147 research outputs found
Online coupling of a catalytic continuous microflow reactor to mass spectrometry
Flow cell reactors used for catalyst development and applications are upcoming due to their small environmental and economic footprint. Online microflow reactor coupling with mass spectrometry (MS) opens new possibilities for monitoring catalyst performance and identifying reaction products in real time. This is demonstrated for the metabolic relevant dealkylation of lidocaine on catalytic gold micro-particles using regular liquid chromatography modules. Yields of up to 90% norlidocaine were realized under mild continuous flow conditions for up to 10 h (pH 7, 30 °C and 20 μL/min). Dissolved oxygen was shown to be a rate-limiting factor, since an inline oxygen generator allowed to increase the reactor capacity by one order of magnitude. Monitoring product time-response curve slopes after starting and ending a substrate feed, provided insights into the adsorption/desorption and conversion kinetics at the catalyst surface indicating the presence of strong adsorption sites that do not contribute substantially to substrate conversion
Online coupling of a catalytic continuous microflow reactor to mass spectrometry
Flow cell reactors used for catalyst development and applications are upcoming due to their small environmental and economic footprint. Online microflow reactor coupling with mass spectrometry (MS) opens new possibilities for monitoring catalyst performance and identifying reaction products in real time. This is demonstrated for the metabolic relevant dealkylation of lidocaine on catalytic gold micro-particles using regular liquid chromatography modules. Yields of up to 90% norlidocaine were realized under mild continuous flow conditions for up to 10 h (pH 7, 30 °C and 20 μL/min). Dissolved oxygen was shown to be a rate-limiting factor, since an inline oxygen generator allowed to increase the reactor capacity by one order of magnitude. Monitoring product time-response curve slopes after starting and ending a substrate feed, provided insights into the adsorption/desorption and conversion kinetics at the catalyst surface indicating the presence of strong adsorption sites that do not contribute substantially to substrate conversion
FabR regulates Salmonella biofilm formation via its direct target FabB
Background: Biofilm formation is an important survival strategy of Salmonella in all environments. By mutant screening, we showed a knock-out mutant of fabR, encoding a repressor of unsaturated fatty acid biosynthesis (UFA), to have impaired biofilm formation. In order to unravel how this regulator impinges on Salmonella biofilm formation, we aimed at elucidating the S. Typhimurium FabR regulon. Hereto, we applied a combinatorial high-throughput approach, combining ChIP-chip with transcriptomics.
Results: All the previously identified E. coli FabR transcriptional target genes (fabA, fabB and yqfA) were shown to be direct S. Typhimurium FabR targets as well. As we found a fabB overexpressing strain to partly mimic the biofilm defect of the fabR mutant, the effect of FabR on biofilms can be attributed at least partly to FabB, which plays a key role in UFA biosynthesis. Additionally, ChIP-chip identified a number of novel direct FabR targets (the intergenic regions between hpaR/hpaG and ddg/ydfZ) and yet putative direct targets (i.a. genes involved in tRNA metabolism, ribosome synthesis and translation). Next to UFA biosynthesis, a number of these direct targets and other indirect targets identified by transcriptomics (e.g. ribosomal genes, ompA, ompC, ompX, osmB, osmC, sseI), could possibly contribute to the effect of FabR on biofilm formation.
Conclusion: Overall, our results point at the importance of FabR and UFA biosynthesis in Salmonella biofilm formation and their role as potential targets for biofilm inhibitory strategies
Development ofLactococcus lactisBiosensors for Detection of Sulfur-Containing Amino Acids
The sulfur-containing amino acids methionine and cysteine play an important role in food industry. These amino acids are used to confer a sulfur smell or meat-related aroma to food products. Besides their use as food additives, methionine and cysteine participate in flavor formation in dairy fermentations. For instance, the characteristic aroma of Cheddar cheeses is derived from methionine. Therefore, bacterial strains with the ability to overproduce and secrete these amino acids are relevant for the food industry. In addition, the quantification of these compounds in food matrices is a laborious task that involves sample preparation and specific analytical methods such as high-performance liquid chromatography. The ability of bacteria to naturally sense metabolites has successfully been exploited to develop biosensors. The presence of a specific metabolite is sensed by the biosensors, and it is subsequently translated into the expression of one or more reporter genes. In this study we aim to develop biosensors to detect methionine and cysteine, which are produced and secreted by wild-type Lactococcus lactis strains. We employed two strategies to create L. lactis biosensors, the first one is based on the methionine auxotrophy of this bacterium and the second strategy is based on a cysteine-responsive promoter. The characterization of the biosensors showed their specific response to the presence of these amino acids. Subsequently, we applied the methionine biosensor to quantify the presence of methionine in bacterial supernatants of wild-type L. lactis that naturally secretes methionine to benchmark the performance of our biosensors. The methionine biosensor responded linearly to the amounts of methionine present in the bacterial supernatants, i.e., the increases in the biosensor cell densities were proportional to the amounts of methionine present in the supernatants. The biosensors developed in this study tackle the limitations of amino acid quantification and the selection of strains with secretion of amino acids. These biosensors may eventually be used for screening of engineered strains to increase methionine and cysteine production, and may facilitate the detection of these amino acids in complex food matrices
Physicochemical parameters affecting the electrospray ionization efficiency of amino acids after acylation
Electrospray
ionization (ESI) is widely used in liquid chromatography
coupled to mass spectrometry (LC–MS) for the analysis of biomolecules.
However, the ESI process is still not completely understood, and it
is often a matter of trial and error to enhance ESI efficiency and,
hence, the response of a given set of compounds. In this work we performed
a systematic study of the ESI response of 14 amino acids that were
acylated with organic acid anhydrides of increasing chain length and
with polyÂ(ethylene glycol) (PEG) changing certain physicochemical
properties in a predictable manner. By comparing the ESI response
of 70 derivatives, we found that there was a strong correlation between
the calculated molecular volume and the ESI response, while correlation
with hydrophobicity (log <i>P</i> values), p<i>K</i><sub>a</sub>, and the inverse calculated surface tension was significantly
lower although still present, especially for individual derivatized
amino acids with increasing acyl chain lengths. Acylation with PEG
containing five ethylene glycol units led to the largest gain in ESI
response. This response was maximal independent of the calculated
physicochemical properties or the type of amino acid. Since no actual
physicochemical data is available for most derivatized compounds,
the responses were also used as input for a quantitative structure–property
relationship (QSPR) model to find the best physicochemical descriptors
relating to the ESI response from molecular structures using the amino
acids and their derivatives as a reference set. A topological descriptor
related to molecular size (SPAN) was isolated next to a descriptor
related to the atomic composition and structural groups (BIC0). The
validity of the model was checked with a test set of 43 additional
compounds that were unrelated to amino acids. While prediction was
generally good (<i>R</i><sup>2</sup> > 0.9), compounds
containing
halogen atoms or nitro groups gave a lower predicted ESI response
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