Optimization of Streptomyces peucetius var. caesius N47 cultivation and epsilon-rhodomycinone production using experimental designs and response surface methods

The truth about metagenomics: quantifying and counteracting bias in 16S rRNA studies

BACKGROUND

Characterizing microbial communities via next-generation sequencing is subject to a number of pitfalls involving sample processing. The observed community composition can be a severe distortion of the quantities of bacteria actually present in the microbiome, hampering analysis and threatening the validity of conclusions from metagenomic studies. We introduce an experimental protocol using mock communities for quantifying and characterizing bias introduced in the sample processing pipeline. We used 80 bacterial mock communities comprised of prescribed proportions of cells from seven vaginally-relevant bacterial strains to assess the bias introduced in the sample processing pipeline. We created two additional sets of 80 mock communities by mixing prescribed quantities of DNA and PCR product to quantify the relative contribution to bias of (1) DNA extraction, (2) PCR amplification, and (3) sequencing and taxonomic classification for particular choices of protocols for each step. We developed models to predict the "true" composition of environmental samples based on the observed proportions, and applied them to a set of clinical vaginal samples from a single subject during four visits.

RESULTS

We observed that using different DNA extraction kits can produce dramatically different results but bias is introduced regardless of the choice of kit. We observed error rates from bias of over 85% in some samples, while technical variation was very low at less than 5% for most bacteria. The effects of DNA extraction and PCR amplification for our protocols were much larger than those due to sequencing and classification. The processing steps affected different bacteria in different ways, resulting in amplified and suppressed observed proportions of a community. When predictive models were applied to clinical samples from a subject, the predicted microbiome profiles were better reflections of the physiology and diagnosis of the subject at the visits than the observed community compositions.

CONCLUSIONS

Bias in 16S studies due to DNA extraction and PCR amplification will continue to require attention despite further advances in sequencing technology. Analysis of mock communities can help assess bias and facilitate the interpretation of results from environmental samples.

Optimization of fermentation conditions for the production of the M23 protease Pseudoalterin by deep-sea Pseudoalteromonas sp. CF6-2 with artery powder as an inducer

Proteases in the M23 family have specific activities toward elastin and bacterial peptidoglycan. The peptidoglycan-degrading property makes these proteases have potential as novel antimicrobials. Because M23 proteases cannot be maturely expressed in Escherichia coli, it is significant to improve the production of these enzymes in their wild strains. Pseudoalterin is a new M23 protease secreted by the deep-sea bacterium Pseudoalteromonas sp. CF6-2. In this study, the fermentation conditions of strain CF6-2 for pseudoalterin production were optimized using single factor experiments and response surface methodology to improve the enzyme yield. To reduce the fermentation cost, bovine artery powder instead of elastin was determined as a cheap and efficient inducer. Based on single factor experiments, artery powder content, culture temperature and culture time were determined as the main factors influencing pseudoalterin production and were further optimized by the central composite design. The optimal values of these factors were determined as: artery powder of 1.2%, culture temperature of 20.17 °C and culture time of 28.04 h. Under the optimized conditions, pseudoalterin production reached 100.02±9.0 U/mL, more than twice of that before optimization. These results lay a good foundation for developing the biotechnological potential of pseudoalterin.

Cell culture medium improvement by rigorous shuffling of components using media blending

A novel high-throughput methodology for the simultaneous optimization of many cell culture media components is presented. The method is based on the media blending approach which has several advantages as it works with ready-to-use media. In particular it allows precise pH and osmolarity adjustments and eliminates the need of concentrated stock solutions, a frequent source of serious solubility issues. In addition, media blending easily generates a large number of new compositions providing a remarkable screening tool. However, media blending designs usually do not provide information on distinct factors or components that are causing the desired improvements. This paper addresses this last point by considering the concentration of individual medium components to fix the experimental design and for the interpretation of the results. The extended blending strategy was used to reshuffle the 20 amino acids in one round of experiments. A small set of 10 media was specifically designed to generate a large number of mixtures. 192 mixtures were then prepared by media blending and tested on a recombinant CHO cell line expressing a monoclonal antibody. A wide range of performances (titers and viable cell density) was achieved from the different mixtures with top titers significantly above our previous results seen with this cell line. In addition, information about major effects of key amino acids on cell densities and titers could be extracted from the experimental results. This demonstrates that the extended blending approach is a powerful experimental tool which allows systematic and simultaneous reshuffling of multiple medium components.

A chemostat study of Streptomyces peucetius var. caesius N47

The behavior of Streptomyces peucetius var. caesius N47 was studied in a glucose limited chemostat with a complex cultivation medium. The steady-state study yielded the characteristic constants mu (max) over 0.10 h(-1), Y (XS) 0.536 g g(-1), and m(S) 0.54 mg g(-1) h(-1). The product of secondary metabolism, epsilon-rhodomycinone, was produced with characteristics Y (PX) 12.99 mg g(-1) and m (P) 1.20 mg g(-1) h(-1). Significant correlations were found for phosphate and glucose consumption with biomass and epsilon-rhodomycinone production. Metabolic flux analysis was conducted to estimate intracellular fluxes at different dilution rates. TCA, PPP, and shikimate pathway fluxes exhibited bigger values with production than with growth. Environmental perturbation experiments with temperature, airflow, and pH changes on a steady-state chemostat implied that an elevation of pH could be the most effective way to shift the cells from growing to producing, as the pH change induced the biggest transient increase to the calculated epsilon-rhodomycinone flux.