PubMed · 9492602
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L BeSaw. 1998. It came from space.. https://pubmed.ncbi.nlm.nih.gov/9492602/
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UNLABELLED: Iodidimonas sp., a bacterium found in bioreactors treating oil and gas produced water as well as iodide-rich brines, has garnered attention for its unique ability to oxidize iodine. However, little is known about the metabolic capabilities that enable Iodidimonas sp. to thrive in certain unique ecological niches. In this study, we isolated, characterized, and sequenced three strains belonging to the Iodidimonas genus from the sludge of a membrane bioreactor used for produced water treatment. We investigated the genomic features of these isolates and compared them with the four publicly available isolate genomes from this genus, as well as a metagenome-assembled genome from the source bioreactor. Our Iodidimonas isolates had several genes associated with mitigating salinity, heavy metal, and organic compound stress, which likely help these bacteria to survive in produced water. Phenotyping tests revealed that while the isolates could utilize a wide variety of simple carbon substrates, they failed to degrade aliphatic or aromatic hydrocarbons, consistent with the lack of genes associated with common hydrocarbon degradation pathways in their genomes. We hypothesize that these microbes may lead a scavenging lifestyle in the bioreactor and similar iodide-rich brines. IMPORTANCE: Occupying a niche habitat and having few representative isolates, the genus Iodidimonas is a relatively understudied alphaproteobacterial group. Its ability to corrode pipes in iodine production facilities has economic implications, and its ability to generate potentially carcinogenic iodinated organic compounds during treatment of oil and gas produced water may cause environmental and health concerns with the recycling of treated water. Therefore, detailed characterization of the metabolic potential of the Iodidimonas isolates in this study both sheds light on their adaptation to the environmental conditions they inhabit and has environmental and economic significance.
Shake flasks are ubiquitous in cell culture and fermentation. However, conventional devices for measuring oxygen concentrations are impractical in these systems. Thus, there is no definitive information on the oxygen supply of growing cells. Here we report the noninvasive, nonintrusive monitoring of dissolved oxygen (DO) in shake flasks using a low-cost optical sensor. The oxygen-sensitive element is a thin, luminescent patch affixed to the inside bottom of the flask. The sensitivity and accuracy of this device is maximal up to 60% DO, within the range that is critical to cell culture applications. By measuring actual oxygen levels every 1 or 5 min throughout the course of yeast and E. coli fermentations, we found that a modest increase in shaker speed and a decrease in culture volume slowed the onset of oxygen limitation and reduced its duration. This is the first time that in situ oxygen limitation is reported in shake flasks. The same data is unattainable with a Clark type electrode because the presence of the intrusive probe itself changes the actual conditions. Available fiber optic oxygen sensors require cumbersome external connections and recalibration when autoclaved.
The performance of an industrial pharmaceutical process (production of an active pharmaceutical ingredient by fermentation, API) was modeled by multiblock partial least squares (MBPLS). The most important process stages are inoculum production and API production fermentation. Thirty batches (runs) were produced according to an experimental planning. Rather than merging all these data into a single block of independent variables (as in ordinary PLS), four data blocks were used separately (manipulated and quality variables for each process stage). With the multiblock approach it was possible to calculate weights and scores for each independent block. It was found that the inoculum quality variables were highly correlated with API production for nominal fermentations. For the nonnominal fermentations, the manipulations of the fermentation stage explained the amount of API obtained (especially the pH and biomass concentration). Based on the above process analysis it was possible to select a smaller set of variables with which a new model was built. The amount of variance predicted of the final API concentration (cross-validation) for this model was 82.4%. The advantage of the multiblock model over the standard PLS model is that the contributions of the two main process stages to the API volumetric productivity were determined.