A novel immunoproteomics method for identifying in vivo-induced Campylobacter jejuni antigens using pre-adsorbed sera from infected patients

Background

Campylobacter jejuni is an important food-borne and zoonotic pathogen with a worldwide distribution. Humans and chickens are hosts of this pathogen. At present, there is no ideal vaccine for controlling human campylobacteriosis or the carriage of C. jejuni by chickens. Bacterial in vivo-induced antigens are useful as potential vaccine candidates and biomarkers of virulence.

Methods

In this study, we developed a novel systematic immunoproteomics approach to identify in vivo-induced antigens among the total cell proteins of C. jejuni using pre-adsorbed sera from patients infected with C. jejuni.

Results

Overall, 14 immunoreactive spots were probed on a PVDF membrane using pre-adsorbed human sera against C. jejuni. Then, we excised these protein spots from a duplicate gel and identified using MALDI–TOF MS. In total, 14 in vivo-induced antigens were identified using PMF and BLAST analysis. The identified proteins include CadF (CadF-1 and CadF-2), CheW, TufB, DnaK, MetK, LpxB, HslU, DmsA, PorA, ProS, CJBH_0976, CSU_0396 and hypothetical protein cje135_05017. Real-time RT-PCR was performed on 9 genes to compare their expression levels in vivo and in vitro. The data showed that 8 of the 9 analyzed genes were significantly upregulated in vivo relative to in vitro.

Conclusion

We successfully developed a novel immunoproteomics method for identifying in vivo-induced Campylobacter jejuni antigens by using pre-adsorbed sera from infected patients.

General significance

This new analysis method may prove to be useful for identifying in vivo-induced antigens within any host infected by bacteria and will contribute to the development of new subunit vaccines.     

Dispersal and dormancy strategies among insect species competing for a pulsed resource

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REPLY TO “COMMENT ON MARDEN (2013) REGARDING THE INTERPRETATION OF THE EARLIEST TRACE FOSSIL OF A WINGED INSECT”

Benner, Knecht, and Engel have replied to my critique of their interpretation of a Carboniferous trace fossil produced by an insect at the edge of water. Here I respond by pointing out that their reiterated scenario still requires mutually exclusive paths of motion and I show that their assertions of methodological shortcomings are tangential and lack merit. Overall, this discussion provides an opportunity to examine in greater detail competing hypothesis about behaviors and taxonomic identity of the trace maker, and relevance thereof to competing theories regarding early events in the evolution of pterygote insects.     

Flagella proteins contribute to the production of outer membrane vesicles from Escherichia coli W3110

Gram-negative bacteria, including Escherichia coli, release outer membrane vesicles (OMVs) that are derived from the bacterial outer membrane. OMVs contribute to bacterial cell–cell communications and host–microbe interactions by delivering components to locations outside the bacterial cell. In order to explore the molecular machinery involved in OMV biogenesis, the role of a major OMV protein was examined in the production of OMVs from E. coli W3110, which is a widely used standard E. coli K-12 strain. In addition to OmpC and OmpA, which are used as marker proteins for OMVs, an analysis of E. coli W3110 OMVs revealed that they also contain abundant levels of FliC, which is also known as flagellin. A membrane-impermeable biotin-labeling reagent did not label FliC in intact OMVs, but labeled FliC in sonically disrupted OMVs, suggesting that FliC is localized in the lumen of OMV. Compared to the parental strain expressing wild-type fliC, an E. coli strain with a fliC-null mutation produced reduced amounts of OMVs based on both protein and phosphate levels. In addition, an E. coli W3110-derived strain with a null-mutation in flgK, which encodes flagellar hook-associated protein that is essential along with FliC for flagella synthesis, also produced fewer OMVs than the parental strain. Taken together, these results indicate that the ability to form flagella, including the synthesis of flagella proteins, affects the production of E. coli W3110 OMVs.     

Decoding the ‘zeep’ complex: quantitative analysis of interspecific variation in the nocturnal flight calls of nine wood warbler species (Parulidae spp.)

ABSTRACT

The “zeep” complex consists of nine birds that produce nocturnal flight calls with similar acoustic features. Our inability to distinguish these calls inhibits the acoustic monitoring of these species. We test the hypothesis that flight calls of nine warblers in the “zeep” complex show sufficient acoustic differences to allow differentiation. We investigate divergence in these vocalizations by recording birds held for banding and collecting additional recordings from sound libraries. We used three approaches to compare calls between species: analysis of variance in acoustic properties, discriminant analysis of acoustic properties, and spectrographic cross-correlation. The first approach revealed five species that were different in one or more acoustic properties. The second approach revealed a level of assignment to the correct species (73%) that exceeded levels expected by chance (36%). The third approach revealed calls of seven species to be significantly more similar to conspecific calls than heterospecific calls. Our results suggest the calls of many members of the “zeep” complex exhibit species-specific differences in structure, which may allow differentiation of at least five “zeep” species based on call alone. We advocate for the combined use of these three approaches for the comparison of “zeep” calls in future flight call studies.     

AUTOMATIC FEATURE EXTRACTION AND CLASSIFICATION OF CROSSBILL (LOXIA SPP.) FLIGHT CALLS

ABSTRACT

In this paper a new method for the automatic classification of bird sounds is presented. Our method is based on acoustic parameters (features) taken from the first harmonic component computed from the sound spectrogram. The features are based on a line segment approximation of the first harmonic component. The final feature vectors, consisting of 16 real numbers, are then classified using a self-organizing map (SOM) neural network. Flight calls of four crossbill species (Loxia spp.) are used as a test example. In the first phase, an unsupervised network was trained and tested using common crossbill L. curvirostra flight calls recorded mainly in the Netherlands. The network was tested using two-barred L. leucoptera, Scottish L. scotica and parrot L. pytyopsittacus crossbill flight calls in the second phase. Finally, the results were validated applying the same network to flight calls of common crossbills and parrot crossbills recorded in Finland. The method automatically separated common crossbill flight calls from those of parrot crossbills. The classification accuracy of the Dutch recordings was 58% in the first phase and 54% in the second phase. The Finnish recordings were classified with 54% accuracy.     

Life history of the Glanville fritillary butterfly in fragmented versus continuous landscapes

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