In oxygenic photosynthesis, light-driven oxidation of water to molecular oxygen is carried out by the oxygen-evolving complex (OEC) in photosystem II (PS II). Recently, we reported the room-temperature structures of PS II in the four (semi)stable S-states, S1, S2, S3, and S0, showing that a water molecule is inserted during the S2→ S3transition, as a new bridging O(H)-ligand between Mn1 and Ca. To understand the sequence of events leading to the formation of this last stable intermediate state before O2formation, we recorded diffraction and Mn X-ray emission spectroscopy (XES) data at several time points during the S2→ S3transition. At the electron acceptor site, changes due to the two-electron redox chemistry at the quinones, QAand QB, are observed. At the donor site, tyrosine YZand His190 H-bonded to it move by 50 µs after the second flash, and Glu189 moves away from Ca. This is followed by Mn1 and Mn4 moving apart, and the insertion of OX(H) at the open coordination site of Mn1. This water, possibly a ligand of Ca, could be supplied via a “water wheel”-like arrangement of five waters next to the OEC that is connected by a large channel to the bulk solvent. XES spectra show that Mn oxidation (τ of ∼350 µs) during the S2→ S3transition mirrors the appearance of OXelectron density. This indicates that the oxidation state change and the insertion of water as a bridging atom between Mn1 and Ca are highly correlated.

Matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) has emerged as a rapid approach for clinical bacterial identification. However, current protein-based commercial bacterial ID methods fall short when differentiating closely related species/strains. To address this shortcoming, we employed CeO2-catalyzed fragmentation of lipids to produce fatty acids using the energy inherent to the MALDI laser as a novel alternative to protein profiling. Fatty acid profiles collected from Enterobacteriaceae, Acinetobacter, and Listeria using CeO2-catalyzed metal oxide laser ionization (MOLI MS), processed by principal component analysis, and validated by leave–one-out cross-validation (CV), showed 100% correct classification at the species level and 98% at the strain level. In comparison, protein profile data from the same bacteria yielded 32%, 54% and 67% mean species-level accuracy using two MALDI-TOF MS platforms, respectively. In addition, several pathogens were misidentified by protein profiling as non-pathogens and vice versa. These results suggest novel CeO2-catalyzed lipid fragmentation readily produced (i) taxonomically tractable fatty acid profiles by MOLI MS, (ii) highly accurate bacterial classification and (iii) consistent strain-level ID for bacteria that were routinely misidentified by protein-based methods.

BackgroundThe Staphylococcus genus is composed of 44 species, with S. aureus being the most pathogenic. Isolates of S. aureus are generally susceptible to β-lactam antibiotics, but extensive use of this class of drugs has led to increasing emergence of resistant strains. Increased occurrence of coagulase-negative staphylococci as well as S. aureus infections, some with resistance to multiple classes of antibiotics, has driven the necessity for innovative options for treatment and infection control. Despite these increasing needs, current methods still only possess species-level capabilities and require secondary testing to determine antibiotic resistance. This study describes the use of metal oxide laser ionization mass spectrometry fatty acid (FA) profiling as a rapid, simultaneous Staphylococcus identification and antibiotic resistance determination method.ResultsPrincipal component analysis was used to classify 50 Staphyloccocus isolates. Leave-one-spectrum-out cross-validation indicated 100 % correct assignment at the species and strain level. Fuzzy rule building expert system classification and self-optimizing partial least squares discriminant analysis, with more rigorous evaluations, also consistently achieved greater than 94 and 84 % accuracy, respectively. Preliminary analysis differentiating MRSA from MSSA demonstrated the feasibility of simultaneous determination of strain identification and antibiotic resistance.ConclusionThe utility of CeO2-MOLI MS FA profiling coupled with multivariate statistical analysis for performing strain-level differentiation of various Staphylococcus species proved to be a fast and reliable tool for identification. The simultaneous strain-level detection and antibiotic resistance determination achieved with this method should greatly improve outcomes and reduce clinical costs for therapeutic management and infection control.

Six metal oxide catalysts were investigated for effective cleavage and laser ionization of bacterial cell wall phospholipid extracts. Calcium oxide has been utilized in the past for this application, but suffered from degradation of catalytic activity. Following evaluation of the six catalysts, CeO 2 was found to be the most stable over time and produced fatty acid profiles of bacterial pathogens similar to freshly activated CaO. A suite of ten bacteria previously studied using CaO catalysis provided cross validation results of analysis of 97% correct correlation for negative-ion data. Cerium oxide catalysis studies yielded cross validation results of 100%. Using analysis of variance-principal component analysis (ANOVA-PCA), four sample sets collected with stored catalyst at 0, 8, 24, and 504 h showed no effect based on long-term catalyst degradation. Supervised learning by a fuzzy rule-building expert system (FuRES) that was validated with training and prediction set partitions independent of CeO 2 age and unsupervised data analysis using a dendrogram of Euclidean distance confirmed that the CeO 2 catalyst age had no effect on the fatty acid mass spectral profiles.

Exometabolomics is an approach to assess how microorganisms alter, or react to their environments through the depletion and production of metabolites. It allows the examination of how soil microbes transform the small molecule metabolites within their environment, which can be used to study resource competition and cross-feeding. This approach is most powerful when used with defined media that enable tracking of all metabolites. However, microbial growth media have traditionally been developed for the isolation and growth of microorganisms but not metabolite utilization profiling through Liquid Chromatography Tandem Mass Spectrometry (LC-MS/MS). Here, we describe the construction of a defined medium, the Northen Lab Defined Medium (NLDM), that not only supports the growth of diverse soil bacteria but also is defined and therefore suited for exometabolomic experiments. Metabolites included in NLDM were selected based on their presence in R2A medium and soil, elemental stoichiometry requirements, as well as knowledge of metabolite usage by different bacteria. We found that NLDM supported the growth of 108 of the 110 phylogenetically diverse (spanning 36 different families) soil bacterial isolates tested and all of its metabolites were trackable through LC–MS/MS analysis. These results demonstrate the viability and utility of the constructed NLDM medium for growing and characterizing diverse microbial isolates and communities.