Characterization of surface proteins of Cronobacter muytjensii using monoclonal antibodies and MALDI-TOF Mass spectrometry

<p>Abstract</p> <p>Background</p> <p><it>Cronobacter </it>spp. is a newly emerging pathogen that causes meningitis in infants and other diseases in elderly and immunocompromised individuals. This study was undertaken to investigate surface antigenic determinants in <it>Cronobacter </it>spp. using monoclonal antibodies (MAbs) and MALDI-TOF Mass spectrometry.</p> <p>Results</p> <p>Spleenocytes from mice that were immunized with heat-killed (20 min, 80°C) <it>Cronobacter </it>cells were fused with SP2 myeloma cells. Five desirable MAbs (A1, B5, 2C2, C5 and A4) were selected. MAbs A1, B5, 2C2 and C5 were of IgG2a isotype while A4 was an IgM. Specificity of the MAbs was determined by using immunoblotting with outer membrane protein preparations (OMPs) extracted from 12 <it>Cronobacter </it>and 6 non-<it>Cronobacter </it>bacteria. All MAbs recognized proteins with molecular weight ranging between 36 and 49 kDa except for one isolate (44) in which no OMPs were detected. In addition, MAbs recognized two bands (38-41 kDa) in four of the non-<it>Cronobacter </it>bacteria. Most of the proteins recognized by the MAbs were identified by MALDI-TOF peptide sequencing and appeared to be heterogeneous with the identities of some of them are still unknown. All MAbs recognized the same epitope as determined by an additive Index ELISA with their epitopes appeared to be conformational rather than sequential. Further, none of the MAbs recognized purified LPS from <it>Cronobacter </it>spp. Specificity of the MAbs toward OMPs was further confirmed by transmission electron microscopy.</p> <p>Conclusions</p> <p>Results obtained in this study highlight the immunological cross-reactivity among <it>Cronobacter </it>OMPs and their <it>Enterobacteriaceae </it>counterparts. Nevertheless, the identity of the identified proteins appeared to be different as inferred from the MALDI-TOF sequencing and identification.</p

Isolation of Cronobacter spp. (formerly Enterobacter sakazakii) from infant food, herbs and environmental samples and the subsequent identification and confirmation of the isolates using biochemical, chromogenic assays, PCR and 16S rRNA sequencing

BACKGROUND: Cronobacter spp. (formerly Enterobacter sakazakii), are a group of Gram-negative pathogens that have been implicated as causative agents of meningitis and necrotizing enterocolitis in infants. The pathogens are linked to infant formula; however, they have also been isolated from a wide range of foods and environmental samples. RESULTS: In this study, 233 samples of food, infant formula and environment were screened for the presence of Cronobacter spp. in an attempt to find its source. Twenty nine strains were isolated from samples of spices, herbs, infant foods, and dust obtained from household vacuum cleaners. Among the 76 samples of infant food, infant formula, milk powder and non-milk dairy products tested, only one sample of infant food contained Cronobacter spp. (1.4%). The other Cronobacter spp. isolates recovered include two from household vacuum dust, and 26 from 67 samples of herbs and spices. Among the food categories analyzed, herbs and spices harbored the highest number of isolates, indicating plants as a possible reservoir of this pathogen. Initial screening with API 20E test strips yielded 42 presumptive isolates. Further characterization using 3 chromogenic media (α-MUG, DFI and EsPM) and 8 sets of PCR primers detecting ITS (internal transcribed spacer sequences), 16S rRNA, zpx, gluA, gluB, OmpA genes followed by nucleotide sequencing of some PCR amplicons did not confirm the identity of all the isolates as none of the methods proved to be free of both false positives or false negatives. The final confirmation step was done by 16S rRNA sequence analysis identifying only 29 of the 42 isolates as Cronobacter spp. CONCLUSION: Our studies showed that Cronobacter spp. are highly diverse and share many phenotypic traits with other Enterobacteriaceae members highlighting the need to use several methods to confirm the identity of this pathogen. None of the biochemical, chromogenic or PCR primers proved to be a reliable method for confirmation of the identity of the isolates as all of them gave either false positives or false negatives or both. It is therefore concluded that 16S rRNA sequencing is pivotal to confirm the identity of the isolates

