Real-time dissolved carbon dioxide monitoring II: Surface aeration intensification for efficient CO2 removal in shake flasks and mini-bioreactors leads to superior growth and recombinant protein yields.

Mass transfer is known to play a critical role in bioprocess performance and henceforth monitoring dissolved O2 (DO) and dissolved CO2 (dCO2 ) is of paramount importance. At bioreactor level these parameters can be monitored online and can be controlled by sparging air/oxygen or stirrer speed. However, traditional small-scale systems such as shake flasks lack real time monitoring and also employ only surface aeration with additional diffusion limitations imposed by the culture plug. Here we present implementation of intensifying surface aeration by sparging air in the headspace of the reaction vessel and real-time monitoring of DO and dCO2 in the bioprocesses to evaluate the impact of intensified surface aeration. We observed that sparging air in the headspace allowed us to keep dCO2 at low level, which significantly improved not only biomass growth but also protein yield. We expect that implementing such controlled smart shake flasks can minimize the process development gap which currently exists in shake flask level and bioreactor level results.

Real-time dissolved carbon dioxide monitoring I: Application of a novel in situ sensor for CO2 monitoring and control.

Dissolved carbon dioxide (dCO2 ) is a well-known critical parameter in bioprocesses due to its significant impact on cell metabolism and on product quality attributes. Processes run at small-scale faces many challenges due to limited options for modular sensors for online monitoring and control. Traditional sensors are bulky, costly, and invasive in nature and do not fit in small-scale systems. In this study, we present the implementation of a novel, rate-based technique for real-time monitoring of dCO2 in bioprocesses. A silicone sampling probe that allows the diffusion of CO2 through its wall was inserted inside a shake flask/bioreactor and then flushed with air to remove the CO2 that had diffused into the probe from the culture broth (sensor was calibrated using air as zero-point calibration). The gas inside the probe was then allowed to recirculate through gas-impermeable tubing to a CO2 monitor. We have shown that by measuring the initial diffusion rate of CO2 into the sampling probe we were able to determine the partial pressure of the dCO2 in the culture. This technique can be readily automated, and measurements can be made in minutes. Demonstration experiments conducted with baker's yeast and Yarrowia lipolytica yeast cells in both shake flasks and mini bioreactors showed that it can monitor dCO2 in real-time. Using the proposed sensor, we successfully implemented a dCO2 -based control scheme, which resulted in significant improvement in process performance.

3D printing PLGA: a quantitative examination of the effects of polymer composition and printing parameters on print resolution.

In the past few decades, 3D printing has played a significant role in fabricating scaffolds with consistent, complex structure that meet patient-specific needs in future clinical applications. Although many studies have contributed to this emerging field of additive manufacturing, which includes material development and computer-aided scaffold design, current quantitative analyses do not correlate material properties, printing parameters, and printing outcomes to a great extent. A model that correlates these properties has tremendous potential to standardize 3D printing for tissue engineering and biomaterial science. In this study, we printed poly(lactic-co-glycolic acid) (PLGA) utilizing a direct melt extrusion technique without additional ingredients. We investigated PLGA with various lactic acid:glycolic acid (LA:GA) molecular weight ratios and end caps to demonstrate the dependence of the extrusion process on the polymer composition. Micro-computed tomography was then used to evaluate printed scaffolds containing different LA:GA ratios, composed of different fiber patterns, and processed under different printing conditions. We built a statistical model to reveal the correlation and predominant factors that determine printing precision. Our model showed a strong linear relationship between the actual and predicted precision under different combinations of printing conditions and material compositions. This quantitative examination establishes a significant foreground to 3D print biomaterials following a systematic fabrication procedure. Additionally, our proposed statistical models can be applied to couple specific biomaterials and 3D printing applications for patient implants with particular requirements.

5-Hydroxymethylcytosine in E-box motifs ACAT|GTG and ACAC|GTG increases DNA-binding of the B-HLH transcription factor TCF4.

We evaluated DNA binding of the B-HLH family members TCF4 and USF1 using protein binding microarrays (PBMs) containing double-stranded DNA probes with cytosine on both strands or 5-methylcytosine (5mC) or 5-hydroxymethylcytosine (5hmC) on one DNA strand and cytosine on the second strand. TCF4 preferentially bound the E-box motif (CAN|NTG) with strongest binding to the 8-mer CAG|GTGGT. 5mC uniformly decreases DNA binding of both TCF4 and USF1. The bulkier 5hmC also inhibited USF1 binding to DNA. In contrast, 5hmC dramatically enhanced TCF4 binding to E-box motifs ACAT|GTG and ACAC|GTG, being better bound than any 8-mer containing cytosine. Examination of X-ray structures of the closely related TCF3 and USF1 bound to DNA suggests TCF3 can undergo a conformational shift to preferentially bind to 5hmC while the USF1 basic region is bulkier and rigid precluding a conformation shift to bind 5hmC. These results greatly expand the regulatory DNA sequence landscape bound by TCF4.