Matrix-Assisted Laser Desorption Ionization-Time of Flight Mass Spectrometry for the Identification of Clinically Relevant Bacteria

Background: Matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS) allows rapid and reliable identification of microorganisms, particularly clinically important pathogens. Methodology/Principal Findings: We compared the identification efficiency of MALDI-TOF MS with that of PhoenixH, APIH and 16S ribosomal DNA sequence analysis on 1,019 strains obtained from routine diagnostics. Further, we determined the agreement of MALDI-TOF MS identifications as compared to 16S gene sequencing for additional 545 strains belonging to species of Enterococcus, Gardnerella, Staphylococcus, and Streptococcus. For 94.7 % of the isolates MALDI-TOF MS results were identical with those obtained with conventional systems. 16S sequencing confirmed MALDI-TOF MS identification in 63 % of the discordant results. Agreement of identification of Gardnerella, Enterococcus, Streptococcus and Staphylococcus species between MALDI-TOF MS and traditional method was high (Crohn’s kappa values: 0.9 to 0.93). Conclusions/Significance: MALDI-TOF MS represents a rapid, reliable and cost-effective identification technique for clinically relevant bacteria

Dinucleotide controlled null models for comparative RNA gene prediction

<p>Abstract</p> <p>Background</p> <p>Comparative prediction of RNA structures can be used to identify functional noncoding RNAs in genomic screens. It was shown recently by Babak <it>et al</it>. [BMC Bioinformatics. 8:33] that RNA gene prediction programs can be biased by the genomic dinucleotide content, in particular those programs using a thermodynamic folding model including stacking energies. As a consequence, there is need for dinucleotide-preserving control strategies to assess the significance of such predictions. While there have been randomization algorithms for single sequences for many years, the problem has remained challenging for multiple alignments and there is currently no algorithm available.</p> <p>Results</p> <p>We present a program called SISSIz that simulates multiple alignments of a given average dinucleotide content. Meeting additional requirements of an accurate null model, the randomized alignments are on average of the same sequence diversity and preserve local conservation and gap patterns. We make use of a phylogenetic substitution model that includes overlapping dependencies and site-specific rates. Using fast heuristics and a distance based approach, a tree is estimated under this model which is used to guide the simulations. The new algorithm is tested on vertebrate genomic alignments and the effect on RNA structure predictions is studied. In addition, we directly combined the new null model with the RNAalifold consensus folding algorithm giving a new variant of a thermodynamic structure based RNA gene finding program that is not biased by the dinucleotide content.</p> <p>Conclusion</p> <p>SISSIz implements an efficient algorithm to randomize multiple alignments preserving dinucleotide content. It can be used to get more accurate estimates of false positive rates of existing programs, to produce negative controls for the training of machine learning based programs, or as standalone RNA gene finding program. Other applications in comparative genomics that require randomization of multiple alignments can be considered.</p> <p>Availability</p> <p>SISSIz is available as open source C code that can be compiled for every major platform and downloaded here: <url>http://sourceforge.net/projects/sissiz</url>.</p

Conserved Secondary Structures in Aspergillus

Background: Recent evidence suggests that the number and variety of functional RNAs (ncRNAs as well as cis-acting RNA elements within mRNAs) is much higher than previously thought; thus, the ability to computationally predict and analyze RNAs has taken on new importance. We have computationally studied the secondary structures in an alignment of six Aspergillus genomes. Little is known about the RNAs present in this set of fungi, and this diverse set of genomes has an optimal level of sequence conservation for observing the correlated evolution of base-pairs seen in RNAs. Methodology/Principal Findings: We report the results of a whole-genome search for evolutionarily conserved secondary structures, as well as the results of clustering these predicted secondary structures by structural similarity. We find a total of 7450 predicted secondary structures, including a new predicted,60 bp long hairpin motif found primarily inside introns. We find no evidence for microRNAs. Different types of genomic regions are over-represented in different classes of predicted secondary structures. Exons contain the longest motifs (primarily long, branched hairpins), 59 UTRs primarily contain groupings of short hairpins located near the start codon, and 39 UTRs contain very little secondary structure compared to other regions. There is a large concentration of short hairpins just inside the boundaries of exons. The density of predicted intronic RNAs increases with the length of introns, and the density of predicted secondary structures within mRNA coding regions increases with the number of introns in a gene

New Approaches to Preventing, Diagnosing, and Treating Neonatal Sepsis

Karen Edmond and Anita Zaidi highlight new approaches that could reduce the burden of neonatal sepsis worldwide

Data from: Linking the respiration of fungal sporocarps with their nitrogen concentration: variation among species, tissues, and guilds

Tissue nitrogen (N) concentration has been correlated with respiration (RS) across plants of different life forms, functional and phylogenetic groups, plant organs and ectomycorrhizae of different fungal species. Nothing is known, however, if a similar relationship exists in other organisms like fungi. Here, we explored the N-RS relationship across sporocarps of 93 fungal species that varied in their guilds (mutualistic, saprotrophic, and parasitic) as well as “tissue” types (caps and stipes). We hypothesized that RS, N and protein concentrations were higher for saprotrophic fungi than either mutualistic and parasitic fungi and were higher for caps than for stipes. We also hypothesized that respiration of fungal guild could be predicted by the N concentration. Lastly we predicted N and RS were phylogenetically conserved and that by subtracting metabolically inactive N in chitin, we could improve the N-RS relationship. Sporocarp N concentration only explained 26% of the variation in RS across species. We found a significant difference in the N-RS relationship among the three fungal guilds, but no difference between the two tissue types. Saprotrophic species had higher N concentration and respiration than mutualistic and parasitic fungal species. Sporocarp components differed with caps showing both higher respiration and higher N and protein concentrations than stipes. Overall, our results show that fungal sporocarp nitrogen concentration is phylogenetically conserved among fungal families and may prove to be a strong predictor of fungal guild. The positive N-RS relationships existed for all fungal species (similar to plants), within fungal guilds (similar to plant functional groups), and fungal “tissue” types (like plants’ organs). The clear linkage of fungal sporocarp respiration to total N concentration could help improve C and N cycling models in forest ecosystems by including estimates of fungal respiration based on fungal N concentration