A Systematic Analysis of Cell Cycle Regulators in Yeast Reveals That Most Factors Act Independently of Cell Size to Control Initiation of Division

Upstream events that trigger initiation of cell division, at a point called START in yeast, determine the overall rates of cell proliferation. The identity and complete sequence of those events remain unknown. Previous studies relied mainly on cell size changes to identify systematically genes required for the timely completion of START. Here, we evaluated panels of non-essential single gene deletion strains for altered DNA content by flow cytometry. This analysis revealed that most gene deletions that altered cell cycle progression did not change cell size. Our results highlight a strong requirement for ribosomal biogenesis and protein synthesis for initiation of cell division. We also identified numerous factors that have not been previously implicated in cell cycle control mechanisms. We found that CBS, which catalyzes the synthesis of cystathionine from serine and homocysteine, advances START in two ways: by promoting cell growth, which requires CBS's catalytic activity, and by a separate function, which does not require CBS's catalytic activity. CBS defects cause disease in humans, and in animals CBS has vital, non-catalytic, unknown roles. Hence, our results may be relevant for human biology. Taken together, these findings significantly expand the range of factors required for the timely initiation of cell division. The systematic identification of non-essential regulators of cell division we describe will be a valuable resource for analysis of cell cycle progression in yeast and other organisms

Isolation of <it>Cronobacter </it>spp. (formerly <it>Enterobacter sakazakii) </it>from infant food, herbs and environmental samples and the subsequent identification and confirmation of the isolates using biochemical, chromogenic assays, PCR and 16S rRNA sequencing

Abstract Background Cronobacter spp. (formerly Enterobacter sakazakii), are a group of Gram-negative pathogens that have been implicated as causative agents of meningitis and necrotizing enterocolitis in infants. The pathogens are linked to infant formula; however, they have also been isolated from a wide range of foods and environmental samples. Results In this study, 233 samples of food, infant formula and environment were screened for the presence of Cronobacter spp. in an attempt to find its source. Twenty nine strains were isolated from samples of spices, herbs, infant foods, and dust obtained from household vacuum cleaners. Among the 76 samples of infant food, infant formula, milk powder and non-milk dairy products tested, only one sample of infant food contained Cronobacter spp. (1.4%). The other Cronobacter spp. isolates recovered include two from household vacuum dust, and 26 from 67 samples of herbs and spices. Among the food categories analyzed, herbs and spices harbored the highest number of isolates, indicating plants as a possible reservoir of this pathogen. Initial screening with API 20E test strips yielded 42 presumptive isolates. Further characterization using 3 chromogenic media (α-MUG, DFI and EsPM) and 8 sets of PCR primers detecting ITS (internal transcribed spacer sequences), 16S rRNA, zpx, gluA, gluB, OmpA genes followed by nucleotide sequencing of some PCR amplicons did not confirm the identity of all the isolates as none of the methods proved to be free of both false positives or false negatives. The final confirmation step was done by 16S rRNA sequence analysis identifying only 29 of the 42 isolates as Cronobacter spp. Conclusion Our studies showed that Cronobacter spp. are highly diverse and share many phenotypic traits with other Enterobacteriaceae members highlighting the need to use several methods to confirm the identity of this pathogen. None of the biochemical, chromogenic or PCR primers proved to be a reliable method for confirmation of the identity of the isolates as all of them gave either false positives or false negatives or both. It is therefore concluded that 16S rRNA sequencing is pivotal to confirm the identity of the isolates.</p

Cys4p advances START both by promoting cell growth and by a separate function, which does not require CBS's catalytic activity.

