A Defined Medium for Cultivation and Exometabolite Profiling of Soil Bacteria.

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.

Strain-level Staphylococcus differentiation by CeO2-metal oxide laser ionization mass spectrometry fatty acid profiling.

BACKGROUND: The Staphylococcus genus is composed of 44 species, with S. aureus being the most pathogenic. Isolates of S. aureus are generally susceptible to ß-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. RESULTS: Principal 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. CONCLUSION: The 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.

Rapid Burkholderia pseudomallei identification and antibiotic resistance determination by bacteriophage amplification and MALDI-TOF MS.

Phage amplification detected by MALDI-TOF MS was investigated for rapid and simultaneous Burkholderia pseudomallei identification and ceftazidime resistance determination. B. pseudomallei ceftazidime susceptible and resistant ΔpurM mutant strains Bp82 and Bp82.3 were infected with broadly targeting B. pseudomallei phage ϕX216 and production of the m/z 37.6 kDa phage capsid protein observed by MALDI-TOF MS over the course of 3 h infections. This allowed for repoducible phage-based bacterial ID within 2 h of the onset of infection. MALDI-TOF MS-measured time to detection correlated with in silico modeling, which predicted an approximate 2 h detection time. Ceftazidime susceptible strain Bp82, while detectable in the absence of the drug, owing to the reliance of phage amplification on a viable host, was not detectable when 10 µg/mL ceftazidime was added at the onset of infection. In contrast, resistant strain Bp82.3 was detected in the same 2 h timeframe both with and without the addition of ceftazidime.