Despite the nutritional significance of sulfur, its influence on biosurfactants production has not been sufficiently studied. We investigated the expression of key biosurfactants production genes, rhlABC, in cultures of Pseudomonas sp. AK6U grown with inorganic or organic sulfur sources. AK6U grew with either inorganic sulfate (MgSO4), dibenzothiophene (DBT), or DBT-sulfone as a sole sulfur source in the presence of glucose as a carbon source. The AK6U cultures produced variable amounts of biosurfactants depending on the utilized sulfur source. Biosurfactants production profile of the DBT cultures was significantly different from that of the DBT-sulfone and inorganic sulfate cultures. The last two cultures were very similar in terms of biosurfactants productivity. Biosurfactants yield in the DBT cultures (1.3 g/L) was higher than that produced by the DBT-sulfone (0.5 g/L) and the inorganic sulfate (0.44 g/L) cultures. Moreover, the surface tension reduction in the DBT cultures (33 mN/m) was much stronger than that measured in the DBT-sulfone (58 mN/m) or inorganic sulfate (54 mN/m) cultures. RT-qPCR revealed variations in the expression levels of the rhlABC genes depending on the sulfur source. The DBT cultures had higher expression levels for the three genes as compared to the DBT-sulfone and inorganic sulfate cultures. There was no significant difference in the expression profiles between the DBT-sulfone and the MgSO4 cultures. The increased expression of rhlC in the DBT cultures is indicative for production of higher amounts of dirhamnolipids compared to the DBT-sulfone and inorganic sulfate cultures. The gene expression results were in good agreement with the biosurfactants production yields and surface tension measurements. The sulfur source mediates a fine-tuned mechanism of transcriptional regulation of biosurfactants production genes. Our findings can have an impact on industrial production of biosurfactants and other biotechnological processes like biodesulfurization.
Highlights A biodesulfurizing consortium consisting of biodesulfurizers and non-biodesulfurizers. Sulfur source-driven compositional shifts in a biodesulfurizing consortium. A biodesulfurizing consortium harbors a non-destructive desulfurization pathway.
We followed a comparative approach to investigate how heavy vacuum gas oil (HVGO) affects the expression of genes involved in biosurfactants biosynthesis and the composition of the rhamnolipid congeners in Pseudomonas sp. AK6U. HVGO stimulated biosurfactants production as indicated by the lower surface tension (26 mN/m) and higher yield (7.8 g/L) compared to a glucose culture (49.7 mN/m, 0.305 g/L). Quantitative real-time PCR showed that the biosurfactants production genes rhlA and rhlB were strongly upregulated in the HVGO culture during the early and late exponential growth phases. To the contrary, the rhamnose biosynthesis genes algC, rmlA and rmlC were downregulated in the HVGO culture. Genes of the quorum sensing systems which regulate biosurfactants biosynthesis exhibited a hierarchical expression profile. The lasI gene was strongly upregulated (20-fold) in the HVGO culture during the early log phase, whereas both rhlI and pqsE were upregulated during the late log phase. Rhamnolipid congener analysis using high-performance liquid chromatography-mass spectrometry revealed a much higher proportion (up to 69%) of the high-molecularweight homologue Rha–Rha–C10–C10 in the HVGO culture. The results shed light on the temporal and carbon source-mediated shifts in rhamonlipids’ composition and regulation of biosynthesis which can be potentially exploited to produce different rhamnolipid formulations tailored for specific applications.
In this study, we evaluated the use of a predictive computational approach for SARS-CoV-2 genetic variations analysis in improving the current variant labeling system. First, we reviewed the basis of the system developed by the World Health Organization (WHO) for the labeling of SARS-CoV-2 genetic variants and the derivative adapted by the United States Centers for Disease Control and Prevention (CDC). Both labeling systems are based on the virus’ major attributes. However, we found that the labeling criteria of the SARS-CoV-2 variants derived from these attributes are not accurately defined and are used differently by the two agencies. Consequently, discrepancies exist between the labels given by WHO and the CDC to the same variants. Our observations suggest that giving the variant of concern (VOC) label to a new variant is premature and might not be appropriate. Therefore, we used a comparative computational approach to predict the effects of the mutations on the virus structure and functions of five VOCs. By linking these data to the criteria used by WHO/CDC for variant labeling, we ascertained that a predictive computational comparative approach of the genetic variations is a good way for rapid and more accurate labeling of SARS-CoV-2 variants. We propose to label all emergent variants, variant under monitoring or variant being monitored (VUM/VBM), and to carry out computational predictive studies with thorough comparison to existing variants, upon which more appropriate and informative labels can be attributed. Furthermore, harmonization of the variant labeling system would be globally beneficial to communicate about and fight the COVID-19 pandemic.
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