<p>A, Rate of cell size increase (shown as growth rate, in fl/min) for the indicated strains was measured assuming linear growth from synchronous elutriated cultures in media that contain galactose and induce expression of the <i>P_GAL</i> alleles (see <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1002590#s4" target="_blank">Methods</a>). The average value for each strain is shown with a horizontal bar (± sd). Where indicated, the <i>P</i> values shown were calculated from two-tailed <i>t</i> tests. The data used to calculate the values shown in A and B are in <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1002590#pgen.1002590.s009" target="_blank">Figure S8</a>. B, The critical cell size of the indicated strains (shown in fl), was measured from the same elutriation experiments shown in A (see also <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1002590#pgen.1002590.s010" target="_blank">Figure S9</a>). The analogous experiments in non-inducing, glucose containing, medium are shown in <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1002590#pgen.1002590.s010" target="_blank">Figure S9</a>.</p

Network representation of the “Low G1” group.

<p>The interactions shown are from the gold-standard reference database BioGRID <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1002590#pgen.1002590-Stark1" target="_blank">[54]</a>. The network was constructed with Cytoscape <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1002590#pgen.1002590-Smoot1" target="_blank">[83]</a>, and displayed using an unbiased, force-generated layout. Only the factors that showed interactions (physical or functional) are included. We also included the essential gene <i>CDC28</i> (shown in red), encoding the major yeast Cdk.</p

Decreased fitness correlates with altered cell cycle progression.

<p>The y-axis shows the fitness values of Giaever et al <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1002590#pgen.1002590-Giaever1" target="_blank">[33]</a>. Higher values indicate reduced fitness. The cutoff for reduced fitness was about <85% of the wild type in that study <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1002590#pgen.1002590-Giaever1" target="_blank">[33]</a>. Thus, strains with possible small reductions in fitness have been assigned a “WT-like” fitness score of 1. Giaever et al <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1002590#pgen.1002590-Giaever1" target="_blank">[33]</a> evaluated fitness of the same strains we used, during growth in rich (YPD-2%Dextrose) liquid media, allowing for a direct comparison with our dataset. We used the non-parametric Spearman test to obtain the correlation (<i>r</i>) values we show. The correlation coefficient for all the strains (<i>r</i>_T) is shown at the bottom right of the graph. We colored the r values for the sub-groups as in <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1002590#pgen-1002590-g002" target="_blank">Figure 2</a>. For every gene we included in this analysis, the values we used in this correlation are shown in <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1002590#pgen.1002590.s001" target="_blank">Dataset S1</a>.</p

Schematic overview of our approach.

<p>For a detailed description of all the protocols we used, see <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1002590#s4" target="_blank">Methods</a>.</p

Cys4p has a vital, non-catalytic role in cell proliferation.

<p>A, Immunoblots showing the levels of Cys4p in the indicated strains, detected with an antibody against human CBS. We probed the same blot with an antibody against yeast Cdc28p, to indicate loading. B, Growth of the same strains on rich (YPD) and synthetic minimal media (SMM). We added cysteine (at 2.5 mM), to the SMM plate at the bottom. All strains were spotted on plates at 5-fold serial dilutions from liquid cultures, starting at ∼5,000 cells.</p

Interactions among the factors of the “High G1” group.

<p>The network of interactions was constructed and displayed as in <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1002590#pgen-1002590-g007" target="_blank">Figure 7</a>. We also included factors with known roles at START (shown in red), which were not identified in our study. Among the G1 cyclins, we only included Cln3p, which is responsible for initiating the positive feedback loop of the large G1/S transcriptional program <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1002590#pgen.1002590-Skotheim1" target="_blank">[10]</a>–<a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1002590#pgen.1002590-Doncic1" target="_blank">[12]</a>. The other G1 cyclins, Cln1p and Cln2p, are important for this feedback, once it is initiated by Cln3p, but they were not included in this network. 60S ribosomal proteins are in yellow, while 40S ribosomal proteins are in orange. The most highly connected factors among the ones we identified are in green, and Cys4p is in blue.</p