Toward Spectral Library-Free Matrix-Assisted Laser Desorption/Ionization Time-of-Flight Mass Spectrometry Bacterial Identification

Bacterial identification is of great importance in clinical diagnosis, environmental monitoring, and food safety control. Among various strategies, matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) has drawn significant interest and has been clinically used. Nevertheless, current bioinformatics solutions use spectral libraries for the identification of bacterial strains. Spectral library generation requires acquisition of MALDI-TOF spectra from monoculture bacterial colonies, which is time-consuming and not possible for many species and strains. We propose a strategy for bacterial typing by MALDI-TOF using protein sequences from public database, that is, UniProt. Ten genes were identified to encode proteins most often observed by MALD-TOF from bacteria through 500 times repeated a 10-fold double cross-validation procedure, using 403 MALDI-TOF spectra corresponding to 14 genera, 81 species, and 403 strains, and the protein sequences of 1276 species in UniProt. The 10 genes were then used to annotate peaks on MALDI-TOF spectra of bacteria for bacterial identification. With the approach, bacteria can be identified at the genus level by searching against a database containing the protein sequences of 42 genera of bacteria from UniProt. Our approach identified 84.1% of the 403 spectra correctly at the genus level. Source code of the algorithm is available at https://github.com/dipcarbon/BacteriaMSLF

Transcriptome Profile of the Green Odorous Frog (<i>Odorrana margaretae</i>)

<div><p>Transcriptome profiles provide a practical and inexpensive alternative to explore genomic data in non-model organisms, particularly in amphibians where the genomes are very large and complex. The odorous frog <i>Odorrana</i><i>margaretae</i> (Anura: Ranidae) is a dominant species in the mountain stream ecosystem of western China. Limited knowledge of its genetic background has hindered research on this species, despite its importance in the ecosystem and as biological resources. Here we report the transcriptome of <i>O</i><i>. margaretae</i> in order to establish the foundation for genetic research. Using an Illumina sequencing platform, 62,321,166 raw reads were acquired. After a <i>de novo</i> assembly, 37,906 transcripts were obtained, and 18,933 transcripts were annotated to 14,628 genes. We functionally classified these transcripts by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG). A total of 11,457 unique transcripts were assigned to 52 GO terms, and 1,438 transcripts were assigned to 128 KEGG pathways. Furthermore, we identified 27 potential antimicrobial peptides (AMPs), 50,351 single nucleotide polymorphism (SNP) sites, and 2,574 microsatellite DNA loci. The transcriptome profile of this species will shed more light on its genetic background and provide useful tools for future studies of this species, as well as other species in the genus <i>Odorrana</i>. It will also contribute to the accumulation of amphibian genomic data.</p> </div

Characteristics of gene annotation of assembled transcripts against the reference dataset.

<p>(A) E-value distribution of BLASTX hits for transcript with a cut-off E-value of 1E-5. (B) Similarity distribution of BLASTX hits for transcript.</p

Distribution of <i>O</i><i>. margaretae</i> transcripts among Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways.

<p>The top 16 most highly represented pathways are shown. Analysis was performed using Blast2GO and the KEGG database.</p

Additional file 1: of Gene coexpression network analysis of fruit transcriptomes uncovers a possible mechanistically distinct class of sugar/acid ratio-associated genes in sweet orange

A list of genes correlated with the sugar level with Pcc = +/−0.8 and 0.9, respectively. (XLSX 286 kb

Length distribution of transcripts in base pairs.

<p>The numbers of transcripts are shown on top of each bar.</p

Distribution of Gene Ontology (GO) categories (level 2) of transcripts for <i>O</i><i>. margaretae</i>.

<p>GO functional annotations are summarized in three main categories: cellular component, molecular function and biological process.</p

Coupling Isoelectric Focusing Gel Electrophoresis to Mass Spectrometry by Electrostatic Spray Ionization

Gel electrophoresis has been used for decades as a high-resolution separation technique for proteins and protein isomers but has been limited in the coupling with MS because of low throughput and poor automaticity compared with LC–MS. In this work, we have developed an ambient ionization strategy, electrostatic spray ionization, for <i>in situ</i> ionization of proteins or peptides inside a surfactant-free polyacrylamide gel. The samples can be first separated by isoelectric focusing in a gel and then quickly <i>in situ</i> detected by scanning the gel with the electrostatic spray ionization mass spectrometry. With this strategy, nanograms of proteins or peptides inside a band are enough to be ionized for MS detection. This method for protein/peptide spots visualization is sensitive, providing sample molecular weight information while avoiding spot staining and chemical extraction procedures that can introduce contaminants and sample loss. Proof-of-principle results have demonstrated that the electrostatic spray ionization can produce sample ions from a complex background, and with a spatial resolution matching the isoelectric focusing, it is therefore a good choice to couple directly isoelectric focusing gel electrophoresis with mass spectrometry

Orientation-Dependent Oxygen Evolution Activities of Rutile IrO₂ and RuO₂

The activities of the oxygen evolution reaction (OER) on IrO₂ and RuO₂ catalysts are among the highest known to date. However, the intrinsic OER activities of surfaces with defined crystallographic orientations are not well-established experimentally. Here we report that the (100) surface of IrO₂ and RuO₂ is more active in alkaline environments (pH 13) than the most thermodynamically stable (110) surface. The OER activity was correlated with the density of coordinatively undersaturated metal sites of each crystallographic facet. The surface-orientation-dependent activities can guide the design of nanoscale catalysts with increased activity for electrolyzers, metal-air batteries, and photoelectrochemical water splitting applications

Multifunctional Nanoreactor for Comprehensive Characterization of Membrane Proteins Based on Surface Functionalized Mesoporous Foams

An integrated protocol is proposed here for efficient analysis of membrane proteins based on surface functionalized mesoporous graphene foams (MGF). The inherent hydrophobic nature of MGF and surface modification with hydrophilic chitosan (CS) make it highly suitable for the enrichment of hydrophobic membrane proteins from organic solvent, while remaining well-dispersed in aqueous solution for subsequent proteolysis. Therefore, such a multifunctional reactor ensures a facile solvent adjustment route. Furthermore, as a chitosan modified nanoporous reactor, it also provides a biocompatible nanoenvironment that can maintain the stability and activity of enzymes to realize efficient <i>in situ</i> digestion of the enriched membrane proteins. The concept was first proved with a standard hydrophobic membrane protein, bacteriorhodopsin, where a high number of identified peptides and amino acid sequence coverage were achieved even at extremely low protein concentration. The mesoporous reaction system was further applied to the analysis of complex real-case proteome samples, where 931 membrane proteins were identified in triplicate analyses by 2D LC-MS/MS. In contrast, with in-solution proteolysis, only 73 membrane proteins were identified from the same sample by the same 2D LC-MS/MS. The identified membrane proteins by the MGF-CS protocol include many biomarkers of the cell line. These results suggest that the multifunctional MGF-CS protocol is of great value to facilitate the comprehensive characterization of membrane proteins in the proteome research