BackgroundThe bacterium Bacillus subtilis, which is not a natural riboflavin overproducer, has been converted into an excellent production strain by classical mutagenesis and metabolic engineering. To our knowledge, the enhancement of riboflavin excretion from the cytoplasm of overproducing cells has not yet been considered as a target for (further) strain improvement. Here we evaluate the flavin transporter RibM from Streptomyces davawensis with respect to improvement of a riboflavin production strain.ResultsThe gene ribM from S. davawensis, coding for a putative facilitator of riboflavin uptake, was codon optimized (ribMopt) for expression in B. subtilis. The gene ribMopt was functionally introduced into B. subtilis using the isopropyl-β-thiogalactopyranoside (IPTG)-inducible expression plasmid pHT01: Northern-blot analysis of total RNA from IPTG treated recombinant B. subtilis cells revealed a ribMopt specific transcript. Western blot analysis showed that the his6-tagged heterologous gene product RibM was present in the cytoplasmic membrane. Expression of ribM in Escherichia coli increased [14C]riboflavin uptake, which was not affected by the protonophore carbonyl cyanide m-chlorophenylhydrazone (CCCP). Expression of ribMopt supported growth of a B. subtilis ΔribB::Ermr ΔribU::Kanr double mutant deficient in riboflavin synthesis (ΔribB) and also deficient with respect to riboflavin uptake (ΔribU). Expression of ribMopt increased roseoflavin (a toxic riboflavin analog produced by S. davawensis) sensitivity of a B. subtilis ΔribU::Kanr strain. Riboflavin synthesis by a model riboflavin B. subtilis production strain overproducing RibM was increased significantly depending on the amount of the inducer IPTG.ConclusionsThe energy independent flavin facilitator RibM could in principle catalyze riboflavin export and thus may be useful to increase the riboflavin yield in a riboflavin production process using a recombinant RibM overproducing B. subtilis strain (or any other microorganism).
Cardiovascular disease is the leading cause of death in Western civilization. In this pilot study we evaluated a new method for the diagnosis of myocardial infarction and heart failure by determining the typical fingerprint in the infrared (IR) spectrum of 1 microL of a dried patient serum sample by Fourier transform IR spectroscopy. For classification, cluster analysis and artificial neural networks (ANN) were applied. In this study 567 subjects were enrolled, comprising 225 controls (Co) and 342 patients with myocardial infarction (MI) (n = 157) and heart failure (HF) (n = 185). By applying artificial neural network algorithms, the following sensitivities and specificities of the same spectra were determined: MI versus Co (98%, 97%), HF versus Co (98%, 100%), MI versus HF (100%, 100%), and MI plus HF versus Co (100%, 100%). Based on our data, mid-IR spectroscopy appears to be a promising new method to diagnose heart diseases from serum samples. Artificial neural network algorithms proved to be superior to cluster analysis for correct prediction.
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