top-down proteomics, recently developed MALDI-tandem TOF (MALDI-TOF-TOF) MS was shown to fragment small or modest-size proteins (5 kDa > molecular mass < 15 kDa) without prior digestion (28). Demirev and coworkers (7) identified Bacillus atrophaeus and Bacillus cereus spores by fragmenting their protein biomarkers using a MALDI tandem mass spectrometer and analyzing the sequence-specific fragment ions generated by comparison to in silico fragment ions derived from protein amino acid sequences from genomic databases. Protein and microorganism identities were determined using a probability-based significance-testing algorithm (P value). The P value algorithm calculates the probability that a protein or microorganism identification occurred randomly. The smaller the P value, the lower the probability that an identification occurred randomly. The data analysis was performed using software developed in house (7).In the current study, web-based software and databases, developed in house at the U.S. Department of Agriculture (USDA), were used to identify 10 protein biomarkers from three pure strains of Campylobacter by sequence-specific fragmentation using a MALDI-TOF-TOF mass spectrometer. Many of the protein biomarkers had been identified previously by bottom-up proteomics techniques (9, 11, 12), which provided an excellent data set to test the accuracy and performance of the algorithms incorporated into the software. MALDI-TOF-TOF MS-MS fragment ions were compared with a database of in silico fragment ions derived from bacterial protein sequences. The sequence-specific MS-MS fragment ions were used to identify a protein and thus the source microorganism. A simple peak-matching mathematical algorithm, incorporated into the software, was used to score and rank protein and microorganism identifications. In addition, the P value algorithm of Demirev and coworkers (7) was also incorporated into the USDA software (available with execution of appropriate control usage agreement) for comparison to the peak-matching algorithm. The peak-matching algorithm correctly identified a protein biomarker among as many as ∼1,400 possible bacterial proteins and gave rankings for protein identification comparable to the rankings obtained by more complicated and computationally intensive P value calculation. We often observed enhancement of the score for correct identification when results for MS-MS fragment ions were compared to results for residue-specific in silico fragment ions compared to non-residue-specific in silico fragment ions. In addition, the correctness of the algorithm''s identification was, in certain cases, further confirmed by fragment ion error analysis which compared random error caused by false matches between MS-MS fragment ions and in silico fragment ions with the systematic error observed for correct matches due to drift in the calibration of the TOF mass analyzer (38).(Portions of this work were presented at the 121st AOAC Conference [13] and at the 55th American Society of Mass Spectrometry Conference [14].)     

Development and analysis of a germline BAC resource for the sea lamprey, a vertebrate that undergoes substantial chromatin diminution

Over the last several years, the sea lamprey (Petromyzon marinus) has grown substantially as a model for understanding the evolutionary fundaments and capacity of vertebrate developmental and genome biology. Recent work on the lamprey genome has resulted in a preliminary assembly of the lamprey genome and led to the realization that nearly all somatic cell lineages undergo extensive programmed rearrangements. Here we describe the development of a bacterial artificial chromosome (BAC) resource for lamprey germline DNA and use sequence information from this resource to probe the subchromosomal structure of the lamprey genome. The arrayed germline BAC library represents ∼10× coverage of the lamprey genome. Analyses of BAC-end sequences reveal that the lamprey genome possesses a high content of repetitive sequences (relative to human), which show strong clustering at the subchromosomal level. This pattern is not unexpected given that the sea lamprey genome is dispersed across a large number of chromosomes (n ∼ 99) and suggests a low-copy DNA targeting strategy for efficiently generating informative paired-BAC-end linkages from highly repetitive genomes. This library therefore represents a new and biologically informed resource for understanding the structure of the lamprey genome and the biology of programmed genome rearrangement.     

Cooccurrence of prey species alters the impact of predators on prey performance through multiple mechanisms

When prey are differentially affected by intra and interspecific competition, the cooccurrence of multiple prey species alters the per capita availability of food for a particular prey species which could alter how prey respond to the threat of predation, and hence the overall‐effect of predators. We conducted an experiment to examine the extent to which the nonconsumptive and overall effect of predatory water bugs on snail and tadpole traits (performance and morphology) depended on whether tadpoles and snails cooccurred. Tadpoles and snails differed in their relative susceptibility to intraspecific and interspecific competition, and predators affected both prey species via consumptive and nonconsumptive mechanisms. Furthermore, the overall effect of predators often depended on whether another prey species was present. The reasoning for why the overall effect of predators depended on whether prey species cooccurred, however, differed for each of the response variables. Predators affected snail body growth via nonconsumptive mechanisms, but the change in the overall effect of predators on snail body growth was attributable to how snails responded to competition in the absence of predators, rather than a change in how snails responded to the threat of predation. Predators did not affect tadpole body growth via nonconsumptive mechanisms, but the greater vulnerability of competitively superior prey (snails) to predators increased the strength of consumptive mechanisms (and hence the overall effect) through which predators affected tadpole growth. Predators affected tadpole morphology via nonconsumptive mechanisms, but the greater propensity for predators to kill competitively superior prey (snails) enhanced the ability of tadpoles to alter their morphology in response to the threat of predation by creating an environment where tadpoles had a higher per capita supply of food available to invest in the development of morphological defenses. Our work indicates that the mechanisms through which predators affect prey depends on the other members of the community.